論文 / 著書情報
Article / Book Information
題目(和文)
Title(English)

Intermodal Hub-and-Spoke Transport Network for an Archipelagic
Country, the Philippines

著者(和文)

OdchimarAnita II Alvarez

Author(English)

Anita II Odchimar

出典(和文)

学位:博士(工学),学位授与機関:東京工業大学,
報告番号:甲第10263号,
授与年月日:2016年5月31日,
学位の種別:課程博士,
審査員:花岡 伸也,髙田 潤一,山下

幸彦,朝倉

康夫,福田

Citation(English)

Degree:Doctor (Engineering),
Conferring organization: Tokyo Institute of Technology,
Report number:甲第10263号,
Conferred date:2016/5/31,
Degree Type:Course doctor,
Examiner:,,,,

学位種別(和文)

博士論文

Type(English)

Doctoral Thesis

Powered by T2R2 (Science Tokyo Research Repository)大輔

INTERMODAL HUB-AND-SPOKE TRANSPORT NETWORKFOR AN ARCHIPELAGIC COUNTRY, THE PHILIPPINESA Dissertation
Submitted to the Department of International Development Engineering
Graduate School of Science and Engineering of Tokyo Institute of Technology
in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Anita II Alvarez Odchimar

ACKNOWLEDGEMENTSFirst and foremost, I would like to express my gratitude to my supervisor
Professor Shinya Hanaoka for the opportunity to conduct doctoral studies in hislaboratory. He has provided me professional guidance, expertise and opportunities
that are valuable to the research. I am very thankful for the patience and support hehas given me, making me actually appreciate my field of research.
I am also indebted to Professor Nobuaki Otsuki for being instrumental in myfirst acceptance to the International Graduate Program of Tokyo Tech in 2009. Also, I
am grateful to the Monbukagakusho Scholarship for the financial means to study inJapan.
I would like to express my appreciation to the thesis committee, Prof. Yasuo
Asakura, Prof. Daisuke Fukuda, Prof. Jun-ichi Takada and Prof. Yukihiko Yamashita
for their kind comments and suggestions toward the improvement of the dissertation.
I also acknowledge the precious time, assistance, data and knowledge thevarious Philippine government agencies (Philippine Ports Authority, Cebu Ports
Authority, Maritime Industry Authority, National Statistics Office, etc.), shipping
companies and freight forwarders have shared that have become essential inputs tothis study.
I am also thankful to the members of the Hanaoka Research Group, toAssistant Professor Kumiko Nakamichi for her kindness and assistance whenever I
need help, and to all laboratory members whose company made my PhD life morebearable and, at certain parts, enjoyable.
My appreciation also goes to my friends who patiently listened to me when I
had to vent about the trivialities of everyday life during the course of my PhD. Theirencouragements and support helped me not give up and instead continue toward thecompletion of this degree.
Most importantly, I would like to express my deepest gratitude to my parents
and brothers for their love and support. They are my inspiration for this endeavor.
Ad majorem Dei gloriam, for Him who makes all good things possible.

iINTERMODAL HUB-AND-SPOKE TRANSPORT NETWORK FOR
AN ARCHIPELAGIC COUNTRY, THE PHILIPPINES

Anita II Alvarez Odchimar
Tokyo Institute of Technology, 2016

ABSTRACTFor archipelagic regions, physical isolation is a development challenge.
Especially for developing countries where uneven progress among the islands occurs,
communities in small islands with small trade sizes and situated far from large cities
would pay more to send and have access to needed goods. The challenge therefore isto build the region’s infrastructure in a manner conducive to distribute goods andcommodities efficiently using economies of density, while not aggravating othercurrent problems the region is facing.
The Philippines is a developing country with archipelagic characteristics that
could benefit from a seamless spoke-hub transport network design. An intermodal
road–Roll-on Roll-off (RoRo) transport has been in use and promoted by thegovernment to provide seamless transport; while, the use of hub-and spoke has been
advocated by the private sector. While the country’s capital city’s port has the highest
cargo throughput, it is not ideal to be a transport hub since the additional cargo traffic
will increase the truck presence in the already congested roads of the metropolitan.
Therefore, this study i) presents the current position of intermodal road-RoRotransport in the Philippines, ii) develops a hub-and-spoke network model suitable foran archipelagic region, and iii) explores the use of hub-and-spoke network while
shifting cargo from Manila to adjacent port of Batangas to lessen the presence oftrucks that contributes to road congestion in the capital.
The intermodal transport of the Philippines is unique from the motorways ofthe sea of other regions (e.g. Europe) since the self-powered cargo carrying vehicle
traverses chains of islands and seas by RoRo vessels. As starting point, this study
clarifies the current position of intermodal transport in the country by conducting aiiquestionnaire survey with freight forwarders as respondents. The survey tackles theshares of the following domestic cargo transport modes i) container vessel transport,ii) intermodal road–RoRo transport and iii) air transport; and the attributes that affectshippers’ mode preferences. Survey results show that the top influential attributes tothe choice of intermodal road-RoRo transport are transport time, transport cost,frequency of vessels and reliability in terms of delay. Transport times and transport
costs are estimated for several origin-destinations for both intermodal road-RoRo andcontainer vessel transport choices. The following could be drawn from the results: i)dominance of intermodal transport for destinations along the western seaboard(Mindoro, Panay and Negros) from Manila could be attributed to lower transport time
and transport cost, and high frequency of vessels; ii) lower container transport costs
from Manila to farther destinations more than 600km away, and the daily container
vessel’s regular trips to some destinations, could have led the higher share of interisland container vessel; and iii) estimated transport cost and transport time forintermodal transport are lower for Manila to Tacloban in the eastern seaboard but thehigher share of container vessel transport could be due to the poor quality of road.
Next, a hub-and-spoke network suitable for archipelagic setting is developed
incorporating intermodality of land mode (truck) and sea modes (container vessel and
RoRo vessel modes), and the properties of multiple allocations, non-restrictive
networking policy and general hub network topology; all of which have not beentackled simultaneously in one network model by other studies. The model here allows
direct origin-destination calls without going through hubs thus coined as “mixednetwork”. The Philippine scenario is considered for the numerical data and the large
network problem of 25 nodes and up to 6 hubs cases is solved using Lagrangian
relaxation heuristic. The model is able to locate hub ports where cases of intermodal
road-RoRo and container transport could transship and be used complementarily. The
proposed mixed-network model results in considerable total network transport costsavings compared with only direct transport case.
Lastly, a mixed hub-and-spoke network is modeled taking Batangas, Cebu andBacolod as locations for hub ports. With this strategy, 11 to 23% of cargoes intended
for Manila port would be shifted to Batangas port while there would be transport costs
saving by shippers, as well as shipping costs reduction by shipping lines wheniii

operation is restructured from multi-port calling to direct calls within hub-to-hub.
Shift in cargoes entails that the presence of trucks in the metropolitan area adjacent to
the ports would be lessened and thus help decongest the roads in the area. From theresults, policy suggestions are drawn such as improvement of port facilities for quick
operations of multimodal transport and providing incentives in using Batangas port in
the form of discounts or port fees elimination.
This study therefore contributes (i) knowledge on intermodal road-RoRotransport for archipelagic geography and its choice basis, (ii) on the development a
hub-and-spoke network suitable for an archipelagic setting, and (iii) on the feasibility
utilization of a hub-and-spoke network and cargo shifting in reducing the number oftrucks intended for Manila port and, thus, lessen the presence of trucks in the capitalthat contribute to road congestion.

iv

TABLE OF CONTENTS

LIST OF FIGURES ....................................................................................................... viii
LIST OF TABLES ............................................................................................................ x
LIST OF ABBREVIATIONS ........................................................................................ xiii
Chapter 1 Introduction ...................................................................................................... 1
1.1 Background........................................................................................................ 1
1.2 Research Objectives .......................................................................................... 4
1.3 Scope and Limitations of the Research ............................................................. 4
1.4 Outline of the Thesis ......................................................................................... 6
1.5 Contributions of the Study................................................................................. 8
Chapter 2 Literature Review ............................................................................................. 9
2.1 Introduction ....................................................................................................... 9
2.2 Maritime Transport in the Philippines............................................................... 9
2.2.1 The Domestic Shipping Industry ........................................................ 9
2.2.2 Port System in the Philippines .......................................................... 13
2.3 Intermodal Transport ....................................................................................... 15
2.3.1 Difference between Intermodal Transport of thePhilippines and other Regions ................................................................... 15
2.3.2 Impacts of the Road-RoRo Intermodal Transport in thePhilippines.................................................................................................. 16
2.3.3 Preference for Intermodal Transport with RoRo Shipping ............... 19
2.4 Hub-and-Spoke Transport Network ................................................................ 20
2.4.1 Definition, Classifications and Assumptions .................................... 20
2.4.2 Economies of Density and How it is Embedded in Huband-Spoke Models ..................................................................................... 23
2.4.3 Heuristics Used in Solving Hub-and-Spoke Network
Problems .................................................................................................... 25
2.5 The Road Congestion Problem of Metro Manila and the Proposed
Solutions .................................................................................................... 25
2.6 Estimation of Shipping Cost ............................................................................ 26v

2.7 Chapter Conclusion ......................................................................................... 30
Chapter 3 Intermodal Road-RoRo Transport in the Philippines, its
Development and Position in the Domestic Shipping ............................... 32
3.1 Introduction .................................................................................................... 32
3.1.1 RoRo Transport Prior to Road RoRo Terminal System(RRTS) ....................................................................................................... 32
3.1.2 Inception of the RoRo Policy............................................................ 34
3.1.3 RoRo Routes and Inter-island Shipping Routes ............................... 35
3.2 Intermodal Road-Roro In The Current Domestic Shipping ........................... 38
3.2.1 Field Survey Method......................................................................... 38
3.2.2 Questionnaire Survey Results ........................................................... 39
3.2.3 Transport Costs and Travel Times Comparison between
Intermodal Road-RoRo Transport and Inter-island Sea
Shipping ..................................................................................................... 45
3.2.4 Summary: Mode Choice Condition .................................................. 51
3.3 Chapter Conclusion ......................................................................................... 52
Chapter 4 Intermodal Freight Network Incorporating Hub-and-Spoke andDirect Calls for Archipelagic Geography .................................................. 54
4.1 Introduction ..................................................................................................... 54
4.2 The Characteristics of Archipelagic Philippines Considered in the
Hub-and-Spoke Network Model ................................................................ 54
4.3 Model Formulation .......................................................................................... 58
4.4 Solution Heuristic Development ..................................................................... 62
4.5 Application to the Philippines ......................................................................... 64
4.6 Results and Discussion .................................................................................... 72
4.5.1 Location of Hubs, Total Network Costs and Validity of
the Heuristic Method.................................................................................. 72
4.5.2 The resulting intermodality and incomplete hub network
topology ..................................................................................................... 75
4.6 Chapter Conclusion ......................................................................................... 78
Chapter 5 The Cost Effects of Shifting Cargoes and Port Call from Manila
to Batangas Port as Hub............................................................................. 79vi

5.1 Introduction ..................................................................................................... 79
5.2 Selection of Hub Ports ..................................................................................... 85
5.3 Estimation of the Effect to Carrier’s Profit ..................................................... 90
5.3.1 MV Lorcon Manila Existing Multi-Port Calling Voyage ................. 93
5.3.2 MV Lorcon Manila Hypothetical Inter-hub Direct
Voyage ....................................................................................................... 94
5.3.3 Estimations of Variable Costs Components for the Two
Case Scenarios ........................................................................................... 95
5.3.4 Estimation of the Difference in Profit as Indicator ofInter-hub Tariff Discount ........................................................................... 98
5.4 Transport Costs Savings for Shippers ........................................................... 101
5.4.1 Model Formulation ......................................................................... 101
5.4.2 Results ............................................................................................. 103
5.5 Chapter Conclusion ....................................................................................... 111
Chapter 6 Conclusions .................................................................................................. 112
6.1 Summary of Findings .................................................................................... 112
6.2 Scope of Future Works .................................................................................. 113
REFERENCES ............................................................................................................. 115
APPENDIX A OD Tables ......................................................................................... 124
APPENDIX B Variable Cost Estimation................................................................... 128

vii

LIST OF FIGURES
Figure 1.1: Organization of dissertation ........................................................................... 7
Figure 2.1: Domestic Shipping Cargo Market Share in 2011 ......................................... 11
Figure 2.2: The Philippines Port System ........................................................................ 13
Figure 2.3: Number of Vehicles Passing through the Western Nautical
Highway ..................................................................................................... 17
Figure 2.4: Number of Vehicles Passing through the Eastern Nautical
Highway ..................................................................................................... 18
Figure 2.5: Allocation Schemes for HS Network ........................................................... 22
Figure 2.6: Examples of Forms of a Hub Network ......................................................... 22
Figure 2.7: Example of Non-Restrictive Hubbing .......................................................... 22
Figure 2.8: Model incorporating properties deemed suitable for archipelago ................ 22
Figure 2.9: Cost structure of a hypothetical ship ............................................................ 26
Figure 3.1: The three main trunklines of the Strong Republic Nautical
Highway ..................................................................................................... 36
Figure 3.2: Lateral RoRo Links in the Visayas ............................................................... 37
Figure 3.3: Percentages of cargo shipped by each mode type ........................................ 40
Figure 3.4: Locations of selected destinations ................................................................ 46
Figure 3.5: Average transport cost of 10 and 20 footer container by interisland shipping ........................................................................................... 47
Figure 4.1: Simplified illustration of incomplete hub network ...................................... 55
Figure 4.2: The characteristics of the Philippine archipelago......................................... 56
Figure 4.3: Simplified representation of the proposed HS model .................................. 60
Figure 4.4: Iterative process of the Lagrangian relaxation heuristic .............................. 63
Figure 4.5: Location of 25 port nodes ............................................................................. 66
Figure 4.6: Total Domestic Inbound and Outbound Cargo Volumes ............................. 68
Figure 4.7: Number of Registered Freight Vehicles ....................................................... 68

viii

Figure 4.8: Tariff versus distance of the 3 modes of transport, namely landby container or truck, RoRo vessels and container vessels ....................... 69
Figure 4.9: Cargo flows that are routed through hubs for the case of N=25,
p=4 and α=0.7, direct flows are not included. Weight of thelines is indicative of the relative volume of flow ....................................... 77
Figure 5.1: Road Traffic Volume and V/C Ratio based on Traffic
Assignment Model in 2012 ........................................................................ 80
Figure 5.2: Containerized domestic cargo throughput for Manila North
Harbor in Metric Tons ............................................................................... 82
Figure 5.3: Location of Batangas Port relative to Manila ............................................... 83
Figure 5.4: Locations of the Selected Hub Ports ............................................................ 85
Figure 5.5: Existing multi-port calling route of Lorcon Manila ..................................... 90
Figure 5.6: Hypothetical inter-hub direct transport route from Batangas to
Bacolod ...................................................................................................... 90
Figure 5.7: Conceptualization of Total Shipping Cost ................................................... 93
Figure 5.8: Percent tariff discount for inter-hub transport ............................................ 101

ix

LIST OF TABLES
Table 2.1 Services Provided by the Domestic Inter-island Shipping Industry ............... 10
Table 2.2 Domestic Merchant Fleet Profile for Cycle Year 2014 .................................. 10
Table 2.3 Domestic Shipping Stakeholders .................................................................... 12
Table 2.4: Cost structure of container shipping .............................................................. 27
Table 2.5: The three main categories of shipping cost ................................................... 28
Table 3.1 Daily trip frequencies of short-distance RoRo links along the three
nautical highways....................................................................................... 37
Table 3.2 Less frequent weekly trips of long-distance inter-island shipping
originating from Manila ............................................................................. 38
Table 3.3 Classification of companies interviewed for the survey ................................. 40
Table 3.4 Sample Number per Destination ..................................................................... 41
Table 3.5 Scores of influential attributes for the choice of Air Transport ...................... 43
Table 3.6 Scores of influential attributes for the choice of Inter-island Sea
Transport .................................................................................................... 43
Table 3.7 Scores of influential attributes for the choice of Intermodal RoadRoRo Transport .......................................................................................... 44
Table 3.8 Vessel Tariff for 10-wheeler truck.................................................................. 47
Table 3.9 Other incurred costs other than vessels tariffs for both inter-island
sea transport and intermodal road-RoRo transport .................................... 48
Table 3.10 Estimates of total transport costs and travel times for inter-island
shipping and intermodal road-RoRo transport ........................................... 49
Table 3.11 Cost per ton basis considering maximum payload of both modes ............... 50
Table 4.1 Input variables................................................................................................. 59
Table 4.2 Decision variables ........................................................................................... 59
Table 4.3 Quantity Domestic Trade data in Million Tons .............................................. 67
Table 4.4 Port fees .......................................................................................................... 67xTable 4.5 Shipping Lines interviewed for RoRo and Container vessel tariff
data ............................................................................................................. 69
Table 4.6 Common load-carrying capacity in cubic meters of containers andvehicles................................................................................................ 70

Table 4.7: Definitions of symbols used .......................................................................... 71
Table 4.8 Results of the mixed network problem ........................................................... 72
Table 4.9 Flows routed through hubs for the case of N=25, p=4 and α=0.7 .................. 76
Table 5.1 Number of Registered Vehicles in GCR from 2007 to 2013 .......................... 81
Table 5.2 Foreign and domestic container throughput and capacity of
selected ports .............................................................................................. 82
Table 5.3: Summary of the possible effects of the strategy to thestakeholders................................................................................................ 86
Table 5.4: Value of Commodities that Flow from the National Capital
Region in Thousand Pesos (2012) ............................................................. 87
Table 5.5: Shipping companies Serving Manila-Cebu (vice-versa) Routeand Their Vessel Frequencies for the Month of August ............................ 88
Table 5.6: Shipping Lines Serving Manila-Bacolod (vice-versa) Route andTheir Vessel Frequencies for the Month of August ................................... 89
Table 5.7: Lorenzo Shipping Lines Company Vessel Information ................................ 91
Table 5.8: Notations for routes, ports and vessels .......................................................... 91
Table 5.9: Existing Vessel Route and Schedule ............................................................. 93
Table 5.10: Hypothetical Vessel Routes and Schedule for Inter-hub Voyages .............. 94
Table 5.11: Domestic Vessel Dockage Fee in Government Ports .................................. 95
Table 5.12: Calculated charge at port for MV Lorcon Manila ....................................... 95
Table 5.13: Calculated fuel cost at port i by the MC Lorcon Manila ............................. 96
Table 5.14: Wharfage and Stevedoring Charges for 1 TEU Container .......................... 97xi

Table 5.15: Variable costs of vessel and calling types as function of loadfactor .......................................................................................................... 98
Table 5.16: Tariff for 1 TEU container for transport between ports .............................. 98
Table 5.17: Input variables ........................................................................................... 102
Table 5.18: Decision variables ...................................................................................... 102
Table 5.19: Shifted Cargo Volume Intended for Manila Ports (Metric Ton) ............... 104
Table 5.20: Case 0.7 discount factor in hub-to-hub transport (F=100%) ..................... 105
Table 5.21: 0.6 discount factor in hub-to-hub transport (F=100%) .............................. 107
Table 5.22: Additional details for the case of 0.6 discount factor (F=100%) ............... 109
Table 5.23: Transport modes taken per link for the resulting cargo flows of
the case of 0.7 discount factor in hub-to-hub transport(F=100%) ................................................................................................. 110
Table 5.24: Transport modes taken per link for the resulting cargo flows of
the case of 0.6 discount factor in hub-to-hub transport (F =100%) ....................................................................................................... 110
Table A.1: Estimated Origin to Destination Cargo Volume Flow in TEU ................... 124
Table A.2: Estimated Origin-Destination Cargo Volume Flows in Thousand
Metric Tons for the Year 2012................................................................. 126

xii

LIST OF ABBREVIATIONS
ADB
ARRM
ATS
BCDA
CEZA
CPA
DOTC
ECMT
FCL
GCR
HS
IFO180
IPA
JICA
LGU
Lo-Lo
LSC
LTL
MARINA
MCPT
MGO
MMDA
NCR
NEDA
NSO
PIA

: Asian Development Bank
: Autonomous Region of Muslim Mindanao: Aboitiz Transport Systems Corp.
: Bases Conversion Development Authority: Cagayan Economic Zone Authority: Cebu Port Authority: Department of Transportation and Communication: European Conference of Ministers of Transport: Full Container Load
: Greater Capital Regions: Hub-and-Spoke: Intermediate Fuel Gas Oil 180: Independent Port Authorities: Japan International Cooperation Agency: Local Government Unit
: Load-on load-off or conventional liner system: Lorenzo Shipping Corporation: Less Than Truckload: Maritime Industry Authority: Mindanao Container Port Terminal: Marine Gas Oil: Metro Manila Development Authority: National Capital Region: National Economic Development Authority: National Statistics Office: Phividec Industrial Authority

PHP: Philippine Pesos

PPA
PTP
RoRo
RRTS
SBMA
SEC
SFOC
SLEX
SRNH
SSS
STAR
TEU
V/C

: Philippine Ports Authority: Purely Point-to-Point: Roll-on Roll-off: Road-RoRo Terminal System: Subic Bay Metropolitan Authority: Security and Exchange Commission: specific fuel oil consumption: Southern Luzon Express Way: Strong Republic Nautical Highway: Short Sea Shipping: Southern Tagalog Arterial Road
: Twenty-foot Equivalent Unit
: Volume-Capacity ratioxiiiChapter 1: Introduction
1.1 BackgroundA country with islands geography, especially that of a developing one, faces
challenges in terms of trade and transport. Uneven development is common for a developing
country which entails that some island communities are small and marginalized and could
even be situated far-flung from the large cities. These islands would have small trade sizes
thus pay more to send or have access to their needed goods. The challenge therefore is infinding a way to build the country’s infrastructure in a manner that will efficiently distribute
goods and commodities using economies of density.
A country facing such challenges is the Philippines. The Philippines has a uniquegeography characterized by 7,107 islands of which around 2,000 are inhabited. The
archipelagic characteristic demands an especial approach to connectivity – (1) the ability to
not just enable seamless transport for cargoes and people but also (2) facilitate transport cost
efficiency of which one manner is by realizing economies of density. Pienaar (2013) defines
economies of scale as existing “when an expansion of the output capacity of a firm, fleet or
plant causes total production costs to increase less than proportionately to the increasing
output capacity”. And since ships often operate as separate business entities, economies ofscale in transport (or shipping) often refers to vehicle rather than firm, fleet or plant size.
Hence, two types of economies of density are distinguished by Jansson and Shneerson(1985), economies of scale of the size of the firm and economies of density. In this study, thefalling average cost is attributed to the increase in utilization of existing vehicle fleet (in thiscase container vessel) for a particular route, which is within the definition of economies ofdensity.
Thus, this study’s goal is to aid the two demands mentioned by exploring the
combination of intermodality to provide seamless transport and hub-and-spoke (HS)transport to facilitate economies of density.
High cost of domestic cargo transport has been a prevalent issue in the country.
Many could not understand why it is more expensive to ship containers domestically, from
Mindanao (the largest island in the south of Philippines) to Manila, than from the capital toHong Kong. Later on, it was identified that the cost and inefficiency of the cargo handlingcharges in the conventional container transport system was the major factor in the high costof domestic transport (Basilio, 2008).

The Roll-on Roll-off (RoRo) policy was issued in1

2003 of which key features encouraged the use of intermodal transport by land (using truck)and by sea (truck loaded into RoRo vessels) as alternative or competition to the conventional
container vessel transport. This is facilitated by the development of the Road-RoRo Terminal
System (RRTS), a network of RoRo ferry terminals linked all over the country by RoRo
ferry ships. Initial assessments of Basilio (2008) and ADB (2010) report that the policy
brought positive impacts; however, the paper of Kobune (2008) shows that the advantage of
RRTS is overemphasized only for its quick procedure at terminals (because transport
through RoRo does not require cargo handling), and is competitive to the inter-island
shipping in terms of total transport cost only within a specific distance (200km). A study istherefore needed to present greater knowledge on the current position of intermodal roadRoRo transport in the Philippines, its advantages over the conventional or container meansof inter-island shipping, and the attributes that influence mode choice by providing
literatures reviews, conducting field survey and survey interviews with freight forwarders.
There are several studies about RoRo as part of an intermodal system (Paixao andMarlow, 2002; Torbianelli, 1999, 2000; Woxenius, 2012), and advantages of the system overcontainer transport have been cited. However, these studies are in the context of short sea
shipping (SSS) and motorways of the sea (e.g. in Europe, Asia-Europe, North America andAustralia) where intermodal systems generally only involve one sea leg and are incompetition with land-based transports. The intermodal system of the Philippines is uniquein that the vehicles in road-RoRo intermodal shipments traverse chains of islands and seas,or several land and sea legs, to compete with the long-distance container shipping. The
preference for and the advantages of this system in an archipelagic context over the containertransport mode has not been clarified.
Moreover, a more recent act, the Republic Act (RA) no. 10668, was signed by the
President in July of 2015, which allows foreign vessels to transport and co-load foreign
cargoes for domestic transshipment and other purposes. This amends the 50-year-old
Cabotage law and eyes at creating a more level playing field on competition and offer cost
reductions in domestic shipping. The act allows foreign vessels, arriving from a foreign port
to a port of entry, to carry foreign cargo, originally its own or by another foreign vessel
calling at the same port of entry, to any port in the country. Moreover, it also authorizes
foreign vessels to take cargo intended for export at any Philippine port, and convey the samecargo upon itself, or by another vessel calling in the same intermediary transshipment port,
to a foreign port. The act is in its very early stages of implementation and would take time
for its full effects to be felt.
2

RA 10668, though to an extent anticipated, is a latter policy; this research has been
conceptualized before it was signed. The act will indeed increase competition, but on one
hand, could harshly affect the domestic shipping players if they do not improve theirservices. One way to be competitive is to modernize their fleets and operations. Another way
is to facilitate economies of density which could be done by employing a hub-and-spoketransport network.
Furthermore, the use of hub-and-spoke network is advocated by the private sector.
The Joint Foreign Chambers of Commerce of the Philippines suggests that to increase thecountry’s competitiveness among neighboring countries, a hub-and-spoke system should bein place with developed ports for larger ships and with cargoes delivered from smaller
production centers by truck or small RoRo (JFC, 2010). Hub-and-spoke network models
have been developed but some of common properties often employed in existing studies are
not favorable to an archipelagic country, such as ‘strict and restrictive hubbing policy’ and‘single allocation’ properties. There is a lack of studies that applies hub-and-spoke to anarchipelagic context, thus this study attempts at providing suitable model that also
incorporates intermodal transport.
The Philippine Development Plan 2011-2016 pointed out the ‘lack of integrated andcoordinated transport network’, thus the planning focus is to come up with a seamless
multimodal system by upgrading the quality and capacity of existing transport infrastructures
based on a strategy that takes modal complementarity into account (NEDA, 2011). The
developed model could be used to identify which ports are best to be allocated investments
for upgrade.
The developed network model is then applied as part of a solution to alleviate thecongestion of Manila roads. Manila ports have 51% and 84.2% share of domestic andforeign container throughput, respectively, which exceed the ports’ capacities (Philippine
Ports Authority (PPA), 2012). A truck ban imposed in 2014 for the purpose of decongesting
the roads in Manila led the already over-utilized port to be more congested, which in turn led
to big economic loses (Cruz, 2014). Thus, cargo flow shift to the adjacent port in Batangas incombination with hub-and-spoke transport configuration is explored as a solution to lessen
the presence of trucks in the highly congested roads adjacent to the Manila port.

3

1.2 Research Objectives
The aim of the study is to design a cargo transport network model suitable for acountry with archipelagic geography that, in parallel, would enable seamless transport byintermodal transport and cost efficiency brought by density economies of density. The
concept of hub-and-spoke provided by the model would in turn used to alleviate traffic in
Metro Manila. To achieve this aim, the following objectives are drawn:
1. To clarify the current position and mode share of intermodal road-RoRo transport in thePhilippines over the conventional or container means of inter-island shipping, and theattributes that influence mode choice .
2. To model a hub-and-spoke network suitable for an archipelagic geography which
incorporates transport intermodality.
3. To explore the use of hub-and-spoke network and cargo shifting from Manila toadjacent port of Batangas as hub port to help reduce the presence of trucks in Metro
Manila which contribute to road congestion.

1.3 Scope and Limitations of the Research
The study considers cargo transport only and does not tackle passengers. While airtransport has market share as determined in Chapter 3, it is relatively small and is notconsidered in the estimation of transport costs and travel times in the same chapter as well as
in the network models of Chapters 4 and 5. Only sea-base modes (container and Roll-on
Roll-off vessels) and land base transport (20-footer container in chassis maneuvered byprime mover and 10-wheeler truck) are considered.
In Chapter 3 survey for mode share and attributes influencing mode choice, thesurvey is limited in the number and classification of respondents but the results are able tooffer an overview of the current situation of intermodal road-RoRo transport and its
competition with inter-island shipping.
The following are the limitations and assumptions taken in the development andapplication of the hub-and-spoke network model:a. Capacity constraint for ports is not considered-Port capacity constraint is not considered because one of the purposes of the model is
to identify the location of hub ports where future investments for capacity and facility
upgrade will be allocated.

