国際商取引における書類手続き効率化に関する研究
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言語: English
出版者:
公開日: 2019-06-25
キーワード (Ja):
キーワード (En): International Trade Transaction Mode,
International Logistics Ontology, Supporting System,
Optimized information flow, Simulation Modeling
作成者: ポンアナン, カイルン
メールアドレス:所属:

URL

https://doi.org/10.15118/00009907

A Study on Promoting Efficient Paper Procedures inInternational Trade Transaction

Klairung Ponanan

A dissertation submitted in partial fulfillment of therequirements for the degree ofDoctor of Philosophy of EngineeringofMuroran Institute of Technology

Course of Advanced Information and Electronic
Engineering, Division of Engineering
Mach 2019

DECLARATIONI hereby declare that this thesis is my own work and effort and that it has not been
submitted anywhere for any award. Wherever contributions of others are involved, every
effort is made to indicate this clearly, with due reference to the literature, andacknowledgement of collaborative research and discussions.

Muroran, March 2019

Klairung PONANANi

ii

ACKNOWLEDGEMENTS
I would never have been able to finish my dissertation without the guidance of my advisor
and committee members, help from friends, and support from my family.
Firstly, I would like to express my sincere gratitude to my advisor Prof. SUTO Hidetsugu
and Prof. WATANABE Shinya for the continuous support of my Ph.D. study and related
research, for their patience, motivation, immense knowledge and providing me with anexcellent atmosphere for doing research. I could not have imagined having a better advisor
and mentor for my Ph.D. study. Your advice on both research as well as on my career havebeen invaluable.
Besides my advisor, I would like to thank the rest of my thesis committee i.e. Prof.
Yoshifumi Okada for his insightful comments and encouragement, but also for the hardquestion which encouraged me to widen my research from various perspectives.
I thank my fellow the members of Computational Intelligence Laboratory and System
Design Laboratory in for the stimulating discussions, for the helping me about thisresearch, and for all the fun we have had in the last three years. Also, I thank my friends
in the following institution. Especially, I would like to say THANK you for my tutor, hisname is JUNYA Inafune for amazing help all the time. I thank to SATOSHI Yamashita
and JUNYA Tanaka, they were always willing to help me. I also thank to Dr. Woramol
Chaowarat WATANABE for academic suggestions.
Moreover, I would like to say THANK YOU for every Thai student that was with me in
Muroran. They are not only my friends but also my family here. When I am tired or
disappointed, they always stand my side and encourage me to be strong again. I always get
spiritual from them. Especially, I would like to thank Tanapun SRICHANTHAMIT, shealways stands by me.
Last but not the least, I would like to thank my family for supporting me spiritually
throughout writing this thesis and my life in general, especially my mother Mrs. Bangon
WICHAI. Words cannot express how grateful I am to them. They were always encouraging
me with their best wishes, and always there cheering me up and stood by me through thegood and bad times.

Muroran, December 25, 2018

Klairung PONANAN

iii

iv

ABSTRACTIn this thesis, a novel framework for supporting international trade transaction processes
in ASEAN countries is proposed. The ASEAN has been established for promoting economic
activities in this region. Usually, in international trade transaction, many paperwork
processes are required in both import and export countries. The documents required in theprocesses have been created ad-hoc ways. Such facts make the paperwork processes of theinternational trade transaction system complex.
Due to the above-mentioned situations, supporting systems for optimizing paperwork
processes are required. A framework for such supporting system is proposed in this thesis.
This thesis consists of three proposals; (1) an international trade transaction model, (2) aninternational logistic ontology, and (3) an algorithm for optimizing information flow.
(1) An international trade transaction model: This model is an underlying basis of theframework of supporting system for international trade transaction. The model consists of
3 layers; document layer, information layer and presentation or user interface layer. Theselayers are based on the results of analyzing the actual international trade transaction
processes. Paperwork processes are described on the document layer. Information flow
processes are described on the information layer. And the descriptions depending on theusers’ nationality are described on the presentation layer.
(2) An international logistics ontology: The ontology was created for describing theinternational trade transaction model. It was created in accordance with the results ofsurveying documents which are used in international trade transaction processes among
the ASEAN countries.
(3) An algorithm for optimizing information flows: This algorithm optimizes information
flows on the information layer. Optimized information flows are converted to document
flows and they are described on the document flow layer. A case study is shown in order toillustrate processes of the supporting system. In addition, results of multi-agent
simulations conducted to investigate effects of the proposed algorithm are shown. The
results show that the total time of optimized information flow can be reduced 27.28% whencompared with the total time of current information flow.
Keywords: International Trade Transaction Model, International Logistics Ontology,
Supporting System, Optimized information flow, Simulation Modelingv

vi

Table of contents

TABLE OF CONTENTSDECLARATIONiACKNOWLEDGEMENTS

iii

ABSTRACTv

LIST OF FIGURES

ix

LIST OF TABLES

xi

Chapter 1

INTRODUCTION ................................................................................................ 1

1.1

Background of study ................................................................................................... 1

1.2

Goal .............................................................................................................................. 2

1.3

Scope ............................................................................................................................ 3

1.4

Contributions............................................................................................................... 3

1.5

Structure and outline of the thesis ............................................................................ 4

Chapter 2
2.1

BACKGROUND ................................................................................................... 7

Literature review ........................................................................................................ 7
2.1.1

International trade transaction ...................................................................... 7

2.1.2

Information and information flow for organization..................................... 11

2.1.3

Modeling information flow ............................................................................ 12

2.2

Ontological engineering ............................................................................................ 17

2.3

Multi-agent simulation ............................................................................................. 20

Chapter 3

RESEARCH METHODOLOGY ........................................................................ 23

3.1

Literature review methodology ................................................................................ 23

3.2

Proposed technique methodology............................................................................. 24

3.3

Simulation methodology ........................................................................................... 24

Chapter 4

SUPPORTING SYSTEM FOR INTERNATIONAL TRADE TRANSACTION
29

4.1

International trade transaction model .................................................................... 29

4.2

Outline of supporting system for international trade transaction ........................ 32

4.3

International logistics ontology ............................................................................... 32vii

Table of contents

4.4

Algorithm for optimizing information flows ........................................................... 38

Chapter 5
5.1

5.2

EXPERIMENTS ................................................................................................ 45

Case study for optimizing information flow ............................................................ 45
5.1.1

Example of optimizing document flow.......................................................... 47

5.1.2

Discussion ....................................................................................................... 54

Simulation models .................................................................................................... 55
5.2.1

Experimental design ...................................................................................... 55

5.2.2

Information flows before applying the proposed algorithm ........................ 57

5.2.3

Information flows after applying the proposed algorithm .......................... 59

5.2.4

Results ............................................................................................................ 60

5.2.5

Discussion ....................................................................................................... 61

Chapter 6

CONCLUSIONS AND FUTURE DIRECTIONS ........................................... 67

6.1

Conclusions ................................................................................................................ 67

6.2

Directions for future works ...................................................................................... 68

APPENDIX A
APPENDIX B
APPENDIX CREFERENCES

viii

Table of contents

LIST OF FIGURES
Figure 1-1 History of ASEAN ................................................................................................... 1
Figure 1-2 ASEAN country members ...................................................................................... 3
Figure 2-1 Trade of Goods and Services, 2005-2016 ............................................................... 8
Figure 2-2 Volumes of trade in goods, 2005-2015 ................................................................... 8
Figure 2-3 Trade flows across regions and change during 2015-2016................................... 9
Figure 2-4 Number of international trade documentation in each region, 2016 ................ 10
Figure 2-5 Time for export in ASEAN countries, 2013......................................................... 10
Figure 2-6 Time for import in ASEAN countries, 2013 ........................................................ 11
Figure 2-7 Graphes à Résultats et Activités Interreliés (GRAI) Modeling Technique ...... 14
Figure 2-8 Petri net representations and constructs: a) Sequential execution; b)
Concurrency; c) Synchronization; d) Merging; e) Conflict; and f) Confusion ...................... 15
Figure 2-9 A complex network as a graph ............................................................................. 16
Figure 2-10 A snapshot of Ontology Editor ........................................................................... 19
Figure 2-11 A legend of part-of relation................................................................................. 20
Figure 2-12 Conceptualization of a simulation model .......................................................... 21
Figure 3-1 General simulation methodology ......................................................................... 25
Figure 4-1 International trade transaction Model ................................................................ 29
Figure 4-2 Outline of documents flow of international trade transaction process in ASEAN
countries ................................................................................................................................... 30
Figure 4-3 Paths of documents flow in case of ASEAN countries........................................ 31
Figure 4-4 Outline of supporting system for international trade transaction .................... 32
Figure 4-5 Structure of international logistics ontology....................................................... 33
Figure 4-6 Structure of Organization class in international logistics ontology .............. 34
Figure 4-7 Structure of Person_in_Charge class in international logistics ontology ..... 35
Figure 4-8 Structure of Item class in international logistics ontology ............................... 35
Figure 4-9 Structure of Price class in international logistics ontology ............................. 36
Figure 4-10 Structure of Place class in international logistics ontology ........................... 36
Figure 4-11 Structure of Vehicle class in international logistics ontology ..................... 37
Figure 4-12 Structure of Date class in international logistics ontology ............................ 37
Figure 4-13 Structure of Referance_Number class in international logistics ontology .. 38
Figure 4-14 Procedure of the algorithm for optimizing information flow ........................... 39
Figure 4-15 Information flows of information a .................................................................... 40
Figure 4-16 Optimized flows of information a ....................................................................... 41
Figure 4-17 Procedure of the transitive closure .................................................................... 42
Figure 4-18 Adjacency matrix of optimized information flow .............................................. 42
Figure 4-19 Transitive closure of optimized information flow ............................................. 43
Figure 5-1 An example of information in commercial invoice document ............................ 45
Figure 5-2 An example of information in packing list document ........................................ 46
Figure 5-3 An example of information in bill of lading......................................................... 46
Figure 5-4 An example of information in forwarding instructions document .................... 46
Figure 5-5 Flows of documents in the case study ................................................................. 47
Figure 5-6 Optimized document flows ................................................................................... 54ix

Table of contents

Figure 5-7 An example of directed graphs ............................................................................. 54
Figure 5-8 Average number of packages a day ..................................................................... 55
Figure 5-9 Triangle distribution function of writing and recording task............................ 56
Figure 5-10 Conceptual of information flow among organizations ...................................... 57
Figure 5-11 Outline of actual information flow model ......................................................... 58
Figure 5-12 Outline optimized information flow model ....................................................... 59
Figure 5-13 Time of before and after optimizing information flow...................................... 60
Figure 5-14 Average waiting times of writing and recording task ...................................... 61
Figure 5-15 Average numbers of queues of writing and recording task ............................. 61
Figure 5-16 Time of before, after optimizing and modified information flow (1) ............... 62
Figure 5-17 Time of before, after optimizing and modified information flow (2) ............... 63
Figure 5-18 Time of before, after optimizing and modified information flow (3) ............... 63
Figure 5-19 Time of before, after optimizing and modified information flow (4) ............... 64
Figure 5-20 Time of before, after optimizing and modified information flow (5) ............... 64
Figure 5-21 Time of before, after optimizing and modified information flow (6) ............... 65
Figure 5-22 Time and number of staffs of before, after optimizing and modified information
flows (1) – (6) ............................................................................................................................ 65xTable of contents

LIST OF TABLES
Table 1-1 Structure of the thesis .............................................................................................. 5
Table 3-1 Relationship between research objectives and research methodology ............... 23𝛼
Table 4-1 A matrix 𝑚𝑖,𝑗which stands for flows of information α ........................................ 40
𝛼
Table 4-2 Matrix of information flow 𝑚𝑖,𝑗and 𝑚′𝛼𝑖,𝑗 after eliminating edge (1,4) and edge (2,3)................................................................................................................................................... 41
Table 5-1 A matrix which represents the current documents flows .................................... 48
Table 5-2 Current information matrix (Mi,jimport_company) and optimized information matrix(M'i,jimport_company) ....................................................................................................................... 49
Table 5-3 Current information matrix (Mi,jimport_address) and optimized information matrix(M'i,jimport_address) ........................................................................................................................ 49
Table 5-4 Current information matrix (Mi,jitem_amount) and optimized information matrix(M'i,jitem_amount) ........................................................................................................................... 50
Table 5-5 Current information matrix (Mi,jitem_ID no.) and optimized information matrix (M'i,jitem_ID no.) .................................................................................................................................... 50
Table 5-6 Current information matrix (Mi,jitem_size) and optimized information matrix (M'i,jitem_size) ....................................................................................................................................... 51
Table 5-7 Current information matrix (Mi,jtrailer_license plate no.) and optimized information
matrix (M'i,j trailer_license plate no.) .................................................................................................. 51
Table 5-8 A matrix which represents the optimized information flows (M'i,jα) .................. 52
Table 5-9 A matrix which represents the optimized document flows.................................. 53
Table 5-10 Comparing average number of sets of information between before and after
optimizing information flow.................................................................................................... 60
Table 5-11 Number of staffs in each case of modified information flows ............................ 62xi

Table of contentsxiiChapter 1

Chapter 1
INTRODUCTION
1.1 Background of study
The Associations of Southeast Asian Nations (ASEAN) was formed in 1967 with five nation
members: Indonesia, Malaysia, the Philippines, Singapore, and Thailand. Brunei
Darussalam (1984), Vietnam (1995), Laos (1997), Myanmar (1997) and Cambodia (1999)
joined the association. ASEAN was established to accelerate economic growth and promote
regional peace and stability, while enhancing cooperation on economic, social, cultural,technical, and educational matters. ASEAN is a largely organization with an economicallyand politically diverse membership. Since its founding, ASEAN has followed a slow stepby-step approach in changing regional cooperation in order to make it more legally binding
with institutionalized agreements. Figure 1-1 shows the history of ASEAN.

