Climate Change and Transport: Assessment of Freight Modal Shift andEmissions through Dry Port Development

MADAN B. REGMI
BE (Civil), MSc, MBA(09D18051)

A dissertation submitted in partial fulfillment of the requirements for the
Degree of Doctor of Engineering in International Development Engineering

Tokyo Institute of Technology
School of Science and Engineering
Department of International Development Engineering
Tokyo, Japan
3 February 2012

ACKNOWLEDGEMENTS
The thought of academic research and possible PhD started while exploring options for mysabbatical leave. I landed in Tokyo Tech in 2009 and decided to carry it through and explore theacademic world further.
I would like to express my appreciation to my academic advisor Dr. Shinya Hanaoka for his
advice and guidance provided to me during the course of the research.
I would like to extend my appreciation to all professors of the Transport Study Unit and theDepartment of International Development Engineering for their valuable advice, comments andfeedback provided to me during the doctoral seminars and departmental presentations.
I highly appreciate and value the words of encouragement and advice received from Prof. Tetsuo
Yai. Similarly, I thank Dr. Yasunori Muromachi, Dr. Naoya Abe, and Dr. Daisuke Fukuda for
their valuable suggestions and advice on my research.
I am thankful to the members of the Hanaoka Research Group for their company during my stayat Tokyo and at times responding to my difficult queries. I also would like to thank Ms. Tomoko
Tanaka and Ms. Tomoko Matsuzaki for their support during my research and stay in Tokyo.
I would like to acknowledge the support and encouragement of my colleagues at the Ministry ofLand, Infrastructure, Transport and Tourism, East Nippon Expressway Company Limited,
Infrastructure Development Institute, Central Consultants and other offices and above all making
my stay in Tokyo enjoyable and assuring.
I would also like to thank my friend Dr. Surya Raj Acharya for his encouragement andreassuring me at difficult junctures.
I would like to express my appreciation to the officials of the Laos International Freight
Forwarder’s Association, Vientiane and Laem Chabang Port Authority in Thailand for assistingin data collection and arranging meetings. Also, thanks are due to the transport officials in Asiaand government officials in Laos for providing their valuable feedback on my survey.
I would like to express my appreciation to the United Nations Economic and Social Commission
for Asia and the Pacific, Bangkok for approving my request for PhD and the Office of Human
Resources Management, New York for providing me the opportunity to undertake the researchunder sabbatical leave initially. I would also like to acknowledge the support of Mr. Dong-Woo
Ha, Director, Transport Division for providing flexibility on my work and other colleagues fortheir encouragement.
This would have not been possible without support of my wife Anju and daughter Shreeya, bothfor sacrificing their family time, coping with my long absence from home as well as tolerating
my unusual schedule while at home. I promise to compensate for the missed family time.
3 February 2012, Tokyoi

ABSTRACTThe recent frequent occurrence of extreme weather events in Asia provides evidence of increased
intensity and frequency of climate events. On one hand, the transport sector is affected by theseclimate events; on the other hand, transport system contributes to the global warming throughemissions of greenhouse gases. The current research attempts to analyze and address the issuesof adaptation and mitigation in the transport sector in Asian context.
Firstly, an assessment of impacts of climate change on transport was done through a survey oftransport policy makers in Asia. The result showed the need to create awareness, plan and designtransport infrastructure with consideration of the likely impacts of climate change and the needfor greater collaboration among agencies. It also highlighted the importance of strategic
environmental assessment and environmental impact assessment and identified the need toreview design philosophy and consider life cycle costing while developing adaptation strategy.
With respect to mitigation, the research looked at the potential of freight modal shift through thedevelopment of dry ports. The review of selected case studies of dry ports development in Asia
revealed their potential environmental benefits. It also highlighted the importance of
coordination among various stakeholders and agencies during the development and operation,
importance of railway connectivity and the need to improve efficiency of transport operation
between seaport and dry port.
The four alternative locations of dry ports in Laos were analyzed using the analytic hierarchy
process and the goal programming considering evaluation criteria such as transportation time,cost, intermodal transport connectivity, environmental impact and regional economic
development. The analysis based on the feedback of policy makers and freight forwarders
prioritized Thanalaeng which is close to the capital Vientiane.
Stated preference survey of freight forwarders in Laos and Thailand was conducted to develop amode choice model and estimate potential mode shift to railways from road. The respondents
were asked to choose a freight mode in given scenario of transportation time, cost and reliabilityof the truck and train transportation between Laem Chabang seaport in Thailand and Thanalaengin Laos. The result showed that a modal shift of 43% from road to railways is possible in basecase scenario, provided that dry port is developed and freight train service is available.
Assessment of CO2 emission from the freight transport operation was done considering the mode
shift. The result indicates a 30% reduction of CO2 emission was possible at the base casescenario compared to business-as-usual corresponding to a 43% mode shift to railways. Scenario
analysis showed that the mode shift would vary from 32% to 54% and the corresponding CO2
emissions reduction would also vary from 23% to 39% depending on the scenario considered.
Life cycle emission assessment of the construction of dry port at Thanalaeng showed that theconstruction emissions would be compensated by emissions reduction from mode shift within
three years of start of operation of freight train service.
The application of integrated methodology enabled to explore environmental benefits of the dry
ports development in addition to its function as logistics and distribution centre. The various
results and information that would be useful to decision makers can be derived throughapplication of the methodology and to make informed decision.
ii

TABLE OF CONTENTS
Chapter

1.

Title

Page

Acknowledgements
Abstract
Table of Contents
List of Tables
List of Figures

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iii
vii
ix

INTRODUCTION

1

1.1
1.2
1.3
1.4
1.5
1.6

1
2
4
4
4
5
5
6
6
7

1.7
1.8
2.

Background
Problem statement
Research questions
Research objectives
Research framework
Scope and limitation
1.6.1 Scope and study area
1.6.2 Limitation
Scholarly contribution of the research
Structure of the thesis

LITERATURE REVIEW

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2.1
2.2

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2.3

2.4

Introduction
Sustainable transport development
2.2.1 Adaptation
2.2.1.1 Climate change and transport
2.2.1.2 Adaptation measures
2.2.1.3 Design review
2.2.1.4 Life cycle costing
2.2.2 Mitigation
2.2.2.1 Energy use in the transport sector
2.2.2.2 Transport sector emissions
2.2.2.3 Emissions measurement
2.2.2.4 Freight mode share
Intermodal transport
2.3.1 Transport links
2.3.2 Transport nodes
2.3.3 Transport services
Development of dry ports
2.4.1 Definition and functions
2.4.2 Policies related to the dry ports
2.4.3 Benefits of dry port development
2.4.4 Contribution of dry ports to emissions mitigationiii

2.4.5. Dry port location problem
Multi criteria decision analysis
2.5.1 Analytic hierarchy process
2.5.2 Location analysis using AHP
2.5.3 Multi-objective decision making
2.5.4 Goal programming
Mode choice
2.6.1 Stated preference (SP) experiment2.6.2 Application of SP experiment in mode choice
Case of freight transport in Laos
Chapter summary

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RESEARCH FRAMEWORK AND METHODOLOGY

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3.1
3.2
3.3
3.4

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2.5

2.6
2.7
2.8
3.

3.5

3.6
3.7
3.8
3.9
3.10
4.

Introduction
Integrated methodology and analysis modules
Module 1: Adaptation policy analysis
Module 2: Analysis of dry port development and location
3.4.1 Case studies of dry port development in Asia
3.4.2 Identification of decision criteria and sub-criteria
3.4.3 AHP model development
3.4.4 Weight derivation
3.4.5 Derivation of location priorities
3.4.6 Goal programming and AHP-Goal programming model
3.4.6.1 Goal programming
3.4.6.2 Combined AHP-GP model
Module 3: Mode choice model
3.5.1 Model structure
3.5.2 Attributes
3.5.3 Utility functions
3.5.4 Model estimation
Module 4: Assessment of CO2 emissions
3.6.1 Emissions from operation
3.6.2 Life cycle assessment of construction
Scenario and elasticity analysis
Model limitation
Data collection and surveys
Chapter summary

IMPACTS OF CLIMATE CHANGE ON TRANSPORT

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4.1
4.2
4.3

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Introduction
Regional climate predictions for Asia
Survey of impacts of climate change on transport
4.3.1 Questionnaire development
4.3.2 Selection of respondentsiv

4.3.3
4.3.4
4.3.5

Respondents details
Limitation of the survey
Findings of the survey
4.3.5.1 Awareness of climate change and adaptation
4.3.5.2 Emergency preparedness
4.3.5.3 Design standards and practices
4.3.5.4 Policies, institutions and coordination
4.3.5.5 Additional feedback from the respondents
4.3.5.6 Summary of findings
Assessment of impacts of climate change on transport
Adaptation strategies
4.5.1. Development and implementation of adaptation strategies
4.5.2 Financing adaptation
Adaptation strategies for dry port development
Results and discussion
Chapter summary

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CASE STUDIES OF THE DEVELOPMENT OF DRY PORTS IN ASIA

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5.1
5.2
5.3

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4.4
4.5
4.6
4.7
4.8
5.

5.4
5.5
5.6
5.7
6.

Introduction
Collection of case studies
Case studies of the development of dry ports in Asia
5.3.1 Uiwang ICD, South Korea
5.3.2 Birgunj ICD, Nepal
5.3.3 Lat Krabang ICD, Thailand
5.3.4 Dry port development in China
5.3.5 Dry port development in India
5.3.6 Navoi International Logistics Centre, Uzbekistan
5.3.7 Cikarang dry port, Indonesia
5.3.8 Kamalapur ICD, Bangladesh
Key findings of the case studies
Requirement of a good dry port and policies
Results and discussions
Chapter summary

LOCATION ANALYSIS OF DRY PORTS

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6.1
6.2

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6.3

Introduction
Survey for analysis of dry port locations in Laos
6.2.1 Selection of evaluation criteria and sub-criteria
6.2.2 Questionnaire development
6.2.3 Selection of respondents and the survey
6.2.4 Field visit to potential dry port locations
6.2.5 Limitation of the survey
Location analysis of dry ports in Laos
6.3.1 Analytic hierarchy process modelv

6.3.27.

Pair-wise comparison and derivation of weights
6.3.2.1 Derivation of weights of main criteria
6.3.2.2 Weights of sub-criteria
6.3.2.3 Location comparison with sub-criteria
6.3.2.4 Evaluation of tangible criteria
6.3.2.5 Synthesis and derivation of final priority
6.3.2.6 Limitation of AHP analysis
6.4
Combined AHP-Goal programming
6.4.1 AHP-GP Model
6.4.2 Goal programming model outputs
6.5
Results and discussions
6.6
Chapter summary
ASSESSMENT OF FREIGHT MODAL SHIFT AND EMISSIONS
7.1
7.2

7.3

7.4
7.5
7.6
7.7
7.8
8.

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Introduction
133
Data collection
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7.2.1 Selection of route, modes, attributes and attribute levels
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7.2.2 Pilot survey to determine attributes levels
134
7.2.2.1 Estimation of freight train speed
134
7.2.2.2 Values of attributes and levels
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7.2.3 Design of orthogonal choice experiment136
7.2.4 Development of choice sets and SP questionnaire
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7.2.5 Stated preference survey
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7.2.5.1 SP survey of freight forwarders in Thailand
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7.2.5.2 SP survey of freight forwarders in Laem Chabang Port 138
7.2.5.3 SP survey of freight forwarders in Laos
139
7.2.5.4 Summary of stated preference survey
139
7.2.6 Limitation of the SP survey
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7.2.7 Interview with policy makers and freight forwarders
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7.2.8 Outcome of the stated preference survey
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Mode choice model
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7.3.1 Estimation of model parameters142
7.3.2 Estimation of probability of choosing a mode
146
7.3.3 Elasticity of time and cost147
7.3.3.1 Variation in mode share due to cost variation
148
7.3.3.2 Variation in mode share due to time variation
149
7.3.3.3 Variation in mode share due to cost and time149
7.3.3.4 Variation in mode share due to reliability
150
7.3.3.5 Results of elasticity analysis
151
Assessment of CO2 emissions from operation
151
Emissions assessment of other dry ports
154
Life cycle assessment of construction
154
Results and discussion
156
Chapter summary
157

CONCLUSIONS

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8.1
8.2

8.3
8.4
8.5

Introduction
Summary of the findings
8.2.1 Impacts of climate change on transport and adaptation
8.2.2 Development of dry port and location analysis
8.2.3 Freight modal shift and CO2 emissions
Results and discussion
Conclusions
Further research

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REFERENCES

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Appendix I: Review of evaluation criteria, sub-criteria for location analysis

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Appendix II: Adaptation questionnaire

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Appendix III: AHP survey questionnaire

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Appendix IV: Questionnaire for the stated preference survey

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LIST OF TABLES
Table

Title

Page

Table 2.1: Emission factors of various transport modes
Table 2.2: Functions and services required at a dry port
Table 2.3: Salient features of proposed dry ports in Laos

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Table 3.1: Criteria and sub-criteria for AHP analysis of dry port location
Table 3.2: Saaty’s pair wise comparison scale
Table 3.3: Comparison matrix
Table 3:4.Primary data collection schedule, method and area

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Table 4.1 Vulnerable infrastructure, design parameters and potential impacts
Table 4.2: Adaptation options and policy framework

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Table 5.1: Assessment of CO2 emissions at Birgunj Dry Port, Nepal
Table 5.2: Comparison of key features of selected dry ports

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Table 6.1: Selected evaluation criteria and sub-criteria for AHP analysis
Table 6.2: Alternative dry port locations
Table 6.3: Details of survey response
Table 6.4: Judgmental matrix of evaluation criteria (GODM)
Table 6.5: Comparison matrix of PSFF model
Table 6.6: Comparison matrix of COMB model
Table 6.7: Derived weights of evaluation criteria
Table 6.8: Evaluation matrices of sub-criteria for GODM model
Table 6.9: Evaluation matrices of sub-criteria for PSFF model
Table 6.10: Evaluation matrices of sub-criteria for COMB model
Table 6.11: Derived weights of sub-criteria
Table 6.12: Evaluation matrices of alternatives with sub-criteria (GODM)
Table 6.13: Evaluation matrices of alternatives with sub-criteria (PSFF)
Table 6.14: Evaluation matrices of alternatives with sub-criteria (COMB)
Table 6.15: Estimated values of tangible criteria and sub-criteria
Table 6.16: Final synthesis and derived weight of alternative dry ports
Table 6.17: Derived local weights of main criteria corresponding to alternatives
Table 6.18: Final weights of decision criteria of COMB model
Table 6.19: Goal programming model output
Table 6.20: Values of deviation variables

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Table 7.1: Route, choice and attribute levels
Table 7.2: Attribute levels of choices
Table 7.3: Orthogonal and balanced choice sets generated by SPSS
Table 7.4: Scenarios for questionnaire design A
Table 7.5: Scenarios for questionnaire design B
Table 7.6: Summary of response received on SP Survey

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viii

Table 7.7: Estimated generic model parameters
Table 7.8: Estimated model parameters
Table 7.9: Attributes and level of changes for determining elasticity
Table 7.10: Mode share from elasticity analysis
Table 7.11: Emission factors
Table 7.12: Forecasted freight demand at Thanalaeng
Table 7.13: Road and rail distance from port to dry port
Table 7.14: Assessment of CO2 emissions
Table 7.15: Freight demand and distance
Table 7.16: Emissions from other dry ports
Table 7.17: Life cycle CO2 emissions of construction of Thanalaeng dry port

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LIST OF FIGURES
Figure

Title

Page

Figure 1.1: Study area in Laos and Thailand

6

Figure 2.1: Energy consumption by sector in Asia and the PacificFigure 2.2: Energy consumption by transport sector
Figure 2.3: Global GHG emissions by sector
Figure 2.4: CO2 emission by sector Asia and the PacificFigure 2.5: CO2 emissions by countries
Figure 2.6: CO2 emissions by modes in EU
Figure 2.7: Transport share of emissions by modes
Figure 2.8: Emission factor of transport modes
Figure 2.9: Phases of life cycle assessment
Figure 2.10: Freight modal split of inland transport in EU
Figure 2.11: Freight modal split for selected Asian countries
Figure 2.12: Laos freight mode share
Figure 2.13: Policies and regulations relevant to dry ports
Figure 2.14: Laos foreign trade volume
Figure 2.15: Study area and location of dry ports in Laos

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Figure 3.1: Relationship between research objectives and analysis modules
Figure 3.2: Integrated methodological framework
Figure 3.3: AHP model

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Figure 4.1 Age, gender and geographical distribution of respondents
Figure 4.2: Education level and experiences of the respondents
Figure 4.3: Awareness levels of policy makers and general public
Figure 4.4: Response to transport and climate change related statements
Figure 4.5: Level of response and coordination during emergencies
Figure 4.6: Response to design standards and practice related statements
Figure 4.7: Response to design and practice questions
Figure 4.8: Response to policy and institutions related questions
Figure 4.9: Coordination and policy implementation
Figure 4.10: Conceptual framework of adaption adoption process
Figure 4.11 SEA and EIA policy framework

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Figure 5.1: Block train and container yard, Uiwang ICD
Figure 5.2: Container throughput at Uiwang ICD and mode share of road and rail
Figure 5.3: Block train and containers at Birgunj ICD, Nepal
Figure 5.4: Cargo handled at Birgunj ICD
Figure 5.5: Block train being assembled for Lat Krabang and containers
Figure 5.6: Containers handled at Lat Krabang ICD
Figure 5.7: Mode share of containers handled at Lat Krabang ICD
Figure 5.8: Container traffic through border dry ports in China

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x

Figure 5.9: Alashankou dry port and truck near Horgos border, China
Figure 5.10: Containers handled by CONCOR, India
Figure 5.11: Container and block train at Tughklabad ICD, India
Figure 5.12: Navoi Logistics Centre, Uzbekistan
Figure 5.13: Cikarang Dry Port, Indonesia
Figure 5.14: Block train and container yard in Kamalapur ICD, Dhaka
Figure 5.15: Volume of container handled at Kamalapur ICD

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Figure 6.1: Location of dry ports
Figure 6.2: Format of pair-wise comparison questionnaire
Figure 6.3: Gender and distribution of the respondents of AHP survey
Figure 6.4: Friendship bridge border check posts and Thanaleang railway station
Figure 6.5: New 3rd Mekong Bridge at Thakhek and existing ferry upstream
Figure 6.6: Border check post and Savannakhet and container truck
Figure 6.7: Border crossing point Vang Tao-Chong Mek and truck at borderFigure 6.8: Relative weights of alternatives with respect to five criteria
Figure 6.9: Final derived weights of alternative dry ports for COMB model
Figure 6.10: Results of synthesis of environmental criteria for COMB model
Figure 6.11: Final weight and ranking of alternative dry ports

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Figure 7.1: Format of the choice scenarios presented in the questionnaire
Figure 7.2: Block train to Lat Krabang ICD and Laem Chabang Port
Figure 7.3: Age, gender and experience of the respondents of SP survey
Figure 7.4: Mode choice decision and railway use
Figure 7.5: Respondents perception on rating of cost, time and reliability
Figure 7.6: Elasticity of mode share due to cost variation
Figure 7.7: Elasticity of mode share with variation in transportation time
Figure 7.8: Elasticity of mode share with cost and time variation
Figure 7.9: Elasticity of mode share with variation in reliability

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CHAPTER 1
INTRODUCTION
1.1

Background

Sustainable transport development involves the provision of safe, reliable and environmental
friendly transport without aggravating adverse global phenomenon. Sustainable mobility isdefined as the ability to meet the needs of society to move freely, gain access, communicate,
trade, and establish relationships without sacrificing other essential human or ecological values,
today or in the future (WBCSD 2004). While social sustainability, environmental sustainability,and economic sustainability, the three pillars of sustainability, are equally important, the current
research focuses on environmental sustainability of transport system.
Recent frequent occurrences of extreme weather events provide enough evidence of increase inintensity and frequency of climate events in Asia. The rise in temperature, long heat spells,
increase in frequency and intensity of precipitation, tropical cyclones, rise in sea levels in coastal
areas substantially affect transport infrastructure and system (Christensen et al. 2007). Various
studies have assessed the impacts of climate events on transport in developed countries (Wooller
2003, Harvey et al. 2004, Galbraith et al. 2005). These studies showed that the climate events
have substantial effect on planning, design, construction, operation and maintenance of thetransport system (Andrey and Mills 2003, NRCNA 2008). However, limited studies are available
in the area of climate change and adaptation in the transport sector in Asia.
Transport and climate change is a cyclic phenomenon. On one hand, transport system is affectedby the extreme climate events; on the other hand, emissions from transport operations contributeto the global warming which in turns aggravates extreme climate events. It is therefore important
to consider both adaptation and mitigation while dealing with sustainable transport development.
Energy consumption in the transport sector in Asia is growing faster than that of other sectors
and other regions, driven by a rapid increase in motorization and strong transport demand for
economic development. Within the transport sector of the Asia-Pacific region, road transport,
being predominant mode of transport in Asia, consumes about 80 per cent of petroleum products
whereas the share of rail is just 2%. The global energy use in the transport sector is expected toincrease by 50 percent by 2030 (IEA 2009a).
Meanwhile, the transport sector is the primary source of air pollution and one of the largest
contributors to overall green house gas (GHG) and CO2 emissions. Transport sector contributes
23% of global CO2 emissions (IEA 2009b) and road transport contributes about 75% of GHG
emission from transport (IPCC 2007). Freight emissions account for about one-third of the totaltransport emissions.
These days the climate change is high on global and national agenda and there are now growing
concern to initiate measures to reduce energy consumption and emission from the transport
sector. Countries are voluntarily discussing and taking measures to reduce emissions so as tokeep the increase in global temperature below 20C (UNFCCC 2009). To achieve this and cut
1

down global carbon emissions, transport sector has to play a leading role.
Many researches, initiatives and policy measures on sustainable transport development andclimate change focus on passenger and urban transport (Kamakate and Schipper 2009, Han andHayashi 2008, Burwell 2009, Collantes and Gallagher 2009). These include emission reduction
potential through modal shift from private mode to public transport and mass transit system,
demand management through congestion charging, improvement of vehicle efficiency, and useof non-fossil fuels. Guidelines relating to passenger, urban and road transport are readily
available. However, limited studies are available in the area of freight transport emission though
this contributes one-third of total transport emission. As many studies cover passenger and urban
transport and there is research gap in the area of freight transport.
One of the ways to address emission reduction could be through development of intermodaltransport and encouraging modal shift. In order to promote intermodal transport development oftransport links and nodes that include ports, airports, river ports and inland dry ports as well as
improvement of efficiency of transport services is essential. Development of dry ports offers
opportunity for modal shift by integrating various modes of transport.
Intraregional exports and imports are increasing throughout Asia. Exports and imports grew byover 15% year-over-year from 2007 to 2008 (ESCAP 2009b). Asia’s share of worldcontainerized exports and imports are expected to rise to 68% and 56%, respectively, by 2015.
The total number of containers handled in Asian ports is estimated to reach 492 million twentyfoot equivalent units (TEU) by 2015, and the transshipment volume comprises 109 million TEUof this total (ESACP 2007a).
Development of sustainable transport systems to meet the needs of intra- and interregional tradeare an increasingly important issue given the need to optimize the use of scarce energy resources
and to reduce emissions. While all aspects of sustainable mobility are important, the research
focuses on climate change impacts on transport, development of dry ports as an important nodeof intermodal transport, freight modal shift and emissions assessment.
1.2

Problem statement

Sustainable transport development involves dealing with both adaptation and mitigation. While itis essential to safeguard and develop durable transport infrastructure and system from impacts ofextreme climate events, it is also important to reduce energy consumption and emissions fromtransport. The current research is an attempt to look at both aspect of sustainable transport.
Firstly, one way to develop sustainable transport infrastructure is to assess likely impacts ofclimate change and incorporate those in the planning, design and development of transport
infrastructure and system. Analysis of perception of policy makers and general public towards
climate change impacts on transport can provide useful guidance to plan and implement
adaptation measures.
Secondly, with respect to mitigation one of the ways to reduce energy consumption andemissions from the transport sector is to promote freight modal shift. Currently freight transport2

is predominantly carried by road transport in Asia. In order to reduce emissions, mode shift offreight from road transport to more environmental friendly and energy-efficient modes such as
railways, inland waterways and shipping is necessary.
In this respect, in order to promote modal shift, the existing transport system needs to offer
choice of modes such as road, railway and inland waterways. Then there needs to have facilities
such as dry port that integrates various modes and offers opportunities to change mode. There
has been substantial progress in developing road and rail network in Asia. However, thedevelopment of intermodal facility is at initial stage. The strategic location of such facility canoffer and motivate mode choice. Further, as emission is a function of distance travelled andtonnage carried; therefore, the location of dry port is an important consideration for promotingintermodal transport. Strategic location of dry port can reduce total ton-km of freight transported
in whole logistics chain. Therefore, policies and interventions that are conducive to encourage
freight modal shift are necessary. The policy should enhance the attractiveness of modal shift
through provision and availability of efficient and effective modal shift services and facilities
such as dry ports with further connection to sea ports.
It is also necessary to visualize how much would be the shift in mode after developing such dry
port. Therefore, an estimation of mode shift and resulting emissions reduction would also be
useful to the decision makers to consider policy intervention for developing dry ports andintermodal transport. This measure can supplement other efforts to reduce emissions such as
vehicle technology, innovative fuels, demand management etc.
Often, multiple interventions are required to move toward sustainable transport development.
The decision problem involves analysis of location of dry ports considering various factors andviews of different stakeholders and estimation of modal shift and resulting emissions. The
stakeholders include government decision makers as well as private sector freight forwarders andtransport service providers.
Analytic Hierarchy Process (AHP) one of the Multi-criteria Decision Analysis (MCDA)
methodologies (Saaty 1997) can incorporate feedback of various stakeholders and can be utilized
in prioritizing and ranking alternatives. The subjective as well as objective criteria and subcriteria that are relevant to a location problem can be incorporated in AHP (Saaty 1995). MCDA
was used to evaluate alternative options for environmentally sustainable transport system in
Delhi (Yedla and Shrestha 2003) and assessment of transport projects (Tsamboulas et al. 1999). A
transport route that offers two mode choices linking the priority location of a dry port with sea
port can be analyzed through stated preference survey to estimate potential mode share. The topdown, bottom-up approaches and life cycle assessment can be used to estimate emissions.
Further, development of dry ports in secure inland location would safeguard these facilities fromrisk of damage from raising sea levels and storms.
In addition to its contribution toward the modal shift and emission reduction, strategic location ofdry ports can play an important role in the development of an intermodal transport system andhad the potential to become centers for economic development allowing more trades, particularly
in landlocked countries and wider domestic hinterlands.

3

1.3

Research questions

In this respect the research questions that need to be further explored are:(a) How to safeguard transport infrastructure from impacts of extreme weather events andmake it more secure and safe?
(b) How to evaluate environmental benefits of dry port development and prioritize location?
(c) How to encourage freight modal shift from road to railway in order to reduce CO2
emissions from transport?
The research thesis is that the adaptation strategies developed considering impacts of climatechange can assist policy makers in developing robust transport infrastructure and facilities thatprovide intermodal transfer opportunities such as dry ports which can encourage intermodaltransport, modal shift and potentially reduce CO2 emissions. While further exploring the second
research question, as the emissions largely depend on the vehicle-kilometre travelled, therefore
the location of dry port is an important aspect to be considered.
1.4

Research objectives

In this background, the primary objective of the research is to assess the impacts of climatechange on transport and mitigation potential of the dry port development. It aims to propose
adaptation strategies and measures to safeguard vulnerable transport infrastructure. It also aims
to review the development of dry ports in Asia, develop mode choice model and evaluate CO2
emission from freight transport using bottom-up approach. The outcome and results of theanalysis and assessment are indented to assist decision makers to make rational decisions todevelop sustainable transport development including promotion of modal shift and intermodaltransport.
The specific objectives of the research are:(i). To evaluate policy maker’s perception on the impacts of climate change on transport andpropose adaptation strategies to safeguard vulnerable transport infrastructure;(ii). To review the development of dry ports with an environmental perspective and analyze
location of dry ports; and(iii). To assess potential freight modal shift due to the development of dry ports and assess
CO2 emissions for various scenarios.
1.5

Research fr amewor k

The study integrates adaptation and mitigation aspects of sustainable transport development. An
integrated methodology is proposed that combines adaptation policies and strategies to develop
and safeguard transport infrastructure, evaluation of intermodal transfer location such as dry port
utilizing multi-criteria decision analysis and multi-objective decision making, estimation of
freight modal shift through use of stated preference survey and assessment of CO2 emission.
The research takes case study and quantitative analysis approach including formulation andevaluation of quantitative mathematical models such as analytic hierarchy process (AHP), AHP4

goal programming (GP), mode choice model, and emission assessment through bottom-up andlife cycle analysis.
The research framework includes following four stages.
(i) Identification of current issues and problems: Initially, the concept of sustainability andsustainable transport, recent climate events and its impacts on transport infrastructure, trend of
freight transport, energy use in transport sector, emissions from the transport sector withparticular reference to Asia are reviewed to define problem statement and research objectives
more clearly.
(ii) Review of literatures and methodologies: Works carried out in the area of adaptation andmitigation are reviewed. Based on the review, various multi-criteria decision analysis (MCDM),
multiobjective decision making (MODM), and emission measurement approaches, appropriate
methodology is selected for development of mathematical models.
(iii) Data collection: It involves development of questionnaires and data collection fromgovernment policy makers, freight forwarders and transport operators for the study. The primarydata collection involves four stages: (i) perception of government policy makers on climatechange impact on transport and adaptation policy and strategies; (ii) collection of case studies ondevelopment of dry ports in Asia; (iii) judgment of government decision makers, freight
forwarders and transport operators on pair-wise comparison of criteria and sub-criteria andalternative dry port location in Laos; and (iv) stated preference survey of freight forwarders andtransport operators in Laos and Thailand on mode choice between road and railway. Additional
data relating to the costs, time, distance of the O-D route, freight volume, emission factors, andgovernment infrastructure development policies are collected from secondary sources.
(iv) Model analysis: It includes evaluation of models using primary data collected, location
analysis, estimation of mode shift, emission assessment, life cycle emission assessment andscenario analysis and a series of conclusions are drawn. Any need for further research is also
identified within the scope and limitation of the study.
1.6

Scope and limitation

1.6.1

Scope and study area

The study focuses in Asia to assess the impacts of climate change on transport and adaption
measures. Laos, one of the land locked country in Asia is selected for dry port location problem
and analysis, because there is a potential to develop intermodal transport, railways and encourage
mode shift. The study focuses on freight transport as there is substantial volume of trade between
Laos and Thailand. Stated preference survey to estimate the potential mode shift choice andassessment of CO2 emissions is undertaken along a transport corridor between Laem Chabang
Port in Thailand and a dry port in Laos. The origin/destination point in Laos is selected after thelocation analysis of four alternate dry ports. Figure 1.1 shows the study area in Laos andThailand.

5

Figure 1.1: Study area in Laos and Thailand
The study is limited to the analysis of dry ports in Laos and freight transport to/from Thailand. It
considers transport from seaport to dry port and does not consider domestic leg of transport in
Laos. Also, the study area and four alternative dry ports are selected based on proximity toThailand and their potential to serve international and transit transport through Laos.
1.6.2

Limitation

Survey input from transport officials and experts from Asia, government policy makers in Laos,and freight forwarders and transport operators in Laos and Thailand are used for analysis. Modechoice options only consider two choices – road and rail. Emission factors from Thailand areused in the analysis as majority of freight routes pass through Thailand. Five criteria, 12 subcriteria and four-alternative locations are selected for AHP model to ensure more reply fromsurvey respondents. Even this ended with 101 questions for pair-wise comparison. The resultspresented are reasonable and can be generalized in context with some caution in view of thelimitation. Flooding in Thailand during October-December 2011 affected the collection of datafrom freight forwarders for the stated preference survey.
1.7

Scholarly contribution of the research

Followings are the scholarly contribution of the research:(i)

Developed integrated methodology linking AHP, AHP-GP, mode choice, bottom-up
6

analysis and life cycle assessment to analyze dry port location problem, estimate
mode shift and assess resulting CO2 emission;(ii) Collected four set of primary data for the research from policy makers and private
sector freight forwarders;(iii) Analyzed perception of policy makers on the impacts of climate change on transportand proposed adaptation strategies in the Asian context;(iv) Revealed environmental benefits of intermodal transport and development of dry
ports;(v) Analyzed actual dry port locations in Laos from the perspective of government
decision makers and users such as freight forwarders, transport operators, transport
service providers and representatives of commerce and industries; and(vi) Developed mode choice model and estimated mode share of freight transport throughthe development of dry ports, and rail service and assessed resulting CO2 emissions aswell as life cycle emissions of dry port construction.
1.8

Str ucture of the thesis

The thesis is presented in the following structure.
Chapter 1 presents background, research questions, objectives, and research framework.
Chapter 2 includes extensive literature review covering all aspects of sustainable transport,
adaption, mitigation, ongoing research on mitigation. It further elaborates CO2 emission
assessment, development of intermodal transport and outlines MCDA focusing on AHP, goal
programming, and mode choice.
Chapter 3 presents integrated methodology proposed for the study that includes assessment ofclimate change impacts and policies for adaptation measures and strategies, AHP and goal
programming for analysis of dry port location problem, mode choice model, emissions
assessment through bottom up approach and life cycle assessment and scenario analysis.
Chapter 4 presents details of survey of policy makers on climate change policies and adaptation.
It presents assessment of impacts of climate change on transport analyzing the survey data
received from policy makers, and proposes adaptation strategies and measures to safeguard
vulnerable transport infrastructure. It also discusses how the adaptation measures in thetransportation sector could be financed within framework of clean development mechanism(CDM) or other mechanisms.
Chapter 5 presents the collection and analysis of case studies of the development of dry ports in
Asia. The case studies are analyzed with respect to their ownership and operational model,
potential environmental benefits, potential area of improvement to enhance efficiency, andlessons are drawn.
Chapter 6 presents details on primary data collection for the location analysis that involved
seeking feedback from decision makers and freight forwarders in Laos. It includes the analysis ofdata utilizing analytic hierarchy process and goal programming. It involves pair wise comparison7

of criteria, sub-criteria and alternative location of dry ports in Laos and analysis to prioritize thelocations, results and discussion.
Chapter 7 presents details of data collection for estimation of mode shift through statedpreference survey of freight forwarders and multimodal transport operators in Laos and Thailand.
The data are analyzed to develop a freight mode choice model to choose between road and rail.
The model is used to estimate potential mode shift and then emission assessment throughbottom-up approach and life cycle emission assessment. It also includes discussion on the
research results, measures to reduce emissions, and effects on mode shift due to variation in timeand cost of each mode.
Chapter 8 presents summary of findings, conclusions of the research and its contribution andsuggestions for further research.
Appendices contain supplementary information related to the research including questionnaires
used for data collection.

8

CHAPTER 2
LITERATURE REVIEW
2.1

Introduction

This chapter outlines review of relevant literature related to the current research.
Firstly, various definitions and approaches to the sustainable transport development are
explained. The needs to incorporate both climate change adaptation of transport infrastructure
and mitigation approach are elaborated. This then outlines adaptation and mitigation measuresand measurement of emissions from transport sector. Various approaches and methods to assesstransport emissions including top-down and bottom up approaches are stated. Emission factors
relevant to the study area; namely, Laos and Thailand, and emissions measurement studies intransport and Asian context are elaborated. The concept of life cycle assessment is introduced
highlighting various approaches of measuring emissions from the construction of dry port
infrastructure.
Secondly, state of freight mode share in Asian context and the need to encourage modal shift
through intermodal transport are elaborated. This further looks at the freight transport, issues ofmodal shift, dry port development and potential environmental benefits of such system, andillustrates dry port location problem.
Thirdly, various approaches to location analysis of intermodal transfer points such as dry ports
are outlined, which include multi-criteria decision analysis (MCDA), analytic hierarchy process(AHP), goal programming (GP) and combined AHP and GP. An account of earlier research andstudies in this area is provided.
Fourthly, mode choice model, design of choice experiment, choice sets and stated preferences
experiment are highlighted thereby citing many similar studies used in freight transport.
Fifthly, the status of freight transport in Laos is elaborated highlighting existing freight transportsystem and the plans to develop dry ports, logistics centres and intermodal transport.
Finally, a chapter summary with suggestion for appropriate methodology to be used for thecurrent research is outlined.
2.2

Sustainable transport development

Sustainable development is the development that meets the needs of the present withoutcompromising the ability of future generations to meet their own needs (WCED 1987).
Sustainable transport development involves the provision of safe, reliable and environmental
friendly transport without aggravating adverse global phenomena.
There are various extended definitions of sustainable transport development. The World BusinessCouncil for Sustainable Development defines sustainable mobility as the ability to meet the9needs of society to move freely, gain access, communicate, trade, and establish relationships
without sacrificing other essential human or ecological values, today or in the future (WBCSD
2004). A sustainable transport system should consider three pillars of sustainability namely:social sustainability; environmental sustainability;’ and economic sustainability. The first one
deals with social development which elaborates the objectives of provision of safe andeconomical access, acceptable level of air and noise pollution and supporting achievement of theMillennium Development of Goals (MDG). The second deals with environmental protection,
safeguarding the ecosystem, climate change and optimization of resources. The third deals witheconomic development which considers the efficiency, effectiveness and financial sustainabilityof the transport system.
Sustainability of transport systems is an increasingly important issue given the need to optimallyuse scarce energy resources and reduce emissions. In order to move towards a sustainabletransport system in the region, it is essential to establish institutions that promote good
governance and integrated planning, to enhance capacities of people and institutions and to use
appropriate technologies that are compatible with the level of development.
Sustainability of the transport system could be greatly enhanced through innovation in design,
construction and technology as well as policies to ensure funds for their development andmaintenance. For example, innovation in maintenance and vehicle technology can ensure smooth
operation of transport system, reduce operating costs and emissions. Whereas, innovative
approaches to funding can ensure adequate funding for maintenance which in turns reduce life
cycle costs and prolongs life of transport infrastructure. This research does not deal withtechnology innovations it however discusses the approaches to safeguard transport infrastructurefrom impacts of climate change, development of dry ports and intermodal transport, measures topromote mode shift, reducing emissions and policies that are relevant to freight transport.
One of the ways to address the issues of sustainability in the transport sector is to reduce energy
consumption and vehicle emissions. Adaptation or mitigation alone cannot cope with all
projected impacts of climate change. However, they can complement each other and cansignificantly reduce the risks of climate change (Pachauri 2008, Sperling et al. 2009). Bothadaptation and mitigation aspects of sustainable transport development should encompass theconcept of sustainability. Therefore, the attempt should be not only to look at impacts of climatechange on transport but also towards reducing contribution of transport to climate change. The
current research aims to look at both aspects that include adaption as well as reduction ofemissions in the transport sectors considering policies and initiatives to promote modal shift toenvironmentally friendly transport modes such as railways.
2.2.1

Adaptation

Climate is defined as the average weather. Climate change refers to change in the state of theclimate that can be identified by changes in the mean and/or the variability of its properties, andthat persist for an extended period, typically a decade or longer. Impacts refer to the effects ofclimate change on natural and human systems. Adaptation refers to initiatives and measures toreduce the vulnerability of natural and human systems against actual or expected climate change
effects.
10

2.2.1.1

Climate change and transportFrequent occurrence of extreme weather events provide enough evidence of increase in intensityand frequency of climate events recently in Asia. The Intergovernmental Panel on Climate
Change (IPCC) Fourth Assessment Report predicts that Asia is expected to experience rise intemperature, longer summer heat spells, more intense and frequent precipitation, increase in
extreme rainfall and tropical cyclones, rise in sea levels in coastal areas around the Indian Ocean
and northern and southern Pacific Oceans (Christensen et al. 2007).
Transport system is affected by these climate events. Increase in temperature, precipitation, risein sea levels and storm surges contribute to significant impacts on planning, design, construction
and maintenance, and operation of road transport (Wooller 2003) as well as all modes oftransport. Transport is not only affected by these climate events, it also contributes to the global
warming through emission of green house gases (GHG) from operation of road vehicles. Road
transport contributes about 75% of GHG emission from transport (IPCC 2007).
Some studies have identified research gaps in the area of impacts assessment and quantification,
implications for design guidelines, appropriate adaptation strategies for transport sector(Lemmen and Warren 2004). The IPCC Synthesis Report suggests the need to integrate climatechange considerations into national transport policies and on research and development (IPCC
2007).
Several studies have assessed and documented the impacts of climate change on transport ontransport in developed countries such as Australia, Canada, Scotland, the United Kingdom andthe United States (Wooller 2003, Andrey and Mills 2003, Harvey et al. 2004, Galbraith et al.
2005; NRCNA 2008, ICF 2008). These studies have shown that climate change have madesubstantial impacts on planning, design, construction, operation and maintenance oftransportation system. These studies can provide guidance on the type of potential impacts. The
climate change threatens to severely affect the basic elements of life for people around the worldsuch as access to water, food, health and use of land and environment (Stern 2007). However,very limited studies have been conducted to cover Asian context (ADB 2008a; Hay et al. 2004,
and Tanner et al. 2007).
Koetse and Rietveld (2009) have extensively examined the effects of climate change on transportand concluded that most studies focus on short term impacts with transport sector receiving little
attention. Some of observed impacts listed are effects on coastal transport infrastructure due tosea level rise, effect on traffic safety and congestion on roads by precipitation, delay in railtransport, high winds and visibility have effect on safety and delay for air transport, low and highwater levels affect water transport.
There are many recent examples of extreme climate events in Asia. These include intense rain
and flooding in China in 1999; serious flooding in Japan in 2000 brought about by ten typhoons;serious and recurrent floods in Bangladesh, Nepal, and the northeastern states of India during
2002, 2003, 2004 and 2007; record rainfall of 944 mm in Mumbai in 2005; flooding in Sri Lanka
in 2003; the Ache Food of 2007 in Indonesia; the 2008 flood in Vietnam; heavy rain and floodingin the Philippines in 2004; and flooding in Cambodia in 2000. China, Japan, the Philippines, and11South Asia were frequently hit by cyclones and typhoons during this time, and North-East Asia
was subjected to several extreme snowfalls during the 2009 winter. These extreme events caused
severe damage to transport infrastructure and operations.
The damage done to transport infrastructure by 2007 floods in Bangladesh was 34% costing
about US $ 363 million (MFDM 2007). The Aceh Flood 2007 in Indonesia caused significant
damage to the transportation sector amounting US $ 35 million that is 25% of infrastructure costs(GOI 2006).
Therefore, it can be seen that the scale of impacts on transport infrastructure depends on theseverity of climate events and on the local topography, terrain, and natural conditions. Different
adaptation measures and strategies would be necessary to deal with different types of impacts
and topography.
2.2.1.2

Adaptation measures

In order to safeguard vulnerable transport infrastructure from the impacts of climate change
planning and implementation of appropriate adaptation measures are necessary. Agrawala andFankhauser (2008) have studied costs of adaptation measures and mention that only limited cases
are available in the transportation sector. They concluded that there is a need to conduct a careful
cost-benefit analysis of adaptation measures. The design of adaptation programme must be basedon comparison of cost avoided with costs of adaptation.
For assessment and evaluation of impacts, the IPCC guidelines, Carter et al. (1994) recommend a
standard seven-step approach: (i) define the problem; (ii) select an appropriate assessment
method; (iii) test the methods; (iv) select and apply climate change scenarios; (v) assess
biophysical and socioeconomic impacts; (vi) assess autonomous adjustments; and (vii) evaluate
adaptation strategies. In contrast, Klein et al. (1999) doubted the usefulness of IPCC guidelines
for assessing climate change impacts and adaptation which focuses more on implementation andsuggested a simple four-step approach that includes collaboration, coordination, policy
formulation, and implementation.
A study looked at impact of sea level rise in the coastal area but it mainly focuses on populationand infrastructure planning (Dasgupta and Laplante 2007). Even though it did not covertransport, the study suggests that planning should consider all associated risks and recommends
avoiding coastal and vulnerable areas while planning infrastructure. In terms of impacts they
predict that Vietnam is expected to be badly affected in Asia. In addition to the Pacific Island
countries, coastal mega-deltas in Asia such as Dhaka, Kolkata and Shanghai are at high risks ofbeing severely impacted by the rise in sea level (IPCC 2007).
ADB (2008a) has initiated incorporating adaptation measures in project design andimplementation. Some example includes “climate proofing” of the design of the Avatiu Harbor in
the Cook Island, water resource management infrastructure in Indonesia, and coastal
infrastructure project in Vietnam. ADB’s adaptation programme for the Pacific has initiated“climate proofing” of some infrastructure projects. One of the road construction projects being
implemented was in Micronesia (Hay et al. 2004).
12

2.2.1.3

Design review

Many literatures have indicated that it may be beneficial to review the design life of various
components of the transport infrastructure. Many studies have suggested that as current design
standards may not be sufficient to accommodate climate change and stressed the need to develop
new design standards to address future climate conditions. The projects in highly vulnerable
locations should be built with higher standards (Wooller 2003, NRCNA 2008). Short (2009) has
outlined that there is evidence already that our infrastructure design standards need to be reexamined to better deal with the consequence of climate change.
Meyer (2008) argued that US highway design standards developed 50 years ago, may not be
sufficient to accommodate the impacts of climate change while examining potential changes indesign and engineering practices due to climate changes in the US. He suggested that projects inhighly vulnerable locations should be built with higher standards and stressed the need to review
the current US highway standards and develop new design standards to address future climate
conditions. He mentioned that design change is a time consuming process and gives an example
of introducing “superpave” binder that took 25 years for its adoption as a new standards despite
scientific evidence of benefits. Robert (2007) has looked into the issue of climate change andmobility management.
Meyer (2008) further mentioned that the clearance of bridges have been increased after the
Hurricane Katrina. One meter sea level rise was incorporated into the design of Confederation
Bridge in Canada (Andrey and Mills 2003). Dasgupta and Laplante (2007) suggested integratingtransport and land use planning to consider vulnerable area. Some local authorities in UnitedStates are planning to outlaw transport and infrastructure development in vulnerable coastal
areas.
2.2.1.4

Life cycle costing

Costing is a key factor in deciding the adaptation measures. How safe and strong should be theinfrastructure and at what cost? There are limited research in costing and life cycle costing ofadaptation measures in transport sector (Agrawala and Fankhauser 2008). Ozbay et al. (2004)
have analyzed the application of life cycle cost analysis in highway agencies in US and found
implementation gaps, mistrust between theory and knowledge and its implementation. It was
mainly applied in road pavement but not extensively for other road structure.
A climate risk screening and management approach called Opportunities and Risks of Climate
Change and Disasters (ORCHID) methodology has been developed by the Institute ofDevelopment Studies (Tanner et al. 2007). They argue that the methodology helps development
organizations and their partners to integrate risk reduction and adaptation processes into theirprogrammes. They have implemented pilot projects in India and Bangladesh. In one of thetransport project in Bangladesh the study have evaluated options of raising road embankment
height from 0.5 to 1.0 m to protect the road from flood and found that it was an economically
viable option.
Multilateral institutions have just started to begun to integrate adaptation concern in their13

programmes but it has not yet penetrated the policy makers. One of the important aspects ofadaptation is to streamline responses to climate change policy in development planning (Burtonand van Aalast 2004; MDBs 2007). Most of these approaches are general but not transport
sector specific. Of the six case studies reviewed by the OECD not a single case was related totransport (Agrawala 2005). Mills and Andrey (2002) also acknowledged the gap in
understanding climate change impacts, adaptation and its costs. Bouwer and Aerts (2006) lookedat the financing options and suggest that climate adaption should be seen as general risk
management issues and linking “climate proofing” of development projects to management
practice in national sectors and multilateral donors as a viable option. Srinivasan (2006) argued
adaptation must be considered in an intergraded manner locally, nationally and internationally bymainstreaming adaptation concerns in development planning and policy.
2.2.2

Mitigation

Mitigation refers to implementing policies to reduce greenhouse gas emissions and enhance sinks(IPCC, 2007). Many mitigation initiatives and measures in the transport sector focus on theissues of passengers and urban transport. These include emission reduction potential throughmodal shift from private mode to public transport and mass transit systems, demand management
through congestion charging, improvement of vehicle efficiency, and use of non-fossil fuels.
Guidelines and publications relating to passenger, urban and road transport are readily available(Dalkmann and Branigann 2007, ADB 2006).
2.2.2.1

Energy use in the transport sector

The transport sector is the third largest consumer of energy and the largest consumer ofpetroleum product in the Asia and the Pacific region. Energy consumption in the transport sector
is growing faster than that of other sectors and other regions, driven by a rapid increase inmotorization and strong transport demand from economic development. The global energy use in
the transport sector is expected to increase by 50% by 2030 (IEA 2009a). Within the transport
sector of the Asia and the Pacific region, road transport consumes about 80% of petroleum
products whereas the share of rail is just 2%. Evidently, road is the heavily favoured transportmode in Asia for both passengers as well as freight.
Figure 2.1 illustrates energy consumption in Asia and the Pacific region by sector (IEA
2010a) and shows that the transport is the third largest consumer of energy after industrial
and residential consumption.