4b. Capacity constraint for link is not considered-

The model is based on volume of flow and not on vessel capacity and frequency. The
aim of the model is to determine the allocation of volume flows with noconsideration of the capacity of the link (vessel capacity x frequency).

c. Travel time constraint is not considered-

Congestion may occur in a hub-and-spoke network, thus travel time is an importantfactor. However, since we do not consider constraints of capacity of hubs and links,
which also affects travel time, we also do not consider constraint in travel time.
Travel time would be affected by transshipment time at hub ports, which in turn isaffected by factors such as port capacity, waiting time at anchorage, port facilities
capability, size of vessel, etc. This is, however, considered for future study.

d. Only one cargo loading unit, 20-footer container, is considered for the whole network.
-

This is for the purpose of simplification. Though, it is acknowledged that other cargo
units exist such as 10-wheeler truck, 10 footer container, 40 footer container, etc.

e. Similar to the most classical hub-and-spoke models, the discount factor (α) in transport
cost brought by bundling of cargoes (economies of scale, or in this study we use the term
economies of density) is only applied to inter-hub flows. It is the limitation of the study
that one value for α is used for the whole network at one time, and the parameter is notcargo flow volume dependent. In the model, the bundling of cargoes is therefore aneffect of the exogenous nature of the discount factor.
This is somehow a necessary simplification since the cost minimization is for thewhole network with many modes and fleets as players, and not with a single vessel only,
thus the shipping cost for every mode and vessel type for every link as a function ofcargo volume, in my opinion, would be highly challenging to construct.
Moreover, shipping companies resist divulging their financial information thus itis difficult to estimate the amount of tariff discount shipping companies could offer withincrease in volume. Thus, economies of density, as represented by the α parameter in themodel is assumed to be 0.5, 0.7 and 0.9 for Chapters 4, and 0.6, 0.7, 0.8 and 0.9 for
Chapter 5. However, Chapter 5 attempts at justifying the discount factors used in theassumptions by estimating the percent increase in profit gained by a shipping company
for serving direct transport between a certain hub-to-hub route which could be translated
to the percent discount they could give to shippers for inter-hub transport.
f. Only two-hub stop is considered in this study, and not allow one-hub stop, since the goal
is to let even the islands with small trade volumes participate in trade in long distances.
5

The two-hub stop is deemed appropriate for this purpose at it consolidates volumes andenables economies of density for inter-hub transports. The one-hub stop would beappropriate in short distance as reported by Sasaki et al. (1999); however, it is thelimitation of this study that we are not able to consider this case.
1.4 Outline of the Thesis
The thesis comprises of six chapters as shown in Figure 1.1. The details of which are
as follows:
Chapter 1 introduces the background, the research objectives and the outline of thethesis.
Chapter 2 provides the reviews of literatures on the following topics: (a) shipping andports industry in the Philippines, (b) intermodal transport with RoRo shipping and the choicetheory for selecting Ro-Ro, (c) HS network modelling, its properties and the heuristics forsolving large problems and (d) carriers shipping costs and economies of density.
Chapter 3 details the development of the intermodal road-RoRo transport in thePhilippines and its current position in the domestic shipping market. This chapter presents
the data from field survey namely shipping tariffs, port fees, port locations and cargo flow
volumes. A questionnaire survey was conducted to determine the usage share of modes forselected destinations from Manila (the capital) as well as the attributes that influence thechoice for the mode.
The data from the field survey in Chapter 3 are used as input data to the intermodal
hub-and-spoke network model developed in Chapter 4. The model incorporates properties
deemed suitable for archipelagic scenario. The model is then applied to the Philippines. The
heuristic used to solve the large problem and the resulting savings in total network costcompared to the direct transport case are explained.
In Chapter 5, the concept of hub-and-spoke in conjunction with cargo shifting from
Manila port to Batangas port as hub is employed as a solution to lessen the presence oftrucks in Metro Manila and consequently help the traffic situation. The cost effects oftransferring to Batangas port for shippers and shipping companies are estimated to infer thefeasibility of employing the strategy and be able to suggest appropriate policies.
Chapter 6 summarizes the new findings of this research and details suggestions forfurther research.

6

Chapter 1
Introduction

Chapter 2
Literature Review

Chapter 4Intermodal Freight Network
Incorporating Hub-and-Spoke andDirect Calls for Archipelagic
Geography

Chapter 3
Intermodal Road-RoRo Transport in
the Philippines, its Development andPosition in the Domestic Shipping

Outputs:(1) Location of hub ports(2) Allocation of cargo flows(3) Transport cost efficiency overDirect Point-to-Point Transport(4) The concept and model itself

Outputs:(1)Data from domestic shipping survey
 Transport costs for truck, RoRo,container and intermodal modes(including tariff, port fees, tolls)
 Locations ports and distances between
ports(2) Mode Share(3) Attributes that influence mode choice

Chapter 5
The Cost Effects of Shifting Cargoes andPort Call from Manila to Batangas Port as
Hub
Outputs/result:(1) Maximum shifted cargoes from
Manila to Batangas hub port
(2) Decrease in shippers’ freight
forwarder total network transport
cost(3) Increase in shipping company’s
profit for one vessel

Chapter 6

Conclusions
Figure 1.1 Organization of dissertation
7

1.5 Contributions of the StudyFirstly, this study clarifies the regulatory changes and emergent landscape of rollon/roll-of shipping in the Philippines that helps build knowledge to this area. The study also
provides the mode choice preferences for intermodal transport with RoRo shipping through achain of islands that is distinct from those studied previously such as the short-sea shippingand motorways of the sea of other regions (e.g. Europe, Asia-Europe, Northern America andAustralia).
Secondly, the developed hub-and-spoke network model establishes a basepoint for
future research on the topic for archipelagic geography settings, since the application onarchipelagic context has not been delved into previously. The model also could be areference for the government or social planner in determining the location of hub ports as toappropriate investments for infrastructure development and guide in drafting policies thatwould encourage both shippers and carriers to make use of hub ports and facilitate the huband-spoke transport.
Lastly, this study also explores the application of the hub-and-spoke network concept
to help reduce the presence of trucks in Metro Manila which contributes to road congestion,
which concept could also be considered as future strategy to make domestic vessels
competitive with international vessels amidst the new more laxed cabotage law. The findings
could aid domestic liner shipping companies for their future strategy and the government in
future policy-making.

8Chapter 2: Literature Review
2.1 Introduction
Fundamental concepts from existing literatures are reviewed as starting point. The
succeeding sections tackle the following: 2.2) reports and studies on cargo shipping existingin the Philippines and the maritime modes that are in use; 2.3) studies on the concept ofintermodal transport, types of intermodality existing in other regions and the choice
preferences on intermodal transport involving RoRo mode, as this supports the discussion
about the intermodal transport in the Philippines which is presented in Chapter 3; 2.4) the
hub-and-spoke network concept and modelling; 2.5) the road congestion of Metro Manila;
2.6) shipping lines cost function and concept of economies of density. Lastly, Section 2.7)
presents the gaps in literature which this study intends to fill.
2.2 Maritime Transport in the Philippines
Because of the archipelagic characteristic of the country, maritime transport has been
the major means by which cargoes are moved between islands. From the National Statistics
Office (NSO) 2013 data of Commodity Flow, 99.80% inter-regional commodity trade isdone by water, with the remaining percentage done by air transport. This section provides
literature review on the two sectors relevant to maritime transport of cargoes: the shipping
and ports industry.
2.2.1. The Domestic Shipping Industry
There are several types of shipping services at work for the domestic cargo andpassenger transport in the Philippines as presented in Table 2.1.
Liner, tramper, RoRo and industrial carriers are among the shipping service types
that handle cargoes. Of the 10,694 merchant fleets registered in 2014, 28.53% or 3,051 arecargo vessels. The breakdown of the fleets is shown in Table 2.2.
In 2013, 2,497 domestic operators serve 14 primary routes which handle domestic
volume of national significance and usually cover the major ports of the country, 102 aresecondary routes which handle domestic volume of regional significance and are linked toports of lesser throughputs than major ports, and 1,600 are tertiary routes or feeder routes
that handle cargoes consolidated and destined for primary and secondary ports (MARINA,
2013).
9

Table 2.1: Services provided by the domestic inter-island shipping industry(Source: Llanto, et al., 2007)
Shipping Service Type

Description

Liner

Follows fixed sailing schedules, regular ports of call(routes) and frequency of travel. These handle bothpassengers and cargoes.

Tramper

Do not follow a regular route and schedule, and arecontracted (chartered) by shippers to deliver cargoes fromport to port. These only handle cargoes.

Tanker

These specialized vessels transport oil, chemicals, and LPG.

Fast craft, ferry, andThese vessels travel short distances. They mainly cater

wooden boat

passengers.

RoRo

These are vessels used for short distance travel, and canaccommodate passengers, vehicles and cargo-carrying
vehicles.

The service has a fixed schedule and a regularroute. There is no cargo handling involved since the cargoes
are “moving” (self-propelled) cargoes
Industrial carrier

Vessels owned and used by companies to transport theircargoes and, in many cases, are using their own ports.

Tugs, barges

Used in ship-to-shore loading and unloading of cargoes.

Table 2.2: Domestic merchant fleet profile for Cycle Year 2014, Source: Borci, 2015
Type Of Service
Passenger
Cargo
TankerTugboatPleasure/Yacht
OthersDredger
Special Purpose Ship
Miscellaneous Ship
TOTAL

Number
6,555
3,051
249
566
33
118
28
16
78
10,69410

According to Llanto et al. (2013), the primary routes are served by four major shipping lines
operating 17 long haul vessels. These major shipping lines are not specified in the study, but
Figure 2.1 shows the domestic cargo shipping market share published in 2011. In the same
year, Negros Navigation Co. Inc. and ATS Consolidated Inc. had a merger and branded theircompany as 2Go Group Inc.

Figure 2.1: Domestic shipping cargo market share in 2011
Source: Marina Maritime Review, 2011

In 2014, 2Go Group Inc. has 33% of the freight market as presented in their 2015
Maritime Committee Meeting. From the 2014 annual report of Lorenzo Shipping Corp.
(LSC), the other containerized cargo shipping companies they consider as competitors are
2Go Group Inc. (Aboitiz Transport Systems Corp. (ATS) and Negros Navigation Corp.),
Philippine Span Asia Carrier Corp. (a.k.a. Sulpicio Lines Inc.), Solid Shipping Inc., NMC
Container Lines, Inc. and Oceanic Container Lines, Inc. As can be deduced from thepreceding statement, there are several shipping lines competing for market share in thedomestic cargo shipping.
While the primary routes are serviced dominantly by container vessels, the secondaryroutes are served by RoRo vessels operated by 34 shipping companies (Llanto et al., 2013).
Among these are listed in Table 3.1 of Chapter 3.
The Maritime Industry Authority (MARINA) is the shipping government agency
with both developmental and regulatory functions. It regulates all carriers and shipping
companies, including those in logistics. MARINA exercises its regulatory functions throughthe issuance of a Certificate of Public Conveyance defining the routes and safety regulations,11and fixing the rates of passenger fares and cargo freight. The other stakeholders of thedomestic shipping industry are presented in Table 2.3

Table 2.3: Domestic shipping stakeholders (Source: Llanto, et al., 2007)
Institutions

Description/Function

MARINA

Government agency tasked to oversee the development
and promotion of the shipping industry. Vested witheconomic regulatory powers.

Philippine Coast Guard

Together with Philippine Ports Authority (PPA) andMARINA, tasked to implement safety shipping-related
marine pollution rules and standards, maintains andoperates aids to navigation, and enforces maritime laws
and regulations.

Shipping companies

Domestic and foreign shipping companies calling at
Philippine ports.

Shippers

Private cargo owners; port users (exporters/importers,
domestic manufacturers, traders,).

Forwarding companies

Provides cargo consolidation and freight forwarding
services.

Trucking companies

Inland trucking service providers.

Forwarding companies,

Providecustoms brokers, and 4th

requirements at every stage of the logistics chain,party logistic providers

includingservicestotracking,

shippers,

by addressing

documentation

and

all

customs

clearance.
Consumers/passengers

The general public whose interest the MARINA is
supposed to protect.

Ship classification

Applies ship inspection rules for vessels 500GRT andabove, in accordance with International Association ofClassification Societies.

Pilotage service companies

Offers pilot services at major ports.

Department of Environment

Regulates all kinds of environmental pollution, including

and Natural Resourcesmarine (e.g., oil spillage, garbage dumping).

Seafarers

Ship officers and crew.

12Commission on Higher

CHED regulates all specialized schools, including those

Education, Maritimethat offer maritime education and training of various

Training Council, TESDA,

types of seamen.

other private and public
maritime schools
National

Regulates all forms of telecommunication, including

Telecommunications

grant of radiofrequencies for vessels whether ship-to-Commission

ship, ship-to- shore, or ship-to- global satellite network.

Professional Regulatory

Licensure (marine engineering / marine transport)

Commission

2.2.2 Port System in the Philippines
The Philippines Ports Authority (PPA) is the national authority that administers andmanages the country’s ports including the establishment and operation of ports. The vast portsystem of the Philippine is categorized into four as shown in Figure 2.2 and is summarized
subsequently as presented in Llanto, et al. (2007).
PHILIPPINE PORT SYSTEM

PPA

PublicPorts

Private
Ports

IPA

DOTC

CPA, SBMA,
CEZA, PHIVIDEC,
ARMM

Municipal
Ports/ Fishing
Wharves

RRTS

PrivateRORO
Terminals

LCU
RoRo
Terminals

Figure 2.2: The Philippines Port System (Source: Llanto et al., 2007)

a. PPA port system
This is the most important and extensive ports network existing, with 239 public
ports and over 349 registered private ports in PPA administrative and operational jurisdiction(Javier, 2008). PPA-owned ports are also developed and maintained by the PPA on top of
being under its supervision.
Private ports are mostly for industrial use, with around 30 ports that are forcommercial use as of 2007, of which one is the BREDCO in Bacolod. The PPA has no13

investment in private ports but receives 50% share from usage/berthing fees and wharfage
dues. The PPA is financially autonomous from the government and earns its revenues fromconcession fees from lease of ports, ports charges and the share from the private cargohandling operators and the share it receives from private operated ports. PPA remits 50% of
its net income as mandated by a 1992 law.
b. Independent Ports Authorities (IPA)
These were created to decentralize control of PPA, to create more competition among
the ports, and allow the local government unit (LGU) to have greater control of its port.
There are six IPAs, namely, Cebu Port Authority (CPA), Subic Bay Metropolitan Authority(SBMA), Cagayan Economic Zone Authority (CEZA), Phividec Industrial Authority (PIA)
which manages the Mindanao Container Port Terminal (MCPT) in Cagayan de Oro,
Autonomous Region of Muslim Mindanao (ARRM) and Bases Conversion Development
Authority (BCDA) which supervises the port in San Fernando, La Union and manages theports in Clark Field, Pampanga.
c. Department of Transportation and Communication (DOTC)-developed feeder ports
These are small fishing ports, landing stages and feeder ports developed and fundedby DOTC and eventually handed over to LGUs. There are about 427 ports of this type in
2007.
d. Road-RoRo Terminal System (RRTS)
This is a network of terminals all over the country linked by RoRo vessels. This wasestablished in 2003 through the Executive Order 170 with the goal of providing greater
access to the island provinces and better integration among the different regions. This wascreated as a response to the private sector’s clamor for a solution to the high cost of transport
from Mindanao to Luzon. Executive Order 170 as well as its enhancement, the EO 170-A,
make intermodal transport of a self-powered vehicle by road and RoRo vessel favorable as
they introduce the nautical networks as an integral part of the national highway system.
Transport through the system is not anymore burdened by any costs and procedures that are
not required in land-based transport systems. The regulatory changes are: removal of cargohandling charges and wharfage fees, freight is based on lane meter, documentary
requirements are simplified, among others. Transport through RRTS has been promoted as
an alternative and a complement to the conventional container transport by container vessel.

142.3 Intermodal Transport
Intermodal transport is the movement of goods in the same loading unit or vehicle bysuccessive modes without handling of goods when changing modes (Bontekoning et al.,2004). This differs to multimodal transport defined by European Conference of Ministers ofTransport (ECMT, 1996) as the carriage of goods by at least two different modes oftransport. The ECMT (1996) also defines the term combined transport to be based onintermodal transport but is characterized by two important supplement items; i) the majorpart of the journey is by rail, inland waterways or sea, andii) any initial/final leg carriedout by road is as short as possible (Andersson et al., 2005). Existing studies often use theterm intermodal transport in the same meaning as combined transport, for the reason thatintermodal transport policy has been strongly advocated especially in European regions as a
remedy to road transport concerns related to reducing congestion and pollution, andimproving safety (Andersson et al., 2005, Bontekoning et al., 2004).
2.3.1 Difference between Intermodal Transport of the Philippines and other Regions
Existing studies on intermodal logistic policy in other regions, namely, EU, U.S. andJapan, have the following policy directions: EU’s main concerns are environmental issues,
highway congestion, and technology improvements and innovations. U.S. stresses on global
connectivity and trade, leading role of industry, market treatment of modes, and energy
problem. Meanwhile, Japan aims at competitiveness, increasingly in the Asia-Pacific market,
and environmental and societal needs (Horn and Nemoto, 2004). The commonality among
the policies is their aim for sustainable development (i.e. economic growth andenvironmental progress with global competitiveness as a primary goal). The intermodaltransport in these regions involve rail, inland waterways or sea as the major part of thejourney and road for the initial/final leg, which is as short as possible.
The intermodal policy in the Philippines meanwhile is geared toward greater
efficiency and lower cost in the inter-island good transport by establishing the RRTS (asreferred to 2.2.2d of this Chapter). It was created to answer the clamor of the business
community for a solution to high cost of transport form Mindanao (the largest island in thesouth) to the capital Manila located in the northern region by the removal of cargo handlingcharges and wharfage dues (Basilio, 2008). The policy only covers self-powered carrying
vehicles that are simply rolled in and off a RoRo vessel by their own wheels. The intermodaltransport in the archipelago is posed as an alternative long-distance mode to the inter-island

15

container shipping by container vessels. To compete in the long-distance, the cargo carrying
vehicle unit traverses through chains of highways and seas (as loaded in RoRo vessels)
which are linked by the network of RoRo terminals. This characteristic makes the advocatedintermodal transport of the Philippines unique among the other intermodal transports of otherregions.
Moreover, the intermodal policy in the country is still concerned about efficiency
through seamless operations in the domestic level, while the other regions’ pursue global
competitiveness, environmental sustainability, and innovation in facilities and operations
toward international standardization (Horn and Nemoto, 2005). The inclusion of chassisRoRo as part of the RoRo service is still a policy recommendation. This means that loading
container on chassis to a RoRo vessel still incurs cargo handling charges since the policy
only covers self-powered vehicles. To include this into the policy will enhance the country’s
competitiveness since domestic transshipment of export and import cargoes will be reduced.
There are very few study about intermodal transport in archipelagic regions. Russ etal. (2005) and Yamada et al. (2009) designed a model for multimodal freight-transport
networks for Indonesia and the Philippines that selects a suitable set of investment actions
from a number of possible actions. They presented the overall transport network model as aleader-follower game, the transport planners as the leader and the network users as thefollower, using bi-level programming for the determination of optimal improvement actions
and user assignment.
2.3.2 Impacts of the Road-RoRo Intermodal Transport in the Philippines
The establishment of the RRTS enables the operation of the road-RoRo intermodaltransport in the country. ADB (2010) and Basilio (2008) have written impact assessments of
RRTS. The reported positive impacts are area development, restructuring of inter-island
shipping, changes in cargo mobility, logistics operations and strategy, increased agricultural
productivity and enhancement in tourism since the implementation of RRTS. The succeeding
paragraphs detail these impacts.
In Roxas, Oriental Mindoro, new commercial establishments mushroomed after the
port of Dangay came into operation. Real estate prices increased from P500-P1,000 toP5,000-P10,000 in 2010. From 2003, tax collections from business enterprises amounting toP2 million per year were added to the municipal total income. Meanwhile, port-related
revenues in Pilar, Sorsogon increase by 84% when Montenegro shipping started its RoRo
operation connecting Pilar to Masbate island.
16Market developments brought by the RoRo policy heightened the level ofcompetition which pushed existing players to restructure their operations. For example, thethen Aboitiz Transport System (ATS) launched its RoRo service (former 2GO company).
Also, Manila as inter-island gateway port was significantly reduced. There are no longer
liner vessel servicing Mindoro from Manila, and the long-distance shipping from Manila to
Panay has been reduced to just the port of Iloilo.
Vehicle numbers passing through SRNH also significantly increased (Figures 2.3 and2.4), more notably for the Western Nautical highway. Aside from the RoRo policy, otherfactors also contributed to the shift in the cargo shipment to the intermodal road-RoRo
alternative, namely, increases in fuel prices which prompted operators to sell old and lessfuel efficient vessels; vessel accidents which caused suspension of shipping lines (e.g.
Princess of the Stars of Sulpicio Shipping Lines); and the higher frequency of RoRo vessels

Quantitiy of Vehicles inthousandtrips which allows little lead time.
700
600

568

2010

2011

604

484

500
400
300

555

254

290

298

2004

2005

339

383

420

200
100
0
2003

2006

2007

2008

2009

2012

Figure 2.3: Number of Vehicles Passing through the Western Nautical Highway
Source: PPA Statistics

The developments brought by the policy also prompted some companies to change
their logistics operations and strategy. For Nestle Philippines, because of the RoRo network
they are able to make small, frequent and direct deliveries to clients ensuring product safety
and shorter lead time. In turn they could reduce their distribution centers, closing 32 out of
36 of the centers around the Philippines, and minimize the need for inventories. On the other
hand Universal Robina Corporation, a food manufacturing company, is enabled to deliver 12
trucks trips a day through SRNH from the previously one shipment a week via liner
shipping. Gardenia Bakeries was also able to expand to new market when the Western
Nautical Highway became operational. Each round trip from its Laguna plant to Iloilo only
17

costs P21,000 using RoRo as opposed to P25,000 per 20-foot container by the traditional
shipping. Frequent RoRo trips enables shorter lead time and faster deliveries giving them

Quantity of Vehicles inthousandlonger number of days to sell the bread products.

200

179
158

150

141

141

2007

2008

167

182

100
50
0
2009

2010

2011

2012

Figure 2.4: Number of Vehicles Passing through the Eastern Nautical Highway
Source: Estimated from PPA Statistics data

The efficiency in transporting by RoRo network also encouraged farmers to increase
their production to take advantage of opportunities to increase income. SRNH, especially theWestern Nautical Highway, opened up new markets to farmers. Fruits from Davao such as
mangosteen and durian found new markets in Iloilo and Bacolod. Some of the vegetable
shipments to Caticlan and Iloilo originate from Baguio. Fish shipments from Estancia to
Manila increased from once a week using traditional shipping to daily via RoRo.
The RoRo links along the Western Nautical Highway enable easy access between
tourism gems of the western Philippines. Dangay Port in Roxas, Mindoro Oriental links
tourists from Puerto Galera to proceed further to Boracay Islands in Aklan (and vice versa).
Greater accessibility and affordability are provided in travelling to Panay island, to Negros
island and even down to Mindanao to visit tourism destinations in Dapitan.
Despite the assessed positive impacts, as mentioned in the Introduction, Kobune(2008) shows that the advantage of RRTS is overemphasized only for its quick procedure atterminals (because transport through RoRo does not require cargo handling), and iscompetitive to the inter-island shipping in terms of total transport cost only within a specificdistance (200km). There is a lack of existing study to support and clarify the position ofintermodal transport in the domestic shipping market. A study is therefore needed to present

18the existing market of intermodal road-RoRo and to what extent and distance range it
competes with the inter-island container transport by container vessel.
2.3.3 Preference for Intermodal Transport with RoRo shipping
As prior mentioned, the intermodal transport in the context of archipelagic
Philippines is unique such that the vehicles in road-RoRo intermodal shipments traverse
chains of islands and seas (or several land and sea legs) to compete with the long-distancecontainer shipping. This is contrary to the short sea shipping (SSS) and motorways of the sea
employed in other regions (e.g. Europe, Asia-Europe, Northern America and Australia)
where intermodal systems generally only involve one sea leg and often are in competition
with land-based transports.
Several published studies tackle RoRo shipping as part of an intermodal system aswell as the choice decision bases for this mode. In general, the advantages of maritime RoRotransport over container transport are (i) greater time efficiency since routes are shuttles andnot intertwining as that of container vessels which causes frequent transshipment andwaiting, (ii) less time consuming cargo handling at ports, (iii) greater loading conditions anddimensions (greater volume, refrigerated units etc.) used up by semi-trailer compared tocontainers, and (iv) able to allow transport companies a sole continual physical connection
with their vehicle thus they could maintain economic and quality control of the wholetransport chain Torbianelli (1999, 2000). Comparison by Woxenius (2012) states that the
SSS ferries have very high commercial and technological flexibility as they have very open
interface between cargo and passengers and accept virtually anything allowed on the road,while container feeder vessels have high commercial openness due to the small parcel size
and the large adoption of containerization over the years but is specialized in its containment
unit. Paixao and Marlow (2002) meanwhile report that both ships compete with land-basedtransports in different distance coverage partly due to logistics cost; RoRo on short distanceswith road transport and container ships on long distances with the rail mode. Containers are
the least expensive mode of carrying goods while RoRo has higher inventory costs thus lackcompetitiveness over long distances. Moreover, the quick turnaround time of RoRo is criticalfor operation in short routes.
For the studies on mode choice, Puckett et al. (2011) reveals that shippers’ choice
between SSS and truck in the Atlantic Canada-US eastern seaboard market is strongly
sensitive to cost and frequency of departure. Feo et al. (2011), using stated preference survey
with Spanish freight forwarders with south-west Europe shipments, report that cost has the19

greatest effect with other significant parameters being transit time, delivery time reliability
and service frequency. While D’Este and Meyrick (1992) found that the top factors in the
choice of RoRo carrier are in the order of frequency, reputation for punctual delivery, transit
time, price and response to problems being of particular concern. Their survey results largely
confirm the findings of several earlier studies, while acknowledging that local conditions canaffect the relative importance of particular decision factors. Meanwhile, Paixao-Casaca andMarlow (2005) identified the factors/service attributes essential for a more competitive
multimodal service in Europe, namely, carrier logistic network design and speed, cost ofservice and reliability/quality, carrier’s representatives sales and after-sales behavior,investment

policy,corporate

image,

commercial/operationalandcarrier-shippers’

relationship policies, involvement in the forwarding industry and service guarantee.
Moreover, Lopez-Navarro (2013) shows evidence that shared planning between roadtransport firms and shipping companies positively benefits intermodal; citing the presence of
incentives for collaboration, the importance of trust within the relationship, and the positiveeffects of adaptation of road transport firms to their shipping companies.
2.4 Hub-and-Spoke Transport Network
2.4.1 Definition, Classifications and Assumptions
In a hub-and-spoke network, cargoes are routed through hub facilities that serve asswitching, transshipment and consolidation points that concentrate flows to take advantage
of economies of density. With this network configuration, less connections are needed toserve O-D pairs than with a purely point-to-point (PTP) network where all nodes are fully
connected. Fewer resources are necessary and demand pairs are served more efficiently.
Maritime industry and freight transportation companies are activities that can take advantage
of a HS concept (Farahani et al., 2013). In their study, Takano and Arai (2009) identify the
hub locations for an 18-port containerized cargo transport network using the quadratic modelof O’Kelly (1987) and concluded that cases of hubbing are more economical than adding
more ships.
The basic classification of a hub network is with regard to the allocation of non-hub
nodes to hub nodes, allowing for either single or multiple allocations as differentiated in
Figures 2.5. Moreover, Alumur and Kara (2008) state that studies in this area often assume
three things: (1) the hub network is complete with a link between every hub pair; (2) there
exist economies of density when the inter-hub connections are used; (3) no direct service
20between two non-hub nodes is allowed. Karimi and Setak (2014) present other forms of a
hub network which relax assumption (1) (Figure 2.6 a-c). A complete network has the formshown in Figure 2.6d. Meanwhile, Figure 2.7 shows an example illustration of “nonrestrictive hubbing”, which relaxes the assumption (3) and allows direct transport from a
non-hub node to another non-hub node.
Single allocation property combined the application of assumption (3) is coined the“strict and restrictive hubbing policy” (Aykin, 1995a), where each node is limited to be
assigned to a single hub for all inbound and outbound services. The same author further
states that in many applications, this policy may impose undesirable and rigid operational
restrictions.
The first mathematical formulation addressing the hub location problem by O’Kelly(1987), with the following formulation, is under the strict and restrictive hubbing policy andcomplete hub network. The same is true for a good number of subsequent works.
𝑀𝑖𝑛 ∑𝑖 ∑𝑗 𝑊𝑖𝑗 (∑𝑘 𝑋𝑖𝑗 𝐶𝑖𝑗 + ∑𝑚 𝑋𝑗𝑚 𝐶𝑗𝑚 + 𝛼 ∑𝑖 ∑𝑗 𝑋𝑖𝑘 𝑋𝑗𝑚 𝐶𝑘𝑚 )s.t.

(𝑛 − 𝑝 + 1)𝑋𝑘𝑘 − ∑𝑖 𝑋𝑖𝑘 ≥ 0∑𝑘 𝑋𝑖𝑗 = 1

for all k,

for all i,

(2.2)
(2.3)

∑𝑘 𝑋𝑘𝑘 = 𝑝,
𝑋𝑖𝑗 ∈ {0,1}

(2.1)

(2.4)
for all i, k.

(2.5)

In the formulation of O’Kelly, The objective function minimizes the total networktransport cost; with the first two terms representing the transport cost for origin to hub andhub to destination, and the third term represents the transport cost between hubs. The
parameter 𝛼 signifies the transport cost discount due to scale economies, or more
appropriately in this study, economies of density. 𝑊𝑖𝑗 is the flow between nodes i and j, and𝐶𝑖𝑗 is the transportation cost of a unit of flow between i and j. X are the decision variables.
𝑋𝑖𝑘 is 1 if node i is allocated to hub at k, 0 otherwise; 𝑋𝑘𝑘 is 1 if node k is a hub, 0
otherwise. Constraint (2.2) restricts that only single allocation of non-hub node to hub node
exists. Constraint (2.4) restricts the number of hubs to p, and lastly, Equation (2.5) represents
the binary condition.

