Miles Weaver PhD Thesis

A SIMULATION CONCEPTUAL MODELLING
METHODOLOGY FOR SUPPLY CHAIN
MANAGEMENT APPLICATIONS

MILES WEAVER

DOCTOR OF PHILOSOPHY

ASTON UNIVERSITY

OCTOBER 2010

This copy of the thesis has been supplied on condition that anyone who consults it is
understood to recognise that its copyright rests with the author and that no quotation
from this thesis and no information derived from it may be published without proper
acknowledgement.
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Aston University
A Simulation Conceptual Modelling Methodology for Supply Chain
Management Applications
Miles Weaver
Doctor of Philosophy
2010

Thesis summary
The research focuses upon the development of a simulation conceptual modelling methodology
for SCM applications (termed the ‘SCM2’). The originality of the SCM2 is that it combines a
prescribed procedure for simulation conceptual modelling with supply chain domain-specific
knowledge. This procedure is used to guide participants to create a non-software specific
description of the simulation model to be developed, in the context of SCM applications.

The SCM2 is presented as a series of seven phases, associated steps, who participates in each step,
information needs and points of entry between steps. The SCM2 is entered when a client has a
supply problem to be evaluated using a simulation approach. The supply problem is described in
terms of the improvement(s) to be evaluated, for a given objective(s) within its supply setting.
From this description, how each objective is to be measured and how each improvement is to be
represented is determined. The interconnections between model components and the
immediate supply setting are discriminated, model boundary formulated and level of detail
designed. The output from the SCM2 is a documented and validated conceptual model.

The need for a greater understanding of how to perform the conceptual modelling stage, as part
of a simulation project, is shown to be of great significance and relevance. In particular the thesis
argues that no methodologies exist that can guide participants in a simulation project through the
process of creating a simulation conceptual model. A research methodological programme is
designed to review existing modelling practice, form a specification for the methodology, develop
an outline for the SCM2, detail the outline through refinement and application and a preliminary
validation of the SCM2.

The specification is formed to identify a set of requirements that the methodology should
address. The methodology is developed to meet the specification by refining the outline design
using two developmental cases of typical and complex supply chain problems. The outline design
is founded on existing practice for conceptual modelling and identifies ten key concepts that have
been synthesised by considering the design issues for each requirement identified in the
specification. A major advance made by this thesis is a suggestion that the process of conceptual
modelling could benefit from utilising domain knowledge provided by the Supply Chain Council
SCOR model. It is demonstrated that using SCOR is a powerful way to enable a more focused and
efficient procedure for conceptual modelling. The methodology incorporates the key concepts
and aligns these with a general process for conceptual modelling. A preliminary validation with a
different supply chain illustration demonstrates that the methodology is initially ‘feasible’ and has
‘utility’. Future testing is required in different industrial contexts with actual participants and an
opportunity exists to extend the methodology into a web-based application tool.

Keywords
Supply chain management, conceptual modelling, simulation, performance evaluation

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To my late grandfather for whom I hold great respect and pride

Hon. Alderman Albert [Tom] Matthews MBE

'Forever my inspiration'

Orchards gay with blossom,
Beauty, there to see,
Hollows where breeze is tender,
Moorlands where wind breaks free;
Sowing, Lambing, and Harvest,
Overlooked by Giant Clee,
Hop Kilns, Farmsteads, and TENBURY,
This is happiness is for me.
Source: Anon

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Acknowledgements
Firstly, I would like to sincerely thank Dr. Doug Love and Dr. Pavel Albores for supervising this PhD
thesis and investing their time in mentoring my early research career. Their energy, drive and
support has inspired, empowered and enabled me for which I am entirely grateful.

I would like to warmly acknowledge my family and friends for their continued support,
encouragement and understanding throughout my doctoral studies. My parents, David and Pat
Weaver, have been a source of determination throughout my life providing the bite to seek
fulfilling goals, taking me to new horizons. My sister, Elaine Dolby and my brother, Nigel Weaver,
have been there for me during the highs as well as the lows. Sarah Greenhouse provided me with
strength when times got challenging; I am entirely grateful for her support, detailed discussions
and time invested in me during the writing up of my thesis. Similarly, Sarah’s mother Josie kept
smiling and offering her time by proof-reading the final drafts – I shall never forget the support
and encouragement from ‘Team Greenhouse’. My two best friends, Paul and Neil, for helping me
to switch off from time to time. I would also like to thank certain colleagues and friends in
particular: Alfred, Anita, Breno, Deycy, Emma, Eleanor, Helen, James, Joanna, Naomi, Natalia, Nick
T, T.T., Tony and Wenshin, who I have had the pleasure to work with or interact with during such
stimulating times.