Figure 1-1 History of ASEAN
Source: European ASEAN Business Centre, 2012ASEAN has agreed to establish a regional economic integration, namely the Asian
Economic Community (AEC). The ASEAN was established to promote the ASEAN as asingle market and production base [1]. The main objective of the AEC is to transform
ASEAN into a region with free movement of goods, services, investment, skilled labor, andfree flow of capital. The physical connectivity has been developed by the AEC for enhancing
1Chapter 1

the movement of goods processes [2]. The AEC also is expected to reduce transportation
time among the ASEAN countries. In 2015, the ministry of transportation of Thailand haslaunched a project, the name is “The use of transportation traffic systems as a driving force
for the economic strength and the status of transport and traffic hub in the region” in orderto enhance transportation abilities of the target region [3]. In the project, some fieldworks
have been conducted on Route 12 Economic Corridor (R12), which is an ASEAN highway
network. R12 is the shortest international land route connecting Thailand, Lao PDR,
Vietnam and Guangxi, China [4]. Although it is the shortest route, the international tradetransaction processes on this route still require much time. As a result of the fieldworks, it
has become clear that procedure of passing border is one of bottlenecks in the international
trade transaction processes. The international trade transactions include complex
document flow processes because they have been designing ad-hoc ways. Additionally,
multiple languages used in the processes make the problem more complex. Due to thecomplex document flows, we have to describe similar information in different documents
repeatedly.
In the current situation of international trade transaction processes in the ASEAN,
logistics service providers are facing with the transportation delay time problem. In order
to transport some goods through the ASEAN countries, it takes eight days [5], one day fordomestic processes and seven days for preparing information and document which includes
waiting time in between each process. Transportation delays occur frequently because of
number of documents. These documents are required for declaring the goods in eachprocess of international trade transaction [6]. Each document includes many kinds ofinformation. Similar types of information are filled in different documents repeatedly that
effect on paperwork processes. These points make a complex paperwork in each process ofinternational trade transaction. For these reasons, it leads to high transportation cost in
an international trade transaction process. Such facts make the process of the international
trade transaction process worse. In order to reduce loads of the operators and their humanerrors, these processes should be optimized. An optimizing information flow algorithm has
been proposed for solving the problem of managing information flow among organizations.
The algorithm eliminates redundant information flows.

1.2 Goal
The main aim of the research is to propose a method for optimizing information flows
among organizations delivering in international trade transaction processes. Research’s
objectives are:
1.
2.
3.
4.

To investigate the information flows among organizations of international
trade transaction processes.
To review existing methods for modeling in information flows.
To propose a method for optimizing information flow in international tradetransaction processes.
To investigate effect of the proposed method in term of time reductions in thecase of international trade transaction processes in ASEAN countries.

2

Chapter 1

1.3 Scope
A scope area of this research is an international trade transaction process in the
Associations of Southeast Asian Nations (ASEAN). This study focuses on paperwork
processes among organizations who are involved in the trade processes of ASEAN countries
both of export side and import side. The ASEAN consists of Indonesia, Vietnam, Laos,
Brunei, Thailand, Myanmar, the Philippines, Cambodia, Singapore and Malaysia. The map
in Figure 1-2 shows the location of ASEAN country members.

Figure 1-2 ASEAN country members
Source: EU-Indonesia Business Network

1.4 Contributions
The main contribution of this study is a diagrammatic and mathematical modelling
technique for optimizing information flow among organizations in the international tradetransaction processes. In other to accomplish it, the research with carry out: (1) a surveying
the current situation of international trade processes in ASEAN countries, (2) a scientificexamination of the state-of-the-art in academic literature for techniques and tools formodelling information flow and (3) a study of international trade transaction practice inthe use of tools and techniques for modelling information flow and optimizing information
flow. Insights provided by the review and study will then serve as the basis for themodelling and optimizing technique.

3Chapter 1

1.5 Structure and outline of the thesis
This thesis consists of 6 chapters in which shown in Figure 1-3.
Chapter 1 [Introduction]: A main area of study is addressed in this chapter. I show
background and signification of the research problem. After a broad overview of thethesis has been given, objective of research related researches and researchmethodology have been described.
Chapter 2 [Background]: This chapter presents a comprehensive review of literature on
existing techniques for modelling information flow in organizations. The research
gap for delivery information flow modelling highlighted in academic literature is alsopresented. An overview of ontological engineering is described. In addition, an
overview of multi-agent simulation also is presented in this chapter.
Chapter 3 [Research Methodology]: In this chapter, specific procedures are shown. The
procedures have been used to analyze information flow in the international tradetransaction processes. I describe 3 main processes that consist of literature review
methodology, proposed technique methodology and simulation methodology.
Chapter 4 [Supporting System International for Trade Transaction]: The backbone of thisthesis is described here. This chapter proposes a technique for modelling information
flow among organizations in international trade transaction processes that consistsof an international trade transaction model, outline of the proposed system,
international logistics ontology, and an algorithm for optimizing information flows.
Chapter 5 [Experiments]: Experiments are described in this chapter. This chapter
describes case study for optimizing information flow. Simulation models of
information flow also are shown in this chapter for evaluate the effectiveness ofproposed algorithm.
Chapter 6 [Conclusions and Future Direction]: The study is concluded by summarizing themain outcome of the research and identifying possible directions for future research.

4

Chapter 1

Table 1-1 Structure of the thesis

5Chapter 1

6

Chapter 2

Chapter 2
BACKGROUND
2.1 Literature review
2.1.1

International trade transaction

International trade transactions evolved a customary and regulatory framework tofacilitate the smooth flow of cargo from exporters to importers. In order to carry out
international trade, organizations are required to follow a certain set of procedures anddeal with a wide range of documents. The exporter needs to comply with rules, regulations,and customs procedures of both the exporting and importing countries. An international
trade transaction chain consists of several organizations that form an integral part of theentire system. It includes number of government regulatory agencies in both exporting andimporting countries, such as government agencies under the ministry of trade, commerce,
inspection agencies, insurance companies, customs and central excise, banking
institutions, clearing and forwarding (C&F) agents, shipping companies or airlines,
carriers for inland transportation, etc. As exporters and importers are located in two
different countries. They are governed by different regulations that effect to complex
processes of international trade transactions.
International trade volumes
International trade can be broadly distinguished between trade in goods (merchandise) andservices. The bulk of international trade concerns physical goods, while services accountfor a much lower share. World trade in goods has increased dramatically over the last
decade, rising from about $10 trillion in 2005 to more than $18.5 trillion in 2014 to thenfall to about $16 trillion in 2016. Trade in services greatly increased between 2005 and2016 (from about $2.5 trillion to almost $5 trillion). The value of international trade of both
goods and services declined substantially in 2015 and 2016 [7]. The graph in Figure 2-1
shows trends of trade of goods and services in 2005-2016.

7

Chapter 2

Figure 2-1 Trade of Goods and Services, 2005-2016
Source: UNCTAD secretariat calculations based on COMTRADE data, 2018

Since 2005 the volume of international trade of goods has increased dramatically. However,growth has slowed down significantly in the last few years and virtually stalled in 2015.
Volume growth resumed in 2016 but on a subdue rate. During 2015 and 2016, volumes oftrade fell for many countries both in terms of imports and exports. The graph in Figure 22 shows the volumes of export and import goods in 2005-2015. The volume of international
trade in goods has increased dramatically in the last 10 years. In spite of the financial crisisof 2009, developing countries as a group have almost doubled the volumes of trade in goods
since 2009. While import volumes have been growing relatively more than export volumes
for developing countries, the opposite has happened in regard to developed countries. The
relatively larger increase in the volumes of imports can be explained by the increase in
consumer demand in developing countries. Growth in trade volumes has slowed down
substantially in the last few years, especially in regard to developing countries.

Figure 2-2 Volumes of trade in goods, 2005-2015
Source: UNCTAD secretariat calculations based on COMTRADE data, 2018

Figure 2-3 shows the trade network map. In order to illustrate the importance between andwithin regions during 2015-2016. The width of the corresponding lines reflects themagnitude of trade in 2016, whereas the size of the nodes reflects total trade for each of
the regions. The colors of both the lines and the nodes reflect percentage drops in the valueof trade between 2015 and 2016, darker colors indicating greater declines. Increases are ingreens. As of 2016, world trade continues to be largely concentrated in three main regions:North America, East Asia and Europe, with a large share of trade being intraregional. In
2016, trade declined in regard to most regions and bilateral trade flows. The value of trade8

Chapter 2

declined substantially more commodity in oil exporting regions as well as in sub-SaharanAfrica. The declines in international trade flows were relatively less severe for Europe.

Figure 2-3 Trade flows across regions and change during 2015-2016
Source: UNCTAD secretariat calculations based on COMTRADE data, 2018

International trade documentation
Trade documentation is considered a critical constituent of international sales as exporttransactions involve much complex documentation work. Trade documentation facilitatesinternational transactions, protecting interests of exporters and importers that are locatedin two different countries. The successful execution of an export order ensuring physicaldelivery of goods and remittance of sale proceeds is as important as procurement of anexport order and sourcing or production of goods for exports. An export manager should
carry out the documentation meticulously to avoid problems related to smooth flow of goods[8]. Certain documents are essential in international trade as a matter of “customs ofinternational trade” and conventions governing international commercial practices. Some
documents are required to fulfil the statutory requirements of both exporting andimporting countries, such as the export and import declaration, certificate of origin,packing list, pre-shipment inspections, customs requirements, etc.
Doing business [9] collects the data that includes time and cost of internationaltransportation, number of documents needed to trade internationally. The graph in Figure
2-4 shows number of documents of each region. From Figure 2-4, there are 4 types ofprocesses that are divided. In each process, many documents are required such as 22
documents are required for the pre-arrival process that is the average value of ASEAN
countries.

9Chapter 2

Average

Sub-Saharan Africa

Middle East and North America

EuropeLatin America and Caribbean

South Asia

Central Asia

East Asia and Pacific

OCECD high income
0

5

10

15

20

25

30

35

Number of documents
Inland transport to warehouse

Customs and inspections

Port handling

Pre-arrival documents

Figure 2-4 Number of international trade documentation in each region, 2016
Source: Doing business, 2016

The graph in Figure 2-5 shows time of export in ASEAN countries. There are 4 processes
in the graphs that are explained the time of each process. From the Figure 2-5, thedocument prepare process takes 9 days that is average value of the ASEAN countries. The
graph in Figure 2-6 shows time of import in ASEAN countries. From the Figure 2-6, thedocument prepare process takes 10 days that is average value of the ASEAN countries.
30

25

Time for export (days)

5

2

20
3
15

3

3

3
3

2

3
2

2
1

2

3
15

14
11

11

2

2
1

12
2
1
1
1

0

Document Preparation

Lao PDR

Malaysia Philippines Singapore

Customs Clearance

2

1

5
Cambodia Indonesia

3

3

8

Brunei

4

2

3

10

5

2

4

3

Port Handling98Thailand

VietnamInland Handling

Figure 2-5 Time for export in ASEAN countries, 2013
Source: Trade facilitation consultant for ASW, 201310

Average ASEAN

Chapter 2Time for Import (days)

30

25

3

20

5
4

2

3
15

2

1
2
1

3

2

10

4

1
7

15
5

11

1
4
7
4

0
Brunei

Cambodia Indonesia

Document Preparation

Lao PDR

3

4

2

3

2
1
1

2
2

1
2
1
1
1
1

Malaysia Philippines Singapore

Customs Clearance

Port Handling

4

2

4

2
Thailand

10

VietnamAverage ASEAN

Inland Handling

Figure 2-6 Time for import in ASEAN countries, 2013
Source: Trade facilitation consultant for ASW, 2013

2.1.2

Information and information flow for organization

The term “information” is used in four different ways: as a resource, as a commodity, as
perception of patterns, and as a constitutive force in society [10]. As a resource, information
is interpreted as content from knowledge that is described as data represented or
structured for meaning [11] [12]. As a commodity, information is highlighted from theperspective of businesses where the flow of information (usually computerized) is used astrans-organizational communication [13]. As a perception of pattern, information is viewed
as the reduction of uncertainty in a system [14]. This reduction of uncertainty is useful as
it saves organizational time and cost by minimizing alternate decisions that arise due touncertainty. As a constitutive force in society, information is viewed as a key element forshaping the structure and behavior of organizations [15]. In this context the flow of
information is used to determine the nature of expression and complexity of thetransmission structure of information among organizations in the international tradetransaction processes.
Information is important to the existence of organizations. In profit driven organizations
i.e., businesses, information is a critical factor that determines growth and prosperity [16].
Information flow is defined by the logic of a distributed system that is made up of agents.
It is also defined for the relationship in the distributed system [17]. Information flow isviewed as a one way process from a sender to a receiver [18]. There are many kinds ofinformation flow in organizations: person-to-person; person-to-machine and machine-tomachine, from sources such as electronic data interchange and face-to-face conversations,and through channels for communication such as letters, reports, audio files and video
recordings [19]. These channels offer the means for a company to communicate internallyand externally so as to achieve its business objectives such as the delivery of products andservices.