21

(a) Single Allocation(b) Multiple Allocation

Figure 2.5: Allocation Schemes for HS Network

Non-hub node
Hub(a) Tree(b) Ring

Non-hub to hub linkby mode A
Non-hub to hub linkby mode B
Hub link(c) General(d) Complete

Figure 2.6: Examples of Forms of a Hub Network(Source: Karimi and Setak, 2014)

Figure 2.7: Example of NonRestrictive Hubbing

Figure 2.8: Model incorporating properties
deemed suitable for archipelago

22

There are only a few papers tackling the hub location problem with two-hub-stop
adopting the non-restrictive hubbing policy. Blumenfeld et al. (1985) and Klincewicz (1990)
consider the combination of direct and indirect shipping but with only one consolidation
terminal. Aykin (1995a, 1995b) consider one-hub-stop, two-hub-stop and, when permitted,
direct services. Sung and Jin (2001) build a basic mixed logistics network model with hubs
selected from predetermined clusters of nodes. In their model, each node cluster has one hub
node to consolidate and switch all traffic from the terminal nodes in the cluster, thus, this isalso a single allocation problem. The paper considers an integer-programming model for the
problem and constructed the solution from its associated dual solution. Wagner (2007)
proposes a new (exact) solution procedure and a new model formulation of the nonrestrictive policy hub network introduced by Sung and Jin (2001), offering a faster solution
to the problem. Yu et al. (2009) develops a model to locate urban transit hubs with theobjective of minimizing total travel time. They make the assumption of non-restrictive
policy but also of the cluster-based single hub allocation policy. For the two-hub-stop casesin these models, a flow can be either transported via non-stop service or hub service
depending on which service will provide the lower cost for that certain flow.
The combination of direct and HS shipping is referred to as mixed system by Liu etal. (2003) and Li and Lindu (2011). The term mixed network, as opposed to the purely pointto-point (PTP) or direct network, is adopted in this study for the same definition. Finally,
Figure 2.8 shows a representation of the model incorporating the properties of intermodaltransport, multiple allocation, non-restrictive hubbing and general network configuration.
Moreover, there are also some studies that tackle one-hub stop network. Sasaki et al.
(1999) state that the conventional model of hub-and-spoke usually assume that trips enable
two stops as mass transport between hubs usually helps to reduce the transport cost.
Nevertheless, they consider the one-stop model as they deem it most appropriate especiallyfor distance between each origin-destination pair is not very long.
2.4.2 Economies of Density and How it is Embedded in Hub-and-Spoke models
Economies of scale is the common term to refer to the cost savings derived fromconcentrating flow densities on network links between hub locations (Horner and O’Kelly,2001) and is incorporated to the HS model by the symbol/parameter α. But since thecommon notion for the term is associated with the entire firm or fleet, though in shipping
this could applicable to a single vessel, we take the more specific term of “economies of23

density”. This more specific term is defined by Jansson and Shneerson (1985) as the falling
average cost attributed to the increase of utilization of vehicle fleet (in this case container
vessel) for a particular route.
Discount factor α typically takes a fixed value in classical hub location problems(Alumur and Kara, 2008). Though, O’Kelly and Bryan (1998) point out that to assume thatthe discount factor is independent to the volume of flow miscalculates the total network costand may erroneously select the optimum hub locations and allocations. Moreover, Hornerand O’Kelly (2001) state that many HS network models make three key assumptions thatover-simplify the problem, namely, (1) the bundling of flows on the inter-hub link is theexogenous nature of discount factor; (2) the number of hubs to be located is determined
exogenously; (3) only flow on inter-hub links may receive discount when in reality, discountcould be earned at any portion of a route with sufficient volume.
Several studies have attempted to overcome these modelling limitations andsimplifications. O’Kelly and Bryan (1998) and Klincewicz (2002) employ a non-linear costfunction by a piecewise-linear concave function. Horner and O’Kelly (2001) and Bryan(1998) use another non-linear cost function based on the Bureau of Public Roads (BPR)
function of Sheffi (1985), and which could be earned along any portion of the route with
sufficient volume. As opposed to the BPR, the discount would be based on decreasing𝛽function of link flow, 𝐷𝑙 = (1 − 𝜃𝑥𝑙 ), where 𝐷𝑙 is the discount on a given link l isdependent on link flow 𝑥𝑙 , raised to some power 𝛽 which represents the decay of thefunction and multiplied to a scalar 𝜃.
While specific functional forms for the cost function as used for cost minimization
models have been identified such as the translog cost function, they are not commonly used
for hub-and-spoke network models. Wu (2009) however utilizes a translog variable costfunction to determine the optimal fleet capacity of shipping lines in Taiwan. The translog
shipping variable cost function in the study is expressed in terms of the labor, fuel,intermediate materials inputs, stock of capital invested and technology. For the hub-andspoke network models, the transport cost minimization is based on the volume of flow. As
explained earlier in this section, commonly, only the transport cost for inter-hub links
receive discount from the increase in flow volume. Moreover, also commonly, the inter-hub
transport cost is calculated based on a fixed valued discount factor and is not based on afunctional form cost function.

24

2.4.3 Heuristics used in solving Hub-and-Spoke Network Problems
Three are several heuristics solutions in literature being used to solve large problems
in a short period of time. From the paper of Alumur and Kara (2008), the known methods
used are simulated annealing heuristic (e.g. Ernst and Krishnamoorthy, 1996), tabu searchheuristic (e.g. Skorin-Kapov and Skorin-Kapov, 1994), genetic algorithm and its hybrid (e.g.
Abdinnour-Helm and Venkataramanan, 1998; Abdinnour-Helm, 1998). According to thesame paper, for hub location problems, the use of Lagrangian relaxation is the most effective
heuristic as presented in Pirkul and Schilling (1998) with maximal gaps of less than 1%.
Several other studies have applied the Lagrangian relaxation heuristic. Lu and Ting
(2013) use the method in solving a capacitated hub location problem; while Ernst andKrishnamoorthy (1999) use it for a capacitated p-hub median problem, both studies
considering single allocation.

An et al. (2014) used the Lagrangian relaxation method tosolve the difficult problem on reliable single and multiple allocation hub-and-spoke network
considering disruptions at hubs. Aykin (1993) introduced a capacitated hub-and-spoke
network problem in which hubs have limited capacity, and where direct and hub connected
services between nodes ae allowed, and problem is reduced to a smaller routing problem
where Lagrangian relaxation is then applied.
2.5 The Road Congestion Problem of Metro Manila and the Proposed Solutions
The transport and traffic problems of Metro Manila are linked primarily to economic
development that has resulted in rising car ownerships (Regidor, 2007). Several studies havebeen conducted that examine and propose solutions to the road congestion. Regidor (2007)
evaluates the effectiveness of three schemes namely, Unified Vehicular Reduction Program(coding scheme), the Truck Ban, and the U-turn Scheme and presents quantitative
assessment of the programs as guide for administrators. Castro et al. (2003), meanwhile,
discuss the impacts and evaluate the effectiveness of the implemented truck ban schemes inMetro Manila. Their results indicate that the “no truck ban” scheme is the most favorable
way of improving the traffic environment, but state that this scheme may encounter
resistance from private motorists and resident who will be affected by the lifting of
implemented truck bans. Thus they offer the “all day truck ban at EDSA only” scheme
which resulted to comparatively encouraging reductions in trucks travel distance. Anotherstudy by Castro et al. (2005) reveal that freight carriers cope with large truck restriction
policy by mainly changing their delivery routes and or shifting the delivery times. A report25

by ALMEC Corporation (2014) on the roadmap for transport infrastructure development for
GCR, among the proposed studies to be conducted toward the implementation of the shortterm projects is the feasibility of North Harbor Redevelopment. North Harbor in Manila has
the highest share of domestic cargo throughput in the country. The redevelopment of the area
into a mixed-use waterfront property would require the cargoes to be shifted from Manila toadjacent ports, of which the suggested one is Batangas Port. This shift is seen to provide avolume of exportable TEUs that may entice foreign vessels to call at Batangas Port. The
move would free up the City of Manila which presents an opportunity to revitalize the cityand regain its old glory. Moreover, it would also provide operating costs savings to shipping
companies since domestic shipping is primarily from the south of Manila and Batangas islocated south of Manila.
2.6 Estimation of Shipping Cost
In Chapter 5, we estimate the shipping costs of 2 vessels’ voyages to determine theeffect to the carrier of the strategy of using HS network with Batangas port as hub instead of
Manila port. From McConville (1999), the costs structure of a hypothetical ship withbreakdown in variable and fixed costs is shown in Figure 2.9, where the costs are defined inTable 2.4.

Figure 2.9: Cost structure of a hypothetical ship (McConcile, 1999)

26

Table 2.4: Cost structure of container shipping(Lim, 1994; Gkonis and Psaraftis, 2010)
Fixed costs (running costs and capital costs)
Crew expenses/

wages, overtime, pensions, accident/sickness insurance,

Labourtraveling/repatriation, provisions, victualling and cabin stores, etc.

Vessel expenses

stores/spares, lubricants, maintenance/minor repair, annual survey,
fresh water, communication charge, etc.

Insurance

hull / machinery, war risks, freight / demurrage defense, P&I, othermarine risks, etc.

Depreciations

ship, container, chassis, trailer and other container related
equipment, terminal property and equipment, etc.

Amortization

for long-term terminal, container, chassis and trailer leaseholds andleaseholds improvements, etc.

Variable costs
Cargo-related expenses
Cargo expenses

CFS charges (stuffing, stripping), measuring/weighing, tallying,cargo inspection, customs examination, documentation, noncontainerized/overheight /overwidth/dangerous cargo surcharge,
reefer cargo expenses (pre-trip inspection, pre-cooling, monitoring,storage), etc.

Terminalloading/unloading/receiving/delivery (lift onto chassis for empty

Handling

dispatch, lift off from chassis for receiving outbound load, load into

Charges (THS)

vessel from stacking area for outbound cargo and discharge fromvessel into stacking area, lift onto chassis for delivery, lift off fromchassis for empty return for outbound cargo), shifting (from cell tocell, unload on the terminal and reload on the same vessel),transshipment (unload on the terminal and reload on another vesselon the same terminal), storage of full and empty container,
stevedores or equipment stand-by charge, overtime surcharge, etc.

Haulagesrailroad charge, rail ramp fee, inland depot charge, inlandtransportation, local drayage, port equalization, port, shuttle, feeder
charge, etc.

One-way short-for container, chassis and trailer

27term lease
Navigation expenses
Port charges

pilotage, towage, dockage, wharfage, harbour/tonnage/light/buoy/anchorage

dues,

mooring/unmooring

andrunninglines,

customs/quarantine fee, watchman/agency/cana1 fee, etc.
Bunker expenses

fuel and marine diesel oil

Overhead
Administrativecompensation of officers and directors, salaries and wages of

expenses

employees, fringe benefits, rental expenses, office expenses,
communication expenses, dues and subscription, travel expenses,
advertising, entertainment and solicitation, legal fees, taxes, etc.

Non-operatinginterest income, dividend income, revenue from non-shipping

revenues

operations, foreign exchange gains, income from affiliatedcompanies, etc.

Non-operatinginterest expenses, foreign exchange losses, donations andexpenses

contributions, miscellaneous losses, etc.

According to Hsu and Hsieh (2005), shipping cost can be divided into three maincategories: (1) capital and operating costs, (2) fuel costs, and (3) port charges. Table 2.5
relates these 3 main categories to the container shipping cost structure of Table 2.4 andFigure 2.9.
Table 2.5: The three main categories of shipping cost
Capital andOperating costs

Fuel costs

Port charges.

total expenses paid for using the ship each day; cost of owning theship, crew wages and meals, ship repair and maintenance,
insurance, materials and supplies, and so on. In this category would
also include all the running costs.
Fixed costs + Overhead costs
expense of the fuel consumption by a ship sailing at sea anddwelling in port
Bunker expenses
hull / machinery, war risks, freight / demurrage defense, P&I, othermarine risks, etc.
All Cargo-related expenses

28+ Port charges

The following notations are used to formulate the three cost categories shown inEquations (2.6)-(2.8) which are also taken from the paper of Hsu and Hsieh (2005).
𝐶𝑡𝑚

total shipping cost for route m for a ship type tmroute where 1 is the multiple calls route and 2 is the hub-to-hub routei

port of call on route m, where MLA stands for Manila, BAT for
Batangas, BCD for Bacolod and ILO for Iloilotship type𝑓𝑚

sailing frequency per season of route m𝑚
𝑄𝑖𝑗flow from port i to port j on route m per one round voyage (TEU)

𝑂𝑡

average daily capital and operating costs for a ship of type t (PhP per
day)

𝐷𝑖𝑚

shipping distance between port i and port i+1 (nautical mile)

𝐹𝑡𝑚

fuel cost at sea per nautical mile for a ship of type t on route m (PhP per
nautical mile)

𝐹𝑖𝑡𝑚

fuel cost at port i by a ship of type t on route m (PhP)

𝑉𝑡𝑚

average service speed for a ship of type t (nautical mile per day)𝑅𝑖

average gross handling rate in port i (TEU per day)𝐺𝑖

average handling rate in port i (PhP per TEU)

𝑊𝑖𝑚time a ship spends at port i on route m (day)𝛿𝑖𝑡𝑚

charge at port i for a ship of type t (PhP)

Total capital and operating costs for shipping all container flow on route m perseason f: (the product of the average daily capital and operating costs, 𝑂𝑡 , the total shipping𝐷𝑚

𝑄 𝑚 +𝑄 𝑚

1time per round voyage, ∑𝑖 (𝑊𝑖𝑚 + 𝑉𝑖 ) + 𝑓 ∑𝑖 ∑𝑗 ( 𝑖𝑗 𝑅 𝑗𝑖 ))
𝑡

𝑖

𝐷𝑚

𝑄 𝑚 +𝑄𝑚𝑡𝑖𝑓𝑂𝑡 ∑𝑖 (𝑊𝑖𝑚 + 𝑉𝑖 ) + 𝑂𝑡 ∑𝑖 ∑𝑗 ( 𝑖𝑗 𝑅 𝑗𝑖 )(2.6)

Fuel costs are the expense of the fuel consumption by a ship sailing at sea anddwelling in port for sailing frequency f:
𝑓 ∑𝑖 (𝐹𝑡𝑚 𝐷𝑖𝑚 + 𝐹𝑖𝑡𝑚 )

(2.7)
29

The port charges include the charge for the ship (servicing the ship, including
pilotage, towage, line handling fee, and berth occupancy charge, etc.) and the stevedoring
charges (cargo handling, including a container loading and unloading fee, equipment charge,
and rent of container yard, etc.).
β𝑚𝑚
𝑓 ∑𝑖 𝛿𝑖𝑡 + ∑𝑖 ∑𝑗 [( 𝑅𝑖𝑡 + 𝐺𝑖 ) ∙ (𝑄𝑖𝑗
+ 𝑄𝑗𝑖
)]
𝑖

(2.8)

Thus, the total shipping cost function of a ship type t for a season f on route m is:
𝐶𝑡𝑚 = 𝑓 ∑ [𝛿𝑖𝑡 +𝑂𝑡 𝑊𝑖𝑚 + 𝐹𝑖𝑡𝑚 + 𝐷𝑖 (𝑖𝑂𝑡
β𝑖𝑡 𝑂𝑡𝑚𝑚+ 𝐹𝑡𝑚 )] + ∑ ∑ [(𝐺𝑖 ++ ) (𝑄𝑖𝑗
+ 𝑄𝑗𝑖
)]
𝑉𝑡
𝑅𝑖 𝑅𝑖
𝑖
𝑗

(2.9)
2.7 Chapter Conclusion
The preceding sections provide the basic knowledge supporting the objectives of thisstudy as well as the summary of existing literatures on the study’s topics. The following are
the gaps in literatures that this study intends to fill:a) Section 2.3 presents the positive impacts of intermodal road-RoRo transport based on
initial assessment reports (ADB, 2010 and Basilio, 2008). Among the reported impacts isthe shift of shipments from the convention container transport using container vessel tointermodal transport and the transport cost reduction for long-distance transport, e.g.
Laguna to Iloilo, made when using intermodal transport. However, the study by Kobune(2008) state that the advantage of RRTS is overemphasized only for its quick procedure
at terminals and is competitive to the inter-island shipping in terms of total transport cost
only within 200km. Because of the archipelagic characteristic, the intermodal transport
in the country is unique in that the vehicles traverse chains of islands and seas (or several
land and sea legs) to compete with the long-distance container shipping. This is contrary
to the SSS and motorways of the sea employed in other regions where intermodal
systems generally only involve one sea leg and often are in competition with land-basedtransports.
A study therefore needs to be conducted to clarify the current position and modeshare of intermodal road-RoRo transport in the Philippines, its development and theregulatory changes that shaped it to its present state, its advantages over theconventional or container means of inter-island shipping, and the attributes that30

influence mode choice. These information would be useful as baseline data for futureplans/ studies regarding intermodal transport improvements in the Philippines.

b) While there are a number of studies on hub-and-spoke network modelling, few if none
exist/s where the application is on an archipelagic region. Moreover, some of the policies
followed in earlier models could be limiting and restrictive for an archipelagic topology
to realize a more transport cost efficient network. A study is therefore necessary to modela HS network suited for an archipelagic geography, which relaxes some of the common
assumption of previous models and incorporates the properties of multiple allocations,non-restrictive networking policy, general hub network topology, and intermodality, allof which have not been tackled at once in previous studies. The developed HS model
establishes a basepoint for future research on the topic for archipelagic geography
settings, since the application on archipelagic context has not been delved into
previously.

c) Solutions have been proposed to alleviate the road congestion problem in Metro Manila,
one of which is to shift cargo from Manila ports to Batangas port to free up the city of
Manila from trucks (JICA, NEDA, 2014). The study mentioned the operating costs
savings advantage to shipping companies when they call in Batangas because domestic
shipping is primarily from the south of Manila. However, it is more likely the shippers
will incur additional costs in transporting their cargoes from Manila to Batangas port,thus might not be beneficial to the shippers.
This study therefore explores the feasibility of implementing cargo shifting in
conjunction with a hub-and-spoke network scheme where Batangas port is one of the
hubs. Being a hub, there is consolidation of cargoes which would bring economies ofdensity for inter-hub transport. The study presented in Chapter 5 explores if the discountbrought by a hub-and-spoke network would give shippers an overall savings to their
total transport costs. Moreover, the vessel’s shipping cost savings of a shipping
company from changing its operation to direct interhub calls from the existing multiports calling is estimated as it would justify the tariff discount the company could
provide the shippers due to economies of density in interhub cargo flows.
The study then provides policy suggestions on how to cargo shifting and huband-spoke network could be facilitated.

31

Chapter 3
Intermodal Road-RoRo Transport in the Philippines, its Development andPosition in the Domestic Shipping
3.1 Introduction
As the general aim of the dissertation is in presenting an intermodal hub-and-spoke
network model that is applicable for an archipelagic geography; thus as a starting point, thischapter’s goal is to provide details on the existing intermodal road-RoRo transport in the
country, its development, current position in the domestic shipping market and the attributes
that influence the choice for this mode against the other modes in the market. The topic has
not been presented in other literatures in this approach. Though could be seen as primaryresearch on the topic, the chapter’s contents help build knowledge to the field in which
future researches could bank on.
In that, also the outputs of the chapter are the components of transport costs such astruck’s and vessels’ tariff, tolls and port fees, and locations and distances between ports
which are input to the network models of the succeeding chapters.
3.1.1 RoRo Transport Prior to Road RoRo Terminal System (RRTS)
RoRo vessels started arriving in the Philippines in 1970s, the first could have been
the Millennium Uno from Japan in 1973 (Baylon, 2015). Since then, the Millennium Uno
has been servicing Millennium Shipping and is plying the Liloan-Lipata route of the Eastern
Nautical Highway. In 1978, “Northern Samar” of Eugenia Tabias Shipping Lines also started
sailing the Sorsogon-Samar route (Baylon, 2015). RoRo ferry service between Batangas City
and Calapan, Mindoro island also began operations in the 1970s, which facilitated the supplyof food products from Mindoro to the capital Metro Manila (Kobune, 2008).
The concept of RoRo ferry service as part of the highway system was first introducedin the Pan Philippine Highway, which was conceptualized in 1965 (Basilio, 2008). PanPhilippine Highway, also known as the Maharlika Highway, is a network of roads, bridges
and ferry services across the eastern part of the Philippines connecting the islands of Luzon,
Samar, Leyte and Mindanao. However, it was only in the 1980s when RoRo ports along thisHighway, namely, between Matnog (Sorsogon, Southern Luzon) and Allen (Northern
Samar), and between Liloan (Southern Leyte) and Lipata (Surigao del Norte), were built for
the exclusive use of RoRo service. In 1983, Maharlika I and Maharlika II started operations
32

in these links. However, it is known that even before then, the private sector already utilized
RoRo vessels by using existing and makeshift ports and wharves, some of which wereprivately built. Examples of these were the prior mentioned Millennium Shipping andEugenia Tabias Shipping Lines that serviced the links of the Eastern Nautical Highway evenin the 1970s (Baylon, 2015).
Other RoRo routes soon followed. Manila International Shipping and Viva Lines
pioneered the services between Southern Luzon through Batangas and Lucena with
provinces of Mindoro, Romblon and Marinduque. Short-distance services across the islandsof Visayas were pioneered by Gothong Shipping, Aznar Shipping and Maayo Shipping thatprimarily carried vehicles. In the 1980’s, liner companies such as Negros Navigation,
Sulpicio Lines, Gothong Shipping, and Trans-Asia Shipping already had RoRo vessels thatserved overnight and short-distance routes (Baylon, 2015). Non-vehicle cargoes werecommonly shipped as loose cargoes or in pallets loaded into the vessel using forklifts.
Perhaps wheeled cargoes such as trucks were not popular then because the freight charges
for self-powered vehicles were in cubic meters; contrary to the present where, by RRTS
policy, charging is made in lane meters. Thus, a significant amount would be paid for thevolume of the vehicle, in addition to the intended cargo. It would be more economical totransport the cargoes to and from the ports by trucks but unload/load them to and from theship at ports.
Though RoRo services were present in the two sea links along the Pan-Philippine
Highway which could have seamlessly connected Luzon to Mindanao, long-distanceintermodal transport could not been used in its full potential because of the then poor
condition of some roads. In 1997, further improvement of the Pan-Philippine Highway had
to be done with the addition of 600 kilometers of road from Sto. Tomas, Batangas to
Matnog, Sorsogon (ADB, 2010).
The 1980s also saw the surge of containerization in the domestic shipping, whichbegan with 10-footer and 20-footer containers. In the 1990s, 20-footers dominated, with 40footers present mainly for transshipments for foreign ports. Containers are also carried by
RoRo vessels and are loaded and unloaded using forklifts or mounted on trailers and pulled
by tractor heads to speed up the process. The latter is also a form of intermodal transport.
However, container with prime mover in RoRo vessels is charge higher than the othervehicles (e.g. 10-wheeler truck) and is not charged per lane-meter because of its heavier
material composition (Montenegro Lines, 2014). Container on chassis is not considered aself-powered vehicle thus, as per Executive Order 170, could still be burdened by transport
33

procedures and additional costs in loading into a RoRo vessel. Moreover, container vessels
have the capacity of stacking containers on top of each other to realize density economies
whereas RoRo vessels commonly only have one deck for loose, palletized and rollingcargoes, and have the upper decks for passengers.
Prior to the inception of the RoRo policy in 2003, the predominant method for domestic
shipping is by container vessel, which uses the load-on load-off system facilitated by cranes
and dock equipment (ADB, 2010). This system presented significant cargo handling andwharfage costs.
3.1.2 Inception of the RoRo Policy
According to an ADB (2010), during the various conferences held in Mindanao in
2002, one of the persistent issues raised by shippers was the high cost of transport from
Mindanao to Manila. Many could not understand why certain domestic shipping is more
expensive than shipping from Manila to Hong Kong, China or Bangkok. Cost andinefficiency of cargo handling charges were identified as the major factor in the high cost of
domestic logistics transportation, as they attribute to up to 30% of the sea transport costs.
Extensive use of RoRo shipping is recommended as the most appropriate for an archipelagic
country because it goes away with port-related activities (ADB, 2010). However, the RoRorecommendation was not readily implemented. Various reports attribute this to the lack ofinterest from PPA (Basilio, 2011).
PPA is vested the role to own, develop, maintain, operate and generate income fromits ports. PPA as the operator outsources terminal operations such as cargo handling to theprivate sector and in turn collects 10-20 percent shares from cargo-handling revenues. As per
PPA approval, cargo-handling rates increased annually from 1998-2008. PPA is said to bebiased with cargo handling such that the more cargoes handled and the higher the rates, thehigher is the income of PPA (Basilio, 2011). In effect, most shipping lines converted their
RoRo ships to accommodate cargo handling, and some of them even went to cargo handlingbusiness themselves. In addition, cargo handling was imposed even though no cargohandling service was actually provided; only the false pretense that the ports are notequipped to handle RoRo ships.
There was then a strong clamor for reform from the business sector. Thus in 2003,
the Execute Order 170 was enacted that orders the elimination of any costs and proceduresthat are not required in land-based transportation systems such as cargo handling charges and34

wharfage dues. The order also promotes RRTS by changing the basis of freight charge tolane meter, by simplifying documentary requirements, waiving port authorities’ share in port
revenues, encouraging privatization of public RoRo ports, requiring only minimum permit inport construction and operation, and providing available financing from the Development
Bank of the Philippines for investments related to this cause.
RRTS was also promoted as a solution to the absence of connectivity of rural islands
to economic hubs such as Manila, Cebu, etc. Isolation and lack of connectivity of the island
provinces are important factors that contributed to poverty and underdevelopment. They
serve as major constraints to economic and social interaction and integration, giving limited
incentives to increasing production (because of relatively small market).

With inefficienttransportation, increase in agricultural production only led to wastage and spoilage (ADB,
2010).
3.1.3 RoRo Routes and Inter-island Shipping Routes
The RRTS also called the Strong Republic Nautical Highway (SRNH) has three main
trunk lines –Eastern Nautical Highway, Central Nautical Highway and the Western Nautical
Highway shown in Figure 3.1. There are also lateral RoRo links, examples of which arethose connecting the islands in the Visayas as shown in Figure 3.2.
Moreover, RoRo links also connect the islands of Cuyo, Catanduanes, Romblon,smaller islands of Cebu and Southwestern Mindanao to the bigger main islands or urban
economic nodes. Aside from the short distance RoRo links, there are RoRo vessels that saillong-distance such as the routes of Manila-Cebu-Cagayan de Oro, Manila-Cebu-Butuan,
Manila-Cebu-Dumaguete-Zamboanga, Batangas-Calapan-Odiongan, Manila-Cebu-DavaoGeneral Santos, Manila-Batangas-Iloilo-Bacolod-Cagayan de Oro, etc.
In 2008, there were 68 existing RoRo routes served by 49 shipping companies
operating more than 250 RoRo ships (Basilio, 2008). The trunklines of SRNH alone serve919 kilometers covering 17 cities, towns and islands. As of December 2013, the threetrunklines have multiple trips per day as shown in Table 3.1.
As of December 2013 data, there is no operation between Pilar, Sorsogon to Aroroy,
Masbate and Cawayan, Masbate to Daanbantayan, Cebu (MARINA, 2013). Alternatively,
RoRo operations by Montenegro Lines for Pilar to Masbate City port, and Cawayan to Bogo,
Cebu are listed in the Table 3.1. Moreover, there is also a daily RoRo service from Batangas
directly to Caticlan by Montenegro Lines. The multiple trips per day of short-distance RoRo35

Western Nautical Highway
Central Nautical Highway
Eastern Nautical Highway

Batangas City

1

Calapan, Occidental Mindoro 2
Roxas, Oriental Mindoro 3

Caticlan, Aklan

Pilar, Sorsogon

1
Aroroy, Masbate

4

Dumangas, Iloilo

12Matnog, Sorsogon

2 Allen, Samar

Cawayan,3
MasbateDaanbantayan,
4
Cebu

5

6

5

Bacolod, Negros Occidental

Cebu City,
Cebu

Tubigon, 6
Bohol Jagna, 7
Bohol

Dumaguete, Negros Occidental 7
Dapitan, Zamboanga del Norte

83

Liloan, Southern Leyte

4 Lipata, Surigao del Norte8910

Mambajao, Camiguin
Benoni, Camiguin
Balingoan, Misamis Oriental

Figure 3.1: The three main trunklines of the Strong Republic Nautical Highway

is contrary to the less frequent trips of overnight and long-distance RoRo and container
vessels that commonly only have at most one trip per day for each route per shipping
company.
Gathered from PPA, Table 3.2 shows the weekly trip frequencies and available
destinations served with Manila as origin by 9 shipping companies namely Aleson ShippingCo., Solid Shipping Lines, 2GO Group Inc., Carlos A. Gothong Lines, Gothong Southern
Shipping Lines, Lorenzo Shipping Co., Moreta Shipping Company, Phil. Span Asia Carrier
Corp. and Asian Marine Transport Corp. Escano Lines Inc., Loadstar Shipping Co., Seaford
Shipping Lines, National Marine Container Lines and Oceanic Container Lines Inc. also
service the ports of Manila but their information are not included in the Table. From Kobune(2008), daily services are available only along the routes of Manila-Cebu-Cagayan de Oroand Manila-Iloilo-Bacolod. The other routes only have 1-3 services per week.