I would also like to thank researchers who have supported and shaped my doctoral work. In
particular: Prof. Don Taylor (Virgina Tech), Prof. Rafaela Alfalla-Luque and Dr. Carmen Medina-
Lopez (both from Seville University). The data for the industrial development case was gathered
by the FUSION research group (collaboration between Aston, Liverpool and Strathclyde). I am
grateful for all the support and fun times while conducting this research, and look forward to
future collaborations and projects.

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Notations used in thesis

BeerCo Beer company supply chain case
CarCo Car company supply chain case
CHR Central headrests manufacturer
CM Conceptual Modelling
CoffeePotCo Coffee pot supply chain case
DES Discrete Event Simulation
GSFC Global Supply Chain Forum
LA Luxury Automotive Manufacturer
MABM Multi-Agent Based Modelling
SCM Supply Chain Management
SCM2 Simulation conceptual modelling methodology for supply chain management
applications
SCOR Supply-Chain Operations Reference-model
SD Systems Dynamics
SME Subject Matter Expert
SS Seat set manufacturer
SSM Soft Systems Methodology
T Tracks manufacturer

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Publications

During the period of conducting this research the following publications have been contributed
to:

Albores, P., Love, D., Weaver, M., Stone, J. & Benton, H. (2006) An evaluation of SCOR modelling
tools and techniques. Technology and Global Integration. IN: Proceedings of the Second European
Conference on the Management of Technology. Aston Business School, Birmingham, UK.

Taylor, G. D., Love, D. M., Weaver, M. W. & Stone, J. (2008) Determining inventory service support
levels in multi-national companies, International Journal of Production Economics, 116(1), 1-11.

Niranjan, T., Weaver, M., (2010) A unifying view of goods and services supply chain management,
The Service Industries Journal, iFirst Article, 1–20.

Niranjan, T., Weaver, M., Pillai, S., (2009) Bridging between goods and services SCM: Some fresh
perspectives. Green Management Matters. IN: Proceedings of the Academy of Management
Annual Meeting. Chicago, Illinois, USA

Weaver, M., Love, D. & Albores, P. (2008) Supply chain improvement options and their decision
variables. Tradition and Innovation in Operations Management. IN: 15th Annual EurOMA
Conference of the European Association of Operations Management. University of Gronigen,
Netherlands.

Weaver, M., Love, D. & Albores, P. (2007a) A decision aid to select techniques to evaluate supply
chain improvement options. Managing Operations in an Expanding Europe. IN: 14th Annual
Conference of the European Association of Operations Management. Bilkent University, Ankara,
Turkey.

Weaver, M., Love, D. & Albores, P. (2006) Towards the development of a supply strategy
evaluation methodology. Moving Up the Value Chain. IN: Conference of the European Association
of Operations Management. Strathclyde University, Scotland, UK.