14

Energy Consumption by sector, 2008 (Asia and the Pacific countries)

Others, 5.24%
Commerce and public
services, 6.61%

Industry, 36.55%

Residential, 26.12%
Transport, 16.08%

Source: IEA, 2010aFigure 2.1 Energy consumption by sector in Asia and the PacificFigure 2.2 further illustrates energy consumption by the transport sector (IEA 2010b) andclearly shows that the road transport subsector consumes 436.2 million tonnes of oil
equivalent or about 78% of the consumption of the transport sector. This is followed by pipetransport with an 8.37%, whereas the share of rail subsector is only 4.66%.
Energy Consumption by transport sector, 2008
Domestic navigation,
4.02%
Pipeline transport,
8.37%

Others, 0.50%
Domestic aviation,
4.38%

Rail, 4.66%

Road, 78.07%

Source: IEA, 2010b

Figure 2.2 Energy consumption by transport sector
2.2.2.2

Transport sector emissions

Figure 2.3 illustrates the contribution of various sectors to global greenhouse gas (GHG)
emissions and shows that the transport sector accounts for 13.1% of total world emissions(IPCC 2007).

15

Waste andwastewater, 2.8%
Forestry, 17.4%

Energy supply, 25.9%

Agriculture, 13.5%

Transport, 13.1%

Residential andcommercial
buildings, 7.9%

Industry, 19.4%

Source: IPCC, 2007

Figure 2.3 Global GHG emissions by sector
Globally, CO2 accounts for 75% of the total GHG emissions, of which the transport sector
accounts for 23% (IEA 2009b). Road transport accounts for 75% of transport CO2 emissions,whereas the share of rail and shipping is 12.5% and that of aviation is 12.5% (Stern 2007).
Figure 2.4 shows that in the Asia and the Pacific region CO2 emissions from the transport
sector were 1,587.4 million tons, of which 1,275.8 millions ton or more than 80% was fromroad transport. The transport sector ranked third in term of CO2 emission and accounted for
13.6% of total emission, road transport alone accounting for almost 11% of the total
emissions (IEA 2010b).
CO2 emissions by Sector in Asia and Pacific* in 2008

Other Transport,
2.67%

other sectors, 11.58%

Road Transport,
10.94%

Electricity and heatproduction, 55.57%

Manufacturing andconstruction, 13.85%
Other energy
industries, 5.39%

Source: IEA, 2010b

Figure 2.4 CO2 emission by sector Asia and the Pacific16Figure 2.5 shows CO2 emissions by countries, which clearly shows that US has highest share of
CO2 emissions followed by China. EU share of emission is 16.3%. Major industrialized Asian
countries China, India, Japan, and South Korea collectively accounts for 30.7% of CO2
emissions (EC 2009).

Others, 22.4%

USA, 20.3%

Mexico, 1.5%
Canada, 1.9%

EU-27, 16.3%

Brazil, 1.2%
South Korea,
1.7%Japan, 4.3%

India, 4.5%

Russia, 5.7%

China, 20.2%

Source: EC, 2009

Figure 2.5 CO2 emissions by countries
Figure 2.6 shows CO2 emission by mode in EU which clearly shows that the road transport
accounts for 71% of CO2 emissions while railway has insignificant 0.6% share. This mode shareclearly shows that policies and measures for emission reduction should be focused on roadtransport, if the transport sector has to contribute to the global GHG reduction.

Others,0.8%
Navigation,
15.3%

Civil
Avaitation,
12.2%

Railw ay,
0.6%

Road,
71.0%

Source: EC, 2009

Figure 2.6 CO2 emissions by modes in EU
While in aggregate, 80% of the region’s CO2 emissions from the transport sector originate in
the road subsector, this percentage varies from country to country, depending upon theimportance of each mode of transport in the overall transport task.

17

Figure 2.7 illustrates that the road subsector in Thailand and Kazakhstan accounted for morethan 90% of total CO2 emission generated from road transport activities, whereas roadtransport activities in China and the Russian Federation generated 73% and 54% of total CO2
emission of transport sector respectively in 2008 (IEA 2010b).
Transport: Share of CO2 emissions by mode
100%
90%
80%

0.78%

5.56%
26.81%
45.79%

70%
60%
50%
40%
30%

99.22%

94.44%

othersroad

73.19%
54.21%

20%
10%
0%
China

Kazakhstan

Russian Federation

ThailandSource: IEA, 2010b

Figure 2.7 Transport share of emissions by modes
Among transport sector, the road transport consumes large share of energy and has highest shareof emissions both for passenger and freight. Therefore, the focus of policy interventions andactions should be targeted on reducing energy use and emissions from road transport. One of the
key policy challenges for sustainable transport development therefore would be to increase themodal share of “greener” modes of transport from road to railways and inland waterways
through the increased use of multimodal transport.
2.2.2.3

Emissions measurement

Measurement of transport emissions is necessary to plan and implement policy measures. An
accurate emissions measurement can facilitate monitoring and assessment of emissions includingCO2. It can be useful in planning sustainable transport policies, develop and implement
appropriate climate change mitigation measures, and enhance international cooperation.
Development and use of standard assessment methods for CO2 emissions can also help theassessment of achievement and make possible for comparison among countries.
There are many existing models available to measure emissions such as: US Environmental
Protection Agency’s Mobile and MOVES; European Environment Agency’s COPERT 4;
International Vehicle Emission (IVE) Model; and International Energy Agency’s Mobility Model(MoMo). ADB’s Excel sheets are some frequently used models. Review of some emission
models used in countries can be found in OECD (2002). Recently developed emission model
Changer (IRF 2009) can estimate total carbon footprint of road construction, maintenance, andrehabilitation.
18

However, there are several data gaps in Asia. Most of the emissions data referred to are fromdeveloped countries OECD, European Environment Agency (EEA), and IEA. It is difficult tofind vehicle activity data; therefore, initiatives are required to collect and collate emissions datain Asia.
(i)Top-down and bottom-up approaches

The emission factors are usually aggregated and averaged over a large number of driving cycles
and due to the method employed to estimate emissions factors and disaggregation of emissions
they may not reflect emissions of vehicles driven under actual conditions.
The emission factors estimation are based on either ‘top-down’ or ‘bottom-up’ approaches. In the
top-down approach, total annual road traffic emissions are disaggregated first spatially and thentemporally over the area, using traffic load and speed variation in a dimensionless form. In thebottom-up approach, emissions are calculated on the basis of the available traffic patterns andthen summated. Emissions are calculated for each street or road of the area under simulation, andon an hourly basis. The patterns of traffic flow, and the variation of average speed with time,should be used to calculate the temporal variation in emissions. This means that traffic counts
and speed measurements (or estimates) should be available for the modelled area. Clearly, thebottom-up approach attempts to simulate reality more accurately, and requires more effort than
the top-down method, although it is not yet clear whether such a degree of sophistication resultsin more reliable emission estimates, and consequently better air quality simulations (EEA 2009).
In principle, the top-down and bottom-up estimates of motor vehicle emissions are carried out
independently. In each case the most reliable information (such as traffic counts, statistics ofvehicle registrations and measured emission factors) form the basis of the calculation.
Bottom up approach is useful to calculate emissions for specific conditions and vehicle type thatcan be aggregated. Bottom-up approach provides more clue than top-down, and can provide
more information to policy makers to assess driving force behind the increasing emissions.
However, the bottom-up approach needs more and reliable data that can be compared with topdown estimates (Kumari et al. 2005, Ravindra et al. 2006)
Bottom-up focuses on technology and their characteristics, while top-down focuses more on
process within economy of energy system and historical behavior. Bottom-up approach is suited
to evaluate policy instruments and both top-down and bottom-up approaches are comparable fortransport sector (van Vuuren et al. 2009, Hoogwijk et al. 2010).
For measuring emissions from road transport EMEP/EEA Guidebook (EEA 2009) recommends
using Tier 2 or Tier 3 methods. These are usually called bottom-up approach. While Tier 1,
which uses average emissions factors and fuel sold or consumed is referred at top-down
approach. IPCC guideline also recommends using Tier 1 and Tier 2 for carbon emissions.
(ii)

IPCC Tier 1, Tier 2 and Tier 3 methodologies

Vehicle emissions can be estimated using different approaches and accuracies. Various
19methodologies to be used for measuring emissions are outlined IPCC Guidelines (IPCC 2006).
Countries follow the prescribed method to report national emission to the United Nations
Framework Convention on Climate Change (UNFCCC). Depending on degree of accuracy
required three Tier approach is used. The level of complexity also increases with Tier. CO2
emissions are best calculated on the basis of amount and type of fuel combusted and its carbon
content.
The ‘Tier 1’ approach is a simple method to calculate CO2 emissions by multiplying estimated
fuel sold with a default emission factor. The general Tier 1 equation for CO2 emissions from roadtransport is:
Emission = Σ [Fuela × EFa]

(2.1)

Where:
Emission = Emission of CO2 in (kg),Fuela= fuel sold (TJ);EFa= emission factor (kg/TJ)a= type of fuel (petrol, diesel, natural gas, LPG etc)
Tier 2 approach is similar to Tier 1 but the default emission factors should be replaced bycountry-specific carbon contents of the fuel sold in road transport are used. The Tier 2 approachconsiders the fuel used by different vehicle categories and their emission standards. Equation(2.1) can be used for Tier 2 method as well.
Methodologies for estimation of emissions from railway locomotives are similar for three Tiers
and they only have variation of the same equation:
Emissions=Σ(Fuelj*×EFj )(2.2)

Where,
Emissions = emissions (kg),
Fuelj = fuel type j consumed (as presented by fuel sold) in TJ
EFj = emission factor for fuel type j (kg/TJ),
j = fuel type (diesel, gas oil).
For Tier 1, emissions are estimated using a fuel-specific default emissions factor, assuming thatfor each fuel type the total fuel is consumed by a single locomotive type. Tier 2 uses the same
equation with country-specific data on carbon content of the fuel.
Tier 3 is more detailed than Tier 2 methodology based on activity data and emission factor butwith a greater disaggregation of activity data and emission factors. When a more accurate
estimation of the relevant emissions is required Tier 3 methodology is used. It considers hot andcold start emissions as well as different driving situations like urban, rural and highways.
However, for CO2 emission measurement IPCC Guidelines recommends using only Tier 1 andTier 2 methodologies and for railways there is no advantage of using Tier 3 methodology(Eggleston et al. 2006).
20

EMEP/EEA Guidebook (EEA 2009) provides a different equation containing number of vehicles
and annual distance travelled:
Ei,j= Σ (Nj,k × Mj,k× EFi,j,k)(2.3)

Where,
Ei,j= Emissions
EFi,j,k = technology-specific emission factor of pollutant i for vehicle category j and technology k[g/veh-km],
Mj,k = average annual distance driven per vehicle of category j and technology k [km/veh],
Nj,k =number of vehicles in nation’s fleet of category j and technology k.
Schipper et al. (2009) outlines simple activity based approach called ASIF to calculate emissions.
G = A* S*I*F(2.4)

Where,
G= carbon emissions from transport
A= Total activity (passenger or freight travel)
S= Modal structure (travel by mode)
I=Modal energy intensity
F=Carbon content of fuel.
(iii)

Framework for measuring freight emissions

Most of the above vehicle emission models are centered on emission factors and fuelconsumption for particular type of vehicles. The emission factor considered is also aggregatedand averaged at national level which may differ from actual field condition. All these models
give figures for comparisons which at cases may be far less than actual emissions. There is awide variation in value of emission factors depending on the source being used. Fuelconsumption also may not take account of air conditioning, lights used during driving etc. At
time the estimates could understate the emissions by 25% (OECD 2002).
Therefore, it is proposed to measure emission by combining Equations (2.1) and (2.2) to estimate
total emission from road vehicle and rail as they will be using different fuel compositions. Thisapproach is similar to the emission measurement approach taken by Schipper et al. (2009). The
combined equation is:
Emissions = Σ (Fueli,j × EFi,j)(2.5)

Where,
Where, ‘i’ is total fuel type consumed by vehicle ‘j”
Introducing an average vehicle kilometer and number of vehicle, the equation (2.5) can be
written for a land transport corridor,

21

Emissions = ΣFVj*VTKmj*EFRi,j + ΣFTj*TTKmj*EFTi,j(2.6)

FVj – Number of freight trucks
VTKmj - Average vehicle Ton-km travelled
EFRi,j =emission factor of fuel i for vehicle j (g/veh-km)
FTj = Number freight Train,
TTKmj = Average train Ton-km travelled,
EFTi,j=emission factor of fuel i for locomotive t (g/train-km).
(iv)

Emission factors

The emission equations require emission factors for emission estimation. Vehicle emissions
largely depend on type of vehicle, engine capacity, speed, actual driving pattern, condition ofroad, load factor etc. In case of train, it depends on engine capacity and traction used whether it
is electric, diesel or coals driven, load factor, speed, and track condition. These data are
aggregated and averaged. Variation on emission factors are found based on different sources.
There are many data and research available in IEA countries. IEA used top-down approach foremission calculation. Table 2.1 presents CO2 emission factors complied for LDV, HGV andfreight trains (DEFRA 2009).
Table 2.1 Emission factors of various transport modes
Mode

Emission Factor
gm/ton-km
400.1
118.6
28.3
20
13

Road LGV
HGV
RailSmall tanker
Large container

Source: DEFRA, 2009

IPCC Guidelines suggest that CO2 emission factors should be within a range of +5%. It is goodpractice to ensure that default emission factors reflect local fuel quality and composition.
Figure 2.8 illustrates the emissions factors of various modes of transport in Thailand. It clearlyshows that water and railway transport are far less polluting than road transport. Therefore, inorder to have net environmental benefits, we need to explore ways and means to encourage
modal shifts to more less polluting or environmentally friendly modes.

22Thailand freight emission factors
Trucks

93.1

Train

27.4

Water

10.7

0.0

20.0

40.0

60.0

80.0

100.0

CO2 emissions-g/ton-km
Source: Derived from Chamroon, 2011

Figure 2.8 Emission factors for transport modes(v)

Studies on measurement of transport emissions

Woodburn et al. (2008) suggest interventions such as policy, regulation and infrastructuredevelopment for model shift many opportunities to improve efficiency and environmental
impacts of international road and rail freight transport. Buehler et al. (2008) looked at ways tostimulate environmental friendly behavior through used of inland container depot (ICD) and dry
ports and concluded that potential to reduce CO2 emission through model shift is limited inGermany. Bauer et al. (2009) claim that CIRRELT was first to address environmental issues infreight transport and distribution planning model utilized minimization approach, scheduling andapplication to rail network, container based transport, intermodal nodes and links. The role ofenergy efficient vehicle technology was discussed and predicts 30-50% emissions reduction
possible in 20-40 yrs through improved engine, weight and drag reduction, hybrid technology,
reduce demand and integrated planning (Heywood 2008).
The MOVE software developed in US claims to be best tools for GHG emissions can handle
multi-scale analysis, policy analysis, and requirement to assess emission and develop state
implementation plan. Transport sector use 35% of total energy in Thailand and 76% of transportenergy consumed by road sector indicating high dependence on road sector and suggest
expansion of rail freight transport as one of the policy option (World Bank and NESDB 2009).
A methodology for evaluating environmental impacts of railway freight transportation policies
was developed and used in Leon-Gijon railway line in Spain and revealed that bottom-up
analysis gives good result (Lopez et al. 2009). Freight transport in UK has been analyzed. One
study looked at expert’s opinion on the environmental impact of road freight in the UK in 2020
using the Delphi techniques and concluded that the transport grew faster than GDP during 19952005 and forecasted that freight is expected to grow at slower pace (Piecyk and McKinnon 2006,
McKinnon and Piecyk 2009).
23

Kamakate and Schipper (2009) used bottom-up approach to compare energy intensity of truck
freight in selected developed countries and focus on road freight transport by light and heavy
truck. Similar earlier studies revealed that growth of emissions from trucking and that there is alittle opportunity for a major shift from trucking to rail. Wang et al. (2008) used the bottom-up
methodology to estimate vehicle emissions for the Beijing urban area combining vehicle
emission factors, vehicle activity data, and vehicle emission using a travel demand model.
Woodburn (2003) looked at logistics perspective of freight mode shift from road to rail in GreatBritain.
McCollum and Yang (2009) looked at 80-50 emission reduction potential in US discussed Silver
Bullet Scenario and argued that not a single mitigation option can meet GHG goal. They outlinedthat a combination of technology, public transport, vehicle efficiency were major areas for CO2
reduction. Tsamboulas et al. (2007) analyzed potential of mode shift, sensitivity analysis, andpolicy action plan, applied it to two corridors in Europe and suggested that railway liberalization,
increasing efficiency of terminals and rail speed were some of the policies for action plan. Van
Essen (2009) analyzed modal shift and decoupling transport growth from GDP for freighttransport and proposed infrastructure policy, improving interconnectivity and pricing were major
policy that can influence a modal shift. Timilsina and Shrestha (2009) analyzed trends of energy
use in Asian context applying decomposition analysis. De Jong et al. (2004) reviewed freighttransport models and suggested approaches for future development of fast system dynamics
model for policy analysis and detailed network-based freight transport model with interlinked
modules.
(vi)

Life cycle assessment

The above methods give estimates at a point of time or yearly based on activity. However, whiledeveloping infrastructure usually the assessment of emission over its life cycle is assessed. It canthen be compared to see whether there are any environmental benefits of developing such
facilities.
There are many definition of life cycle assessment (LCA). It comprises a systematic evaluationof environmental impacts arising from the provision of a product or service (Hunt et al. 2009).
LCA is a “cradle to grave’ assessment tool for products or processes (Mundy and Livesey 2004).
ISO: 1997 defines LCA as “compilation of product system throughout its life cycle.”
An ISO 14040 and 14044 standard recommends using four interdependent phases as shown in
Figure 2.9 while carrying out LCA. They are: (i) scope and definition; (ii) inventory analysis;(iii) impact assessment; and (iv) interpretation.

24

Goal andScope

Interpretation

Inventory
Analysis

ImpactAssessment
Source: ISO: 14040, 2006

Figure 2.9 Phases of life cycle assessment
Utilizing process based LCA CO2 emissions of transport infrastructure and related infrastructure
can be estimated. For an O-D pair for freight movement in order to influence modal shift the
infrastructure needs have to be determined. Basically this involves civil infrastructure related toroad, rail, bridges and dry ports construction. The LCA approach can evaluate construction
related CO2 emission due to infrastructure development.
Chang and Kendel (2011) have used similar LCA approach for high speed rail construction in
California. The emission factors of various construction activities can be found in literature andguidelines (Kato et al. 2005, Akerman 2011). Guideline and code of practice for life cycle
assessment have been developed by the Society of Environmental Toxicology and Chemistry andUnited Nations Environment Programme’s life cycle initiatives (UNEP 2011). Institute forTransport Policy Studies (ITPS) and Japan Railway Construction Plc have analyzed effect ofrailway development from the view point of environment. Ministry of Land Infrastructure andTransport (MLIT), Japan has developed summery report of the survey on transport related energy
consumption in Japan. LCA was used in South Korea to analyze LCA of energy consumption
and GHG emission in transport sector using input-output table (Phirada et al. 2010).
The system boundary and activities for LCA is first defined and then life cycle inventory analysis
is carried out to estimate the quantity of various types of infrastructure development such aslength of road, railway, size of dry ports, and length of bridges. The ideal way of doing LCA is tocover material production, material transport and equipment used for construction of transportlinkages. Other approach used is input-output method to evaluate various components.
2.2.2.4

Freight mode share

Figure 2.10 shows the freight modal split of inland transport in EU. The road has more than twothirds of freight mode share. In EU countries overall tonne-km increased by 34% between 1997
and 2007. During the same period road freight increased by 43%, air freight 31% and maritime
transport grew by 10% (EEA 2010). The growth in road sector is outpacing other sector. Freighttransport activity in tonne-km is expected to nearly double by 2020.
25

120

100

Pipelines
Inland Waterw ays
RailPercentage

80

60

40
Road

20

0
2000

2001

2002

2003

Year

2004

2005

2006

2007

Source: EEA, 2010

Figure 2.10 Freight modal split of inland transport in EU
Similarly, Figure 2.11 illustrates the freight modal split of selected Asian countries and indicatesthat road transport has a major share of total tonnes of freight carried in these countries. The
figure also shows a slight growth of freight carried by railways in the Russian Federation and byinland waterways in China, the Russian Federation and Thailand. For Thailand in 2009 thefreight mode share of road transport has 84% share and water transport (inland and coastal) 14%
and train about 2%.

26

Source: CEIC 2010 and ECE 2010

Figure 2.11 Freight modal split for selected Asian countries
However, if freight transportation is considered in tonne-kilometres, total freight in China was
11,030 billion tonne-km in 2009, of which highways accounted for 30%, railway 21% and watertransport 47% While in India total freight was 1,410 billion tonne-kilometres in fiscal year
2007/8, of which road accounted for 50%, railway 36% and water transport 6% (Dayal 2011).
Figure 2.12 shows the freight mode share in Laos which shows that road transport has 79.5%
share and water transport 20.5% and air transport has negligible share (CEIC 2010).

27

Laos freight mode share (Ton)
100%

Road

Water

Air

2004

2005

2006

80%
60%
40%
20%
0%
2000

2001

2002

2003

2007

2008

2009

Source: CEIC, 2010
Figure 2.12 Laos freight mode share
In case of Japan also the freight mode share heavily favoures road transport with share of 61%,
while maritime 34.8%, railway 4%, and air transport 0.2% (JFRC 2009).
As road mode share is more than other modes in all situation, one of the key policy challenges
would be to increase the mode share of non-road transport modes such as railways andwaterways which are more environmentally friendly and energy efficient than road transport.
Woodburn et al. (2007) have analyzed scope of mode shift in UK through fiscal and regulatory
measures.
2.3

Intermodal transport

Intermodal transport refers to the movement of goods in one and the same loading unit or roadvehicle, which uses successively two or more modes of transport without handling the goods
themselves in changing modes (ECE 2001). Intermodal transport is also defined as the use of atleast two different modes of transport in an integrated manner in a door-to-door transport chain(OECD 2001).
Intraregional exports and imports are increasing throughout Asia. Exports and imports grew byover 15% year-over-year from 2007 to 2008 (ESCAP 2009b). Asia's share of world containerized
exports and imports are expected to rise to 68% and 56%, respectively, by 2015. The total
number of containers handled in Asian ports is estimated to reach 492 million twenty-footequivalent units (TEU) by 2015, and the transshipment volume will comprise 109 million TEUof this total (ESCAP 2007). The growth of intraregional trade and the expected growth ofcontainerized transport in Asia clearly demonstrate the need for improved intermodal freighttransport in the region.
Earlier models of transport development have adopted a unimodal approach in which road andrail projects were planned and constructed separately without much consideration for their
possible future integration. Intermodal transport uses more than one mode of transport anddelivery of goods from origin to destination. Such transport has been studied in detail by
policymakers and transport planners, who are undertaking various policy initiatives to promote
28the concept and implementation of intermodal transport. The development of intermodaltransport requires the consideration of three of its attributes: transport links, transport nodes, andthe provision of efficient services. The following section provides further details on thedevelopment of transport link, nodes and services in Asia.
2.3.1 Transport links
In order to promote intermodal transport, it is essential to improve transport links such as
highways, railways, and inland waterways. In Asia, there has been good development oftransport networks such as Asian Highway and Trans-Asian Railway (ESCAP 2003 and 2006).
The Master Plan on ASEAN Connectivity (ASEAN 2010), which includes the SingaporeKunming Rail Link and other transport corridors, is an example of the attention that national
governments are giving to the transport links. Asia includes major countries like China, India andthe Russian Federation, which have extensive railway and highway network; however there is aneed to construct missing links of railways to provide uninterrupted railway connectivity in thesecountries. Further, roads and highways also need to be constructed and upgraded to higher
standards to improve highway connectivity. In addition, certain highways and railways routes
lack capacity and maintenance therefore considerable investment has to be made for regular andperiodic maintenance if they are to provide efficient services.
Railway was first invented to carry freight, and they now run on clean form of energy (Smith
2003). The energy intensity and long life cycle of rail cars, along with new innovations that offer
increased speed, have put railways in a competitive position to take a major share of the growing
transport demand in terms of both freight and passengers. Efforts by policy makers and railway
operators are needed, though, necessary to maintain railway’s environmental superiority among
other modes of transport. The common factors likely to influence consumer’s choice of transportmode choice are relative cost, time and reliability, and for passenger service, the degree ofcomfort.
Other important issue related to international railway transport is break-off-gauge. Railway
tracks in many Asian countries have been developed using different track gauges, for instance,
1,676 mm, 1,520 mm, 1,435 mm, 1,067 mm and 1,000 mm. Different gauges at borders ofcountries prevent rolling-stock from passing through and create the need for goods to betransferred across these borders in a separate operation. These operations include manual ormechanical transshipment of goods from wagons of one gauge to wagons of different gauge, thechange of bogies, and the use of “variable-gauge” wagons (ESCAP 2011a).
2.3.2 Transport nodes
Transport nodes such as airports, seaports, logistics intermodal terminals, and dry ports need to
be developed in order to promote intermodal transport. From among these, seaports havedeveloped rapidly in Asia, as evidenced by the fact that 19 of the top 30 container ports in theworld are located in Asia (CI 2010). Inland dry ports are also important transport nodes,
particularly for landlocked countries. The development of these dry ports in inland area far from
seaports can promote intermodal transport, and provide intermodal transfer opportunities tochange a mode. These facilities also offer transshipment, temporary storage and distribution
29

services. Another important service the dry ports should offer is customs clearance facilities
where traders can clear their goods and cargoes near their business.
2.3.3 Transport services
Intermodal transport requires improvement in the efficiency of transport services. The logistic
performance index (LPI), which indicates the quality of trade, transport, and services, varies
widely among Asian countries. For example, Asian courtiers with high LPI for 2010 include
Singapore (4.09), Japan (3.97), South Korea (3.64), and Thailand (3.29) while Laos (2.46),
Mongolia (2.25), Afghanistan (2.24), Nepal (2.2) and most landlocked countries had a low LPI(Arvis et al. 2010).
Road transport, which is the most flexible transport modes, is usually operated and managed by
the private sector, and in certain limited cases, by the public sector. Most railway route
operations in Asia are still handled by public sector railway companies under overall government
control. Quality is the single most significant problem in railways freight operations. In order toattract greater share of freight, the quality and reliability of service must be improved, and thepunctuality of freight service must be maintained. This requires both a reform of existing railway
operation systems and new approaches to railway marketing. Ballis and Golias (2002) haveexamined ways of improving efficiency of railroad terminals. If private-sector freight forwarders
can provide quality services, public sector railway companies would also be able to improvetheir services. Service quality and price are important factors in encouraging a modal shift(Buehler et al. 2005).
In order provide door-to-door service, railways must be integrated with existing logistical
networks. Interfaces between railways and other transport modes are essential in order toencourage a modal shift. It has been suggested that government can help increase rail freightshare by developing rail freight as a business, encouraging a level playing field as well as private
sector involvement and competition, and reducing barriers of borders (Amos 2009).
2.4

Development of dry ports

The development of dry ports, as an integral part of the intermodal transport and logistics chain,provides opportunities for international trade by facilitating export and import of goods to/frominland locations. It can also bring social and economic development to the surrounding areas byattracting value added services and industries like freight forwarding, transportation, packaging,customs agent and others related services. The dry port can also support local industries byfacilitating their access to markets, and distribution.
While there have been efforts in Asia to develop regional highways, railways, and seaports,
inland dry ports are at an early stage of development. Therefore, efforts are required to extend
the reach of intermodal transport to the inland area and landlocked countries throughdevelopment of dry ports. Through connection with various modes of transport it can promoteintermodal transport and mode shift to energy efficient modes and contribute to the overall goalof emission reduction.

30

In addition, these dry ports have potential for attracting manufacturing and distribution facilities;
and economic stimulus for regional economic development. Furthermore, special economic
zones and free trade areas that provide special tax incentives are also being created adjacent todry port locations.
ESCAP has recognized the importance of dry port locations and suggests that the following
criteria are important when deciding upon a location: (a) inland capitals, provincial/state capitals;(b) existing and potential industrial and agriculture centers; (c) major intersections of railways,
highways, and inland waterways; and (d) intersections along trunk railways lines, major
highways, inland waterway, and at airport (ESCAP 2010a).
There are two type of approaches for the development of dry ports one is initiating a new dry
port to create its own market and service base and the other is servicing the existing demand of amarket. The third type could be upgrading of existing dry port in terms of increasing capacity,
improving efficiency and adding services and connectivity. Following section outlines
definitions, function and benefits of a dry port in more detail.
2.4.1

Definition and functions

A dry port is an inland terminal which is directly linked to a maritime port (ECE 2001). There arevarious terms used interchangeably to refer dry ports such as inland ports, inland container
depots, inland clearance depot, inland freight terminal, freight village, intermodal freightterminal etc. Notteboom and Rodrigue (2009) provide several definitions relating to dry ports,
inland transfer points, and inland terminals. ESCAP publication on logistics sector development(United Nations 2007) also includes various terminology and definition used and comprehensive
information on functions and framework for development of dry ports. ESCAP (2011b) uses theterm "dry port of international importance" and defines it as a “secure inland location forhandling, temporary storage, inspection and customs clearance of freight moving in international
trade.”The main function of dry port is to bring facilities offered by ports to inland areas. The mostimportant requirements of dry ports are: (i) connectivity to a seaport; (ii) customs clearance
service offered; (iii) security of cargoes; and (iv) facilitation of international trade. Rodrigue etal. (2009) stipulate following three fundamental characteristics related to an inland dry port:
(i)
(ii)
(iii)

An intermodal terminal, either rail or barge
A connection with a port terminal through rail, barge or truck services, often througha high capacity corridor.
An array of logistical activities that support and organize freight transited.

In addition Rodrigue et al. (2009) also state that dry ports service three major functions within
supply value chain (i) satellite terminal; (ii) fright distribution clusters or load centres; and (iii)intermodal transshipment facility.
Dry port should provide range of functions, facilities and services to the customers. Some of the
key functions and services required at a dry port are outlined in Table 2.2.
31

Table 2.2 Functions and services required at a dry port
S. No.
1

Transportfunctions

Type
and

logistics

2

International port functions

3

Information
Technology
functions
Other value added service to thecustomers and drivers

4

•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Function and service
Handling and dispatch of cargos and containers
Temporary storage of empty or laden containers
Temporary storage or warehousing of cargoes
Consolidation and deconsolidation
Transshipment of freight and cargoes
Customs inspection and clearance
Issuance of bill of lading
Functions related to international trade
Information systems linking customs/sea
ports/customers/service providers to facilitate transport
Freight forwarding
Customs brokerage
Security
Banking
Repairing and maintenance of vehicle and containers
Packaging
Sanitation
Medicine and emergency.

Source: ESCAP 2010d
In order to provide services to the customers, dry ports should have infrastructure, equipment andfacilities capable of handling existing cargoes and future demand. These largely depend on thecapacity of dry ports and function envisaged, the following list provide guidance on these(ESCAP 2011b).
(i)
(ii)

Secured area with gate and separate entrance and exit;
Covered and open storage areas separated for import, export, transshipment,
dangerous and high value cargoes;(iii) Customs bonded facilities;(iv)
Internal service roads and pavement for use in the operational and stacking area;(v)
Vehicle holding areas with adequate parking space for freight vehicles;(vi)
Container, vehicle and equipment repair and maintenance workshop;(vii) Administrative building for customs, freight forwarders, shippers, customs
brokers, banks, and agencies;(viii) Information and communication systems and services; and(ix)
Appropriate numbers of cargo and container handling equipment.
There is no standard classification of dry ports. They can be classified based on the mode served,
capacity, and location. Roso et al. (2009) suggested classifying dry ports based on distance fromports namely: close, midrange and distant dry port. Once the dry port is established and service isprovided continuous efforts should be made to improve operational efficiency of the dry ports,
streamline clearance procedures, increase reliability of transportation service between seaport
and the dry ports. These are very important aspects as in some developing countries in Asia thelogistics costs amounts to 10-20% of GDP.

32

2.4.2

Policies related to dry ports

Dry ports are a key component of the intermodal transport. Existing government policies andregulations relating to dry ports influence their development and operation. Figure 2.13 shows
the links between dry ports and various sectoral policies that may be relevant to the developmentof dry port (ESCAP, 2010b).

Source: ESCAP, 2010b

Figure 2.13 Policies and regulations relevant to dry ports
Different institutions are involved in development and operation of dry ports. The various
policies shown in Figure 2.13 are those affiliated with various sector and ministries. For
example, overall infrastructure development policy is related to the ministry of planning,
investment policy is related to the ministry of finance, while trade facilitation policy is related toministry of trade and commerce, and transport and logistics policy is related to the ministry oftransport. In addition, different levels of government-central, provincial, and local – will also
have different policies relating to the dry port development. For these reasons, coordination
among various sectors and different levels of the government is essential during development
and operation. Designation of lead or coordinating agency and thus providing potential
developers of dry port projects with “one stop” services and advice, including all necessary
government approvals, license, during planning, development and operation will facilitate thedevelopments of dry ports. Further, special economic zones and free trade areas that provide
special tax incentives are also being designated adjacent to dry port locations to provide
economic stimulus.
33

During operation in addition to the logistics services usually provided by the private sector the
related government agencies should arrange for necessary inspection and clearance. For example
a representative of customs for customs clearance, trade for export and import clearance andsecurity are necessary. Policy frameworks would be necessary in order to improve efficiency andservices at the dry ports. Some of the measures could be integrating transport modes, ensuring
better coordination among various agencies, designating a lead agency, setting up performanceand operational standards, pricing policy, policy on investment such as public private
partnerships, built-operate transfer, lease concession policy, streamlining procedure anddocumentation required for clearance, export and import, subsidies to environmental friendly
modes to promote a modal shift, and enhancing safety and security.
2.4.3

Benefits of dry port development

The development of dry ports offers three types of benefits: transport and logistics benefits;
economic and social benefits; and environmental benefits. First and foremost, benefits of dry
ports are the trade facilitation, customs clearance for medium business at door step rather thanhaving to go to the seaports for clearance. It also contributes to the economic and social
development of the surrounding area by bringing new opportunities for employment generation
and business. It is often seen that the area near dry ports are developed as special economic
zones, free trade areas and production and manufacturing centres. The dry ports make it easierfor business to trade and transport goods. These production and manufacturing centres generatecargoes for the dry ports that again generate employment opportunities and further business.
Thus, it creates a virtuous business cycle that attracts further investment and business to the area.
Door to door to service, customs clearance near business, value added service, opportunities forconsolidation of low volume cargoes, providing business for local trucks, mini trucks and vansfor distribution, and employment opportunity are list of few benefits. Dry ports can extend thecapacities of ports, reduce pollution, help to share cost of infrastructure, and provide additional
space for seaports.
Dry ports, where various modes of transport meet, can offers opportunities to encourage modal
shift from one mode to another. In order to receive net environmental benefits of intermodaltransport, measures that will encourage shift to more environmentally friendly mode arenecessary. The planning and development of freight terminals, freight villages, dry ports, ICDs
can extend the reach of the rail mode through intermodal services. Rail-based intermodal freighttransport is more environmental friendly than truck-only, particularly for long-distance haulage
in terms of CO2 emissions and other pollutants produced by long-distance hauling (Kim and Wee2009). Railway is considered an ideal mode of connection between seaports and dry ports (Rosoet al. 2009).
There are plenty of empirical evidences of environmental benefits of dry port development someof which are outlined in the following paragraphs.
Construction of consolidation centers/dry ports near strategic urban locations can also help
reduce the number of freight trips. One example of this is the Freight Construction Consolidation
Center in London. Established to consolidate construction freights and minimize construction34

traffic for building and development, it has resulted in fewer freight trucks and a 75% reduction
in CO2 emissions (TfL 2007).
Thus location of dry port and freight hubs is an important consideration. When analyzing
intermodal transport and location of dry ports or freight hubs, many studies have considered thepotential environmental impacts to be an important factor for analysis (Lv and Li 2009, Wei et al.
2009). The implementation of a dry port concept in Sweden, in which freight transported from
seaport and dry port by truck was replaced by railway transport, led to as much as a 25%
reduction in CO2 emissions as well as reduced port congestion (Roso 2007).
Activity-based emissions modeling of and intermodal transfer point in north Taiwan compared
distribution by intermodal transport using coastal shipping and trucks to distribution by trucks
alone. The results indicated that the efficiency of coastal shipping led to 60% less emissions(Liao et al. 2009). Other study showed greater reduction in CO2 when transshipment routes arechanged from the established ports to emerging port of Taipei (Liao et al. 2010). A study offreight emissions in London revealed that consolidation and distribution centers have combined
25.7% reduction in emissions (Zanni and Bristow 2009). Freight and consolidation centers/dry
ports have also potential to reduce the empty truck trips. For example, 12-30% of trucks run
empty in Pakistan and 43% run empty in China (Londono-Kent 2009). Improved logisticalorganization, coordination, and route planning could reduce CO2 emissions by as much as 1020% worldwide (OECD 2010).
The promotion and development of intermodal transport and a modal shift to rail transport canhelp to reduce CO2 emissions and other pollutants. Freight carried by rail emits much less CO2
compared to freight being transported by heavy good vehicle (HGV). In the UK, the average
CO2 emission per ton/km is 28.3 g for rail freight, 118.6 g for HGV, and 400 g for light goods
vehicles in UK (DEFRA 2009). Hanaoka et al. (2011) measured energy savings by intermodal
freight transport in Thailand and found that it would be possible to save 25% energy by using
intermodal transport.
Dry ports that are established near manufacturing and distribution facilities can offer positiveenvironmental benefits due to the reduced travel distance for manufacturing goods that are
distributed through dry ports and raw material that are transported to factories.
It is not always that dry port would only bring positive benefits. There are bound to be someadverse environmental impacts may relate to noise, pollution, and congestion. However, it will
also contribute to local economic development and trade.
In some instances, dry ports may induce more cargoes by improving efficiency of transport
services, thus truck haulage are possible to be increased which might also increase the possibilityof growth truck hauling that increases both noise and the emission of pollutants such as CO,
NOx, SO2, volatile organic compounds (VOCs) and hydrocarbons that contribute to local air
pollution. The noise and vibrations generated by freight vehicles, and the operation of handlingequipment, may also be a nuisance to locals living in the area. The quality of fuel used bytransport modes and vehicle congestion on roads as well as at dry ports can have additional
environmental impacts. Therefore, consideration should be given to the utilization of cleaner and35

greener forms of fuel/energy in transport and to the improvement of the operational efficiency oftransport services and dry ports by adopting an integrated and holistic approach. Environmental
impact assessment undertaken for the development and operation of dry ports should consider all
potential impacts and develop a mitigation plan for likely impacts, including emissions ofpollutants, noise, and vibrations. Although we must clearly understand that inland intermodal
freight transport cannot be made emissions-free, efforts should nonetheless be directed towardmaking intermodal transport more sustainable.
2.4.4

Contribution of dry ports to emissions mitigation

From the examples presented above, the environmental benefits of the development of dry ports
can be seen. They can be categorized as (i) reducing road congestion; (ii) reducing number of
empty truck trips; (iii) increasing load factors; (iv) reducing pollution; (v) improving operational
efficiency; and (vi) reducing emissions. As one of the primary characteristics of inland dry port isto have high capacity rail and/or inland waterways connection to the seaports, the resulting mode
shift further contributes to the emissions reduction.
However, it should be noted that the development of dry port itself is not sufficient condition toaffect a modal shift. For these to happen, many policy initiatives are required to make the railway
or inland waterway more attractive. This also highly depends on the frequency of services
offered, transportation cost and total transportation time. Streamlining clearance and inspection
procedure, reducing number of documents required for clearance are also importantconsiderations to improve overall efficiency of whole logistics chain. Mainly the responsibilityof facilitating these rests with the government. As Asia is still in early stage of dry port
development learning through experiences and bring good practices from other region would
help to continuous improve the process. Although not comprehensive, the following actions
would be required for a change of mode to happen.
(i)
(ii)
(iii)
(iv)
(v)

Efficient railway connection to sea ports
Reliability and frequency of service
Competitive dry port use price and delivery time compared to other modes
Customs clearance facilities
Use of information and communication service (ICT) such as electronic datainterchange (EDI), radio frequency identification (RFID) geographic information
system (GIS) to improve efficiency and provide information to the customers(vi)
Security of cargoes, containers, personnel at dry ports(vii) Quality of service;(viii) Provision of other value added service to the customers.
2.4.5

Dry port location problem

There are many factors that need to be considered while planning and developing dry ports. Lackof clear policies and institutional arrangements, conflicting interest of stakeholders pose greater
problem in selecting location of an inland dry port.
Some of the common factors that affect the location of dry ports are its proximity to ports,
36

markets and manufacturing area, connections to other modes of transport, costs of development,
operation and transport, potential of encouraging mode shift, environmental concerns, security,and existing government policies. While some of established cost benefit analysis (CBA),
environmental impact assessment (EIA) can look at economic, financial and environmentallyfeasibility that can compare potential alternatives. However, as many of the above factors are
subjective and cannot be quantified, that makes the location problem a complex.
The dry ports location problem can be analyzed by using multi-criteria decision analysis(MCDA). Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are wellrecognized methodologies to analyze multi-criteria decision problem. The methodology consistsof defining a problem with a set of evaluation criteria and sub criteria, assigning relative weight
for each criteria and evaluating alternatives location. This method can compare and rank possible
alternatives. The AHP/ANP model could help decision makers to evaluate various alternatives
and make decision based on their preferences. Lee (1998) has used AHP for appraisal oftransport projects in South Korea. AHP and ANP were applied for environmental impacts
assessment and evaluation of transport policies (Islam and Saaty 2010, Berrittella and Certa
2007, Brozova and Žika 2010). Yang and Kuo (2003) used AHP and DEA for analyzing facility
location problems.
Blauwens et al. (2006) suggests that a combination of policies can lead to modal shift and it canoccur if the shipper’s logistical requirements are fulfilled and fit in their logistical chain.
Jarzemsks and Vasiliauskas (2007) have analyzed the case of Baltic Sea Region through a survey
to know perception of shippers and industries perspective on dry port concept. Bontekoning et al.
(2004) have reviewed many studies based on search and concluded that there is a need to look at
modal split in routes. Baird (2005) compared existing hubs with new and competing hub
locations in order to optimize the container transshipment hub location in northern Europe.
Dadvar et al. (2010) looked at the feasibility of dry ports in Iran used a survey and StrengthWeakness-Opportunities-Threats (SWOT) analysis.
Arnold et al. (2003) have developed binary location model considering road and rail mode,
continental freight taking a case of Spain and Portugal. Multi-criteria decision analysis
methodology was used to evaluate transport projects such as ports and terminal in Brussels
focusing on stakeholder analysis (Macharis et al. 2004). An optimal location model wasdeveloped and used to evaluate intermodal terminals in Europe using reliability, flexibility andcost criteria (Moreira et al. 1998). Gursoy (2010) analyzed, rail-road sea mode using AHP in
Turkey considering shipping price, time for transportation mode choice.
Macharis (2001) developed decision support system PROMETHEE, using multi-criteria decision
analysis, location of inland water terminals in Belgian situation, and ranking of alternative using
LAMBIT model. Ng and Gajur (2009) surveyed 26 firms to look at the dualist policies ofgovernment, rent seeking behavior, and questioned whether dry ports are consumer oriented?
Wang and Meng (2010) used Monte Carlo simulation to estimate port market share in China andSouth Asia. Falzarano et al. (2007) developed Geospatial Intermodal Freight Transportation(GIFT) model to evaluate energy, environmental, operating cost and time trade off and elaboratea case of route selection of New York-Jacksonville that included intermodal transfer node, roadrail, and road-waterway, rail-waterway connections.
37

2.5

Multi-criteria decision analysis

MCDA has been extensively used to analyze problems that involve many stakeholders’ views
and considers many factors including those involving location problems. MCDA was used toevaluate alternative options for environmentally sustainable transport system in Delhi (Yedla andShrestha 2003) and assessment of transport projects (Tsamboulas et al. 1999). AHP and Analytic
Network Process (ANP) were used to study and evaluate potential location of logistics
centers/inland ports in China (Wang and Wei 2009, Wei et al. 2010), freight village in Greece(Kapros et al. 2005) and intermodal transshipment and hub ports in Turkey (Önüt and Soner
2008, Onut et al. 2010 and Tuzkaya et. al. 2008). AHP was used to analyze location of windobservation station (Aras et al. 2004), to measure performance of intermodal transport in
Thailand (Hanaoka and Kunadhamraks 2009), infrastructure management (Smith and Tighe2006), appraisal of transport projects in South Korea (Lee 1998), and prioritization of pavement
maintenance activities (Farhan and Fwa 2009, Cafiso et al. 2002). An agent based model wasdeveloped to analyze location of inland ports and hubs in Australia (Sirikijpanichkul 2007).
Ho and Dey (2010) have extensively reviewed the use of MCDA methods and found thatcombination of AHP-GP and DEA were the most applied MCDA approaches. Methodology
employing the use of AHP, ANP and AHP-GP were used (Lee 1998, De Montis et al. 2000,
Tanadtang 2004, Firouzabadi 2005). ANP and fuzzy logic were also used to analyze location
problems. However, Saaty (1995) argued that ANP and fuzzy-logic adds to the complexity of the
problem and calculations however the final output compared with AHP is similar. Firouzabadi etal. (2008) used MCDA to select design and manufacturing alternatives employing combined
AHP-GP approach. Sattayaprasert (2008) used AHP and ANP to analyzed transportation of
hazardous material in Thailand.
Therefore, from literature, it can be seen that the location problem can be analyzed by utilizing
MCDA approach. The decision problem involves consideration of various factors and views ofvarious stakeholders that include government decision makers as well private sector transport
service providers. AHP one of the MCDA methodologies (Saaty 1997) can incorporate feedbackof various stakeholders and utilizes this in prioritizing and ranking alternatives. The subjective
as well as objective criteria and sub-criteria that are relevant to the problem at hand can beincorporated in AHP. AHP has been widely used for planning and resource allocation,prioritization of alternatives- which is the problem at hand (Saaty 1995). As many criteria andpreferences could be conflicting- a set of solutions with ranking could be presented to the policy
makers to assist in the decision making process.
2.5.1

Analytic hierarchy process

AHP can consider both quantitative and qualitative criteria and derive relative weights andprioritize alternate locations based on evaluation criteria selected. The AHP has been extensively
used for location analysis and prioritization of alternative. Facility location of inland ports in the
United States was analyzed with objective of minimizing vehicle-miles travelled and promoting
regional freight transport (Rahimi et al. 2008). Wu et al. (2007) applied AHP for analysis of
hospital location in Taiwan, Ozdagoglu and Ozdagoglu (2007) used linguistic evaluation tocompare MCDA methods, Park et al. (2009) used AHP to evaluate air cargo express service of38

the carriers and Reza et al. (2011) applied AHP based life cycle assessment to evaluate flooring
system. AHP was used to prioritize transport projects (Shelton and Medina 2009), to selectrailway station site in Iran (Mohajeri and Amin 2010) and to select port in Nigeria (Ugboma etal. 2006).
Using a systematic hierarchy structure, complex estimation criteria can be clearly and precisely
represented (Saaty 2004). The AHP involves the following process:(i)
Hierarchy development- defining goal, evaluation criteria and sub-criteria andalternatives;(ii)
Pair-wise comparison of criteria, sub-criteria and alternatives;(iii) Weight derivation of criteria, sub-criteria and alternatives;(iv)
Synthesis- derivation of priorities; and(v)
Consistency check.
2.5.2

Location analysis using AHPThe facility location problem needs to be decomposed into levels of hierarchy consisting of one
goal, evaluation criteria, sub-criteria, and alternative locations. The criteria and sub-criteria need
to be further refined after consultation with the related officials. The alternatives selected shouldbe the location of real logistics centers proposed for development. This decomposition ofdecision problem makes it possible to judge the importance of the elements in a given level withrespect to other elements in the same level. The number of main criteria and sub-criteria has tobe not more than six in order to limit numbers of questions for pair-wise comparisons and toincrease probability of receiving feedback on the survey. AHP assumes the criteria and subcriteria should be independent of each other.
Sipahi (2010) and Tubucanon and Lee (1995) have extensively reviewed the application of AHP
in research and transport sectors. Appendix-I includes various criteria and sub-criteria used byother researches for location analysis of dry ports. Relevant criteria and sub-criteria can beselected after reviewing the elements considered by earlier studies (Wang and Wei 2009, Wei etal. 2010, Kapros et al. 2005, Önüt and Soner 2008, Onut and Saglam 2008, Tuzkaya et al. 2008,
Aras, et al. 2004, Mohajeri and Amin 2010, Ugboma et al. 2006, Guneri et al. 2009, Kahraman etal. 2003).
2.5.3

Multi-objective decision making

Some studies have also used multiobjective optimization approach (Racunica and Wynter 2005,
Macharis 2001) and considered minimization of time and costs. Rahimi et al. (2008) looked at
location allocation of ports and inland ports- with objective to minimize vehicle-miles travelled(VMT) and promotion of regional freight transport utilizing the concept of facility location.
Sirikijpanichkul et al. (2007) have analyzed location of inland ports and hubs in Australia anddeveloped an agent based model.
Ballis and Golias (2002) considered terminal design parameters, terminal capacity, and layout,
number of equipments, tracks, stacking policy, and technology. Kim et al. (2009) analyzed tradeoff between CO2 emissions and logistics costs based on multiobjective optimization of hub and39

spoke system for Rotterdam and Gdansk (Poland) port and evaluated various six scenarios.
Limbourg and Jourquin (2009) studied rail road terminals locations while analyzing efficiency ofsustainable transport and concluded that it depend on location of container terminals. Masui and
Yurimoto (2000) used input-output analysis and revealed that a 48% potential for reduction inroad emission which is the largest producer of NOx.
Ng and Gajur (2009) analyzed the spatial characteristics of inland transport hubs in Southern
India. They used mixed integer programming based on cross-sectional data to look at
performance, efficiency, competitiveness, container truck only and truck and train considering
Cochin and Tuticorin ports, Coimbatore and Tirpur ICD/dry ports.
Onut et al. (2010) used fuzzy ANP-based approach for ports selection to evaluate sevenalternative ports and concluded that Istanbul district was convenient in Marmara Region, Turkey.
Pedersen (2005) developed optimization models and solution methods for intermodaltransportation. Preston and Kozan (2001) developed an approach to determine storage locationsof containers at seaports terminals. Optimal location model of intermodal freight hub to look at
the increasing share of rail, hub and spoke system was used (Racunica and Wynter 2005).
Wisetjindawat (2010) discussed all options of freight modal shift presenting various cases ofmodal shift in European countries including water, coastal shipping and rail-environmental
friendly modes. The example included freight villages, consolidation centres and undergroundfreight system being developed in the Netherlands.
2.5.4

Goal programming

Goal programming (GP) is a part of mutli-objective decision making. Contrary to economic
analysis which usually considers single objective such as utility or profit maximization or cost
minimization, GP can consider multi-objective problems. This is common problem with decision
makers who are confronted with multiple and simultaneous objectives. GP attempts to minimize
the deviations from the goals and determines the point that satisfies the set of goals in a decision
problem (Schniederjans 1995, Schniederjans et al. 1982). Each objective is transformed to goals
with addition of deviation variables and specifying the most desirable value as the aspiration goal
(Jones and Tamiz 2010). In generalized term, the goal programming formulation is given byequation (2.7):

f i ( x) + d i− − d i+ = ai(for i= 1, 2..........n)(2.7)

Where d i− , d i+ >=0
d i− , d i+ are negative and positive deviation variables
x= decision variable
ai is the aspiration level of the goal or target.