11

Chapter 2

Information flow is an important part of work flows [20] that requires a synergy between
humans and computer systems in modern organizations. Information flow is based on
information gathering by means of textual, audio, video and graphical media forms. These
media forms are used for communication within an organization or among organization[21]. The aim of these media is to describe processes and activities in a system.
There are many studies that focused on information flow. These studies have been
undertaken in science and engineering fields such as organizational theory, management
science, economics, artificial intelligence and computer science. In organizational theory
and management science, the researches have centered on the analysis of information flow.
It aims to enhance organizations to manage processes for capturing, storing and retrieving
information.
Nicholson [22] investigated the role of production information in the delivery of batch
manufactured products by five companies. The purpose of the study was to develop a design(process-flow grid) for information management. Nicholson also emphasized theimportance of effectively using computer scheduling systems and of applying trade-offs incapacity, total order intake and lead times.
Iskanius et al. [13] studied the transparency of information flow in the supply chains ofsteel companies in Northern Finland. They used the findings of their study to identify theelements of a new business design for supply chains. These elements include: customeralignment, collaboration, systematization, agility, scalability, fast-flow and digitalization.
Iskanius et al. also suggested agent-based technologies for managing this new supply chain
thinking. They argued that this will improve the flexibility of supply chains and overcome
problems of the bullwhip effect i.e. information distortion as it passes through the businessnetwork.
Boersma et al. [23] examined information flow for service delivery in the service and callcenters of a multi-national electronics company. Following interviews with call agents, theauthors made use of the Maturity Index on Reliability (MIR) [24] to propose two new
business models for enhancing information flow. The models centered on reducing
information losses, encouraging the use of knowledge databases and improving information
quality.
Pedroso and Nakano [25] studied the flow of technical information in the supply chain of
four pharmaceutical companies. Based on the findings of case studies at the companies, theauthors drew a distinction between order information (simple, upstream and timely) andtechnical information (rich, downstream and early). Pedroso and Nakano also suggested
that effective information flow management is dependent on effective logistic processes.
2.1.3

Modeling information flow

Modeling information flow is the process of describing how information is transferred pointto-point along communication channels in an organization and outside of the organizations.
Modeling information flow for organizations is motivated by the need to better understandhow to: organize and coordinate processes, eliminate redundant information flows andprocesses, minimize the duplication of information and manage the sharing of intra- andinter-organizational information [26]. It is also required to understand communication

12

Chapter 2

barriers among departments that results in sub-optimal and inflexible organizational
processes.
Becker et al. [27] have suggested that standard models (as-is models) that should be
identified to serve as a starting point for models of planned systems (to-be-models). This
sub-section presents, as a first step towards this approach, an analysis of some key
diagrammatic information flow models. Diagrammatical tools beyond the scope of
information flow, for example models for timeline orientation (UML sequence diagrams),
process orientation (flow chart diagrams) or state orientation (state transition diagrams),
are omitted.
The GRAI (Graphes à Résultats et Activités Interreliés) Engineering method wasdeveloped by GRAI Laboratory at the University of Bordeaux in the 1970s [28]. Figure 2-7
shows the GRAI Modeling Technique which is based on a hierarchical conceptual model(the GRAI model) for supporting decision-making processes during manufacturing andestablishing information flow for facilitating these decisions. The GRAI model is divided
into two parts: a macrostructure which displays the architecture of the overall systemarranged in a hierarchy and a microstructure for system components which are identified
in the macrostructure. The macrostructure of the GRAI model as shown in Figure 2-7a
decomposes the system to be designed into three sub-systems. The technological systempresents the means for delivering products and services such as people, machines andmaterials. It is also concerned with information flows associated with thesetangible/intangible offerings for meeting customer expectations. The decision system canbe elaborated in the hierarchy. This hierarchy is arranged according to decision-making
levels which contain blocks known as decision centers. The information system links thedecision and physical system and the enterprise environment. It also transforms andmemorizes information. The microstructure is concerned with decision centers in terms of
their intelligence based on recognizing the need for a decision to be made, their modelingcapabilities of derived or gathered information, and their choice for selecting appropriate
solutions based on criteria, constraints and context. Two main diagrammatical tools areused in the GRAI model: GRAI grids and GRAI nets. Relationships are used in GRAI
models to specifically describe information flow and decision flow for co-ordination andsynchronization of activities in an organization or system. Relationships are depicted
diagrammatically as arrowed lines as shown in Figure 2-7b. Decision flow between two
decision centers can be represented as large, emboldened lines, while information flow canbe depicted as small dashed lines. GRAI nets are developed after GRAI grids to describe
the activities in a decision center [29]. The GRAI nets, as shown in Figure 2-7c, are madeup of three constructs: states, activity and supports. States are represented by circles orovals. Activities are represented as directed arrows, while the supports (information andtechnological resources) are represented as rectangles.
Petri nets (PNs) or place-transition nets were first proposed by Carl Adam Petri in 1962
for modeling processes in an event-driven system [30]. This system exhibits a wide rangeof characteristics such as non-determinism, concurrency, synchronicity as well as
distributed and/or parallel features. PNs can also be used for representing the information
flow in development and simulation of automated manufacturing systems [31].
Diagrammatically, PNs can be used to methodically describe and communicate ideas
among designers and implementers. A PN is depicted as a directed, weighted, bipartite
graph made up of four main symbols as shown in Figure 2-8. Black dots represent tokens.
Tokens may be resources, counters, metrics or attributes. Circles show places and aremarked with a non-negative integer k of token. Bars depict transitions, while arcs connect13

Chapter 2places to transitions. In the modeling of PNs, transitions represent events in a system,
while places illustrate conditions for occurrence. The tokens provide the premise for theconditions just as input and output places offer pre- and post-conditions for the event
respectively.

Figure 2-7 Graphes à Résultats et Activités Interreliés (GRAI) Modeling Technique

14

Chapter 2

Figure 2-8 Petri net representations and constructs: a) Sequential execution;b) Concurrency; c) Synchronization; d) Merging; e) Conflict; and f) Confusion
Approaches for mathematically modeling information flow in organizations can beclassified according to two main categories: flow analysis that propose quantities andinformation levels for assessing and improving organizational performance andorganizational analysis that idealize organizations as different constructs for improving
information flow.
Datta and Chaudhuri [32] concentrated on serial and parallel information flow in operation
inventory systems for manufacturing organizations. The term “operation inventory
system” was used by Datta and Chaudhuri to describe a chain of manufacturing operations
separated by inventories under periodic review of base stock systems of ordering. Theydeveloped a mathematical model for deciding on the optimum mix for operations that
achieve the greatest efficiency.
Four information flow parameters suggested by Krovi et al. [16] offer useful quantities forassessing the level of performance of an organization. Information node density, the firstparameter, deals with the complexity of information flow and is computed as the numberof intermediate nodes that are present in an information processing channel. Information
velocity is the second parameter and deals with the rate at which information is received
at a node. Information viscosity, the third information flow parameter, is concerned withthe level of conflict at a node i.e. the presence of contradictory information. The fourthparameter, information volatility describes uncertainty in the content, format or timing of
information.
Aoyama et al. [33] modelled information (and commodity) flow in organizations withindependent but linked sub-networks. They focused on logistics networks that incorporate
methodologies for just-in-time manufacturing and inter-period network storage. These
logistics networks in modern businesses incorporate web technologies (particularly the15Chapter 2internet) in e-logistics for overcoming factors such as language barriers, and time zone andspatial constraints. Aoyama et al. studied the characteristics of logistics in geographic/
virtual spaces and concluded that intermediaries (such as middlemen) can still be
important elements in the logistics industry.
Helbing et al. [34] modelled side-links in organizations made up of multiple agents withcomplex non-linear interactions. The model much like the one proposed by Creti [35]proposed side-links for information flows. But unlike Creti, the model focused onhierarchical, regular area-filling kinds of organizational subdivisions according to
triangular, quadratic and hexagonal configurations. Helbing et al. demonstrated how
short-cuts and temporary links in hierarchical organizations can contribute to efficient andeffective information flow during crisis or disaster response management.
Costa et al. [36] developed a mathematical model of information for complex networks madeup of human-made structures. The model analyses trails left by information flow for
identifying contamination sources, strategies for immunization and optimal routing paths.
Caldwell [37] developed a feedback control model that analyses the delay between the time
information is sent from a source and received at a destination. The model introduces atask time quantity for assessing the use of information and communication technologies(ICTs) for supporting human-human communication and for improving task coordination.
A complex network can be described as a graph G = (V, E) containing a set of vertices V(called nodes or points) that are associated by edges E (called links or lines) [38] as shownin Figure 2-9. The vertices represent entities within a network whereas edges indicate
interactions based on relationships in which the entire graph is connected (i.e. for a vertex
i in the graph, there is a path made up of edges to another vertex j) or disconnected. A
complex network can contain a subgraph (G') = (V', E') – a subset of G where V' and E' aresubsets of V and E respectively. In Figure 2-9, subgraphs can be created between sets ofvertices (A, B, C, D), (A, D, G), (B, C, D, F) and so on. Vertices, edges and topology (thatdepicts how vertices and edges are arranged) are the main concepts used to characterize
information structures for analyzing domains such as the World Wide Web, social
networks, brain networks and genetic networks. Within complex network research, social
network analysis (SNA) is the main approach adopted by researchers to study andunderstand relationships, social roles and social structure in organizations [39], [40], [41]and [42].

Figure 2-9 A complex network as a graph

16Chapter 2

2.2 Ontological engineering
Ontological engineering aims to describe knowledges in a domain, provide and share
understanding to conceptual knowledge, define common vocabulary and give clear
definition to relationships [43]. An ontology is a formal explicit description of concepts in adomain of discourse (classes (sometimes called concepts)), properties of each concept
describing various features and attributes of the concept (slots (sometimes called roles orproperties)), and restrictions on slots (facets (sometimes called role restrictions)). An
ontology together with a set of individual instances of classes constitutes a knowledge base.
In reality, there is a fine line where the ontology ends and the knowledge base begins [44].
Gruber [45] proposed to model ontologies using frames and first order logic. He identified
five kinds of components: classes, relations, functions, formal axioms and instances. In thissection we present such components with an example in the traveling domain.
Classes represent concepts, which are taken in a broad sense. For instance, in the travelingdomain, concepts are: locations (cities, villages, etc.), lodgings (hotels, camping, etc.) andmeans of transport (planes, trains, cars, ferries, motorbikes and ships). Classes in the
ontology are usually organized in taxonomies through which
inheritance mechanisms can be applied. We can represent a taxonomy of entertainment
places (theater, cinema, concert, etc.) or travel packages (economy travel, business travel,etc.).
Relations represent a type of association between concepts of the domain. They are formallydefined as any subset of a product of n sets, that is: R ⊂ C1 x C2 x ... x Cn. Ontologies
usually contain binary relations. The first argument is known as the domain of the relation,and the second argument is the range. For instance, thebinary relation Subclass-Of is used for building the class taxonomy. Examples ofclassifications are: A Four-Star-Hotel is a subclass of a Hotel, a Hotel is a subclass ofa Lodging, and a Flight is a subclass of Travel, which is identified by theflightNumber. Binary relations are sometimes used to express concept attributes (akaslots). Attributes are usually distinguished from relations because their range is adatatype, such as string, number, etc., while the range of relations is a concept. The
following code defines the attribute flightNumber, which is a string.
Functions are a special case of relations in which the n-th element of the relation is unique
for the n-1 preceding elements. This is usually expressed as: F: C1 x C2 x ...x Cn-1 → Cn. An
example of a function is Pays, which obtains the price of a room after applying a discount.
Instances are used to represent elements or individuals in an ontology. An example ofinstance of the concept AA7462 is the flight AA7462 that arrives at Seattle on February 8,
2002 and costs 300 (US Dollars, Euros, or any other currency).
Introducing Ontological technology into logistic field is just beginning, but some interesting
result have reported. One of the main goals of logistics ontologies is supporting optimized
information utilization, e.g. time managements, truck location controls, quality controls,
etc.