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Table of Contents
Thesis summary ................................................................................................................................. 2
Keywords ......................................................................................................................................... 2
Acknowledgements ......................................................................................................................... 4
Notations used in thesis .................................................................................................................. 5
Publications ..................................................................................................................................... 6
List of figures in thesis................................................................................................................... 11
List of tables in thesis .................................................................................................................... 12
Chapter 1 Introduction ................................................................................................................. 14
1.1 Research background ........................................................................................................ 14
1.2 Research aims, objectives and programme ...................................................................... 16
1.3 Justification for the research focus ................................................................................... 18
1.4 Outline of the thesis .......................................................................................................... 19
1.5 Delimitation of scope and definitions ............................................................................... 22
1.6 Chapter summary .............................................................................................................. 24
Chapter 2 Research issues in conceptual modelling for SCM applications .................................. 26
2.1 Scope and selection of contributions in literature review ................................................ 27
2.2 Importance of evaluating supply chain problems............................................................. 29
2.3 Complexity of evaluating supply chain problems ............................................................. 31
2.4 Role of simulation to evaluate supply chain problems ..................................................... 32
2.4.1 Range of approaches used in simulation ................................................................. 33
2.4.2 Extent and usage of simulation for research ........................................................... 34
2.5 Role of conceptual modelling in simulation projects........................................................ 37
2.5.1 Importance of conceptual modelling in a simulation project .................................. 38
2.5.2 Key debates around the nature of conceptual modelling ....................................... 38
2.5.3 Defining conceptual modelling for supply chain problems ..................................... 40
2.6 Understanding of CM for SCM simulation applications .................................................... 43
2.6.1 General issues in understanding of conceptual modelling ...................................... 43
2.6.2 Application of the process of conceptual modelling for SCM problems ................. 45
2.7 Usefulness of a CM methodology for SCM applications ................................................... 46
2.8 Benefits of developing a conceptual modelling methodology for SCM applications ....... 48
2.9 Chapter summary .............................................................................................................. 49
Chapter 3 Research programme for the development and preliminary validation of the SCM2 . 50
3.1 Justification of methodological approach ......................................................................... 50
3.1.1 Methodological approaches for the development of methodologies ..................... 51
3.1.2 Key methodological issues in the area of developing a methodology..................... 52
3.1.3 General methodological issues for developing the SCM2 ........................................ 53
3.1.4 Justification of five stage approach.......................................................................... 61
3.2 Research programme and methods.................................................................................. 64
3.2.1 Overview of research programme and methods ..................................................... 64
3.2.2 Stage I: Review of existing conceptual modelling practice ...................................... 65
3.2.3 Stage II: Forming the specification for SCM2............................................................ 67
3.2.4 Stage III: Discussion of the outline design for the SCM2 .......................................... 68
3.2.5 Stage IV: Discussion of the detailed and refined design of the SCM2 ...................... 70
3.2.6 Stage V: Preliminary validation of the SCM2 ............................................................ 71
3.3 Theory building through existing case study applications ................................................ 73
3.3.1 Involvement and reflexivity of the researcher ......................................................... 74
3.3.2 Consistency of the process....................................................................................... 74
3.3.3 Choice of supply chain application cases ................................................................. 75
3.3.4 Data collection methods .......................................................................................... 76
3.4 Limitations of research approach ..................................................................................... 77
3.5 Validity and reliability of the research .............................................................................. 78
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3.6 Ethical considerations and issues...................................................................................... 78
3.7 Chapter summary .............................................................................................................. 79
Chapter 4 Review of existing CM (Stage I) .................................................................................... 80
4.1 Approaches to conceptual modelling in practice ............................................................. 80
4.1.1 Principles in conceptual modelling .......................................................................... 81
4.1.2 Methods of simplification ........................................................................................ 82
4.1.3 Modelling frameworks ............................................................................................. 85
4.2 Problems encountered in simulation modelling ............................................................... 86
4.3 Communicating and representing the conceptual model ................................................ 87
4.3.1 Simulation project specification............................................................................... 88
4.3.2 Representing the conceptual model ........................................................................ 89
4.4 Validation of conceptual models ...................................................................................... 91
4.5 Chapter summary .............................................................................................................. 94
Chapter 5 Forming the specification for the SCM2 (Stage II) ........................................................ 95
5.1 Requirements for an ‘effective’ conceptual model .......................................................... 95
5.1.1 Four requirements of a conceptual model .............................................................. 96
5.1.2 Building ‘valid’ and ‘credible’ models ...................................................................... 97
5.1.3 Fundamental need to keep the model ‘simple’ ....................................................... 98
5.2 Requirements for ‘good’ methodologies .......................................................................... 98
5.3 Requirements for conceptual modelling of supply chain problems ............................... 100
5.3.1 Handle the complexity and detail of supply chain improvements ........................ 101
5.3.2 Address a range of supply chain objectives ........................................................... 105
5.3.3 Identify interconnections with the supply setting ................................................. 106
5.4 Chapter summary ............................................................................................................ 106
Chapter 6 Outline design for the SCM2 (Stage III) ....................................................................... 108
6.1 Design issues for developing a ‘good’ methodology ...................................................... 109
6.1.1 General guide for conceptual modelling................................................................ 109
6.1.2 Role of participants in the process of conceptual modelling ................................. 111
6.1.3 Points of entry in the methodology ....................................................................... 112
6.2 Design issues for creating an ‘effective’ conceptual model............................................ 113
6.2.1 Keep the model as ‘simple’ as possible.................................................................. 113
6.2.2 Creating a ‘valid’ and ‘credible’ conceptual model ................................................ 115
6.3 Design issues for the domain specific needs for creating a CM...................................... 117
6.3.1 Opportunities to use a process reference model for creating a CM ..................... 117
6.3.2 Identification of a suitable process reference model for creating a CM ............... 118
6.4 Using SCOR for conceptual modelling............................................................................. 121
6.4.1 Using SCOR to describe supply chain improvements ............................................ 122
6.4.2 Using SCOR to describe supply chain objectives .................................................... 122
6.4.3 Using SCOR to determine the interconnections with the supply setting .............. 124
6.5 Presentation of outline design ........................................................................................ 125
6.5.1 Key concepts to be incorporated into the methodology ....................................... 125
6.5.2 Linking key concepts to phases in the SCM2 .......................................................... 128
6.6 Chapter summary ............................................................................................................ 130
Chapter 7 Detailed design for SCM2 (Stage IV) ........................................................................... 132
7.1 Overview of the SCM2 ..................................................................................................... 132
7.2 Presentation of the development cases ......................................................................... 136
7.2.1 Development case 1: BeerCo ................................................................................. 136
7.2.2 Development case 2: CarCo ................................................................................... 137
7.3 Application of the development cases to refine and detail the SCM2 ............................ 138
7.3.1 Phase 1: Describe the supply problem from the client’s perspective ................... 139
7.3.2 Phase 2: Determine how each objective is to be measured .................................. 144
7.3.3 Phase 3: Determine how each improvement is to be represented ....................... 150