GP always consist of two types of variables decision variables and deviation variables. The
objective function of the GP is always minimization of deviation variables. There are various
approaches to solve the location problem; weighted GP is commonly used to solve the multi40

objective decision problem. The weighted GP’s objective is to find a solution that minimizes theweighted sum of goal deviations as shown in equation 2.8. The overachievement andunderachievement of goals are undesirable.
Combined AHP-GP model can help decision makers to make proper decisions satisfying overallrequirements of policy maker’s priority and can consider budget and other constraints. AHP
output weights are used as input to GP. The combined model utilizes policy maker’s
perspectives/ preferences in addition to the location attributes-that considers costs, budget,
freight demand and using the coefficient and output of the AHP model makes combined AHP-GP
model more robust (Tu et al. 2010).
G

m(

MinZ = ∑∑ wg ,i d i + d i
g =1 i =1

−

+

)

(2.8)

n

s.t.∑ ai , j X j + d i− − d i+ = bi

(2.9)

j =1

Where,
wg,i- weight of goal g,ai,j -coefficient of decision variables (from AHP output)
Xj-decision variable, location of dry port
d+/- positive and negative deviational variables
bi target value or goal of a criteria
The GP objective functions can be developed for the each criterion used to evaluate the location
and reformulated as constraints adding deviational variables. These objectives can be expressed
as minimization of development and operation costs, transportation time, and environmental
impacts and maximization of intermodal transport connectivity and regional economic
development. Other constraints relating to capacities of proposed dry ports, freight demand, costof development of dry ports and available budget can also be used. Finally, as the location
problem is a binary (0, 1) whether it is selected or not and a constraint in the GP model can also
be added to ensure at least one dry port site is selected. Badri (1999) had combined AHP and
Goal-Programming to analyze global facility location problem. Yang et al. (2010) have applied
AHP-GP to analyze intermodal freight transport from China to Indian Ocean.
2.6Mode choice

The mode choice depends on the utility value of mode for the individual or company making
choice. There are two components of utility the systematic utility which can be measured tosome extent and a random utility component (Ortuzar and Willumsen 2001). Comparing themeasured utility value of one transport mode with other mode the decision to select a mode ismade. This is illustrated by following utility functions (Ben-Akiva and Lerman 1985).

Ui = Vi + εi

(2.10)

Where,

41

U- Utility function
V- Systematic utility
έ-random component of utility
i -number of alternatives/choices
Random utility theory stipulates that the observed inconsistencies in choice behaviour are taken
to be result of observational deficiencies on part of the analyst. The individual is always assumed
to select the alternatives with highest utility. However, the utility are not known to the analyst
with certainty and are treated by the analyst as random variables (Manski and McFadden 1999).
Macharis et al. (2011) have analyzed intermodal terminals and mode choice variables. In ourcase as road and railway are considered options and the attributes are time, cost and reliability ofroad and railways.
Binary choice models can predict the probability of choosing a freight mode. The choices areassociated with attributes mentioned above and utility values. Thus the probability of choosing
mode 1 is the probability of that U 1 is greater than U 2 :P1 = P (U 1 > U 2)

(2.11)

Where,
U 1 - is Utility of mode 1,
U 2 - is utility of mode 2.
The probability of selecting mode 1 is given by, binomial logit,

P (1) =

exp(V 1)
exp(V 1) + exp(V 2)(2.12)

Where,
P(1) –the probability of selecting mode 1
V 1 - measured/observed utility of mode 1
V 2 -measured/observed utility of mode 2.
Providing map based route information to users can induce route choice, similarly provision of
information on freight route, transfer facilities, costs could influence freight route choice. Field(2009) provides very clear explanation of estimation and interpretation using logistic regression
through SPSS.
Soderbom (2011), Eggers (2007), and Louviere et al. (2000 and 2008) suggested ways to design
choice sets. Further guidelines on choice set design have been elaborated (DOT 2002 and 2006).
Samimi et al. (2011) developed truck and rail binary mode choice model and argued that there isa low level of sensitivity of fuel price which did not triggered mode shift. Kofteci et al. (2010)
analyzed freight mode choice in Turkey. Fillone et al. (2006) modeled LRT in Manila using42

discrete choice. A mode choice model was developed and analyzed for Texas (Cambridge
Systematic 2002).
2.6.1

Stated preference (SP) experiment

SP survey can seek response to hypothetical situation such as if dry port is developed, railway isconnected, and frequencies of freight train service, dry ports user charges and providing themsome scenarios for selection. The survey can also include other questions relating to policies,
services that would be important for considering a mode shift and existing situation which isreveal preference (RP). But the RP is not be used for modeling. The attributes to be considered
for mode choice are total transportation time, transportation cost (including dry port charge), andreliability (delay) of services.
Ortuzar and Rose (2010) have extensively reviewed and discussed various development andtrends in designs and understandings of SP experiments and design of choice sets (DeShazo andFermo 2002). Fowkes and Shinghal (2002) have analyzed freight mode choice in Delhi-Mumbai
freight corridor in India using adaptive stated preferences method. Patterson et al. (2008) usedsurvey of shippers and SP experiment to study intermodal services and GHG emissions inQuebec-Windsor corridor in Canada. They analyzed nine scenarios and reveled that a 20%
increase in truck price was sufficient to overcome shippers’ bias. Aljara and Black (1995)
modeled Saudi Arabia-Bahrain corridor mode choice and Al-Ahmdi (2005) evaluated intercity
mode choice in Saudi Arabia.
Caramia and Guerriero (2009) looked at modal shift towards sustainable transport modes
including rail, short shipping, inland waterways, and multimodal considered a route in Italy.
Danielis and Rotaris (1999) have reviewed SP studies and compared of RP and SP approaches.
Cullinane and Toy (2000) reviewed SP literature and concluded cost, speed, transit time
reliability, characteristics of goods, and service are five mostly used attributes. Garcia-Menendez
and Feo-Valero (2009) have estimated binary logit model to estimate mode choice of road andshort shipping in Spain considering additional attributes than cost and time. Loo (2010) studiedcross-boundary container truck congestion in Shenzhen Western Corridor in Hong Kong-Pearl
River Delta region using SP. Fries et al. (2008) have used combined RP and SP to develop a
regional freight mode choice model in France –Nord-Pas-de-Calais. Weis et al. (2010) havedeveloped a mode choice model in Switzerland. Train and Wilson (2008) estimated StatedPreference experiments constructed from revealed preference choice and utilized inColumbia/Snake River System.
Dirghahayani (2009) used SP to analyze passenger mode shift to bus rapid transit system inIndonesia and used block design to present 27 choice sets as presenting all options would
confuse the respondents and can take considerable time thus risking not receiving survey input.
An impact of high speed rail on air transport in South Korea was analyzed using SP (Park andHa, 2006) and found that only 14% of passengers preferred to use air transport.
Major attributes considered for freight transport SP experiment are time, cost and reliability(Garcia-Menendez et al. 2004, Cullinane and Toy 2010, Norojono and Yuang 2005, GarciaMenendez and Feo-Valero 2009). Value of time saving was evaluated and found that time
43

savings represented 60% of benefits generated by infrastructure investment (Alvarez et al. 2007).
Feo-Valero et al. (2011a) have done extensive review of transport demand modeling andattributes to be used for mode choice models. Qualitative factors also play a significant role inthe modal choice, and that their relative importance varies according to samples (Beuthe and
Bouffioux 2008).
2.6.2

Application of SP experiment in mode choice

SP experiment has been extensively used for estimation of mode choice in the transport sector.
For example, Shimizu and Yai (1999) have conducted SP survey and looked at the ways toreduce peak congestion in Tokyo Metropolitan Area. Feo-Valero et al. (2011b) have used SP
technique using three generic variables transit time, transport cost and delivery time reliability to
study mode choice of road and intermodal alternatives. Ahern and Tapley (2007) consideredinterurban trips in Ireland and Khan et al. (2007) developed passenger mode choice logit modelfor Brisbane using SP survey which is capable of estimating mode share in a mutli-modal travel
environment. Feo-Valero et al. (2011b) used SP to develop mixed logit model to study mode
choice between road and rail in inland leg of freight transport in Spain.
Hensher et al. (2007) provide detail explanation of use of SP considering different utility
function that incorporate generic parameters as well as mode specific parameters using data fromSP Greenhouse Gas Emission Survey mode choice survey in Australia. It also explains details ofusing NLOGIT software. McCarthy (2001) has discussed a shipper’s transportation mode choicemodel for truck, rail and piggyback considering transportation rate, time and reliability as
attributes and generic variables. Gujarati and Porter (2009) have also discussed the estimation of
logit model using grouped data and provide clear interpretation of results including various
measures to check the goodness of fit such as pseudo ρ2, and McFadden ρ2and cunt ρ2.
2.7

Case of freight transport in Laos

Laos, a land-locked country, is centrally located in the Great Mekong Subregion (GMS) within
South-East Asia. It uses sea ports in Thailand and Vietnam for export and import of goods. Oneof the routes of the Singapore-Kunming rail project as well as the East-West GMS corridor
linking Vietnam to Thailand and Myanmar also passes through Laos. Thus it has a potential tooffer much needed land transport connectivity to China and Vietnam. Laos aspire to be seen as a“land-linked” rather than “land-locked” country with a vision to be a regional logistics hub in
GMS. Connectivity and logistics services are also part of development agenda in GMS and Laos
(Nolitha, 2011).
Laos total import and export was US $ 1,092 million (equivalent to 1.67 million tons) and US $2,430 million (equivalent to 1.963 million tons) in 2009 (UNCOMTRADE 2011). Figure 2.14
shows the steady growth of volume of foreign trade with its neighbors (ADB 2008b). It showsthat more than 80% of its trade is with Thailand, followed by Vietnam with 13% and China with
8%. Interestingly the volume of trade with southern neighbour Cambodia is very low. Therefore,transport connection to and from Thailand is very important for Laos. Thailand is preferred toVietnam as main transit route for Laos’s imports and exports (Arnold et al. 2003).

44

Source: ADB, 2008b

Figure 2.14 Laos foreign trade volume
Laos is well connected by roads with Thailand. Two bridges across Mekong have already been
constructed at Thanalaeng and Savannakhet. The 3rd Mekong River Bridge at Thakhek was
opened recently on 11 November 2011. Currently construction of a Mekong Bridge at Huayxai is
progressing and to be completed in 2012. National Highway-13 (Asian Highway-12) is the
backbone of road transport. In addition to the roads there is one railway connection toThanalaeng from Thailand. There are also plans to improve railway connectivity and feasibility
studies of connection from Boten, China-Vientiane, Vientiane-Thakhek-Vietnam border areprogressing (ADB 2010). The feasibility study of Boten-Vientiane Railway was completed andcurrently being reviewed at the time of survey. It was estimated that the construction cost would
be high due to the mountainous topography and the need construct many high bridges andtunnels. Vientiane–Thakhek rail route is also in pipeline for development. Railway network in
Laos is expected to expand in near future. The Mekong River is also used for water transport.
The current mode share is 80% by road and 20% by water transport. However, there is no freightshare currently carried by railways. ADB has estimated the freight demand for GMS to be 6.3
million tons for 2014 and 23.8 million tons for 2025 (ADB 2010).
Laos logistics performance index (LPI) is 2.46 which is better than its neighbours Myanmar(2.33) and Cambodia (2.37) while China (3.49), Thailand (3.29) and Vietnam (2.96) have higher
LPI than Laos. If we compare with other landlocked countries it is better than that of Nepal (2.2),
Mongolia (2.25), Bhutan (2.38) and Afghanistan (2.24). However, Kazakhstan (2.83) has higher
LPI than Laos (Arvis et al. 2010).
45

Figure 2.15 Study area and location of dry ports in Laos
Improvement of logistics system and transport connectivity would be the core activity tomaterialize the vision of being a land-linked country. Laos current development plan forecast a
7% growth of freight that reaches 32 million tons and 2.2 billion ton-Km by 2015 and focus ondevelopment of special economic zones already established in Boten, Bokeo and Savannakhet(MPI 2011). Thailand also has railway capacity enhancement plan that includes double tracking
to Nongkhai, track rehabilitation and development of inland container depots in Nongkhai and
Ubon Ratchathani near border with Laos (Mala, 2011). Laos thus can use these facilities as wellas the Lat Krabang ICD near Bangkok which is connected by railway to Laem Chabang port.
Laos national strategic logistics master plan (JICA 2011) has proposed to develop threeinternational logistics parks at Thanalaeng (Vientiane), Savannakhet and Luangnamtha and three
regional logistics parks at Luangparbang, Thakhek and Phakse (Champasak) which are shown in
Figure 2.15. Due to the importance of international trade, potential freight volume and transport
connectivity with Thailand as well as GMS four logistics centers namely Thanalaeng, Thakhek,
Savannakhet and Phakse are considered as cases in the current study. These four alternative
locations have potentials to serve international and transit as well as domestic freight. The salientfeatures of these logistics centers are shown in Table 2.3.

46

Table 2.3 Salient features of proposed dry ports in Laos
Dry ports
Thanalaeng

Freight volume (Tons) Design Area
2015
2025
Sq. m
426,500 1,413,060
295,000

Costs
Million US$
31.1

Thakhek

19,00079,00023,300

3.7

Savannakhet

36,000151,000

51,100

4.56

Phakse106,400

296,000

115,900

14.77

Functions and roles
Road, rail and waterway, import andexport to Thailand, limited transit toChina, consolidation, transshipment
and distribution
Road and waterway, import, export
and transit to/from Thailand andVietnam,consolidation,transshipment and distribution,
bridge to Thailand near completion
Road and waterway, import, export
and transit to/from Thailand andVietnam through GMS East-West
Corridor,consolidation,transshipment and distribution,
Road and waterway, import, andexport to/from Thailand, transit toCambodia,consolidation,transshipment and distribution,
Storageanddistributionofagricultural products
Source: JICA, 2011

Despite having logistics development plan, Laos is finding it difficult to develop these logistics
facilities. Prioritization of logistics facilities would help policy makers to take decision andmobilize resources according to the priority and gradually improve overall logistics system. It isalso intended to assess emissions as a result of development of dry port facility and resulting
modal shift of international freight between Laos and Thailand.
2.8

Chapter summary

The review revealed that there are not many adaptation studies covering transport sector in Asia.
This reinforces the need to look at sustainable transport development, climate change impacts
and development of adaptation strategies in Asian context.
In terms of mitigation, it is noted that many studies and strategies focus on urban and passenger
transport and not many studies covered freight transport in Asia. Therefore, there is a clear
indication that this area needs to be further researched. Considering different level of energy
efficiency of various transport modes –one option is to look at the potential of mode shift. As
there are 12 land-locked countries in Asia, one way to look at the problem is to study extensionof intermodal transport to inland area through development of dry ports which are ideallyconnected by railways as well as other modes of transport.
Chapter 3 further builds on this review and analyzes various methodological aspects and proposeand develop an integrated research framework and methodology that considers both adaptationand mitigation. Approaches such as MCDA, AHP, Goal Programming, Stated Preference, Mode
Choice Model, and CO2 Assessment are further elaborated in the context of the current research.
47

CHAPTER 3
RESEARCH FRAMEWORK AND METHODOLOGY
3.1

Introduction

This chapter outlines proposed framework and methodology for the research. In order to achieve
the objectives of the research, an integrated methodology that incorporates four analysis modules
are proposed. The methodology integrates assessment of climate change impacts, review of dry
ports development, location analysis of dry ports, mode choice analysis and emission
assessment. It also outlines the methodology proposed for primary data collection.
The integrated research framework enables to evaluate alternative location of dry ports andprioritize them according to the preference of stakeholders based on selected evaluation criteria.
It can then assess the potential modal shift through development of dry ports based on theoutcome of the stated preference survey and resulting reduction on emissions as a result of modal
shift.
Initially the framework to study climate change impacts and adaptation policies in Asia is
explained, followed by the Analytical Hierarchy Process (AHP) and AHP-Goal Programming(GP), development of mode choice model and bottom-up approach for emissions assessment.
3.2

Integrated methodology and analysis modules

In order to achieve the objectives of the research the proposed research framework andmethodology integrates four analysis modules: (1) Adaptation policy analysis; (2) Review of dry
port development and location analysis using the analytical hierarchy process (AHP) and AHPgoal programming (GP); (3) Stated preference techniques and mode choice model; and (4) CO2
emission assessment utilizing bottom-up approach and life cycle assessment. Figure 3.1 shows
the relation between the research objectives and proposed analysis modules.

48

Research Objective 1:
To assess policy makers
perspectives on impactsof climate change ontransport

Research Objective 2:
To review and analyze
development of dry
ports and location

P
R
I
M
A
R
Y
D
A
T
A

Research Objective 3:
To assess freight modal
shift
and
CO2
emissions

Module 1: Survey of policy
makers and assessment of
impacts and adaption measures

Module 2: Case studies of dry
port development, survey offreight forwarders, location
analysis

RESULTS

Module 3: Stated preference
survey and mode choice
model

Module 4: Assessment of
CO2 emissions, Life cycle
assessment

Conclusions and discussions
Figure 3.1 Relationship between research objectives and analysis modules
The methodological framework proposed for the study is shown in Figure 3.2. The integrated
framework for analysis incorporates analytic hierarchy process, goal programming, statedpreference techniques, discrete choice model, logit model and emission assessment throughbottom-up approach and life cycle assessment. Due to growing concerns of freight emissions andneed to reduce those, many countries are now introducing policy measures to promoteintermodal transport and modal shift including through the development of dry port. However, inorder to assist decision makers to make informed decisions, evaluation of such policy would benecessary. This integrated framework would help policy makers to understand the perception of
stakeholders in selecting appropriate location of dry ports to promote intermodal transport, as
well as to visualize what would be the potential modal shift and resulting emissions. This
framework would be very useful in applied research, as it can be applied to ‘real situation.’ The
current research proposes to evaluate the case of dry port development in Laos. The output of
preceding modules serves as input to the succeeding modules in a logical sequence. This type of
integrated framework incorporating various analytical modules have not been developed or usedearlier in transport sector. Further, the framework aims to incorporate both adaptation andmitigation aspect of transport. Also, the research proposes to use primary data collected fromgovernment decision makers, transport officials and freight forwarders who manage and deliver
freight transport services.
49

Climate Change and Transport: Assessment of
Freight Modal Shift and Emissions through Dry Port
Development

Intermodal Transport
Links

Services

Nodes

Module 2: Dry Port Location
Review of Dry Ports
Development in Asia

Data Survey 1:
Survey of
Policy Makers
Climate Change andAdaptation Policies

Data Survey 2:
DMs and FFs in
Lao Paired
comparisons

Location Problem

AHP & AHP-Goal
Programming
Model

Selection
Criteria
Model applicationin Laos

Location
Priority

Data Survey 3:FFs, Shippers in
Laos & Thailand

Module 3 : Mode Choice

Module 1: Climate
Change Impacts

SP
SurveyEstimation ofMode Choice
Model

Scenario
Analysis
Estimation of CO2
EmissionsLife Cycle
Assessment

Module 4: CO2 Assessment

Results and Discussion

Conclusions andFurther Research

Figure 3.2 Integrated methodological framework
The following section provides details of individual analysis modules.
3.3

Module 1: Adaptation policy analysis

Initially to familiarize with the sustainable transport development agenda a survey of policy
makers in Asian countries is undertaken. The survey is used to assess the understanding,awareness and the perception of policy makers on ongoing initiatives of climate change andtransport, its impacts on transport infrastructure, implementation arrangements and adaptation50

measures. For this purpose, a questionnaire is developed and a survey of transport policy makers
in Asia is conducted.
3.4

Module 2: Analysis of dry port development and location

This module incorporates review of dry port development to understand the issues and policies
related to dry port taking selected case studies from Asian countries. Identifying and selecting
potential location of dry ports is a challenging problem. The presence of multiple selection
conflicting criteria, many stakeholders with different interest makes the location problem a multicriteria and multi-stakeholder problem. Therefore, in analysis of dry ports location many factors
and criteria that are competing and conflicting need to be considered. Economic analysis tools
such as cost-benefit ratio, net present value (NPV), and internal rate of return (IRR) andenvironmental impact assessment (EIA) are commonly used to evaluate alternate locations andmake decisions. Multi-Criteria Decision Analysis (MCDA) can help to analyze and solve thelocation problem. AHP one of the MCDA methodologies can consider both quantitative andqualitative criteria and derive relative weights and prioritize alternate locations based on
evaluation criteria selected. To derive the local and global weights of the various criteria withrespect to each location pair-wise comparison of criteria and alternatives is done based on surveyof stakeholders that include government policy makers, transport service providers, chambers ofcommerce and industries, freight forwarders.
3.4.1

Case studies of dry port development in Asia

Countries in Asia are at different stages in the development of dry ports. In order to review thedevelopment of dry ports from environmental perspective case studies of dry ports from Asia arecollected and analyzed with respect to key financial, operational, environmental, regulatory andinstitutional aspects of their development and operation.
3.4.2

Identification of decision criteria and sub-criteria

The first task is to develop AHP model for multicriteria decision analysis (MCDA) consideringvarious factors and criteria that would be important in deciding the potential location of dry port.
Based on review of criteria and elements considered by earlier studies (Lee 1998, Yang et al.
2009, Tuzkaya et al. 2008, Guneri et al. 2009, Wang and Wei 2009, Onut et al. 2010,
Kunadhamraks and Hanaoka 2008) following criteria and sub criteria are considered for the AHP
location model. AHP assumes the criteria and sub-criteria should be independent of each other.
(i) Development and operation Costs: Cost of land for development, construction andoperation cost of dry port including transportation cost/processing cost of goods are considered.
The transportation cost includes potential cost at the port, dry port charges, transshipment andclearance costs at border 1 (if any).
(ii) Transportation time: Total transportation time from an origin to destination (O-D) such as
1

Ideally there should be no cost involved and process time required crossing the border- as objective of the dry ports is to enable
to clear and process the cargo at dry ports. But, situation is not ideal in Asia and many part of the world still goods are checked,
customs cleared and transshipment required at borders.

51seaport to the dry port, as well as time required for clearance and transshipment, border crossing,and reach the final destination are considered.
(iii) Environmental impacts: Environmental impacts including CO2 emissions from transport
operations, as well as potential environmental impacts from construction of dry ports are
considered.
(iv) Intermodal transport connectivity: Connectivity of dry ports to different modes oftransport such as road, railway, inland waterways and sea ports are considered. Rail is considered
as ideal connection from port to the dry port (Roso et al. 2009).
(v) Regional economic development: Proximity to market, consumers, manufacturing andprocessing area, prospects of economic development, freight demand, and government policies
related to development of special economic zones and free trade area that can attract foreign
direct investment for industries nearby dry ports location are considered.
3.4.3

AHP model development

The overall objective of the model is to rank and prioritize alternative dry port locations based on
the evaluation criteria. The evaluation criteria and sub-criteria for the analysis are selected basedon the review of the elements considered by earlier studies (Wang and Wei 2009, Wei et al. 2010,
Kapros et al. 2005, Önüt and Soner 2008, Onut and Saglam 2008, Tuzkaya et al. 2008, Aras et al.
2004, Mohajeri and Amin 2010, Ugboma et al. 2006, Guneri et al. 2009, Kahraman et al. 2003).
The final AHP model, criteria and sub criteria, is arrived after short listing relevant criteria
applicable to Laos situation and consultation with experts, transport professionals and officials in
Laos. The selected criteria and sub-criteria are shown in Table 3.1 and proposed model structurein Figure 3.3. In line with suggestion made in various literatures, five main criteria and 12 subcriteria are selected to limit numbers of questions for pair-wise comparisons and to increasechance of receiving more responses during survey. A table containing detail evaluation criteria
and sub-criteria used by other studies for location analysis is included in Appendix-I.
The study takes the case of dry port development in Laos. It considers four potential location
alternatives namely Thanalaeng, Thakhek, Savannakhet and Phakse for dry port development.
These locations represent real situation and are reflected in government five-year logistic plan
(JICA 2011) and were proposed for development during a regional meeting on dry ports (ESCAP
2010c).

52

Table 3.1 Criteria and sub-criteria for AHP analysis of dry port location

Prioritize and rank potential location ofdry ports

Goal

Criteria
1. Development and operationcosts
2. Time3. Intermodal transport
connectivity
4. Environmental impacts
5. Regional economic
development

Sub Criteria
1.1 Land acquisition costs
1.2 Construction costs
1.3 Transportation costs
2.1.Total transport time from seaport
3.1 Highways
3.2 Railways
3.3 Inland waterways
3.4 Seaports
4.1 Impacts from construction
4.2 Impacts from transport operation
5.1 Proximity to market, production centres
and consumers
5.2 Government polices to develop special
economic zone or free trade area nearby
5.3 Freight demand

Alternatives

Alt. 1. Thanalaeng
Alt. 2. Savannakhet
Alt. 3. Thakhek
Alt. 4. Phakse

Figure 3.3 AHP model
3.4.4

Weight derivation

Relative weights of decision criteria and sub-criteria are derived by making pair wisecomparison for all selected criteria at each level. The main objective of this process is to arrive atpriority of the alternative locations based on the criteria and sub-criteria selected. The survey
53

respondents are asked to provide verbal statements to assign values to paired comparison ofelements. The number of pairs in each level, n (n-1)/2, are compared, where n is the numbers ofelements in each level. Individual judgments are combined to arrive at the group judgment
typically by taking the geometric mean method (GMM) of the individual judgment (Forman andPeniwati 1998). The aggregate weight of individual judgments is calculated by the equation(3.1).

ai , j = (a1i , j * a 2 i , j * a 3i , j * a 4 i , j ........................ * a n i , j )1/ n(3.1)

Where,
ai , j - is aggregated judgment value for a pair-wise comparison,

a1i , j , a 2 i , j - are individual judgments of pair-wise comparison
The qualitative judgments expressed by survey respondents are converted into numerical values.
This is done by using Saaty’s pair wise comparison scale as shown in Table 3.2. For quantitative
criteria, the corresponding values are estimated based on the available data from survey and thevalue assigned from pair wise comparison and judgments are replaced.
Table 3.2 Saaty’s pair wise comparison scale
Numerical
values1
35
7
92,4,6,8

Verbal scale
Equally important
Slightly important
Important
Very important
Extremely importantIntermediate value

Explanation
Two elements contribute equally
Experience and judgment slightly favour one element
An element is favoured
An element is very dominant
An element is favoured by at least an order of magnitude
Used to express between two judgments

Source: Saaty 1980
A judgmental matrix is developed based on pair-wise comparison of priorities of criteria. Pair
wise comparison is done by comparing how important is “criteria 1” when compared with“criteria 2” for selecting location for development of dry ports and so on. The respondent isasked to indicate his value judgment/preference in a 1 to 9 point scale as shown in Table 3.2
while making pair wise comparison,
A judgmental matrix, A= (ai,j) such that ai,i=1, ai,j =1/ aj,i for all i, j≤n, is developed based onpair-wise comparison of priorities of criteria (Saaty 2003).

1A=

1 / a12

a12
1

...
...
1 / a1n 1 / a2 n... a1n... a2 n... ..
... 1

(3.2)

54

Where,n number of alternatives,ai,j represents pair-wise comparison rating between the element i and j of a criteria with respect
to goal being considered
Then priorities of the criteria is estimated by calculating the principal eigenvector W of thematrix A,

A *W = λmax *W(3.3)

Where, λmax is principle eigenvalue, when vector W is normalized, it becomes vector of priorities
of criteria of one level with respect to the upper level (Saaty 2003).

ai , j = ai ,k * a k , j∀i,j,k.

(3.4)

After analyzing group judgment, the weights are derived by using by eigenvector method (linear
algebra).

ai , j =wi
w j (for i, j,= 1, 2,......n)(3.5)

The consistency index (CI) is calculated using equation (6).

CI =(λ max − n)(n − 1)(3.6)

C. I should be below 0.2 for the survey to be accepted, C.I. zero indicates consistency in pairwise comparison, below 0.1 indicates logical consistency, if CI is more than 0.2 indicates lack ofconsistency and warrants repeat of survey.
Consistency is estimated by the Consistent Ratio (CR) and is inversely proportional toconsistency - the lower the figure, the higher the consistency of answers. In general, if the CR isless than or equal to 0.1, the consistency is considered very high. The ratio is equal to theconsistency index (CI) divided by the random index (RI). The Consistent Ratio (CR) is
calculated using equation (7), generally CR ≤ 0.1.

CR = CI
RI(3.7)

Where,
CR is consistency ratio55

CI is consistency index
RI is random index.
The measure of consistency enables analysis to review the judgments, modifying them toimprove the overall consistency.
In this case, the final comparison matrix is 5X5. Table 3.3 shows comparison matrix of criteria.
Table 3.3 Comparison matrix
TC

TT

ITC

EI

RD

weight

TC

1

a21

a31

a41

a51

w1

TT

1/a12

1

a32

a42

a52

w2

ITC

1/ a13

1/ a23

1

a43

a53

w3

EI

1/ a14

1/ a24

1/ a34

1

a54

w4

RD

1/ a15

1/ a25

1/ a35

1/a45

1

w5

Where ai,j are values judgment coefficients,
TC- Total development and operation costs
TT-Total transportation time
ITC-Intermodal transport connectivity
EI-Environmental impacts
RD- Regional economic development
w1, w2, w3, w4, w5 are corresponding derived weights of the five selected criteria
The pair-wise comparisons utilized in AHP facilitate the conveyance of the preferences of
respondents, and the measure of consistency enables analysis to return to the judgments,
modifying them here and there to improve the overall consistency.
The AHP model is analyzed using analysis software that also offers facilities to avoid rank
reversal through use of ideal mode and distributive mode.
3.4.5

Derivation of location priorities

The overall priorities are ranked for each alternative according to the score synthesized byweights and values of criteria. Final decision is made based on ranking for each alternative.
3.4.6

Goal programming and AHP-Goal programming model

3.4.6.1 Goal programming
Weighted Goal programming (GP) is used to solve the multi-objective decision problem. It
consists of decision variables and deviation variables. The AHP is used to determine the weights
of various objective/criteria. Equation (3.8) shows general goal programming formulation.
56

fi ( x) + d i− − d i+ = ai(for i= 1, 2..........n)(3.8)

Where d i− , d i+ >=0
d i− , d i+ are negative and positive deviation variables
x= decision variable
ai is the aspiration level of the target.

3.4.6.2 Combined AHP-GP model
AHP-GP model can help decision makers to make proper decisions satisfying overallrequirements of policy maker’s priority and can consider budget, freight demand and otherconstraints. AHP output weights are used as input to GP. The goal is to minimize deviations(sufficing) from achieving multi-objectives derived based on the criteria being considered forlocation analysis. The combined model utilizes policy maker’s perspectives/ preferences in
addition to the location attributes.
In goal programming, all objectives are assigned target levels for achievements and a relative
priority on achieving these levels. It treats these targets as goals to aspire for not as absolute
constraints. In preemptive case, goals at higher priority must be satisfied as far as possible before
lower priority goals are considered. While in non-preemptive case, different weights are assigned
to each goal turning the problem to a single objective optimization (Mendoza et al. 2008). The
main objective here is minimization of deviation from achieving the aspiration level of various
goals. The weighted GP’s objective is to find a solution that minimizes the weighted sum of goal
deviations as shown in equation 3.9. The overachievement and underachievement of goals are
undesirable.
It is important to develop location decision model that considers operating cost and budget andultimate justification is based on economic terms using the coefficient and output of the AHP
model makes combined AHP-GP model more robust. The model is applied to analyze four
alternative locations of dry ports in Laos.
G(m

MinZ = ∑∑ wg ,i d i + d i
g =1 i =1

−

+

)

(3.9)

n

s.t.∑ ai , j X j + d i− − d i+ = bi

(3.10)

j =1

Where,
wg,i- weight of goal g,ai,j -coefficient of decision variables (from AHP output)
Xj-decision variable, location of dry port
d+/- positive and negative deviational variables
bi target value or goal of a criteria
In the case study, as there are five main criteria used to evaluate the locations, these correspond57

to five goals which are reformulated as constraints by adding deviational variables.
The goal of development and operation costs can be expressed as,n∑a X + d − d = b
ij

j =1

−
C

j

+
C

(3.11)

C

Total transportation time goal,n∑a X + d − d
ij

j =1

−
TT

j

+
TT

= bTT

(3.12)

Goal for intermodal transport connectivity,(3.13)n∑ aij X j + dTR− − dTR+ = bTR
j =1Goal for environmental impacts,n∑a X + d
ij

j =1

j

−
EI

− d EI+ = bEI(3.14)

Goal of regional economic development,n∑a X + d
ij

j =1

j

−
RD

+
− d RD= bRD(3.15)

Other constraints relating to capacities of proposed dry ports, freight demand, cost ofdevelopment and budget available can be added.
For freight demand and capacity we have,4∑fX =Fi =1i(3.16)j

For costs and budget,
4∑C X = Bi =1i(3.17)j

For AHP weights,
4∑w X =Wi =1i(3.18)

jFinally as the location problem is a binary (0, 1) whether it is selected or not?
Xj= (0, 1)(3.19)

We can also introduced a constraint in the GP model to ensure at least one dry port site is
selected,58

X1+X2+X3+X4>=1(3.20)The deviational variables are non-negative,d i− , d i+ >=0(3.21)

Where,
Xj- is location of dry port
bC, bTT, bTR, bEI, bRD- right hand side coefficients corresponding to costs, transport time, transport
connectivity, environmental Impacts and regional development
Ci- Cost of dry port i,
B- Total budget available
fi- Freight demand of dry port i,
F- Total freight demand
L- Distance from port to dry port
E- Target value for CO2 emission
wi-corresponding AHP weights.
There are various approaches used to determine target value of different objective criteria (righthand side of the constraint in equation). Firouzabadi et al. (2008) suggested using largest partial
weights of intangible criteria. While, Badri et al. (2001) recommended to add the best two or
three coefficients of criteria. LINDO software can handle both preemptive and non-preemptive
optimization problem and it is used to solve the AHP-GP model.
The four alternatives dry port locations considered are: (i) Thanalaeng; (ii) Thakhek; (iii)
Savannakhet; and (iv) Phakse (see Figure 1.1). These are the real locations proposed by Laos fordevelopment. The mode shift model considers freight transport between seaport in Thailand to
dry ports in Laos. These four locations provide four possible routes for mode choice analysis andemission assessment which are: Laem Chabang Port-Thanalaeng; Laem Chabang Port-Thakhek;
Laem Chabang Port-Savannakhet; and Laem Chabang Port-Phakse. For mode choice analysis,
the O-D pair with highest ranking (priority) location of dry ports in Laos determined by AHP and
AHP-GP model based on survey feedback of government decision makers and freight forwarders
is to be used for stated preference (SP) survey and development of a mode choice model andassessment of CO2.
3.5

Module 3: Mode choice model

3.5.1

Model structure

The development of mode choice model involves selection of modes, mode attributes, utility
function and model estimation that includes estimation of parameters and mode shift. The
problem has two mode options truck and train.
3.5.2

Attributes

The attributes to be considered for mode choice are total transportation time, transportation cost59

(including dry port charge), and reliability (delay) of service for both truck and freight train.
3.5.3

Utility functions

The generalized utility function is shown in equation (3.22). The chances of selecting a mode
largely depend on the observed component of the utility.

Ui = Vi + εi

(3.22)

Where, U- Utility function
V- Systematic utility
ε -random component of utility
i is transport mode.
As transportation time, transportation cost and reliability of a mode are selected, the mode
specific utility functions for truck and rail modes can be expressed as linear function as
perceived by user n is shown in equation (3.3) and (3.4).

Utruck = Vtime + V cos t + Vrel + εtruck(3.23)

Urail = Vtime + V cos t + Vrel + εrail(3.24)

Thus the probability of choosing ‘rail’ instead of ‘road’ is the probability of that Urail is greaterthan Uroad , and is given by equation (3.25).

Pr ail = P(Urail > Utruck )(3.25)The probability of selecting the rail mode is given by equation (3.26).

P(rail ) =3.5.4

exp(Vrail )exp(Vrail ) + exp(Vtruck )(3.26)

Model estimation

Stated preference (SP) survey is conducted to seek response from freight forwarders andtransport service providers in Laos and Thailand. The SP presents hypothetical situation if dry
ports are developed, railway is connected, and service is available, frequency of freight train,transportation costs including charges for dry ports use. The survey also includes other questions
relating to policies, services that would be important for considering a mode shift. Providing map
based route information to users can induce route choice, similarly, provision of information on
freight route, transfer facilities, time, and costs could influence freight mode choice. Clean
Development Mechanism (CDM) recognizes “modal shift” as one of the approved methodology(UNFCCC 2010).

60Model estimation is done by using LIMDEP econometric software to estimate model parameters
including log likelihood ratio. After determining the attributes values, utility function of eachmode, the mode share is estimated using equation (3.26).
3.6

Module 4: Assessment of CO2 emissions

The assessment of CO2 emissions involves estimation of CO2 emissions from operation of
freight transport from seaport to dry port taking account of the potential modal shift from. It also
estimates life cycle CO2 emissions from dry port construction and transport infrastructure.
3.6.1

Emissions from operation

The CO2 emissions from operation of freight transport from the seaport to the dry port areassessed utilizing bottom-up approach. The mode shares estimated by the mode shift model are
utilized to calculate CO2 emissions from transport operations. The emission factors are derived
for Thailand (Chamroon 2011) as these factors are similar to Laos since the type of vehicles andtrain to be used are similar.
The emissions are estimated using the following equation (3.27):

E i , j = ∑ EFVi , j *VTKmi , j + ∑ EFTi , j * TTKmi , j(3.27)

Where,
E- Emissions
EFV= Emission factor for the vehicle for the fuel type,
EFT-emission factor for the train for fuel type
VTKm- total freight transported by vehicle in ton-km
TTKm- total freight transported by train in ton-km.
3.6.2

Life cycle assessment of construction

The life cycle emission assessment for the selected dry port location is done utilizing the result of
location analysis. Depending on the site selected, it involves estimating the quantity of dry port
construction and road or railway connection to the seaport. If Thanalaeng is selected it will
involve construction of dry port, road and railway sidings inside the dry port. However, forThakhek, Savannakhet and Phakse, in addition to the dry ports the railway connectivity to theseaport has to be constructed as well.
The quantities of main construction items such as earthworks, cement concrete for roads andcontainer yard, building with steel and concrete structure and railway construction with the dry
port are first estimated. The life cycle emission factor that incorporates from raw material
acquisition, construction process, use of equipments and disposal (from cradle to grave) are ofused. The product of construction quantity and life cycle emission factor per unit give the totallife cycle emissions. The life cycle emission is estimated using the following equation (3.28).

61

LC-CO2= ∑Qi*LCEFi(3.28)

Where,
LC-CO2 is life cycle CO2 emissions
Qi is quantity of construction items i,
LCEFi is life cycle emissions factors per unit of construction item i
i is construction items such as earthworks, cement concrete, types of buildings, railway line.
The life cycle assessment (LCA) evaluates construction related CO2 emission due toinfrastructure development. Construction quantities estimated by the feasibility study are used
(JICA, 2011). The life cycle emission factors for the construction are difficult to find in Asian
context. Instead, the life cycle emission factor from the Ecoinvent database is used (Ecoinvent,2007).
Assessment of emissions from potential modal shift and LCA of transport infrastructuredevelopment will used to determine net emissions and estimate time required to offset theemission from construction of the dry port and related infrastructure.
3.7

Scenario and elasticity analysis

Different likely scenarios are considered to assess the effect on modal share and resulting CO2
emissions. Elasticity analysis would be conducted to see the variation on modal shift andemissions due to variation in transport cost and time of freight transport. Some of the likely
scenarios that could be evaluated are:
(i)
(ii)
(iii)
(iv)
(v)
3.8

Variation in transportation cost of truck and train;
Variation in transportation time of truck and train;
Variation in cost and time of truck and train;
Evaluate resulting change in the mode shift of truck and train; andEvaluate resulting CO2 emissions.

Model limitations

Only international freight transport to and from Thailand is considered both bilateral andinternational export/import trade to third countries. It is assumed that the transportation of
distribution leg in the Laos from dry ports to consumers and production centres and to industry isdone by road transport and would be the same now and after the development of the dry ports.
Therefore, this distribution leg is not considered in the model. Growth of international freight isconsidered based on projected trade growth based on GDP growth in Laos.
Majority of the international freight travel occur in Thailand. It does not discuss how this isaccounted for Laos and Thailand. Emissions being global issue, overall emissions reduction
potential along the corridor are assessed.