17

Chapter 2

Andreas and Julia [46] have proposed logistics ontologies to annotate logistics services
semantically. Their ontologies are modularly organized and covers the overall concepts of
the logistics domain. The logistics ontologies include the elements for describing bothdeclarative and procedural aspects. The ontologies model consists of three layers, (1) alogistics semantic layer, (2) a logistics service description layer, and (3) a logistics processdescription layer. With the ontologies, terms in logistics service are defined clearly.
Ontological technique has been also applied in food industry. MEat Supply Chain Ontology(MESCO), which is an ontology model for traceability in meat supply chains, has been
proposed by Pizzuti et al. [47]. Important concepts of meat supply chains are defined in
MESCO, such as activity, food product, service product, lot and process. The main featuresof MESCO are providing definitions of keyword of all activities which is using for tracingfrom the farmer to the final consumer. The MESCO allows users to illustrate all knowledge
and information, which related to the meat traceability domain with unified notification.
Moreover, the MESCO enables interoperability among different systems and allows for
integrating heterogeneous databases used by each actor involved in the supply chains. The
main advantages in using MESCO is providing platform for obtaining essential data,
fundamental in case of occurring sudden diseases of foods.
Seedah et al. [48] proposed a standardized knowledge representation method of freightdata sources using ontological technology. The method makes knowledge understandablefrom both of computer systems and humans. The ontology was developed by using the role
based classification schema (RBCS) that organizes and classifies data elements. The freightdata ontology was developed to resolve users’ misunderstanding among different freightdatabases and support the users to identify a proper data. By using their ontologies, we
can use multiple freight data seamless because the semantic gaps are eliminated. Besides,
it can identify similar data elements across different data sources, which is same principlewith data mining.
Hozo – Ontology Editor 1 has been used to describe the classes of international logistics
ontology that will be described in Chapter 4, Section 4.3. Hozo is a tool for building
ontologies in a distributed environment. Among many existing ontology building tools, themain characteristics of Hozo are summarized as follows:
•

•
•
•
•

Unlike OWL, its conceptual level is closer to that of humans. OWL is a lowlevel language which is good for an interlingua for ontology exchange. If one
uses it as an ontology representation language directly, it would degrade user’s
understanding of ontology by restricting their idea to semanticnetwork/description-logics levels which are inappropriate for understanding
ontology.
Its representation scheme is based on the frame structure
It helps users build ontologies with Roles in a natural way supported by theadvanced theory of Roles.
It is easy to represent a nested structure of slots. That is, any slot can have its
own slots.
Inheritance information is explicit and is always accessible. Two ways ofinheritance: one from super classes through is-a link and the other from classconstraint
1 http://www.hozo.jp/

18Chapter 2

•
•
•
•

A friendly Graphical User Interface (GUI) is available.
Version management is available with a useful function for displaying changes.
Ontology building in a distributed environment over internet is supported.
Application programming interfaces (APIs) are available for accessing
ontologies and instances.

An ontology editor in Hozo provides users with a graphical interface, through which we canbrowse and modify ontologies by simple mouse operations. Its interface mainly consists ofthe following 3 panels as shown in Figure 4-6: navigation panel, definition panel andbrowsing panel. The last two panels are located centrally in this tool. They display thedefinition of the concept that is selected in the is-a hierarchy browser and allows users toedit it. It is composed of a browsing panel and a definition panel.
The browsing panel shows an ontology and users edit it mainly on this panel. It has two
display modes. One displays it graphically by using nodes and links. Each node represents
a whole-concept or a relation-concept which has slots representing its part-concepts orparticipant-concepts by such a manner that is shown in Figure 4-7 (a). A diagram of a partconcept is composed of three parts. Each of them represents 1) a role-concept, 2) a classconstraint, and 3) a role holder. A symbol besides a link connecting a whole-concept and apart-concept denotes kinds of relation (“p/o” denotes part-of relation, “p/i” denotes
participant-in relation and “a/o” denotes attribute-of) and a numeral represents the numberof part-concepts (or attributes). Fig.4-7 (b) shows a person, who is referred in the classconstraint, plays “a teacher role”, and the wheel becomes a role holder “a teacher”. The
other mode displays an ontology under editing in RDF(s).

Figure 2-10 A snapshot of Ontology Editor

19

Chapter 2

Figure 2-11 A legend of part-of relation

2.3 Multi-agent simulation
Simulation is a powerful tool for modeling, planning and controlling complicatedoperational systems [49]. The simulation has been used in various purposes: identifying
bottlenecks; studying system behaviors; forecasting future events; testing new designs for
system. Particularly, many researchers have employed discrete event simulation model forprocess analysis and improvement.
Vaghefi and Sarhangian [50] have proposed the mathematical model for optimizing
inspection costs of the multistage manufacturing system. Simulation experiments wereconducted to examine the effects of several parameters. ARENA simulation software was
employed for determining the optimal inspection plan.
Hsu et al. [51] explored the customs clearance processes of import goods in Taiwan.
Customs clearance network model in the import processes have been constructed foranalyzing the delay time of customs clearance processes. Then, the customs clearance
processes have been reconstructed by using the application of Radio Frequency
Identification (RFID). The simulation models were conducted for comparing the delay timeof the reconstructed customs clearance processes with the current customs clearance
processes.
Opasanon and Kitthamkesorn [52] have proposed a framework of system for modern
customs and cross-border transportation. The proposed framework aims to design
infrastructures and facilities of the Sadao customs for serving the freight flows between
Thailand and Malaysia. The simulation models have been constructed to justify various
operations and designs of border-crossing facilities: immigration control booths; vehicle
inspection station; truck clearance area.
Haughton and Michael [53] conducted the simulation model of truck schedules for bordercrossing between Canada and the United States. The ARENA simulation software has been
employed to analyze the current truck schedules, evaluate alternatives of the truck
processing capacity at border crossings. Based on the studies that are mentioned, thesimulation model becomes a practical for new system design and operation in various
border crossing problem.

20

Chapter 2

In this thesis, simulation models are developed through ARENA simulation software
version 15.12 to determine the current information flow and the optimized information flow
among organizations in international trade processes. The ARENA is a discrete event
simulation software, based on the process-oriented simulation scheme, in which travelers
are represented by entities flowing through the system.
Discrete-event simulation is an important tool for the modeling of complex system. It is
used to represent manufacturing, transportation, and service system in a computer
program for the purpose of performing experiments. Representation of the system via
computer program enable the testing of engineering design changes without disruption to
the system being modeled. Simulation modeling involves elements of system modeling,
computer programming, probability and statistics, and engineering design. A key
advantage of simulation modeling is its capability of modeling entire systems and complex
interrelationships. The representational power of simulation provides the flexible modelingthat is required for capturing complex processes. As the result, all important interactions
among components of the system can be accounted for within the model. The modeling ofthese interactions is inherent in simulation modeling because simulation imitates the
behavior of the real system. The ARENA is predicted on the modeling the process flow of“entities” through a system. The prediction of future behavior of the system is then archived
by monitoring the behavior of various modeling scenarios as a function of simulated time.
The main purpose of simulation model is to allow observations about a particular system
to be collected as a function of time. Figure 2-12 illustrates the fact that system is embedded
within an environment, and that typically a system requires input and produces output
using internal components.

Figure 2-12 Conceptualization of a simulation model

2 www.arenasimulation.com

21Chapter 2

22

Chapter 3

Chapter 3
RESEARCH METHODOLOGY
There are 3 phases of the research methodology. These phases are: literature review;proposed method for optimizing information flows and case studies. The researchmethodology is used in the research phases to fulfil the research objectives as summarizedin Table 3-1.
Table 3-1 Relationship between research objectives and research methodology
Objective

Methodology(1) To investigate the information flows amongorganizations of international trade transaction
processes.

Literature review methodology(2) To review existing methods for modeling in
information flows.
(3) To propose a method for optimizing information
flow in international trade transaction processes.

Proposed method methodology(4) To evaluate the proposed method by using
simulation models in the case of international tradetransaction processes in ASEAN countries.

Simulation methodology

3.1 Literature review methodology
To achieve objective (1) and (2), existing method for modeling information flow in an
organization and outside of the organizations are reviewed. The information flows amongorganizations of international trade transaction processes are also investigated. A review
of academic literature was carried out through a 3-stage analytical process: plan, sourceand study.
In the first stage, a plan was drawn up in which the aim, motivation and focus for theliterature review were defined. This also included questions which the review would seek
to answer as well as the initial or planned structure for the review. For the second stage,
academic publications (books, journal articles, conference proceedings, report and othermaterials) were selected using an online database for literature. The third stage involved
studying the publications and re-examining the sources from stage two. The literature
review plan drawn up in the first stage was also reconsidered during this stage.

23

Chapter 3

3.2 Proposed technique methodology
To accomplish objective (3), a framework of supporting system for international tradetransaction is proposed. The system can generate an optimized process of paperwork froma complex process of international trade transaction. First, an international logistics
ontology, which has been developed for describing the international trade transaction
model is shown. Then an algorithm for optimizing information flow has been proposed.

3.3 Simulation methodology
To accomplish objective (3), a framework of supporting system for international tradetransaction is proposed. The system can generate an optimized process of paperwork froma complex process of international trade transaction. First, an international logistics
ontology, which has been developed for describing the international trade transaction
model is shown. Then an algorithm for optimizing information flow has been proposed.
1.
2.
3.
4.
5.
6.

Define the problem
Establish measures of performance for evaluation
Generate alternative solutions
Rank alternative solutions
Evaluate and iterate as necessary
Execute and evaluate the solution

The first step in the DEDREE methodology [54] helps to ensure that problem is right. The
second step helps to ensure that the problem is solved for the right reason; that is metrics
must be coherent with the problem. The next 2 steps ensure that evaluate the multiple
solutions to the problem. In other words, these steps help to ensure that the right solution
is developed to the problem. In step 5, the process is evaluated by proceeding and allows
for iteration. Although an important concept, iteration is new to many modelers. Iteration
recognizes that the problem-solving process can be repeated until the desired degree ofmodeling fidelity has been achieved. Start the modeling at a level that allows it to be
initiated and do not try to address the entire situation in each of the steps. Start with small
model that work and build them up until we reached our desired goal. It is important to
set start and get something established at each step, and then continually repeats the steps
until the model is representing reality in the way that we intended. The final step is often
overlooked. Simulation is often used to recommend a solution to a problem. This step
indicates that if we have the opportunity, we should execute the solution by implementing
the decision. Finally, we should always follow up to ensure that the projected benefits ofthe solution were obtained.
The DEGREE problem-solving methodology should serve us well. However, simulation
involves certain unique actions that must be performed during the general overall problemsolving process. When applying DEGREE to a problem that may require simulation, thegeneral DEGREE approach needs to be modified to explicitly consider how simulation willinteract with the overall problem-solving process. Figure 3-1 represents a refined general
methodology for applying simulation to problem-solving.

24

Chapter 3

Figure 3-1 General simulation methodology

25

Chapter 3

The first phase, problem formulation, captures the essence of the first two steps in the in
the DEGREE process. The second phase, model building, captures the essence of step 3 ofthe DEGREE process. When building model, we are either explicitly or implicitly
developing certain design alternatives. The third phase, experimental design and analysis,
encapsulates some of step 3 and 4 of the DEGREE process. In designing experiments,
design alternatives are specified, and when analyzing experiments their worth is being
evaluated with respect to problem objectives. The fourth phase, evaluate and iterate,
captures the notion of iteration. Finally, the fifth and sixth phases, documentation andimplementation, complete the simulation process. Documentation is essential to ensure theongoing and future use of simulation model. Implementation recognizes that simulation
projects often fail in the absence of follow-through on recommended solutions.
The problem formulation phase of the study consists of five primary activities.
1.
Defining the problem
2.
Defining the system
3.
Establishing performance metrics
4.
Building conceptual models
5.
Documenting modeling assumptions
A problem starts with a perceived need. These activities are useful in developing anappreciation for and an understanding of the problem requirements. The basic output ofthe problem definition activity is a problem definition statement. A problem definition
statement is narrative discussion of the problem. A problem definition statement isnecessary to accurately and concisely represent the problem stakeholders. The problem
definition statement should include all required assumptions so that we can examine theireffect on the model during the verification, validation, and experimental analysis steps ofthe methodology. A well- written problem definition statement ensures that the problem iswell understood and that all parties agree on the nature of the problem and the goal of
study.
The general goals of simulation study often include:•
Comparison of system alternatives and their performance measures acrossvarious factors (decision variables) with respect to some objectives.
•
Optimization, a special case of comparison in which are tried to find the system
configuration that optimizes performance subject to constraints.
•
Prediction of system behavior at some future point in time.
•
Investigation to learn about and gain insight into behavior of the system given
various inputs.
These general goals will need to be specialized to the problem under study. The problem
definition should include a detail description of the objectives of the study, the desired
output from the model, and the type of scenarios to be examined or decisions to be made.
The second activity of this phase produce a definition of the system. A system definition
statement is necessary to accurately and concisely define the system, particularly its
boundaries. The system definition statement is narrative and of ten contains a pictorial
representation of the major elements of the system. This ensure that the simulation study
is focused on appropriate areas of interest to stakeholders and that the scope of the projectis well understood.

26

Chapter 3

When defining the problem and the system, one should naturally begin to develop anunderstanding of how to measure system performance. The third activity of the problem
formulation makes this explicit by encouraging to define the required performancemeasures for the model. To meaningfully compare alternative scenarios, objective andmeasurable metrics describing the performance of the system are necessary. The
performance metrics should include quantitative statistical measures from any models
used in the analysis (e.g., simulation mode), quantitative measures from the systems
analysis, (e.g., cost/benefits), and qualitative assessments (e.g., technical feasibility, humanoperational feasibility). The focus should be placed on the performance measures that areconsidered to be the most important to system decision makers and tied directly to theobjective and unbiased manner to determine which system scenario performs the best
according to decision maker preferences.