36

Palompon

Bogo
CarmenEscalante

IsabelTabuelanDanao
ToledoMandaue City
Cebu CityNaga

San Carlos

Guihulngan

Dumanjug
Argao
Samboan
Oslob

Amlan
SibulanSan Jose
Dumaguete

Ormoc

Hindang
Bato
MaasinTalibonClarinUbay
TubigonLoon
TagbilaranSantander

Figure 3.2: Lateral RoRo Links in the Visayas

Table 3.1. Daily trip frequencies of short-distance RoRo links along the three nauticalhighways (Source: Maritime Industry Authority, 2013; and retrieved from interview)
Number ofOperators

Trips per day

Batangas City – Calapan, Oriental Mindoro

4

37 toward, 36 return

Roxas, Oriental Mindoro – Caticlan, Aklan

2

6

Dumangas, Iloilo – Bacolod, Negros Occidental
Dumaguete, Negros Oriental – Dapitan, Zamboangadel Norte
Central Nautical Highway:

3

19

3

5

Pilar, Sorsogon – Masbate City, Masbate

1

5

Cawayan, Masbate – Bogo, Cebu

1

2

Cebu City – Tubigon, Bohol

3

9

Jagna, Bohol – Balbagon, Mambajao, Camiguin

12Benoni, Camiguin – Balingoan, Misamis Occidental

3

18 toward, 16 return

Allen, Northern Samar - Matnog. Sorsogon

3

7

Liloan, Southern Leyte - Lipata, Surigao del Norte

3

7

RoutesWestern Nautical Highway:

Eastern Nautical Highway:

37

Table 3.2. Less frequent weekly trips of long-distance inter-island shipping originating from
Manila (Source: Retrieved from shipping companies websites (September 2014))
Destinations from Manila
Cebu
Cagayan de Oro
Bacolod
IloiloNasipit
Davao
General Santos
Zamboanga
Puerto Princesa
TaclobanOzamizRoxas City
Dumaguete
IliganCotabato
Masbate; Romblon; Coron; Dipolog;
Tagoloan, Misamis Oriental; Ormoc

3.2

Number ofOperators
6
5
4
3
2
3
3
3
2
1
3
1
2
2
1

Trips per Week

1

22
14
8
9
5
5
5
4
3
3
3
2
2
2
2
1

Intermodal Road-Roro in the Current Domestic Shipping

3.2.1 Field Survey Method
To better understand the market of intermodal road-RoRo transport in thePhilippines, a field survey was conducted in Metro Manila on 3-24 of July 2014. The firstpart is a questionnaire survey carried out with 17 freight forwarder respondents. The goal is
to determine from these representative companies the share of their shipments done byintermodal road-RoRo and the transport attributes that influenced their choice of mode. The
second part of the field survey investigates the transport costs and travel times of bothintermodal road-RoRo and inter-island shipping for selected origin-destinations. Since
freight forwarders are hesitant to divulge their shipment cost breakdown and strategy, thesecond part of field survey involved the collection of data such as shipment tariff fromshipping companies, ports fees, road toll fees, as well as travel times, loading cut-off time,
average times in container yards, etc. pertinent to the selected origin-destination cases.
Part I of the questionnaire survey gathered the percentages of shipments from Manila
to 9 destinations via (i) inter-island sea shipping from Manila port, (ii) intermodal roadRoRo transport and (iii) air transport. Air transport is included in the questionnaire as it isamong the 3 modes generally used for freight transport in the country. The 9 selected38

destinations, with the approximate straight line distance to the farthest point of the island or
location, were (1) anywhere within Luzon island (within 400 km), (2) Mindoro island (300km), (3) Panay island (500 km), (4) Negros island (650 km), (5) Samar island (650 km), (6)Leyte island (700 km), (7) Cebu island (630 km), (8) Zamboanga (850 km), and (9) Davao(950 km). The destinations such as Mindoro, Panay and Negros islands can be reachedintermodally through the Western Nautical Highway, while Samar and Leyte can be reachedthrough the Eastern Nautical Highway. Respondents were also asked to specify the routetaken especially for the case of intermodal road-RoRo transport. Characteristics of theshipment in terms of travel time, total transport cost incurred by the company and thebreakdown of cost (to include toll fee, shipping line tariff, port terminal fee, etc.) wereobtained when permitted by the company.
The Part II of the questionnaire survey asked the respondents to rank from 1 to 5 (1as highest) the top attributes that influence their choice of a specific mode over the othermodes. A list of attributes was given. Since a percentage of cargoes are also transported
through air, this mode is also considered in this part of the questionnaire. The result of thissection gives us an insight on the factors that contribute to the freight forwarders preferenceof mode and the advantage of the use of mode over the others.
3.2.2 Questionnaire Survey Results
a. Respondents classification
Freight forwarder respondents can be further classified based on the services theycater or their service niche. For example, some companies offer both inter-island(specifically using container) and intermodal road- RoRo transport services while some only
focus on one service. Some are dedicated truckers only of certain routes, and “co-loads” theshipment to other companies when they do not serve the specific area or when the shipment
characteristic requires container transport. Such that, we were able to interview truckers
catering only the Western Nautical Highway, covering the capital Manila to Negros island,and some providing transport only along the Eastern Nautical Highway up to Mindanao, etc.
Thus, we show in Table 3.3 the classifications of the interviewed freight forwarders
based on the services they provide. Five out of the 17 has their own intermodal trucking
services. Eight companies have international cargo export and import as their main niche andonly do pick-up and delivery within a certain reach. They seek the services of intermodal
trucking services when necessary.
39

Table 3.3: Classification of companies interviewed for the survey
Characterization of Services Provided
freight consolidation, domestic forwarding, intermodal trucking services
freight consolidation, domestic forwarding
international and domestic forwarding
parcel/freight forwarding services
TOTAL

Number ofCompanies
5
2
8
2
17

b. Shipment share of Modes
From Part I of the questionnaire survey, Figure 3.3 shows the cargo volume
percentages transported by each mode for the 9 selected destinations. There are many cases
when not all 9 destinations are serviced by a freight forwarder, thus we provided Table 3.4 toVolume Percentage of Cargoshow the data sample size per destination.
100%
80%

60%
40%
20%
0%

Shipment Destinations from Metro Manila
by inter-island sea shippingby trucking or intermodal road-RoRo transport
by airFigure 3.3: Percentages of cargo shipped by each mode type

Unlike in Europe, short-sea shipping, or sea transport along the coastline, is not
popular in the Luzon main island. To ship to destinations outside the Manila, land transport
is often used except for cases when the destination is another island in Luzon (i.e. Batanes)
wherein air transport is an option because of the often unfavorable weather condition for sea
transport. For the islands in the western seaboard (i.e. Mindoro, Panay and Negros), greater

40

Table 3.4: Sample Number per Destination
Destinations being Served by Freight Forwarders

Sample number

Within Luzon
MindoroPanay
Negros
Samar
Leyte
Cebu
Zamboanga
Davao

7
7
11
3
7
7
13
6
9

volume of cargoes are transported using intermodal road-RoRo transport than either interisland sea transport or air transport. For Mindoro as destination, 74% is done by intermodal
road-RoRo transport. This is not surprising since there currently is no liner vessel from
Manila that serves Mindoro Island. The use of inter-island sea transport in this case is often
for project cargoes, for example cargoes of a client building an industrial plant where thecargoes are bulky and oddly shaped that it is more suitable to transport them using tramper
vessels. Moreover, interview with 3 freight forwarders with shipments to Negros Island
revealed that more than 72% of their shipments are via intermodal road-RoRo transport.
Meanwhile, high percentage of cargoes shipped in destinations along the eastern seaboard(Samar and Leyte islands) are transported using inter-island sea transport, despite that only
Tacloban and Ormoc ports have vessels coming from Manila. The choice of mode may also
have been affected by the condition of road network from Allen to Calbayog City, which has
been categorized by travelers and bus operators as “bad” according to ADB (2010).
Moreover, only around 4% of cargoes for Cebu Island are shipped intermodally, and evenless for destinations in Mindanao Island (Davao and Zamboanga).
Also from the interview of 3 freight forwarders, intermodal transport and inter-island
sea transport both carry every type of commodity from the following categories: (a) personal
effects, (b) manufactured goods, (c) chemicals and related products, (d) mineral fuels,
lubricants and related materials, (e) food and beverages, (f) crude materials, (g) machineryand transport equipment and (h) animal and vegetable oils, fats and waxes. Personal effects
compose a substantial portion of commodities transported by intermodal transport, and theseare often in the form of “balikbayan boxes” or boxes from overseas Filipino workers
containing gifts and other effects intended for relatives in the Philippines.

41

c. Ranking of Important Attributes in the Choice of Mode
For each mode, the respondents were asked to rank the top 5 attributes (from a list of
18 attributes) which influenced them in choosing the particular mode (air, inter-island sea
transport and intermodal road-RoRo transport). Tables 3.5 to 3.7 evaluate the ranking basedon score, assigning scores 5, 4, 3, 2 and 1 to ranks 1, 2, 3, 4 and 5, respectively. The numberof times the attribute is designated to a rank by the respondents is filled in the columns “B”,
and these are multiplied to the corresponding score in column “A”. The sums of the AxB are
the general weight of the attribute, which gives us the idea on the general ranking of
attributes in the choice of mode. Note that not all of the freight forwarders respondents
conduct shipping by all 3 modes; only 9 respondents ship using air transport, 14 by interisland sea transport and 11 by intermodal road-RoRo transport.
Air transport has the advantage of speed, thus the choice of this mode ispredominantly because of the short travel time and reliability in terms of delay, as indicatedin Table 3.5. Among the highest in weighted score are security in terms of cargo losses anddamage, flights availability and frequency. Air shipment charges the fee for insurance, andairline companies have extensive coverage of domestic cities destinations several of whichhave multiple flights per day. It is not surprising that transport cost is not among the top in
weighted score since the tradeoff of having fast speed is high cost.
For inter-island sea transport, transport cost is the most important attribute for the choice ofmode with 71% of the respondents ranking it in top 1, and which also garnered the highest
weighted score. Travel time only follows second in weighted score. Suitability to the cargo
characteristics also has a high weighted score because for 20-footer container full container
load (FCL) in container vessel, the maximum load allowed is 18 tons, which is higher than
the 13 tons limit commonly imposed for 10-wheeler FCL when loaded into short-distance
RoRo vessels. This is despite that a 20-footer container has 33 cbm volume while a 10wheeler truck has 45 cbm. RoRo vessels are relatively smaller and an instance of unbalanced
weight of wheeled cargoes could make a vessel susceptible to overturning thus the strict
weight limit. In effect, freight forwarders prefer to transport dense cargoes by container
vessel because of the higher weight restriction.

42

Table 3.5: Scores of influential attributes for the choice of Air Transport
Attributes
1
Rank

Score
(A)

1
2
3
4
5

5
4
3
2
1
Sum

2

3

=4

=4

5

6

=7

=7

=8

=8

9

Security in
Reliability interms of
Availability of Frequency ofTravel timeterms of delay cargo losses
flights
flights
and damage

Quality ofservice

Suitability to
Qualiy of
the cargo Transport cost airports andcharacteristics
their facilities

Safety interms ofaccidents

Delay atAvailability ofconsolidation
tracking
warehouse forservice
LCL cargoes

#(B)
7
1
0
1
0
9

#(B)
0
0
3
1
0
4

#(B)
0
1
1
1
0
3

#(B)
0
0
0
1
0
1

#(B)
0
0
0
1
0
1

AxB
35
4
0
2
0
41

#(B)
1
2
1
1
2
7

AxB
5
8
3
2
2
20

#(B)
0
2
1
0
3
6

AxB
0
8
3
0
3
14

#(B)
0
2
1
0
2
5

AxB
0
8
3
0
2
13

#(B)
1
1
0
2
0
4

AxB
5
4
0
4
0
13

AxB
0
0
9
2
0
11

AxB
0
4
3
2
0
9

#(B)
0
0
1
0
0
1

AxB
0
0
3
0
0
3

#(B)
0
0
1
0
0
1

AxB
0
0
3
0
0
3

AxB
0
0
0
2
0
2

AxB
0
0
0
2
0
2

#(B)
0
0
0
0
1
1

AxB
0
0
0
0
1
1

Table 3.6: Scores of influential attributes for the choice of Inter-island Sea Transport
Attributes
1

Rank

2

3

Score
(A) Transport cost Travel time

1
2
3
4
5

5
4
3
2
1
Sum

#(B)
10
1
1
1
1
14

AxB
50
4
3
2
1
60

#(B)
1
5
2
0
1
9

AxB
5
20
6
0
1
32

4

=5

=5

Suitability toFrequency ofthe cargo
vessels
characteristics

Security interms ofcargo losses
and damage

#(B)
1
2
2
2
1
8

#(B)
0
1
1
2
2
6

AxB
5
8
6
4
1
24

#(B)
1
0
3
2
1
7

AxB
5
0
9
4
1
19

AxB
0
4
3
4
2
13

=5

6

=9
=9
10
Delay in
Delay atSafety in
Qualiy of port
transaction at Availability of Availability of
Quality of
Reliability in
Availability of consolidation
terms ofand theirports fortracking
facilities alongserviceterms of delay
vessels
warehouse for
accidents
facilities
dangerous
servicethe route
LCL cargoes
goods#(B) AxB #(B) AxB #(B) AxB #(B) AxB #(B) AxB #(B) AxB #(B) AxB #(B) AxB #(B) AxB
1
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
4
2
8
1
4
1
4
0
0
0
0
0
0
0
0
0
0
0
0
1
3
1
3
0
0
2
6
1
3
0
0
0
0
0
0
1
2
1
2
1
2
1
2
0
0
0
0
1
2
1
2
0
0
2
2
0
0
0
0
1
1
1
1
0
0
0
0
0
0
1
1
5
4
3
3
3
1
1
1
1
13
13
9
7
7
3
2
2
1

43

=7

=7

8

Table 3.7: Scores of influential attributes for the choice of Intermodal Road-RoRo Transport
Attributes
1

Rank

Score
(A)

1
2
3
4
5

5
4
3
2
1
Sum

2

3

4

5

6

Security in
Frequency of Reliability interms ofTravel time Transport costvessels
terms of delay cargo losses
and damage
#(B)
5
2
1
3
0
11

AxB
25
8
3
6
0
42

#(B)
5
2
0
1
1
9

AxB
25
8
0
2
1
36

#(B)
1
1
2
1
2
7

AxB
5
4
6
2
2
19

#(B)
0
2
2
0
0
4

AxB
0
8
6
0
0
14

#(B)
0
1
2
1
1
5

AxB
0
4
6
2
1
13

9
HavingCapacity to
Availability ofsufficient
Availability ofdeliver along
tracking
cargo volume
vessels
the way
servicefor the return
trip
#(B)
0
0
2
1
0
3

7

AxB
0
0
6
2
0
8

#(B)
0
1
1
0
0
2

8

AxB
0
4
3
0
0
7

#(B)
0
1
0
0
2
3

AxB
0
4
0
0
2
6

44

#(B)
0
0
1
1
0
2

AxB
0
0
3
2
0
5

10
Safety interms ofaccidents
#(B)
0
1
0
0
0
1

AxB
0
4
0
0
0
4

=11
=11
=11
Delay in
Delay attransaction at Quality ofconsolidation
ports for ports and theirwarehouse fordangerous
facilities
LCL cargoes
goods
#(B)
0
0
0
1
0
1

AxB
0
0
0
2
0
2

#(B)
0
0
0
1
0
1

AxB
0
0
0
2
0
2

#(B)
0
0
0
1
0
1

AxB
0
0
0
2
0
2

=11

=12

=12

Quality ofservice

Quality ofroads to be
taken

Suitability to
the cargo
characteristics

#(B)
0
0
0
0
2
2

#(B)
0
0
0
0
1
1

#(B)
0
0
0
0
1
1

AxB
0
0
0
0
2
2

AxB
0
0
0
0
1
1

AxB
0
0
0
0
1
1

For intermodal transport, travel time was ranked among the top 5 by all
respondents (Table 3.7)

and it has the top weighted score for the most important

influential attribute. Transport cost only follows in second highest weighted score.
Frequency of vessels comes third in the weighted score, higher than that in sea
transport as more routes have more frequent vessel trips. Capacity to deliver todestinations along the way was also ranked among the top 5 by some respondents, anattribute unique only for this mode. Freight forwarder are enabled to fill one truckload
faster since the load is composed of less than truckload (LTL) cargoes intended for
different destinations along the route, thus also leading them to have more frequent
trips.

Tracking of cargoes is also easier for this mode since it often only involvescontacting the truck driver or the truck’s accompanying personnel using mobile
messaging.

3.2.3 Transport Costs and Travel Times Comparison between Intermodal RoadRoRo Transport and Inter-island Sea Shipping
Transport cost and travel time are ranked at top 1 and 2 as most important
attributes that influence the choice for intermodal and inter-island sea transport. Thus,
we gather transport costs and travel times data for transport originating from Manila
to 7 destinations reachable by both modes. These destinations are Tacloban andDavao (reachable from Manila through the Eastern Nautical Highway route), Cebu
(reachable intermodally through the Central Nautical Highway) and Iloilo, Bacolod,
Dumaguete and Zamboanga City (reachable through Western Nautical Highway) as
shown in Figure 3.4.
Figure 3.5 shows the average tariff for port-to-port transport of 10 footer and
20 footer container from Manila to the chosen destinations as gathered from shippinglines. These do not include port fees and cargo-handling fees. Table 3.8 shows theport-to-port tariff for 10-wheer truck when transported through short-distance RoRo
vessels of Montenegro Lines. The said shipping company caters for most of the linksof the nautical highways. We do not consider the transport of 20-footer using longdistance intermodal road-RoRo transport because it is rarely used for this mode forthe difficulty to maneuver a container trailer by prime mover for long-distance land45

travel (such as distance from coast-to-coast of an island). This is only commonly used
for intra-city transport such as transport from consignee door to the port. Ten-wheeler
truck is the common mode unit for intermodal transport using by the respondents.
Twenty-footer container, meanwhile, is the standard unit for the domestic containertransport.

Figure 3.4: Locations of selected destinations46

To transport from Manila to the destination city’s center, other costs should beconsidered such as land trucking to-and-from ports, port fees and cargo handling fees.
We estimate the total transport cost to include these other said costs (also gatheredfrom interviews) to the tariffs in Figure 3.5 and Table 3.8. Table 3.9 shows the

Average Transportation Cost
(Thousand Php/container)

additional costs for both modes.

80
70
60

50

10 ftr container
20 ftr container

67.3
61.2
53.2

45.3

34.9

40
30

43.3

42.1

24.8

28.1

25.1

21.7

25.7

20
10
0
Bacolod/Iloilo Dumaguete

Zamboanga

Cebu

Tacloban

Davao

Destinations (with Manila port as origin)

Figure 3.5: Average transport cost of 10 and 20 footer container by inter-island
shipping (Source: interview, July 2014)

Table 3.8: Vessel Tariff for 10-wheeler truck (Source: Montenegro Shipping Lines
Routewebsite, September, 2014)
Tariff for 10-wheeler truck (PhP)(as estimated to occupy 11.1-12 lane meters)

Batangas to Calapan
Roxas to Caticlan
Dumangas to Bacolod
Dumaguete to Dapitan
Matnog to Allen
San Ricardo to Lipata
Pilar to Masbate
Cataingan to Bogo

4,608.00
8,832.00
3,072.00
7,872.00
2,880.00
5,040.00
7,776.00
11,136.00

47

Table 3.9: Other incurred costs other than vessels tariffs for both inter-island sea
transport and intermodal road-RoRo transport (source: interview with private sector)
Fees

Amount (PhP)

For inter-island sea transport:
Trucking (Manila city center to Manila port)

5,950.00

Trucking from destination port to city center (average)

2,678.56

Arrastre/cargo-handling fee (average)

939.65

Wharfage282.24Document stamp

10.00

Weighing fee

80.00

For intermodal transport of 10-wheeler truck:
Truck driver and crew wages and allowances

2,566/day

Truck fuel cost (1 liter of diesel per 2 km at 45Php per liter)

22.5/kmToll fees
Manila to Laguna South Luzon Expressway (SLEX)
Laguna to Batangas Southern Tagalog Arterial Road
(STAR)
Port fees (Terminal fee, Weighing fee, PPA RoRo Terminal Fee)
Maintenance cost*

496
200
611
9.85/km*Maintenance cost = (33 liters oil at 180Php/liter per 9,000km = 0.66Php/km)+ (gear oil, automatic transmission fluid, brake fluid at total of 10,800Php per
30,000km=0.36Php/km)+ (oil filter at 2,000Php/9,000km = 0.22Php/km) + (fuel filter at 1,800Php/9,000km =0.20Php/km)+ (air cleaner at 2,500Php/9000km = 0.28Php/km)+ (tires at 19,000Php per tire x 10 tires / 55,000km = 3.09Php/km)+ (RPS at 8,000Php/1,800km = 4.44Php/km)+ (batteries at 6,500/piece x 2 pieces / 21,600km = 0.60Php/km)= 9.85PhP/km

48

From the vessel tariffs and the other costs incurred, the total transport costs forboth modes are estimated as shown in Table 3.10. Port-to-port distances and travel
times data to aid the estimation, particularly for intermodal road-RoRo transport, wereobtained from ADB (2010). The estimated total travel time range for intermodaltransport mode indicates the shortest time when the truck does not have to wait in theport and the maximum time to include the maximum waiting time in the port in thecase when the truck misses a vessel. This waiting time was made to equal to the
maximum time interval between vessel arrivals.

Table 3.10: Estimates of total transport costs and travel times for inter-island
shipping and intermodal road-RoRo transport
20-Footer Container in Inter-

10-Wheeler Truck in Intermodal

island Sea Shipping

Road-RoRo Transport

Destinations

Estimatedfrom Manila

TotalTransport
Cost (PhP)

Port-to-Port

Estimated Total

Travel Time

Transport Cost(hours)(PhP)

Estimated
Total TravelTime(hours)Iloilo55,278.08

20 – 24

32,610.90

16 – 22.5

Bacolod

55,278.08

20 – 68

38,859.90

17.5 – 28

Dumaguete

63,098.34

25 – 44

50,690.65

23.5 – 34

Zamboanga

71,119.97

37 – 72

70,579.69

30 – 48.5

Cebu

52,075.24

22 – 27

43,525.15

22 – 60

Tacloban

53,252.16

̴ 30

32,707.85

18 – 24

Davao

77,210.48

̴ 60

65,200.66

31.5 – 45.5

Meanwhile, the port-to-port travel times for inter-island transport are theranges gathered from shipping lines as posted in their websites. The variations andranges are due to different vessel routes and port of calls. Total travel times for doorto-door transport for this mode will be longer than the port-to-port travel times shownsince inevitably it takes time to transport from door to port (vice-versa), for the timeleeway for the vessel loading cut-off time, and time in storage in container yards. A
conservative estimate of 6 hours, in total, could be spent for these activities.

49

From Table 3.10, the transport cost estimates for 10-wheeler truck unit inintermodal transport are lower than the 20-footer container in inter-island shipping.
The range of total travel times of intermodal transport is also lower than the port-toport travel times of inter-island shipping, except for Cebu destination, which is due toless frequent RoRo trips from Cataingan, Masbate to Bogo, Cebu. Cebu being thesecond largest city in the Philippines has regular and frequent inter-island shipping
vessels from Manila.
However, note that 10-wheeler truck and 20-footer container have different
volumes and maximum payload limits, and interview with one of the largest freight
forwarding company revealed that they take advantage of these characteristics tominimize cost. The maximum payload for 20-footer container (33 cbm) in container
vessel is 18 tons and for 10-wheeler truck (45 cbm) is 13 tons. Thus, freight
forwarders consolidate lighter cargoes with cargoes having shorter travel time
demands and load them into 10-wheeler truck since intermodal transport arrives fasterand the truck could carry bigger volume but lower weight. On the contrary, heavier
cargoes are loaded into containers. Thus, if we calculate transport costs for bothmodes in per ton basis considering the maximum payload given, we can come up withthe values in Table 3.11 for comparison.

Table 3.11: Cost per ton basis considering maximum payload of both modes
Destinations from
ManilaCost per Ton Basis (PhP)
20-Footer Container in

10-Wheeler Truck in IntermodalInter-island Sea Shipping

Road-RoRo Transport

Iloilo3,071.00

2,508.53

Bacolod

3,071.00

2,989.22

Dumaguete

3,505.46

3,899.28

Zamboanga

3,951.11

5,429.21

Cebu

2,893.07

3,348.09

Tacloban2,958.45

2,515.99

Davao

4,289.47

5,015.44

50

Intermodal transport to destinations in Panay island (Iloilo) and Negros island(Bacolod and Dumaguete) has shorter travel time and lower or comparable transportcost, thus intermodal transport has higher volume share than the other modes for these
destinations as shown in Figure 3.3. Meanwhile, transport by container in inter-island
shipping would cost less (per ton basis) for destinations such as Zamboanga, Cebu
and Davao, which likely led to freight forwarders preferring this mode over the others
as also indicated in Figure 5.3. In addition, Cebu has more regular and frequent interisland vessel trips from Manila. Transport costs by both modes for Tacloban do notdiffer significantly, and indirect transport using inter-island shipping could be done
through Manila-Cebu and Cebu-Tacloban. Both routes have regular and frequent
trips, with Tacloban being near Cebu. Thus, this could be the reason why inter-island
shipping dominates for Leyte island where Tacloban is located. Moreover, the roadfrom Allen to Calbayog City, an intermediate link to be taken for Manila-Tacloban
intermodal transport is categorized as having “bad” condition (ADB, 2010); and from
Table 3.7, the “quality of road” has a low score on what makes intermodal transport
attractive.
3.2.4

Summary: Mode Choice Condition
Transport cost and travel time are the top influential attributes for the choicefor either of the two considered modes. Lower transport cost per unit container or per
ton basis for relatively far destinations would lead freight forwarders to choose interisland shipping over intermodal road-RoRo transport. This would be the case fortransport to destinations such as Dumaguete, Zamboanga, Cebu and Davao, which are
more than 600 km from Manila. Intermodal road-RoRo transport costs lesser and haveshorter travel time for destinations along the western seaboard such as Mindoro,
Panay and Negros islands, thus more cargoes are transported thru this mode according
to the survey. In addition, the frequent RoRo trips along these destinations contributeto the preference for the intermodal mode. Frequent trips shorten the waiting time inports and, consequently, lead to shorter travel times. On the other hand, inter-island
shipping has daily regular trips to Cebu, adding to the preference for the said mode forthis destination. Transport to Tacloban island is cheaper via intermodal road-RoRobut the choice for this mode could be discouraged by the bad condition of some roads.

51

3.3 Chapter Conclusion
This chapter details the developments of intermodal road-RoRo transport in
the Philippines and provides an overview of its current state in the country. RoRo
vessels have been in use in the country since the 1970s. However, increase use of
RoRo transport as part of the intermodal transport system started when policies wereenacted in 2003. The policies established the Road-RoRo Terminal System (RRTS),
and provided policy changes that promote intermodal operations. The developments
increased RoRo operations and heightened the competition in the shipping industry
pushing some companies to remove or reduce inter-island shipping operations insome regions and venture into RoRo vessel operations. Positive impacts were realized
since the operation of RRTS, namely, economic growth and area development intowns with RoRo ports, transport efficiency due to more frequent trips, opening of
new markets especially for agricultural products, and enhancement of tourism.
The study contributes knowledge on the choice basis for intermodal roadRoRo transport over inter-island container transport and air transport for an
archipelagic topology such as the Philippines, noting that this intermodal transport isdistinct in that the vehicle traverses several land and sea legs in one shipment. The top
five influential attributes for the choice of the intermodal modally with the findings of
D’Este and Meyrick (1992), but relative importance is in the order of travel time, cost,frequency of vessels, reliability of delay and security in terms of losses and damages.
The frequent trips of RoRo vessels in most legs compared to the inter-island shipping
vessels give intermodal transport the advantage of shorter lead times leading toshorter travel times. Thus, from the survey, travel time, followed by transport cost, isthe top attribute that influence freight forwarder on choosing intermodal transport.
The result also indicates that even when transport using intermodal transport to a
destination is cheaper, the choice for the mode could be countered by the poor
condition of roads.
The results of the surveys conducted offer only an overview of the current
situation of intermodal road-RoRo transport and the competition with inter-island
shipping. The survey is limited in the number and classification of respondents. Since
it is difficult to obtain actual transport costs information from freight forwarders, it issuggested to also interview frequent shippers such as individuals, farmers or

52

companies of consumer goods. Moreover, for the transport costs comparison, thepaper is limited in only considering 20-footer container and 10-footer truck for interisland shipping and intermodal road-RoRo transport, respectively. Other transportunits and vehicles are suggested to be looked upon in the next studies. For further
study, a more comprehensive stated preference survey is suggested in order todevelop a mode choice model for the alternative modes present in the Philippines; andthus, also be able to suggest concrete improvements for the freight transport
operations of the country.

53

Chapter 4: Intermodal Freight Network Incorporating Hub-andSpoke and Direct Calls for Archipelagic Geography
4.1 Introduction
In Chapter 3, the position of intermodal transport, as well as the other players
in the shipping market in the Philippines has been detailed. This chapter then aims toachieve the second objective of this dissertation, which is to model a hub-and-spoke(HS) freight transport network that incorporates intermodality of transport modes
existing in an archipelago such as the Philippines. From the data gathered in the
Chapter 3 on the components of transport costs, namely, truck’s and vessels’ tariffand port fees as shown in Figure 4.8 and Table 4.4, respectively, we are able to precalculate the minimum link cost in Equation 4.20, which is input variable to themodel. The location of ports and the distances between them are gathered from thefield survey conducted in Chapter 3 study. These are plotted in Figure 4.8, and areused as input data to the model, particularly in the transport cost per link calculation.
4.2 The Characteristics of Archipelagic Philippines Considered in the Hub-andSpoke Network Model
While we have established that intermodal transport has market share in thePhilippines, previous studies also report as detailed in Section 2.3 that maritime
industry and freight transportation companies could benefit from hub-and-spoke
network concept.