62

3.9

Data collection and surveys

Four sets of primary data are collected for the research from policy makers, private sector freight
forwarders and reprehensive of commerce and industry. The first stage was a survey of policy
makers in Asia on climate change impacts on transport and adaptation policies. Secondly, asurvey on the judgment and evaluation of government decision makers, private sector freight
forwarders and transport operators for assessment of alternative dry port locations in Laos was
conducted. Thirdly, a stated preference survey of freight forwarders and multimodal transport
operators in Laos and Thailand was conducted to develop freight mode choice model between
truck and train. Fourthly, visits to dry ports in Asia were undertaken to collect data for casestudies of development of dry ports
The schedule, method, targeted respondents and areas of primary data collection are depicted in
the Table 3.4.
Table 3.4 Primary data collection schedule, method and area
S.
No.
1.

Data description

Schedule

MethodSurvey Area

Perception of climate change
impacts on transport andpolicies
Pair-wise comparison ofevaluation
criteria/subcriteria and dry ports
locations

June-July
2009

Email survey

AsianCountries

July-August
2011

Interview survey,
email survey andvisit to potential
locations

Laos

3.

Stated preference survey offreight mode choice between
truck and train

SeptemberNovember
2011

Thailand andLaos

4

Data collection for casestudied of dry ports

June
2010September
2011Interview
surveyand follow-up by
telephoneandemailsVisits to the dry
ports, interview anddiscussion
withofficials

2.

China, South
Korea,
Uzbekistan,
Bangladesh
and Nepal

Targeted
respondents
Transport policy
makers
Policymakers,freight forwarders
andrepresentative ofcommerceandindustries
Freight
forwardersandtransport
operators
Dry
port
developers
andoperators

In addition to the above mentioned structured primary data collection various interviews,
consultation and discussion were undertaken with the freight forwarder and government policy
makers in Laos and Thailand to understand the insight of freight logistics, international freighttransport and the prospects for introduction of freight rail service between Thailand and Laos.
Further, secondary data were also collected and used for the study. These includes collection of
secondary data relating to costs, time, distance of the route, freight volume, emission factors, andgovernment infrastructure development policies.
Further details on data collection and survey including the approach, questionnaires design, andselection of respondents for data collection survey and face-to-face interviews are included in
respective analysis Chapter 4, 5, 6 and 7.
63

3.10

Chapter summary

This chapter provided details of framework and methodology used for the research involving
four modules. The modules 1, 2 and 3 correspond to the research objectives 1, 2 and 3
respectively and module 4 corresponds to objective 3. Details of analytic hierarchy process, goal
programming and logit model is provided. This integrated framework would be very useful tools
for transport professional, policy and decision makers in order to make rational decisions
regarding the development of dry ports as well as reduction on emissions from freight transport.
It also introduced the methodology of primary data collection for the research.
The integrated methodology developed is applied in the Asian context. In developing adaptation
strategies the views of policy makers from Asia are considered. For location analysis, the case of
dry ports development in Laos is evaluated; and international freight movement between
Thailand-Laos is considered for modal shift with feedback of freight forwarders and emission
assessment. The next chapter discusses the application of module 1 to assess the impacts ofclimate change on transport.

64

CHAPTER 4
IMPACTS OF CLIMATE CHANGE ON TRANSPORT 2
4.1

Introduction

The recent frequent occurrence of extreme weather events in Asia provides some evidence ofincreased intensity and frequency of climate events. Asia is expected to experience rises intemperature, longer summer heat spells, more intense and more frequent precipitation, increased
extreme rainfall, a higher number of extreme tropical cyclones, and rises in sea levels. Transport
infrastructure and service are affected by these climate events. Increases in temperature andprecipitation, rises in sea levels, and storm surges significantly affect planning, design,
construction and maintenance, and operation of transport system. This chapter presents theregional climate predictions for Asia and the findings of the survey of policy makers on impact
of climate change and transport. It then assesses the impacts of climate change on transport andlist vulnerable transport infrastructure. Finally, adaptation strategies and measures to safeguard
transport infrastructure including dry port and possible ways of financing adaptation are outlined.
4.2

Regional climate predictions for Asia

The IPCC Fourth Assessment Report (Christensen et al. 2007) predicts warming is likely 3 to bewell above the global mean in Central Asia (3.70C), on the Tibetan Plateau (3.80C), and in
Northern Asia (4.30C); above the global mean in Eastern Asia (3.30C) and South Asia (3.30C);
and similar to the global mean in South-East Asia (2.50C). Precipitation in boreal winter regions
is highly likely to increase in Northern Asia and on the Tibetan Plateau, and also likely toincrease in Eastern Asia and the southern parts of South-East Asia. Precipitation in summer islikely to increase in Northern Asia, East Asia, South Asia, and most of South-East Asia, but islikely to decrease in Central Asia. It is very likely that heat waves and hot spells in summer will
be of longer duration, and these events will be more intense and more frequent in East Asia.
Fewer very cold days are highly likely in East Asia and South Asia. There is very likely to be anincrease in the frequency of intense precipitation events in parts of South Asia and in East Asia.
Extreme rainfall and winds associated with tropical cyclones are likely to increase in East Asia,
South-East Asia, and South Asia.
The rise in sea level is likely to be in the range of 18–59 cm depending on the scenarios
predicted. Rises in sea levels are likely to be average around the Indian Ocean and the northernand southern Pacific Ocean. The Indian Ocean and the North and South Pacific Islands are very
likely to warm during the century, but the warming is likely to be somewhat less than the global
annual mean. Annual rainfall is likely to increase in the northern Indian Ocean and in theequatorial Pacific. Significant increase in annual runoff of major Siberian Rivers, expansion of2

Part of this chapter was published as Regmi, M. B. and Hanaoka, S. (2011) A survey on impacts of climate change on roadtransport infrastructure and adaptation strategies in Asia, Journal of Environmental Economics and Policy Studies, (2011) 13:2141. The paper was the highest downloaded paper during June to December 2011. The paper is available from:(http://www.springerlink.com/content/g783546t53271847/)
3
The IPCC report uses standard terminology for the likelihood of occurrence: virtually certain>99% probability; very likely>90% probability; likely >66% probability; more likely than not >50% probability; about as likely as not 33–66% probability;
unlikely<33% probability; very unlikely <10% probability; exceptionally unlikely<1% probability.

65

deserts, more frequent and severe water crises, and increased rainfall intensity during thesummer monsoon and increase flood risk in the flood-prone areas in Asia are expected.
4.3

Survey of impacts of climate change on transport

A survey of climate change impacts on transport and adaptation in Asia was conducted during
June-July 2009 to assess: (i) the level of awareness of policy makers and general public; (ii) thelevel of response and coordination to climate events related emergencies; (iii) adequacy of
current design standards and practices; and (iv) adequacy of existing policies, institutionalarrangements and coordination. The finding of the survey is also used to assess the potential
impacts, identifying vulnerable transport infrastructure and planning adaptation strategies andmeasures.
4.3.1

Questionnaire development

A questionnaire consisting of 28 questions divided into four sections was developed. The four
sections included in the questionnaire are: (A) awareness of climate change and adaption
measures in transport sector; (B) information on emergency preparedness; (C) design standards
and practices; and (D) policy, guidelines, institution, coordination for implementation. The
questionnaire also included a section (E) on information about the respondents. A pre-test of thequestionnaire was done by sending it to the master and doctorate students undertaking researchin the area of transport for feedback and comments. The questionnaire was finalized
incorporating the comments and suggestions received during the pre-test. The survey
questionnaire is attached as Appendix-II.
4.3.2

Selection of respondents

Transport professionals working within transport ministries, departments and agencies from 30
Asian countries were selected for the survey based on the existing contact. Even though the
Pacific Island countries are potentially affected by the climate events such as the rise in sea level
they were not included in the survey simply because of lack of contacts.
The questionnaire was sent to 81 transport professionals by emails in 30 Asian countries. At least
two officials representing each country were requested to provide their opinion. Total 24
responses from 21 countries (total 30% response rate covering 70% of countries) representing all
four subregions 4 within Asia were received namely from: Azerbaijan; Bhutan; Cambodia; China;
India; Indonesia; Iran; Japan; Kazakhstan; Kyrgyzstan; Malaysia; Mongolia; Myanmar; Nepal;
Pakistan, South Korea; Singapore; Thailand; Turkey; Uzbekistan; and Vietnam.
4.3.3

Respondents details

Figure 4.1 shows the distribution of respondents by age, gender and geographical subregion. Itshows the majority of respondents were male (79%) and only 21% of the respondents werefemale representing all four subregions of Asia. In terms of age group, the age group 41-50 years
4

Four subregions of Asia classified by the United Nations are: Central and South-West Asia; North and North-East
Asia; South Asia; and South-East Asia.

66(42%) has highest number of respondents followed by 52-60 years group with 25%.

Male

15

Geogrphical distribution of respondents

FemaleNo of respondents

Numbers

Age and Gender of the Respondents

10
5
0

9
8
7
6
5
4
3
2
1
0
South-East Asia<30

31-40 41-50
Age group

51-60

60>

South Asia

North and North
Central andEast Asia
South+West Asia

Subregions

Figure 4.1 Age, gender and geographical distribution of respondents
Figure 4.2 shows the education level and experiences of the respondents. It shows most of the
respondents were with masters degree (62.5%) followed by bachelors degree (25%) and only
three respondents were with doctorate degree (12.5%). In terms of experience, majority of the
respondents were with more than 15 years of experiences (58%) followed with experience range
11-15 years (17%). The respondents having more than 10 years of experience were 75%.
Experience of the Respondents

Respondents Education

NumberNumber

16
14
12
10
8
6
4
2
0
Bachelor Master

PhD

16
14
12
10
8
6
4
2
0
0-5 yr

6-10 yr.
11-15 yr.
Experinece in Years

15 yr>

Figure 4.2 Education level and experiences of the respondents
The age group, education and level of experience of most of the respondents can reflect the highlevel of maturity and can be interpreted to reliability of the survey and response received.
4.3.4

Limitation of the survey

The survey has limitation in terms of total number responses received. Therefore, the findings
have some limitations. However, as most of the respondents were senior transport officials withmore than 10 years experience and some of the respondents mentioned that they had consulted
officials working in the area of environment and climate change while completing thequestionnaire, the responses can be considered reasonably acceptable to reflect current situationin Asia without much bias. However, caution should be taken in utilizing and interpreting the67

results.
All the survey responses were tabulated and summarized corresponding to each questions in fourmain sections after adjusting some outliers responses. However, we can see both similarities aswell as differences on the responses received which is solely by coincidence. The analysis andfindings of the survey would be helpful in assessing impacts, planning interventions andadaptation strategies to the climate change impacts at regional, subregional and country level.
4.3.5

Findings of the survey

The following section outlines the findings of the survey of policy makers on climate change
impacts on transport and adaptation. It assesses the level of awareness, institutionalarrangements, and coordination, existence of rules and design guidelines, and current practices ofincorporating climate change impacts on transport projects in Asia. It also includes additional
feedback provide by the respondents on transport and climate change
4.3.5.1

Awareness of climate change and adaptation

Figure 5.3 shows the different level of perception of awareness of policy makers (government
officials) and general public about the climate change, transport and environmental agenda. The
respondents were asked to rate the level of awareness on a five point Likert Scale (5, very high;4, high; 3, adequate; 2, low; 1, very low). As seen in Figure 4.3, the level of awareness of thegeneral public rated as low or very low is 75% while the level of awareness of policymakers
rated as low or very low is 38%. This difference may be a result of ongoing climate change
advocacy programs reaching government officials but not the general public. This clearly showsthat there is scope to improve the awareness of the general public and to further enhance theawareness levels of policymakers.
Indonesia and Japan mentioned that the level of awareness of policy makers and transport
officials was very high. Contrary to this Kazakhstan and Nepal indicated that the awareness level
was very low. Similarly, Bhutan and Japan indicated the very high level of awareness of generalpublic while Nepal and Thailand indicated as very low.
Very HighHigh

Adequate

Low

Very Low% low

Level of aw areness of general public
about environment and climate change

75

Level of aw areness of policy makers
about environment and climate change

38

0%

20%

40%

60%

80%

100%

Figure 4.3 Awareness levels of policy makers and general public
Despite numerous global efforts in tackling the issues of climate change, the levels of68

understanding and coordination have yet to be matched by those required The situations are
similar in the United States and the United Kingdom where there is still some scope to improveawareness in the transportation sector (Woollier 2003, DOT 2007; NRCNA 2008).
The respondents were also asked to rate 14 statements related to climate change and transport byusing a five-point Likert scale (1, strongly disagree; 2, disagree; 3 neutral; 4, agree; 5, strongly
agree). Figure 4.4 shows the response received and confirm the broad beliefs on climate change
and the potential impacts on transport infrastructure. Some of the rankings highlight theimportance of particular aspects of impacts and adaptation. Most of the respondents (79%)
strongly disagreed or disagreed with the statement “Our region will not be much affected byclimate change,” indicating that climate change is a cause of concern in Asia.
All but one respondent (96%) indicated the need for awareness programs on transport andclimate change. The survey demonstrated the need for environmental and climate change
awareness programs targeting all stakeholders including policymakers, project officers, andmanagers as well as the general public involved in planning, design, construction, operation, andmaintenance of transport.
Strongly Disagree

Disagree

10%40%

NeutralAgree

Strongly Agree

Our region w ill not be much affected by climate change
The climate change is a cause of concern
Climate events w ill affect transport and operation
Coastal infrastructure are vulnerable to climate change
Design standards and criteria may need to be revised
It w ill be costly to adopt higher design standards
Bridges are prone to damage
Possibility of overflow of side and cross drains
Heavy snow w ill disrupt transport and traffic
Pavements deterioration w ill be faster by high temperature
More traffic disruption due to land slides
Poor driving condition due to fog, storm
Strong w inds may damage road signs
It w ill be costly to repair infrastructure
0%

20%

30%

50%

60%

70%

80%

90% 100%

Figure 4.4 Response to transport and climate change related statements
4.3.5.2

Emergency preparedness

Transport plays a vital role in mobilizing immediate help and relief to the area affected by theextreme climate events. All respondents indicated that extreme climate events had occurred
within the past three years. Figure 4.5 shows the level of response and relief coordination of
government agencies during emergencies. The respondents indicated that the coordination and69

response to emergencies have been adequate. However, it also shows that there is some scope of
improvement as indicated by the combined low and very low score of 38% for coordination and
33% for relief operation. All respondents except Kazakhstan and South Korea indicated that
there is some scope of improvement in the way the help and relief operation are managed.
Very HighHigh

Adequate

Low

Very Low

Coordination betw een variousorganizations

% low
38

Response from the relief andtransport agencies in relief
operations
0%

33
20%

40%

60%

80%

100%

Figure 4.5 Level of response and coordination during emergencies
Respondents from Azerbaijan, China, Indonesia, Iran, Japan, Kyrgyzstan, Mongolia, Myanmar,
Singapore, Turkey, South Korea and Uzbekistan indicated that some policy initiatives andimprovement in dealing with emergency preparedness had occurred after recent extreme climate
events. Furthermore, the survey clearly showed the scope to improve coordination among
various relief and transport agencies dealing with evacuation planning and emergency relief
operations. Transport infrastructure including roads along important routes would require more
frequent inspection and monitoring of condition to ensure immediate access to plan and provide
assistance.
4.3.5.3

Design standards and practices

Figure 4.6 shows the cumulative responses to the fourteen design standards and practice related
statements, and clearly demonstrate that rain and flood related damages is a major cause ofconcerns in Asia. The low ranking of the statements related to coastal roads could be because thePacific island countries were not included in the survey. Similarly, the low rating of snow
impact-related statements could be due to less response received from countries experiencing
severe cold climates.

70

Relocation of coastal road to higher place
Use stiffer bitumen in pavement to safeguard from hightemperature
Use thick and strong pavement to safeguard against snow
and frequent icing-thawing
Provide adequate slope protection works
Increase capacity and size of culverts and cross drainage
Provide additional protection to coastal roads
Provide adequate river protection works
Consider increasing waterway and protection works tosafeguard bridges
Place sufficient warning and information signs
Raise height of embankment in flood plains
Increase clearance above high flood level for bridges
Estimate design flood and storm water taking account ofpredicted climate
Increase capacity of side drains
Ensure effective drainage of surface water from pavement
0%

10%

20%

30%

40%

50%

60%

70%

Figure 4.6 Response to design standards and practice related statements
Figure 4.7 shows the response to design and policy related questions, and clearly indicates theneed to consider climate change impacts in planning and designing transport infrastructure, theneed to review the existing design standards, and the need for clear policy guidelines to consider
climate impacts. The survey also indicated the need to review design standards in relation toforecasting design discharge, freeboard, height of embankments, and additional protection
measures necessary for critical components of transport infrastructure such as drainages, bridges,
culverts, pavements, coastal roads, and slopes. However, Cambodia and China indicated there isno need to review or revise the design standards to consider the climate change impacts. Further,
Cambodia, India and South Korea indicated that it may not be appropriate to revise design flood
estimation methods contrary to other response. Adopting new design standards is relatively easy
at the planning stage. Many respondents have suggested streamlining construction guidelines andpractices taking account of climate events. In addition, there will be subregional variations inscale and type of impact depending on location and topography. Therefore, different andappropriate adaptation policies, strategies, and measures need to be taken. Depending on theseverity of climate impacts, the frequency of maintenance activities may have to be increased.
Regular clearing the drains, vegetation, more frequent inspection of road signs and steel bridges
for corrosion will be required. Installment of additional warning information boards and signs,
strengthening of coastal protection would help operation.
As indicated by the survey, in many cases it may be beneficial to review the design life ofvarious components of the transport infrastructure. There are ample studies and examples ofadaptation measures applied mostly in developed countries. While applying these examples in an
Asian context technical and economic viability as well as life-cycle costing should be evaluated71for the proposed design and adaptation measures depending on the capability and affordability of
the country. Differing from the general view Cambodia, China, Japan, Nepal and Uzbekistan
viewed that adopting higher standards may not be economical in long run because of high initial
cost.
Yes

No

Adopting higher design standards may cost more
initially but may be economical in long run
Need to consider climate change in planning anddesigning transport infrastructure
Are there existing clear guidelines to consider
impacts of climate change

Need to revise design flood estimation methods

Need to review design standards for transport
infrastructure
0%

20%

40%

60%

80%

100%

Figure 4.7 Response to design and practice questions
4.3.5.4

Policies, institutions and coordination

Figure 4.8 shows the response to questions related to policy, institutions and coordinated. The
majority of respondents indicated that there are no existing laws, rules and guidelines to assess
environmental and climate change impacts. Respondents from Bhutan, India, Indonesia, Iran,
Kyrgyzstan, Mongolia, Nepal, South Korea, Thailand, and Turkey indicated that there areexisting laws, rules and guidelines. However, most of the laws, policies, and guidelines listed
were related to the environment, global warming, and air pollution and very few were related totransport and climate change. Most of the respondent favoured extension of the existing transportand road sector environmental impact assessment guidelines to include the climate change andadaptation issues.
The environmental impact assessment (EIA) process is well recognized and followed in Asia.
The EIA process includes assessment of potential environmental impacts, planning,
implementing and monitoring mitigation measures during construction and operation. In the
beginning the environmental guidelines (United Nations 2002, ADB 2003) could beappropriately extended and revised to take account of risk and uncertainty of climate change. The
guidelines would be useful in incorporating the effect of predicted climate events into project
design and enhancing the understanding of climate change (Lemmen and Warren 2004). It would72

be easier to expand these environmental guidelines rather than developing new guidelines, which
may take long time. There are some initiatives by donors to introduce guidelines on climatechange and adaptation but they are general and not specific to the transport and road transport
sector. Therefore, as indicate by the survey, there is a pressing need to develop guidelines forclimate change impact assessment in the transport sector. Respondents indicated that there wereongoing adaptation projects in the transport sector in China, Indonesia, Mongolia, Myanmar,
South Korea and Turkey.
Yes

No

Existing laws and rules to assess environmental
and climate change impacts
Need of awareness programme for policy
makers in environmental and climate change
adaptation
T ransport, climate change and adaptation
related projects in being implemented
Useful to extend EIA guidelines to cover
climate change
0%

20%

40%

60%

80%

100%

Figure 4.8 Response to policy and institutions related questions
Most of the respondents (83%) indicated the existence of a central level coordination body intheir country responsible for environment and climate change and 61% of the respondents
indicated the existence of a coordinating unit or division within the line ministries and road/highway/railway department. Figure 4.9 shows the response to questions related to coordinationand level of implementation of existing environmental policies, rules and guidelines. The results
clearly indicate the need for greater collaboration and effective implementation of environmental
and climate change policies and guidelines. Nepal and Thailand indicated the application andimplementation of existing environmental, climate change and adaptation guidelines as very
poor.

73

Very HighHigh

Adequate

Low

Very Low% low

Use of existing environmental andclimate change rules, polices
guidelines

46

Coordination betw een variousorganizations

38
0%

20%

40%

60%

80% 100%

Figure 4.9 Coordination and policy implementation
The survey also revealed the need to establish units, divisions or branches to be responsible for
dealing with climate change issues within line ministries and road/highway/railway agencies. In
order to improve coordination among various agencies, these organizational units should be
strengthened so that they could effectively advocate, initiate and implement climate change
policies. These units need to be adequately staffed with trained professionals in assessment ofclimate change impacts and implementation of adaptation measures. UNFCCC has recognized
the capacity building needs for developing countries and countries with economies in transition.
The impacts of climate change could be widespread as well as localized so that coordination at
central, regional and local level is essential in planning and implementation of adaptation
measures. Structural limitations of organizational system and functions of bureaucracy areusually found in Asia. Because climate change is multidisciplinary issues, coordination among
various institutes and capacity building of staff are essential. The Climate Cell Centre in
Bangladesh and the Office of Climate Change in the United Kingdom are examples of
institutions established for coordination of climate change policy at the national level (DOT2007).
4.3.5.5

Additional feedback from the respondents

The survey also included questions seeking respondent’s suggestions for making transport
infrastructure safe to withstand the impacts of climate change and what should be done tosafeguard transport infrastructure from impacts of climate change. Some of the notablesuggestions included the need to:
(a)
(b)
(c)
(d)
(e)

Integrate impacts of climate change in the present planning and design;
Organize workshops, trainings and seminars to increase understandings andawareness of politicians, policy makers and general public;
Update and revise construction and drainage standards, guidelines and code ofpractices;Strengthen EIA process to take account of climate change;
Utilize available technology to predict weather more accurately and share/provide
timely information to the designer and planners;
74

(f)
(g)
(h)
(i)
(j)
(k)
(l)

Ensure adequate periodic supervision of transport infrastructure;
Avoid cost cutting measures however evaluate technical and economic viability as
well as life-cycle costing of the proposed design;
Undertake a detailed survey of impacts of climate change on transport;
Incorporate climate proofing and risk assessment while developing national plans;
Increase investment for development and maintenance of transport infrastructure;
Plan adaptation measures on the capability and affordability of the country; andEnsure good cooperation among all stakeholders and people in the society.

The respondents also offered suggestions to utilize alternate fuels and energy efficient engines toreduce emissions, and encourage modal shift to reduce pollution. They also mentioned that it isdifficult to plan solutions during emergencies therefore provision of information on climate
events and potential effects to the designer, implementing agencies, managers and executing
agencies in some rational ways becomes very critical. Further, good cooperation among all
stakeholders is essential in planning and implementation of adaptation measures.
4.3.5.6

Summary of the findings

There is much focus on mitigation not many initiatives are in areas of adaptation. It was clearthat lack of awareness at all levels of the government from policy making to project
implementation and general public. Also, the need for strategic direction and guidelines, as 50%
responded mentioned those, even use and implementation of existing rules and guidelines was
not evident. Therefore, implementation of adaption measures can be considered more of policy
and institutional issues. Based on the findings of the survey, the following points are considered
important to safeguard transport infrastructure in Asia:
(i)
(ii)
(iii)
(iv)
(v)
(vi)
(vii)

Advocate and create a greater level of awareness in the general public
Further enhance awareness among policymakers and managers
Initiate polices and extend EIA guidelines to include climate change impacts intoplanning processes
Review design standards and practices with consideration of life-cycle cost andabsorptive capacities of countries
Establish institutions and organization units responsible for climate impacts in thetransport sector and enhance coordination among various stakeholders
Plan and implement capacity-building programs for government officials
Mobilize additional resources through internal and external sources.

It can be argued that the issues of climate change have not been addressed adequately in Asia. It
can be further argued that the adaptation is overshadowed by mitigation which is getting muchprominence in the global and national agenda. As the climate change is evident adaptation
measures are needed to safeguard existing infrastructures as well as developing new transport
infrastructure. Infrastructure are being developed and maintained – but the question is how can
we address the likely impacts of extreme climate events more effectively? Therefore, there isstrong need to incorporate climate impacts and adaptation into practice. It is difficult to quantify
climate impacts as they are associated with risk, vulnerability and uncertainty. So risk assessment
tools are necessary to assess the likely impacts and their occurrence. Further, there is subregional
75

variation of climate events within Asia, for this reason, the adaption strategies and measure
would be different for different geographical areas. The following section assess the impacts andlist vulnerable transport infrastructure and related design parameters.
4.4

Assessment of impacts of climate change on transport

The climate prediction is not uniform for all parts of Asia therefore the scale of impacts ontransport infrastructure depends on the severity of climate events and the local topography,
terrain, and natural conditions. In terms of impacts assessment also the mitigation is measurable
in terms of emissions while adaptation cannot be measured. Therefore, subjective assessment has
to be made based on past experience and projected climate. In many instances it may not be
possible to quantify the impacts, and qualitative assessment has to be used to express the degreeof impact (ADB 1996).
The transport systems in South and South-East Asia are likely to be subjected to high-intensity
rain and hot weather events, those in Northern Asia and on the Tibetan Plateau are likely to beaffected by increased winter precipitation, and those on the islands and in coastal areas aroundthe Indian and Pacific Oceans will be affected by rise in sea levels. In particular, the coastal areasof Bangladesh, the Maldives, Pacific islands, and Vietnam are highly vulnerable to rises in sea
levels.
The increases in temperature, rain, and flood, frequent freeze–thaw phenomena, storm surges,
and a rise in sea level will affect transport infrastructure and operations. Specific impacts ofclimate change on transport include thermal expansion of bridge joints, the liquidation of asphalt
pavements and increased maintenance of pavement due to high temperatures, overflow of sidedrains and cross drainage works, submersion of bridges during flooding, and inundation ofcoastal roads due to rise in sea level. Sometimes operation of transport system can face closuresdue to landslides and mudslides of slopes.
Some of the secondary impacts of climate events are traffic disruption due to flood, heavy snow
and rains, difficult driving conditions, and the postponement of travel during such events. The
slow driving speeds required under extreme conditions reduce the severity of accidents but theprobability of accidents could increase due to slippery surfaces. Table 4.1 lists the climate events,
vulnerable transport infrastructure, design parameters and potential impacts.
Table 4.1 Vulnerable infrastructure, design parameters and potential impacts
Climate event
Temperature

Vulnerable infrastructure and design parameters
Pavement: selection and use of type of stiff bitumen towithstand heat in summer, soft and workable bitumen
with solvent in winter, control of soil moisture andmaintenance planning
Steel bridges and structures: selection of material,
provision of expansion joints, corrosion protection
Rail tracks: heat resistance material, rail track joints,
expansion joints
Sea ports, river ports and harbours: selection of heat
resistant materials for platforms, design of sheds

76

Potential impacts
Extended warm weather can cause
pavement deterioration due toliquidation of bitumen, heating andthermal expansion of bridges,
railway tracks and buckling of jointsof steel structure.
Low temperature can affect transport
operations;operation
andmaintenance costs are likely toincrease for additional snow and ice

Airports: Pavement material, snow and ice removal plan,
Rainfall

Bridges and culverts: flood estimation, return period,
design discharge, high flood level, clearance above highflood level, length of waterway, design load, wind load,foundation, river and bank protection, corrosion
protection
Drains: discharge estimation, size and shape of drain,
drain slope
Mountainous road and rail: subsurface drains, catchdrains,Slopes: slope protection and stabilization
Pavement: increase surface camber for quick removal of
surface water, frequency of maintenance, design of baseand subbase, and material selection
Airport: Drainage capacity, flood barrier

Stormsandstorm surges

Drains and cross drains: capacity enhancement,
Bridges and foundation: river bank protection,foundation, high flood level, frequency and intensity ofrains for design
Road and rail embankment: increase height, protection
Traffic and information signs: wind load, structuraldesign, foundation, corrosion protection
Sea ports, river ports and harbours: design for storm andsurge action
Water transport: Free board and overhead clearance,
dredging, flood protection at sea entrance
Airport: Wind direction, airport runway alignment
Coastal road and rail: protection wall, additional
warning signs, realignment of road and rail sections tohigher areas, edge strengthening
Sea ports, river ports and harbours: height of platform,
protection work

Sea level riseremoval as well as additional costs ofsalts to be used for snow melting.
Increased intensity of summer andwinter precipitation would create
floods,affectdrainage,road
pavement, airport runways, driving
condition and visibility, affectbridges and culverts waterways andclearance, damage bridges andculverts foundation due to scouring,affect road, rail, airport, ports andharbours, water transport channels,
damage bridges foundation due toscoring.
Rainfall can trigger landslides andmudslides in mountainous area andcan blocks transport system.
Rainfall and winds associated withstorm/cyclone can create flooding,inundation of embankments, andaffect roads, rail and airports andwater transport.
Disrupt traffic safety and emergency
evacuation operations, affect trafficboards and information signs.

Rise in sea level will affect coastalroads, railways, port and harbour,
airport near coastal area, marinetransport in the affected areas., may
be need to realign or abandon thetransport system in affected areas.

A closer look at the Table 4.1 indicates that the rainfall, storm and storm surges are mostdestructive climate events affecting most infrastructure of the transport system. Therefore,
appropriate consideration to the corresponding design parameters has to be given while planning,
designing and maintenance of the transportation system. This would increase their serviceability
and life.
The following section discusses adaptation strategies and measures required to safeguard
transport infrastructure from the potential impacts of climate change.
4.5

Adaptation strategies

Two types of adaptation strategies would be required to safeguard transport infrastructure. Firstly
to address the vulnerability and risk of damage of existing infrastructure and secondly planning,
designing and developing new infrastructure taking into account of likely impacts of climatechange. In order to achieve those strategic and policy level decision and action would be
required. Once the strategic policy decision are made on how to respond and intervene to the77climate events, then the different level organizational unit and project should implement those.
The following can serve as a check list of actions:
(i)
(ii)
(iii)
(iv)
(v)

Strategic policy decisions in response to likely climate events and impacts;
Raise awareness of climate events and impacts at all level in the organization, as wellas general public;
Make rational decision based on design review, life-cycle costing of planned
measures;
Create institutions, if necessary, to ensure effective implementation and coordination;
Commission specific studies to assess impacts to the vulnerable infrastructure andrisky infrastructure.

Different types of impacts would need different adaptation strategies and measures forovercoming the impacts of climate change on vulnerable infrastructure components. OECD hasmodelled that each £ 1 spent on climate change adaptation delivers four times its values in termsof potential damage avoided (de Bruin et al. 2009).
The lack of polices and guidelines and where the policies and guidelines were existing lack ofimplementation was evident from the survey. Therefore, while developing adaption strategies,
every aspect of development and operation of transport system, such as planning, design,
construction, operation, and maintenance, need to be considered. Many projects and initiatives
have targets that seek to reduce climate-change-induced risk and vulnerability. Because forecasts
are uncertain, we need to use a risk-assessment approach for adaptation. In most cases, risk isassessed as low, medium, high, or very high.
Table 4.2 shows the adaptation options, strategies, and policy measures for the transport sector.
There is a strong need to initiate detail climate impact assessments and adaptation studies togenerate new knowledge and provide reference and guidelines for future studies.
Table 4.2 Adaptation options and policy framework
Options/strategy
Realignment/relocation;
designstandards
andplanning for transport andother infrastructure to copewith warming and drainage

Policy frameworks
Integrating climate change
consideration into nationaltransport policy; investment in
Research and Development
for special situations, e.g.
permafrost areas

Constrains
Financialandtechnological barriers;
availability of lessvulnerable routes

Opportunities
Improved
technologies
andintegration with key
sectors (e.g. energy)

Source: Adapted from IPCC (2007)
Figure 5.10 shows a conceptual framework of the adaptation process. The process starts with theprediction of climate events and then assessment of the likely impacts using risk analysis andimpact-assessment guidelines. Then an appropriate response is planned and evaluated using lifecycle assessment. If the cost is feasible, then it passes to design, implementation, monitoring, andevaluation processes. The adaptation process within the shaded area of Figure 4.10 is actually aniterative process involving planning responses, life-cycle costing, design, implementation,
construction, monitoring, and evaluation. The final objective of the adaptation process is to havesustainable transport infrastructure. The whole process is supported by adaptation policy andstrategy, capacity building, and coordination.
78

Climate
Predictions
Risk
Analysis

ClimateEventsDesign
Review

Construction
Materials
NO

ImpactAssessment
Guidelines

Existing
Management
Practices

Awareness

Impacts
Assessment

Planning
Response

Life cycle
costing

DesignOK

Adaptation policy,
strategy

Implementation,
Construction

Monitoring
Evaluation

Sustainable
Transport
Infrastructure

Financing

Capacity Building, Coordination

Source: Adapted from Smit and Pilifosova, 2001
Figure 4.10 Conceptual framework of adaptation process

794.5.1Development and implementation of adaptation strategy

It is clear that the climate change impacts affect all stage of development planning, design,
construction, operation and maintenance of transport infrastructure and systems. Owing to thefact it is difficult to measure the impacts risk analysis based assessment should be done based on
the past experience. Further, a paradigm shift in strategic planning is essential in order to focus
on adaption and not be carried away by too much focus and attention on mitigation. Coordination
among different sector and level of administration is essential. It needs some lead time to plan
adaptation measures. The focus should not be only on physical infrastructure but also policies,
guidelines and by-laws can also help the adaptation process. One thing is clear while investment
in mitigation leads to global benefits, in case of adaptation the investment is local and thebenefits are also local as well.
Strategic environmental assessment (SEA) and environmental impact assessment (EIA) can help
in developing adaptation strategies and its implementation. Firstly, the scope of SEA and EIA
should be extended to cover climate change impacts. Adaptation measure to the impacts ofclimate change for infrastructure should be effective, efficient, equitable and evidence based(DEFRA 2011). Strategic decision and policies are required with respect to planning and design
such as how to incorporate risk factor in design, and considering life cycle costing forsafeguarding vulnerable infrastructure or planning new infrastructure. Once the strategic decision
are made these needs to be implemented and followed through at all levels in the institutions
such as at the policy, prorgamme, planning and design and project level implementation that
actually implements decision relating to construction and maintenance activities.

SEA

PolicyStrategic decision, policies, how to undertake SEA,
EIA, institute, coordination

Programme

LCA, design review, focus on vulnerable and high risk
infrastructure, funding

Planning
DesignEIA

Follow SEA, decisions, policy direction, costing,budgeting, plan and design

andProject level
Implementation

Conduct project level EIA, extend scope to include
climate change impacts, implementation

Figure 4.11 SEA and EIA policy framework
Figure 4.11 shows SEA and EIA policy framework. The following section further elaborates the
key elements adaption strategy that includes: (i) Advocacy and awareness of climate change
impacts; (ii) Strategic environmental assessment (SEA) and environmental impact assessment(EIA) guidelines for mainstreaming adaptation; (iii) Planning and designing of adaptation
measures; (iv) Life cycle costing; and (v) Institutional set up and coordination.

80

(i)

Advocacy and awareness of climate change impacts

Despite numerous global research and efforts in tackling the issues of climate change, the levelof understanding and coordination has yet to be matched with the requirement. In majority ofdeveloping Asian countries greater awareness among all stakeholders is essential. The awarenessinitiative should target all professional, policy makers, technical and politicians and private
sector consultants and contractors working in the transport sector. Asia needs to learn fromexperience of the other region. One of the important aspects of adaptation is to streamlining
responses to climate change policy in development planning.
(ii)

Strategic environmental assessment (SEA) and EIA guidelines

The environmental impact assessment process is well recognized and followed in Asia while
designing and implementing a project. The current practice is to assess the potential
environmental impacts of projects and mitigate and monitor the identified impacts during
construction and operation. This impact assessment and adaption process should also take into
account the risks; uncertainty and vulnerability of climate change and incorporate the effect ofpredicted climate events into project design. Impacts quantification involves expressing the
expected magnitude of each impact in terms of appropriate quantitative physical units. Although
there are some initiatives by donors to introduce guidelines on climate change and adaptationthey are general and not sector specific. It is felt that there is a need to have comprehensive
adaptation guidelines for the transport sector. As transport infrastructure needs very highinvestment – a thorough analysis following a prescribed/suggested process would ensure ‘fit for
purpose’ for intended life time. Therefore, the existing SEA/EIA guidelines need to be extended
to cover climate change considerations and adaptation.
(iii)

Planning and designing of adaptation measures

Incorporating new standards is relatively easy while planning new infrastructure. The only issue
would be to look at cost implication. There would be very little additional investment toincorporate design to adapt to climate changes. In many cases it is economically feasible todesign infrastructure components such as bridges, drainage, slope protection walls- considering
impacts of climate change and related design parameters. It may be beneficial to review thedesign life of various components of the transport infrastructure. In some cases, current design
standards may not be sufficient to accommodate climate change and there is the need to develop
new design standards to address future climate conditions. Therefore, it may be a right time toinitiate debate on the review of design parameters in Asia. Projects in highly vulnerable locations
should be built with higher standards.
It is also necessary plan and design maintenance of transport infrastructure considering theclimate events. It may include the increase the frequency of inspection and periodic maintenanceof vulnerable infrastructure such as pavement, drains, expansion joints, bearings, foundations,and structure of steel bridges, coastal infrastructure. Further selection of suitable construction
material such as bitumen, still, porous material for drains, also helps to withstand the impacts.

81

(iv)

Life-cycle costing

Adaptation can add costs, but not adapting can be more costly. One adaptation strategy is tomake infrastructure more robust against the economic cost of failure. Costing is a key factor in
deciding adaptation measures. How safe and strong should the infrastructure really be and at
what cost? Therefore, it is clear that the benefits of planning adaptation and maintenance well inadvance are greater. The design of adaptation progamme must be based on comparison of cost
avoided with costs of adaptation. Appropriate consideration of potential weather events inplanning, designing and maintenance of transportation system would increase their serviceability
and life.
(v)

Institutional set up and coordination

It may be necessary to establish institutions and organization units responsible for climate
impacts in the transport sector and enhance coordination among various stakeholders. As theimpacts of climate change are widespread proper coordination and planning of adaptation
measures are essential. The adaption measures are site specific and localized coordination andcollaboration is essential with central, regional and local agencies are required to implement
adaptation measures. The region’s developing countries needs qualified professionals. Planningand implementation of capacity-building programs for government officials and professionals
would help in assessing climate change impacts and implementation adaptation strategies.
Further, as transportation system is vital for evacuation planning and emergency response, more
frequent monitoring of infrastructure condition during these events would be required. The
transport providers should also be integrated to the emergency response team and should receive
advance weather warnings so as predict potential failure and plan appropriate response tosafeguard the infrastructure, warn public to stay away from the road as well as to facilitateevacuation and emergency response.
4.5.2

Financing adaptation

Many survey respondents have sought technical and financial support to initiate adaptation andcapacity-building projects in the transport sector in Asia. Under the framework of the UNFCCC
and the Kyoto Protocol funding support for developing countries, least developed countries andcountries with economies in transition are to be made available through the Global Environment
Facility (GEF), the Special Climate Change Fund (SCCF), the Least Developed Country Fund(LDCF) and the Adaptation Fund (AF). However, there are very few adaptation projects intransport sector within the Clean Development Mechanism (CDM) and GEF (Wright and Fulton2005). Since 1999, the GEF has financed 37 transport sector projects with total GEF support of
US$ 201 million. Although, the GEF has 7 transport projects covering 32 cities, most of the
project focus on GHG emissions. Not a single project concerns adaptation measures because
GEF projects need to demonstrate CO2 reduction potential (GEF 2009). Many of these projects
focus on sustainable transport, new fuels, and public transport and not a single project relates totransport infrastructure. National Adaptation Programme of Actions (NAPA) does not even classtransport as a sector. Transport is grouped within infrastructure sector and sometimes fuel relatedtransport projects are grouped within energy sector. Countries should look at the ways to initiate82

more transport projects under CDM. The Asian Development Bank has recently establishedclimate change fund. Project proponents and countries may approach international financing
institutions and bilateral donors to seek technical and financial resources for planning andimplementation of climate change adaptation measures on transport. Adapting to climate changetakes time and additional financial and human resources are required to implement adaptation
strategies. There has been long debate on financing climate change initiatives- the developed
nations need to fulfill their commitments by providing financial and technical support to thedeveloping countries.
4.6

Adaptation strategies for dry port development

The adaptation strategy and framework outlined is section 4.5 is now applied to a case of dry
port development. Sustainability and safeguarding dry port infrastructure from impact of climatechange is very important as they are an integral part of an intermodal transport system. First andforemost information related to climate predictions in the area vicinity of the proposed locationneeds to be collected. The probability of occurrence of these climate events need to beconsidered in planning, design and construction of dry ports. The identification of structurallysound and safe location is also a challenge. Once the site is finalized then the design process
starts considering the freight volume and transport modes considered. As the connectivity to theseaports from dry port is important, the overall condition and likely impacts of climate events on
the transport infrastructure need to be assessed as well giving detail attention to the vulnerable
location and infrastructure sections. Transport infrastructure includes roads, railways, and inland
waterways and could belong to different government agencies as well as service providers,
therefore, coordination with these institutions is essential to safeguard those and ensure lessinterruption during operation.
The common infrastructure and facilities a dry port should have are general cargo and container
area, ware house, railway siding, truck holding area, customs clearance and inspection area,administrative buildings, security gate, and specialize cargoes area. Depending on the types ofcommodity expected to be handled such oil, cement, raw materials, etc. the dry port would needseparate areas to handle these. The layout of these facilities should be planned such a way thatwould ensure smooth operation of dry ports.
There should be clear strategic environmental assessment (SEA) of the dry port development thatwould develop and finalize strategies such as guidelines on adaptation policy, design andplanning response in case of likely impacts in developing new dry port. Life cycle costing can beapplied to look at trade-off between various designs of infrastructure components and its costs.
Once the SEA is finalized, project level EIA should be done to study the forecast climate events,
assess likely impacts considering each infrastructure during construction and operation. Planningappropriate adaptation measures and implementation of those during construction and operationof dry ports are necessary. One important aspect of adaptation is to ensure periodic monitoringand maintenance of key infrastructure.
The concept of the dry port is to bring the facilities offered by seaport in inland area; the coastal
areas where the ports are located are usually vulnerable to climate change impacts such as sea
level rises and storms. Development of dry ports at secure and safe inland location can be83

considered as an adaptation measure to safeguard these infrastructures from potential damage by
the climate events. Therefore, while deciding the location of dry ports the suitability of inland
location to withstand impact of climate events need to be considered. If we invest in adaption
measures the cost are local and benefits are also local
Even developing dry port in secure inland areas the likely impacts from excessive rain, potential
flooding, cyclones, heat and snow need to be considered. The scale of impacts depends on thelocation. However, some adaptation measures that can be incorporated during planning anddesign stages are: (i) increasing plinth level of the cargoes, container and warehouse to safeguard
from flooding; (ii) construction of adequate cross drainage, drainage and dykes along theperiphery of the dry ports to avoid rush of flood waters and flooding; (iii) ensue the structuralsafety of covered warehouse and cargo area in case of storms and cyclone, as these would bevulnerable due to long span and height; and (iv) selection of suitable construction materials forroad pavement and container yard within dry port to withstand the heat as well as cold
temperature.
Provision of facilities offered by ports in inland and hinterland area is one of the key concepts ofdevelopment of dry ports. Such concept and their development in suitable and secure area would
contribute to the overall efforts of climate change adaptation. This would bring about economic
development in inland area as well as safeguard transport infrastructure from risk to be affectedby rising sea level and sea storms. The implementation of adaptation strategies and measures forthe development of dry port and operation can safeguard it from likely impacts of climate events.
4.7

Results and discussions

Transport infrastructure and operations are affected by climate events such as extreme rainfall,elevated temperature, rises in sea levels, and storm surge. Despite global efforts in addressing
climate change, Asia still lags in formulation and implementation of adaptation strategies forclimate change impacts in the transport sector. Further, the survey showed the need to plan anddesign transport infrastructure such as bridges, culverts, drains and cross drains, pavements, andcoastal roads with consideration of the likely impacts of climate change. The variation in climate
events’ intensity and the degree of impact in different Asian subregions indicates the need for
different adaptation strategies and policies. The assessment also identified the need to increase
the awareness level of the general public and to enhance the awareness of policymakers. The
need to review the design standards to incorporate the likely impacts of climate change and theneed for impact-assessment guidelines have also been identified. Policy and implementation gaps
have been identified and these need to be addressed in order to mainstream climate change
impacts, adaptation, and vulnerability issues and consider life-cycle costs. There is clear need for
greater collaboration among agencies, and, in many cases, the need to establish organizational
units and branches responsible for planning and implementing adaptation strategies. The issues
of funding and technical support required to plan and implement adaptation strategies also
emerged as a major cause of concern for developing countries.
In order to develop sustainable transport infrastructure, the most important consideration is toassess the likely impacts of climate change based on available predictions and incorporate theseassessments in the planning process. Considering that many Asian countries still lack clear
84

impact assessment guidelines, it is advisable and important to extend SEA/EIA guidelines to takeaccount of the risk and uncertainty of climate change and incorporate the predicted climate
events into project design. Climate change impact-assessment guidelines would help tosystematically evaluate the impacts. The next step is to review existing policies, design
standards, and practices. Because adaptation measures in transport are costly, life-cycle costingof proposed adaptation measures would be useful to select appropriate and feasible alternatives.
In addition, because impacts are widespread, coordination at national, regional, and local levels
is essential for implementation of adaptation strategies. Increased levels of awareness andcoordination among all Asian stakeholders are essential to develop sustainable transport.
Country-specific adaptation studies are required to develop adaptation strategies to plan andsustainable transport infrastructure.
Developing dry ports in secure inland areas, strategic decisions and policies at the planning anddesign level can contribute greatly to prolong the life of dry ports and ensure their sustainable
operation. The limited literature on transport and climate change studies in Asia indicates thatfurther research is needed in country-specific assessment and quantification of impacts andadaptation strategies for developing robust and sustainable transport infrastructure.
4.8

Chapter summary

The chapter outlined climate predictions for Asia, the perception of policy makers on climatechange and proposed adaptation strategies for the transport sector. Some of the key messages are
the need to consider climate impacts in design, taking life cycle assessment approach and theneed to develop sustainable transport infrastructure to withstand the likely impacts of weather
events. Nee to enhance awareness of both policy makers and general public also came out as animportant issue. It also elaborated on some of the resources available for transport and climatechange. Utilization of available resources in an efficient ways also is very important in thisrespect capacity of policy makers and project managers in implementing policies and projects
related to transport and climate change need to be enhance. This chapter dealt with adaptation
aspect of developing sustainable transport and dry ports. The next chapter focuses on otheraspect of sustainability of transport – mitigation and looks at the development of dry ports fromenvironmental perspective.