The simulation models used to evaluate the alternative solutions are then developed,
verified, and prepared for analysis. Within the context of a simulation project this processincludes:Input data preparation: Input data is analyzed to determine the nature of data anddetermine future data collection needs. Necessary data are also classified by area. This
classification establishes the different aspects of the model that are used in model
development.
Model translation: The act of implementing the model in computer code, including timing
and general procedures and the translation of the conceptual models into computer
simulation program representations.
Verification: Verification of the computer simulation model is performed to determine
whether the program perform as intended. Verification consists of model debugging tolocate any errors in the simulation code. Errors of particular importance include improper
flow control or entity creation, failure to release resources, and logical/arithmetic errors orincorrectly observed statistics. Model debugging also include scenario repetition using
identical random number seeds, “stressing” the model through a sensitively analysis toensure compliance with anticipated behavior, and testing of individual modules in thesimulation code.
Validation: Validation of simulation model is performed to determine whether thesimulation model adequately represents the real system. The simulation model is shownto personnel associated with the system in question. Their input concerning model realism
is critical in establishing the validity of the simulation. I addition, further observations ofsystem are performed to ensure model validity with respect to actual system performance.
A simple technique is to statistically compare the output of simulation model to the outputof the real system and to analyze whether there is significant different between two.

27

Chapter 328

Chapter 4

Chapter 4
SUPPORTING SYSTEM FOR
INTERNATIONAL TRADE
TRANSACTION
4.1 International trade transaction model
In international trade transaction processes, many kinds of information are transmitted
for carrying out the office procedures. This information is transmitted by using several
ways, e.g. paper documents, forms on the internet system, etc. [55]. In addition, eachcountry has its own formats and they are expressed by the local languages. Thus,
transmitting processes can be grasped from the three different aspects, i.e. document flows,
and information flows, and notifications. Based on the above discussion, the author has
proposed a representation model of international trade transaction processes. Figure 4-1
illustrates the proposed model.

Figure 4-1 International trade transaction Model
29

Chapter 4This model consists of three layers, Document flow layer, Information flow layer, andPresentation layer. The details of each layer are shown below:•••

Information flow layer: On this layer, information flows of international tradetransactions are represented.
Document flows layer: On this layer, flows of documents in international tradetransaction processes are represented. Both of paper and electronic document
flows are shown on this layer. Each document on this layer can be considered
as a set of information on the Information layer.
Presentation layer or interface layer: On this layer, linguistic labels of
information are represented. Each information on the information layer isconnected with the labels, which are represented by several different
languages.

The results of surveying the current documents flow in the international trade transaction
processes in ASEAN countries, there are many documents that are required amongorganizations in both of export and import country side. Figure 4-2 shows a diagram oftypical document flow of international trade transaction procedure. These document flows
can be abstracted as information flows by using the proposed classes as described in section
4.2. This type of knowledge is described on the information flow layer shown in Figure 4-1
and Figure 4-2. The paths of each document flow have been explored as shown in Figure 43.

Figure 4-2 Outline of documents flow of international trade transaction process in
ASEAN countries

30

Chapter 4

Figure 4-3 Paths of documents flow in case of ASEAN countries

31

Chapter 4

4.2 Outline of supporting system for international tradetransaction
Figure 4-4 shows the outline of the supporting system. This system consists of three
procedures, (1) Convert (document flows → information flows), (2) Optimize information
flows, and (3) Convert (information flows → document flows). The procedures of optimizing
document flows are shown below:
1.
2.
3.

Current document flows are converted to current information flows.
The current information flows are optimized by using the proposed algorithm
for optimizing information flows.
From the optimized information flows, new document flows are generated.

Figure 4-4 Outline of supporting system for international trade transaction

4.3 International logistics ontology
An ontology of international trade transaction domain, which called international logistics
ontology, has been developed to represent the proposed model. It has been created inaccordance with the results of surveying documents which were used in international tradetransaction processes. To design the ontology, two approaches were adopted: top-down andbottom-up [56].
A top-down approach was used to define the most general concepts in common
international trade transaction environments. Organization, Item, Vehicle, Place andPrice were defined as sub-concepts of the top concept because they are the essential
concepts of the logistics processes. A bottom-up approach was used to define the definitionof the most specific classes based on each item on the documents. As a result, classes of
Person_in_Charge, Date and Reference_Number have been defined in the ontology.

32

Chapter 4

Figure 4-5 Structure of international logistics ontology
Figure 4-5 shows the structure of the ontology. There are eight sub-concepts under the top
concept of “any.” The details of each sub-concept are shown below:
Organization: An instance of the class stands for an actor in the international tradetransactions. The class of Organization denotes roles of groups or participants in theprocesses [57].

33

Chapter 4

Item: An instance of the class stands for a product that is transported from an original
country to a destination country.
Vehicle: An instance of the class stands for a vehicle that is used for carrying products.
Place: An instance of the class stands for a location in a country.
Price: An instance of the class stands for financial information such as values andcurrency types.
Person_in_Charge: An instance of the class stands for a responsible man. This class isused for determining a person who plays a role in an organization.
Date: An instance of the class stands for a date in the documents such as departure dateand registration date.
Reference_Number: An instance of the class stands for a reference number in the
documents, for example, an invoice number, a purchase order number.
From description of the Hozo ontology editor that is mentioned in Chapter 2, Section 2.2,
properties of all classes in the international logistics ontology have been identified. Figure
4-8 to 4-15 show detail of each class.

Figure 4-6 Structure of Organization class in international logistics ontology

34

Chapter 4

Figure 4-7 Structure of Person_in_Charge class in international logistics ontology

Figure 4-8 Structure of Item class in international logistics ontology

35

Chapter 4

Figure 4-9 Structure of Price class in international logistics ontology

Figure 4-10 Structure of Place class in international logistics ontology

36Chapter 4

Figure 4-11 Structure of Vehicle class in international logistics ontology

Figure 4-12 Structure of Date class in international logistics ontology

37

Chapter 4

Figure 4-13 Structure of Referance_Number class in international logistics ontology

4.4 Algorithm for optimizing information flows
In this section, the proposed algorithm for optimizing information flows is shown. Thisalgorithm is used in the information flow on the information layer that presented in Figure
4-2. The procedures shown in Figure 4-14 represents the proposed algorithm. In this𝛼algorithm; 𝑀𝑖,𝑗
is a matrix, which stands for flow of information α from source i todestination j, and n stands for number of rows or columns of matrix. Each row of the matrix𝛼𝑀𝑖,𝑗stands for a source node of the information, and each column stands for the destination
node of the information. Thus, when an information α is transmitted from source i to𝛼
destination j, the value of 𝑀𝑖,𝑗
is 1, otherwise 0.

38

Chapter 4

Figure 4-14 Procedure of the algorithm for optimizing information flow

39

Chapter 4

Redundancy of information flows among organizations are considered in this algorithm. To
reduce the redundancy of information flow, repeated information flows are eliminated. For
example, flows of information α shown in Figure 4-15. They can be optimized as shown in
Figure 4-16 by using the algorithm.

Figure 4-15 Information flows of information α
Table 4-1 A matrix 𝑴𝜶𝒊,𝒋 which stands for flows of information α
SourceDestination
2
3
1
1
X
1
X

1
X

1
2
3
4
Sum

0

1

2

4
1
1
X
2

Sum
3
2
0
0
X

The pseudo-code of the proposed algorithm in Figure 4-14 can be summarized as:𝛼
Step 1: Matrix table 𝐴 = [𝑚𝑖,𝑗]𝑚∗𝑛

is generated from the graph as shown in Table 4-1. In

Table 4-1, the last rows and the last columns represent summation of each row
and column.
𝛼Step 2: Matrix table 𝐴′ = [𝑚𝑖,𝑗]is generated as an empty matrix table for marking𝑚∗𝑛visited 𝑚𝑖,𝑗 .
Step 3: Summation of all number in lines is calculated for each row.
Step 4: Summation of all number in rows is calculated for each sum of each column.
Step 5: If for all col_max is greater than 1, the following steps are executed. In this case,
it is 2 and the following steps are executed.
Step 6: Find a column which has largest number of summation and it is substituted for i,i.e. 1 is substituted for i.
Step 7: Find a row which has largest number of summation and it is substituted for j. In
Table 4-1, the largest number is column no. 3 and 4.
Step 8: If numbers of col_max are coincided, go to step 9, otherwise select that column for
col_max.
Step 9: Select a column that has highest index of column number. In this case, column no.
4 is selected for j.
𝑎𝛼Step 10: Value of 𝑚′1,4 in 𝐴′ = [𝑚𝑖,𝑗]is checked.
𝛼𝑚∗𝑛Step 11: If 𝑚′1,4=1, go to step 12, otherwise go to step 14.
Step 12: Find a column which has second largest value of summation and it is substituted
for i.

40

Chapter 4

Step 13: Find a row which has second largest value of summation and it is substituted forj.
𝛼Step 14: 𝑚1,4
is checked the condition of disconnection by calculating a transitive closure of𝐺𝐺
𝐴 = [𝑚𝑖,𝑗]that is described in Figure 4-17.
𝑚∗𝑛𝐺
Step 15: If summation of all number in columns of 𝐴𝐺 = [𝑚𝑖,𝑗]is greater than or equal to𝑚∗𝑛𝛼summation of all number in columns of 𝐴 = [𝑚𝑖,𝑗], go to step 16, otherwise go
𝑚∗𝑛
𝑛−1 𝐺
𝑛−1 𝛼
to step 13. In this case ∑𝑖=0 𝑚𝑖,𝑗 greater than ∑𝑖=0 𝑚𝑖,𝑗 .
𝛼Step 16: 0 is substituted for 𝑚1,4
. Notification of “1” in Table 4-2 stands for the 1 changed

to 0. As the results, the matrix is changed as shown in Table 4-2.
𝛼𝛼Step 17: 𝑚′ 𝑖,𝑗 = 1 is put in 𝐴′ = [𝑚′ 𝑖,𝑗 ]𝑚∗𝑛 .

Step 18: Summation of all column is calculated again.
Step 19: If for all summation of column is greater than or equal to 1, go to step 4, otherwise
𝛼stop to find 𝑚𝑖,𝑗to be eliminated.
𝜶

Table 4-2 Matrix of information flow 𝒎𝜶𝒊,𝒋 and 𝒎′ 𝒊,𝒋after eliminating edge (1,4) and edge (2,3)
𝛼

𝛼
𝑚𝑖,𝑗

Source1𝑚′ 𝑖,𝑗Destination

Source

1

2

3

4

X

1

1

1

2

1

X

1

1

1

2

0

3

X

0

4

1

X

Sum

2
3

X

4
Sum

Sum

0

1

1

Destination
1

2

3

4

X

0
X

0
X

0

Sum

0

0

0
X

0

0

X

Finally, we can get an information flow shown in Figure 4-16 as a graph.

Figure 4-16 Optimized flows of information a
Due to a removal of some information flows, reachable information for each node has toconfirm. A transitive closure relation is used for investigating reachability of informationfor each node or disconnection of information flows. The transitive closure can be thoughtof as establishing a data structure that makes it possible to solve reachability questions(can I get to x from y?) efficiently. After the preprocessing of constructing the transitive
closure, all reachability queries can be answered in constant time by simply reporting amatrix entry. Transitive closure is fundamental in propagating the consequences ofmodified attributes of a graph G [58].
In this thesis, the transitive closure of a directed graph G= (V, E) is a directed graph
G+ = (V, E+) such that for ∀< 𝑢, 𝑣 > ∈ 𝐸 + if and only if there exists a non-null path from u
to v. The n-step transitive closure of a directed graph G = (V, E) is a directed graph
41

Chapter 4

Gn = (V, En) such that for ∀< 𝑢, 𝑣 > ∈ 𝐸 𝑛 if and only if there exists a non-null path from u
to v and the length of the path is less than or equals to n. Figure 4-16 shows a graph of
optimized flows of information α. A graph of optimized information flow G = (V, E) can be
represented by an m×n adjacency matrix 𝐴 = [𝑚𝑖𝑗 ] , where;
𝑛×𝑛

(4-1)
The procedures shown below represent the transitive closure:

Figure 4-17 Procedure of the transitive closure
The graph of optimized information flow, its adjacency matrix is shown in Figure 4-18. The
adjacent matrix representations for its transitive closure and its transitive closure aredisplayed in Figure 4-19.

Figure 4-18 Adjacency matrix of optimized information flow

42

Chapter 4

Figure 4-19 Transitive closure of optimized information flow
From the results of transitive closure, information a can be reached from original source toall of nodes.

43Chapter 4

44

Chapter 5

Chapter 5
EXPERIMENTS
5.1 Case study for optimizing information flow
In this section, a case study is shown in order to explain the details of the proposed
framework. Examples of document flows, in which four types of documents are transmitted
among seven organizations are used. The organizations consist of (1) a seller, (2) a customs
broker of origin, (3) a customs of origin, (4) a freight forwarder, (5) a customs of destination,(6) a customs broker of destination and (7) a buyer. They are described by using theOrganization class shown in section 4.2. Four types of documents: (1) commercial invoice,(2) packing list, (3) bill of lading and (4) Forwarding instructions are used in the case study.
The details of the documents are explained below:
Commercial invoice: Commercial invoices are used by customs to calculate taxes. They arealso used in billing processes to request payment for products and services.
Commercial invoices are issued by sellers and suppliers. Usually, these documents
include information of an import company and ID numbers of transported items.
Figure 5-1 shows a format of commercial invoices and information included in it. The
left side of the figure shows the format and the right side of the figure shows theinformation by using the international logistics ontology shown in section 4.2. In thissection, each class is described by using a two-line table: The first line stands for“instance name: class name” and the second line stands for properties. For example,
in the upper box of right side in Figure 5-1 means that import_company is an
instance of Trader class, and it has properties of Name and Address.