Compared to point-to-point (PTP) transport, a hub-and-spoke

network benefits from consolidation of cargoes in hubs which results to lower averagecosts for inter-hub transport due to economies of density. Moreover, with hub-andspoke, less resources are needed compared to the fully connected point-to-point
network thus there is saving in investment (Farahani et al., 2013). However, thearchipelagic nature of the Philippines necessitates a unique HS network with certain
deviations from the general model. The general model has the following the common
assumptions as stated in Section 2.3, (1) the hub network is complete with a link
between every hub pair; (2) there exists economies of scale when the inter-hub
connections are used; (3) no direct service between two non-hub nodes is allowed54

(Alumur and Kara, 2008). Moreover, there are two types of allocation of non-hub
nodes to hub nodes: single allocation and multiple allocations.
The Philippine archipelago shown in Figure 4.1 is characterized by manyislands, most of which are small, that are spread in different directions often in chain
formations and are only a short sea distant apart. These four characteristics
mentioned justifies the need for a unique HS formulation that incorporates theproperties of general network configuration, multiple allocation, intermodal transport
and, non-restrictive hubbing, respectively.
The following explains in detail the consequence of each of the characteristic:
Many islands are small in size – small islands are characterized by small tradea.

volume; thus, a hub-and-spoke transport network that consolidates cargoes to achieve
economies of density is fitting to be used. Moreover, what may also be a consequenceof having small trade volume is that some islands conduct trade only with few
regions. Thus, there are cases when even there are two hubs in the vicinity, it is notbeneficial to route the cargo demands through these hubs because it would transport
the cargoes farther from the regions the islands commonly do trade. Therefore, we
relax the assumption that every hub is connected in a complete hub network. A hub
pair is only created when transporting consolidated flows through it would improve
the total transport cost of the network, and therefore a general hub (or incompletehub) network is employed.
1A

B

Non-hub node2

HubNon-hub to hub link
Hub link

3

C

4

Figure 4.1: Simplified illustration of incomplete hub network

From Figure 4.1, hubs B and C are not connected. This probably exists
because there are no cargoes from nodes 3 and 4 that are intended for node 2, or viceversa.

55

the islands are spreadin different directions
separated only by
short sea distances
chains ofislands

Mostly small
islands

Figure 4.2: The characteristics of the Philippine archipelago56

b. The islands are spread across different directions – the cargo flows of one region
or island could be destined to (or originate from) locations of different (oropposite) directions. If all the cargoes of the region are allocated to only one hub,when the hub is in the opposite direction to the destination of the flow, shipping
the cargoes via that hub would cost more. Li and Lindu (2011) state that adjacentdemand ports have the tendency to ship a longer distance with single allocation
case. Thus, the allocation of cargoes from a node is not restricted to only one hub(single allocation), but instead allows multiple allocations.
c. Chain of islands formations – In Chapter 3 we have established that intermodaltransports along chains of islands (or along the Eastern and Western Nautical
Highways) have mode share in the domestic shipping (it competes with thecontainer vessel transport). The chain formation of islands makes it apt forintermodal land-sea-land-sea transport.

Also in Chapter 3, we have establishedthat road-RoRo intermodal transport is advantageous in the short distance thus
could be utilized as feeder mode; while, for the inter-hub transport where travel
could be of longer sea distance, container vessel could be used. Thus, the HS
model incorporates intermodal transport.
d. Only a short sea distant separates the islands – a port in one island is only a shorttravel away from a port in an adjacent island. If we restrict that the cargo flows
between all nodes are routed through hubs, the shipping cost for cargo flows
between two adjacent ports could significant be greater. Thus, direct service shallbe allowed between two non-hub nodes whenever it would is more cost efficient;in this case, non-restrictive networking policy is employed.
Therefore, the network is modeled to incorporate the properties ofintermodality, non-restrictive networking policy, multiple allocations and general hub
network topology.

57

4.3 Model Formulation
The mathematical model in this study is a total network transport costs
minimization problem with the freight forwarder as decision maker as it tries tominimize the transport costs for the whole network it covers or serves. The model
decides the location of a predetermined number of hubs p from a given node set N,
and in the same time it also decides whether the flow from any origin to destination istransported directly or via a hub pair, while minimizing total network costs. The two
hubs stop is considered since the goal is to realize economies of scale so that small
islands with small trade volume could share in trade even for long distances. As statedin Section 4.2.1, the conventional model of hub-and-spoke usually assume that trips
enable two stops as mass transport between hubs usually helps to reduce the transport
cost Sasaki et al. (1999). The one-hub stop would be appropriate for short distances asalso mentioned in the said study, but it is a limitation of this study that this case is notconsidered since it is presumed that it is in the inter-hub transport that significant
consolidation, thus economies of density, is realized than in the one-hub stop.
The model is a formulation with O(n4), which the developed heuristic
algorithm solves in a reasonable time. Nodes are represented by notations i, j, k andm; with i and j corresponding to origin and destination nodes, respectively; and, k andm corresponding to 1st hub stop and 2nd hub stop, respectively. The input anddecision variables are presented in Tables 4.1 and 4.2, respectively. The discountfactor (α) represents the economies of density brought by cargo consolidation in interhub connections, and is fixed at values 0.9, 0.7 and 0.5. “Economies of density” isdefined as the falling of average cost attributed to the increase of utilization of vehicle
fleet (in this case container vessel) for a particular route (Jansson and Shneerson,1985).
The number of hub arcs will not be an input variable as in other hub arc
related papers (Campbell et al, 2005a; 2005b; Alumur et al., 2009) but it will dependon the number of hubs p, and simply those which minimize total network costs. For p
number of hubs, each hub could be paired to a maximum of p-1 number of hubs. Thisis the concept used in formulating constraints (4.4) and (4.5). As a consequence of
these constraints, the developed model falls under the general hub network category
as classified by Karimi and Setak (2014) as in Figure 2.5(c). In addition, the model in58this paper identifies hub arcs and ensures that more than one flow goes through eachhub arc as compliant to assumption (2).
The following is the developed model:
MIXED-HUB:
𝐶𝑉,𝑅𝑉
𝑀
𝑀
𝑀
Min ∑𝑖 ∑𝑗 ∑𝑘 ∑𝑚 𝑊𝑖𝑗 [𝑐𝑖𝑘+ 𝛼𝑐𝑘𝑚+ 𝑐𝑚𝑗]𝑋𝑖𝑗𝑘𝑚 + ∑𝑖 ∑𝑗 𝑊𝑖𝑗 𝑐𝑖𝑗
𝑌𝑖𝑗

(4.1)

s.t. ∑𝑘 ∑𝑚 𝑋𝑖𝑗𝑘𝑚 + 𝑌𝑖𝑗 = 1(4.2)∀𝑖, 𝑗 ≠ 𝑖∑𝑘 ℎ𝑘 = 𝑝

(4.3)

∑𝑚 𝐻𝑘𝑚 ≤ ℎ𝑘 (𝑝 − 1)∀𝑘 ≠ 𝑚(4.4)∑𝑘 𝐻𝑘𝑚 ≤ ℎ𝑚 (𝑝 − 1)∀𝑚 ≠ 𝑘

(4.5)

𝑋𝑖𝑗𝑘𝑚 ≤ 𝐻𝑘𝑚∀𝑖, 𝑗 ≠ 𝑖, 𝑘, 𝑚 ≠ 𝑘(4.6)∑i ∑j 𝑋𝑖𝑗𝑘𝑚 ≥ 2𝐻𝑘𝑚

∀𝑘, 𝑚 ≠ 𝑘

(4.7)

𝑋𝑖𝑗𝑘𝑚 , 𝑌𝑖𝑗 , ℎ𝑘 , 𝐻𝑘𝑚 ∈ {0,1}(4.8)

Table 4.1: Input variables
SymbolDefinition

𝑊𝑖𝑗

cargo flow volume from node i to node jΑdiscount on the unit cost of flows for travel between hubs asconsequence of economies of density

𝑃

total number of hubs to be established𝑀
𝑐𝑖𝑘cost of unit flow between nodes i and j using transport mode M, where
M could be either truck, intermodal truck-RoRo, container vessel (CV)or RoRo vessel (RV) (when considering the two latter cases only, the𝐶𝑉,𝑅𝑉cost of unit flow is given by 𝑐𝑘𝑚)

Table 4.2: Decision variables
SymbolDefinition

𝑋𝑖𝑗𝑘𝑚

1 if flow from node i to j goes through hubs k and m, 0 otherwise

𝑌𝑖𝑗

1 if flow from node i goes directly to j, 0 otherwiseℎ𝑘

1 if a hub is installed at k, 0 otherwise

𝐻𝑘𝑚

1 if a hub link (arc) is established between hubs k and m, 0 otherwise.

59

Non-hub node
Hub
Non-hub to hub linkby mode A

intermodal transport

5
3

2

4

Hub link
6

1

direct transport between
non-hub nodes

Non-hub to hub linkby mode B

7

9

8

10

Multiple flow
allocations

incomplete hubbing

Figure 4.3: Example of the proposed Hub-and-Spoke model
The following decision variables would then have one as their value:ℎ3 = ℎ4 = ℎ7 = ℎ9 = 1; 𝐻34 = 𝐻43 = 𝐻48 = 𝐻84 = 𝐻89 = 𝐻98 = 1
𝑋1434 = 𝑋1534 = 𝑋1634 = 𝑋2434 = 𝑋2534 = 𝑋2634 = 𝑋3434 = 𝑋3534 = 𝑋3634 = 1
𝑋4143 = 𝑋4243 = 𝑋4343 = 𝑋5143 = 𝑋5243 = 𝑋5343 = 𝑋6143 = 𝑋6243 = 𝑋6343 = 1
𝑋4748 = 𝑋4848 = 𝑋5748 = 𝑋5848 = 𝑋6748 = 𝑋6848 = 1
𝑋7844 = 𝑋7845 = 𝑋7846 = 𝑋8844 = 𝑋8845 = 𝑋8846 = 1
𝑋1989 = 𝑋11089 = 𝑋7689 = 𝑋7989 = 𝑋71089 = 𝑋8989 = 𝑋81089 = 1
𝑋6198 = 𝑋6798 = 𝑋6898 = 𝑋6198 = 𝑋9798 = 𝑋9898 = 𝑋10198 = 𝑋10798 = 𝑋10898 = 1
𝑌12 = 𝑌13 = 𝑌17 = 𝑌18 = 1 ; 𝑌21 = 𝑌23 = 𝑌27 = 1 ; 𝑌31 = 𝑌32 = 1
𝑌71 = 𝑌72 = 𝑌78 = 1 ; 𝑌81 = 𝑌87 = 1 ; 𝑌910 = 𝑌109 = 1
The resulting formulation has n4+2n2+n binary variables with n4+2n2+2n+1
linear constraints. The objective function (4.1) minimizes the total transportation costfor shipments via hub pairs and direct shipments. Note that hub-to-hub transport isrestricted to use only container or RoRo vessels, the modes which are capable ofconsolidating containers. The superscript notations signify that different modes could
be used per transport link, thus intermodal transport is allowed. Constraint (4.2)
ensures that each pair of demand nodes has to be served either directly or via hubs.
This constraint reflects the non-restrictive networking policy. Constraint (4.3) limits
the number of hubs to p. Because of constraints (4.4) and (4.5), hub link can only be60established if both ends of the link are hub nodes. When a node is a hub, themaximum number of possible hub links that can be created with it as a starting (orending) hub is p-1. Constraint (4.6) ensures that a flow can only be routed through a
hub link if the hub link is established. This constraint reflects the general hub (orincomplete hub) network policy, in that Hkm could also be 0, meaning a connection
between these 2 hubs do not exists. This constraint, in essence, show that multiple
allocation is allowed. Flows from any i to j, could be allocated to any k and m onlywith the restriction than hub arc k-m is established. Constraint (4.7) restricts that every
established hub link serves more than one origin-destination flow, or that at least 2
flows go through it. Lastly, constraint (4.8) represents the binary requirement. As
earlier mentioned, the model does not require that all hubs are connected, as aconsequence of the inequality used in constraints (4.4) and (4.5). Moreover, a moreaccurate constraint in lieu of (4.7) that would ensure only consolidated flows go
through hub arcs is
𝐶𝑉,𝑅𝑉∑𝑖 ∑𝑗 𝑋𝑖𝑗𝑘𝑚 ≥ 𝐻𝑘𝑚 𝑉𝑘𝑚(𝛼)∀𝑘, 𝑚 ≠ 𝑘, 𝑊𝑖𝑗 ≠ 0

(4.9)

𝐶𝑉,𝑅𝑉
where 𝑉𝑘𝑚(α) is the minimum consolidated cargo volume for hub arc k-

m and given mode type (CV or RV) to merit a discount of factor α. However, with thecurrent lack of knowledge of the relationship between discount and consolidated
cargo volume, constraint (4.7) is instead employed.
For simplification, the transport cost of a flow from node i to j via hub pair kand m is denoted simply as Fh in equation (4.10), and the transport cost for direct
shipment as Fd in equation (4.11).
𝐶𝑉,𝑅𝑉
𝑀
𝑀
𝐹ℎ = 𝑊𝑖𝑗 [𝑐𝑖𝑘+∝ 𝑐𝑘𝑚+ 𝑐𝑚𝑗](4.10)

𝑀
𝐹𝑑 = 𝑊𝑖𝑗 𝑐𝑖𝑗(4.11)

Since the application of the HS model to the Philippines will generate aproblem with large number of constraints, a heuristic with Lagrangian relaxation as astarting point is used for the solution.
The difference between the proposed formulation to the general hub-andspoke model is particularly evident from constraints (4.2) and (4.6) which reflect the61non-restrictive hubbing and incomplete hub network policies, respectively. The
former constraint is deemed necessary because of the short sea distance separating theislands, and the latter because of the existence of small trade volume of the small
islands, which are both characteristics of the archipelagic Philippines.
4.4 Solution Heuristic Development
The Lagrangian relaxation used in this study tackles the entire problem. A
similar approach was undertaken by Pirkul and Schilling (1998). The constraints are
selected to be relaxed in such a way that the problem is decomposed into two sub
problems, making it easier to solve. Constraints (4.6) and (4.7) are chosen to berelaxed, which results in the following formulation:
MIXED-REL (ZR):̅̅̅̅ 𝑋𝑖𝑗𝑘𝑚 + ∑𝑖 ∑𝑗 𝐹𝑑𝑌𝑖𝑗 + ∑𝑘 ∑𝑚 𝐴𝑘𝑚 𝐻𝑘𝑚∑𝑖 ∑𝑗 ∑𝑘 ∑𝑚 𝐹ℎs.t.

(4.12)(4.2) – (4.5), (4.8)̅̅̅̅ = 𝐹ℎ + 𝛽𝑖𝑗𝑘𝑚 − 𝛾𝑘𝑚 and 𝐴𝑘𝑚 = 2𝛾𝑘𝑚 − ∑𝑖 ∑𝑗 𝛽𝑖𝑗𝑘𝑚 and 𝛽𝑖𝑗𝑘𝑚 andwhere 𝐹ℎ
𝛾𝑘𝑚 are the Lagrangian multipliers for constraints (4.6) and (4.7), respectively.
The problem now becomes completely separable, into two sub-problems(SUB-1 and SUB-2) without losing solution accuracy.
SUB-1: Min ∑𝑖 ∑𝑗 ∑𝑘 ∑𝑚 ̅̅̅̅𝐹ℎ𝑋𝑖𝑗𝑘𝑚 + ∑𝑖 ∑𝑗 𝐹𝑑𝑌𝑖𝑗
s.t.

(4.13)(4.2) and (4.8)

andSUB-2:Min ∑𝑘 ∑𝑚 𝐴𝑘𝑚 𝐻𝑘𝑚(4.14)

s.t. (4.3)-(4.5) and (4.8)
SUB-1 is straightforward to solve, and SUB-2 has O(n2) variables and can besolved by existing solvers in a reasonable time. Standard subgradient optimization isused to obtain a good, but not necessarily optimal, set of multipliers (β∗ , γ∗ ) or
bounds for the relaxed formulation MIXED-REL (ZR),ZR ( β∗ , γ∗ ) = Maxβ,γ ZR (β, γ).
The heuristic procedure uses the Lagrangian relaxation as starting point andhas the iterative procedure shown in Figure 4.4. The step size △ is used in adjusting62

the Lagrangian multipliers. No_improv is the limit of number of consecutive iterations
with no improvement (or increase) in the lower bound; after which the step size △ isdivided by 2.

Initialize β and γ, and the step size △,values for No_improv

Solve SUB-1 + SUB-2 and obtain lower bound (the ZR
value in equation (12))

Construct a feasible solution to obtain Upper Bound (Z)based on Xijkm of SUB-1

YES
stop

If no
improvement in
LB after numberof iterations
indicated by
No_improv,
decrease thestep size △Is (UB-LB)/LB < ε?
NO

Adjust β, and γ by the amount of infeasibility
Figure 4.4: Iterative process of the Lagrangian relaxation heuristic

A feasible solution (Z̅) is generated in every iteration, and the best feasible
solution is retained as the Upper Bound. The approach to produce the feasible solution
uses the Xijkm obtained from SUB-1. If ∑𝑘 ℎ𝑘 , corresponding to all Xijkm equal to 1,
is greater than p, the elements in set ℎ𝑘 selected to remain as 1 (so ∑𝑘 h𝑘 = 𝑝) arethose that would give the maximum cost savings when flows in the set {Xijkm = 1}
are routed via hubs rather than directly, as shown below:
Feasible solution (Z̅):
Max ∑i ∑j FdYij − ∑i ∑j ∑k ∑m FhXijkm
s.t. (4.2), (4.3) and (4.8).

63∀𝑖, 𝑗, 𝑘, 𝑚 ∈ {Xijkm = 1} (4.15)

If the gap between the Upper Bound and Lower Bound is greater than ε, theLagrangian multipliers are adjusted as follows:
TT
βT+1
ijkm = βijkm + t (X ijkm − Hkm )∀ 𝑖, 𝑗 ≠ 𝑖, 𝑘, 𝑚 ≠ 𝑘

T
T
γT+1
km = γkm + t (2Hkm − ∑i ∑j X ijkm )∀ 𝑘, 𝑚 ≠ 𝑘(4.16)(4.17)

Where the computed Lagrangian multipliers should be non-negative such that,β𝑇𝑖𝑗𝑘𝑚 = max(0, β𝑇𝑖𝑗𝑘𝑚 ) and γ𝑇𝑘𝑚 = max(0, γ𝑇𝑘𝑚 ), and where,𝑡 𝑇 = ∆𝑇 [

𝑇 𝑇
̅−ZT
Z
L( β , γ )2∑𝑖 ∑𝑗 ∑𝑘 ∑𝑚(Xijkm −Hkm ) +∑𝑘 ∑𝑚(2Hkm −∑i ∑j Xijkm )2](4.18)

Z̅ is the best (smallest) feasible solution value, and ZLT , the Lagrangian value
from the current iteration t.
Moreover, the solution quality is evaluated as percent gap between the best
feasible solution Z̅, or the Upper Bound, and the best Lagrangian value ZR ( β∗ , γ∗ ) ,or the Lower Bound, calculated as:
𝐺𝑎𝑝, % =̅−ZR ( β∗ ,γ∗ )Z
x100.
ZR ( β∗ ,γ∗ )(4.19)

4.5 Application to the Philippines
To reiterate, according to the Joint Foreign Chambers of Commerce of thePhilippines, to increase the country’s competitiveness among neighboring countries, aHS system should be in place, with highly developed ports for larger ships, and withcargoes delivered from smaller production centers by truck or small RoRo (JFC,2010). This is among the recommended long-term actions to be undertaken by thePhilippine Ports Authority (PPA) and Department of Transportation andCommunication (DOTC). Moreover, according to Kobune (2008), it is understoodthat the advantage of RoRo ferry service for short distance transportation is fully
utilized when a RoRo route provides a transverse service that complements a national
HS network.
However, noting that certain cargoes are better transported directly without
going through hubs, especially when the ports are adjacent to each other, the freight64

network model for the Philippines should give a leeway to allow direct transport
between origin-destination demands and not only allocate demands to designatedhubs. Thus, the proposed model of a mixed HS and PTP network where hub locations
are determined to serve as consolidation and transshipment points of cargoes comingfrom feeder nodes (these could be sea ports in small islands with few throughputs
catered by trucks and RoRo vessels). Then, transport within hubs (two-hub stop)
would be by container vessels, or RoRo vessels, which are the modes deemed capableof delivering economies of density, or multiple containers in one shipment.
The University of the Philippines National Center for Transportation Studies
conducted a survey of inter-regional freight flows for the whole country. This is the
only available source of origin-destination (O-D) traffic data for all water, air andland modes (NCTS, 2004). Cargo volumes were allocated to the 25 ports shown in
Figure 4.5. These ports are existing RoRo and/or container vessel ports. Each island
was set to have at least two nodes (except for Palawan island in the far left) tocapture the possible route when intermodal road-RoRo transport is used. Cebu wasselected to have three nodes (Cebu port (12), Toledo port (13) and Argao port (14))
because it is often the intermediate island for east-west and north-south (vice-versa)
intermodal transport in the mid-Philippine (Visayas) region.
The available cargo flows volume data, in metric tons, by water mode, for2004 were projected to 2012, and not to the current year, due to data availability.
Table 4.3 shows the total domestic trade data for 2004 and 2012 for rail, air andwater, with the water mode being the dominant one. There is no rail trade data for2012, as PNR Main Line South became non-operational in 2006 (Javier, 2008).
Inbound and outbound throughput data per port from the Philippines Ports
Authority (2004, 2012) were used to project cargo volumes transported by water(Figure 4.6). Since road cargo volume data is only available for 2004, obtained
through a roadside survey by University of the Philippines National Center for
Figure 4.7. Linear extrapolation was used to obtain the vehicle quantities for 2012.
Transportation Studies (UP NCTS, 2004), the increase in volumes for 2012 wasestimated to be proportional to that of registered trailers and trucks shown in The OD data is found in Appendix Table A.1. The transport costs per link for container and
RoRo vessels, trucks and intermodal truck-RoRo/container modes were calculated65

from transport tariffs (Figure 4.8) and port fees (Table 4.4). These data were gatheredfrom interviews with freight forwarders in Cebu City, the Cebu Ports Authority and
the PPA in Surigao City in September 2013. Data for RoRo transport were obtained
from interviews with seven shipping companies (for 61 origin-destinations), and thatof container transport were obtained from seven shipping companies (for 20 origindestinations). The shipping companies are tabulated in Table 4.5. Data for landtransport were obtained from Alrey Cargo Forwarding, for 44 origin-destinations.

Cebu
islandFigure 4.5: Location of 25 port nodes

66

Table 4.3: Quantity Domestic Trade data in Million Tons
Mode

Year
2004

2012

Water

24.57

20.31

Air

0.044621

0.033087

Rail0.001751---

Table 4.4: Port fees
Item

Tariff (PhP)*

Terminal Fee

516.00Document stamp

10.00

Weighing fee

80.00

Arrastre

939.65*1USD=44.5Php
Source: Field survey (Sept. 2013)67

Figure 4.6: Total Domestic Inbound and Outbound Cargo Volumes
Source: Philippine Ports Authority

Figure 4.7: Number of Registered Freight Vehicles
Source: Philippine Statistics Authority, National Statistical Coordination Board

68

Land transport tariffs
RoRo vessel tariffs
Container vessel tariffs
Land transport linear fit
RoRo vessel linear fit
Container vessel linear fit

Tariff (thousand Philippine Peso)

120

100

80

60

40

20

0
0

200

400

600

800

1000

1200

1400

1600

1800

Distance (km)Figure 4.8: Tariff versus distance of the 3 modes of transport, namely land bycontainer or truck, RoRo vessels and container vessels
Source: Field survey (Sept. 2013)

Table 4.5: Shipping Lines interviewed for RoRo and Container vessel tariff data
With RoRo vessels

With Container vessels

Asian Marine Transport Corporation

Aleson Shipping Lines

Lite Shipping

Cokaliong Shipping Lines

Medallion Shipping Lines

Escaño Lines Inc.

Montenegro Shipping Lines

Gothong Southern Shipping

Philharbor Ports And Ferries Services Inc.

Lorenzo Shipping Lines

Rapal Inter-Island Shipping

Solid Shipping Lines Corp.

Super Shuttle Roro

2go Travel

One TEU, the unit capacity of a twenty-foot container, is the basis for thetariffs. Weight carried by other container types and vehicle modes used in thePhilippines are converted to 1 TEU based on Table 4.6.

69

Table 4.6: Common load-carrying capacity in cubic meters of containers and vehicles
Vehicle/20 foot

container

container

type(1 TEU)

Volume(cbm)

10 foot

40 foot

WingvanForwardCantercontainer

container(Isuzu)(Isuzu)(Mitsubishi)

14

67

45

26

14

33

Source: Field survey (Sept. 2013)
Moreover, terminal handling charges, or “arrastre” as it is called in thePhilippines, vary per port. The arrastre fee shown in Table 4.4 is the average of thearrastre fees in 11 ports namely, Manila, Bacolod, Cagayan de oro, Cebu, Cotabato,
Davao, Dumaguete, General Santos, Iloilo, Zamboanga and Surigao. Note that roadtolls are not considered because the present length of operational tolled expressways
in the Philippines is roughly 345 km (Toll Regulatory Board, 2014), which is onlyaround 0.16% of the total road length based on 2009 data from Department of Public
Works and Highways (ASEAN-Japan Transport Partnership, 2014).
The transport mode used per link i-k is determined as the mode that gives theminimum transport cost, precalculated before input to the model as follows:
𝑀 𝑀
Min [𝑐𝑖𝑘, 𝑐𝑖𝑎 + 𝑙(𝑎, 𝑘)](4.20)

1
1 1
s.t. 𝑐𝑖𝑘= 𝑡𝑖𝑘
𝑑𝑖𝑘(4.21)

2
2 2
𝑐𝑖𝑘
= 𝑡𝑖𝑘
𝑑𝑖𝑘 + 𝑇𝐹 + 𝐷𝑆 + 𝑊𝐹

(4.22)

3cik= t 3ik d3ik + 𝑇𝐹 + 𝐷𝑆 + 𝑊𝐹 + 𝐴(4.23)

where the terms used are defined in Table 4.7. Equation (4.20) is the shortest path
formula which finds the route with the minimum transport cost between two nodes in
the network. The route could consist of links catered by modes M being container
truck, RoRo and container vessels, in combination (intermodal) or unimodal,
whichever path/route would provide the minimum transport cost between two nodes ik. Equations (4.21) to (4.23) are the formulas for transport cost for container truck,
RoRo, and container vessel, respectively. As mentioned, RoRo cargo will not pay for70terminal handling charges (arrastre) because vehicles are simply rolled-in and out ofthe vessel, as stated in Section 2 of the Presidential Executive Order 170-B (Basilio,2008) . Intermodality in the case where both RoRo and containership are used with
one cargo shipment could be realized with the use of container on chassis.

Table 4.7: Definitions of symbols used
SymbolDefinition

I

Originating nodeK

Ending nodeC

Cost in Philippine pesoMMode, designated with
1 for container truck
2 for RoRo vessel
2

3 for container vessel

T

Tariff fee per kilometer per TEU

DDistance per kilometer

TF

Terminal fee

DS

Documentation stamp fee

WF

Weighing fee

AArrastre fee

A

The last node travelled to being a closed statel(a,k)

Minimum cost among modes in set M for the link joining node a to k

The discount given by shipping companies is subject to the type of client, i.e.
special clients with regular shipments or ordinary clients. Thus, three different
discount factors ( α) are tested in the model, namely, 0.5, 0.7 and 0.9, each
uniformly applied to the whole network.

71

4.6 Results and Discussion
The proposed algorithm was coded in MATLAB and ran using 31 GB
memory/node capacity of a supercomputing facility that enables running several
problem scenarios simultaneously. Three network sizes are considered, N=8, 15,
and 25, for 3 types of hub-to-hub discount factors (∝), 0.5, 0.7 and 0.9. The nodes inthe subset used for the N=8 case are ports (9) to (16), while in the N=15 case are ports(1)-(2), (4)-(14) and (17)-(18). The number of hubs per network size is also varied,
p=2 to 6 for N=8 and p=2 to 4 for N=15 and 25. Larger memory and longer solving
times are required for larger networks with more hubs.
The N=8 cases are solved using an exact solution branch and bound algorithm
to compare the solving time with the Lagrangian heuristic given a 0.001 gap, ascalculated in equation (4.19). MATLAB bintprog solver is used for the branch andbound method; however, this is inefficient in solving the problem with larger
networks.
Lagrangian multipliers are initially set to 0 and Max_iter to 10,000. The step
sizes used are 1 for N=8, 2 for N=15 and 4 for N=25; No_improv is set to 100.
4.5.1 Location of hubs, total network costs and validity of the heuristic method
The results are shown in Table 4.8. Total network costs are in billions ofPhilippine Pesos, and exact and heuristic solution algorithm running times are inseconds.
Table 4.8: Results of the mixed network problem

Nodes,N

8

Pure PTP
total
network
cost (inTrillion
Pesos)
9,565

Hubs
p

2

3

Hub discount factor, αData

Mixed network total
cost (billion PhP)
Saving %Exact time (seconds)
Heur. time (seconds)
Iterations
Hub ports
Mixed network cost
Saving %

72

0.5

0.7

0.9

7,041,339

8,126,312

9,119,743*

26.39
0.95
5.20
118
(9),(12)
6,116,038
36.06

15.05
0.98
1.84
44
(9),(12)
7,608,933
20.45

4.66
0.83
4.90
117
(9),(12)8,989,952
6.02

4

15

454,657

5

Mixed network cost
Saving %Exact time (seconds)
Heur. time (seconds)
Iterations
Hub ports

6

Mixed network cost
Saving %Exact time (seconds)
Heur. time (seconds)
Iterations
Hub ports

2

Mixed network cost
Saving %Heur. time (seconds)
IterationsGap %Hub ports
Mixed network cost
Saving %Heur. time (seconds)
IterationsGap %Hub ports
Mixed network cost
Saving %Heur. time (seconds)
IterationsGap %Hub ports
Mixed network cost
Saving %Heur. time (seconds)
IterationsGap %Hub ports
Mixed network cost
Saving %Heur. time (seconds)
Iterations

3

4

25

615,159

Exact time (seconds)
Heur. time (seconds)
Iterations
Hub ports
Mixed network cost
Saving %Exact time (seconds)
Heur. time (seconds)
Iterations
Hub ports

2

3

73

104.45276.89175.42
7.39
4.91
0.72
85
60
15
(9),(11),(12) (9), (11), (12) (9), (11),(12)5,641,793
7,428,911
8,940,934
41.02
22.34
6.53
1481.772570.23757.77
14.99
20.67
2.39
118
203
29
(9), (10),(9), (10),(9), (10),(11), (12)(11), (12)(11), (12)5,485,224
7,270,727
8,906,122
42.66
23.99
6.89
13831.41
1475.29781.85
3.06
7.24
6.16
48
105
50
(9), (10),(11) (9), (10),(11) (9), (10),(11)(12), (13)(12), (13)(12),(13)5,351,804
7,156,137
8,892,066*
44.05
25.19
7.04
7593.271735.64
1156.25
3.06
4.60
5.76
58
93
64
(9), (10),(11) (9), (10),(11) (9), (10),(11)(12),(13),(14) (12),(13),(14) (12),(13),(14)365,706,788 404,227,748 437,336,243
19.56
11.09
3.81
5.49
3.22
2.22
50
27
19
0.723
0.005
0.118
(1),(9)(1),(9)(1),(9)333,074,983 391,451,502 437,322,172
26.74
13.90
3.81
102.3349.76
347.67
216
119
667
0.851
0.612
0.824
(1),(2),(9)(1),(2),(9)(1),(5),(9)307,561,891 381,100,732 433,230,301
32.35
16.18
4.71
875.76287.178778.78
348
187
1012
0.966
0.939
0.926
(1),(2),(8),(9) (1),(2),(8),(9) (1),(8),(9),(12)525,053,786 563,162,330 602,892,382
14.65
8.45
1.99
47.20
259.801065.81
43
436
1092
0.271
0.951
0.973
(1),(9)(1),(9)(1),(9)496,597,299 552,846,862 597,948,003
19.27
10.13
2.80
387.87605.11296.55
152
153
96

4

Gap %
Hub ports
Mixed network cost
Saving %Heur. time (seconds)
IterationsGap %Hub ports

0.947
0.659
0.785
(1),(2),(9)(1),(9),(23)(1),(9),(23)466,915,999 541,700,926 597,858,503
24.10
11.94
2.81
26095.06
7601.69
1387.27
440
335
417
0.758
0.976
0.006
(1),(2),(8),(9) (1),(2),(8),(9) (1),(2),(8),(9)*the solution of the heuristic algorithm is the optimal solution
Pure PTP total network costs is the sum of all direct shipment costs for all
cargo flows when the transport mode with the minimum cost is used per link, ascalculated in equation (4.24).