85

CHAPTER 5
CASE STUDIES OF THE DEVELOPMENT OF DRY PORTS IN ASIA 5
5.1

Introduction

In order to promote intermodal transport, it is essential to develop transport links, service andnodes, which include ports, airports, river ports, and inland dry ports, as well as to improve theefficiency of transport services. Intermodal transport nodes provide opportunities for a modal
shift. Development of dry ports can enhance consolidation and distribution of goods. Various
studies have focused on development of dry ports, inland terminals, and intermodal transport inEurope and developed countries (Rodrigue et al. 2010 and Caris et al. 2008). Therefore,
development of dry port and identifying strategic location that could enhance environmental
benefits in Asia need to be further explored.
This chapter presents details on the collection and analysis of case studies of dry ports
development in Asia. Finally, it presents key findings through a comparison of the cases.
5.2

Collection of case studies

Intermodal transport can facilitate modal shifts from one mode to another. The planning anddevelopment of freight terminals, freight villages, dry ports, and inland container depots (ICDs)
can extend the reach of the rail mode through intermodal services. In this respect, in order toreview the development of dry ports in Asia from environmental perspective the following casestudies have been collected. Site visits to Uiwang, Birgunj, Alashankou, Navoi and Kamalapur
dry ports were undertaken. The dates of the visits are indicated within parentheses.
i.
ii.
iii.
iv.
v.

Alashankou, Horgos dry port, China (16-17 June 2010);
Uiwang ICD, South Korea (16 July 2010);
Navoi International Logistics Centre, Uzbekistan (26 Nov. 2010);
Kamalapur ICD Dhaka, Bangladesh (14 September 2011); andBirgunj Inland Container Depot, Nepal (17 September 2011).

Information for the following dry ports were collected during a regional meeting on dry ports
held in Bangkok during 1-3 November 2010 and from other secondary sources.
i.
ii.
iii.

Lat Krabang ICD, Thailand;
Dry port development in India; andCikarang Dry Port, Indonesia.

5Part of this chapter was published as Hanaoka, S. and Madan B. Regmi, (2011), Promoting intermodal freighttransport through the development of dry ports in Asia: An environmental perspective, Journal of International
Association of Traffic and Safety Sciences (IATSS) Research, Vol.35, No.1, 2011, 16-23. The paper is available
from: (http://www.sciencedirect.com/science/article/pii/S0386111211000148).

86

5.3

Case studies of development of dry ports in Asia

Countries in Asia are at different stages in the development of dry ports. At present, both roadand rail-based intermodal dry ports near production and industrial centers are being developed toextend the reach of intermodal transport and to effectively consolidate and distribute cargoes.
Selected case studies of the development and operation of dry ports in Asia is outlined and key
financial, operational, environmental, regulatory and institutional factors involved in theirdevelopment and operation are discussed in the following section. Key findings from these casestudies can provide guidance for transport and logistics policy makers and professionals inplanning, development and operation of such dry ports.
5.3.1

Uiwang ICD, South Korea

Rapid growth in South Korea’s export and import volumes has led to an expansion of thenation’s ports. The pace of port expansion, however, was slower than the growth of trade: this led
to congestion at gateway ports such as Busan, Gwangyang, and Inchon, which handled the
majority of South Korea’s foreign trade. In response, in 1980, the government initiated a policy
to develop inland logistics centers.
The Uiwang ICD, which is located 25 km from Seoul, was developed by a public-private
partnership (PPP) in 1993. The Korean Rail Road Company and private transportationcompanies have invested in the Uiwang ICD. It has a capacity of 1.3 million TEUs and spans
417,000 m2. In addition to private-sector facilities and operating companies, customs, foodinspection, plant quarantine, and railway operations are located within the ICD. Shippers send
goods by road to the ICD, where they are consolidated and sent to seaports by rail. With a rail
capacity of 36 trains per day, the ICD utilizes both modes of transport, which helps to ease roadcongestion and enables the facility to serve as a clearance depot. Figure 5.1 shows the container
yard and block train at Uiwang ICD.

Figure 5.1 Block train and container yard, Uiwang ICD
Figure 5.2 shows the containers handled at Uiwang ICD, which exceeded 2 million TEU in 2006.
As can be seen in the Figure 5.2, there was a decrease in the volume of containers handled after2008 due to the economic recession. Further, the road mode share was approximately 75%,
except for a drop in 2008. Figure 5.2 also shows that the rail mode share of throughput handled87

by the ICD was about 25% in 2010, even though the ICD was running over capacity. The rail
share increased to about 35% in 2008 but again dropped. This use of railways for transport
to/from the ICD to seaports has helped to ease road traffic congestion and reduce vehicle
emissions. An expansion of the ICD’s and railway’s capacity would further enhance theenvironmental benefits, as would an increase in the rail mode share of freight.
Rail

Road

Total

Road mode share

Rail mode share
0.90

2,500

0.80
2,000

0.70

TEUs in Thousand

0.60
1,500
0.50
0.40
1,000
0.30
0.20

500

0.10
0.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Year

Source: Uiwang ICD, 2011
Figure 5.2 Container throughput at Uiwang ICD and mode share of road and rail
The Ministry of Land, Transport and Maritime Affairs (MLTM) is the regulatory authority
responsible for the planning, construction, and management of dry ports in South Korea. MLTM
encourages private sector investment in the development of dry ports and logistics centers.
Large-scale infrastructure project proposals from the private sector are reviewed by the Publicand Private Infrastructure Investment Management Center (PIMAC) to determine whether they
are consistent with the government’s long-term plans and investment priorities. The government
provides some support for the development of dry ports by assuming part of the land acquisitionand project costs. Infrastructure projects under PPP are either selected by the government or
proposed by the private sector. Uiwang ICD presents an interesting case of market-driven dry
port development that uses PPP for both financing and the improvement of operational
efficiency. Government logistics policies and PIMAC have played a supportive role in thisdevelopment.

88

5.3.2

Birgunj ICD, Nepal

The Birgunj ICD was developed by the government of Nepal with the support of the World
Bank. It has a 12 km rail link to the ICD from the Raxaul railhead near the border with India, andit connects further to the Kolkata/Haldia ports in India. The length of the road from Kolkata,
India, is 924 km, and that of the railway is 704 km. The ICD facilities include a broad gauge
railway yard with six full-length lines, a container stacking yard, a covered container freightstation, goods sheds, and parking space. It is equipped with the automated system for customs
data (ASYCUDA). Figure 5.3 shows the container yard and block train at Birgunj ICD. Since
majority of rail links are in India, it took the government of Nepal some time to conclude a rail
service agreement with India for the operation of the dry port. The Birgunj ICD, which wascommissioned in July 2004, but whose operations began two years later, is leased to the private
sector for operation. It now handles containers, tank wagons for liquid cargo, and flat wagons forbilateral break-bulk cargo, following amendments that were made to the service agreement.

Figure 5.3 Block train and containers at Birgunj ICD, Nepal
The Nepal Intermodal Transport Development Board (NITDB), which has representatives fromthe public as well as the private sector, is the regulatory body overseeing all dry ports/ICDs in
Nepal. As envisaged in Trade Policy 2009, the Nepal Intermodal Transport Development
Authority (NITDA) is planned to be established to regulate operational issues, including theissuance of licenses for the development and management of dry ports, container freight stations,and integrated customs points in the country.
The Birgunj ICD currently receives an average of around 15–16 freight trains per month. The
volume of container and cargo handled there is shown in Figure 5.4 (Regmi 2011). The sharp
increase in volume for break-bulk and container cargo from 2004/5 to 2005/6 was due to the
expansion of the railway service agreement to allow covered wagons and bilateral trade throughthe dry port. Prior to this, only transit trade with containers had been handled at the ICD. The
drop in volume during 2009/10 can be attributed to the global economic recession.

89

18000

Containerize
Cargo, TEUs

16000

Break, Bulk
Cargo, MT

12000
150000
10000
8000
100000

Break Bulk Cargo, MT

20000014000
Containerized cargo, TEU

250000

6000
4000

50000

2000
0

0

Year

Source: Regmi 2010
Figure 5.4 Cargo handled at Birgunj ICD
Figure 5.4 shows that the freight handled at Birgunj ICD in 2008/09 comprised 16,928 TEU(equivalent to 406,272 MT 6) and 237,104 MT of cargo. The following scenario illustrates theemissions reduction potential of the rail-based Birgunj ICD: had there been no dry port, allfreight from Kolkata 7 would have been transported to the dry port by heavy goods vehicle(HGV). Freight carried by rail emits much less CO2 compared to freight being transported by(HGV. For example, an average 28.3 g of CO2 emission per tonne-km of rail freight, 118.6 g for
HGV are in use in UK (DEFRA 2009). Using these emissions factors, the resulting CO2 savings
would have been 57,687 MT for 2008/9, which accounts for about 82% of the total roademissions. Table 5.1 shows resulting CO2 emissions savings from development of rail based dry
port in Birgunj, Nepal.

6
7

Using maximum allowed weight, 1 TEU = 24 MT.
Kolkata–Birgunj: road distance, 924 km; railway distance, 704 km.

90

Table 5.1: Assessment of CO2 emissions at Birgunj Dry Port, Nepal
Mode
Rail
Road

Length Km
704
924

Freight
TEU
MT
16,928237,104
16,928237,104

Eq. Freight,
MTT-km
643,376452,936,704
643,376594,479,424
Saving in CO2 Emissions (B-A)

CO2Emissions, MT
12,81870,50557,687(A)(B)

The lessons learned from the case of Nepal show that it is relatively easy to develop an ICD
infrastructure but that more effort is required to put it into operation. In any event, this ICD is aunique case, in the sense that it is located near the border, its main railway connection is from theKolkata port in India, and most of its freight route is in India. The conclusion and expansion of
the railway service agreement to include open break-bulk and freight wagons took more timethan anticipated. Therefore, it is worth considering operational issues during the development of
infrastructure. The case of this Birgunj ICD underscores the importance of operational andfacilitation issues, and the need to initiate and discuss operational agreements in advance.
Now, adjacent to the Birgunj dry port/ICD an integrated border post is being developed. This
integrated check post would process clearance of goods as well as passenger. The construction of
integrated check post has already been started. A field visit to see the operation of the Birgunj dry
port and observe initial construction of the integrated post was undertaken on 17 September
2011.
Other dry ports in Nepal are in Biratnagar, Bhairahawa, and Kakarbhitta, which are near the
India border, and at Kodari, near the Chinese border. Recent initiatives to promote intermodaltransport and railway in Nepal includes ongoing feasibility study of an east-west railway, a 60km-long Kathmandu-Birgunj railway, and connections to the four railheads in India.
Furthermore, talks are underway to extend the railway line from Lhasa in the Tibet region ofChina to the dry port at Kodari and further south to Kathmandu.
5.3.3

Lat Krabang ICD, Thailand

The Lat Krabang ICD was developed by the State Railway of Thailand (SRT) and operations
started in 1996. It is located about 27 km east of Bangkok and 118 km north of Laem Chabang
Port, with cargo carried by both railway and road between the Lat Krabang ICD and Laem
Chabang Port. Terminal operations are managed by six private-sector concessionaires who
provide services related to cargo consolidation, distribution, warehousing, customs clearance,and empty container storage. Figure 5.5 shows container block train and yard at the Lat Krabang
ICD.

91

Figure 5.5 Block train being assembled for Lat Krabang and containers
Thailand is giving priority to the development of dry ports in order to help shift the movement offreight from road-based transport to intermodal transport. The existing Lat Krabang ICD has afull electronic data interchange (EDI) link and handled around 1.7 million TEUs in 2008, farmore than its initial design capacity of 500,000 TEU. Because of the resulting congestion, many
containers from Laem Chabang Port are now bypassing the Lat Krabang ICD and proceeding
directly to external facilities for consolidation and deconsolidation.

Thousand TEU

INBOUNDOUTBOUND

1,000
900
800
700
600
500
400
300
200
100
0
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009Year

Source: Ratanachinda 2010
Figure 5.6 Containers handled at Lat Krabang ICD
Figure 5.6 shows the continuous increase in containers handled at the Lat Krabang ICD. Figure
5.7 shows the modal share of containers handled by truck and rail. Although it was designed fora rail-to-road mode share ratio of 40:60, the rail share has been decreasing due to limited rail link
capacity, congestion at the ICD, and the greater flexibility of road transport. On weekdays, 26
freight trains with 30 bogie container flat wagons capable of carrying 60 TEUs operate between
92

Laem Chabang Port and Lat Krabang ICD.
Rail

Road

80%
70%

Percentage

60%
50%
40%
30%
20%
10%

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0%

Year

Source: Ratanachinda 2010
Figure 5.7 Mode share of containers handled at Lat Krabang ICD
Figure 5.7 shows that the rail mode share of the throughput handled by the ICD was about 25%
in 2009 (Ratanachinda 2010), contributing to an overall reduction in congestion and emissions,since this reduced throughput would otherwise have been transported by road. The ICD iscurrently running at nearly twice its capacity. Therefore, SRT’s planned expansion of the ICD
capacity can positively contribute further to have environmental benefits.
In addition to the expansion of the Lat Krabang ICD, SRT is planning construction of new dry
ports to enhance the country’s logistics capabilities and to encourage a modal shift from roadtransport to the more environmentally friendly rail and water transport.
5.3.4

Dry port development in China

China is developing 18 large inland container rail transfer and logistics distribution centers (Wu2009) as part of its “Go West” strategy to encourage investment in, and the industrialization of,
the country’s interior. The China Railway Container Transport Center (CRCTC) was establishedby the Ministry of Railways as a container rail operator that can attract foreign investment.
CRCTC has also attracted other companies to invest in a number of specific ventures. Thesefacilities are operated by China United International Rail Container Co., Ltd, a special-purpose
entity set up by the Ministry of Railways in 2007.
Dry ports play an important role in stimulating economic development and facilitatinginternational trade and transport in China’s central and western inland areas. In this regard, three
aspects of this initiative need careful consideration: (i) the role of the national government in93

promotion and coordination; (ii) the development of dry port infrastructure, including othertransport infrastructure that links to dry ports; and (iii) the streamlining of institutional andregulatory frameworks (ESCAP 2010c).
The Shijiazhuang dry port, with a design capacity of 205,000 TEUs per year, is one of the largest
dry ports in China. This dry port has both rail and road access. Customs, inspection, andquarantine are available here. This dry port has direct links with Tianjin seaport and mainly
serves as a feeder for that port.
China also has a road-based dry port in Urumqi. A number of small-scale dry port facilities areunder construction near the Urumqi railway station. All these dry ports in Urumqi mainly serve
markets in Xinjiang and are not used for international trade. International cargo to and from
Lianyungang to Alashankou normally bypasses Urumqi.
In terms of cargo volume, Alashankou is the second largest border station in China; it connects to
the Dostyk station in Kazakhstan. It can handle all types of cargo: containers, break-bulk, oil, etc.
On average, the Alashankou dry port handles about 20 freight trains daily. The Erenhot dry port
near the border with Zammin-Uud in Mongolia also handles containerized and bulk cargo.
Figure 5.8 presents the volume of containers handled by Alashankou and Erenhot, showing
growth of 36% and 52%, respectively, between 2006 and 2007.

Alashankou Dry Port
250

Export
Total

ImportErenhot Dry Port
60

150

50
Thousand TEU

Thousand TEU

200

100

50

40
30
20
10
0

0
2006

Year 2007

2006

2008

2007

Source: Wu 2009
Figure 5.8 Container traffic through border dry ports in China
An international free trade economic zone (FTEZ) whose aim is to attract the construction of
manufacturing factories is being established in Horgos, near the border between China andKazakhstan. A logistics center is also planned within the FTEZ. Currently, border crossing andtransport at Horgos are conducted by road. The average wait-time for trucks to cross the border is
2–3 days. Around 75–100 trucks cross the border each day from China to Kazakhstan, and a94

similar number travel from Kazakhstan to China. Trucks from Kazakhstan that receive special
permission are allowed to operate in specified areas in China. An equal number of permits areissued to Chinese trucks operating in Kazakhstan. A railway linking Jinghe, Yining, and Horgos
has recently been completed. A railway connection on the Kazakhstan side from the border ofKhorgos to Almaty is also being planned. Figure 5.9 shows Alashankou dry port and trucks
crossing China-Kazakhstan border at Horgos.

Figure 5.9 Alashankou dry port and truck near Horgos border, China
In order to improve rail freight efficiency, China has been running double-stack container train
services to and from the main coastal ports on selected routes, using new specialized wagons andpowerful locomotives. In 2007, Chinese Railways operated 680 double-stack trains that carried
53,161 TEU, compared to 2005, when it operated 454 trains that carried 39,437 TEU (ESCAP
2009).
Development of dry ports, improvement of railway links and efficiency of double-stack trains
mentioned above would improve overall efficiency of the intermodal transport and take moreshare of freight and contribute to overall environmental benefits.
5.3.5

Dry port development in India

India has an extensive network of 59 ICDs, 49 of which can handle export-import. These inland
dry ports provide customs clearance, warehousing, container parking, repair facilities, and officefacilities. In almost all cases, these terminals are linked by rail to the Indian railway network. The
operation is handled by the Container Corporation of India, Ltd. (CONCOR), a subsidiary ofIndian Railways. Figure 5.10 presents the volume of containers handled by CONCOR and showsthat the share of international containers has grown gradually from 60% in 1996/97 to 81% in
2007/08. The decrease in container volume beginning in 2007/08 could be due to the economic
recession. CONCOR is investing in the modernization of facilities and improved efficiency by
improving its fleet and developing dedicated container platforms, advanced information systems,
e-Business, and the use of information and communication technology (ICT) for container
tracking.

95

Domestic

International

Total

Share of Int. Cont.

3000

0.90
0.80

2500

2000

0.60
0.50

1500
0.40
0.30

1000

Share of Int. Cont.

Thousand TEU

0.70

0.20
500
0.10
0.00

0

Source: CONCOR, 2011
Figure 5.10 Containers handled by CONCOR, India8
The Tughlakabad ICD, which is located 17 km to the southwest of Delhi, has an area of 55
hectares and is the largest rail-linked ICD in North India. It has a handling capacity of 400,000
TEUs per year. It has good links to the Mumbai and Jawaharlal Nehru ports through the Delhi–
Mumbai arterial trunk corridor and national highways. The ICD is equipped with completely
modern facilities that include EDI, export and import warehouses, radio-frequency identification(RFID) container tracking, and customs clearance. In 2009/10, Tughlakabad ICD handled
413,384 TEUs. Figure 5.11 shows container and block trains at Tughlakabad ICD.

Figure 5.11 Container and block train at Tughklabad ICD, India8

http://www.concorindia.com

96India is also implementing a project to develop dedicated freight corridors with an investment of
about US$10 billion. One of these is the Mumbai–Delhi corridor, which is receiving assistancefrom the Japanese government. This freight corridor segregates freight from passengers and be astate-of-the-art system with a high axle load and capacity (Parhi 2009).
The increasing trend of container handled at ICDs and transport to ports by railways shows
overall positive environmental benefits. These environmental benefits would be further
augmented when the efforts to improve operational efficiency of ICDs and dedicated freight
corridors would be complete.
5.3.6

Navoi International Logistics Centre, Uzbekistan

Uzbekistan has established an international intermodal logistics centre at Navoi, situated about
350 km of south-west of Tashkent with the aim of becoming a regional transshipment hub inCentral Asia. Currently, it is a predominantly air-based logistics centre serving as a consolidation
hub for transport of high-value goods from Asia to Europe and vice versa. Freight service is on
operation from Navoi to major destinations including Inchon, Milan, Brussels, Delhi, Mumbai,
Bangkok, Frankfurt, Shanghai, Moscow and Dhaka. There are plan to extend cargo service toIstanbul, Almaty, Dubai, and Tel Aviv.
Korean Air has been engaged to manage and operate the logistics center and develop and market
a business plan up to 2018. Uzbekistan Air and Korean Air operate 40 cargo flights per week.
Even though sufficient cargo and freight is not generated at Navoi, it is being used as
consolidating and distribution hub for transporting air cargos to Central Asia and Europe. The
Navoi airport operates 24 hour and can cater for 10 heavy aircraft such as Boeing-747 per day
and parking for five heavy aircraft. It has a 4,000 m × 45 m runway with instrument landing
system and has a plan to develop another runway. It has capacity to process 300 tons of cargo perday (100,000 tons per year). It is capable of receiving all types of aircraft.
The new cargo terminal with capacity of storing 1,000 tons of cargo was opened in August 2010.
It includes facilities like refrigeration and freezer, heating chamber, the storage area of dangerous
goods, perishable foodstuffs and animals. Other facilities required for international logistic
terminals are being developed such as hotel, expansion of capacity, parking areas for trucks.
Administration building houses all essential services. Figure 5.12 shows railway track and cargostorage area at the Navoi logistics centre.

Figure 5.12 Navoi Logistics Centre, Uzbekistan97

In 2009 it handled 26.7 thousand tons of cargo and it was estimated that the volume handled toreach to 60 thousand tons in 2010. Outside of Inchon, Navoi is the 2nd largest air fright hub interms of cargo frequency. Navoi is aiming to be number one cargo service provider. Its central
location is interesting as major cities such as Moscow, Istanbul, Tel Aviv, Dubai, Mumbai, New
Delhi and Almaty are within radius of 6 hours flight time while Milan, Frankfurt, Brussels,
Bangkok, Shanghai and Inchon are within 8 hours flight radius.
A free economic industrial zone (FIEZ) in Navoi was established in 2008 to attract foreign direct
investment from manufacturer to produce high value cargos. The initial lease within the FIEZ is
30 years. It is an extensive 584 hectares development, which is still under construction that
includes a logistics centre with an area of 40 hectares. International joint ventures withcompanies from Japan, South Korea and Singapore have established manufacturing factories
within the zone. FIEZ provides one stop licensing and registration service including tax
incentives for investment and customs incentives on equipment imports.
Navoi provides a very useful example of development of logistics centre/dry port on policy
initiatives of the government and commitment of various organizations from the beginning.
Examples of policies include provision of infrastructure, land lease, tax incentives for bringing
FDI to the free economic zone to generate cargo and one stop service to grant business andmanufacturing license, customs incentives to import equipments.
5.3.7

Cikarang Dry Port, Indonesia

Cikarang Dry Port has started operation since 2010 and is the largest and busiest dry port inIndonesia. It has an area of 200 hectare and is accessible by road and railway and serves Tanjung
Priork International Port in Java province in Indonesia. It is located in Jababeka Industrial Estate 9
and is just 50 km away from the port. The dry port is developed by private sector concessionaire.
The Cikarang Dry port has state of art facilities and provides one stop services to the customers.
It has integrated and automated customs clearance facilities, customs bonded area, truck pool,
empty container area, logistics area and supporting services including maintenance area. It also
has Customs Advance Trade System (CATS) and electronic sealing system for added security ofcargoes. Banking and supporting facilities are available in the dry port. Figure 5.13 shows the
Cikarang Dry Port. It is forecast to handle 168,950 TEU in 2015 and 215, 625 TEU in 2020. 10

9Cikarang Dry Ports (www.cikarangdryport.com) accessed on 23 November 2011.
Indonesia country report on dry ports, ESACP, 2011.

1098

Figure 5.13 Cikarang Dry Port, Indonesia 11
The dry port also designated as the port (point) of origin and destination having port code
“IDJBK.” Thus multimodal bill of loading can be issued to/from Cikarang. It handles
international export and import as well as domestic distribution. Due to this many shipping lines
have opened route to Cikarang Dry Port.
It provides integrated port and logistics services. It is mentioned that the use of Cikarang Dry
Port offers 30% cost and 55% time saving compared to existing conventional system. From
September 2011 the customs has announced implementation of the National Single Window for
import and export at Cikarang Dry Port.
Although clear environmental benefits of the dry ports are yet to be seen, as it is relatively new
facility, the use of integrated and automated system claim to have clear time and cost benefits tothe users. Even though, railway service is available the data on mode share of cargoes coming
and going out of the dry port is not yet available. Improving railway connectivity to and from dry
port and its use would provide environmental benefits.
5.3.8

Kamalapur ICD, Bangladesh

Kamalapur ICD, the only ICD in Bangladesh, was established by a Presidential order in 1987
and started its operation. It has direct rail link to Chittagong Port. The length of railway from
Kamalapur to Chittagong port is 320 km. The ICD has annual handling capacity of 90,000 TEU
and daily handling capacity of 4067 TEU. It is owned by the Bangladesh Railway and operated
by Chittagong Port Authority (CPA). The ICD is customs bounded facility and “through bill of
lading” can be issued to/from the ICD. Bangladesh Railway operates two block trains every day
and it takes about 12 hours. Figure 5.14 shows block train and container yard at Kamalapur ICD,
Dhaka.
In terms of capacity, it has limited capacity to handle containers due to the problems associatedwith shortage of railway wagons and engines. Reefer containers are not handled at ICD. The ICD
has container yard with an area of 449,143 sq m and container freight station with an area of
27,149 sq m. It also has container handling equipments such as rubber tired gantries, saddle
11

Source: www.cikarangdryport.com

99

carriers, fork lift trucks and reach-stackers.

Figure 5.14 Block train and container yard in Kamalapur ICD, Dhaka
Initially it handled about 7% of country’s total containers. Figure 5.15 shows the volume ofcontainer handled at Kamalapur ICD. It does not allow less than container loads (LCL) and has
is no cargo storage facilities, so only full containers are handled. It handles both export andimport, computerized customs clearance system is available. The office complex houses ICD
office customs brokers, freight forwarders and banking facility. Figure 5.15 shows containers
handled at Kamalapur ICD. The drop of container handled in 2009 and 2010 can be attributed to
the global economic recession. In month of August 2011 it handled 5409 TEU. On 14th
September 2011 there were 1358 containers in the ICD that is 33% of its capacity.
It was learned that as the ICD is generating operating profit and there was a competition between
Bangladesh Railway (the owner) and Chittagong Port Authority (the operators) to operate the
ICD even both are government undertakings. The operation agreement has recently been
extended to another 10 years till 2021 to the Chittagong Port Authority. As the block train is
operated by the Bangladesh Railway and ICD is operated by the Chittagong Port Authority there
seems to be lack of coordination among the owner and operator.

100Thousands TEU

Container handled at Kamalapur ICD
90
80
70
60
50
40
30
20
10
0
2004

2005

2006

2007

2008

2009

2010

Source: Kamalapur ICD 2011
Figure 5.15 Volume of container handled at Kamalapur ICD
A visit to the Kamalapur, ICD was undertaken on 14 September 2011 and met with operating
officers, customs officers and observed its facility and operation. Lack of sufficient locomotives
and wagons was mentioned as the constraint to increase the frequency of container block train
from Chittagong port to the ICD. Further, it was mentioned that due to extensive built-up area
nearby ICD it is difficult to expand its handling capacity. Therefore, the government is planningto develop another ICD in Dhirasram with handling capacity of 354,000 TEU. Improvement ofports, ICDs and container service can enhance the potential of Bangladesh to provide transit
service to Bhutan and Nepal as well as West Bengal and North-East India. Bangladesh is giving
high priority to improvement of Dhaka-Chittagong corridor.
Use of regular dedicated container block-trains in length of 320 km from ICD to Chittagong
seaport take share of road transport and has reduced freight transport emissions in addition to
reducing road congestion. However, there is need to increase these environmental benefits
through procurement of locomotives and wagons and increasing frequency as well as efficiencyof block train operation.
5.4

Key findings of the case studies

Table 5.2 summarizes some characteristics of dry ports related to their development andoperation. All dry ports included in the case studies were evaluated in terms of modes served;
environmental benefits/concerns; potential mode-shift opportunities; ownership; operationalarrangements; government policies and incentives for the development of dry ports; and lessons
learned from the development and operation of dry ports.
The case studies further supported the argument that the development of dry ports is at different
stages of development in Asia. Therefore, there is a scope to further enhance its development andpromote intermodal transport. All dry ports had railway connection and in most of the cases they101Table 5.2 Comparison of key features of selected dry ports
Key issues Dry
ports

Modes
servedEnvironmental benefits/concerns, potentialof mode-shift

Ownerships

Operation

Government policies and incentives

Lessons
learnedfromthedevelopment and operation of dry
ports

Uiwang, South
Korea

Rail,
road

The use of railway to transport freight to/fromports to ICD contributes to a reduction in roadcongestion and vehicle emissions.

Public-private
partnership

PrivatePromotion of PPP projects through
PIMAC.

Good example of PPP and role of
PIMAC, connecting port and ICD withhigh-capacity railway can reduce roadcongestion.

Birgunj, Nepal

Rail,
road

The modal shift to railway for transport
between port and ICD, with collection anddistribution of cargo by truck, contributes toemissions reduction.

Government

Private(leased)Government investing in facility andhas developed other dry ports as well.

Operation delayed due to delay inconcluding rail service agreement with
Indian Railways.

Lat Krabang,
Thailand

Rail,
road

Contribution to reduced road congestion andvehicle emission, but share of rail freight isdecreasing due to vehicle queues, ICD
congestion and limited railway capacity.

Public-private
partnership

Private(Concession)

Concessions to private sector for
development
andoperation.
Considering capacity enhancement.

Congestion at ICD and limited capacityof railway connecting to port.

Alashankou,
China

Rail,
road

Long haul freight is mainly by rail.
Development of dry ports, improvements ofrailway links and efficiency would contributeto environmental benefits.

ChineseRailway,
CRCTC

Public-private
CRCTC

Operation entrusted to CRCTC, apublic-private venture.

Government policy in developing
railways and dry ports and attract moreshare of freight to railways, capacity
enhancement ongoing, starting double
stack freight trains.

Tughlakabad,
India

Rail,
road

Transportation to/from ports is mainly byrailway, with roads used for collection anddistribution. Increasing trend of container
handled at ICDs and transport to ports byrailways shows overall positive environmental
benefits.

CONCOR,
Subsidiary ofIndianRailway

Publicundertaking

CONCOR investing in modernizationof facilities and improving efficiency
through improving fleet, dedicatedplatforms, use of ICT for container
tracking.

Good ICD and railway network,
dedicated freight corridors to enhance
efficiency of operations.

Navoi,
Uzbekistan

Air, roadand railMode shift possible but not currently, notenough freight volume for railway, reductionof air freight time.

Government

Private(management
contractor)

Tax incentives and one stop service forlicensing provided and Free Economic
Zone established adjacent to thelogistic centre.

Government policies and tax incentives
were conducive to attract FDI. Limited
volume of local freight.

Cikarang,IndonesiaRoad
and railConnected to Tanjung Priork Port by road andrail, now transportation is mainly by road.

Concession(Private
sector)Concession(Private
sector)Claims to be with state of art facilitiesSingle Window Clearance System,
electronic security.

Reduce congestion at the port, relatively
new dry port, so benefits are yet to beseen, need to connect to railways andstart block train operation.

Kamalapur,
Bangladesh

Road,
rail

Connected to Chittagong port by railway,
regular block train service running, distribution
by road, limited handling capacity andconstraint for expansion due to located in builtup area.

Bangladesh
Railway

Chittagong
Port Authority((Government
undertaking).

Due to limited capacity government
planning development of other dry port
at Dishasram, computerized customs
processing and clearance facility
available.

Limited capacity, lack of sufficient
locomotives and wagons for freight,
need to improve operational efficiency.

102

were connected to seaports by railways. The dry ports were at different distances from theseaport, Cikarang dry port and Lat Krabang ICD were close to the seaport, while the dry ports in
China, Nepal and Uzbekistan were far away from the seaports. The Kamalapur ICD was at midrange distance of 320 km from Chittagong seaport. These cases clearly illustrated their role inpromoting mode shift and emission reduction, as 25% of the total throughput handled at Uiwang
and Lat Krabang was carried by railways. Some dry ports had regular freight train service
to/from seaports. The development of rail connected dry port in Nepal demonstrated reduction oflarge percentage of emissions. A further scope to improve efficiency of operation of railway
system was indicate by the need to increase capacity of rail lines through double tracking,provision of efficient locomotives, provisions of sufficient wagons and improving load factors.
The use of double stacking of containers in railway flat wagons in China demonstrated one of themeasures to improve efficiency and load factor,
The partnerships and collaboration between public and private sector was evident from the cases
and in some cases the need to enhance collaboration. In most cases, governments have involved
in development where as either private sector or subsidiaries of governments were managing theoperation. There was an interesting case of competition between two subsidiary government
agencies to operate the Kamalapur ICD, as it was generating profit.
In addition to their function as logistics and distribution hubs, the role of dry ports as intermodaltransfer points for mode shift as well as their emission reduction potential was also visible. New
initiatives and policies would be required in Asia to further to promote the mode shift. The
European Commission‘s Marco Polo project which aims to increase the share of rail freight inEurope (EC 2011) could serve as a good example for Asia. However, many Asian countries may
not be in a position to introduce subsidies to railways yet to increase its mode share.
5.5

Requirement of a good dry port and policies

The review of the cases and literatures (ESCAP 2009a, United Nations 2007) show that there is aneed of greater collaboration among the government agencies and stakeholders in planning,development and operation of dry ports. The following list though not comprehensive, canprovide guidance on the requirement of a good dry port.
(i) Location at or near rail based intermodal terminals;(ii) Access to seaports and air ports;(iii) High quality and efficient transport system with connection to modes;(iv) Railway connectivity with seaport with regular freight train service;(v) Availability of sufficient cargo handling equipments, locomotives and wagons;(vi) Continuous improvement of operation efficiency;(vii) Use of advance information communication technology;(viii) Meet need of the consumer capacity with full range of services;(ix) Proximity to market and labour availability;(x) Availability of large area for future phased expansion;(xi) Located near free trade area or special economic zone;(xii) Security of cargoes, container and customers, users;(xiii) Proximity to manufacturing and production centres;103

(xiv) Effective partnerships and cooperation between public and private companies;(xv) Availability of office facilities with value added service; and(xvi) Contribution to the development of regional and local economy.
The support and cooperation of government agencies is essential in planning, development andoperation phase. During planning the government polices on licensing, allocation of land for thedry port as it needs larger area and financing relating to how to mobilize funding are essential.
During operation provision and location of government service at the dry port are necessary.
More importantly policy commitment of the government to streamlining customs clearance,
reduction of documents to be handled in dealing with export and import, implementation single
window system, eliminating double inspection of cargoes at the border as well and at the dry
ports are some of the policy issues that are essential to attract freight to the dry port. In someinstance, policies to encourage environmental friendly mode also is necessary for example
through subsides In addition, sharing of experience gained in development and operation dry
ports also becomes useful and can enhance capacity to planning, development and operation ofdry ports.
5.6

Results and discussions

Case studies of development and operations of dry ports in Asia provided insight into the role ofgovernments, markets, and the private sector in developing successful dry ports/ICDs. The casestudies also served to emphasize various factors that have influenced the development andoperation of dry ports and intermodal transport. Strong policy commitments by governments—
aiming to bring together all facilities and services, including customs clearance, inspection, andconsolidation, along with market-driven development—are some of the important factors thatneed to be considered. In addition, the dry ports/ICDs are being developed as growth centersnear Free Trade Economic Zones (FTEZ) in order to attract investment and other services as in
the case of Navoi Logistics Centre. Governments are able to initiate and promote suchdevelopment, as shown by the case of South Korea and Uzbekistan. At times, governments need
to “push” with new policies required to facilitate new developments and by liberalization andderegulation.
In addition to focusing upon infrastructural development, it is also necessary to consider
operational issues in conjunction with infrastructure development. The discussion of road/railservice and international transit agreements takes considerable time, as shown by the case in
Nepal. Here, dry port operation began two years after construction was completed because theconclusion of a rail service agreement with Indian Railway took longer time.
Railway connections to dry ports can reduce freight emissions through a modal shift that reduces
the number of long-haul trucks plying on roads. The cases of Birgunj, Uiwang, Lat Krabang and
Kamalapur demonstrate this potential as regular block train service is operated from these dry
ports to respective ports. Moreover, the current congestion and pollution at Uiwang and Lat
Krabang are isolated cases that are expected to be eased once the capacity of the ICDs is
expanded and the share of rail freight is increased. Investment in railway infrastructure/dry ports
can encourage modal shifts to greener modes of transport. In order to improve operational
efficiency, the modernization of facilities and the use of cleaner and greener fuels are necessary.
104

In case of Kamalapur procurement of locomotives and wagons to increase frequency of block
train service was necessary. The use of modern ICT technology is also important, as can be seenat the Tughlakabad ICD in India. In Cikarang relatively new dry port in Indonesia, apart fromreducing congestion other environmental benefits are yet to be seen.
One policy issue that needs to be addressed is coordination among the various government
agencies involved in the development of dry ports, including those responsible for licensing,investment, promotion of private-sector initiatives, etc. Both government and the private sector
need to work together to develop intermodal transport in Asia that not only provides access toinland and landlocked areas but also promotes environmentally friendly freight transport. In caseof Laos Nolitha (2011) argues that the development of dry port and logistics centers should be
driven from real economic potential, implementation of facilitation measures and improvementof road infrastructure.
Developing dry ports in secure inland areas away from vulnerable coastal area can support theadaptation initiative and contributes towards development of sustainable intermodal transportsystem and enhance its sustainability to withstand potential impacts of climate change.
5.7

Chapter summary

This chapter provided an overview of development of dry port in Asia through description ofcase studies. It highlighted importance of policy initiative of the government as well as the needto have partnerships with private sector for its development and operation.
The chapter also illustrated many factors and issues that need to be considered while planning,developing and operating dry ports. It also provided some empirical evidence on theenvironmental benefits that dry ports and its role in supporting mitigation through promotion ofmodal shift. The cases of Lat Krabang, Uiwang and Birgunj illustrated this fact. The list ofrequirement of a good dry port and policies suggested in this chapter can provide some guidance
and would be useful in development and operation. The location analysis of dry ports is anotherimportant issue as it involves different interest of stakeholders, which is discussed and analyzed
in next chapter.

105

CHAPTER 6
LOCATION ANALYSIS OF DRY PORTS
6.1

Introduction

This chapter presents the analysis of primary data collected for analysis of dry port locations.
The results of survey of policy makers indicated that there is a further need to provide
information to enhance awareness and understanding of transport problems. Presenting theresults of module 2 to the decision makers would assist and support in their decision making.
Initially, the detail of AHP survey is provided and the potential locations of dry ports in Laos areanalyzed using module 2 that incorporates AHP and goal programming.
6.2

Survey for analysis of dry port locations in Laos

Inland dry ports are important nodes of intermodal transport. Their development in inland areas
including land locked countries would facilitate modal shift and help reduce emissions fromtransport. There are many criteria that need to be considered for selecting/prioritizing location fordry ports. A survey of policy makers, freight forwarders and multimodal transport operators forthe analysis of dry port locations in Laos was undertaken. The data collection process included
interview survey, visits to the potential four dry ports location, and meetings with stakeholders in
Savannakhet and Vientiane. This section outlines details of primary data collection for AHP and
GP analysis for location priority of dry ports in Laos.
6.2.1

Selection of evaluation criteria and sub-criteria

The first task is to develop AHP model for multicriteria decision analysis (MCDA) consideringvarious criteria and sub-criteria that would be important in deciding the potential location of dry
ports. Considering the situation in Laos, and after extensive review of criteria and elements
considered by earlier studies, the criteria and sub criteria shown in Table 6.1 were selected forthe analysis of dry ports location. Prior to finalizing, these were sent to transport policy makers
in Laos and transportation professionals for their feedback. Five evaluation criteria and 12 subcriteria were chosen as suggested by literature to limit number of criteria to 6. This reduces thenumber of questions for pair-wise comparisons, increases chance of receiving more responses
and avoids complex calculations. The criteria and sub-criteria are considered to be independentof each other.

106

Table 6.1 Selected evaluation criteria and sub-criteria for AHP analysis
Criteria
Development and operation costs(C1)

Sub-criteria
Land acquisition costs (C11)
Construction costs (C12)Transportation costs (C13)Transportation time (C2)Intermodal transport connectivity(C3)

Total transport time from seaport (C21)
Highways (C31)
Railways (C32)
Inland waterways (C33)
Seaports (C34)
Impacts from construction (C41)
Impacts from transport operation (C42)

Environmental impacts (C4)
Regional economic development(C5)

Proximity to market, production centres and consumers (C51)
Government polices to develop special economic zone or free
trade area nearby (C52)
Freight demand (C53)

The four selected alternative locations of dry ports are based on that proposed the Laos Logistics
Development Plan. These locations are close to border with Thailand and could facilitate
international trade as Laos trade with Thailand accounts for more than 80% of international trade(ADB 2008). Figure 6.1 and Table 6.2 show four locations alternative dry ports.
Table 6.2 Alternative dry port locations
S. No.
Alt 1
Alt 2
Alt 3
Alt 4

Location
Thanalaeng
Thakhek
Savannakhet
Phakse107

Figure 6.1 Location of dry ports
6.2.2

Questionnaire development

Questionnaire survey for pair-wise comparison of criteria, sub-criteria and alternative locations
was developed and refined based on the feedback received from researchers, government
officials and transport professionals. Even though the evaluation criteria were limited to fivemain criteria and 12 sub-criteria, the total number of questions included in the questionnaire
were 101 for pair-wise comparison in addition to seven questions on general information of the
respondents. The respondents were asked to make pair-wise comparison and rate/judge theirpreference in Saaty’s 1 to 9 scale. The questionnaire included four sections: section I on general
information of the respondents; section II on evaluation of main criteria; section III on evaluationof sub-criteria; and section IV on preference of alternative dry ports locations with respect to acriterion/sub-criterion. Figure 6.2 shows a sample of question for comparing two criteria. The
full questionnaire is included as Appendix-III.

108

9

7

6

5

4

3

2

1

2

3

4

5

Extremely Important

Very important

Important

Very important

8

Slightly important

Development &transport costs

Slightly important

1

Important

Criteria

Extremely importantS.
NoEqually Important

Please indicate in 1- 9 point scale while making pair wise comparison of two criteria/subcriteria in a row. Please mark only one box in a row.

6

7

8

9

Criteria

Time

Figure 6.2 Format of pair-wise comparaison questionnaire
6.2.3

Selection of respondents and the survey

Contact was maintained with transport and logistics related government officials, LaosInternational Freight Forwarders’ Association (LIFFA) and Lao National Chambers ofCommerce and Industry (LNCCI) to develop a long list of potential respondents. From the long
list 50 people were selected for the survey that included 23 government officials, all (22)members of LIFFA and 5 members of LNCCI.
Prior to the visit to Laos for survey, the questionnaire was sent to all 50 potential respondents.
On site data collection was done during 6-12 July 2011. The survey of the government policy
makers was conducted during a subregional meeting on dry ports held in Vientiane on 7 and 8
July 2011. They were briefed on the objective and how to complete the response. The interview
survey of freight forwarders was done during 9-12 July 2011.
Additional survey inputs were also requested during meeting at the Ministry of Public Works andTransport on 11 July 2011. Similar approach was taken after the meeting with LIFFA and LNCCI
some questionnaires were left and collected on next day. In some cases, the replies were received
by email after returning to Bangkok. Repeated follow-ups, with email reminders and telephone
calls were made but without much success, to receive more response to survey.
Total 24 responses were received with an overall response rate of 48%. The response of private
sector was 44.4% (12 response from 27 requests) compared with government policy makers 52%(12 response from 23 requests). The total number of responses received can be considered quitesatisfactory as all most all sectors of policy makers related to the transport and logistics and 8
freight forwarders (36.4% of LIFFA members) provided feedback. Two questionnaires received
were incomplete and were discarded. Most of the responses received were consistent. Figure 6.3
shows gender and distribution of the respondents.

109

Gender of the Respondents

Distribution of the Respondets

25

15

20

10

15
5

10
5

0

0

Government
Male

FemaleFreight
Forwarders

Commerce& Industry

Figure 6.3 Gender and distribution of the respondents of AHP survey.
The opinion of the respondents received from the survey is used to evaluate location of dry ports
by AHP. The outputs of AHP were utilized as input for the GP model for further analysis of dry
port locations.
6.2.4

Field visit to potential dry port locations

The data collection also involved field visits to all four alternative locations, Thanalaeng,
Thakhek, Savannakhet, and Phakse, during 9-12 July 2011. It also involved meetings anddiscussions with freight forwarders, private sector representatives, and government officials at
Vientiane and Savannakhet. The discussion during these meetings focused to receive feedback
and perception on the importance of development of dry ports, modal shift, and development ofrail freight transport. The following provides a brief description of four dry port locations.
(i) Thanalaeng
An area near Thanalaeng railway station is selected for dry port/logistic park. Currently only
passenger train is in operation. It is expected to grow and serve as transshipment and distribution
centre for cargo coming and going the north using National Road NR-13N. Figure 6.4 shows
existing railway station and road border crossing from the Friendship Bridge. The railway needs
to be extended to the logistic park including siding to the railway track.

110

Figure 6.4 Friendship bridge border check posts and Thanalaeng railway station(ii) Thakhek
Figure 6.5 shows the 3rd Mekong Bridge. During the visit, this was under construction to connect
Thakhek with Nakhon Phanom. The existing ferry upstream of Thakhek was used to cross the
Mekong River. The bridge has opened as planned on 11 November 2011. The bridge now
provides short transport connection along the Asian Highway road 15 to Vietnam through border
Ban Lao.

Figure 6.5 New 3rd Mekong Bridge at Thakhek and existing ferry upstream(iii) Savannakhet
Savannakhet is being developed as international logistics hub. The government is also supporting
its development through free economic zone, the Savan-Seno Free Economic Zone (SSFEZ).
Figure 6.6 shows the 2nd Mekong River Bridge that facilitates international and transit traffic
along the Mekong-East West Corridor. The site for the logistic park is about 24 km from thebridge and Savannakhet city.

111Figure 6.6 Border check post at Savannakhet and container truck(iv)

PhakseThe logistic park at Phakse function is seen as more of supporting local and bilateral trade withThailand rather than international trade. Laos’s international trade with Cambodia is very
negligible despite its proximity with Champasak province. The site selected for the logistic
center is near the border crossing point at Vang Tao. It is near to the new planned custom office.
Figure 6.7 shows the border crossing point of Vang Tao and Chong Mek.