Figure 5-1 An example of information in commercial invoice document
Packing List: A packing list is issued by sellers and exporters. The purpose of this type of
documents is to provide information of items for transport agencies, government
authorities, and customers. In a packing list, details of package are described along45

Chapter 5with number of packages, and details of import company, i.e. name and address.
Figure 5-2 shows a format of packing lists and information included in it.

Figure 5-2 An example of information in packing list document
Bill of Lading: A bill of lading is issued by a party who provides the physical transportation
services, i.e. freight forwarders. Usually, this type of documents is sent to sellers,
exporters, shippers, and consignor. Bill of lading is used as a receipt for cargoes. This
document also contains the details of vehicle such as license plate number of avehicle. Figure 5-3 shows a format of bill of ladings and information included in it.

Figure 5-3 An example of information in bill of lading
Forwarding Instructions: In this document, conditions of shipment and details of packages
are described such as size of each package. A forwarding instruction is prepared bya freight forwarder. Figure 5-4 shows a format of forwarding instructions andinformation included in it.

Figure 5-4 An example of information in forwarding instructions document46

Chapter 5

Figure 5-5 shows the flows of documents which shown above. In these flows, six types of
information are exchanged among seven nodes.

Figure 5-5 Flows of documents in the case study
5.1.1

Example of optimizing document flow

In order to evaluate effectiveness of the proposed system that was described in section 4.2
outline of the supporting system., this case study is employed for representation the wholeprocesses of optimizing document flows as shown below:
Step (1) Create current information flows matrix
A matrix which represents the document flows is generated. Table 5-1 shows the generated
matrix. In this step, the matrix of current document flows is converted to matrices of𝛼information flows (𝑀𝑖,𝑗), where α stands for an index of information included in the
documents, i stands for the source of information, and j stands for the destination of theinformation respectively.

47

Chapter 5

Table 5-1 A matrix which represents the current documents flows
SellerCustoms
Broker of
OriginX• Commercial
Invoice• Packing
List

Destination
SourceSellerCustoms
Broker of
OriginCustoms ofOriginFreight
ForwarderX

Customs ofOriginFreight
Forwarder• Commercial
Invoice• Packing
List• Commercial
Invoice• Packing
List

Customs of
Destination

Customs
Broker of
Destination• Commercial
Invoice• Packing List

Buyer
• Commercial
Invoice• Packing
List• Commercial
Invoice• Packing List

X
• Bill of
Lading• Forwarding
Instructions• Billof
Lading• Forwarding
Instructions

X

Customs of
Destination
Customs
Broker of
Destination

X• Commercial
Invoice• Packing ListX
• Commercial
Invoice• Packing List

Buyer

X

Step (2) Optimize information flows
The information flows are optimized by using the algorithm described in the Section 4.4.
Six informations are used in the case study. Here, an information of Organization.
Trader. [import_company. Name] is focused on for explanations. It is contained in allof 4 documents that are described above. The flows of this information are described as thematrix Mi,jimport_company shown in Table 5-2. There are 10 edges in the matrix.
m1,5import_company, m1,3import_company, m2,5import_company and m4,1import_company are eliminated withthe algorithm. The optimized information flow (M'i,jimport_company) is shown on the right sidein Table 5-2. As same ways, all information flows are optimized as shown in Table 5-3 to 57. The results are shown in Table 5-8 as a matrix M'i,jα.

48

Chapter 5

Table 5-2 Current information matrix (Mi,jimport_company) and
optimized information matrix (M'i,jimport_company)

Sum

2

X
1

0
X

1
X

1

1

2

0

2
0

1

X

3

1
1

X

1

1

1
X
2

1
X

Sum

1

Sum

1

Buyer

1

Customs Brokerof Destination

1

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

1

X

SourceFreight
Forwarder

1

4

Customs ofOriginX

1

Customs Brokerof Origin1

Seller

1

Destination

Sum

1

Optimized information flow (M'i,jimport_company)

Buyer

Customs ofOriginSellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

Customs Brokerof Origin

X

SourceFreight
Forwarder

SellerDestination

Customs Brokerof Destination

Current information flow (Mi,jimport_company)

1

2
1

X
1

0
X

1
X

1

1

0

1
0

1

X

1

1
1

1
X
1

1
X

Table 5-3 Current information matrix (Mi,jimport_address) and
optimized information matrix (M'i,jimport_address)

Sum

2

X
1

0
X

1
X

1

1

2

0

2
0

1

X

3

1
1

X

1

1

1
X
2

1
X

Sum

1

49

Sum

1

Buyer

1

Customs Brokerof Destination

1

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

1

X

SourceFreight
Forwarder

1

4

Customs ofOriginX

1

Customs Brokerof Origin1

Seller

1

Destination

Sum

1

Optimized information flow (M'i,jimport_address)

Buyer

Customs ofOriginSellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

Customs Brokerof Origin

X

SourceFreight
Forwarder

SellerDestination

Customs Brokerof Destination

Current information flow (Mi,jimport_address)

1

2
1

X
1

0
X

1
X

1

1

0

1
0

1

X

1

1
1

1
X
1

1
X

Chapter 5

Table 5-4 Current information matrix (Mi,jitem_amount) and
optimized information matrix (M'i,jitem_amount)

1

1

2

0

2
0

1

X

3

1
1

1

1
X
2

1
X

Sum

1

Sum

1

Buyer

X

Customs Brokerof Destination

1

1

2
1

X
1

0
X

1
X

1

1

0

1
0

1

X

1

1
1

1
X
1

1
X

Sum

X

1

Buyer

0

X

1

Sum

2

X
1

1

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

1

X

SourceFreight
Forwarder

1

4

Customs ofOriginX

1

Customs Brokerof Origin1

Seller

1

Destination

Sum

1

Optimized information flow (M'i,jitem_amount)

Buyer

Customs ofOriginSellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

Customs Brokerof Origin

X

SourceFreight
Forwarder

SellerDestination

Customs Brokerof Destination

Current information flow (Mi,jitem_amount)

1

2

Table 5-5 Current information matrix (Mi,jitem_ID no.) and
optimized information matrix (M'i,j item_ID no.)

Sum

2

X
1

0
X

1
X

1

1

2

0

2
0

1

X

3

1
1

1

1

X

1

1

1
X
2

1
X

Sum

1

50

Customs Brokerof Destination

1

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

X

SourceFreight
Forwarder

1

Customs ofOrigin1

4

Customs Brokerof OriginX

1

Seller1

Sum

1

Optimized information flow (M'i,jitem_ID no.)Destination
Buyer

Customs ofOrigin1

Customs of
Destination

Customs Brokerof Origin

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Freight
Forwarder

SellerX

SourceCustoms Brokerof Destination

Current information flow (Mi,jitem_ID no.)Destination

1

X
1

0
X

1
X

1

1

0

1
0

1

X

1

1
1

1
X
1

1
X

Chapter 5

Table 5-6 Current information matrix (Mi,jitem_size) and
optimized information matrix (M'i,j item_size)

Sum

2

X

0
X

0
X

0

1

2

0

0

1

X

3

1
1

1
X
1

1
X

1

X

1

1

Sum

Sum

1

Customs Brokerof Destination

1

Buyer

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

1

X

SourceFreight
Forwarder

1

4

Customs ofOriginX

1

Customs Brokerof Origin1

Seller

1

Destination

Sum

1

Optimized information flow (M'i,jitem_size)

Buyer

Customs ofOriginSellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer

Customs of
Destination

Customs Brokerof Origin

X

SourceFreight
Forwarder

SellerDestination

Customs Brokerof Destination

Current information flow (Mi,jitem_size)

1

2
1

X

0
X

0
X

0

1

1

0

0

1

X

1

1
1

1
X
1

1
X

Table 5-7 Current information matrix (Mi,jtrailer_license plate no.) and
optimized information matrix (M'i,j trailer_license plate no.)SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer
Sum

0
X

0
X

1

0
X

1
X

0

0

0

2
0

X

0

0

0
X
1

0
X

SellerCustoms
Broker of
OriginCustoms ofOriginFreight
Forwarder
Customs of
Destination
Customs
Broker of
Destination
Buyer
Sum

Sum

Buyer

Customs Brokerof Destination

Customs of
Destination

Freight
Forwarder

Customs ofOrigin

X

0
X

0
X

1

0
X

1
X

0

0

0

0

2
0

X

1

51

Customs Brokerof Origin

SellerSum
SourceX

1

Optimized information flow (M'i,jtrailer_license plate no.)Destination

Buyer

Customs of
Destination

Freight
Forwarder

Customs Brokerof Destination

SourceCustoms ofOriginSellerDestination

Customs Brokerof Origin

Current information flow (Mi,jtrailer_license plate no.)

0

0
X
1

0
X

Chapter 5

Table 5-8 A matrix which represents the optimized information flows (M'i,jα)Destination(1)

Seller

Source(2)

Customs Brokerof Origin(3)

Customs ofOrigin(4)

Freight
Forwarder(5)

Customs of
Destination(6)

Customs Brokerof Destination• import_company:(1)

Seller

X

(7)

Buyer

• import_company:

Trader [Name]• import_company:
Trader [Address]• itemn: Package[Amount]• set_of_item:
Item_Group [ID_no.]

Trader [Name]• import_company:

Trader [Address]• itemn: Package[Amount]• set_of_item:

Item_Group [ID_no.]• import_company:

Trader [Name](2)• import_company:

Customs
Broker of
OriginX

Trader [Address]• itemn: Package[Amount]• set_of_item:

Item_Group [ID_no.](3)

Customs ofOrigin(4)

Freight
Forwarder(5)X• itemn: Package[Size]• itemn: Package [Size]• trailer: Vehicle

X• trailer: Vehicle[License_plate_no.][License_plate_no.]

Customs of
DestinationX• import_company:

Trader [Name](6)• import_company:

Customs
Broker of
Destination

Trader [Address]• itemn: Package

X[Amount]• set_of_item:
Item_Group [ID_no.]• import_company:

Trader [Name]• import_company:(7)

Trader [Address]

Buyer• itemn: Package[Amount]• set_of_item:
Item_Group [ID_no.]52

XChapter 5

Table 5-9 A matrix which represents the optimized document flows
Destination
Source(1)

Seller(2)

Customs
Broker of
Origin(1)
Seller(2)
Customs
Broker of
OriginX

Document
A
X(3)
Customsof Origin(4)
Freight
Forwarder(5)
Customs of
Destination

(7)
Buyer
Document
A

Document
A(3)

Customs ofOrigin(4)

Freight
Forwarder(5)

Customs of
Destination

X(6)

Customs
Broker of
Destination

Document
A

(7)

(6)
Customs
Broker of
Destination

X
Document
B

Document
B

X

X
Document
A

Buyer

X

Step (3) Convert information flows to document flows
Then, the information flows are converted to document flows. First, group of cells which
has same information is found in Table 5-8. We can find that m1,2Import_company,
m1,7Import_company, m2,3Import_company, m6,5Import_company, and m7,6Import_company have the same
information. Thus, they are made as a group. In this way, two groups of information are
made:Group A; import_company: Trader[Name],
import_company:
Trader[Address], itemn: Package [Amount] and set_of_item: Item_Group [ID_no.]
Group B; itemn: Package [Size] and trailer: Vehicle [License_plate_no.]
Information included in a group are arranged into a document. In this case, informations
in Group A are put into Document A, and information in Group B are put into Document
B respectively as shown in Table 5-9. The flow of Document A has five edges i.e. (1) ⇾ (2),(2) ⇾ (3), (1) ⇾ (7), (6) ⇾ (5), and (7) ⇾ (6). The flow of Document B has two edges whichare (4) ⇾ (1) and (4) ⇾ (7). Finally, the optimized document flow is obtained as shown in
Figure 5-6.

53

Chapter 5

Figure 5-6 Optimized document flows
5.1.2

Discussion

After optimizing information flows, the number of information transmissions is decreased.
Some distance between original node and destination node is increased. To discuss the
distance between original node and destination node, an example is shown. Figure 5-6
shows information flows of the example. In this figure, Graph A represents an original
information flows and Graph B represents the optimized information flows.

Figure 5-7 An example of directed graphs
The Graph A consists of six edges and four nodes. For each node, some indegree edges are
eliminated until the number of indegrees become one. In this case, edges of DA and BC are
eliminated as represented by Graph B in Figure 5-6. Although these edges are eliminated,
all of the nodes can receive the information. However, the distance between node D and A
increased from 1 (D ⇾ A) to 2 (D ⇾ C ⇾ A) because the edge BC is eliminated.
In some cases, the distance may induce additional financial and time costs oftransmissions.
Timings of retrieving information also have to be considered. Some information must be
synchronized together but the algorithm does not consider the situations. Tackling thesethree problems is the direction of the future works.