Mixed network total cost per case results as thesolution of equation (4.1). Percentage savings for mixed network compared to apurely PTP network are calculated by equation (4.25). The definition of iterations is
illustrated in Figure 4.4. The Lagrangian heuristic gap is calculated in equation (4.19),
and the identified hub ports for each case are also shown.
Min ∑i ∑j Wij cijM Yij
𝑆𝑎𝑣𝑖𝑛𝑔, % =(4.24)

PTP total network cost − Mixed Network Total Cost
PTP total network costx100

(4.25)For N=8 and p=3 to 7, the heuristic algorithm within a 0.001% gap is able toprovide the optimum solutions in shorter time durations than the branch and boundalgorithm. This proves that the heuristic is valid, in that it is able to come up with thesame optimal solution obtained with the exact branch and bound solution method.
We, therefore, are able to prove that the Lagrangian relaxation heuristic is able tosolve hub-and-spoke model that incorporates at once the properties of intermodality,
non-restrictive networking policy, multiple allocations and general hub network
topology, which application has not been done before.
The case of N=25, ∝=0.5 and p=4 took the longest solving time (26,095.06
seconds or 7.25 hours), which is reasonable for a network size of such complexity. Allother scenarios were solved in a reasonable number of iterations.
Within an 1% gap, all mixed networks can provide cost savings compared topurely PTP. However, total network cost savings are less than 10% in all cases where∝=0.9, which may not compensate the possible added costs to the port operators for74

running a hub. For all network sizes, total network costs decline as the number ofhubs increases, and the discount factor decreases. For the N=25 network cases,
significant savings of 8.45% and higher are possible when discount factors are either
0.5 or 0.7.
The combination of hubs identified by the heuristic algorithm is not always thesame across the different discount factors used in the cases of N=15, p=3 and N=25,
p=3. Moreover, the same ports are not always retained as hubs with the increase of thenumber of hubs. Such is Davao port (23), which is a hub for the cases of N=25, p=3,
discount factors of 0.7 and 0.9, but no longer among the hubs for the N=25, p=4 cases.
Nevertheless, these hub combinations provide good solutions (total network costs
savings) when solved by the heuristic algorithm.

4.5.2 The Resulting Intermodality and Incomplete Hub Network Topology
To examine the mixed network in more detail, the routes taken for N=25, p=4
and α=0.7 are tabulated in Table 4.9 and shown in Figure 4.9. Since there are a totalof 471 cargo flows between the 25 ports, Table 4.9 only shows the 48 cargo demands
that go through hubs. All other cargo demands are transported directly. The hub ports
identified are Manila (1), Batangas (2), Iloilo (8) and Bacolod (9). Eight out of the 48
O-D flows that are routed through hubs use a combination of road and sea vesselintermodal transport, as shaded in Table 4.9. The cargo flow from Toledo (13) toIloilo (8) uses two sea links and one land leg. This route intermodally connects Cebu
Island to Panay Island while traversing the Negros Island, and shows that intermodaltransport through chain of islands could be utilized in the HS network. Several otherroutes with spoke to hub, and vice versa, use RoRo and container vessel incomplement to each other. Notice that although ports (1), (2), (8) and (9) are
identified as hub ports, there are no hub-to-hub links between ports (1) and (2), (1)and (8), (2) and (8), and (8) and (1). The resulting network therefore has anincomplete network configuration. The hub-to-hub links created are those that could
provide good solution (total network cost saving), and a hub is not restricted to beconnected to all other hubs (of quantity p-1) if the creation of a hub-to-hub link will
not increase the total network cost saving.

75

Table 4.9: Flows routed through hubs for the case of N=25, p=4 and α=0.7
Originnode, i
1
1
5
5
5
6
6
6
6
7

1st hubnode, k
1
1
1
1
1
1
1
1
1
1

2nd hubnode, m
9
9
9
9
9
9
9
9
9
9

End
node, j
9
16
7
8
12
10
15
21
22
23

i to k----Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.

Mode per linkk to mContainer v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.

17

1

9

13

Container v.

Container v.

18
20
22
23
24
24
2
3
2
2
3
3
3
14
8
8
8
8
8
11
23
24
25
8
8
8
8
8
8
9
15
19
9
9
9

1
1
1
1
1
1
2
2
2
2
2
2
2
2
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
9
9
9
9
9
9

9
9
9
9
9
9
1
1
9
9
9
9
9
9
2
2
2
2
2
2
2
2
2
9
9
9
9
9
9
1
1
1
2
2
8

9
9
10
10
10
17
1
1
9
10
4
5
8
9
2
3
5
6
14
2
3
2
2
9
10
18
20
22
23
1
1
1
2
3
8

Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Roro v.
Roro v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
Roro v.
Roro v.
Roro v.
Roro v.
Roro v.
Roro v.
Container v.
Container v.
Container v.
Container v.
Container v.
Roro v.

13

9

8

8

Container v.
Container v.
Container v.
Container v.
Container v.
Container v.
--Roro v.
----Roro v.
Roro v.
Roro v.
Container v.
----------Container v.
Container v.
Container v.
Container v.
--------------Container v.
Container v.
------Intermodaltransport

m to j--Container v.
Container v.
Roro v.
Container v.
Truck/trailer
Container v.
Container v.
Container v.
Container v.
Intermodaltransport----Truck/trailer
Truck/trailer
Truck/trailer
Container v.
------Truck/trailer
Container v.
Container v.
Roro v.
----Roro v.
Container v.
Container v.
Container v.
--Roro v.
------Truck/trailer
Container v.
Container v.
Container v.
Container v.
--------Roro v.
---

Roro v.

---

20

9

8

8

Container v.

Roro v.

---

Total network cost

PhP 466,915,999

Total saving compare to purely PTP

PhP 148,242,660

76

Moreover, the current model is able to restrict more than one flow going
through a hub pair (or a hub pair serving more than one origin-destination flow),
given that a hub is defined as a consolidation port. This constraint is overlooked inprevious mixed network models.

Hub node
Non-hub node
Container vessels links
RoRo vessel link
Truck/trailer link

Figure 4.9: Cargo flows that are routed through hubs for the case of N=25, p=4 and
α=0.7, direct flows are not included. Weight of the lines is indicative of
the relative volume of flow77

4.6 Chapter Conclusion
The application of the intermodal mixed network model to an archipelagic
setting resulted to considerable cost savings compared when only direct transport isapplied. This chapter presented a suitable HS freight network model that integrates
intermodal transport across the said modes and which allows non-stop direct services,incorporates multiple flow allocations, non-restrictive networking policy and general
hub network topology. These properties have not been tackled at once by other HS
network models. We are also able to show that the Lagrangian relaxation heuristic isable to solve a hub-and-spoke network problem that incorporates such properties atonce.
Being of such geography, the Philippines necessitates a seamless multimodal
system that incorporates the use of road transport, RoRo vessel, and container vesselin complement with each other. The model therefore could be used as a tool for the
strategic planning level such as in the Philippines in identifying the ports that need
upgrade to cater hub quality, hub capacity, and facilities capable of modal
complementarity.

78Chapter 5
The Cost Effects of Shifting Cargoes and Port Call from Manila to
Batangas Port as Hub
5.1 Introduction
Thus far, we have shown from Chapter 4 that the HS freight network could
provide a more cost efficient transport network than the purely point-to-point
network. In this chapter, we attempt at using the same concept and properties of theHS freight network model of Chapter 4 in maximizing the number of trucks that could
be shifted from Manila port to Batangas port, taking it as one of the hub ports, with
the intention of minimizing the presence of trucks in the adjacent congested roads ofthe Manila ports, and in the Metro Manila in general.
To give a background, the Ports of Manila shown in Figure 5.1 is located very
close to the oldest part of the town and Tondo, the most densely populated district ofManila. As can be seen in Volume-Capacity ratio (V/C) of Metro Manila in Figure5.1, the road section of Roxas Boulevard that is adjacent to the ports is already at or
above its capacity the same as most of the roads in the capital. Most roads areoperating at saturation level where for the study area of 805 km road length, theaverage V/C is 1.25 and 62% of the section operates at less than 10kph.
Table 5.1 shows that trucks amount to only 3.80% of the vehicles registered in
the Greater Capital Regions (GCR), comprising of the National Capital Region(NCR), and adjacent Central Luzon and Southern Tagalog regions. Nevertheless,from the study of Castro (2003), one of the most popular alternatives in improving
operational efficiency of urban streets is to restrict the presence of large trucks, as
perceived by the motoring public. Trucks are often viewed as slow moving andoccupy a large amount of road space thus hampers the smooth flow of traffic. Given
that the ports are located in the densest district of Manila, restricting the port activity
would limit the truck traffic in the metropolitan areas close to the ports and thus
contribute to the improvement of local traffic (Boquet, 2013).

79

Figure 5.1: Road traffic volume and v/c ratio based on traffic assignment model in2012, Source: JICA, NEDA (2014)
Since the presence of trucks was often cited as a cause of traffic congestion,
truck bans that had been in effect for more than 3 decades, were adopted in the major
thoroughfares in Metro Manila by the Metro Manila Development Authority(MMDA). However, the recent truck ban issued by the City of Manila (Ordinance No.
8366) brought congestion problem in the ports and made quite a steer. The ban was
Manila’s answer to the internal traffic jam of the city. It was implemented fromFebruary 24 to September 13, 2014 and restricted eight- wheeler and up whosegross vehicle weight exceeds 4,500 kilograms to enter the City of Manila from 5am
to 9pm daily. The severe congestion caused to the port of Manila had a domino effecteven up to the national level. The domino effect progressed as follows: delay in theunloading of international vessels increased container inventory resulted to slower
yard production and higher dwell time and caused undue strain on

80

Table 5.1: Number of Registered Vehicles in GCR from 2007 to 2013

Vehicle
Type
Cars
UV
SUV
Buses
TrucksMC/TC
Trailers
Total GCR
Philippines
GCR % to
Phil.

2007

2008

2009

2010

2011

2012

2013

575,925
1,019,740
143,255
16,649125,226
1,224,365
15,8633121023
5,530,052
56%

591,070
1,004,479
146,827
16,984135,412
1,425,905
16,7813337458
5,891,272
57%

593,775
1,015,616
160,930
19,960144,745
1,559,836
19,5183514380
6,220,433
56%

619,970
1,051,241
190,648
23,092
144,575
1,679,571
19,99637290936,634,855
56%

639,039
1,063,456
207,762
23,330148,095
1,876,486
22,4903980658
7,138,942
56%

652,753
1,060,031
227,478
22,402150,913
1,958,798
24,216
4,096,591
7,463,393
55%

661,661
1,065,361
252,612
20,998
159,514
2,007,585
24,877
4,192,608
7,689,898
55%

VehicleType toGCR Totalfor 2013(%)
15.78%
25.41%
6.03%
0.50%
3.80%
47.88%
0.59%

Note: UV–Utility Vehicle; SUV–Service Utility Vehicle; MC/TC – Motorcycle/Tricycle
Source: Department of Transportation and Communication (DOTC) – Motor Vehicle Registered by District and Type, 2007 - 201381

port resources. Truck turnaround worsened and affected the normal delivery of
supplies and aggravated traffic along major roads. The road logistic cycle of supply
chains was disrupted especially that in Metro Manila area (Perez, 2015; Mira, 2015).
The economic loss to businesses and citizens amounted to P30-billion-a day (Cruz,
2014).
The negative effects of the truck ban are emphasized on international cargoes
as it comprises 72% of the cargoes serviced by the Manila Ports as shown in Table
5.2. Nevertheless, to be able to divert a portion of the domestic cargoes, which
throughput has continuously increased as shown in Figure 5.2, would contribute inalleviating the road traffic of Metro Manila.
Table 5.2: Foreign and domestic container throughput and capacity of selected ports
CapacityPort

Volume/Foreign

Share(%)

Domestic

Share
(%)

Capacity(%)

2,800,000 1,842,183

54.93

35,085

1.62

67.05

(TEU)

M.I.C.T.

Volume (TEU)

Manila - South Harbor

850,000

889,464

26.52

-

-

104.64Manila – North Harbor

1,500,000--

1,043,705

48.07

69.58

2,731,647

81.45

1,078,790

49.69

Total for Manila Ports
Subic

600,000

76,652

2.29

-

-

12.78

Batangas400,000

97,614

2.91

37,428

1.72

33.76

448,04513.36

1,054,945

48.59

Other ports

Source: PPA, 2014

Throughput in Millions
Metric Tons

14
12

OutboundInbound

10
8
6
4
2
0
Year

Figure 5.2: Containerized domestic cargo throughput for Manila North Harbor in
Metric Tons

82

Moreover, cited as among the Medium-term Transportation Investment
Program studies to be conducted is the feasibility of redeveloping the North Harbor
into a mixed-used waterfront property while shifting the cargo movement to Batangas
Port that is 100 km south of Manila ports as shown in Figure 5.3 (JICA, NEDA,2014). Batangas port is accessible from Manila through three expressways: Southern
Luzon Express Way (SLEX), Southern Tagalog Arterial Road (STAR) Express Way
and the SLEX-STAR Interlink. Domestic shipping is primarily from the south of
Manila, thus there would be saving in ship operating cost if they dock at the Batangas
port rather in than in the North Harbor. This move would also provide a volume ofexportable TEUs that may entice foreign vessels to call at Batangas Port (JICA,
NEDA, 2014). This chapter’s aim relates with the said program in that we study theshifting of cargo to Batangas Port but also in conjunction with the usage of the HStransport concept.

Figure 5.3: Location of Batangas Port relative to Manila;
Source: JICA, NEDA (2014)83

With the country being archipelagic and having scattered small markets, thechallenge is in finding a way to build infrastructures that are conducive to efficiently
distribute goods using economies of density. The largest percentages of people arescattered and difficult to reach, thus to have access to their needs, these people have to
pay more. It has therefore been a recommendation by groups of business companies todevelop economies of density by building HS network where cargoes from smaller
towns is transported quickly and efficiently to hubs via road or smaller ships (JFC,
2010; The Report, 2012). Hubs will be developed with cranes and equipment for
greater efficiency.
The HS network is a viable approach, as also been shown in Chapter 4. While
the Manila ports account around 50% share of total domestic container throughput asseen in Table 5.2, it may not be the best choice to be a hub. From the previous
premise that container traffic has contributed to the street traffic congestion in Manila
Metropolitan area, assigning Manila ports as hub will increase the container
throughput and thus the traffic congestion.
This chapter therefore explores the feasibility of a HS network with Batangas
port as a designated hub as opposed to the Manila ports. The study will look into the
incentive/disincentive of this strategy to (i) shippers and (ii) shipping companies.
For the shipper’s perspective, transport using HS could lower transport cost
due to the discount in inter-hub transport cost brought by economies of density.
However, when cargoes intended for Manila would use Batangas hub port instead, theshipper will incur additional land transport cost. For the shipping company’s
perspective, calling in Batangas port instead of Manila port would shorten the
distance to the source and destination of cargoes (since cargoes inbound and outboundof Metro Manila comes from the south of the capital). Shorter distance and directtransport to other hubs (and not calling in multiple ports since consolidated cargoes ofinter-hub transport would then be sufficient to fill the vessel’s capacity) would lead tofaster turnaround time. This would allow the vessel to have more round voyages thanthe multi-ports calling case given the same time interval. More round voyages could
lead to greater revenues.
The shift of vessel calling from Manila to Batangas port would likely be either
prompted or encouraged exogenously such as by a governmental order or policy. This84

would only be welcomed by the shipping stakeholders (shipper and shipping
companies company) if the shift of operations from Manila to Batangas port would
not increase their transport costs and lower their profit, respectively.
The succeeding sections attempt to estimate both the effects to shippers’
transport costs and carriers’ profit of implementing the HS network wherein one of
the hubs is Batangas port. Table 5.3 summarizes this strategy’s effect to thestakeholders involved. But since the move is not intended to increase the carrier’s
profit, should they only maintain their profit as to the multi-ports calling case, what
would be an increase in their profit would be the tariff discount the carrier would
provide to the shipper for using the inter-hub route.
5.2 Selection of Hub Ports
The hub ports for this chapter will be predetermined. From Table 5.3,
Batangas port is under-utilized even with the foreign and domestic throughput
combined. A study by JICA and National Economic Development Authority (NEDA)(2014) recommends that the foreign cargoes be shifted to the adjacent ports ofBatangas and Subic. However, for the purpose of this research, we explore thetransport cost feasibility of shifting also the domestic cargoes. Domestic cargoes
provide exportable cargoes to international vessels.
From Chapter 4, result of the model designated Bacolod port as hub port.
Moreover, Table 5.4 shows that that top 2 destinations of commodities from NCR are
Central and Western Visayas, which leads us to select Cebu and Bacolod located. The
hub port locations, Batangas, Bacolod and Cebu are shown in Figure 5.4.

Manila Port
Batangas Port
Cebu Port
Bacolod Port

Figure 5.4: Locations of the Selected Hub Ports

85

Table 5.3: Summary of the possible effects of the strategy to the stakeholder
Shipper
Carrier
For carriers serving inter-hub route, lowered shipping cost is due to theshorter distance taken with Batangas as hub, as opposed to Manila, since
Lower transport cost when Batangas is nearer to the sources and destinations of cargo demands (whichrouting cargoes via hubs due are mostly south of Manila)
Possible effects of HS
to economies of density.
network and the use of
The vessel serving inter-hub routes would then have sufficient consolidated
Batangas port as hub
The possible drawback would cargoes to fill its capacity. The vessel would then call directly between hubs
instead of Manila ports
be the additional land and not in multiple ports.
to the following
transport cost of cargoes
stakeholders
intended for Manila but The possible drawback would be the saving in shipping cost, when translated
shifted to Batangas port.
to the tariff discount they would give the shippers should they maintain theirprofit at the same level, would not be enough to attract shippers to use
Batangas port.

Method to estimate thepossible positive effects

Compare the total networktransport cost for HS and
PTP with the aid of the
maximization problem of
equation 5.1.

Estimate the increase in profit due to the decrease in shipping costs. The
increase in profit would translate to the discount in tariff the carrier could
provide to the shipping line.

86Table 5.4: Value of commodities that flow from the National Capital Region in thousand Pesos;
Source: National Statistics Office (2012)

REGIONS

NCR
CAR
Ilocos Region
Cagayan Valley
Central Luzon
CALABARZONIMAROPA
Bicol Region
Western Visayas
Central Visayas
Eastern Visayas
Zamboanga Peninsula
Northern Mindanao
Davao Region
SOCCSKSARGEN
CaragaARMM
Total value
Total Quantity in
Tons

Food andLive
Animals

Beverages
andTobaccoCrude
Materials,
Inedible,
Except
Fuels

MineralFuels,
Lubricantsand RelatedMaterials

Animaland
VegetableOils, Fats
and Waxes

Chemicaland Related
Products

Manufactured
Goods
Classified
Chiefly byMaterial

MachineryandTransport
Equipment

Other
Manufactured
Articles

9,856
0
949
0
3,526
502
3,025,328
53,66910,423,147
13,396,247
1,406,456
2,805,188
6,974,786
4,500,481
1,954,007
904,984
64,25645,523,382
5,719,116

0
0
39
0
0
0
1,186,931
8
5,840,884
3,352,719
1,093,509
1,174,834
2,440,128
1,392,842
1,18,09722,429
4,427
17,248,581
615,063

15051
0
18
0
0
0
53371
3021
18799829516614804
41666
108797
43808
58723
13316
188
835,927
1,349,961

1408805
0
0
0
1160
7639
1396835707
26362931322017107910931818422814647629431
4228
42,784,607
5,488,285

0
0
0
0
0
0
8549
0
11410
10627
1171
6464
5105
4373
2125
1767
0
51,591
236,411145671
0
278
0
376
2530
70331113825944256594154930
4830606815402681758
16585918976587409413448
16,718,010
1,574,194

26636
0
45
0
12311
537435232301916511969883768543064926727
1865338
58106186746452
267864610144703738
37,641,994
3,699,195

501
0
633
0
5130
41588
161867051718
3530693725075045627272919754791113356369932081111262512484
24,577,822
1,382,921

8672
0
1822
10
848
1244
96500415106
4539424519016237009310753834022978237454583310453699154467
19,989,853
793,618

87

Others00100942050
10508
1501742402
47249894462713965616110240861633574098657
35917
238924
3,099,813
709,008

From the Philippine Ports Authority and Cebu Ports Authority, the shipping
companies plying Manila-Cebu and Manila-Bacolod are shown in Table 5.5 and 5.6.
Table 5.5: Shipping companies serving Manila-Cebu (vice-versa) route and theirvessel frequencies for the month of August
SHIPPING LINES
Escaño Lines Inc.
Fortune Sea Carrier Inc.

Gothong Southern
Shipping Lines, Inc.

Lorenzo Shipping Lines

Oceanic Container Inc.

Philippine Span Asia
Carrier Corporation

VESSELNRT

TRIP
FREQUENCY
both ways(August)FoxbatFortune Express
Fortune Harvest
Don Alberto Sr.
Don Albino Sr.
Don Alfredo Sr. 2
Don Daniel
Don Carlos Sr. 2
Don Daxton
Don Alfonso Sr.
Lorcon CDO
Lorcon GenSan
Lorcon Visayas
Lorcon Dumaguete
Ocean Greatness
Ocean Hope
Ocean Mighty
Ocean Serenity
Ocean WisdomPrincess Of The South
Span Asia 12
Span Asia 16

878.65295.50348.001,094.00
1,532.00
1,532.00
1,532.00
1,532.00
1,532.00
1,532.00
300*
2724.00300*
3513.00
1,516.00
986.002,437.00
1,038.00
1,516.00
3,452.01
1,575.00
3,255.41
368
289
289
303.80348.00401.39

2
1
1
4
4
3
4
4
4
1
3
3
2
2
2
4
3
2
3
9
2
6
1
1
1
1
2
1

LCT Brizu
LCT Cratus
LCT Daichi

SF Horizon
Seaford Shipping Lines
SF Mariner
SF Navigator*in the absence of NRT data, TEU is provided;
Source: Interview with Cebu Ports Authority, vesselfinder.com, Lorenzo ShippingLines website, Manila North Harbor Vessel Schedule (http://www.mnhport.com.ph)88

Table 5.6: Shipping lines serving Manila-Bacolod (vice-versa) route and theirvessel frequencies for the month of August

SHIPPING
LINES

Aleson ShippingLines Inc.

Lorenzo Shipping
Lines
Moreta ShippingLines Inc.
Oceanic
Container Lines
Inc.
Philippine Span
Asia Carrier
Corp.
Agro Marine
Corp.
Philippine Span
Asia Carrier
Corp.

Seaford Shipping
Lines

MV Aleson Con
Carrier 12
MV Aleson Con
Carrier 14
MV Aleson Con
Carrier 15
MV Lorcon Iloilo

1,340

MANILABACOLOD /BACOLODMANILA TRIP
FREQUENCY(AUGUST 2014)
4x / 4x

1,826

4x / -

1,383- / 4x1988

4x / 4x

MV Lorcon Manila
MV Moreta Cargo 5
MV Moreta Venture
MC Hunter
MV Ocean Abundance
MV Ocean Blessing
MV Ocean Serenity
MV Span Asia 2

2196
2,055
1,839
2,982
3,149
2,428
1,038
1,733

4x / 4x
4x / 4x3x / 3x1x / 1x2x / 2x3x / 3x1x / 1x4x / 4xMV Span Asia 22

1578

4x / 4x

Agro Marine 1
Agro Marine Ii
Agro Marine 3
LCT Brizu

137.96384.7499.5
368

1x / 1x2x / 2x
1x / 1x
1x / 1x

LCT Cratus
LCT Daichi
LCT Mazu
Seaford 9
SF Mariner

289
289
289
336
348

1x / 1x
1x / 1x3x / 3x1x / 1x2x / 2x

VESSEL

NRT

Port of Calls

Manila, Bacolod,
Zamboanga
Manila, Bacolod,
Zamboanga
Manila, Bacolod,
Zamboanga
Manila, Tagoloan,
Iloilo, Bacolod
Manila, Bacolod, Iloilo
Manila,Iloilo, Bacolod
Manila,Bacolod, Iloilo
Manila,Bacolod, Iloilo
Manila,Iloilo, Bacolod
Manila,Iloilo, Bacolod
Manila,Bacolod, Iloilo
Manila,Bacolod,
OzamizManila, Bacolod,
Cagayan de Oro
Manila, Bacolod
Manila, Bacolod
Manila, Bacolod
Manila, Bacolod ,CDO, Cebu
Manila, Bacolod, Cebu
Manila, Bacolod, Cebu
Manila, Iloilo, Bacolod
Manila,Bacolod, Iloilo
Manila,Bacolod, Iloilo

Source: Interview with Philippine Ports Authority PMO Pulupandan
Almost all of these vessels have several ports of calls other than Manila, Cebu
and Bacolod. For instance, MV Lorcon General Santos and MV Lorcon Manila(Figure 5.5) of the Lorenzo Shipping Lines call at ports Manila-Iloilo-Batangas andManila-Cebu-Dumaguete-Zamboanga respectively. The Lorenzo Shipping Company
vessels ply at speeds of 11 knots to 15 knots (SEC Lorenzo Shipping Company

89

Annual Report 2013), with the other vessel characteristics for MV Lorcon Manilasummarized in Tables 5.7. The execution of the HS network would prompt changes instructure of the existing shipping lines. One is the transfer of port of calls from Manila
port to Batangas port. Second is the change from multiple ports calling to just directcalls from two hub ports as it would be given that the consolidated cargoes would
increase or maximize the vessels’ capacity to just cater the two hub ports, thus the
economies of density. Figures 5.6 shows the case of the corresponding direct call.
5.3 Estimation of the Effect to Carrier’s Profit
Here we estimate the difference in the shipping company’s profit when multiports calling is altered to direct calls between hub ports as illustrated in Figures 5.6 to
5.7 for MV Lorenzo Manila, a vessel of Lorenzo Shipping Lines, with properties
shown in Table 5.7.