Figure 6.7 Border crossing point Vang Tao-Chong Mek and truck at borderThailand is planning to develop dual track system railway from Ubon Ratchathani and Laosborder. The Office of Transport and Traffic Policy and Planning (OTP) is undertaking feasibility
study and plans to spend 85 million baht for (Bangkok Post 2011) covering Ubon Ratchthani andChong Mek. The last train stop is Warin Chamrap and 80 km extension to Chong Mek (borderwith Laos) would cost about 10 billion baht. The dual track system would make logistics more
efficient as the value of trade between Thailand and Laos is 5.5 billion/year.
6.2.5

Limitation of the survey

During the survey it was felt that the questionnaire was too long as it contained 101 questions
and took around 20-30 minutes to complete. As a result, some of the potential respondents
promised to provide feedback but never did. However, due to large numbers of questions, some112

questions were left unanswered due to possible “reply fatigues.”
6.3

Location analysis of dry ports in Laos

The analysis is done using AHP which can consider both quantitative and qualitative criteria andderive relative weights and prioritize alternate locations based on selected criteria and subcriteria. It may not be always possible to measure and present these factors –as numerical values.
Rather these factors are expressed as value judgment, preferred options based on criteria. Three
AHP models are developed and analyzed based on the feedback received on evaluation criteria
and sub-criteria and alternatives. The local and global weights are derived, synthesis was done toarrive at final priority, and consistency check was done.
6.3.1

Analytic hierarchy process model

The location problem is decomposed into four levels of hierarchy consisting of (i) one goal; (ii)five criteria; (iii) 12 sub-criteria; and (iv) four alternatives. The four alternatives selected
represent actual location of dry ports in Laos, they are namely: Thanalaeng; Thakhek;
Savannakhet; and Phakse (see Figure 6.1). These are reflected in the government’s five-year
logistic plan (MPI 2011) and were proposed for development during a regional meeting on dry
ports (ESCAP 2010c). These locations were also studied in the Laos Logistics Master Plan Study(JICA 2011). This decomposition of decision problem makes it possible to judge the importanceof the elements in a given level with respect to other elements in the same level.
6.3.2

Pair-wise comparison and derivation of weights

The location analysis is based on the 24 feedback received from targeted 50 requests with an
overall response rate of 48%. The total number of feedback received from freight forwarders was
8 which represented 36% of total LIFFA members as total registered members of LIFFA are 22
in Laos. 4 responses (80% response rate) were received from chamber of commerce andindustries. It also includes feedback from almost all sectors of officials that are related tologistics development representing public works and transport, department of roads, departmentof transport, customs, railway, national transport facilitation committee, legal affairs, andofficials of special economic zones. Table 6.3 shows the summary of survey response.
The individual survey responses were tabulated and aggregated separately in two groups andanalyzed formulating government decision makers (GODM) and private sector freight forwarder(PSFF) models. The third model combines all feedback received from the government decision
makers and private sector freight forwarders, and is referred as the combined model (COMB).
Thus three types of AHP model are developed. This would be useful in comparing the preferenceof the policy makers and private sector freight forwarders.

113

Table 6.3 Details of survey responseType of respondents
Government
Decision makers
Private sector
Freight forwarders
Commerce andindustry
Total

6.3.2.1

No. ofrequests23

No ofreplies
12

27

12
22
5

% feedback
received
52%

Valid
response
12% of valid
response
54.6%

44.4%
36.4%
80%

10

45.4%
36.3
9.1%

PSFF

48%

22

92%

COMB

8
4

50

24

8
2

Model
GODM

Derivation of weights of main criteria

The respondents were asked to indicate their value judgment/preference in a 1 to 9 point scale
while making pair wise comparison. A judgmental matrix is developed based on pair-wisecomparison of priorities of criteria. The judgmental matrix of the main criteria for theGovernment Decision Makers’ Model (GODM) is shown in Table 6.4. In the judgmental matrix,
the values in matrix are not whole numbers, as geometric means method was used to aggregate
the responses so as to reflect views of all respondents. Using normalization and eigenvector
method, the weights of the five criteria were calculated. The weights were calculated using the
AHP analysis software. It shows the high importance assigned to the regional economic
development (C5), transportation cost (C1) and intermodal transport connectivity (C3) by thepolicy makers. The consistency ratio was 0.02.
Table 6.4 Judgmental matrix of evaluation criteria (GODM)
C1

C2

C3

C4

C5

Weights

C1

1

2.4

1/ 1.21.4

1/ 1.2

0.238

C2

1/2.4

1

1.2

1/1.5

1/1.9

0.124

C3

1.0

1/1.4

1

1.5

1.1

0.230

C4

1/1.4

1.5

1/ 1.5

1

1/1.4

0.168

C5

1.2

1.9

1/ 1.1

1.4

1

0.239

Similarly, Table 6.5 shows the judgmental matrix and resulting weights of main criteria ofprivate sector freight forwarders (PSFF) model. The overall consistency ratio was 0.05.
Interestingly, the freight forwarders have assigned high priority to the environmental impacts(C4) followed by regional economic development (C5).

114

Table 6.5 Comparison matrix of PSFF model
C1

C2

C3

C4

C5

Weights

C1

1

2.5

1/ 1.5

1/2.7

1/ 3.6

0.141

C2

1/2.5

1

1.0

1/1.6

1/1.6

0.130

C3

1.5

1.0

1

1/2.6

1/2.1

0.137

C4

2.7

1.6

2.6

1

1.4

0.309

C5

3.6

1.6

2.1

1/1.4

1

0.283

Table 6.6 shows the comparison matrix and derived weights of COMB model which incorporates
the feedback of the government policy makers and private sector freight forwarders. The resultshows the high importance given by the respondents to the regional economic development (C5)and environmental impacts (C4) criteria for location selection decisions. The transportation time
was considered as the least important criteria by the respondents.
Table 6.6 Comparison matrix of COMB model
C1

C2

C3

C4

C5

Weights

C1

1

2.4

1/ 1.2

1/1.1

1/ 1.7

0.202

C2

1/2.4

1

1/1.2

1/1.5

1/1.7

0.133

C3

1.2

1.2

1

1.0

1/1.2

0.201

C4

1.1

1.6

1.0

1

1/1.1

0.209

C5

1.7

1.7

1.2

1.1

1

0.255

Table 6.7 summarizes the derived weights of five evaluation criteria for three models. The
consistency ratio (CR) is also shown in the Table which in all case is less than 0.1 indicating
consistency of the pair-wise comparison and weight derivation.
Table 6.7 Derived weights of evaluation criteria
Criteria
Development and operation costs (C1)
Transportation time (C2)Intermodal transport connectivity (C3)
Environmental impacts (C4)
Regional economic development (C5)GODM
(C.R=0.02)
0.238
0.124
0.230
0.168
0.239

PSFF
(C.R=0.05)
0.141
0.130
0.137
0.309
0.283

COMB
(C.R.=0.02)
0.202
0.133
0.201
0.209
0.255

The above results show that the government decision makers assign high priority to the regional
economic development, followed by the development and operation cost and intermodaltransport connectivity. While the environmental impacts received second lowest weightindicating low importance and time for the government policy makers. Interestingly, private
sector and freight forwarders assign high priority to the environmental impacts followed by theregional economic development. Based on the analysis, the private sector seems to be more
responsible to environmental issues as they can visualize the difference they can make. It also
115

could be partly from their corporate social responsibility. Ideally, government decision makers
should also be aware of this. It could be that they could not foresee impacts of their policies. This
is in line with outcome of adaption survey that have shown the need to create more awareness ofgovernment policy makers on environmental and climate change issues
6.3.2.2

Weights of sub-criteria

The respondents were asked to indicate his value judgment/preference in a 1 to 9 point scale
while making pair wise comparison of sub-criteria within one criterion. A judgmental matrix isdeveloped based on pair-wise comparison. Tabulating and aggregating the individual judgments
and feedback received from the survey, weights of sub-criteria are derived. There would be four
matrices for each model corresponding to each criterion having sub-criteria. The transportation
time does not have sub-criteria, so there would be no matrix for time. So evaluating 12 matrices
gives the local priority weight of the sub-criteria. Table 6.8 shows judgmental evaluation
matrices comparing the importance of sub-criteria of government decision makers model(GODM).
Table 6.8 Evaluation matrices of sub-criteria for GODM model
C11
1
1.6
1.1

C11
C12
C13

C12
1/1.6
1
1.1

C13
1/1.1
1/1.1
1

Weights
0.274
0.352
0.374

C31
C32
C33
C34

C31
1
1/1.3
1/3.1
1/4.3

Costs
C41
C42

C41
1
1

C42
1
1

C32
1.3
1
1/2.1
1/3.3

C33
3.1
2.1
1
1/2.1

C34
4.3
3.3
2.1
1

Weights
0.423
0.338
0.149
0.090

Transport connectivity
Weights
0.5
0.5

C51
C52
C53

C51
1
1/1.3
1/1.9

C52
1.3
1
1/2.4

C53
1.9
2.4
1

Weights
0.425
0.386
0.190

Regional development

Environmental impacts

In similar manner, Table 6.9 shows the matrices and weights derived from various sub-criteria of
PSFF model.
Table 6.9 Evaluation matrices of sub-criteria for PSFF model
C11
1
1/1.7
2.3

C11
C12
C13

C12
1.7
1
3.1

C13
1/2.3
1/3.1
1

Weights
0.266
0.169
0.566

C31
C32
C33
C34

C41
1
1/1.4

C42
1.4
1

C32
1.1
1
1/3.0
1/1.8

C33
1/1.3
3.0
1
1/1.3

C34
2.3
1.8
1.3
1

Weights
0.280
0.359
0.211
0.150

Transport Connectivity

Cost
C41
C42

C31
1
1/1.1
1.3
1/2.3

Weights
0.583
0.417

C51
C52
C53

C51
1
2.0
1.4

C52
1/2.0
1
1/2.2

C53
1/1.4
2.2
1

Regional development

Environmental impacts
116

Weights
0.221
0.511
0.268

In similar manner, Table 6.10 shows the matrices and weights derived from various sub-criteria
of COMB model that incorporates feedback of government decision makers and private sector
freight forwarders.
Table 6.10 Evaluation matrices of sub-criteria for COMB model
C11
1
1/1.1
1.8

C11
C12
C13

C12
1.1
1
1.4

C13
1/1.8
1/1.4
1

Weights
0.276
0.282
0.442

C31
1
1/1.2
1/1.8
1/3.4

C31
C32
C33
C34

C41
1
1/1.1

C42
1.1
1

C33
1.8
2.8
1

C34
3.4
2.6
1.7
1

Weights
0.365
0.352
0.170
0.113

Transport Connectivity

Cost
C41
C42

C32
1.2
1
1/2.8
1/2.6

Weights
0.524
0.476

C51
C52
C53

C51
1
1.1
1/1.3

C52
1/1.1
1
1/2.3

C53
1.3
2.3
1

Weights
0.340
0.438
0.222

Regional development

Environmental impacts

Table 6.11 shows the summary of evaluation above matrices with derived local weight of theevaluation sub-criteria and consistency ratio calculated using AHP analysis software. By
multiplying this local weight with weight of corresponding criteria–global weight of eachcriterion is derived later.
Table 6.11 Derived weights of sub-criteria
Local priority weights
Criteria

Sub-criteria

Development
andoperation costs (C1)Land acquisition costs (C11)
Construction costs (C12)Transportation costs (C13)Time (C2)

Total transport time from seaport(C21)
Highways (C31)
Railways (C32)
Inland waterways (C33)
Seaports (C34)

Intermodaltransport
connectivity (C3)

Environmental impacts(C4)
Regional
economicdevelopment (C5)Impacts from construction (C41)
Impacts from transport operation(C42)
Proximity to market, production
centers and consumers (C51)
Government polices to develop
special economic zone or free
trade area nearby (C52)
Freight demand (C53)

117

GODM

PSFF

COMB

0.274
0.352
0.374
(C.R=0.02)
1

0.266
0.169
0.566
(C.R=0.01)
1

0.276
0.282
0.442
(C.R=0.01)
1

0.423
0.338
0.149
0.090
(C.R=0.01)
0.50
0.50
(C.R=0.0)
0.425

0.280
0.359
0.211
0.150
(C.R=0.08)
0.583
0.417
(C.R=0.0)
0.221

0.365
0.352
0.170
0.113
(C.R=0.02)
0.524
0.476
(C.R=0.0)
0.340

0.386

0.511

0.438

0.190

0.268

0.222

(C.R=0.03)

6.3.2.3(C.R=0.02)(C.R=0.02)

Location comparison with sub-criteria

The respondents were asked to indicate their value judgment/preference in a 1 to 9 point scale
while making pair wise comparison of alternative dry ports with respect to each evaluation subcriterion. A judgmental matrix corresponding to each sub-criterion is developed based on pairwise comparison of the locations. There are 13 matrices for each model corresponding to each
sub-criterion. The relative weights of the dry ports location corresponding to a criterion being
considered is determined and is used for overall synthesis later. The analysis is done with AHP
software after entering data to the corresponding evaluation matrix. Table 6.12 shows evaluation
matrices for comparison of alternatives with respect to sub-criteria for the government decision
makers’ model (GODM Model).
Table 6.12 Evaluation matrices for alternatives with sub-criteria (GODM)

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/3
1.5
1.3

Alt 2
1/1.3
1
1/1.2
1/1.3

Alt 3
1/1.5
1.2
1
1.9

Alt 4
1/1.3
1.3
1/1.9
1

Weights
0.194
0.292
0.223
0.291

Alt 1
Alt 2
Alt 3
Alt 4

Land acquisition cost (C11)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.8
1/1.6
1/1.8

Alt 2
1.8
1
1.6
1.8

Alt 3
1.6
1/1.6
1
1.2

Alt 4
1.8
1/1.8
1/1.2
1

Alt 1
1
1/1.6
1/1.1
1/1.5

Alt 2
1.6
1
1.6
1.2

Alt 3
1.1
1/1,6
1
1/1.1

Alt 4
1.5
1/1.2
1.1
1

Weights
0.363
0.159
0.227
0.251

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.4
1/1.1
1/1.4

Alt 2
1.4
1
1/1.3
1/1.6

Alt 3
1.1
1.3
1
1

Alt 4
1.4
1.6
1
1

Alt 3
1/1.2
1/1.2
1
1.2

Alt 4
1
1/1.5
1/1.2
1

Weights
0.243
0.209
0.260
0.288

Alt 1
1
1.3
1.7
1.1

Alt 2
1/1.3
1
1.4
1.1

Alt 3
1/1.7
1/1.4
1
1/1.6

Alt 4
1/1.1
1/1.1
1.6
1

Weights
0.196
0.236
0.241
0.228

Transportation time (C21)Weights
0.312
0.185
0.276
0.227

Alt 1
Alt 2
Alt 3
Alt 4

Highway connectivity (C31)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 2
1.1
1
1.2
1.5

Construction costs (C12)Transportation costs (C13)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.1
1.2
1

Alt 1
1
1/3.3
1/3.6
1/3.6

Alt 2
3.3
1
1/1.7
1/1.4

Alt 3
3.6
1.7
1
1/1.4

Alt 4
3.6
1.4
1.4
1

Weights
0.533
0.193
0.145
0.129

Railway connectivity (C32)
Weights
0.301
0.244
0.228
0.227

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.5
2.4
1.2

Alt 2
1/1.5
1
1.6
1/1.4

Alt 3
1/2.4
1/1.6
1
1/1.9

Alt 4
1/1.2
1.4
1.9
1

Seaports connectivity (C34)

Inland waterway connectivity (C33)118

Weights
0.164
0.253
0.389
0.194

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.4
1/1.4
1/1.4

Alt 2
1.4
1
1/1.7
1.4

Alt 3
1.4
1.7
1
1.3

Alt 4
1.4
1/1.4
1/1.3
1

Weights
0.314
0.238
0.186
0.262

Alt 1
Alt 2
Alt 3
Alt 4

Environmental impacts from construction
(C41)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.7
1/2.3
1/1.8

Alt 2
1.7
1
2.1
1.3

Alt 3
2.3
1/2.1
1
1/1.1

Alt 4
1.8
1/1.3
1.1
1

Alt 1
1
½.3
1/1.9
1/1.7

Alt 2
2.3
1
1.8
1.8

Alt 3
1.9
1/1.8
1
1/1.3

Alt 4
1.7
1/1.8
1.3
1

Alt 2
1.3
1
1/1.5
1.3

Alt 3
1.2
1.5
1
1.3

Alt 4
1.4
1/1.3
1/1.3
1

Weights
0.301
0.240
0.200
0.259

Environmental impacts from operation (C42)

Weights
0.389
0.163
0.239
0.209

Alt 1
Alt 2
Alt 3
Alt 4

Proximity to markets (C51)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.3
1/1.2
1/1.4

Alt 1
1
1.1
1/3
1/1.3

Alt 2
1/1.1
1
1.8
1.3

Alt 3
3.0
1/1.8
1
1/1.7

Alt 4
1.3
1/1.3
1.7
1

Weights
0.352
0.202
0.245
0.201

Government’s SEZ/FTA Policies (C52)
Weights
0.388
0.142
0.247
0.223

Freight Demand (C53)
Table 6.13 shows the evaluation matrices of alternative location with respect to sub-criterion for
PSFF model.
Table 6.13 Evaluation matrices of alternatives with sub-criteria (PSFF)

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.3
2.3
3.5

Alt 2
1/1.3
1
1.2
1.1

Alt 3
1/2.3
1/1.2
1
2.3

Alt 4
1/3.5
1/1.1
1/2.3
1

Weights
0.127
0.233
0.239
0.401

Alt 1
Alt 2
Alt 3
Alt 4

Land acquisition cost (C11)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/2.1
1/1.6
1/2.6

Alt 2
2.1
1
2.1
1/1.2

Alt 3
1.6
1/2.1
1
1/1.6

Alt 4
2.6
1.2
1.6
1

Alt 1
1
1.7
1.6
1.2

Alt 2
1/1.7
1
1/1.2
1/1.3

Alt 3
1/1.6
1.2
1
1/1.8

Alt 4
1/1.2
1.3
1.8
1

Alt 2
1/1.2
1
1.2
1.5

Alt 3
1/1.4
1/1.2
1
1.2

Alt 4
1
1/1.5
1/1.2
1

Weights
0.219
0.224
0.268
0.289

Construction costs (C12)Weights
0.397
0.168
0.280
0.155

Alt 1
Alt 2
Alt 3
Alt 4

Transportation costs (C13)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.2
1.4
1

Alt 1
1
1/1.3
1/1.4
1/1.7

Alt 2
1.3
1
1.7
1

Alt 3
1.4
1/1.7
1
1/1.4

Alt 4
1.7
1
1.4
1

Weights
0.325
0.201
0.279
0.195

Transportation time (C21)Weights
0.180
0.310
0.304
0.206

Alt 1
Alt 2
Alt 3
Alt 4

Highway connectivity (C31)

Alt 1
1
1/1.4
1/2.7
1/2.5

Alt 2
1.4
1
1.2
1.1

Alt 3
2.7
1/1.2
1
1/1.6

Alt 4
2.5
1/1.1
1.6
1

Railway connectivity (C32)119

Weights
0.414
0.203
0.215
0.169

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.5
1/1.5
1/1.3

Alt 2
1/1.5
1
1.1
1.5

Alt 3
1.5
1/1.1
1
1.1

Alt 4
1.3
1/1.5
1/1.1
1

Weights
0.268
0.249
0.220
0.263

Alt 1
Alt 2
Alt 3
Alt 4

Inland waterway connectivity (C33)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.4
1/1.5
1.2

Alt 2
1.4
1
1/1.4
1/1.3

Alt 3
1.5
1.4
1
1.9

Alt 4
1/1.2
1.3
1/1.9
1

Alt 1
1
1/3.3
1/1.4
½.7

Alt 2
3.3
1
2.8
1.2

Alt 3
1.4
1/2.8
1
1/2

Alt 4
2.7
1/1.2
2.0
1

Weights
0.282
0.264
0.171
0.283

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/2.7
1
1/2.2

Alt 2
2.7
1
2.2
1.4

Alt 3
1
1/2.2
1
1/2.9

Alt 4
2.2
1/1.4
2.9
1

Alt 3
1/1.5
1/2.7
1
1/2.5

Alt 4
1.2
2.0
2.5
1

Weights
0.204
0.231
0.419
0.146

Alt 1
1
1/2
1/1.9
1/2.3

Alt 2
2
1
1/1.3
1.3

Alt 3
1.9
1.3
1
1.8

Alt 4
2.3
1/1.3
1/1.8
1

Weights
0.406
0.196
0.162
0.236

Environmental impacts from operation (C42)

Weights
0.415
0.121
0.312
0.152

Alt 1
Alt 2
Alt 3
Alt 4

Proximity to markets (C51)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 2
1/1.3
1
2.7
1/2

Seaports connectivity (C34)

Environmental impacts from construction
(C41)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.3
1.5
1/1.2

Alt 1
1
2.3
4.2
2.3

Alt 2
1/2.3
1
1.6
1.4

Alt 3
1/4.2
1/1.6
1
1/2.2

Alt 4
1/2.3
1/1.4
2.2
1

Weights
0.101
0.223
0.433
0.243

Government’s SEZ/FTA Policies (C52)
Weights
0.350
0.133
0.361
0.156

Freight Demand (C53)
Table 6.14 shows evaluation matrices of alternative locations with respect to each evaluation
sub-criterion for the combined model (COMB).
Table 6.14 Evaluation matrices of alternatives with sub-criteria (COMB)

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1.3
1.7
1.8

Alt 2
1/1.3
1
1/1.1
1.2

Alt 3
1/1.7
1.1
1
2

Alt 4
1/1.8
1/1.2
1/2
1

Weights
0.171
0.251
0.228
0.350

Alt 1
Alt 2
Alt 3
Alt 4

Land acquisition cost (C11)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.9
1/1.6
1/2.1

Alt 2
1.9
1
1.8
1/1.3

Alt 3
1.6
1/1.8
1
1/1.1

Alt 4
2.1
1.3
1.1
1

Alt 2

Alt 3

Alt 4

Alt 2
1
1
1.3
1.2

Alt 3
1/1.3
1/1.3
1
1.1

Alt 4
1
1/1.2
1/1.1
1

Weights
0.233
0.222
0.278
0.267

Construction costs (C12)Weights
0.376
0.189
0.254
0.281

Alt 1
Alt 2
Alt 3
Alt 4

Transportation costs (C13)
Alt 1

Alt 1
1
1
1.3
1

Alt 1
1
1.1
1.2
1/1.1

Alt 2
1/1.1
1
1.5
1.1

Alt 3
1/1.2
1/1.5
1
1/1.5

Alt 4
1.1
1/1.1
1.5
1

Weights
0.237
0.224
0.317
0.222

Transportation time (C21)Weights

Alt 1

120

Alt 2

Alt 3

Alt 4

Weights

Alt 1
Alt 2
Alt 3
Alt 4

1
1/1.1
1.1
1/1.2

1.1
1
1.2
1

1/1.1
1/1.2
1
1/1.3

1.2
1
1.3
1

0.260
0.232
0.285
0.223

Alt 1
Alt 2
Alt 3
Alt 4

Highway connectivity (C31)
Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/1.1
1/1.2
1/1.3

Alt 2
1.1
1
1/1.1
1.2

Alt 3
1.2
1.1
1
1

Alt 4
1.3
1/1.2
1
1

Alt 1
1
1/1.4
1/1.4
1/1.1

Alt 2
1.4
1
1/1.6
1.1

Alt 3
1.4
1.6
1
1.5

Alt 4
1.1
1/1.1
1/1.5
1

Weights
0.285
0.238
0.232
0.245

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/2.2
1/1.9
1/2.1

Alt 2
2.2
1
2.3
1.3

Alt 3
1.9
1/2.3
1
1/1.3

Alt 4
2.1
1/1.3
1.3
1

Weights
0.298
0.249
0.182
0.271

Alt 1
Alt 2
Alt 3
Alt 4

Alt 1
1
1/2.4
1/1.5
1/1.9

Alt 2
2.4
1
2
1.6

Alt 3
1.5
1/2
1
1/1.7

Alt 4
1.9
1/1.6
1.7
1

3.1
1.2
1.5
1

0.486
0.198
0.172
0.144

Alt 1
1
1.4
2.4
1.1

Alt 2
1/1.4
1
1.9
1/1.6

Alt 3
1/2.4
1/1.9
1
1/2.1

Alt 4
1/1.1
1.6
2.1
1

Weights
0.168
0.244
0.411
0.177

Alt 1
1
1/1.5
1/1.4
1/1.7

Alt 2
1.5
1
1/1.4
1.3

Alt 3
1.4
1.4
1
1.5

Alt 4
1.7
1/1.3
1/1.5
1

Weights
0.337
0.224
0.187
0.252

Environmental impacts from operation (C42)

Weights
0.401
0.146
0.262
0.191

Alt 1
Alt 2
Alt 3
Alt 4

Proximity to markets (C51)
Alt 1
Alt 2
Alt 3
Alt 4

3.2
1.3
1
1/1.5

Seaports connectivity (C34)

Environmental impacts from construction
(C41)
Alt 1
Alt 2
Alt 3
Alt 4

2.4
1
1/1.3
1/1.2

Railway connectivity (C32)

Inland waterway connectivity (C33)
Alt 1
Alt 2
Alt 3
Alt 4

1
1/2.4
1/3.2
1/3.1

Alt 1
1
1.4
3.4
1.1

Alt 2
1/1.4
1
1.7
1.4

Alt 3
1/3.4
1/1.7
1
1/1.9

Alt 4
1/1.1
1/1.4
1.9
1

Weights
0.154
0.203
0.422
0.221

Government’s SEZ/FTA Policies (C52)
Weights
0.337
0.140
0.287
0.196

Freight Demand (C53)
The above analysis of matrices are used to derived local weights of the alternative dry ports
location with respect to each sub-criteria based on the feedback of the survey. These local
weights and weights of five evaluation criteria and sub-criteria are used for synthesis and final
weight derivation of the alternative.
Figure 6.8 shows the compiled local weights of the alternative locations with respect to the fivemain criteria for the combined model (COMB). The outputs are taken from the AHP analysis
software – by performing an analysis from the main criteria nodes.

121

Relative weights of dry ports location
Cost

Time

Trp. Con.

Envi.

Reg. Dev
0.279
0.237

Thanalaeng

0.334
0.317
0.288
0.215
0.224
0.222
0.237

Thakhek
0.17

0.253
0.317

Savannakhet

0.25
0.184
0.337
0.252
0.223

Phakse

0.194
0.262
0.205

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Local Weights

Figure 6.8 Relative weights of alternatives with respect to five criteria (COMB)
6.3.2.4

Evaluation of tangible criteria

Construction cost (C12), transportation time (C21), proximity to market and production centers(C51) and freight demand (C53) are tangible criteria which can be measured. For landacquisition cost (C11) comparison of land cost at different location is used. Sub-criteriatransportation cost (C13) is also measurable, but due to sensitivity of the transportation priceamong freight forwarders and transport operators, it could not be collected and the rating
provided by the respondents was used instead. The data for these criteria and sub-criteria wascollected during the survey and secondary sources. Table 6.15 shows the tangible data collected
and their normalized values which were used for the final analysis. The corresponding values
were replaced with the calculated comparison values. Except for ‘freight demand’ the higher thevalue of element would lower the resulting weights and priority. For example, higher
construction cost of an alternative would encourage decision makers to consider other alternative
locations with lower construction costs.

122

Table 6.15 Estimated values of tangible criteria and sub-criteria
Alternatives

Thanalaeng
Thakhek
Savannakhet
PhakseLandacquisition
cost (C11)
Ratio Norm.
1 0.192
0.65 0.295
0.8 0.240
0.7 0.274

Construction
cost
(C12)
M US$ Norm.

6.3.2.5

Synthesis and derivation of final priority

32
3.7
4.56
14.77

Transport time
(C13)

0.053
0.459
0.373
0.115

Hours

Norm.

7
9
8
7

0.291
0.227
0.255
0.227

Proximity tomarket (C51)
Km

Norm.
21
24
28
50

0.328
0.287
0.246
0.138

Freight demand
(C53)
Tons

Norm.

4032000
1150000
1577000
803000

0.533
0.152
0.209
0.106

The overall synthesis was done using AHP analysis in the distributive mode. The above analysis
evaluated the local priorities of four alternative locations. Also in earlier sections, the relative
weights of five evaluation criteria and sub-criteria were derived. In the last step of AHP analysis,
the global priorities of four alternative locations are evaluated using the global weight of each
sub-criterion. This is done by multiplying the corresponding weights and adding up. A relative
preference matrix is developed; and corresponding global weights are calculated. For thetangible criteria, the weights derived in Table 6.15 are used. Detail weight derivation and ranking
for three different AHP models are shown in Table 6.16. Incidentally, the final derived priority of
the alternatives is same for all three models, with Thanalaeng receiving the highest priority withweights of 0.311, 0.296 and 0.295 from analysis of government decision makers (GODM),
private sector freight forwarders (PSFF) and the combined (COMB) models, respectively. Figure
6.9 shows final derived weight of each dry port location for GODM model.

Derived Final Weights of Alternate Dry Ports
Cost

Time

Trp. Con.

0.02

0.04

Env.

Reg. Dev.

Thanalaeng

ThakekSavannakhet

Phakse
0

0.06

0.08

0.1

Global Weights

Figure 6.9 Final derived weights of alternative dry ports for COMB model
123

The overall consistency ratio of the combined model (COMB) is 0.04, consistency ratio of thegovernment decision makers (GODM) model is calculated as 0.02, and the consistency ratio of
the private sector freight forwarders (PSFF) model is 0.05. Literatures suggest a value of 0.1 forthe consistency index as acceptable and explain consistency of the analysis and outcome. An
inconsistency ratio of more than 0.1 may warrant further investigation, in some case, repeat of
the survey. Therefore, these values indicate overall consistency of data and analysis andreliability of the outcome.
Figure 6.10 shows the final global weights received by alternative dry ports evaluated withrespect to the environmental impact criteria. The analysis clearly shows the preference ofThanalaeng followed by Phakse and Thakhek. The preference of Thanalaeng could be related tothe possibility of railway operation as it is connected with railway and possible use of inland
waterways. Thakhek is also near Mekong River. Interestingly, Savannakhet received the lowest
preference. This could be due the fact that the dry port location, being 24 km inside MekongRiver, difficulty in utilizing for inland water transport to the dry port as well as having no firmplan to connect it with railways.

Evaluation of Environmental Criteria
Total

Const. Imp.

Oper. Imp.
0.067

Thanalaeng
0.052

Thakek
0.039

Savannakhet

0.055

Phakse
0

0.02

0.04

0.06

0.08

Global Weight
Figure 6.10 Result of synthesis of environmental criteria for COMB model
Figure 6.11 shows final derived weights and ranking of four alternative locations using threedifferent AHP models. The results show that all three location models ranked Thanalaeng as thehighest priority location followed by Savannakhet and Thakhek. This result output is in line withthe view of policy makers and freight forwarders. The result highlights the importance ofThanalaeng because of its railway connectivity, proximity to Vientiane capital and expected
freight volume. Further, Thanalaeng dry port is expected to serve the capital and surroundingarea as well with Northern region of Laos.

124

Table 6.16 Final synthesis and derived weight of alternative dry ports
Criteria\
Location

C11

C12

C13

C21

Thanalaeng

0.01250.00450.032

0.0361

0.031

0.041

0.01

0.003

0.026

Thakhek

0.01920.03860.014

0.0281

0.018

0.015

0.008

0.005

Savannakhet

0.01600.03130.021

0.0320

0.027

0.011

0.008

Phakse0.01800.00970.022

0.0281

0.022

0.01

0.008

C31

C32

C33

C34

C41

C42

Total

Rank

C51

C52

C53

0.025

0.034

0.032

0.024

0.311

1

0.021

0.02

0.029

0.017

0.007

0.240

3

0.008

0.016

0.017

0.025

0.023

0.009

0.245

2

0.004

0.022

0.022

0.014

0.019

0.005

0.204

4

0.052

0.020

0.015

0.041

0.296

1

0.012

0.233

3
2

Government Decision Makers (GODM) Model

Private Sector Freight Forwarders (PSFF) Model
Thanalaeng
Thakhek

0.00710.01100.00130.0110

0.032
0.013

0.03800.0295

0.007
0.012

0.02
0.01

0.008
0.007

0.004
0.005

0.051
0.048

0.025

0.018

0.032

Savannakhet

0.00900.00900.022

0.0332

0.012

0.012

0.006

0.009

0.031

0.021

0.015

0.062

0.016

0.257

Phakse0.01010.00280.012

0.0295

0.008

0.008

0.008

0.003

0.051

0.03

0.009

0.035

0.008

0.214

4

Combined (COMB) Model
Thanalaeng

0.01000.00300.034

0.0388

0.019

0.034

0.01

0.004

0.033

0.034

0.028

0.017

0.030

0.295

1

Thakhek

0.01650.02620.017

0.0302

0.017

0.014

0.008

0.006

0.03

0.022

0.025

0.023

0.009

0.243

3

0.011

0.259

2

0.006

0.203

4

Savannakhet
Phakse0.01340.01530.02120.0060

0.023
0.016

0.03300.0302

0.021
0.016

0.012
0.01

0.008
0.008

125

0.009
0.004

0.02
0.03

0.019
0.025

0.021
0.012

0.047
0.025

Derived Weights of Dry Port Location
GODM

PSFF

COMB
0.311
0.296
0.295

Thanalaeng
0.240
0.233
0.243

Thakhek

0.245
0.257
0.259

Savannakhet
0.204
0.214
0.203

Phakse
0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

WeightFigure 6.11 Final weights and ranking of alternative dry ports
6.3.2.6

Limitation of AHP analysis

The location analysis was based on the judgment and evaluation of the government decision
makers and private sector freight forwarders. For objective criteria and sub-criteria, objective
data were used for analysis and comparison of alternative location, wherever possible. The data
for total transportation cost (C130) and environmental impacts (C41 and C42) for all alternatives
were not available. Therefore, subjective judgments provided by the respondents were used.
6.4

Combined AHP-Goal programming

AHP-Goal programming allows to look at the achievement of the conflicting goals. The fivecriteria used in AHP analysis were framed as goals of the optimization problem. Thus the goal of
the AHP-Goal programming is to select the location(s) that would minimize transportation andoperation cost, transportation time and environmental impacts and maximizing the intermodaltransport connectivity and regional economic development. For this analysis, the AHP outputs ofthe combined model are used. This model combines feedbacks received from the government
decision makers, private sector freight forwarders and chamber of commerce and industries. All
24 responses received for the AHP analysis are used. Table 6.17 shows the derived weights offive main criteria corresponding to the locations used for analysis of location using AHP. The
coefficients were derived based on pair wise comparison on the importance of four alternate dry
126port locations with respect to each evaluation criterion.
Table 6.17 Derived local weights of main criteria corresponding to alternatives
Criteria
Development and operation costs(C1)
Transportation time (C2)Intermodal transport connectivity(C3)
Environmental impacts (C4)
Regional economic development(C5)

Thanalaeng
(X1)
0.279

Thakhek(X2)
0.215

Savannakhet
(X3)
0.253

Phakse
(X4)
0.252

0.237
0.334

0.224
0.222

0.317
0.250

0.223
0.194

0.317
0.288

0.237
0.170

0.184
0.337

0.262
0.205

The final weights (priority) of the decision criteria obtained from AHP analysis of combined
input of policy makers and freight forwarders is reproduce here in following Table 6.18.
Table 6.18 Final weights of decision criteria of COMB Model
Criteria
Development and operation costs (C1)
Transportation time (C2)Intermodal transport connectivity (C3)
Environmental impacts (C4)
Regional economic development (C5)
Total

6.4.1

Weights
0.202
0.133
0.201
0.209
0.255
1.0

AHP-GP model

Goal programming is used to further analyze the dry port location by considering additional
tangible criteria budget constraint and ability to meet the freight demand. By utilizing
optimization techniques, the underachievement and overachievement of targeted goals can beassessed, which would be useful for making rational decisions. As outlined in the methodology,
using the coefficient of Table 6.17, the Goal Programming model is developed. The main
objective of this GP is to minimize the sum of unwanted deviation from the goals. The goals
corresponding to the minimization and maximization of the five evaluation criteria becomes
constraints of the goal programming objective. The corresponding values are used as thecoefficients of corresponding decision variables (location of dry ports), X1, X2, X3, and X4.
Deviation variables are introduced in the left hand side (LHS) of each criterion. Right hand side(RHS) side of the equations for the goals two maximum coefficients are added (Badri 2001,
Firouzabadi et al. 2008). This ensures selection of alternatives having combined higher
preference (represented by local weights) of all criteria selected.
The final AHP weights derived (Table 6.18) for the evaluation criteria become the weights of thecorresponding deviational variables. The objective function is the minimization of sum of
deviation variable.

127

MIN
0.202D_COST_P+0.133D_Time_P+0.201D_TRN_N+0.209D_ENV_P+0.255D_RD_N++D_BDTG_P+D_FD_P+D_WT_N(6.1)
Subject to,
0.279X1+0.215X2+0.253X3+0.252X4-D_COST_P+D_COST_N=0.532(6.2)(Goal relating to development and operation cost)
0.237X1+0.224X2+0.316X3+0.223X4-D_Time_P+D_Time_N=0.554(6.3)(Goal relating to total transportation time)
0.334X1+0.222X2+0.25X3+0.194X4-D_TRN_P+D_TRN_N=0.6(6.4)(Goal relating to intermodal transport connectivity)
0.317X1+0.237X2+0.184X3+0.262X4-D_ENV_P+D_ENV_N=0.42(6.5)(Goal relating to environmental impacts)
0.288X1+0.17X2+0.337X3+0205X4-D_RD_P+D_RD_N=0.53.

(6.6)(Goal relating to regional economic development)
Following three additional constraints are added to meet the requirement of budget and freight
demand for 2025. The corresponding coefficients used are taken from the Laos Logistic Study(JICA, 2011).
32X1+4X2+5X3+15X4-D_BDGT_P+D_BDGT_N=47(6.7)(Budget constraint)
1400X1+80X2+150X3+300X4-D_FD_P+D_FD_N=1930(6.8)(Freight demand)
0.295X1+0.243X2+0.259X3+0.203X4-D_WT_P+D_WT_N=1(6.9)(Constraint relating to AHP weights)
X1+X2+X3+X4=>1(6.10)(Constraint introduced to select at least one dry port location)
128

All deviation variables are non-negative DV+/-=>0
Also, the decision variables X1, X2, X3 and X4 are 0, 1 variables,
Xi= (0, 1)
Where,
D_COST_P
D_COST_N
D_TIME_P
D_TIME_N
D_TRN_P
D_TRN_ND_ENV_P
D_ENV_N
D_RD_P
D_RD_N
D_BDTG_P
D_BDTG_N
D_FD_P
D_FD_N
D_WT_P
D_WT_Nis positive deviational variable for Costs
is negative deviational variable for Costs
is positive deviational variable for Time,is negative deviational variable for Time,is positive deviational variable for Intermodal Transport Connectivity
is negative deviational variable for Intermodal Transport Connectivity
is positive deviational variable for Environmental Impacts,
is negative deviational variable for Environmental Impacts,
is positive deviational variable for Regional Development
is negative deviational variable for Regional Development
is positive deviational variable for Budget
is negative deviational variable for Budget
is positive deviational variable for Capacity and Freight Demandis negative deviational variable for Capacity and Freight Demandis positive deviational variable for weights
is negative deviational variable for weights

Xi- is location of the dry ports, decision variables,
6.4.2

Goal programming model outputs

The Goal Programming model can be solved by using LINDO software 12. For the solution of thelocation problem the analysis was done by using LINDO software (student version 6.1). The
analysis of the model produced the following outputs as shown in Table 6.19 and 6.20.
Table 6.19 Goal programming model output
S. No.
1
2
3
4

VARIABLE
VALUE
Interpretation
X1
1.0
Thanalaeng is selected
X2
1.0
Thakhek is selected
X3
1.0
Savannakhet is selected
X4
0
Phakse is not selected
Objective function value = 0.30932

The model selected Thanalaeng, Thakhek and Savannakhet locations but did not selected Phakse.
This is consistent with AHP outputs. The value of deviations for each constraint provides ameasure for deviation from goal. The smaller the resulting deviation indicates better model
12

www.lindo.com

129accuracy and outcome. The values of deviational variables are shown in 6.20.
Table 6.20 Values of deviational variable
S. No.
1
2
3
4
5
6
7
8

Variable
D_RD_P
D_ENV_P
D_WT_N
D_COST_P
D_TRN_P
D_TIME_P
D_BDGT_N
D_FD_N

Value
0.170
0.159
0.203
0.215
0.222
0.223
6.0
300.0

The following deviation variables have 0 values:
D_TRN_N, D_RD_N, D_BDTG_P, D_FD_P, D_COST_N, D_TIME_N, D_ENV_N, D_WT_P
Based on the outcome, the goals corresponding to the regional development, environmental
impacts, transportation cost, intermodal transport connectivity and transportation time resulted inpositive deviation variables. This indicates that overachievement of the goals. The target values
for goals were set by adding the best two corresponding coefficients. This is due to the model
selected three locations. The deviation variables relating to budget, freight demand and AHP
weights constraints resulted in negative deviation variable, indicating underachievement. The
negative deviational variable for budget and freight demand are 6 and 300 respectively, whichcorresponds to the dry ports at Phakse- which was not selected by the GP model. Also, thenegative weight corresponds to the AHP weight of Phakse.
Thus the combined AHP-Goal Programming methodology can further enhance the prioritization
process by addition of other system and resource constraints. The difference of the two
approaches is: while AHP result is based on the preference of stakeholders; the AHP-GP utilizes
the outcome and enables to prioritize location considering other constraints, and the decision
makers can set the achievement level which is right hand side of equation representing goals.
6.5

Results and discussion

The modules 2 of the integrated methodology for location analysis of dry ports included AHP
and goal programming. It provided a framework to evaluate and analyze complex problem
involving both qualitative and quantitative information. The qualitative information received
from the respondents was converted to numerical values based on their judgments.
Interestingly, analysis of all three models returned the same results. The output from the AHP
showed high ranking for Thanalaeng, AHP-GP model also selected Thanalaeng, as well as
Thakhek and Savannakhet. This is more of the reflection of priority of policy makers and private
sector including freight forwarders. Savannakhet, which is located along the GMS East-West
Corridor, ranked second and this outcome support ongoing policy initiatives to promote
130development of the Seno-Savana Free Economic Zone (SSFEZ). The Third Mekong River
Bridge connecting Thakhek and Nakhon Phanom in Thailand was recently completed andopened for traffic on 11 November 2011. The opening of the bridge is expected to increase
further the importance of Thakhek dry port which was ranked third. Phakse scored lowest rank in
all three models. It could be because this is much to support local market and bilateral trade withThailand. Trade and connectivity with Cambodia is not well developed. It is also interesting to
see the outcome of the combined model (COMB) as well as government policy makers’ (GDM)
and private sector freight forwarders (PSFF) models returned same outcome.
The integrated methodology applied in the case of Laos showed consistent output and its ability
to provide decision makers views of various stakeholders. The overall high importance given to
the transport connectivity, regional development and environmental impacts shows the strengthof the analysis – which are mostly intangible –otherwise thus would have been overlooked insuch analysis. The goal programming outputs showed the consistency and strength of theanalysis. It can incorporate users (policy makers) defined goals and targets in the analysis. It alsoenabled to add other system constraints such as AHP weights, budget and freight demand. In theanalysis, the goals were set to select the alternative(s) that have combination of highest
preference of five criteria (the right hand side of the goals were set by adding two highest
weights of each criterion).
The consistency of feedback and analysis was noted while deriving local priorities of alternate
dry ports location based on criteria. The analysis also showed a particular preference or highpriority given to an evaluation criterion by separate stakeholders. For example, the analysis offeedback from the government policy makers showed the high priority assigned to the regional
economic development (weight 0.239), followed by costs and intermodal transport connectivity
and the transportation time (weight 0.124) received the least priority. Interestingly, the analysisof feedback from the freight forwarders showed the high priority to the environmental impacts(weight 0.309) followed by the regional economic development (weight 0.283).Transportation
time received the lowest priority (weight 0.130). The analysis of combined input showed highpreference to the regional economic development (0.255), followed by the environmental
impacts (0.209). The above results show that time and costs are not only criteria for analyzing
dry port locations; there are other important criteria that need to be considered. This shows somedeviation from general perception about cost and time.
The importance given to the environmental impacts by the freight forwarders could explain theircapacity to visualize the real impacts as they work on the field. It also could be that the
government policy makers are aware of concerns but they could not visualize the impacts of theirpolicies. This is one area needing attention to raise awareness of policy makers on the issues ofenvironmental impacts and climate change. This is also consistence with finding of the survey ofpolicy makers on climate change impacts.
The consistency of the evaluation and analysis was also noted while comparing preference ofalternate dry port location with respect to a criterion and sub-criterion. For example, Thanalaengreceived low score while synthesizing the land acquisition cost due to high land price inThanalaeng. While it received high score while synthesizing the intermodal transport
connectivity as it is connected by road, railway and inland waterways.
131It would be good to include many other evaluation criteria for the location analysis. Appendix-I
include a compiled list of factors/criteria and sub-criteria used for location analysis. But due tocomplexity of the analysis and the need for many questions, five criteria and 12 sub-criteria wereused. This also required 101 questions. One lesson from the survey was to pursue for feedback
while meeting a respondents-even by rescheduling appointment and extending survey duration if
necessary. In many cases, while approaching the potential respondent requested to sendquestionnaire by email with a promise to reply but many never replied - even after repeatedfollow-ups.
AHP-Goal programming allowed to look at the achievement of the conflicting goals. The fivecriteria used in AHP analysis were framed as objective of the optimization problem. Thus theobjective of the AHP-Goal programming was to select location that would minimize
transportation cost, transportation time and environmental impacts and maximizing theintermodal transport connectivity and regional economic development. In addition it helped toanalyze the real case in Laos considering the constraints of budget and freight demand of eachpotential location. The outcome was consistent with the AHP outputs and general belief of the
stakeholders. During discussion with stakeholders in Laos, they confirmed the priority assigned
and importance of Thanalaeng and Savannakhet.
6.6

Chapter summary

This chapter applied modules 2 of the integrated methodology and provided details on analysis
of primary data collected for the analysis of location of dry ports in Laos using AHP and goal
programming. The outcome of both analyses was consistent and Thanalaeng dry port near
Vientiane capital received highest priority among other alternative location. This also indicatesthe consistency of feedback of the government policy makers and private sector freight
forwarders in evaluating the dry port locations.
Among the four alternate locations, Thanalaeng is now used as a one of the origin/destination
location for international freight transport between Laos and Thailand. The otherorigin/destination location considered is Laem Chabang Port in Thailand. The next chapter
outlines the development of mode choice model and analysis.