54

Chapter 5

5.2 Simulation models
5.2.1

Experimental design

In the processes of exporting some product from Thailand to another ASEAN countries,
twenty-two types of documents are used in 16 organizations. In these types of documents
555 types of information are included. To make simple state of simulations, 12 types of
documents with 4 types of information and 14 organizations are used in this experiment.
The graph in Figure 5-8 shows average number of packages that will be transported by alogistics service provider. The number of packages were calculated by using the datacollection of the ABC co., Ltd 3. These sets of data were collected for twenty days (weekday)
in November 2014. In the simulation, the frequency of appearing packages are determinedin accordance with the graph. When a package appeared, a document is sent from a seller(export_company) to a logistics service provider (freight_forwarder).

Number of packages (packages/hour)

80

70

69

60
50

53
48

40
30

56

33
25

23

20
12
8

10

7

0

Time slot

Figure 5-8 Average number of packages a day
Each organization in the transaction process conducts a task for each document. The task
consists of “writing” and “recording.” The required time for each task was calculated byusing data collection from ABC co., Ltd. As shown in Appendix C. The required time for thetask depends on the document. Thus, the time are determined as following:
Writing: a minimum time is 10 minutes, a maximum time is 20 minutes, and a most likely
time is 15 minutes.
Recording: a minimum time is 5 minutes, a maximum time is 10 minutes, and a most likely
time is 7 minutes.
In each task, staffs are needed: 3 staffs for writing and 1 staff for recording. These staffs
are used for treating the documents.
3 ABC co., Ltd., Annual Report, 2014

55

Chapter 5

In this experiment, the required times are defined by using a probability density functionof a triangular distribution which depend on the case of documents. The required time ofwriting task is assumed as a function which shown as graph in Figure 5-9 (a). The service
time of recording process is assumed as a function which shown as graph in Figure 5-9 (b).

(a)

Writing task(b)

Recording task

Figure 5-9 Triangle distribution function of writing and recording task
A triangular distribution is a continuous probability distribution with a probability density
function shaped like a triangle. It is defined by three values: the minimum value (Min), themaximum value (Max), and the peak value (Most likely). The probability density functionof a triangular distribution
The formula for the probability density function is:(5-1)

The aim of this experiment is to investigate the effect of the algorithm shown in Chapter
4, Section 4.4. In this experiment, information flow simulations are con generated. Figure
5-10 shows a conceptual of information flow simulation.

56

Chapter 5

Figure 5-10 Conceptual of information flow among organizations
Number of submitted documents are defined as the type of schedule which are submitted
at first organization in the ASEAN transaction process during a day. The submitted ratesof documents can be assumed by using the number of transported packages as shown in
Figure 5-8. In this simulation, initial number of iterations is 10 trials at 95% confidence
interval. In order to reduce error value (half-width) from the simulation, number of
iterations should be increased. The number of iterations is determined as equation (5-2) or(5-3).
𝑛 ≅ 𝑡𝛼2⁄

𝑠2

(5-2)

2,𝑛−1 ℎ2ℎ2

(5-3)

𝑛 ≅ 𝑛0 ℎ02

Where n denotes the number of replications, n0 denotes initial number of replications, sdenotes standard deviation value, h0 denotes initial half-width of number of submitted
documents, and h denotes desired half-width. After calculating number of replications, 10,40, and 100 iterations are used in this simulation. In each iteration, an iteration length is
10 hours. The outline of the current and optimized information flow will be described in
section 5.2.2 and 5.2.3.
5.2.2

Information flows before applying the proposed algorithm

In order to make the simulation real, the actual ASEAN trade transaction processes were
investigated. Figure 5-11 shows the transaction model that is created based on the results.
In this figure, nodes represent organizations, arrows represent flows of sets of information(document). Line width of the arrows stand for number of sending same type of information.
First Document i.e. purchase order is generated by Buyer (import_company). Then the
document with sets of information is moved through other organizations based onorganized orders that are shown on arrows in Figure 5-11. From Figure 5-11, we can seethat many organizations send or receive same type of information repeatedly. For example,
a customs of destination sends a port authority’s destination same type information fourtimes.

57

Chapter 5

Figure 5-11 Outline of actual information flow model

58

Chapter 5

5.2.3

Information flows after applying the proposed algorithm

The flows of sets of information are optimized by using the proposed algorithm describedin Chapter 4, Section 4.4. Figure 5-12 shows the transaction model after using the proposed
algorithm. In this model, nodes represent organizations, line arrows represent flows of setsof information. From Figure 5-11 and 5-12, we can compare that number of sending andreceiving the sets of information are reduced obviously after applying the proposed
algorithm. In Figure 5-12, organizations receive a set information one time that is affected
on number of recording information.

Figure 5-12 Outline optimized information flow model

59

Chapter 5

5.2.4

Results

In this section, the results of multi-agent simulations which were conducted to investigate
the effects of the proposed algorithm are shown. The results show that number of thetreated sets of information after optimizing information flows can be increased 25.32%
when compared with the treated sets of information before optimizing information flow.
Table 5-10 shows average number of sets of information between before and after
optimizing information flow. From Table 5-10, we can see that before optimizing
information flows, 14 sets of information can be completed from all tasks of organizations
at 95% confidence level. After optimizing information flows, 56 sets of information can becompleted from all tasks at 95% confidence level.
Table 5-10 Comparing average number of sets of information between before and after
optimizing information flow
Number of
iterations
10
40
100
Number of
iterations
10
40
100

Before optimizing information flow
Submitted sets of
Half
Treated sets of
information
width
information
315.60±8.4700
14.00
323.50±3.4200
14.00
331.36±1.9200
14.16
After optimizing information flow
Submitted sets of
Half
Treated sets of
information
width
information
324.40±8.0200
55.60
328.90±2.9800
55.90
330.00±1.7700
55.92

Half
width
±0.3800±0.1600±0.1000
Half
width±0.2300±0.1400±0.0900

The graph in Figure 5-13 shows times of before and after optimizing information flow.
There are three types of bar in the graph: blue bars represent value-added time (VA time),orange bars represent waiting time, and grey bars represent transfer time. From thegraphs, total time of information flow can be reduced from 8.21 hours to 5.97 hours at 95%
confidence level after optimizing information flow. The waiting time is 1.48 hours forwriting tasks and 0.18 hours for recording tasks before optimizing information flows at
95% confidence level. The graphs in Figure 5-14 and 5-15 show the waiting time and queuesof writing and recording tasks.

Time (hours)

9.00
8.00

0.67

0.67

0.67

7.00

1.05

1.17

1.13

6.00

4.00
3.00

3.00

2.99

2.94
6.39

0.50

0.50

0.50

5.00

6.41

6.37

2.00
2.47

1.00

2.47

2.47

0.00
beforeAfter

10 replications
VA TimebeforeAfter

40 replications
Waiting Time

beforeAfter

100 replications

Transfer Time

Figure 5-13 Time of before and after optimizing information flow
60

Chapter 5

1.80
p<0.05

Average of waiting time (hours)

1.60

1.40

1.48

1.47

1.20
1.00
0.80
0.60
0.40

p<0.05

0.20
0.18

0.00
Writing Process
Before optimizing

0.00

Recording Process
After optimizing

Average queue (mumer of waiting)Figure 5-14 Average waiting times of writing and recording task
18.00
16.00
14.00

p<0.05

14.57

14.49

12.00
10.00
8.00
6.00
4.00

p<0.05

2.00

0.27

0.00
Writing process
Before optimizing

0.00

Recording process
After optimizing

Figure 5-15 Average numbers of queues of writing and recording task
5.2.5

Discussion

After optimizing information flows, the number of sending and receiving sets of information
have been decreased. From the results of multi-agent simulations, the reduction in numberof sending and receiving the sets of information are able to reduce total time of information
flows. The graph in Figure 5-13, total time of information flows is reduced 27.28% after
applying the proposed algorithm. Although the total time could be reduced, waiting times
are remained in each task of the paperwork processes. From the graph in Figure 5 - 13, we
can see the waiting times after optimizing information flows is 50.25% of total time at 95%
confidence level. The value-added time (VA time) after optimizing information flow is
61.41% less than before applying the proposed algorithm at 95% confidence level. Due toreductions of VA time, the speed of sets of information are faster than before applying the61Chapter 5

proposed algorithm. It makes increased queues of the sets of information at eachorganization. When sets of information are submitted at each organization, some sets of
information must wait until the other sets of information are finished for treating by astaff. Workloads of staffs in before and after applying the proposed algorithm are different
because number of documents’ arrival is increased in each organization. With the same
number of staffs, it is difficult to deal with the queue of sets of information after optimizing
the flow. Therefore, number of staffs in each task should be considered for reducing waitingtimes. In order to design number of staffs, modified information flows are constructed todesign number of staffs for realizing optimal waiting times of information flows. In themodified information flow simulations, the document with sets of information is moved
through other organizations based on organized orders shown in Figure 5-12. In each case,different number of staffs are defined by increasing number of staffs. There are 6 cases ofmodified information flow that are shown in Table 5-11.
Table 5-11 Number of staffs in each case of modified information flows
Simulation

Number of staffs
Recording task
1
1
1
2
2
2
3
3

Writing task
3
3
5
2
4
5
4
5

Before optimizing
After optimizing
Modified (1)Modified (2)Modified (3)Modified (4)Modified (5)Modified (6)

Total
23
23
24
32
36
38
50
52

The graphs in Figure 5-16 to 5-21 show times of before, after and modified information
flows. In this graph: blue bars represent value-added time (VA time), orange bars represent
waiting time, and grey bars represent transfer time.
9.00

8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

0.50

4.00
3.00

2.94

2.99

2.50

6.39

0.50

0.50

0.50

5.00

2.64

0.50

3.00

2.65

2.47

2.47

After

Modified (1)

6.41

6.37

2.00

1.00

2.47

2.47

After

Modified (1)

2.47

2.47

After

Modified (1)0.00
Before10 replications

Before40 replications

VA TimeWaiting Time

Before100 replications

Transfer Time

Figure 5-16 Time of before, after optimizing and modified information flow (1)62Chapter 5

9.00
8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

4.00
3.00

0.50

0.50

5.00
2.94

2.99

2.57

6.39

0.50

0.50

2.69

0.50

3.00

2.69

2.47

2.47

After

Modified (2)

6.41

6.37

2.00
1.00

2.47

2.46

After

Modified (2)

2.47

2.47

After

Modified (2)0.00
BeforeBefore10 replications

Before40 replications
VA TimeWaiting Time

100 replications

Transfer Time

Figure 5-17 Time of before, after optimizing and modified information flow (2)

9.00
8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

0.50

0.50

5.00
4.00
3.00

2.94
6.39

1.16

0.50

2.99

0.50

1.48

6.37

0.50

3.00

1.50

6.41

2.00
1.00

2.47

2.45

After

Modified (3)

2.47

2.46

After

Modified (3)

2.47

2.46

After

Modified (3)0.00
Before10 replications

Before40 replications
VA TimeWaiting Time

Before100 replications

Transfer Time

Figure 5-18 Time of before, after optimizing and modified information flow (3)63Chapter 5

9.00
8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

0.50

0.50

5.00
4.00
3.00

6.39

1.24

0.50

2.99

0.50

2.94

6.37

1.35

0.50

3.00
6.41

1.41

2.00
1.00

2.47

2.45

After

Modified (4)

2.47

2.46

After

Modified (4)

2.47

2.46

After

Modified (4)0.00
BeforeBefore10 replications

Before40 replications
VA TimeWaiting Time

100 replications

Transfer Time

Figure 5-19 Time of before, after optimizing and modified information flow (4)

9.00
8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

0.50

0.50

5.00
4.00
3.00

2.94
6.39

1.15

0.50

2.99

0.50
6.37

1.31

0.50

3.00
6.41

1.32

2.00
1.00

2.47

2.46

After

Modified (5)

2.47

2.46

After

Modified (5)

2.47

2.46

After

Modified (5)0.00
Before10 replications

Before40 replications
VA TimeWaiting Time

Before100 replications

Transfer Time

Figure 5-20 Time of before, after optimizing and modified information flow (5)64Chapter 5

9.00
8.00
7.00

0.67

0.67

0.67

1.05

1.17

1.13

Time (hours)

6.00

0.50

0.50

0.50

5.00
4.00
3.00

3.00

2.99

2.94
0.50
0.62

6.39

0.50

6.37

0.72

0.50

6.41

0.78

2.00
1.00

2.47

2.46

After

Modified (6)

2.47

2.46

After

Modified (6)

2.47

2.46

After

Modified (6)0.00
BeforeBefore10 replications

40 replications
VA TimeWaiting Time

Before100 replications

Transfer Time

Figure 5-21 Time of before, after optimizing and modified information flow (6)From graphs in Figure 5-16 to 5-21, we can see that the average numbers of waiting time
have been reduced after adjusting number of staffs in each case. The waiting time of themodified information flow (1) is less 12% than the optimized information flow. The waitingtime of the modified information flow (2) is less 10% than the optimized information flow.
The waiting time of the modified information flow (3) is less 50% than the optimized
information flow. The waiting time of the modified information flow (4) is less 53% thanthe optimized information flow. The waiting time of the modified information flow (5) isless 56% than the optimized information flow. The waiting time of the modified information
flow (6) is less 74% than the optimized information flow.
As describe above, modified information flow (6) is the best in the simulations from the
aspect of time. However, it needs most number of staffs. Although adding number of staffs
in each process can help to reduce waiting time, number of staffs are affected on costs ofeach organization. The cost effect will be considered in the future direction.
7.00