Figure 5.6: Hypothetical inter-hub directtransport route from Batangas to Bacolod
Hubs

Figure 5.5: Existing multi-port calling routeof Lorcon Manila

90

Table 5.7: Lorenzo Shipping Lines Company Vessel Information
DetailMV Lorcon Manila

DWT (tons)

5,998.30

GT (tons)

4,328.00

NRT (tons)

2,196.00

Capacity (TEU)

426

Design Service Speed (knots)

15

Average Recorded Speed (knots)

11.6

Engine Type and Power in bhp*4,843.74bhp

Year Built

1996*in the absence of searchable data for Lorcon Manila engine power, value is estimatedfrom the regression model found in Cullinane and Khanna (2000) as
ln(bhp)=2.6308+0.967ln(TEU) which has r2 of 0.94.
Sources: http://www.alphaliner.com/
As we attempt to estimate the differences in profit between the two callingcases, which would translate to the tariff discount in inter-hub transport, theformulations are simplified by designating notations. The following notations (Table
5.8) are used to differentiate the route and ports, as well as the cost variables, as will
be used in the formulas. Since we only consider one vessel, MV Lorcon Manila, wewill not denote any notation for t and simply ignore it.
Table 5.8: Notations for routes, ports and vessels and cost variables
DetailNotation

DetailNotation

Multi-port calls case1

Vessel Capacity

Cap

Inter-hub port calls case2

Variable Cost

VC

Manila port

MNL

ProfitP

Batangas port

BAT

Revenue

Rev

Bacolod port

BCD

Load Factor

LF

Iloilo port

ILO

Tariff

T

91

The estimation of the difference in profit for the two calling scenarios will bebased on Equation (5.1).
∆𝑃 = ∆𝑅𝑒𝑣 − ∆𝐶𝑡2−1(5.1)

Where from Equation (2.9), total shipping cost based on Cullinane andKhanna (2000) is
𝑂𝑡
β𝑖𝑡 𝑂𝑡𝑚𝑚
𝐶𝑡𝑚 = 𝑓 ∑ [𝛿𝑖𝑡 +𝑂𝑡 𝑊𝑖𝑚 + 𝐹𝑖𝑡𝑚 + 𝐷𝑖 ( + 𝐹𝑡𝑚 )] + ∑ ∑ [(𝐺𝑖 ++ ) (𝑄𝑖𝑗
+ 𝑄𝑗𝑖
)]
𝑉𝑡
𝑅𝑖 𝑅𝑖
𝑖
𝑖
𝑗

(2.9)
From Figure 2.9, the daily capital and daily operating costs, or the expenses
paid for using the ship each day, 𝑂𝑡 , are fixed costs and are the same for the same
vessel. So for the same duration or season, 𝑂𝑡 would be the same for the same
vessel. Thus, the difference in shipping costs for the two scenarios of multi-port
calling and inter-hub direct transport for the same season or time duration is only withthe variable costs (assuming there are no additional crew expenses).
∆𝐶𝑡2−1 = 𝑉𝐶𝑡2 − 𝑉𝐶𝑡1

(5.2)

Where the shipping variable costs are expressed as follows
β𝑚𝑚
𝑉𝐶𝑡𝑚 = 𝑓 ∑𝑖[𝛿𝑖𝑡 + 𝐹𝑖𝑡𝑚 + 𝐷𝑡 𝐹𝑡𝑚 ] + ∑𝑖 ∑𝑗 [(𝐺𝑖 + 𝑅𝑖𝑡) (𝑄𝑖𝑗
+ 𝑄𝑗𝑖
)]
𝑖

(5.3)

Therefore the difference in profit of the two calling cases could be expressed as∆𝑃 = ∆𝑅𝑒𝑣 − (𝑉𝐶𝑡2 − 𝑉𝐶𝑡1 )(5.1a)

From Figure 5.7, the cost components considered for the variable costs,
Equation (5.3), are the highlighted ones.

92

5.3.1 MV Lorcon Manila Existing Multi-ports Calling Voyage
The existing route of MV Lorcon Manila is multi-ports calling as can be seenin Figures 5.5. Table 5.9 shows the existing schedule and duration of one roundvoyage. MV Lorcon Manila can make one round voyage in 7 days.

Figure 5.7: Conceptualization of Total Shipping Cost (Cullinane and Khanna, 2000)

PORT
ManilaBacolod
IloiloManilaTable 5.9: Existing Vessel Route and Schedule(Source: Lorenzo Shipping Lines website)
ETD
PORT
Mon 19:00H
Bacolod
Thu 04:00HFri 04:00H
Mon 19:00HIloiloManilaETA
Wed 01:00HThu 10:00H
Sat 10:00H

1
For the estimation of flow between ports, 𝑄𝑖𝑗, it could be rational to assume

that the vessel is not likely to carry cargoes loaded from Iloilo intended for Bacolod
since the distance from the two location is 100km and it is shown from Figure 4.8 that
container transport tariff for this distance is cheaper for RoRo vessel than container

93vessel. Moreover, RoRo transport between Bacolod and Iloilo is frequent at 19 tips
per day as can be seen in Chapter 3 Table 3.1. From this, it is assumed that
1
𝑄𝐵𝐶𝐷−𝐼𝐿𝑂
= 0.

(5.4)

Different vessel capacity utilizations will be considered in the estimation
where their values will be set the same for the all port-to-port flows of a voyage.
Then, the flow between the ports is:
1
1
1
1
𝑄𝑀𝐿𝐴−𝐼𝐿𝑂+ 𝑄𝑀𝐿𝐴−𝐵𝐶𝐷= 𝑄𝐼𝐿𝑂−𝑀𝐿𝐴+ 𝑄𝐵𝐶𝐷−𝑀𝐿𝐴= 𝐿𝐹 ∙ 𝐶𝑎𝑝(5.5)

Moreover, the distances between ports are as follows:
𝐷𝑀𝐿𝐴−𝐵𝐶𝐷 = 330 𝑛𝑚; 𝐷𝐵𝐶𝐷−𝐼𝐿𝑂 = 54 nm; 𝐷𝐼𝐿𝑂−𝑀𝐿𝐴 = 347nm
5.3.2 MV Lorcon Manila Hypothetical Direct Inter-Hub Voyage
We try to create a hypothetical schedule for the vessel following the route in
Figures 5.7, which shall also be in accordance to the vessels’ characteristics (e.g.
vessel maximum speed). The estimation of the time of the vessel at port is estimatedtaking the data from Cebu Daily News (2013) where the average gross productivity incontainer per hour of vessels (or average gross handling rate, 𝑅𝑖 ) of 7 shipping lines
docking at Cebu ports is 10.18 containers per hour. Note that the distance between
Batangas and Bacolod is 251.
From Table 5.10, for the hypothetical inter-hub direct calling case, MV
Lorcon Manila could complete one round voyage in 5 days when it is operating at sea
at speed of 14 knots. The same as the multi-ports calling case, different capacity
utilizations scenarios will be considered, thus the flows will be taken as:
22
𝑄𝐵𝐴𝑇−𝐵𝐶𝐷= 𝑄𝐵𝐶𝐷−𝐵𝐴𝑇= 𝐿𝐹 ∙ 𝐶𝑎𝑝(5.6)

Table 5.10: Hypothetical Vessel Routes and Schedule for Inter-hub Voyages
PORT
ETD
PORT
ETA
Batangas

Mon 19:00H

BacolodTue 13:00H

Bacolod

Thu 07:00HBatangas

Fri 01:00HBatangas

Sun 19:00H

94

5.3.3 Estimations of Variable Costs Components for the Two Case Scenarios
From the formula of variable cost in Equation (5.1), the following are thecomponents and their values considering the two vessels and the two calling types.
a. Charge at Port for a Type of Ship for Certain Route, 𝛿𝑖𝑡𝑚
From PPA website, vessels engaged in domestic trade that berth or drop
anchor at any government port shall be charged a Domestic Dockage Fee (Usage Fee)as shown in Table 5.11. Domestic vessels calling at officially registered private ports
shall be charged at one-half (1/2) of the Domestic Dockage Fee at a government port
but shall not be less than PhP82.00 nor greater than PhP 413.00.
Table 5.11: Domestic Vessel Dockage Fee in Government Ports
Gross Registered Tonnage (GRT)

Charge in PhP

6 to 100 GRT per calendar day or fraction thereof

82.00

Over 100 GRT per GRT per calendar day or fraction thereof

0.80

From this information, we can formulate the charge at government port for a
type of vessel t as 𝛿𝑖𝑡𝑚 = [0.80(𝐺𝑇 − 100) + 82]𝑊𝑖𝑡𝑚 where we would know from
Table 5.9 the days the vessel spends in the ports for the existing multi-port callingcase. (Note that Bacolod port (or BREDCO port) is a private port thus will have half
the charge.) From this formula, the calculated values are as follows:
Table 5.12: Calculated charge at port for MV Lorcon Manila
DetailCharge at Port (PhP)

DetailCharge at Port (PhP)

1
𝛿𝑀𝐿𝐴

8,227.95

1
𝛿𝐼𝐿𝑂

2,598.30

1
𝛿𝐵𝐶𝐷

1,948.73

22
𝛿𝐵𝐴𝑇
, 𝛿𝐵𝐶𝐷

6,062.70

b. Fuel Cost at Port i by a Ship of Type t on Route m, 𝐹𝑖𝑡𝑚
Fuel cost at port is the product of the metric ton fuel consumed in port perhour, time at port and the cost of fuel per ton,
𝐹𝑖𝑡𝑚 = 𝐹𝑤 ∙ (𝑊𝑖𝑚 ∙ 24) ∙ 𝐹𝑐𝑏

(5.7)

95

Where from the report of Clean North Sea Shipping (2014, March), theapproximation of total hourly fuel consumption of container ships in metric ton perhour as a function of ship volume is 𝐹𝑤 = 0.000041(𝐺𝑇)0.83 . Moreover, fromshipadbunker.com, Marine Gas Oil (MGO) which is used by vessel at berth is priced
at 550usd/metric ton or, taking 1 usd = 47.89 PhP, fuel cost for MGO per metric ton,
𝐹𝑐𝑀𝐺𝑂 , is PhP26,213.85. Thus the calculated costs are:Table 5.13: Calculated fuel cost at port i by the MC Lorcon Manila
DetailCost (PhP)

DetailCost (PhP)1
𝐹𝑀𝐿𝐴

63,871.62

1
𝐹𝐼𝐿𝑂

20,169.99

1
𝐹𝐵𝐶𝐷

30,254.98

2
2
𝐹𝐵𝐴𝑇, 𝐹𝐵𝐶𝐷

47,063.30

c. Fuel cost at sea per nautical mile for a ship of type t on route m, 𝐹𝑡𝑚 (PhP per
nautical mile)
Fuel cost at sea (𝐹𝑡 ) can be calculated from fuel oil consumption per hour(FO) in metric tons which can be ascertained from the installed engine power in bhp
and the specific fuel oil consumption (SFOC) (Cullinane and Khanna, 2000) throughthe formula:𝑚𝐹𝑡(𝑑𝑒𝑠𝑖𝑔𝑛𝑒𝑑)=𝐹𝑂∙
𝑉𝑡𝑚 (𝑑𝑒𝑠𝑖𝑔𝑛𝑒𝑑)

𝑓𝑐𝐼𝐹𝑂

(5.8)

The paper moreover presented that SFOC information could be derived fromthe Institute of Marine Engineers (1994) and The Motor Ship (1995 and 1996) to be
on average equal to 125 gms/bhphr.
𝐹𝑂 =𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝑏ℎ𝑝 [ 𝑆𝐹𝑂𝐶] [𝑈𝑡𝑖𝑙𝑖𝑠𝑎𝑡𝑖𝑜𝑛 (80%)]⁄1,000,000 (5.9)

From shipadbunker.com, Intermediate Fuel Gas Oil 180 (IFO180) used byvessel at sea is priced at 280usd/metric ton, or taking 1usd=47.89PhP, fuel cost for𝑃ℎ𝑃13,407.66
MGO per metric ton is𝑓𝑐𝐼𝐹𝑂180 =. Therefore, 𝐹𝑡(𝐴𝑉𝐸) values are:𝑚.𝑡.
𝑚𝐹𝑡(𝑑𝑒𝑠𝑖𝑔𝑛𝑒𝑑)==

0.4843 m. t.⁄
hr ∙ PhP13,407.66 = PhP 432.89⁄
n. m.
15 n. m.⁄
m. t.
hr

96

Operations of vessel at lower than the designed speed results in fuel savings
because of the reduced water resistance. From Stopford (2003), actual fuelconsumption will be calculated based on ‘cube rule’.
𝑚𝑉(actual)𝑚
𝐹𝑡𝑚 = 𝐹𝑡(designed)
(𝑉 𝑚
)

𝑎

(5.10)(designed)

where a is about 3 for diesel engines. Thus,
11.6 3 PhP 200.21
PhP
432.89⁄⁄n. m.
𝐹 =n. m. ( 15 ) =1

14 3 PhP 351.96
PhP
432.89⁄n. m. ( ) =⁄n. m.
𝐹 =15
2

d. Average Handling Rate in Port, 𝐺𝑖 , Variable Portion of Port Charge 𝛽𝑖𝑡 , andAverage Gross Handling Rate, 𝑅𝑖
Here, the average handling rate in port (𝐺𝑖 ) is what we would refer as thewharfage fee or the charge that the owner of the port charges for the movement of𝛽cargo through the facility. While the port charge per average gross handling rate ( 𝑅𝑖𝑡)𝑖would be the stevedoring fee. These are the only known fees incurred in the port forthe cargoes from the PPA website, which the PPA regulates. In Table 5.14 are thecharges on cargoes for all ports. The cargo charges are independent of the handlingrate.
Table 5.14: Wharfage and Stevedoring Charges for 1 TEU Container(Source, PPA website)
Charge in PhP
Wharfage fee

126.00

Stevedoring fee

301.00

𝐺𝑖 = 𝑃ℎ𝑃 126.00/𝑇𝐸𝑈 ;

97

𝛽𝑖𝑡
𝑅𝑖

= 𝑃ℎ𝑃 301.00/𝑇𝐸𝑈

5.3.4 Estimation of the Difference in Profit as Indicator of Inter-hub Tariff
Discount
The difference in profit can be calculated from Equation (5.1a) from variable
costs and revenues.
a. Variable Costs
These are estimated from Equation (5.3) with the components of the formula
already calculated in the preceding Section 5.2.3. Considering one round voyage,
we arrived at the following formulation based on load factor. The full process inarriving at these formulations could be found in the Appendix B.
Table 5.15: Variable costs of vessel and calling types as function of load factor
DetailFormulation for 1 round voyage based on Load Factor

𝑉𝐶 1

𝑃ℎ𝑃 273,425.08 + 𝑃ℎ𝑃 620,256 ∙ 𝐿𝐹1

𝑉𝐶 2

𝑃ℎ𝑃 282,935.92 + 𝑃ℎ𝑃 620,256 ∙ 𝐿𝐹 2

b. Tariff
Tariff in thousand PhP for 1 TEU container can be estimated from the linear
fit of container vessel case of Figure 4.8, which is
Y = 22.122 X + 19,119(5.11)

where X is kilometer travelled by the container vessel. Moreover, we have stated in
Sections 5.2.1 and 5.2.2 the distances between ports. Thus, in Table 5.16 are thecalculated tariff for 1 TEU container transport between the ports.
Table 5.16: Tariff for 1 TEU container for transport between ports
DetailTariff (PhP/TEU)

𝑇(𝑀𝐿𝐴−𝐼𝐿𝑂) ; 𝑇(𝐼𝐿𝑂−𝑀𝐿𝐴)

32,633.542

𝑇(𝑀𝐿𝐴−𝐵𝐶𝐷) ; 𝑇(𝐵𝐶𝐷−𝑀𝐿𝐴)

33,341.446

𝑇(𝐵𝐴𝑇−𝐵𝐶𝐷) ; 𝑇(𝐵𝐶𝐷−𝐵𝐴𝑇)

29,403.73

98

c. Percent Difference in Profits as Percent Tariff Discount in Inter-hub Flow
From Section 5.2.1 and 5.2.1, it has been established that MV Lorcon Manila
could complete one round voyage for the multi-ports calling and the inter-hub directcalling cases in 7 and 5 days, respectively. If considering one season to be 35 days,
using Equation (5.1a) and the preceding information, the difference in profit for thetwo calling scenarios can be estimated from the following formulas:∆𝑃 = ∆𝑅𝑒𝑣 − (𝑉𝐶𝑡2 − 𝑉𝐶𝑡1 )(5.1a)

While the percent difference of profit compared to the original (existing)multi-ports calling case is:Calculating, we will have:
PhP29,403.73
7 {(2) () (426TEU )(𝐿𝐹 2 )}
TEU
2−1
∆𝑃
=[
]
PhP32,633.542 + PhP33,341.446
1−5 {(2) () (426TEU)(𝐿𝐹 )}TEU− [7{PhP 282,935.92 + PhP 620,256(𝐿𝐹 2 )}− 5{PhP 282,935.92 + PhP 620,256(𝐿𝐹1 )}]∆𝑃2−1 = PhP171,022,053.7𝐿𝐹 2 − PhP137,425,444.4𝐿𝐹1 − PhP613,426.04

As mentioned earlier in the introduction of this chapter, the shift in port of callfrom Manila to Batangas by shipping company is not intended to maximize theirprofit but to comply with a regulation or policy imposed by the government. Thus, if
the profit level will be maintained, the would be increase in profit as a consequence ofincreased revenue and decrease in total shipping costs shall be the tariff discount thecarrier would give to the shipper for using the inter-hub link. Mathematically, therationale is as follows:∆𝑃 = ∆𝑅𝑒𝑣 − ∆𝑉𝐶(5.1a)∆𝑃 = [(𝑇 2 𝑓 ∑𝑖 ∑𝑗 𝑄2𝑖𝑗 ) − 𝑅𝑒𝑣 1 ] − ∆𝑉𝐶(5.12)

If ∆𝑃 is set to zero, but is instead used to decrease 𝑇 2 , the new tariff for the
direct inter-hub calls case is expressed as shown:99

̅̅̅2̅ =𝑇2 − 𝑇∆𝑃2
𝑓 ∑𝑖 ∑𝑗 𝑄𝑖𝑗(5.13)

Thus, the tariff discount in percent is
2 ̅̅̅̅̅
2

𝑇 −𝑇%𝑇 𝑑𝑖𝑠𝑐𝑜𝑢𝑛𝑡 = 100 ( 2 )𝑇(5.14)For the scenario considered,
PhP171,022,053.7𝐿𝐹 2−PhP137,425,444.4𝐿𝐹1−PhP613,426.04−
7(2)(426TEU)(𝐿𝐹 2 )%𝑇 𝑑𝑖𝑠𝑐𝑜𝑢𝑛𝑡 = 100 𝑥
PhP29,403.73
TEU
PhP 171,022,053.7𝐿𝐹 2 − PhP137,425,444.4𝐿𝐹1−PhP613,426.04=
PhP 1,753,638.457𝐿𝐹 2
A JICA and MARINA (2005) study shows that a sample container vessel with
5,589GT plying Manila-Cebu-Iloilo-Bacolod-Manila has an annual container loadfactor of only 13.9% in 2003. This is very low compared to the common load factor of
70% for vehicles. Figure 5.8 shows the graph of %tariff discount with varying loadfactors of vessels in the two calling cases.
Load factors of 0.1 to 1.0 are provided for the multi-ports calling case.
Considering 0.2 and 0.4 load factor for multi-ports and inter-hub direct calling cases,
respectively, more than 60% tariff discount could be provided to the shipper. The caseof inter-hub direct calling is assumed to have higher load factor since consolidation is
expected with inter-hub transport. Even if we consider the common load factor of 0.7
for the multi-ports calling case and 0.8 for the inter-hub direct calling case, the tariff
discount is at approximately 30%.
Therefore, we can consider different discount factors, α, in the HS model
since, from what we have shown, the existing load factor is very low. The effect of100

consolidation and increase in load factor could facilitate tariff discount of even as
high as 60%. This justifies the use of α=0.5, 0.7 and 0.9 in the Chapter 4.

Tariff discount for interhub transport
(%)

100
90
80
70
60
50
40
30
20
10
0

Exisitng multiports calling case
1.0 load factor
0.9 load factor
0.8 load factor
0.7 load factor
0.6 load factor
0.5 load factor
0.4 load factor
0.3 load factor
0.2 load factor
0.1 load factor
0.0

0.2
0.4
0.6
0.8
1.0
Load Factor for the Hypothetical Inter-hub Direct Calling Case
Figure 5.8: Percent tariff discount for inter-hub transport

For the succeeding section, we consider αvalues of 0.6, 0.7, 0.8 and 0.9.

5.4 Transport Costs Savings for Shippers
5.4.1 Model Formulation
The model in this chapter is based on that of Chapter 4 and incorporates thesame properties of intermodality, multiple allocations of flows, non-restrictive
networking policy and general hub network topology. The decision maker is a freight
forwarder who aims to minimize the total transport cost for the network it covers.
In this model, the volume of cargoes intended for Manila ports but shifted to
the Batangas port, which is a predetermined hub, is maximized as the objectivefunction. Concurrently, the route taken (whether via hubs or directly), modes,
allocation to hubs and the total transport cost savings are determined. In Tables 5.17
and 5.18 are the input and decision variables used in the model, respectively.

101

Table 5.17: Input variables
SymbolDefinition

𝑊𝑖𝑗

cargo flow volume from node i to node j. In this study, the origindestination data considered is the total national domestic cargo data forthe year 2012 as shown in Table 5.10
discount on the unit cost of flows for travel between hubs asconsequence of economies of density
Total transport cost of TEU unit between nodes i and j using transportmode M, where M could be either truck, intermodal truck-RoRo,container vessel (CV) or RoRo vessel (RV) (when considering the two𝐶𝑉,𝑅𝑉latter cases only, cost of unit flow is given the symbol 𝑐𝑖𝑗
)

α
𝑀
𝑐𝑖𝑗

𝐹

Increase in volume to be satisfied in the link for it to be a hub arc
Table 5.18: Decision variables

Symbol𝑋𝑖𝑗𝐾
𝑌𝑖𝑗𝐻𝐾

Definition
1 if flow from node i to j goes through hub arc K, 0 otherwise
1 if flow from node i goes directly to j, 0 otherwise
1 if a transport arc K is utilized as hub arc, 0 otherwise

Transport costs per link for container vessel and, RoRo vessels, trucks andintermodal truck-RoRo/container modes were calculated from port fees and transport
tariffs as can be found in Table 4.4 and Figure 4.8 of Chapter 4. The transport mode
used per link i-k is determined as the mode that gives the minimum transport cost,which is precalculated before input to the model as shown in Equations 4.20 to 4.23
of Chapter 4 with the definition of the symbols in Table 4.7. The discount factor (α)
represents the economies of density brought by cargo consolidation in inter-hub
connections, and is fixed at values 0.9, 0.7 and 0.5. “Economies of density” isdefined as the falling of average cost attributed to the increase of utilization ofvehicle fleet (in this case container vessel) for a particular route (Jansson andShneerson, 1985).
Max ∑𝑖=2 ∑𝑗=2 𝑊𝑖𝑗 𝑋𝑖𝑗𝐾
s.t.

∀K

(5.15)∑𝐾 𝑋𝑖𝑗𝐾 + 𝑌𝑖𝑗 = 1∀𝑖, 𝑗 ≠ 𝑖, K

(5.16)𝑋𝑖𝑗𝐾 ≤ 𝐻𝐾∀𝑖, 𝑗 ≠ 𝑖, 𝐾

(5.17)102∑𝑖 ∑𝑗 𝑊𝑖𝑗 𝑋𝑖𝑗𝐾 ≥ 𝐹(𝑊𝐾 )𝐻𝐾∀𝑖, 𝑗 ≠ 𝑖, 𝐾

(5.18)

𝑀
𝑀∑𝑖 ∑𝑗[(𝑐𝑖𝐾+ 𝛼𝑐𝐾𝐶𝑉,𝑅𝑉 + 𝑐𝐾𝑀2 𝑗 ) − 𝑐𝑖𝑗]𝑊𝑖𝑗 𝑋𝑖𝑗𝐾 < 0 ∀𝑖, 𝑗 ≠ 𝑖, 𝐾
1(5.19)𝑋𝑖𝑗𝐾 , 𝑌𝑖𝑗 , 𝐻𝐾 ∈ {0,1}(5.20)The objective function (5.15) maximizes the volume to be shifted from Manila
harbour to Batangas port. These include both incoming and outgoing cargoes.
Constraint (5.16) regulates that each pair of demand nodes has to be either transported
directly or via hubs. Constraint (5.17) ensures that a flow can only be routed through a
hub arc if the arc or link is established as a hub arc. Constraint (5.18) restricts that
there is an increase of volume for the route serviced by the hub arc by a factor F.
Constraint (5.19) ensures that the sum of transport costs when HS network is used isless than when cargoes are simply transported directly. Lastly, constraint (5.20)
represents the binary requirement.
The problem is coded in MATLab and run using its solver intlinprog for linear
integer programming. It is the limitation of this study that the actual discount benefit
due to density economies is not calculated as part of the research, since shipping
companies do not divulge their financial information such as operating, capital,
bunker cost, etc. The discount factor αis varied at values 0.9, 0.8, 0.7 and 0.6. The
consolidated volume is designated by the increase in the hub link volume by a factorof “F”.
5.4.2 Resultsa. Consolidated Volumes and Transport Costs Savings
The hub arcs K considered are (1) Batangas-Bacolod, (2) Batangas-Cebu, (3)Bacolod-Batangas, and (4) Cebu-Batangas. Since transport cost discounts for hub-tohub transport is brought by economies of density, we restrict that the increase inconsolidated volumes in hub-to-hub links be at least 30%, thus we examine the casesof “F” equal to 30%, 50%, 100% and 150% increases in hub link volumes. Table 5.19
shows what would be the shifted volume intended for Manila to Batangas ports thatsatisfy our objective function in equations in 5.1 to 5.6. These are for the cases of
discount factors 0.9, 0.8, 0.7 and 0.6 with the said increase in consolidated volumes.

103

Table 5.19: Shifted Cargo Volume Intended for Manila Ports (Metric Ton)
Discount

Increase in Link Volume, F

Factor (α)

30%

50%

100%

150%

0.9

101,190

-

-

-

0.8

215,985

152,451

76,185-0.7

2,076,362

2,060,821

2,039,088

1,960,000

0.6

205,863

4,193,992

4,193,992

1,960,000

From Figure 5.2, the average total containerized volume domestic throughput
is 12,206,481 metric tons. Discount factors for hub-to-hub transport costs of 0.9 and0.8 would not yield substantial shift in cargo volume, while discount factors 0.7 and
0.6 for F=100% case could yield shifts of 17% and 34% of Manila port cargoes,
respectively.
The objective function represented in equations 5.1 to 5.6 maximizes thevolume of cargoes intended for Manila port given that a HS system is in place which
hub arcs are Batangas-Bacolod, Batangas-Cebu and vice-versa, and which totaltransport cost for the resulting network provides costs saving relative to when purely
PTP network is used. The transport costs saving are ensured by equation 5.5, but are
not determinate as of how much.
The optimal volume of cargo flows routed through hubs given at least 100%
increase in link volume and 0.7 transport cost discount factor for hub-to-hub transport
is shown in Table 5.20.
Only the Batangas-Cebu link satisfies the constraint that to be a hub arc given,
there shall be 100% increase in link volume. Thus, the results show nine flows
intended for Manila as origin are routed through the Batangas-Cebu hub link. The
negative values in parenthesis in column 8 entails that more is paid to transport 1 TEUof these cargoes through this route. These cargo flows are included in the results
because even when the per TEU transport cost via hubs is more expensive than directtransport, the total transport cost when the consolidated volumes and discount factor
are considered, there is transport cost saving of 0.18%.

104

Table 5.20: Case 0.7 discount factor in hub-to-hub transport (F=100%)
Cargo
Flow
1
2
3
4
5
6
7
8
9

i

K

j

Volume(Metric
Tons)

Batangas
Batangas
CalapanManilaManilaManilaManilaManilaManilaBatangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu

Cebu
Toledo
Cebu
Cebu
Ubay
Benit
Allen
DangayCalapan676,212
98,973665
1,960,000
76,185
103
144
2,655
2,260

Flow Cost of
DirectTransport1(PhP)
1,258,355,812
193,301,162
1,200,234
4,042,395,689
160,218,185
224,034
266,670
4,061,348
3,132,406

Considering Cargo Flows 1 to 9

2,817,198

5,663,155,540

5,660,931,762

Considering Cargo Flows 1 to 4

2,735,850

5,495,252,897

5,413,746,434

Ports

𝑀
1 𝑊𝑖𝑗 𝑐𝑖𝑗𝑀
2 𝑊𝑖𝑗 (𝑐𝑖𝐾+∝ 𝑐𝐾𝐶𝑉,𝑅𝑉 + 𝑐𝐾𝑀2 𝑗 )1105

Flow Cost of
Transport via
Hubs2
(PhP)
880,849,068
176,459,889
1,192,173
4,355,245,304
226,773,855
370,079
530,595
10,408,878
9,101,921

Transport Cost
Saving due to
Discount Factor(PhP/TEU)
10,0493,063
218(-2,873)(-15,725)(-25,485)(-33,024)(-43,037)(-47,537)
Total Cost Saving
via Hubs (PhP)
2,223,778(0.18%)
81,506,463(6.48%)

The total consolidated volume when considering cargo flows 1 to 9 is2,817,198 metric tons. However, if only cargo flows 1 to 4 are considered, theconsolidated volume is 2,735,850 metric tons which is still 316.61% higher than theoriginal cargo volume of Batangas-Cebu, and greater than our 100% restriction andthus would merit density economies. Nonetheless, the transport costs saving evenincrease to 6.48% when only cargo flows 1 to 4 are routed through the hubs.
The minimization optimization described by the objective function suggests a
strategy to be taken by a freight forward given a certain O-D matrix of cargo flows.
However, in this case the cargo volume O-D flows are taken to be that of the wholedomestic cargo flows of the Philippines for year 2012. The full transport cost saving
would be realized and achieved by the freight forwarder if there is only one freight
forwarding company player that services all the cargo flows; but to assume that is afallacy. It is therefore not realistic for a small freight forwarding company to route 1
TEU of cargo with Manila-Calapan as OD through the hubs even though he has othercargoes that could be routed in the same route (e.g. for Batangas-Cebu) that would
give him transport costs saving. However, the 2,873 PhP increase in per TEU cost for
Manila-Cebu when routing through hubs is minimal and could be eliminated if
policies will be implemented favoring shifting of cargoes to Batangas port (e.g.
discount in port fees, improvement of access road, etc.); thus, this route is retained.
The problem with Manila port congestion in 2015 prompted the government toencourage shippers to shift cargoes to Batangas and Subic ports by giving 50-90%
discount to the total port fees. If the total port fees amount to PhP 606 per TEU fordomestic cargoes (not including arrastre) as shown in Table 4.4, discount of PhP 545
would be given.
The consolidated volume of 2,735,850 metric tons is 316.61% increase in the
Batangas-Cebu volume and 39.58% increase in the Manila-Cebu volume. The liner
vessels listed in Table 5.5 with total NRT of 1,361,754 tons, and having other ports ofcalls aside from Manila and Cebu, could be re-routed to cater Batangas-Cebu solely.
No container liner vessel is currently plying the Batangas-Cebu route.
Meanwhile, Tables 5.21 and 5.22 show the results that satisfy the case of atleast 100% increase in link volume for 0.6 discount factor for hub-to-hub links.