132

CHAPTER 7ASSESSMENT OF FREIGHT MODAL SHIFT AND EMISSIONS
7.1

Introduction

This chapter outlines the data collection through the use of stated preference survey and analysisof data for estimation of a mode choice model. The freight mode shift is estimated by using theutility function and logit model. CO2 emissions as a result of the mode shift are estimated bybottom-up approach. In order to have a mode shift from road to rail the dry port at Thanalang has
be constructed. The life cycle emissions from the constriction of the dry port are assessed andcompared with the emissions reduction through mode shift. Finally, results are discussed and thechapter concludes with a summary.
7.2

Data collection

The location analysis of the dry ports in Laos prioritized Thanalaeng (Vientiane) among the four
alternate locations. Therefore, Thanalaeng is now used as a one of the origin/destination point forinternational freight transport between Laos and Thailand. The other origin/destination locationconsidered is Laem Chabang Port in Thailand. The following section outlines details of datacollection process, questionnaire development and stated preference survey.
7.2.1

Selection of route, modes, attributes and attributes levels

Currently goods are transported between Laos and Thailand by road using trucks. The railway
line between Thailand and Laos (Thanalaeng) is completed and currently passenger train is inoperation. There is a plan to develop a dry port/logistics centers in Thanalaeng and discussion aregoing on between Thailand and Laos to start freight train service in future. Therefore, the mode
choice options considered for the analysis are truck and train along the route Thanalaeng-Laem
Chabang Port/Laem Chabang Port- Thanalaeng.
Three type of attributes that can be considered for mode choice problems are:
(i)
(ii)
(iii)

Attributes relating to the mode: time, cost, reliability, safety etc;
Attribute relating to the shipment: type of goods, dangerous cargo, frequency etc.;
Attributes relating to the shipper: location, experience, bulk discount offered etc.

The most frequently used attributes for freight mode choice decisions are time, cost andreliability (punctuality) of service which are the attributes relating to the modes. It is good toconsider attributes relating to the shipment type but for our analysis standard containerized cargo
is considered. The shippers attribute relating to their experience in the logistics, whether they areable to make mode choice decision or not, their perception on the attributes are collected. These
are not used in the model but separately analyzed. The main objective of the mode choiceanalysis is to estimate future share of each mode once the dry ports is developed and once freightrail operation is available. Therefore, only attributes relating to the modes namely time, cost andpunctuality are considered. The total transportation cost includes vehicle operation cost, cost of133

fuel, driver and labour, loading, unloading and handling at ports and dry ports and in case ofrailway track access fee, handling of container and return of empty containers. In terms of totaltransportation time it includes time taken from port to dry ports including loading, unloading
time, driving time, time taken at the border crossing. Table 7.1 shows the route, modes, attributes
and level.
Table 7.1 Route, choice and attributes level
Route
Mode choice options
Modes attributes
Attributes level
7.2.2

Vientiane (Thanalaeng)- Laem Chabang Port
Truck and Train (Labeled)Total Transportation cost, Total Transport Time, Punctualityof service
Three for each attribute

Pilot survey to determine attributes levels

A pilot survey of freight forwarders in Laos and Thailand was done during 1-12 September 2011
to determine levels of each attributes and sensitivity of variation of attributes to assign at
different levels. 10 freight forwarders in Thailand and Laos, as well as State Railway of Thailand(SRT) were selected for the pilot survey. The respondents of the pilot survey were requested toprovide estimate of total transportation time and total transportation cost as well as break-down
for freight transport by truck and train between Vientiane (Thanalaeng) –Laem Chabang Port /Laem Chabang Port -Vientiane (Thanalaeng). The pilot survey also included questions on timeand cost sensitivity, providing variation of cost and time and punctuality variation range fortransportation by truck and train and asking whether they would you change your decision tochoose a mode. For punctuality range, the respondents were requested to their preference ofrange classification with option of time delays for high, medium and low punctuality.
7.2.2.1

Estimation of freight train speed

As there is no freight train in operation, in order to establish the value of travel time attribute of
freight train it is necessary to estimate average speed of freight train. The ESCAP study indicates
670 Km length from Vientiane to Bangkok port and cost of US $ 700 time taken by truck is from17.76 hours to 31.25 hours for transport from Vientiane to Bangkok. It however, notes different(higher) costs of transport from Bangkok- Vientiane estimated around US $ 1200-1500 (United
Nations 2003).
Another ESCAP study (United Nations 2001) mentions that commercial speed of freight block
trains would be around 65% of the running speed. The speed of Karachi Lahore block train was
20.3 km/hr, in Malaysia maximum speed of freight trains is allowed from 19 to 26 Km/hr. The
commercial speed of Port Klang-Bangkok train is 27 km/hr.
Analysis of various demonstration runs of container block trains by ESCAP gave following
average speed 22.5 km/hr (Tianjin-Ulaanbaatar, 2003), 35 Km/hr (Brest-Ulaanbaatar, 2004), 35
km/hr (Vostochny-Malacewicze, 2004) and 29.2 km/hr (Lianyunganag-Almaty, 2004). Also a
study shows that the average speed of 20 foot container train from Tashkent –Paris was 27.6
134

km/hr, Moscow- Paris was 33.1 km/hr (Raballand et al. 2005).
There is also regular container block train between Chittagong Port and Kamalapur ICD in
Dhaka, Bangladesh. It takes about 12 hours to travel 320 km which gives the average speed of
the block train as 26.67 km/hr. Between Laem Chabang Port and Lat Krabang ICD, 12 scheduled
container block trains operate in both direction. Depending on the time of departure, the total
time taken by the block train varies from 3 to 4 hours for 126 km 13. Taking average time, thisgives average speed of 36 km/hr.
From above, it can be assumed that improved railway freight service in Thailand would have an
average speed of 35 km/hr and corresponding time of 22 hour is considered for the freight train
service between Laem Chabang and Thanalaeng (Vientiane). Considering 4 hour for loading,unloading time and border checking and clearance process, 26 hours would be the total travel
time for freight train.
7.2.2.2

Values of attributes and levels

The values and levels of attributes for mode choice survey are determined based on the feedback
received on the pilot survey, interview and discussion with the freight forwarders and railway
officials. It also involved collection of data on total freight time and transportation cost of bothrail and truck mode transport between Vientiane and Laem Chabang. The base case scenario of
total transportation cost and time for one TEU of standard cargo by truck is considered as US $1400 and 14 hours, and US $ 800 and time 26 hours by train.
The transportation cost by truck and train is increased by a step $200 to estimate another levels,
while the time for truck is increased in a step of two hours and that for train in a step of 4 hours
are increased and decreased simply because the total estimated travel time of freight train isalmost double to that of truck. In case of punctuality, delivery within 0-8 hours of estimated time
is considered as high punctuality, and for other level increased in step of 8 hours for both modes.
Table 7.2 shows the attributes and levels for the SP design.
Table 7.2 Attribute levels of choices
Attributes
Total transport cost

Truck
Level 1: US $ 1400
Level 2: US$ 1600
Level 3: US$ 1800
Total transportation time Level 1: 14 Hours
Level 2: 16 Hours
Level 3: 18 Hours
Punctuality (Chances of Level 1: High (0-8 Hours)delivery within hours)
Level 2: Medium (9-16 Hours)
Level 3: Low(17-24 Hours)

13

http:/www.laemchabangport.com/lcp/internet/en/sch.train.php

135

Train
Level 1: US$ 800
Level 2: US$ 1000
Level 3: US$ 1200
Level 1: 22 Hours
Level 2: 26 Hours
Level 3: 30 Hours
Level 1: High (0-8 Hours)
Level 2: Medium (9-16 Hours)
Level 3: Low(17-24 Hours)7.2.3

Design of orthogonal choice experiment

As there are two choices (M=2) and three Attributes (A=3), the degree of freedom is 6+1=7. This
gives minimum treatment combination required. As there are two choices (M=2), three Attributes(A=3) and three levels (L=3), it can generate 32X3 = 243 choices. It is not possible to present allthese choices to the potential respondents. Therefore, fractional factorial design is employed.
Literatures further suggest that maximum choice options that can be offered are 16.
The combination of attributes can be presented to the respondents to estimate the parameters andutility of each mode. The minimum number of treatment combination is necessary for fractional
factorial design. Balance orthogonal design is generated by SPSS. A balanced design has each
attribute level occurring equally often, and minimizes variance in the parameter estimation(Kuhfeld 2009). In orthogonal fractional factorial design, the parameters estimates in linear
model are uncorrelated, which means that the attributes of the design are statistically independentof each other.
Table 7.3 shows factor factorial orthogonal balanced design generated by using SPSS. It
generated 18 scenarios.
Table 7.3 Orthogonal and balanced choice sets generated by SPSS
S. No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

7.2.4

Cost
1800
1400
1800
1400
1600
1800
1600
1600
1400
1800
1400
1400
1800
1400
1600
1800
1600
1600

Truck
Time
Punctuality
16
High
18
Medium
18
Low
16
Low
14
High
16
Medium18
Medium14
Medium14
Low
14
Medium16
Medium
18
High
14
Low
14
High
18
Low
18
High
16
Low
16
High

Cost
1000
1000
800
800
800
800
800
1200
1000
1000
1200
1200
1200
800
1000
1200
1200
1000

Train
Time
22
22
26
26
30
30
22
26
30
26
30
26
22
22
30
30
22
26

Punctuality
High
Low
High
Low
Low
MediumMediumHigh
MediumLow
High
MediumMedium
High
High
Low
Low
MediumDesign
A
B
A
B
A
A
B
A
B
A
B
B
A
B
B
A
B
A

Development of choice sets and SP questionnaire

Drawing on the experience of AHP survey, in order to ensure more feedbacks and to increase
reliability of feedbacks the 18 scenarios are divided into two sets of questionnaire each with 9
choice scenarios. The 9 scenarios to be included in design A and B were randomly selected as136show in the last column of Table 7.3. The number of scenario to each respondent can range from
1 to 32 (Boxall et al. 1996). Johnson and Devousges (1997) mentioned that up to 26 sets forpaired comparison have been presented to the respondents. In the case of research, one
questionnaire contains 9 scenarios. Truck and train options are mentioned (labeled) in thequestionnaire. In the questionnaire, the value of punctuality was included high (0-8 hours),
medium (9-16 hours) and low (17-24 hours). Table 7.4 and 7.5 show the choice scenarios
included in questionnaire design A and B respectively.
Table 7.4 Scenarios for questionnaire design A
S. No.
1
2
3
4
5
6
7
8
9

Cost
1800
1800
1600
1800
1600
1800
1800
1800
1600

Time

Truck
Punctuality
16
High
18
Low
14
High
16
Medium14
Medium14
Medium
14
Low
18
High
16
High

Cost
1000
800
800
800
1200
1000
1200
1200
1000

Train
Time
22
26
30
30
26
26
22
30
26

Punctuality
High
High
Low
MediumHigh
Low
MediumLow
MediumTable 7.5 Scenarios for questionnaire design B
S. No.
1
2
3
4
5
6
7
8
9

Cost
1400
1400
1600
1400
1400
1400
1400
1600
1600

Truck
Time
Punctuality
18
Medium16
Low
18
Medium14
Low
16
Medium
18
High
14
High
18
Low
16
Low

Cost
1000
800
800
1000
1200
1200
800
1000
1200

Train
Time
22
26
22
30
30
26
22
30
22

Punctuality
Low
Low
MediumMediumHigh
Medium
High
High
Low

Each questionnaire contained brief introduction of the survey, purpose, and future scenarios. Part
I of the questionnaire presented 9 scenarios in the format shown in Figure 7.1. Part II of thequestionnaire contained 9 questions seeking details of the respondent’s gender, age, education,
experience in the logistics sector, role in making mode choice decisions, perception on
importance of time, cost and punctuality, would they consider using freight train if available, andviews on importance of dry ports/logistics centre in promoting mode shift and intermodaltransport. This also provides a break of momentum from choosing scenarios presented – if the
respondent agreed to provide feedback to the other set of questionnaire. Both sets ofquestionnaire design A and Design B are attached as Appendix-IV.

137

Attributes
Mode
Travel Time
Transportation cost/TEU
Punctuality

Truck
Train
16 Hours
26 hours
US$ 1600
US $ 1000
High (0-8 Hrs) Medium
(9-16
hrs)

Which option would you choose(please select one box)
Figure 7.1 Format of the choice scenarios presented in the questionnaire
7.2.5
7.2 5.1

Stated preference survey
SP survey of freight forwarders in Thailand

During face to face interview the respondents were asked to consider transportation of standard
and normal one TEU container – non- hazardous and non-dangerous cargo. The face to facesurvey in Thailand was conducted during the Thailand International Logistics Fair held in
Bangkok during 23 to 25 September 2011. It provided opportunity to meet and interview many
freight forwards at one location. Total 16 responses were received during the logistics fair. Somefreight forwarders requested to send questionnaire by email. The questionnaires were sent by
email as well and were followed-up through repeated reminders and calls. Some replies werereceived by email.
Second round of face to face interview was conducted by visiting freight forwarders office in
Bangkok during 13 - 20 October 2011 and after calling for appointments, this time also somerequested by email and both set of design A and B was sent to the freight forwarders. Total 23
completed surveys were collected from Thailand.
7.2.5.2

SP survey of freight forwarders in Laem Chabang Port

A survey of freight forwarders in Laem Chabang area and a visit to the Port Authority ofThailand was conducted on 7 November 2011. During the visit to the block train station yard,
port facilities were observed and discussion was held with the Laem Chabang Port officials.
Figure 7.2 shows the starting point of the block trains to the Lat Krabang ICD and a view of theLaem Chabang port. 12 scheduled container block train leaves Laem Chabang port for Lat
Krabang ICD and 12 block trains returns from ICD. Depending on the time of departure the total
time taken by the block train varies from 3 to 4 hours for 126 km. Also, face to face interview
were conducted with freight forwarders. Total 10 responses from 5 freight forwarders werereceived including 2 received by email.

138

Figure 7.2 Block train to Lat Krabang ICD and Laem Chabang Port
7.2.5.3

SP survey of freight forwarders in Laos

Contact was maintained with LIFFA to help for the survey in survey with a request to seek
appointments with freight forwarders. Questionnaire survey in Vientiane was undertaken during
20-23 October 2011. Questionnaires were sent to all LIFFA members prior to the visit. Interview
surveys were carried out on 21 and 22 October through visiting freight forwarders office.
Telephone calls were placed again to confirm the appointments and seek new appointments.
Some freight forwarders were out of Vientiane and they informed that they will reply to email
request. Emails were sent to them. A local assisted in visits and translation, whenever required.
During survey, nine face to face interviews returned 18 replies (both set A and B). 8 replies from
4 freight forwarders were received by email. Thus total responses were from 13 freight forwarder(out of total 22 members of LIFFA). These represent about 59% replies from potential populationin Laos.
7.2.5.4

Summary of stated preference survey

Table 7.6 shows details of response received from the SP survey and valid replies and data sets.
Total 59 questionnaires were returned from 34 freight forwarders that included 33 replies fromThailand and 26 replies from Laos. This gives total data sets of 59X9= 531.
Table 7.6 Summary of response received on SP Survey
Surveylocation
Thailand
Laos
Total

No of freight Number offorwarders
questionnaires
replying
returned
21
33
13
26
34
59

Total data sets
33X9=297
26X9=234
531

2 questionnaires were incomplete and there were 14 biased replies towards a mode, where a
respondent selected only one mode in whole questionnaire. These were not included in analysis
and total data set used for analysis is 43X9=387.
139

7.2.6

Limitation of the SP survey

The flood situation in Thailand during October –November 2011 constrained the outcome of thesurvey and limited access and travel to Lat Krabang and opportunity to meet many freight
forwarders. As indicated above many freight forwarders in Laos and Thailand requested to send
the questionnaire by email and promised feedback. But the email response was not as anticipatedas only few replies came by emails even after repeated email reminder as well as telephone calls.
Some bias of freight forwarders owning fleet of truck was noted. One of the important aspects offreight transport by train was raised during the survey in Laos. It is - why passenger and freighttrain cannot be combined? The example cited was – planning a train’s half of the wagon/bogie
for passenger and half of the bogie/wagon for fright. Was it the question of security? The view
was this could make freight transport feasible when there is not enough freight volume to start
regular freight trains.
Another aspect raised during the interview was relating to the truck owners lobbying power. In
some case they could have strong lobbying power that can influence government logistics
policies that are favourable to truck at the cost of rail mode. During interview, many freight
forwarders mentioned that the choice also depends on the traders, manufacturers and clients andsuggested to seek their views as well.
7.2.7

Interview with policy makers and freight forwarders

In addition to the structured questionnaire survey as outlined above, during the course of
research in depth unstructured interviews and discussions were held with policy makers,
international freight forwarders (TIFFA and LIFFA), Thai Ship-owners Association and transport
professionals in Laos and Thailand as well as at international forums. The main objectives ofthese interviews and discussion were to understand their future transportation and logistics plan,
there perception on modal shift, roles of private sector and government in integrating transportmodes, expectation of private sector in facilitation of international import and export. Further, indepth discussion was held with the officials of State Railway of Thailand, Marketing Department
to understand their plan of starting freight train service, future expansion of railways to otherborder of Laos.
7.2.8

Outcome of the stated preference survey

The respondents were requested to select a mode in various mode choice scenarios. The
respondents were also asked general questions about themselves and related to their experiencein the logistics industry and making mode choice decisions. The gender, age and distribution of
the respondents as well as their feedback are summarized below.
(i) Gender and age of the respondents: Figure 7.3 shows the age, gender and experience of the
respondents. Majority of respondents were male representing about 80% of the response
received. This may be due to logistics industries are dominantly managed by men. It indicates theneed to encourage women to pursue careers in the logistic industry. In terms of age group,
majority fall in the category of 31-40 years and 51-60 years category. Also, the majority of140

respondents were with more than 15 years of logistics experience (47%), followed by thosehaving experience up to 5 years. This can attribute to the reliability of responses owing to theirexperience in making mode choice decisions.
Experineces of the respondents
12

18
16
14
12
10
8
6
4
2
0

Distribution of age and gender of the
respondents
Male

Number10

Female

8
6
4
2
0

0-5

6-10

11-15

16>

<30

31-40

Experience, Years

41-50
51-60
Age group, Years

61>

Figure 7.3 Age, gender and experience of the respondents of SP survey(ii) Do you make mode choice decisions and consider using railway for freight? Figure 7.4
shows the respondent’s replies to questions on whether they would make mode choice decisions
and consider using railway for freight if regular service is available. 57% of the respondents
replied that make mode choice decisions and 86% of the respondents said that they would use
railway for freight transport. This clearly shows the need to introduce the freight train services.
Further, during discussions many respondents raised the issues of possibility of combining
passenger and freight train to start freight service as early as possible. This is of particularimportance as the current freight volume may not be enough for full container block train with
30-40 containers.
Mode Choice and Rail Use

Mode choicedecisions

Yes
No
NA

Use Rail

0%

20%

40%

60%

80%

100%

Figure 7.4 Mode choice decision and railway use 14
14

NA=No answer

141

(iii) Importance of time, cost and reliability: The respondents were also asked to rateimportance of three attributes that can influence mode choice decisions. As there were three
attributes, the respondents were asked to rate in order of importance 1, 2 and 3. Figure 7.5 shows
the respondents perception on the importance of transportation cost, transportation time andreliability in making mode choice decision. The rating is converted to a weighted average scorein a three points scale. The transportation cost scored high with 2.55, transportation time stoodsecond with 2.31 and reliability stood third with 1.62 score. This clearly indicates the importanceof cost, time and reliability in making mode choice decisions.
Respondents perception on the importance of attributes

Reliability

1.62

Tim e

2.23

Cost

2.55

0

0.5

1

1.5

2

2.5

3

Figure 7.5 Respondents perception on rating of cost, time and reliability
Respondents further mentioned that other factors important for mode choice decisions are
insurance, damage to cargoes, safety, delivery, train schedule, security, trucking and tracking
system and connectivity to other modes of transport.
(iv) Importance of logistics centres/dry ports: The respondents highly rated the importance ofdry ports for encouraging intermodal transport and modal shift. On a five point scale it received
aggregate the score of 3.77. This indicates that the logistics centres and dry ports cansignificantly influence mode choice decisions as they integrate and connect different modes oftransport are connected/integrated thus providing modal shift opportunities.
7.3

Mode choice model

The data collected from freight forwarders in Laos and Thailand is tabulated and analyzed toestimate mode choice parameters. Module 3 of the integrated methodology is used for analysis.
Discreet choice model with two choices options are used. All three variables are considered as
generic parameters for total time, costs and reliability (delay) are estimated. A model constant isestimated for truck mode.
7.3.1

Estimation of model parameters

The attributes and levels have been limited to three and so as not to overwhelm the respondents
with too many choices. The collected data are tabulated in NLOGIT format. There are options toestimate mode specific constants and generic constant. NLOGIT/ LIMDEP software (Greene142

2008) was used to estimate the model. Among the total 59 survey response received (total 531
data sets) 43 valid responses 15 with total data sets of 387 are used in analysis.
Initially parameter estimation was done including alternate specific constant (ASC) for truckmode and generic parameters corresponding to time, cost and reliability of both modes truck andtrain. The utility functions are expressed as shown equations 7.11 and 7.12.
U(TRUCK) = A+B*TIME+C*COST+D*DELAY(7.11)U(TRAIN) =(7.12)B*TIME+C*COST+D*DELAY

Where,U(TRUCK)- observed utility value of truck
U(TRAIN) – observed utility value of train
TIME- total transportation time
COST- total transportation cost
DELAY- reliability of truck service (measured in average delay to the scheduled time)
A is mode specific constant for truck
B is generic parameter corresponding to transportation time
C is generic parameter corresponding to transportation cost
D is generic parameter corresponding to reliability (delay) of service.
While estimating three parameters as generic variables, the results showed the significance andnegative signs for all parameters for cost, time and delay as expected, but the alternate specificconstant for truck was not statistically significant (t-value-0.222 and p-value-0.8245) andreturned much higher error as shown in Table 7.7. As constant term is important for binomial
model than can explain errors terms that is not covered by the attributes considered for the model
formulation. Further, the negative sign of the constant term indicated that some preference to thetrain mode given all other condition remaining the same.
Table 7.7 Estimated generic model parameters
Variable
ASC_TRUCK (A)Coefficient-0.0953

Standard Error
0.4298t-value-0.222

P-value
0.8245

TIME (B)-0.1691

0.0320-5.2820.0000COST (C)-0.00280.0005-5.2410.0000

DELAY(D)-0.0660

0.0136-4.8530.0000

Number of observation= 387
Log likely hood function (L) = -227.1740
Log likely hood only constant (L0) = -268.1846
McFadden likelihood ratio index (ρ2M) = 1-Log L/Log L0 = 0.1529
15

2 incomplete and 14 biased replies towards a mode, where respondent selected only one mode in wholequestionnaire were not included.

143

Adjusted likelihood ratio (ρ2M) =0.1441
Chi-squared (χ2)
= 82.0214
The model could be used omitting the insignificant mode specific constant (A_TRUCK). This
would mean that the responded did not consider the other unobserved factors while selecting amode or they considered other factors however their influence on mode selection decision was
insignificant. Further, as currently the mode share of truck is 100%, a positive sign of the mode
specific constant for truck is normally expected.
Therefore, in order to increase the reliability of the model, the data are again analyzed to estimate
alternative specific constant and different mode specific parameters. The following utility
equations 7.13 and 7.14 are defined in the NLOGIT:U(TRUCK) = A1+B1*TIME+C1*COST+D1*DELAY(7.13)U(TRAIN) =(7.14)

B2*TIME+C2*COST+D2*DELAY

Where,U(TRUCK)- observed utility value of truck
U(TRAIN) – observed utility value of train
TIME- total transportation time
COST- total transportation cost
DELAY- reliability of truck service (measured in average delay to the scheduled time)
A1 is mode specific constant for truck
B1 is mode specific parameter corresponding to transportation time of truck
C1 is mode specific parameter corresponding to transportation cost of truck
D1 is mode specific parameter corresponding to reliability (delay) of truck service.
B2 is mode specific parameter corresponding to transportation time of train
C2 is mode specific parameter corresponding to transportation cost of train
D2 is mode specific parameter corresponding to reliability (delay) of train service.
In this case, the results show that the significance of alternate specific constant and otherparameters is greatly improved and estimated parameters values show significance at 95%
indicated by t-values. Only, the parameter for the cost of truck (C1) shows less significance thanother variables but still acceptable at 89% level of significance.

144

Table 7.8 Estimated model parameters
Variable

Coefficientt -value

p-value-4.6704

Standard
Error
2.1335

ASC_TRUCK (A1)

-2.1890.0286

TIME_TRUCK (B1)

-0.13650.0740-1.8440.0652

COST_TRUCK (C1)-0.00110.0007-1.5650.1175

DELAY_TRUCK (D1)

-0.10150.0187-5.4130.0000

TIME_TRAIN (B2)

-0.1791

0.0355-5.0440.0000

COST_TRAIN (C2)DELAY_TRAIN (D2)

-0.0047-0.03860.00080.0182-6.040-2.1140.00000.0345

Number of observation=387
Log likely hood function (L) = -217.3192
Log likely hood only constant (L0) = -268.1846
McFadden likelihood ratio index (ρ2M) = 1-Log L/Log L0 = 0.1897
Adjusted likelihood ratio (ρ2M) = 0.1747
Chi-squared (χ2) = 101.7309
We can see from the Table 7.8, all mode specific parameters are significant and have negative
signs as expected, indicating an inverse relationship. An increase in values of cost, time anddelay would lead to decrees in utility of that mode - meaning the chances of choosing a mode
decreases with increase in these parameters. Further, the negative sign of the mode specificconstant for truck indicates that in given situation (the dry port and rail service available) the
respondents have some preference to train compared to truck. However, due to existing situationa positive sign would have explained the existing situation of 100% truck share and preference
towards it. The negative sign of the constant could reflect the respondent’s preference for the
train as 86% of the respondents have said they would consider using train if freight train service
is available. Further, while selecting a mode in a given scenario, the cumulative selection of railmode was 52%. Also, in binary logit models the goodness of fit is of secondary importance(Gujarati and Porter 2009), the expected signs of regression coefficients and their statistical andpractical significance are more important. Greene (2011) 16 also advised that “The rho-squared is
not a fit measure. It is simply a function based on how much the log likelihood changes when
you add variables to a model that only includes a constant term. It is common for models withlarge numbers of variables that are highly significant to have quite low values of this statistic.”
Further, in order to compare the generic model (Table 7.7) and the model with mode specificparameters (Table 7.8), a chi-squared test was conducted.
Difference in χ2 of two models=101.73-82.02= 19.71
Difference in degree of freedom (df)=3
16

Personal email communication with Prof. W. Greene on NLOGIT output, 8 November 2011.

145

For 3 degree of freedom and p-value of 0.001, the χ2 value is 16.27; this indicates that the test χ2
statistics is significant at more than 99.9% level. Thus, we can conclude that the model withmode specific parameters fit the data significantly better than the generic model. Therefore, thelater model is used for the further analysis.
The utility functions are given by equations 7.15 and 7.16.
U(TRUCK)=-4.6704-0.1365*TIME-0.0011*COST-0.1015*DELAY(7.15)U(TRAIN) = - 0.0854*TIME-0.0047*COST-0.0386*DELAY(7.16)

7.3.2

Estimation of probability of choosing a mode

The probability of choosing the rail mode is estimated using the logit model.

P(rail ) =exp(Vrail )exp(Vrail ) + exp(Vroad )(7.17)The probability of choosing a mode depends on the attributes values selected. From the pilot
study for the base case, the transportation on the Laem Chabang –Thanalaeng route by truck
takes 14 hours and the cost is US $1400. Similarly, the time taken by freight train is estimated as
26 hours considering total travel time including loading, unloading and border checking and thecost as US $ 800. JICA (2011) also estimated 48 hours for a total round trip. Assuming there isno delay for both modes in base case scenario the resulting utility values are:
U(TRUCK)=-4.6704-0.1365*14 -0.0011*1400-0.1015*0 = - 8.4493
U(TRAIN) = - 0.0854*26-0.0047*800-0.0386*0 = - 8.1758
The resulting mode share is;P(Truck ) =exp(−8.4493)
exp(−8.4493) + exp(−8.1758)

P(Truck) = 56.8%
P(Train) =1-0.568= 43.2%
This indicates reasonable estimate of mode share by using the model 17 with mode specificparameters. During the survey many respondents have indicated that they would choose railway
if service is available. Further, the JICA study had estimated the share of railway to be 49% in
17

Use of the generic model by omitting the non-significant mode specific constant for truck estimated 58.6% mode
for truck and 41.4% train share in base case scenario. This is very close to the mode share estimate by the second
model.

146

2025 using empirical study from Delhi-Mumbai Freight Corridor (JICA 2011) which may not bevery relevant in here. Based on the survey, the results indicates that the freight forwarders havehigh expectation from future freight railway service as the estimated mode share is slightly lessthan 50% which currently is being transported 100% by trucks.
Tsamboulas and Moraitis (2008) developed a methodology for estimating fright mode shift of anintermodal corridor and applied it to the transportation corridor from the Black Sea to the Greek
port. The mode share attracted by the intermodal corridor was 21%, 22% and 50% depending on
the combination of train and maritime route considered. Feo-Valero et al. (2011b) modelled
choice between road only mode and road and rail transport mode for the inland leg transport
from port of Valencia and Madrid in Spain considering time, cost and reliability and found thatparameters are generic for both modes and show preference of using road.
7.3.3

Elasticity of time and cost

As indicated by equation 7.15 and 7.16 the utility value of a mode depends on the values of
attributes. Thus, the mode share also depends on utility values of the modes. As the mode shareis estimated for future scenarios, the following scenarios are considered and mode shareestimated. The effect on mode share due to the percentage variation in transportation cost,transportation time and delay are considered. Table 7.9 shows the level of change of theattributes.
Table 7.9 Attributes and level of changes for determining elasticity
Attributes
Total Cost
Total Time
Cost and Time

Mode
Truck
Train
Truck
Train
Truck
Train

Reliability

Truck
Train

-10%
-10%
-10%
-10%
-10%C,+10%T-10%C,
+10%T
-10%
-10%

Level of changes
-20%
10%
-20%
10%
-20%
10%
-20%
10%
-20%C,
10%C,
+20%T
-10%T
-20%C,
10%C,
+20%T
-10%T
-20%
10%
-20%
10%

20%
20%
20%
20%
20%C, 20%T
20%C, 20%T
20%
20%

All of the above level of changes on time and cost are not practical. They have been arbitrarily
chosen to draw the elasticity graphs. While estimating resulting CO2 emission, only the practicalvalues are taken that range increase and decrease in 10% variation in time and cost. While
increase in 10% cost and time for the freight transport by train and truck in the route is possible.
This could be due to decrease in speed of truck and train, increase in handling and loading timeat port and dry port. Also delay due to poor condition of road and railway tracks and bordercrossing procedure. Among these, some of these transport operators do not have control overcondition of route and border clearance so these are external factors. While cost could increase
due to increase in fuel price, driver’s cost, labour cost that affect container and cargo handling at
port and dry ports. Another way to analyze is using existing vehicle operation cost (VOC) model
for both modes.
147

Reduction of cost could be possible if the railway uses electric traction. This would also reduceaverage emission factors. Other way to reduce cost would be to secure bulk transportation
contracts and ensuring of cargo loads in both transport legs can reduce overhead and have effecton price. As railways is more energy efficient and emit fewer emissions than truck- one way to
influence the mode choice decision is to provide subsidies to railways through reduced fuel pricefor railway. This could reduce the cost of transportation make railway more attractive. Such
practice has been used and being used in Europe.
For other value of variation in time and cost, the corresponding variation on mode shift can be
estimated by taking direct reading from the elasticity graphs.
7.3.3.1

Variation in mode share due to cost variation

The model has mode specific parameters; therefore, the elasticity was conducted to look at theeffect of percentage cost variation of truck and train on the mode share. The results show that a
10% reduction of cost of truck mode would increase its mode share by 3.9% thereby decrease therail share by same amount. Similarly, 10% increase in the transportation cost of truck would
reduce its mode share by 3.9%. In case of train a 10% reduction in transport cost would increase
its mode share by 9.4% whereas a 10% increase in transportation cost would reduce its share by
9%. Figure 7.6 shows the elasticity graph which is linear.

Elasticity of cost variation
25%

Variation in Mode Shift

20%

TRUCK

18.70%

TRAIN

15%
10%
5%

9.40%
7.60%

3.90%

0%

0

0

-3.90%-7.90%-5%-10%-9.00%-15%-16.90%

-20%
-20%

-10%

0%

10%

20%

Variation in cost
Figure 7.6 Elasticity of mode share due to cost variation148

7.3.3.2

Variation in mode share due to time variation

Variation in mode share

The effect of variation in total transportation time on mode share was also evaluated. The results
show that a 10% reduction of total transportation time of truck would increase its mode share by
4.6%, thereby decreasing the rail share by same amount. Similarly, 10% increase in thetransportation time of truck would reduce its mode share by 4.7%. In case of train, a 10%
reduction in transportation time would increase its mode share by 11.6% whereas a 10% increasein transportation cost would reduce its share by 10.9%. Figure 7.7 shows the elasticity graph ofthe variation in time.

25%
20%
15%
10%
5%
0%
-5%
-10%
-15%
-20%
-25%

Elasticity of time variation
22.70%

TRUCK

TRAIN

11.60%
9.00%
4.60%

0.00%

-4.70%-9.50%-10.90%-20.10%

-20%

-10%

0%

Variation in time

10%

20%

Figure 7.7 Elasticity of mode share with variation in transportation time
7.3.3.3

Variation in mode share due to cost and time

The above cases looked at the elasticity of the cost and time independently on the mode share.
There is a tradeoff between cost and time. The total transportation time can be reduced by using
reliable and urgent service by paying more. Similarly, if the cost is a concern and a customer
wants transportation cost to be low then shipment transportation time would be more as the
shipment would be assigned a low priority. To evaluate the trade off, a combination of time andcost variation was evaluated to see its effect on the mode share. The results were not muchencouraging. A combination of 10% increase in cost of truck transport and 10% reduction intransport time showed only 0.8% increase in mode share of truck. This is almost like a 10%
tradeoff between cost and time in case of truck mode. Similarly, a 10% decrease in transportation
cost of train and 10% increase in time showed a decrease of 2.1% mode share of train. This
indicates that in case train time is more sensitive than cost for mode share. Figure 7.8 shows theelasticity of combined time and cots variations.

149

Variation in Mode share

Elasticity of Cost and Time

5%
4%
3%
2%
1%
0%
-1%
-2%
-3%
-4%
-5%

4.30%

TRUCK

TRAIN

2.10%
1.50%
0.80%

0.00%

-0.80%-1.60%-2.10%-4.20%

20%C,-20%T

10%C,-10%T
0%
10%T, -10%C
Variation in Cost and Time

20%T, -20%C

Figure 7.8 Elasticity of mode share with cost and time variation
7.3.3.4

Variation in mode share due to reliability

The effect of reliability measured by delay in scheduled delivery of cargo on mode share wasalso evaluated. The results show that a decrease in reliability (delay by 1.4 hours) of truck
transport would reduce its mode share by 3.5% thereby decrease the rail share by same amount.
Similarly, increase in reliability of the truck mode (early arrival by 1.4 hours) would increase its
mode share by 3.4%. In case of train a 10% reduction in reliability of the mode would decrease
its mode share by 2.4% whereas a 10% increase in reliability (early arrival) would increase its
share by 2.5%. Figure 7.9 shows the elasticity of reliability (delay).

Variation in Mode Share8%

Effect of Reliability on Mode Share
6.80%

6%

TRUCK

3.40%

4%

5.00%

2%
0%

0.00%
-2.40%

-2%
-4%

2.50%

-4.80%-3.50%-6%-8%-7.10%
-20%

-10%

0%

10%

20%

Relaibility
Figure 7.9 Elasticity of mode share with variation in reliability
1507.3.3.5

Results of elasticity analysis

From the above analysis, it can be seen that the transportation time is more elastic than thetransportation cost. A 10% increase in truck time led to a reduction of 4.7% truck share while
10% increase in transportation cost of truck led to 3.9% reduction in mode share. Similarly, 10%
increase in transportation time of train led to 10.9% decrease in its mode share where as a 10%
increase in transportation cost of train led to a reduction 9% mode share. Also, while comparing
modes, freight train is more sensitive to cost and time variation than truck transport. The
business as usual (BAU) scenario represents the case if the dry port and freight rail service are
not developed, and there would be no modal shift and truck would continue to carry 100% ofinternational freight. The base case (SC-1) represents the mode share estimated based on cost andtime of each modes determined by the pilot study. The following Table 7.10 summarizes theresults of elasticity analysis.
Table 7.10 Mode share from elasticity analysis
Scenario
BAU
SC-1
SC-2
SC-3
SC-4
SC-5
SC-6
SC-7
SC-8
SC-9

7.4

Scenario detail
Business as usualBase case
10% increase in cost of truck transport
10% decrease in cost of truck transport
10% increase in cost of train transport
10% decrease in cost of train transport
10% increase in time of truck transport
10% decrease in time of truck transport
10% increase in time of train transport
10% decrease in time of train transport

Mode share
Truck
Train
100%
0%
56.8%
43.2%
52.8%
47.2%
60.7%
39.3%
65.8%
34.2%
47.4%
52.6%
52.1%
47.9%
61.4%
38.6%
67.7%
32.3%
45.2%
54.8%

Assessment of CO2 emissions from operation

The types of goods vehicles and train used in Laos are similar to that of Thailand. Further as the
majority of Thanalaeng- Laem Chabang route is in Thailand, the emissions factor applied in
Thailand are used for assessment of emissions. The emission factors are derived based on theinformation provided by the Ministry Transport, Thailand (Chamroon 2011). Using the factor of2328 gm CO2 emissions/litre, the derived emission factor for freight train and truck is shown in
Table 7.11.
Table 7.11 Emission factors
Mode
Truck
Freight Train

Emission factors
93.12 gm /ton-km
27.4 gm /ton-km

The above emission factors are comparable to similar factors in Europe (92 gm /ton-km for
Heavy Duty Vehicle and 22.8 gm /ton-km for rail) and Canada (114 gm /ton-km for truck and17.85 gm /ton-km for train). ADB’s TEEMP project uses 80 grams/ton-km for roads and 25
gm/ton-km for trains (ADB 2011). For the purpose of comparison the emission factor for151

commercial truck in Japan is 150 gm/ton-km and that for freight train is 20 g/ton-km. This is due
to use of more energy efficient electric train and the higher factor for trucks could be due to useof smaller trucks for delivery and low load factor.
Table 7.12 shows the forecast of freight volume at Thanalaeng dry port (JICA 2011). The freight
demands are estimated based on 2009 values, the total import and export through Vientiane is1.026 million tons. The estimates are based on the annual GDP growth of 8.0% during 2011 to2020 and population growth of 1.7%. Applying the same principle, freight volumes for 2011 and2020 are estimated as shown in Table 7.12. It was also estimated that 32% of general cargo
would be transported in container by 2025.
Table 7.12 Forecasted freight demand at Thanalaeng
Year
2009
2011
2015
2020
2025

Cargo
Demand, MT
2126802480704265009197801413060

Utilizing the above emission factors and mode share scenarios outlined in Table 7.23, theassessment of CO2 emissions for the estimated international traffic to/from Thanalaeng is done.
While estimating the emissions as the total trade with Thailand is 70% and the transportation ofimport and export is considered to Bangkok and other 30% of international transport would
originate/terminate in Laem Chabang port. The length of Thanalaeng-Nongkhai railway line is
3.5 Km, Nongkhai- Bangkok is 624 Km and Bangkok-Laem Chabang line is 140 km (SRT2011) 18. In case of road, the length of Thanalaeng-Bangkok is 622 km and Thanalaeng -Laem
Chabang is 771 Km (ESCAP 2008) 19. Table 7.13 shows the road and rail distance used foranalysisTable 7.13 Road and rail distance from port to dry port
S. No.
1
2

Origin/Destination
Thanalaeng – Bangkok
Thanalaeng – Laem ChabangRoad
622 km771 kmRailway
628 km768 kmTable 7.14 shows the assessment of CO2 emissions for various scenarios shown in Table 7.10.

18
19

Railway Network, State Railway of Thailand, www.railway.co.th/English/network.asp (accessed on 15 October 2011)
Asian Highway Database, 2008, ESCAP

152

Table 7.14 Assessment of CO2 emissions (in tons)

Scenarios
BAU

Reduction in
CO2 Emission emissions compared2015 (MT)to BAU
26478
0SC-1 (Base)
SC-2

18406
17658

30.5%
33.3%

SC-3
SC-4
SC-5
SC-6
SC-7
SC-8
SC-9

19134
20087
16649
17527
19265
20442
16238

27.7%
24.1%
37.1%
33.8%
27.2%
22.8%
38.7%

The above assessment shows that 43.2% fright mode shift to railways (base case) resulted in
30.5% less CO2 emissions than business as usual (BAU) scenario 20, while scenario 9 with railmode share of 54.8% freight mode shift to railways resulted in 38.7% CO2 emissions reduction
than BAU. Scenario 8 results in 22.8% CO2 emission reduction which is least among theevaluated scenario that corresponds to a mode shift of 32.3% to railways.
The above assessment seems reasonable and valid based on the outcome similar research
conducted earlier. For example, the energy saving from the use of intermodal transport wasestimated as 25% in Thailand (Hanaoka et al. 2011), use of freight train for transport from aseaport to a port in Sweden resulted in 25% emission savings (Roso 2007), Liao et al. (2010)
showed a 60% savings from use of intermodal transport (truck and coastal shipping) instead oftruck only transport in Taiwan and Patterson et al. (2008) demonstrated that a reduction of freight
CO2 emissions by 16% (on average) 16% and 50% (at best case scenario) was possible by use ofintermodal transport services in the Quebec City-Windsor Corridor.
The emissions reduction depends on the emission factors used, freight volume, distance andmode share. The survey of emission factors of freight train show variation from 21 g/ton-km to
63 g/ton-km for freight train. The emission factor for diesel train in Finland is 22g/ton-km andfor US is 63 g/ton-km (ADB 2011). Using the emission factors of 103.6 g/ton-km for truck and30.5 g/ton-km for train 21, the estimated CO2 emissions is 29,458 tons and 20,479 tons
respectively for BAU and base case for 2015. Even though slight optimistic default emissions
factors 80 g/ton-km for truck and 25 g/ton-km for heavy train (ADB 2011) gives 22,748 tons and15,992 tons respectively for BAU and base case for 2015. The use of different factors givedifferent absolute value of emissions but both give same 30% emission reduction compared to20

Assessment of emissions using the generic model outlined in Table 7.20 and omitting the insignificant alternate
specific constant for truck show a 29.1% CO2 emission reduction compared to BAU.
21
Derived using the activity data and the carbon content of diesel (2590 gm/l) provided by the Petroleum Authorityof Thailand (PTT).

153

the base case. Thus in a given scenario the emission reduction largely depends on the potential
mode shift to railways.
7.5

Emission assessment for other dry ports

An assessment and comparison of emissions that would be generated from other dry ports is alsodone. Table 7.15 shows the freight demand for Thakhek, Savannakhet and Phakse (JICA 2011).
The volume for Thakhek for 2015 is estimated considering similar growth figure as in
Savannakhet.
Table 7.15 Freight demand and distanceFreight volume (tons)
2015
2025
19,00079,00036,000151,000
106,400
296,000

Dry port
Thakhek
Savannakhet
PhakseDistance to
Bangkok Laem Chabang
681 Km846 Km608 Km773 Km689 Km854 KmSource: JICA, 2011

The emission is estimated based on the emission factors considering the same factor as
Thanalaeng that 70% of cargo would be bilateral trade and 30% would be international trade.
Table 7.16 shows the comparison CO2 emissions for all dry ports considering the same amountof mode shift with share of truck 57% and train as 43%. It can be seen from the figure that theemissions would be higher from the Thanalaeng because of the freight volume. Interestingly, thereduction share does not depend on the distance and freight volume. It depends on mode shareand the emission factors used.
Table 7.16 Emissions from other dry ports

7.6

Dry ports
Thakhek

CO2, Tons (2015)
BAU
Mode shift
1,292
898

Savannakhet

2,204

1,532

30.5%

Phakse

7,317

5,086

30.5%

Thanalaeng

26,47818,406

30.5%

Emission
Reduction
30.5%Life cycle assessment of construction

The construction of dry port at Thanalaeng is essential to start the freight train service. The life
cycle assessment (LCA) of CO2 emissions from the construction of the dry port is assessed. It isvery difficult to find construction emission factors in the Asian context. The emission factors
provided by the Swiss Centre for Life Cycle Inventories (Ecoinvent Centre, 2007) are used for
estimation of the life cycle emissions.
154

The estimated quantities for the development of dry ports are taken from the feasibility study(JICA, 2011). For the estimation of earthworks, the average depth of ground preparation andslope protection work is taken as 30 cm. The thickness of various sizes of concrete drain andcover is taken as 10 cm, and height of the administrative office complex is taken as 4 m. The
assessment does not include emission for construction of water supply works, electricity lines,
signals and communication equipments within the dry ports, as the construction cost of these
items were not significant and also it was difficult to estimate the emission factors for these
items. The road pavement inside the dry port is considered to be of cement concrete similar tothe pavement of the container yard.
Table 7.17 shows the main construction activities, CO2 emissions factor and life cycle emissions
from the construction of dry port at Thanalaeng.
Table 7.17 Life cycle CO2 assessment of construction of Thanalaeng dry port
S.
No
Construction item
1
Earthwork
Ground preparation work
Excavation
Filling
Slope protection
Total earthworks
2
Cement concrete in container
yard, road and drains
3
Building with steel structure forwarehouse, container freightstation, truck terminal,
maintenance shop and parking
4
Concrete buildings foradministrative office complex andsecurity gate
5
Railway siding inside the dry port
Total

Quantity

CO2
Unit emission/unit

CO2 emissions,(kg)

120,000
1,278,266
10,6241,500
1,410,390

m3
m3
m3
m3
m3

0.515

726,351

44,560 m3

255.4

11,380,624

30,810 m2

286.9

8,839,389

4,160 m2
64,000 m

46.575
39.7

193,775
2,540,800
23,680,916

The life cycle CO2 emission of the dry port is estimated at 23,681 tons. For the base casescenario the emissions reduction was 8072 tons in 2015, considering the 7% growth (similar toGDP) of freight volume and same mode share the emissions savings for 2016 and 2017 would be8637 tons and 9242 tons, respectively. The resulting emission reduction in 3 years would be
25,951 tons. This demonstrates that the life cycle emissions from the construction of the dry port
would be offset in three years from the start of operation of the dry port and freight train. Itshould be noted however that the above estimate does not cover the emissions from operation of
the dry port.