60

6.00

Time (Hours)

5.00

40

4.00
30
3.00
20

2.00

10

1.00
0.00

0
BeforeAfter
VA Time

Modified (1) Modified (2) Modified (3) Modified (4) Modified (5) Modified (6)Waiting Time

Transfer Time

Number of staffs

Figure 5-22 Time and number of staffs of before, after optimizing and modified
information flows (1) – (6)65Total number of staffs

50

Chapter 566

Chapter 6

Chapter 6
CONCLUSIONS AND
FUTURE DIRECTIONS
6.1 Conclusions
Based on surveying actual processes of international trade transaction in ASEAN
countries. 3 aspects in the international trade transaction trade processes are found thatconsist of document layer, information layer and presentation layer. These 3 aspects havebeen considered to determine an international trade transaction model. Then theinternational trade transaction model is shown for describing international tradetransaction processes. There are 3 layers in the model that consist of information flow layer,
document flow layer and presentation or interface layer.
In this thesis, a framework of supporting system for international trade transaction system
has been proposed. This system consists of three procedures, (1) Convert (document flows→ information flows), (2) Optimize information flows, and (3) Convert (information flows→ document flows). Due to many types of information that are contained in each document,
an ontology has been required for interpreting information in each document. Therefore,
an international logistics ontology has been developed for describing the model andinterpreting information. The results of surveying, complex of information flows also havediscovered. In order to solve the complex of information flows, an algorithm for optimizing
information flow has been proposed. With the proposed algorithm, we can optimize
document flows in international trade transaction processes.
Due to the proposed algorithm, information flow simulations are conducted for evaluating
the proposed algorithm. These simulations are also employed for representation theinformation flow before and after optimizing of the paperwork processes. The results ofsimulation, total time of information flows can be reduced 27.28% after applying the
optimizing information flow algorithm. Furthermore, in order to reduce waiting time,number of staffs in each organization are designed in the modified information flow
simulations. The average of waiting time can be reduced at least 10% that is compared withthe average of waiting time of optimized information flows. Developing user friendly
system is expected with the proposed framework due to different languages of each country.
The presentation layer of the international trade transaction model is also expected tocontribute to develop user-friendly systems, because they can provide suitable language
environment for the users by using the layer. To implement practical system, we also haveto develop whole of classes of the ontology.

67

Chapter 6

6.2 Directions for future works
An algorithm for optimizing information flow is proposed based on reducing redundancies
of information flow. From the results of optimizing information flow, redundancies
information flows are eliminated. Although we can reduce some redundant information
flows, the distance between source and destination of information is not considered yet.
The distance of some information flow is still far from original source. In some cases, thedistance may induce additional financial and time costs of transmissions. Timings ofretrieving information also have to be considered. Some information must be synchronized
together but the algorithm does not consider the situations. Therefore, further studies
should be made to develop the proposed model for proving the reliability of intermediate
node. Tackling these problems is the direction of the further studies. Moreover, number ofstaffs in each organization should be considered as a factor that is affected on costs of eachorganization.

68Appendix

APPENDIX A
Table A-1 The data collection of information arrivals by the ABC co., Ltd in November 2014
Time

Date

Average

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

10.00-11.00

67

56

65

71

62

65

100

69

64

69

71

73

92

68

72

64

69

54

63

69

69.15

11.01-12.00

77

38

44

51

44

65

53

46

44

38

44

48

55

40

36

48

38

48

46

52

47.75

12.01-13.00

63

19

17

15

21

27

40

15

15

18

19

23

25

15

21

15

23

19

35

17

23.10

13.01-14.00

27

56

50

55

40

62

44

59

51

78

48

68

26

58

66

51

65

56

52

50

53.10

14.01-15.00

21

55

56

73

62

76

31

56

54

70

61

68

45

52

72

52

66

54

56

49

56.45

15.01-16.00

2

41

43

47

36

40

15

35

43

37

29

45

25

33

25

43

37

28

35

19

32.90

16.01-17.00

7

27

25

31

12

52

2

23

25

20

30

28

22

24

21

25

33

27

36

25

24.75

17.01-18.00

5

7

10

16

11

10

8

6

20

10

10

29

7

10

14

20

10

13

6

10

11.60

18.01-19.00

8

14

11

2

2

6

2

14

6

6

2

16

10

2

10

9

6

7

14

11

7.90

19.01-20.00

3

3

6

8

7

2

7

4

3

6

12

6

7

14

6

5

10

12

4

8

6.65

327 369297

405 302

327

325

352

326

404

314

316

343

332

357

318

347

310

333.35

Total

280 316

Source: ABC co., Ltd

69

70

Appendix

APPENDIX B
Table B-1 Set of information in commercial invoice document
Class
Reference_Number
Date. Issued_Date
Reference_Number
Payment
Organization. Trader. Seller
Organization. Trader. Seller
Organization. Trader. Seller
Organization. Trader. Seller
Place. Country
Organization. Trader. Seller
Organization. Trader. Buyer
Organization. Trader. Buyer
Organization. Trader. Buyer
Organization. Trader. Buyer
Place. Country
Organization. Trader. Buyer
Payment

Item_Group

Property
Invoice. No.
Invoice. Date
Purchase order. No.
Item price. Term_of_Payment
Export_company. Status
Export_company. Name
Export_company. Tax_ID_No.
Export_company. Address
Origin_country. CodeExport_company. E-mailImport_company. Status
Import_company. Name
Import_company. Tax_ID_No.
Import_company. Address
Destination_country. Code
Import_company. E-mailItem_price. Currency_Code
Item1, Item2, …, Itemn.
Manufacture_Country_Name
Item1, Item2, …, Itemn. Weight

Item_Group
Payment
Payment
Payment
Payment
Payment
Payment
Payment
Payment
Payment
Payment
Person_in_Charge. Authority

Item1, Item2, …, Itemn. HS_Code
Item_price. Number_of_Item
Item_price. Unit_of_Measure
Item_price. Unit_of_Price
Item_price. Total_Amount
Freight_cost. Total_AmountInsurance_cost. Total_AmountInvoice. Total_Amount
Freight_cost. Currency_code
Insurance_cost. Currency_code
Packing_charge. Currency_code
Export_company. Name

Item_Group71

Appendix

Table B-2 Set of information in packing list document
Class

Property

Reference_Number

Packing_list. No.

Date. Issued_Date

Packing_list. Date

Date

Shipping_date. Date

Date. Isssued_Date

Purchase_order. Date

Reference_Number

Purchase_order. No.

Reference_Number

Invoice. No.

Person_in_Charge. Contact_Person

Export_company. Name

Organization. Trader. Seller

Export_company. Name

Organization. Trader. Seller

Export_company. Address

Organization. Trader. Seller

Export_company. Telephone_No.

Organization. Trader. Buyer

Import_company. Name

Organization. Trader. Buyer

Import_company. Address

Person_in_Charge. Contact_Person

Import_company. Name

Organization. Trader. Buyer

Import_company. Telephone_No.

Item_Group. Package

Item1, Item2, …, Itemn. Amount

Item_Group. Package

Item1, Item2, …, Itemn. No.

Item_Group. Package

Item1, Item2, …, Itemn. Type

Item_Group. Package

Item1, Item2, …, Itemn. Dimension

Item_Group

Item1, Item2, …, Itemn. Weight

Item_Group

Set_of_item. Container_No.

Person_in_Charge. Authority

Export_company. Name72

Appendix

Table B-3 Set of information in bill of lading document
Class

Property

Date. Issued_Date

Bill_of_lading. Date

Reference_Number

Bill_of_lading. No.

Organization. Freight_Forwarder

Transportation_provider. Name

Organization. Freight_Forwarder

Transportation_provider. Address

Organization. Trader. Buyer

Import_company. Name

Organization. Trader. Buyer

Import_company. Address

Person_in_Charge. Contact_Person

Import_company. Name

Person_in_Charge. Driver

Transportation_provider. Name

VehicleTrailer. License_Plate_No.

Item_Group

Set_of_item. Container_No.

Reference_Number

Tracking. No.

Place. Location. Port

Loading_port. Name

Place. Location

Place_of_reciept. Address

Place. Location. Port

Discharge_port. Name

Place. Location

Place of delivery. Address

VehicleVessel. License_Plate_No.

Item_Group. Package

Item1, Item2, …, Itemn. Amount

Item_Group. Package

Item1, Item2, …, Itemn. Type

Item_Group

Item1, Item2, …, Itemn. Weight

Payment

Freight_cost. Total_AmountPayment

Freight_cost. Term_of_Payment

Place. Location. Issued_Place

Transportation_provider. Address

Date. Issued_Date

Bill_of_lading. Date

Date

Departure_date. Date73

Appendix

Table B-4 Set of information in forwarding instructions document
Class

Property

Reference_Number

Bill_of_lading. No.

Organization. Freight_Forwarder

Transportation_provider. Name

Organization. Freight_Forwarder

Transportation_provider. Address

Organization. Trader. Buyer

Import_company. Name

Organization. Trader. Buyer

Import_company. Address

Organization. Trader. Buyer

Import_company. E-mailOrganization. Trader. Buyer

Import_company. Telephone_No.

Person_in_Charge. Contact_Person

Import_company. Name

Person_in_Charge. Driver

Transportation_provider. Name

VehicleVessel. License_Plate_No.

Item_Group. Package

Item1, Item2, …, Itemn. Amount

VehicleTrailer. License_Plate_No.

Item_Group

Item1, Item2, …, Itemn. Weight

Item_Group. Package

Item1, Item2, …, Itemn. Type

Item_Group. Package

Item1, Item2, …, Itemn. Dimension

Place. Location. Port

Loading_port. Name

Place. Location. Port

Discharge_port. Name

Place. Location

Place_of_reciept. Address

Place. Location

Place_of_delivery. Address

Item_group

Set_of_item. Temperature_Required

Item_Group

Set_of_item. Type

Person_in_Charge. Authority

Transportation_provider. Name

Date. Issued_Date

Forwarding_instructions. Date74

Appendix

APPENDIX C
Table C-1 Data collection of time for writing process
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Time of writing process (minutes)
10
22
35
27
11
12
22
9
12
17
13
13
12
9
25
20
15
12
23
11
17
12
13
33
23
31
22
13
12
10
17
23
23
23
14
12
23
11
17
12

No.
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80

Time of writing process (minutes)
25
10
17
26
35
27
11
12
25
12
10
17
26
23
23
14
12
12
10
17
26
23
23
14
12
10
17
26
23
23
14
12
23
12
10
17
26
23
23
14

75

Appendix

No.
81
82
83
84
85
86
87
88
89
90

Time of writing process (minutes)
12
23
12
10
17
26
23
23
14
12

No.
91
92
93
94
95
96
97
98
99
100

Time of writing process (minutes)
10
17
15
12
23
11
17
12
13
10

Figure C-1 Distribution summary for Lognormal fit to service times of writing process76Appendix

Table C-2 Data collection of time for recording process
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50

Time of recording process (minutes)
4
7
3
5
6
4
10
7
3
5
4
5
7
12
5
6
9
5
8
11
10
6
9
4
9
10
8
4
5
8
10
7
5
4
6
8
6
7
6
6
9
9
10
8
7
7
8
8
6
10

No.
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100

Time of recording process (minutes)
8
4
5
8
8
6
10
8
4
5
8
7
7
5
8
8
8
7
7
5
7
6
8
6
7
6
6
6
6
6
5
11
5
7
5
8
5
8
5
5
8
5
5
7
5
6
6
12
8
7

77

Appendix

Figure C-2 Distribution summary for Beta fit to service times of recording process

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PUBLICATIONSJournal•Klairung PONANAN, Tanapun SRICHANTHAMIT, Woramol Chaowarat
WATANABE, Shinya WATANABE and Hidetsugu SUTO, “A Framework of
Supporting System for Optimizing Information Flow in International Trade
Transaction”, International Journal of Affective Engineering, Vol. 18, No. 1,
2019, DOI: 10.5057/jjske.TJSKE-D-18-00040.

Proceeding of International Conference•

Klairung Ponanan, Hidetsugu Suto and Shinya Watanabe. “An approach forsupporting system of international logistics based on ontological engineering”,
2017 International Conference on Biometrics and Kansei Engineering(ICBAKE2017), Tokyo, Japan, pp.49-54, September 2017.

Domestic Conferences••

Klairung Ponanan, Hidetsugu Suto and Shinya Watanabe, “Ontologicalapproach for international transportation problems”, Joint Seminar on
Environmental Science and Disaster Mitigation Research 2017 (JSED2017), 室蘭工業大学 教育・研究 7 号館, pp.137-138, March 2017.
Klairung Ponanan, Tanapun Srichanthamit, Woramol Chaowarat Watanabe,
Shinya Watanabe, and Hidetsugu Suto, “A Framework of Supporting System
for Optimizing Information Flow in International Trade Transaction”, The 20th
Annual Meeting of Japan Society of Kansei Engineering, Tokyo, Japan,
September 2018.

83

84