106

Table 5.21: 0.6 discount factor in hub-to-hub transport (F=100%)
Flow Cost of
DirectTransport1(PhP)
166,908,368
1,332,146
24,565,856
2,227,940,693
4,061,348
1,015,112
3,132,406

Flow Cost of
Transport via
Hubs2
(PhP)
100,145,021
1,212,310
23,105,997
2,284,291,859
9,372,147
2,515,187
8,211,361

Transport Cost
Saving due to
Discount Factor(PhP/TEU)

755,013,487
158,042,058
1,068,413
442,350,322
223,529,012
218,880,316
3,990,510,718
1,961,917,002
721,845,135
215,851,876
36,744,710

13,398
6,412
3,568
945
516
480
476
(-9,167 )(-9,850 )(-12,788 )(-53,975 )

263,921,502

12,435iK

jVolume(Metric
Tons)

1
2
3
4
5
6
7

Batangas
CalapanBatangas
ManilaManilaCalapanManilaBatangas-Bacolod
Batangas-Bacolod
Batangas-Bacolod
Batangas-Bacolod
Batangas-Bacolod
Batangas-Bacolod
Batangas-Bacolod

Bacolod
Bacolod
San Carlos
Bacolod
DangayManilaCalapan

96,641794
12,8081,168,021
2,655
733
2,260

8
9
10
11
12
13
14
15
16
17
18

Batangas

Batangas-Cebu

Cebu

676,212

Batangas
CalapanBatangas
Batangas
Batangas
ManilaBatangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu

ToledoCebu
Argao
Tagbilaran
Ubay
Cebu

98,973665
255,553
116,981
116,9811,960,000

ManilaManilaManilaDapitanBatangas-Cebu
Batangas-Cebu
Batangas-Cebu
Batangas-Cebu

Argao
ToledoTagbilaran
Manila740,237
286,873
76,266
7,101

1,258,355,812
193,301,162
1,200,234
455,769,982
226,879,335
222,001,963
4,042,395,689
1,584,922,548
564,864,341
161,669,429
15,452,902

19

Bacolod

Bacolod-Batangas

Batangas

254,688439,869,171

Cargo
Flow

Ports

107

12,4352,716
2,052(-868 )(-36,008 )(-36,862 )(-40,446 )

20
21
22
23
24
25

Bacolod
San Carlos
Bacolod
San Carlos
IloiloUbay

Bacolod-Batangas
Bacolod-Batangas
Bacolod-Batangas
Bacolod-Batangas
Bacolod-Batangas
Bacolod-Batangas

CalapanBatangas
ManilaManilaManilaManila1,725
33,754
753,795
99,90048,205
10,6702,892,552
64,740,688
1,437,826,827
193,207,998
93,829,386
22,438,742

2,632,347
60,893,385
1,474,193,692
272,077,089
138,809,252
37,326,080

2,716
2,052
(-868 )(-14,211 )(-16,796 )(-25,115 )

26
27
28
29
30
31
32

Cebu
Cebu
Tagbilaran
Benit
DangayManilaCebu-Batangas
Cebu-Batangas
Cebu-Batangas
Cebu-Batangas
Cebu-Batangas
Cebu-Batangas

Batangas
ManilaManilaManilaManilaBenit

7,276
312,176
10,670
44
2,289
103

ManilaCebu-Batangas

Allen

13,540,591
643,845,317
22,618,099
95,9253,502,172
224,034
266,670

8,124,354
635,581,432
30,198,406
150,238
8,549,744
533,351
698,032

13,398476(-12,788 )(-22,135 )(-39,687 )(-53,975 )(-53,975 )144𝑀
1 𝑊𝑖𝑗 𝑐𝑖𝑗𝑀
2 𝑊𝑖𝑗 (𝑐𝑖𝐾+∝ 𝑐𝐾𝐶𝑉,𝑅𝑉 + 𝑐𝐾𝑀2 𝑗 )1108

With the given discount factor, all the four arcs can have consolidated
volumes of more than 100% of the original volumes the link service. The same caseas with the 0.7 discount factor results of Table 5.21, if cargoes would enjoy 0.6
discount factor in hub-to-hub transport costs, hub arcs Batangas-Cebu and BacolodBatangas would have significant increase volume. The liner shipping vessels intended
for Manila (i.e. Manila-Cebu and Bacolod-Manila) in Tables 5.5 and 5.6 could beshifted to Batangas Port. The significant increases in volume could merit the 0.6
discount factor.
Table 5.22: Additional details for the case of 0.6 discount factor (F=100%)
Cargo

Total Transport Costs

Consolidated

Flows being

Savings

VolumeConsidered
1 to 4

PhP
11,991,876%
0.50(Metric Ton)
1,278,264

Increase in Volume
Reference Flow
Batangas-Bacolod%
1

Manila-Bacolod
1

8 to 14610,509,850

9.54

3,225,366

19 to 23

143,688,312

7.39

1,043,962

26 to 27

13,680,122

2.08

319,452

Notes:

11222.69
9.44

Batangas-Cebu

376.98Manila-Cebu

64.56

Bacolod-Batangas1

309.90Bacolod-Manila

38.49

Cebu-Batangas1

4,290.24

Cebu-Manila

2.33

Hub arcs;*the table does not include the cargo flows in italics in Table 5.14

b. Mode Per Link
Table 5.23 and 5.24 show that should the cargo flows be routed to the hub arc,transport intermodality shall be taken by the cargoes. Thus, the hub ports should beequipped with facilities that would cater fast servicing of intermodal transport.

109

Table 5.23: Transport modes taken per link for the resulting cargo flows of the caseof 0.7 discount factor in hub-to-hub transport (F=100%)
Ports

Mode

i

K

j

i

K

j

Batangas

Batangas-Cebu

Cebu

-

Container Vessel-

Batangas

Batangas-Cebu

Toledo-Container Vessel

Truck

CalapanBatangas-Cebu

Cebu

RoRo VesselContainer Vessel-

ManilaBatangas-Cebu

Cebu

Truck

Container Vessel-

Table 5.24: Transport modes taken per link for the resulting cargo flows of the caseof 0.6 discount factor in hub-to-hub transport (F = 100%)
Ports

Mode

i

K

j

i

Batangas

Batangas-Bacolod

Bacolod-

CalapanBatangas-Bacolod

Bacolod

RoRo
VesselBatangas

Batangas-Bacolod

San Carlos-

ManilaBatangas-Bacolod

Bacolod

Truck

Batangas

Batangas-Cebu

Cebu

-

Container
Vessel-Batangas

Batangas-Cebu

Toledo-Container
VesselTruck

CalapanBatangas-Cebu

Cebu

RoRo
VesselContainer
Vessel-Batangas

Batangas-Cebu

Argao

-

Batangas

Batangas-Cebu

Tagbilaran-

Batangas

Batangas-Cebu

Ubay

-

ManilaBatangas-Cebu

Cebu

Truck

Bacolod

Bacolod-Batangas

Batangas-

Bacolod

Bacolod-Batangas

Calapan-

San Carlos

Bacolod-Batangas

Batangas

Truck

Bacolod

Bacolod-Batangas

Manila-Cebu

Cebu-Batangas

Batangas-

Cebu

Cebu-Batangas

Manila-110

K
Container
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
VesselContainer
Vessel

j
Truck
-

Truck
RoRo
VesselRoRo
VesselRoRo
Vessel

Truck
Truck

5.5 Chapter Conclusion
The study reveals that significant volume of cargoes intended for Manila port
(1,960,000 Metric Tons of cargoes for Manila to Bacolod) could be shifted to ply
through Batangas to Bacolod if the latter link be created as hub ports to consolidated
increased volumes thus could prompt shipping lines to offer 30 to 40% transport costdiscount per TEU. In the same way, Bacolod to Manila cargo of volume of 753,795
Metric Tons could be shifted to Bacolod-Batangas link if the arc Bacolod-Batangas
were designated as hub arc which within hubs transport could give 0.6 discount intransport costs. This would yield a total of 2,713,795 metric tons of cargoes to be
shifted to Batangas port or 22.23% of the average annual throughput of Manila ports.
This chapter shows that there could be transport cost saving benefits for the
shippers in shifting cargoes intended for Manila ports to the adjacent Batangas ports
when the latter port is a hub port that consolidates other domestic volume flows, andshipping cost savings benefits for the shipping in restructuring from multiple port
calls to direct hub-to-hub transport. These benefits could only be realized withgovernment interventions to create policies to encourage shippers to route throughBatangas port as hub port. The following interventions could be taken:i.

Equip Batangas, Bacolod and Cebu ports with facilities that could cater quick
operations and transshipment of multimodal transport

ii.

Improve access to Batangas port to shorten travel time and lower landtransport costs from Manila to Batangas. Rail transport infrastructure issuggested to be created for this link.

iii.

Provide incentive by discounting or eliminating port fees at Batangas port.
This has been done for the case of international cargoes.

iv.

Initiative to discourage or restrict shipping companies (i.e. those that service
Manila-Bacolod and Bacolod-Manila) to call in Manila port and instead in
Batangas port. Item iii is an encouragement to the shipping lines to follow thisinitiative.

v.

Promote industrial development in Region III and Region IV-A for products tobe more proximate to Batangas port thus encouraging vessels to call in this
port.

111

Chapter 6
Conclusions
6.1 Summary of Findings
As a whole, this study aimed at developing an intermodal hub-and-spoke
network that is suitable for an archipelagic country such as the Philippines that would
enable goods to be moved efficiently (lower cost and in a seamless manner) while notaggravating the existing problem of road congestion.
This section summarizes how the study has addressed its objectives:

Chapter 3: One of the characteristics of the HS network model for thePhilippines is the use of intermodality. However, there is a lack of studies about theintermodal transport that exists in the country. Thus, the first objective was to clarify
the development of the intermodal road-RoRo transport in the Philippines and its
current position in the domestic shipping market against the inter-island shipping
mode. We were able to address this objective in Chapter 3 by showing that the roadRoRo intermodal transport in the country has been brought to its current position by
the regulatory changes made in 2003. Positive impacts have been realized since theoperation of RRTS, and the road-RoRo intermodal transport has established its sharein the domestic cargo shipping market. Its market dominance compared with theconventional container vessel shipping is primarily influenced by transport cost andtravel time attributes of the shipment. The elimination of cargo handling charges
reduces the transport cost, while frequent trips of RoRo vessels in most legs comparedto the inter-island shipping vessels give intermodal transport the advantage of shorter
lead times leading to shorter travel times. For example, the intermodal transport has
higher market share for transport from Manila to destination along the westernseaboard, except for destinations 600 km away, because of lesser transport costs andshorter travel time than the container vessel mode.

Chapter 4: An intermodal mixed HS network model suitable for archipelagic
setting was developed in Chapter 4 that could provide considerable total transport112

costs savings compared to direct transport. The model incorporates properties of HS
that has not been tackled at once in the model development of the previous studies.
The Chapter also provided a step-by-step procedure, with Lagrangian as starting
point, in solving the problem as it is applied to the large Philippines scope. The model
is able to identify hub locations as well as cargo flow allocation to hubs, thus would
be useful tool in the domestic transport strategic planning level in identifying the portsthat need upgrade to cater hub quality, hub capacity, and facilities capable of modal
complementarity.

Chapter 5: In Chapter 5, we were able to show that the strategy of shiftingcargo from Manila to Batangas port with the latter port designated as a hub in a huband-spoke transport network would reduce the trucks that uses Manila ports, thus also
reduce the presence of trucks in the Manila City and Metro Manila, by 11 to 23% of
its current number. We are also able to show that both shipper and shipping company
could benefit from the strategy, with the aid of some government regulatoryinterventions.
6.2 Scope of Future Works
The scope for future works is geared toward addressing the limitationencountered in the conduct of this study. Though the findings in this paper contributeto the body of knowledge in the field and are useful baseline information for actual
implementation in the Philippines, the following are interesting areas that could still
be explored further:a. Mode Choice Model for the cargo transport modes - The current questionnaire
survey in Chapter 3 tackles the attributes that influence the choice of mode
between intermodal transport, container transport and air transport. The number of
respondents in the questionnaire survey is limited thus a mode choice model isbeyond the scope of the methodology. Thus, modelling of mode choice based on
utility function gathered from a shippers’ behavior survey would be interesting to
explore.

113

b. Consideration of various loading units in the Hub-and-Spoke Network modelling –One TEU is taken as the loading unit to simplify the model. Considerations ofother loading units would make the analysis and results more realistic.
c. Consideration of time constraints – because we encountered complexity inestimating travel times especially during that of transshipment in hub ports, time
constraints have not been considered in the modelling. Results would be reflectiveof reality when time constraints are taken into account.
d. Consideration of link capacity constraint – this is a limitation of the current study
but could be considered in the future. Future study could incorporate vessel
capacity and frequency per route to determine the exact capacity of links.
e. Flow dependent tariff discount for the HS model – various fixed-valued discountfactors are considered in the HS model instead of the actual tariff discounts that theinter-hub volumes merit. Equation (4.9) in Chapter 4 is provided to give a moreaccurate constraint that takes the minimum consolidated volume corresponding to𝐶𝑉,𝑅𝑉
discount factor (𝑉𝑘𝑚(α)). This would entail further research, data gathering ofvessel capacities and details, and estimations related to the shipping economics.
Moreover, the volume flow dependent discount could also be applied to non-hub
node to hub node transport if the consolidated volume is sufficient to merit
economies of density.
f. Minimization of transport costs components (e.g. tariff, port fees) as higher order
optimization as initial optimization or concurrent optimization with the hub-andspoke transport network minimization would be a challenging but more realistic
approach which could be considered for future research.

114

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123

APPENDIX A: OD Tables
Table A.1: Estimated Origin to Destination Cargo Volume Flow in TEU
D

PuertoPrincesa

Matnog

3.72

25.64

243.83

42.67

69.80

112.64

14.93

7.20

182.63133.13

62.37

62.37

125.6250.46

381.96

30.48

4.04

5.42

386.14

0.89

0.00

0.75

0.54

0.00

0.10

0.79

0.00

0.00

0.00

0.14

0.26

6.14

0.25

0.00

0.45

0.05

0.01

0.04

0.03

0.00

0.00

0.05

Puerto Princesa

86.75

6.14

0.04

0.45

0.00

0.05

1.18

1.22

0.14

0.02

0.00

1.21

Matnog132.58

10.43

4.53

2.94

2.94

0.00

0.38

2.46

11.27

1.49

4.08

11.94

Culasi

96.16

0.23

0.27

0.01

0.47

0.16

0.00

0.50

3.43

0.45

0.00

3.04

Iloilo105.78

0.88

1.03

0.05

0.50

0.54

0.28

0.00

13.07

1.73

0.00

10.56

Bacolod5054.93646.51

37.16

66.88

66.99

319.58282.672139.89

0.00

0.00

51.08

179.48San Carlos

669.93

85.68

4.92

8.86

8.88

42.35

37.46

283.60

0.00

0.00

38.18

23.79

Dumaguete

32.31

1.29

0.00

0.00

0.00

3.51

0.00

0.00

13.15

13.15

0.00

6.53

Cebu

247.31

0.05

0.00

0.02

0.21

0.73

0.76

4.71

1.71

0.23

2.98

0.00

Toledo

36.20

0.01

0.00

0.00

0.03

0.11

0.11

0.69

0.25

0.03

0.44

0.29

Argao

61.92

0.02

0.00

0.01

0.06

0.27

0.27

1.76

0.53

0.07

1.13

0.64

Tagbilaran

0.55

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.27

8.98

Ubay

0.15

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.08

2.52

Allen

17.80

1.89

0.00

0.24

0.24

0.00

0.00

0.00

0.00

0.00

0.00

4.55

Ormoc

14.23

2.36

0.00

1.65

1.65

2.83

0.22

1.67

0.83

0.11

2.83

39.85

Benit

2.45

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Dapitan

54.08

0.00

0.11

0.00

0.02

0.00

0.19

0.53

0.53

0.07

0.78

3.38

Zamboanga

50.49

0.00

0.04

0.00

0.02

0.00

0.15

0.27

0.20

0.03

0.27

1.20

Cagayan de Oro

181.42

5.73

0.00

0.00

0.00

0.46

0.60

4.57

6.94

0.92

1.76

61.37

Davao

ManilaBatangas

Calapan

0.00

356.22

13.06

Batangas3081.140.00

Calapan

15.49

DangayO
ManilaDangayCulasi

IloiloBacolod

San
CarlosDumaguete

Cebu

566.29

0.36

0.95

0.00

0.49

1.52

1.77

5.42

3.96

0.52

32.45

40.01

General Santos

7.60

2.22

2.48

0.64

0.64

7.68

2.49

18.85

10.93

1.45

4.01

10.70

Surigao

86.73

0.57

0.00

1.89

1.89

0.19

0.02

0.17

0.50

0.07

0.75

16.97

124

Table A.1: Estimated Origin to Destination Cargo Volume Flow in TEU (Continuation)
ToledoArgao

Tagbilaran

Ubay

Allen

Ormoc

Benit

DapitanZamboanga

Cagayan deOro

Manila

26.59

18.15

11.18

1.32

7.99

45.09

5.73

26.87

26.87

77.71

201.67

23.71

25.71

Batangas

56.21

38.38

148.44

17.73

21.20

5.92

0.00

30.86

14.99

26.13

75.44

38.46

70.51

Calapan

0.02

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

3.21

0.00

0.00

Dangay

0.01

0.00

0.01

0.00

0.05

0.06

0.00

0.01

0.00

0.00

0.00

0.01

0.16

Puerto Princesa

0.18

0.12

0.01

0.00

0.05

0.06

0.00

0.07

0.07

0.00

0.74

0.26

0.16

Matnog

1.74

1.19

0.81

0.10

4.98

3.62

0.00

3.05

1.48

0.91

2.35

14.49

0.00

Culasi

0.44

0.30

0.02

0.00

0.04

0.31

0.01

0.23

0.12

0.41

0.61

0.07

0.04

Iloilo

1.54

1.05

0.09

0.01

0.15

1.15

0.01

0.82

0.41

1.43

1.41

0.26

0.04

Bacolod

26.13

17.84

0.00

0.00

0.00

37.38

0.07

25.10

12.24

223.04

7.87

37.16

7.50

San Carlos

3.46

2.36

0.00

0.00

0.00

4.95

0.01

3.33

1.62

29.56

1.04

4.92

0.99

Dumaguete

0.95

0.65

0.16

0.02

0.00

0.00

0.00

1.37

0.66

2.40

0.00

0.37

0.18

Cebu

0.29

0.22

9.41

1.12

2.21

10.96

0.01

4.40

2.19

15.27

4.14

1.76

5.58

Toledo

0.00

0.09

1.38

0.16

0.32

1.60

0.00

0.64

0.32

2.24

0.61

0.26

0.82

Argao

0.15

0.00

3.56

0.42

0.84

4.14

0.00

1.65

0.81

5.77

1.39

0.66

2.11

Tagbilaran

1.31

0.89

0.00

0.12

0.00

0.00

0.00

0.00

0.00

1.36

0.00

0.27

0.55

Ubay

0.37

0.25

0.20

0.00

0.00

0.00

0.00

0.00

0.00

0.38

0.00

0.08

0.15

Allen

0.66

0.45

0.00

0.00

0.00

1.01

0.07

0.00

0.00

1.42

3.31

23.15

0.00

Ormoc

5.80

3.96

0.84

0.10

3.37

0.00

0.07

0.00

0.00

40.63

3.78

26.93

0.00

Benit

0.00

0.00

0.00

0.00

0.07

0.07

0.00

0.00

0.00

0.00

0.00

0.00

66.62

Dapitan

0.49

0.34

0.80

0.10

0.00

0.02

0.01

0.00

4.42

7.39

2.68

7.83

0.07

Zamboanga

0.17

0.12

0.27

0.03

0.00

0.02

0.01

3.10

0.00

7.02

1.58

2.75

0.07

Cagayan de Oro

8.93

6.10

1.32

0.16

1.11

1.11

0.00

28.09

27.73

0.00

64.22

22.21

80.44

Davao

5.82

3.98

0.11

0.01

0.00

1.22

0.20

10.83

6.01

128.600.00

203.68

37.55

General Santos

1.56

1.06

2.29

0.27

0.94

15.62

0.00

10.44

3.60

22.28

114.340.00

2.24

Surigao

2.47

1.69

1.35

0.16

0.19

0.00

25.27

1.84

0.93

247.48118.14

19.48

0.00

D
O

125

Davao

GeneralSantos

SurigaoTable A.2: Estimated Origin-Destination Cargo Volume Flows in Thousand Metric Tons for the Year 2012
O

Subic

ManilaBatangas

CalapanDangay4271.62

PuertoPrincesa
66.32

3.14

3.14

649.69

33.21

33.21

5640.64472.102.26

2.65

4118.12315.79315.7940700.15

0322.709.19

9.19

943.37237.59

88.82

13.55

0

4.41

0.53

0.00

3.31

0.05

0.73

111.08

4.56

0

0.54

0.68

0.05

2.29

111.08

0.69

0.54

0

0.68

Matnog341.772142.95

164.98

26.72

1.06

1.06

Culasi

0.12

48.20

8.24

10.44

0.03

0.04

Iloilo

0.12

48.20

8.24

10.44

0.03

0.04

3.88

Bacolod

0753.80254.69

15.77

1.72

1.73

100.79San Carlos

0

99.90

33.75

2.09

0.23

0.23

13.36

30.88

30.88

Dumaguete

0188.50

46.08

0

0

0

100.15

0

0

Cebu

0

312.18

7.28

0

0.24

0.24

81.57

190.10190.10Toledo

0

45.45

1.06

0

0.03

0.04

11.87

27.67

27.67

Argao

0

31.67

0.72

0

0.02

0.02

8.11

18.89

Tagbilaran

0

10.67

0

0

0

0

0

0

Ubay

0

10.67

0

0

0

0

0

Allen

0

84.24

27.61

0

0.23

0.23

0

Ormoc

0

17.77

12.20

0

0.56

0.56

Benit

0

0.04

0

0

0

0

D
Subic

0

30603.81

Manila46146.92

0Batangas9270.470CalapanDangayPuerto Princesa

MatnogCulasi

IloiloBacolod

Dumaguete

135.41San
Carlos
17.95

Cebu

0.94

426.031168.02

154.80220.98

1960.0237.59

96.64

12.81

8.01

676.21

3.31

0.00

0.00

0.00

1.69

0.21

0.21

0.79

0.11

0.00

0.67

0.23

0.23

0.80

0.11

0.00

0.69

0

3.63

3.63

86.42

11.45

14.65

44.99

3.88

0

5.45

173.03

22.93

0.00

74.51

5.45

0

173.03

22.93

0.00

74.51

233.01233.0100655.69

54.90

0

0

652.367.28

236.77236.770

181.05172.0322.80

295.97

0

25.04

3.32

43.09

27.01

18.89

17.10

2.27

29.42

18.82

0

0

0

9.18

358.73

0

0

0

0

9.18

358.73

0

0

0

0

0.00

51.78

11.72

2.38

2.38

6.07

0.80

9.61

160

0

0

0

0

0

0

0

Dapitan

4.73

7.10

0

0.60

0

0

0

0.55

0.55

3.46

0.46

2.56

12.87

Zamboanga

45.56

61.06

0

3.93

0

0

0

3.57

3.57

22.70

3.01

16.76

84.39

Cagayan de
Oro
Davao

0

681.10299.92

0

0

0

19.37

66.14

66.14

511.60

67.80

60.30

2497.512.28

411.32

2.00

5.75

0

0.01

4.82

6.54

6.54

15.81

2.10

119.50138.19General Santos

18.44

21.98

17.23

20.71

0.33

0.33

47.77

40.46

40.46

119.59

15.85

20.44

64.63

0

45.31

1.46

0

0.32

0.32

0.39

0.12

0.12

1.81

0.24

1.27

33.97

Surigao126

Table A.2: Estimated Origin-Destination Cargo Volume Flows in Thousand Metric Tons for the Year 2012 (Continuation)O

ToledoArgao

Tagbilaran

Ubay

8.96

Allen
0

62.44

0

29.24

171.40

Cagayan deOro
266.38

76.19

0.14

187.56

0.10

83.60

488.972199.80

1955.02179.10111.02116.98

77.26

3.75

0

17.30

49.25

79.28

152.68

50.21

34.13

0

0

0

0

0

0

43.87

0

0

1.38

0.30

0

0.04

0.10

0

0

0.12

0.64

1.38

0.30

0

0.04

0.10

0

0.01

0.13

0.64

44.18

5.58

0

4.16

11.84

6.69

11.16

46.04

0

2.35

3.00

0

1.87

5.32

17.64

9.16

1.41

0

2.35

3.00

0

1.87

5.32

17.64

9.16

1.41

0

0

0

4.12

0

2.46

6.99

118.39

2.64

8.49

0.63

0

0

0.55

0

0.33

0.93

15.69

0.35

1.13

0.08

0

0.00

0

12.14

34.56

115.37

0

7.64

1.42

541.99464.680162.21461.873109.47379.57151.96181.54

78.90

67.65

0

23.61

67.24

452.67

55.26

22.12

26.43

53.87

46.19

0

16.12

45.91

309.06

37.73

15.10

18.04

9.95

0

0

0

0

0

94.35

0

8.12

6.02

0

0

0

0

0

0

94.35

0

8.12

6.02

0

0

5.08

1.19

0

0

27.92

43.46

196.23

0

1.53

28.85

0

1.19

0

0

282.92

17.56

80.69

0

D

62.36

161.01

8.96

Manila286.87740.24

76.27

Batangas

98.97

255.55116.98

Puerto Princesa

0.25

0.64

0

0

Calapan

0.10

0.25

0.07

0.07

Dangay

0.10

0.25

0.07

0.07

Matnog

6.58

16.99

1.55

1.55

Culasi

10.91

28.16

0.30

0.30

Iloilo

10.91

28.16

0.30

0.30

Bacolod

8.04

20.75

0

San Carlos

1.06

2.75

0

Dumaguete

26.50

68.42

2.06

2.06

Cebu

27.15

68.23

498.52498.52

Toledo

0

10.95

72.57

72.57

Argao

3.77

0

49.55

49.55

Tagbilaran52.51

135.57

0

Ubay

52.51

135.57

9.95

Allen

7.58

19.57

0

Ormoc

23.44

60.53

1.53

Ormoc

Benit

DapitanZamboanga

Davao

Surigao294.90GeneralSantos
67.28

19.09

Benit

0

0

0

0

1.19

1.19

0

0

0

0

0

0

164.81

Dapitan

1.88

4.86

1.39

1.39

0

0

0

0

32.14

126.01

24.21

23.47

1.19

Zamboanga

12.35

31.89

9.13

9.13

0

0

0

74.00

0

146.8665.92

147.25

1.19

Cagayan de
Oro
Davao

365.55943.86

24.21

24.21

94.00

16.33

0

502.13518.6101204.29406.041432.29

20.23

52.18

0.21

0.21

0

0.95

0

30.98

55.16

2305.95

03647.00

644.01

General Santos

9.46

24.43

6.22

6.22

11.81

34.13

0

21.26

41.26

375.982046.80

031.87

Surigao

4.97

12.84

1.21

1.21

0.79

0

109.1
7

2.33

4.44

4092.892102.78229.260127

APPENDIX B: Variable Cost Estimation

The variable costs are calculated based on Equation (5.3):

𝑉𝐶𝑡𝑚 = 𝑓 ∑ [𝛿𝑖𝑡 + 𝐹𝑖𝑡𝑚 + 𝐷𝑡 𝐹𝑡𝑚 ] + ∑ ∑ [(𝐺𝑖 +
𝑖

𝑖

𝑗

β𝑖𝑡
𝑚
𝑚
) (𝑄𝑖𝑗+ 𝑄𝑗𝑖)]
𝑅𝑖

For MV Lorcon Manila existing multi-ports calling case:
1
𝑉𝐶𝑀= (𝑃ℎ𝑃 8,227.95 + 𝑃ℎ𝑃 1,948.73 + 𝑃ℎ𝑃 2,598.30)+ (𝑃ℎ𝑃 63,871.62 + 𝑃ℎ𝑃 30,254.98 + 𝑃ℎ𝑃 20,169.99)+ (330 𝑛𝑚 + 54 𝑛𝑚 + 347𝑛𝑚)(𝑃ℎ𝑃 200.21⁄𝑛𝑚)+𝑃ℎ𝑃 126.00/𝑇𝐸𝑈[(2 𝑥 426𝑇𝐸𝑈) ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀1 ] +2(𝑃ℎ𝑃 301.00⁄𝑇𝐸𝑈 )[(2 𝑥 426𝑇𝐸𝑈) ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀1 ]1
𝑉𝐶𝑀= 𝑃ℎ𝑃 273,425.08 + 𝑃ℎ𝑃 620,256 ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀1

For MV hypothetical inter-hub direct calling case:2
𝑉𝐶𝑀= 2(𝑃ℎ𝑃 6,062.70) + 2(𝑃ℎ𝑃 47,063.30) + 2(251 𝑛𝑚)(𝑃ℎ𝑃351.96⁄𝑛𝑚)+𝑃ℎ𝑃 126.00/𝑇𝐸𝑈[(2 𝑥 426𝑇𝐸𝑈) ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀2 ]+ 2(𝑃ℎ𝑃 301.00⁄𝑇𝐸𝑈 )[(2 𝑥 426𝑇𝐸𝑈) ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀2 ]2
𝑉𝐶𝑀= 𝑃ℎ𝑃 282,935.92 + 𝑃ℎ𝑃 620,256 ∗ 𝑙𝑜𝑎𝑑 𝑓𝑎𝑐𝑡𝑜𝑟𝑀2

128