155

7.7

Results and discussion

The modules 3 and 4 of the integrated methodology were applied to estimate the mode choicemodel between truck and train, mode shift and resulting CO2 emissions. In order to estimate themodel time, cost and reliability of freight transport were used as model parameters. A robustmodel with high level of significant parameters was developed based on the feedback received
from freight forwarders in Laos and Thailand. The model result showed a modal shift of 43% torailways from road at base case. The resulting CO2 emissions was calculated using bottom-up
approach, the result showed that 30% CO2 emission reduction.
The construction of dry port at Thanalaeng, priority location selected by location analysis, is theminimum requirement to facilitate and initiate rail freight transport and mode shift. The dry port
facility would also need infrastructure and equipment to handle containers and cargoes
transported by railways. These would be reach stackers, gantry cranes, stock yard, covered cargo
areas, railway siding and vehicle parking, office space including customs processing. As therailway link is already complete, the cost involved is only for the development of dry ports.
While, in case of other potential location, in addition to construction of dry ports- railway lines
and connectivity has to be improved. The life cycle assessment showed that the CO2 emissions
from the construction of dry ports would be compensated from the reduction of emissions fromthe mode shift within three years of the start of operation of the dry port.
This demonstrates the role of dry ports in contributing to climate change mitigation byfacilitating a mode shift and reducing emissions. Also, the development of dry ports in inland
secure area can contribute to adaptation. Thus, dry port development in inland area can havepositive environmental benefits as it contributes to mitigation as well as adaptation.
Elasticity analysis of allowed to evaluate the effect of variation of attributes considered on modeshare. This analysis is very useful in real case scenarios as it allows the stakeholders and decision
makers to see the tradeoff between cost and mode shift as well as time and mode shift. This
would enable the decision makers to consider measures and ways to influence the attributes. For
example if the time is likely to increase and cause the mode share to decrease, policy makers
may consider ways to reduce transportation time such as making border crossing efficient andincreasing efficiency of railway operation. If the cost is a cause of concern of reduced modeshare, then it could be left to the market to compete or in some cases possible ways could be
providing subsidies to railways.
The analysis is based on the stated preference survey of freight forwarders in Laos and Thailand.
One of problem encountered during the interview survey was bias of respondents to a particularmode, in this case truck or train. Even though they were asked to consider and evaluate values of
attributes prior to selecting a mode in a question, about 16 respondents chose only one mode.
Therefore, due to their bias those were not included in the analysis. Similar experience as in AHP
survey was also observed, many potential respondents promised to send feedback through email
but they did not.
The integrated methodology can demonstrate importance of environmental consideration and its
emission reduction potential in addition to their commonly understood roles to facilitate logistics
156

services. As modal shift is recognized as an approved methodology for UNFCCC, if emission
reduction potential of a project can be demonstrated utilizing the integrated methodology, this
could qualify as a project for consideration by the Global Environment Facility (GEF). One of
the criteria to qualify is to demonstrate emission reduction as a result of implementing policy anda project. The result shows the overall usefulness of the integrated methodology, which canprovide stakeholders and policy maker’s information concerning the various options, modes,
emissions, elasticity of variation which would be useful in evaluating policy options to makeinformed decisions.
7.8

Chapter summary

This chapter applied modules 3 and 4 of the integrated methodology. The stated preference data
were analyzed for parameter estimation of the utility functions for choosing truck and train
mode. All together six mode specific parameters were estimated corresponding to time, cost anddelay variables. Using the mode specific utility function, mode share of each mode wasestimated using the logit model which resulted in 57% share to truck and 43% to train.
Sensitivity analysis was conducted to evaluate various scenarios resulting from different
attributes values. The corresponding modal share were estimated and used for assessment of CO2
emissions. Based on the scenarios being considered, the resulting reduction in CO2 emission
varied from 24% to 39% compared to business as usual.

157

CHAPTER 8CONCLUSIONS
8.1

Introduction

The current research attempted to explore adaptation and mitigation aspect of the sustainabletransport development. The research proposed and applied an integrated methodology to assess
impacts of climate change on transport and to evaluate potential mode shift and emission
reduction through dry port development. This chapter outlines the findings, results anddiscussions and conclusions of the research and overall discussion on the use of the integrated
methodology. It also lists some areas for extension of current methodology and research that canbe further explored in future research.
8.2

Summary of the findings

The primary objective of the research is to assess the impacts of climate change on transport in
Asia and study mitigation potential of the dry ports. Within this main objective the research
focused around three objectives of the research as outlined in section 1.3 which included
assessment of climate change impacts, analysis of dry ports location to promote intermodaltransport and assessment of resulting modal shift and emissions. The key summary of thefindings are outlined in the following paragraphs.
8.2.1

Impacts of climate change on transport and adaptation

The assessment was done utilizing module 1 of the integrated methodology. Climate events suchas rainfall, rise in temperature, rise in sea levels and storm surges have substantial impacts ontransport infrastructure and operations. This research highlighted the importance of planning anddesigning transport infrastructure considering the likely impacts of climate change as well as life
cycle costs. The process of reviewing designing standards and practices could be relatively easierin Asia. Climate change impact assessment guidelines would help to systematically evaluate theimpacts, awareness and advocacy programme would help to initiate, plan and implement
adaptation strategies. As impacts are widespread, coordination at national, regional and local areessential for implementation of strategies.
The variation of intensity of climate events and degree of impacts in different Asian subregions
indicated the need to adopt different strategies and policies to develop sustainable transport
development. Adaptation measures in transport are costly and it takes time to mainstream theprocess. The increased level of awareness and coordination among all Asian stakeholders would
be essential to develop sustainable transport.
A conceptual framework of the adaptation process is proposed. The strategic environmental
assessment (SEA) at policy, programme and planning level and EIA at the project level would
help to implement adaptation strategies and measures. The development of dry ports at secure
inland locations away from vulnerable coastal areas safeguards it from risk of damage fromrising sea level or storms and thus contributes to the adaptation process. The adaption framework158was applied to the development of dry port.
8.2.2

Development dry ports and location analysis

The case studies of dry ports revealed their roles in promoting modal shift and environmental
benefits due to reduction in road congestion and emissions due to modal shift. Countries aretaking various measures and different approaches for development and operation of dry ports.
While for infrastructure development all forms of ownerships such as public, private and publicprivate partnerships were evident. The operation of dry ports was mostly handled by the private
sector and in some cases by subsidiary of the government. Some of the constraints to improve
intermodal transport were lack of sufficient locomotives and wagons to increase frequency ofcontainer block train services from dry port to/from seaports and the need to improve efficiencyof services.
The location of proposed dry ports in Laos was analyzed utilizing module 2 of the integrated
methodology that included and AHP and combined AHP-goal Programming. The location
analysis ranked Thanalaeng, which is close to Vientiane, with highest priority. Savannakhet was
ranked 2nd, Thakhek the 3rd and Phakse received least priority. The combined AHP-Goal
Programming analysis selected Thanalaeng, Savannakhet and Thakhek. These results are
consistent with the view of the freight forwarders and government officials. However, somedifference in weights of each criteria and sub-criteria were noted among government decision
makers and private sector freight forwarders.
The development of dry port and logistics infrastructure is not sufficient in itself; further
additional efforts are required to operate these facilities. More importantly reduction of
documents to be handled in dealing with export and import, implementation single window
system thus eliminating double inspection of cargoes at the border as well and at the dry ports aresome of the policy issues that need to be considered. There is no “one fits for all policies” theseshould be implemented by taking a step by step approach. As the railway connectivity toThailand has now been completed, the start of regular freight train between Thailand and Laoswould help to improve international freight transport and to reduce environmental burden tosome extent. By effectively using the dry ports as consolidation and distribution centers numberof less-than-truck trips could also be reduced. These facilities would also help to improve transit
transport through Laos and transforming it as a “land-linked” country in South-East Asia.
8.2.3

Freight modal shift and CO2 emissions

Utilizing the outcome of the location analysis module 2, the potential modal shift was assessedby utilizing module 3 of the integrated methodology. Initially based on the feedback received
from freight forwarders in Laos and Thailand on the stated Preference survey – model
parameters were estimated for the utility functions. The outcome of discrete choice analysis
showed very significant output and robust utility model. Using the utility function and logit
model, the mode share estimated was 57% to road and 43% to railways at the base case.
Elasticity analysis was conducted to evaluate variation in modal shift due to change in totaltransportation cost, transportation time and combination of both. The results showed that a 10%
increase in transport costs truck would reduce its mode share by 3.9%; while 10% increase in159

transport cost of train would reduce share of train by 9%. While, a 10% decrease intransportation time of truck would lead to an increase of 4.6% mode share. Similarly, 10%
reduction in transportation time by train would result in 11.6% increase in its mode share.
Module 4 of the integrated methodology was used to analyze the CO2 emissions from potential
modal shift. In base case scenario the reduction in CO2 emissions was estimated as 30% for 2015
compared to business-as-usual case. The life cycle assessment also showed that the CO2
emissions from the construction of the dry port can be offset within three years of start ofoperation.
8.3

Results and discussion

The integrated methodology allowed not only selecting and prioritizing dry ports based on thetransport cost and transportation time but also considering subjective criteria that are importantto the policy makers such as environmental benefits, regional economic development. The
analysis provides policy makers added information on the perception of the stakeholders in
addition to the cost benefit analysis for project appraisals. Further, the goal programming utilized
the optimization techniques of the evaluation criteria used. It allowed to define and include user’s
defined goals and targets of the criteria such as minimization of costs, time and environmental
impacts and maximization of intermodal transport linkages and regional economic development.
There is much argument about whether to encourage centralized or decentralized freight
distribution system. This helps to visualize how much these important goals are under or overachieved. This again considered input from government policy makers; freight forwarders thus
can help decision makers in making rational decisions while considering the feedback of
stakeholders. Badri (1999) used combined AHP-GP in location allocation problems. The
methodology is further enhanced and integrated by combining stated preference techniques formode choice and emission assessment.
There has been much argument on the role of dry ports in promoting modal shift. The statedpreference survey and analysis allowed to assess the modal shift opportunities. Further, the life
cycle assessment as well as life cycle costs to see how the carbon emissions can be offset would
be interesting to see as well as well as the cost involved to develop infrastructure to create modal
shift opportunities.
The railway connection to Laos has already been developed, now the efforts and investment are
required for the construction of the dry port at Thanalaeng with cargo and container handlingfacilities. This is essential to start the rail freight operations. The overall cost involved to start
operation would also be less compared to other potential dry ports as only dry port construction
is needed at Thanalaeng. While other locations need construction of railway links in addition to
dry port. Owing to the fact that passenger train between Thailand and Laos is already inoperation, there is high possibility to start the freight train service after completion of the dry
port in near future.
The integrated methodology also assessed CO2 emission and enabled to compare with base casescenario. Elasticity analysis helped to study the effects of cost and time variation on modal shift
and emissions.
160

Further there is strong logical linkage between analytical modules and thus integrates well witheach other. The output of the preceding modules feed into the subsequent modules as an input.
The application of the integrated methodology in ‘real case’ situation in the development of dry
ports in Laos and international freight transport and robust results and outcome shows its
feasibility for application in other cases. It could be further enhance through integrating life cycle
assessment as well as cost analysis.
Four set of primary data were collected for the research through (i) adaptation survey; (ii) AHP
survey; (iii) SP survey; and (iv) visits to dry ports for collection of case studies. There has been
mixed experience during primary data collection. One of the difficulties during the research was
problem faced during data collection. Despite having good contacts with transport policy makers,in Asia, Freight forwarders in Laos and Thailand and government decision makers in Laos, thedata collection exercise took much time and efforts than originally envisaged. While the datacollection interview survey, visit to the site were well organized with local coordination, the levelof response from freight forwarders and private sector was not encouraging. One of the reasons
was that the AHP questionnaire was long and it took about 20-30 minutes to complete it, so they
asked to leave the questionnaire during the meeting with a promise to send reply by email– but inmany cases they did not responded. The lesson is to get feedback during direct interview
possibly through setting another interview date and extending the time allocated for theinterviews. The flooding situation in Thailand during October-November 2011 also hampered
mobility and travel to freight forwarders offices for interview, as many were located in the areas
affected by floods and many potential respondents have to be relocated due to the floods.
8.4

Conclusions

For the development of sustainable transport, the research identified the need to consider climatechange impact while planning and designing transport infrastructure. The need of strategic
climate change and environmental impact assessment (SEA and EIA) guidelines and the need tostrengthen capacity of transport professionals and policy makers in Asia to consider climatechange impact emerged as important considerations.
The research proposed integrated methodology, and applied in real case situation. The outputs
were validated through comparisons of results from other studies and judgments. The applicationof methodology would be useful for the decision makers and assist in making informed andrational decision making by comparing various outcomes of the analysis of alternatives.
The research extended the methodology used by Badri (1999) and integrated to include modal
shift and emission assessment analysis and applied in transport sector. Also the methodology
incorporated the assessment of climate change impacts and covered both adaptation andmitigation issues for sustainable transport development.
Thanalaeng dry port in Laos received high priority among the policy makers as well as freight
forwarders compared to other dry port location being considered. The analysis of statedpreference survey result showed a modal shift of 43% to railway from road if freight train service
would be available along Laem Chabang-Thanalaeng route after construction of the Thanalaeng
dry port. This would result in 30% CO2 emission reduction from modal shift. The life cycle
161

assessment indicated that the construction emissions can be offset within three years of start ofdry port operation. The application of integrated methodology to demonstrate emission reduction
potential of dry port could be useful in formulating policies and project.
Application of the integrated methodology and elasticity analysis can provide decision makers
useful information to support rational decision making to initiate adaptation measures tosafeguard transport infrastructure develop sustainable transport, develop dry ports to promote
modal shift.
8.5

Further research

Availability of limited literatures on transport and climate change studies in Asia indicates further
research needs in area of country specific assessment and quantification of impacts andadaptation strategies for developing sustainable transport infrastructure.
The mode choice analysis only considered two modes road and rail. The research can beextended to third mode as intermodal transport. Further, the mode choice model can be improvedby adding more attributes of freight and shipment such as frequency of freight trains, type andvalue of commodity to be transported.
In terms of emission assessment, there is scope to further extend the research to analyze process
based life cycle assessment as well as life cycle costing approach to infrastructure investment topromote modal shift. The correlation between investment in dry ports and railways, and resulting
modal shift would be an interesting area to explore.

162

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177

Appendix I- Review of evaluation criteria, sub-criteria for location analysis
Reference

Criteria

Sub criteria

1. Kahraman et (i) Environmentalal. (2003)
regulation(ii) Hostcommunity(iii) Competitive
advantage(iv) Political risk
2. Guneri et al. (i) Labour(2009)• Labour quality,• Labour cost,• Labour supply(ii) Government• Incentive(iv) Environmental • Geological• Climate• Transportation• Demographic structure(iv) Regional• Economic
economy• Industrial situation(v) Physical• Land costcondition• Construction cost
• Enlargement of shipyard• Protection from sea condition(vi) Raw material
3. Onut et al. (i) Port Location• Proximity to import/export area(2010)• Feeder or hub port
• Main navigation route(ii) Hinterland• Volume of import/export
economycontainers,• Transshipment containers• Frequency of ship calls(iii) Physical• Infrastructurefeatures of port
• Port facility and equipment• Intermodal links(iv) Port efficiency • Container handling efficiency• Port berthing time length• Container yard efficiency• Custom efficiency(v) Costs• Port charge• Inland transshipment freight
rates(vi) Others• Port future development plan,
178

Goal and
alternatives
Selectbest
location for a
factory:• Istanbul,• Ankara• Izmir.
Select shipyard
locationusing
ANP among four
alternatives:• Samsun• Yalova• Izmir• Yumurtahk

Develop MCDA
port
selectionmodel,
alternatives are:
• Marport• Kumport• Mardas• Aktas• Gemport• Borusan• TCDD
Haydarpasa

4. Lv(2009)

andLi (i) Development
status(ii) Traffic
convenience(iii) Labour
resources andtechnology(iv) costs

5. Wang and Wei (i) Natural(2008)
environment(ii) Operating
Environment(iii) Infrastructure
status(iv) Costs

6. Kunadhamraks
and Hanaoka(2009)(i) Logistic costs(ii) Service quality(iii) Reliability• Personal relations, information
service at port,• Port security• Good reputation related todamage delays• Development of the city
• Development level of nearby
cities• Potential of the city
development• Traffic between dry ports andsea port• Traffic radiation area of the city
• Traffic capacity• University and colleges• Capacity of local labour market• Status of high tech industry andlabour• Transport costs• Local labour wage level• Use of land resources• Environment protection• Weather• Geological• Hydrological• terrain• Labour condition• Characteristics of goods• Service level• Customer condition• Traffic• State of public facilities• Information infrastructure• Transport costs,• Local labour wage level• Use of land resources• Environment protection• Transport cost
• Handling cost
• Holding cost;• Travel time
• Information system• Flexibility;• Frequency of disruption
179

Selection oflocation of a dry
port for Tianjin
port. The options
considered were:• Yinchuan• Datong• Shijiazhuang• Handan.

Location of a dry
port for Tianjin
port the options
were:• Baoding• Dezhou• Huhhehoate• Haozhou

Evaluate logistic
performance ofintermodaltransport.

(iv) Security
7.Lee (1998)• Frequency of delay• Duration of disruption• Duration of delay• Frequency of freight damage• Severity of freight damage(i) Travel timesaving(ii) Comfort andsafety(iii) Project cost(iv) Urban travelcost(v) Socio economic
benefits

Select best
railway network
development
among threealternatives:• Alternative 1• Alternative 2• Alternative 3
Also considered
three groups ofstakeholders:• Supplier• User• Community
Employeeselection criteria• Capital• Labour• Land• Population number• Population density• Population age distribution(iii) Firm strategy, • Management objectives
structureand • Rank of competitive hospitals
rivalry• Policymakers attitude(iv) Related and • Healthcare sector
supporting• Medicine and pharmaceuticalindustries• Hospital administration(v) Government• Regulation and standards• Efforts to promote medical

Hospital location
selection
alternatives:• Taichung City
• Taiping• Dali(Taichung ranked
1st)• Regional development• Severance effect• House replacement(vi) Environmental • Noiseeffects• Ecology• Visual Intrusion• Cultural assets
8.Ozdagoglu and (i)Technical • Proficiency
Ozdagoglu
attributes• Carefulness(2007)• Harmony with the team working(ii)
Behavioral • Devotion
attributes• Cleanliness• Morality(iii) Other factors• Not being the criminal record• Residing
in
the
close
environment• Being a reference
9. Wu et al. (i) Factor condition(2005) Building
and Environment(ii) Demandcondition

180

(v) Chance(i) Energy(ii) Environment(iii) Cost(iv) Technology(v) Adaptability(vi) Barrier
11. Yang et al. (i) Market(2008), Facility attraction
location

network• Hospital assessment• Change in market demand• Cost fluctuations• Change in financial market andexchange rate

10. Yelda andShrestha (2007),
Urban transport
options in New
Delhi(ii) Consumer
characteristics(iii) Location
qualification

12. Macharis(2001), Locationof barge
terminals(i) Increase of users
benefits(ii) Increasing
benefits of theinvestors/operators

Options:• 4S-2 Wheelers• CNG Car
• CNG Bus
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Passerby flow
Security issue
Clustered market
Public transit
competition
Consumer population
Consumer density
Disposable income
Purchasing power
Brand loyalty
Rent
Flexibility of lease term
Shop size
Employee recruiting
Expected revenue
Visibility of the shop
Accessibility of the shop
Synergy between each branch

•
•
•
•

Reduction in transport cost
Reduction in transport time
Reliability of connection
Time variation between
collection and delivery of
goods
Integration with other modes
Extension of services
Maximizing the actual value
Maximizing the possibility toextendMaximizing the existing
infrastructure

•
•
•
•
•

181

(iii) Increasing
benefits of thecommunity

13. Ugboma andUgboma (2006),
Nigerian PortsMaritime Eco andLogistics• Optimization of the efficiencyof network• Minimization of the roadcongestion• Max economic benefits• Minimization of effect on theneighbor• Minimization of pollution
levels(i) Efficiency(ii) Frequency of ships visits(iii) Adequate Infrastructure(iv) Location(v) Port charges(vi) Port reputation for cargo damages(vii) Quick response to Port user needs

14. Tuzkaya et al. (i) Cost
(2008), Transportmode selection
between Turkey
and Germany(ii) Flexibility(iii) Productcharacteristics(iv) Reliability(v) Risks(vi) Safety
problems

•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Handling costs
Defective freight costs
ICT cost
Transportation cost
Handling
theunexpectedchangesCapacity flexibility
Route flexibility
WeightPackaging features
VolumeStacking-up requirements
Transportation features
Product life
Product value
Late arrivals
Stable arrivals
Reliability on schedule
Storage risk
Political risksSocial risks
Environmental risks••

Burglary
Accident
182

Servicecharacteristic
consideredbyshippers on port
selection
alternative Ports:• Lagos• Tincan• Harcourt• Ro-Ro Port
Alternatives:• Rail• Road• Sea

(vii) Speed(viii) Traceability

15. Reza et al. (i) Environmental(2011), Flooring, impacts
LCA and AHP(ii) Economic
impacts(iii) Socio-political
impacts• Diversity of accident cause• Damaged product• Transshipment time
• Transportation speed• Transportation distance• Transportation time
•
•
•
•
•
•
•
•
•
•
•
•
•

Freight and vehicle
Container
All other factors
Resources depletion
Wastes and emissions
Waste and management
Climate change
Environmental risk
Embodied energy
Energy loss
Material cost
Construction cost
Occupation and maintenancecost• Social acceptance• Vulnerability of area
• Building weights

•
•
•
•
•
(ii) Senses and •waste/energy•••(iii) Countryside
•
•
•
•
(iv)
Technology •and safety•

16. Brozova and (i) Water and Air
Zika (2010), EIA
of Transport

17. Berrittella et

Options flooring:• Clay blocks• Concrete
blocks• Expanded
polystyrene(EPS)blocks

Local air quality
Regional air quality
Quality of water
Ozone depletion
Climate changes
Noise and vibration
Waste
Light pollution
Non-renewable resource use
Preserved nature areas
Losses of biodiversity
Cultural and technical heritage
Land takeTechnological hazards
Safety of transport users andpedestrians(i) Less carbon content fuel183

Six policy

al. (2007), AHP
toevaluatetransport policies
to reduce climatechange impacts(ii) Vehicle efficiency(iii) Increase public and multi-modal transport share(iv) Better mobility management
Option 3 evaluated as thehighest rankingenvironmentally friendly mode

18.
Mohajeri (i) Rail related(2010) Railway
site selection in
Iran

•
•
•
•
•
•
•

(ii) Passenger
Services

•
•
•
•
•
•

(iii) Architecture
and urbanism

•
•
•
•
•
•
•
•

options:
1. Agreement toimprove vehicle
efficiency
2.Incentives- carfleet renewal
3. Promote
environmentallyfriendly mode
4.Integration oftransportation
planning
andland use
5. Better
infrastructure
6. ITS
Feasibility of connecting new Four options:and old lines• Moveto
SalaamCreating new lines• Renovation ofUsing existing equipments
existing
Access to existing rail
• Redevelopment
networkof existing andCommunication with otherestablishing astations
satellite station
Geometric limitation• Satellite station
Coordination of train
next tomovement and maneuvers
underground
Services to passenger
stationAccess to city transportsystemAccess to intercity transportsystemProximity to station
Reduction in journey time
Easy access to urban
facilities
Harmony
Coordination with dev plans
Effective land possession
Harmony with city image
Harmony with environment
Potential for future
development
Easy access
Coordination with defense184

(iv) Economics

19. Park et al. (i) Promptness(2010),
Competitivenessof aircargo
carriers(ii) Accuracy(iii) Safety(iv) Convenience(vi) Economic
efficiency(vi) Dependability• Return on investment• Opportunity cost on existingjobs• Creating added value to theregion• Decrease in passenger costs• Useful land uses
• Quick pick-up• Quick delivery• Network• Quick response• On time pick-up• Pick-up service area
• On-time delivery• Accurate delivery• Handling• Compensation• Problem solving• Information• Facility• Damage and loss
• Service area
• Branch• Booking• Tracing• Schedule• Moderate price• Variety rate
• Reasonable price• Rate policy• Packing condition• Image• Customs clearance

185

Alternatives:
• DHL
• FDX
• UPS
• TNT
• EMS
DHL ranked 1st

Appendix II: Adaptation Questionnaire
Survey of Climate Change Impacts on Transport and Adaptation in Asia
(Please return the completed questionnaire by 20 July 2009)
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report makefollowing predictions of climate variability in Asia:i. the increase in temperature will be higher than global mean;ii. summer heat spells will be longer and more intense and frequent in East Asia;iii. precipitation will increase in most of Asia;
iv. the frequency of intense precipitation will increase in parts of South and East Asia;
v. extreme rainfall and winds due to tropical cyclones will likely increase in East, Southeast
and South Asia.
The transportation system such as roads, railways, air transport and water transport will beaffected by these climate events. There are compelling arguments that transport infrastructure
should be able to withstand the impacts of climate events such as excessive rains, flooding, risein sea level, rise in temperature, storm surges, frequent snowing and ice melting triggered by theclimate change.
In this background, a research on studying the Impacts of Climate Change on Transport and
Adaptation in Asia is being undertaken at the Tokyo Institute of Technology. This survey is being
conducted to assess the existing state of environment and climate change policies, guidelines,
implementation, coordination and institutional set up in Asian countries.
Your support in timely completion of the survey questionnaire and contribution to the study will
be highly appreciated. The finding of the study will help plan and develop sustainable transport
policies/programmes for Asia that could be implemented in member countries.
Please provide your personal view while answering questions even some questions may refer togovernment programmes, policy and implementation. Your response will be treated in strict
confidence. All responses will be aggregated and analyzed.
Please return the completed questionnaire to Madan B. Regmi:• on or before 20 July 2009
• by email mbregmi@gmail.com• or by FAX: +81-3-5734-3468
Prof. Shinya Hanaoka/Madan Bandhu Regmi, Visiting Researcher
Department of International Development Engineering
Graduate School of Science and Engineering
Tokyo Institute of Technology
2-12-1-I4-12, O-okayama, Meguro-ku,
Tokyo 151-8550, Japan
Fax: +81-3-5734-3468.
If you have any questions related to the questionnaire please contact Madan B. Regmi, by email<mbregmi@gmail.com> or Tel/Fax: +81-3--5734-3772.
186

Section A: Awareness of climate change and adaption measures in transport sector
1.
How do you rate the general level of awareness of policy makers and transport
officials about environment, climate change and adaptation 22 and in your country?
VERY HIGH

HIGH

ADEQUATE

LOW

VERY LOW2.
How do you rate the general level of awareness of general public about environment,
climate change and adaptation in your country?
VERY HIGH

HIGH

ADEQUATE

LOW

VERY LOW

3.
Please indicate in the scale given below to which extend you agree to the following aboutclimate change and impact on transport (1-Strongly Disagree, 2-Disagree, 3-Neutral,
4-Agree, 5-Strongly Agree)
The climate change is a cause of concern

1

2

3

4

5

Climate events will affect transport and operation

1

2

3

4

5

Coastal infrastructure are vulnerable to climate change

1

2

3

4

5

Bridges are prone to damage

1

2

3

4

5

Possibility of overflow of side and cross drains

1

2

3

4

5

Heavy snow will disrupt transport and traffic

1

2

3

4

5

Pavements deterioration will be faster by high temperature

1

2

3

4

5

More traffic disruption due to landslides

1

2

3

4

5

Poor driving condition due to fog, storm

1

2

3

4

5

Strong winds may damage road signs

1

2

3

4

5

Our region will not be much affected by climate change

1

2

3

4

5

It will be costly to repair infrastructure

1

2

3

4

5

Design standards and criteria may need to be revised

1

2

3

4

5

It will be costly to adopt higher design standards

1

2

3

4

5

Section B. Information on emergency preparedness
4. Please indicate occurrence significant climate events (such as heavy rain, flooding, heavy
snow, extreme temperature, wind storm etc.) within last 3 years in your country?
YESNO

5. How do your rate the response from the relief and transport agencies to provide immediate
help and relief (opening road, providing assistance etc.)?
22

Adaptation refers to initiatives and measures to reduce the vulnerability of natural and human systems against
actual or expected climate change effects.

187

VERY FASTFASTNORMALSLOW

VERY SLOW

6. Do your think there is some scope of improvement in earlier emergency responses?
YESNO

7. Any change in emergency preparedness policies, guidelines for reopening transport and indealing with extreme climate events after those events?
YESNO

8. Do you think coordination between the transport agencies and agencies responsible for
emergency responses should be improved?
YESNO

C. Design Standards and Practices:
9. To safeguard transport infrastructure from the impacts of heavy rains, floods, storms, heavy
winds, sea level rise in your opinion which of the following options could be appropriate? (Youcan check more than one)
Increase clearance above high flood level for bridges
Design flood estimation, storm water taking account of predicted climate
Consider increasing waterway and protection works to safeguard bridges
Increase capacity of side drains
Increase capacity and size of culverts, cross drainage
Ensure effective drainage of surface water from pavement (camber, subsurface drains)
Provide additional protection to coastal roads and railway
Relocation of coastal road to higher place
Raise height of embankment in flood plains
Place sufficient warning and information signs
Provide additional protection to ports and harbour
Ensure efficient drainage in airports
Provide adequate river protection works
Provide adequate slope protection works
Use stiffer bitumen in pavement (to safeguard from higher temperature)
Use thick and strong pavement (more snow, icing, thawing)
10. Various structural components of transport infrastructure are designed for fit for purpose
following existing standards, specifications and practice. Do you consider that design standards
for critical and structural components of transport infrastructure should be reviewed or revised towithstand the impact of climate events?
YESNO
11. Do you think it will be appropriate to revise the design flood estimation method and design
188flow taking account of heavy precipitation, uncertainty and probability of occurrence of floods?
YESNO

12. Are there existing clear guidelines to consider impacts of climate change while planning,
designing and maintaining transport infrastructure?
YESNO

13. Do you think that while planning and designing the vulnerable transport infrastructure thepotential impacts of climate change should be considered?
YESNO

14. Adopting higher design standards, criteria and guidelines may cost more initially. But in longrun it may be an economical solution? Do you agree?
YESNO

15. Provide any other suggestion how could we make transport infrastructure safe to withstand
impacts of climate change?
____________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

D. Policy, guidelines, institution, coordination for implementation
16. Are there existing laws, and rules in your country to assess environmental and climate change
impacts? (e. g. Environmental Impact Assessment (EIA), guidelines Climate Change Adaption
and Mitigation)
YESNO

17. If yes, please provide name of these, laws, rules, guidelines, policies decrees, and executive
orders related to environment and climate change.
S. No.

Name

Year[Please provide web link or electronic copy of the documents if available]
18918. Which the followings reflects the need about the laws, rules, polices and guidelines on
climate change and adaptation? (Choose one)
Revision and extension of rules, polices and guidelines necessary
New policies and guidelines to cover climate change and adaptation necessary
No need to revise and introduce new polices and guidelines
19. If revision or extension of rules, guidelines are necessary, do you think extending the exiting
EIA guidelines to include the climate change and adaption issues would be useful?
YESNO

20. Are there climate change and adaptation projects in transport related being implemented inyour country?
YES

NO

21. If yes, please provide brief project detail and sector (road/railways/air/water transport):
S. N.

Project Name, description

SectorYear

22. Institutional arrangements: Is there an institution unit/division/department responsible forenvironment and climate change adaptation issue in: (answer all questions from a to f)a. Central level high coordination body:

YES

NO

b. Ministry of Transport/Highway/Railway:

YES

NO

c. Road/Highway Department:

YES

NO

d. Railway organization:

YES

NO

e. Air Transport

YES

NO

f. Water Transport

YES

NO

23. How do you rate the coordination between above organizations transport/road/railway
departments, agencies, ministries, other units and central units?
VERY GOOD

GOOD

SATISFACTORYPOOR

VERY POOR

24. How do you rate the application and implementation of existing environmental, climate
190

change, adaption rules, polices guidelines?
VERY GOOD
GOOD
SATISFACTORYPOOR

VERY POOR

25. Is there a need of environmental, climate change adaptation awareness programme for policy
makers and other staff involved in this area?
YESNO

26. If yes, what type of programme will be appropriate? (Choose one)
Programme targeting high level policy makers (politicians)
Programme targeting high level Government official
Programme targeting project officers/managers
Programme targeting general public
27. In your view what should be done to safeguard transport infrastructure from impact ofclimate change?
__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
28. Any other things you want to mention on impact of climate change and adaptation ontransport?
______________________________________________________________________________________________________________________________________________
E. Please tell us about yourself
29. You are:Male
Female 30. Your country: ____________________________
31. Age:<30 years,
31-40 Years,
41-50 Years,
51-60 Yr,
61Yr.>
32. Your education:
Bachelor,
Master,Doctorate
33: Your area of work_________________________________________
34. Work Experience:
0-5 years,
6-10 Years, 11-15 years, 15 years above
Thank you for completing the survey!

191

Appendix III: Survey of Policy Maker’s and Freight Forwarder’s/Transport
Operator’s Opinion for analysis of dry port location in Lao PDR
The importance of intermodal transport is being perused in Asia. Inland dry port is one of theimportant nodes of intermodal transport and promotion of intermodal transport can facilitate
modal shift and help reduce emissions from transport. Development of dry ports is even more
important for land locked countries. There are many criteria that need to be considered forselecting/prioritizing location for dry ports.
In this background, a research on analysis of location of dry port in Lao PDR is being undertaken
at the Tokyo Institute of Technology.
This survey is being conducted to evaluate location of dry ports and will be utilized to develop
modal shift model in later part of the study and evaluate resulting reduction in carbon emissions– if such facilities are developed and connected by railways and inland waterways which are
more environmental friendlier modes than road transport. The finding of the study will be usefulto plan and develop intermodal and sustainable transport through dry ports.
Please provide your personal view while answering questions even some questions may refer togovernment programmes, policy and implementation. Your response will be treated in strict
confidence. All responses will be aggregated and analyzed.
Please return the completed questionnaire to Madan B. Regmi on or before 30 June 2011, by
email mbregmi@gmail.com or regmi.unescap@un.org by FAX: +66-2-288-3050 or in thefollowing address
Madan B. Regmi
Transport Division
UN Building
UNESCAP
Bangkok, Thailand
Fax: +66-2-288-3050
Email: regmi.unescap@un.org

Prof. Shinya Hanaoka
Dept. of International Development Engineering
Graduate School of Science and Engineering
Tokyo Institute of Technology
2-12-1-I4-12, O-okayama, Meguro-ku,
Tokyo 151-8550, Japan
Fax: +81-3-5734-3468
Email: hanaoka@ide.titech.ac.jp

If you have any questions related to the questionnaire please contact Madan B. Regmi, by email<mbregmi@gmail.com> or Tel/Fax: +66-2-2881571.
Your support in timely completion of the survey questionnaire and contribution to the study will
be highly appreciated.
The survey will take about 20-30 minutes. It involves pair wise comparison of two
criteria/subcriteria/location (one Left and right side of column). Please use your value
judgment/preference in 1-9 scale.

192

Part I: Evaluation of Main Criteria
Using your value judgment/preference please compare importance of the criteria on the “lefthand side” with the criteria on the “right hand side” in each row and mark with (X) or shade
one box in a row with 1-9 scale for evaluation location of dry port
Example: If you think “Regional economic development” is 3 times as important than “Costs”
then you will mark 3 on Left hand Side..
Costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

X

Regional
economicdevelopment

Please indicate from in 1- 9 point scale while making pair wise comparison of two
criteria/subcriteria in a row. Please mark only one box in a row.

Costs
Costs

9
9

8
8

7
7

6
6

5
5

4
4

3
3

2
2

1
1

2
2

3
3

4
4

5
5

6
6

7
7

8
8

9
9

3

Costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

4

Costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

5

Time

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

6

Time

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

7

Time

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

8

Intermodal
Connectivity
Intermodal
Connectivity

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Environmental
Impacts

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

9

10

193

Very important

Important

Slightly important

Slightly important

Important

Very important

Part II: Evaluation of Sub-criteria

Extremely Important1
2

Equally Important

Criteria

Extremely importantS.
No

Criteria

TimeIntermodal
connectivity
Environmental
Impacts
Regional
economicdevelopment
Intermodal
connectivity
Environmental
Impacts
Regional
economicdevelopment
Environmental
Impacts
Regional
economicdevelopment
Regional
economicdevelopment

Please compare importance of the criteria/subcriteria on the “left hand side” with the criteria on
the “right hand side” in each row and mark with (X) or shade one box in a row with 1-9
scale for evaluation location of dry port. Please mark only one box in a row.
Example: If you think “Railway connectivity” is 5 times as important than “Inland water
ways connectivity” then you will mark 5 on Left hand Side.
Railways

9

8

7

6

X

4

3

2

1

2

3

4

5

6

7

8

9

Inlandwaterways

5

Costs
11
12
13

Land
acquisition
costs
Land
acquisition
costs
Construction costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Construction
costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Transport costs

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Transport costs

Intermodal transport connectivity
14

Highways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Railways

15

Highways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

16

Highways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Inlandwaterways
Seaports

17

Railways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

18

Railways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Inlandwaterways
Seaports

19

Inlandwaterways

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Seaports

5

6

7

8

9

Operation
impacts

6

7

8

9

Government
policestodevelop special
economic zones
or free trade

Environmental impacts
20

Constructio
n impacts

9

8

7

6

5

4

3

2

1

2

3

4

Regional Economic Development
21

Proximity
9
to market,
production
centres andconsumers

8

7

6

5

4

3

2

194

1

2

3

4

5

22

23

Proximity
9
to market,
production
centres andconsumers
Government 9
polices todevelop
specialeconomiczones
orfree tradearea nearby

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

area nearby
Freight Demand

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Freight DemandPart III. Preference of alternative locations with respect to criteria/sub criteria
Thanaleang, Savanakhet, Thakek and Phakse are potential location of dry ports being
analyzed for transport towards Thailand. While considering criteria/subcriteria please compare
preference of alternative locations in the 1-9 scale. Please mark only one box in a row.
Example: Considering “land acquisition costs” if you think “Savanakhet” is 4 times
important/preferred than Thanaleang (because of cheap land price), then you will mark 4 on
Right side.
Land acquisition costs
Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savanakhet

Land acquisition costs
24

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savanakhet

25

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek26

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse27

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek28

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse29

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseConstruction costs
30

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savanakhet

31

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek32

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse195

33

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek34

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse35

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTransportation costs
36

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savanakhet

37

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek38

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse39

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek40

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse41

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTotal transportation time from port
42

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

43

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek44

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse45

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek46

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse47

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTransport connectivity to highways
48

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

49

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek50

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse51

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek52

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse53

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTransport connectivity to railways
54

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

55

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek56

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse196

57

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek58

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse59

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTransport connectivity to inland waterways
60

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

61

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek62

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse63

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek64

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse65

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseTransport connectivity to seaports
66

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

67

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek68

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse60

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek70

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse71

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseEnvironmental impacts from construction
72

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

73

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek74

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse75

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek76

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse77

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseEnvironmental impacts from transportation operations
78

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

79

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek80

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse81

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek197

82

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse83

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseProximity to market, production centres and consumers
84

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savannakhet

85

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek86

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse87

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek88

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse89

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseGovernment polices to develop special economic zones or free trade area nearby
90

Thanaleng

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Savanakhet

91

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek92

Thanaleang

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse93

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Thakek94

Savanakhet

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

Phakse95

Thakek

9

8

7

6

5

4

3

2

1

2

3

4

5

6

7

8

9

PhakseFreight demand
96

Thanaleng

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

Savanakhet

97

Thanaleang

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

Thakek98

Thanaleang

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

Phakse99

Savannakhet

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

Thakek100

Savanakhet

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

Phakse101

Thakek

9

8

7

6

5

4 3

2

1

2

3

4

5 6

7 8

9

PhaksePart IV: General Information of the respondents
1. You are:Male
Female2. Age:<30 years,
31-40 Years,
41-50 Years,
51-60 Yr,
61Yr.>
3. Your education:
Bachelor,
Master,Doctorate
5: Your area of work_________________________6. Sector:
Government
Private Sector
7. Work Experience:
0-5 years,
6-10 Years, 11-15 years, 15 years above
Thank you very much for your cooperation.

198

Appendix IV: Questionnaire for the Stated Preference Survey (Design A)
Freight Transport between Laem Chabang Port, Thailand and Thanaleang (Vientiane),
Laos/ Thanaleang (Vientiane), Laos and Laem Chabang Port, Thailand
Part I: We are seeking your feedback on freight transport mode choice decision. The options
available to you are transportation using a Truck and Train. Each mode is described by the totaltransportation cost, total transportation time (including customs clearance, border crossing andhandling at dry ports/logistics centres) and punctuality (reliability) of transport service.
The rail link between Thailand and Laos has been completed and there is a plan to construct a
Logistics Centre/dry port in Thanaleang/Vientiane. It is assumed that regular freight train service
will be available in near future. Assume you are considering transportation of goods in a 20 footcontainer from Thailand to Laos/ Laos to Thailand. The following 9 scenarios of freighttransport by truck and train (hypothetical future scenarios) are presented to you. Please choose
your preferred mode (Truck or Train) considering the given scenarios situation of transportation
cost, time and punctuality of transport service.
1.

Scenario 1
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

2.

Train
26 hours
US $ 800
High (0-8 hrs)

Truck
14 Hours
US$ 1600
High (0-8 hrs)

Train
30 hours
US $ 800
Low (17-24 hrs)

Truck
16 Hours
US$ 1800
Medium (9-16 hrs)

Train
30 hours
US $ 800
Medium (9-16 hrs)

Truck
14 Hours
US$ 1600
Medium (9-16 hrs)

Train
26 hours
US $ 1200
High (0-8 hrs)

Scenario 4
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

5.

Truck
18 Hours
US$ 1800
Low (17-24 hrs)

Scenario 3
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

4.

Train
22 hours
US $ 1000
High (0-8 hrs)

Scenario 2
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

3.

Truck
16 Hours
US$ 1800
High (0-8 hrs)

Scenario 5
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

199

6.

Scenario 6
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

7.

Truck
14 Hours
US$ 1800
Low (17-24 hrs)

Train
22 hours
US $ 1200
Medium (9-16 hrs)

Truck
18 Hours
US$ 1800
High (0-8 hrs)

Train
30 hours
US $ 1200
Low (17-24 hrs)

Truck
16 Hours
US$ 1600
High (0-8 hrs)

Train
26 hours
US $ 1000
Medium (9-16 hrs)

Scenario 8
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

9.

Train
26 hours
US $ 1000
Low (17-24 hrs)

Scenario 7
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

8.

Truck
14 Hours
US$ 1800
Medium (9-16 hrs)

Scenario 9
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

Part II: General Information of the respondents and business1. You are: Male
Female2. Age:<30 years,
31-40 Years,
41-50 Years,
51-60 Yr,
61Yr.>
3. Your education:
Bachelor,
Master, Doctorate
4: Years in Logistics Business:
0-5 years,
6-10 Years, 11-15 years, 15 years above
5. Indicate your order of importance (1, 2, 3) of the followings for mode choice decisions:a. Transportation timeb. Transportation costc. Punctuality (reliability)
6. What are other factors important for mode choice decisions?
a. _______________________ b. _______________________
c. _______________________ d. _________________________
7. Do you make mode choice decisions?
YesNo
8. Would you use train for freight transport –if regular service is available?
Yes
No
9. Rate importance of dry ports/ICDs/Logistics centers for intermodal transport and inencouraging modal shift.
1 (Low)
2
3
4
5 (High)Thank you very much for your feedback.
Madan Regmi, Transport Division, United Nations, ESCAP, Bangkok- mbregmi@gmail.com
Dr. Hanaoka Shinya, Tokyo Institute of Technology, Tokyo, Japan- hanaoka@ide.titech.ac.jp200Stated Preference Survey (Design B)
Freight Transport between Laem Chabang Port, Thailand and Thanaleang (Vientiane),
Laos/ Thanaleang (Vientiane), Laos and Laem Chabang Port, Thailand
Part I: We are seeking your feedback on freight transport mode choice decision. The options
available to you are transportation using a Truck and Train. Each mode is described by the totaltransportation cost, total transportation time (including customs clearance, border crossing andhandling at dry ports/logistics centres) and punctuality (reliability) of transport service.
The rail link between Thailand and Laos has been completed and there is a plan to construct a
Logistics Centre/dry port in Thanaleang/Vientiane. It is assumed that regular freight train service
will be available in near future. Assume you are considering transportation of goods in a 20 footcontainer from Thailand to Laos/ Laos to Thailand. The following 9 scenarios of freighttransport by truck and train (hypothetical future scenarios) are presented to you. Please choose
your preferred mode (Truck or Train) considering the given scenarios situation of transportation
cost, time and punctuality of transport service.
1.

Scenario 1
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

2.

Train
26 hours
US $ 800
Low (17-24 hrs)

Truck
18 Hours
US$ 1600
Medium (9-16 hrs)

Train
22 hours
US $ 800
Medium (9-16 hrs)

Truck
14 Hours
US$ 1400
Low (17-24 hrs)

Train
30 hours
US $ 1000
Medium (9-16 hrs)

Truck
16 Hours
US$ 1400
Medium (9-16 hrs)

Train
30 hours
US $ 1200
High (0-8 hrs)

Scenario 4
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

5.

Truck
16 Hours
US$ 1400
Low (17-24 hrs)

Scenario 3
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

4.

Train
22 hours
US $ 1000
Low (17-24 hrs)

Scenario 2
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

3.

Truck
18 Hours
US$ 1400
Medium (9-16 hrs)

Scenario 5
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

201

6.

Scenario 6
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

7.

Truck
14 Hours
US$ 1400
High (0-8 hrs)

Train
22 hours
US $ 800
High (0-8 hrs)

Truck
18 Hours
US$ 1600
Low (17-24 hrs)

Train
30 hours
US $ 1000
High (0-8 hrs)

Truck
16 Hours
US$ 1600
Low (17-24 hrs)

Train
22 hours
US $ 1200
Low (17-24 hrs)

Scenario 8
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

9.

Train
26 hours
US $ 1200
Medium (9-16 hrs)

Scenario 7
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

8.

Truck
18 Hours
US$ 1400
High (0-8 hrs)

Scenario 9
Attributes\ Mode
Total Transportation Time
Total Transportation cost/TEU
Punctuality (Delivery within hrs of schedule)
Which option would you choose ( select one box)

Part II: General Information of the respondents and business1. You are: Male
Female2. Age:<30 years,
31-40 Years,
41-50 Years,
51-60 Yr,
61Yr.>
3. Your education:
Bachelor,
Master, Doctorate
4: Years in Logistics Business:
0-5 years,
6-10 Years, 11-15 years, 15 years above
5. Indicate your order of importance (1, 2, 3) of the followings for mode choice decisions:a. Transportation timeb. Transportation costc. Punctuality (reliability)
6. What are other factors important for mode choice decisions?
a. _______________________ b. _______________________
c. _______________________ d. _________________________
7. Do you make mode choice decisions?
YesNo
8. Would you use train for freight transport –if regular service is available?
Yes
No
9. Rate importance of dry ports/ICDs/Logistics centers for intermodal transport and inencouraging modal shift.
1 (Low)
2
3
4
5 (High)Thank you very much for your feedback.
Madan Regmi, Transport Division, United Nations, ESCAP, Bangkok- mbregmi@gmail.com
Dr. Hanaoka Shinya, Tokyo Institute of Technology, Tokyo, Japan- hanaoka@ide.titech.ac.jp
202