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7.3.4 Phase 4: Determine how the inputs and their sources interconnect .................... 153
7.3.5 Phase 5: Formulation of the model boundary ....................................................... 157
7.3.6 Phase 6: Design of the detail of the model ............................................................ 166
7.3.7 Phase 7: Validate and document the conceptual model ....................................... 172
7.4 Implementing the SCM2 using a spreadsheet application ............................................. 177
7.5 Alignment of detailed design of the SCM2 against specification..................................... 177
7.5.1 Meet the requirements for an ‘effective’ conceptual model ................................ 178
7.5.2 Meet the requirements of ‘good’ methodologies ................................................. 179
7.5.3 Meet the requirements for conceptual modelling of supply chain problems ....... 181
7.6 Chapter summary ............................................................................................................ 182
Chapter 8 Preliminary validation of the SCM2 (Stage V) ............................................................. 184
8.1 Presentation of validation case: CoffeePotCO ................................................................ 184
8.2 Application of SCM2 to preliminary validation case ........................................................ 185
8.2.1 Phase one: Describe the supply problem............................................................... 186
8.2.2 Phase two: Determine how each objective is to be measured ............................. 187
8.2.3 Phase three: Determine how each improvement is to be represented ................ 189
8.2.4 Phase four: Determine the model inputs and source process elements ............... 190
8.2.5 Phase five: Formulate the model boundary .......................................................... 191
8.2.6 Phase six: Designing the model detail .................................................................... 194
8.3 Purpose of the evaluation of the methodology .............................................................. 195
8.3.1 Criteria for evaluating the feasibility of the SCM2 ................................................. 195
8.3.2 Criteria for evaluating the utility of the SCM2 ........................................................ 196
8.4 Evaluation of the initial feasibility of the SCM2............................................................... 196
8.4.1 Evaluation of the availability of information required by the SCM2 ...................... 197
8.4.2 Evaluation of the availability of information provided by the SCM2 ..................... 198
8.5 Evaluation of the initial utility of the SCM2 ..................................................................... 199
8.5.1 Relevance of output derived from the SCM2 ......................................................... 200
8.5.2 Usefulness of the output derived from the SCM2 .................................................. 200
8.5.3 How the methodology could be facilitated............................................................ 202
8.6 Identification of issues for testing................................................................................... 204
8.6.1 Feasibility ............................................................................................................... 204
8.6.2 Utility ...................................................................................................................... 204
8.6.3 Usability.................................................................................................................. 205
8.7 Opportunities to improve the SCM2................................................................................ 206
8.7.1 Role and impact of automating the methodology ................................................. 206
8.7.2 Strengthening the utilisation of domain knowledge ............................................. 207
8.7.3 Development of a web based tool ......................................................................... 208
8.8 Chapter summary ............................................................................................................ 208
Chapter 9 Conclusion and future work ....................................................................................... 210
9.1 Original contribution made by the thesis ....................................................................... 210
9.1.1 Primary research contribution ............................................................................... 211
9.1.2 Secondary research contributions ......................................................................... 217
9.2 Conclusions from the research objectives and questions .............................................. 219
9.2.1 Objective one: Documentation of required specification...................................... 219
9.2.2 Objective two: Development of SCM2 addressing the specification ..................... 220
9.2.3 Objective three: Preliminary validation of the SCM2 ............................................. 221
9.3 Limitations of study ........................................................................................................ 222
9.3.1 Application in different industrial contexts with primary data.............................. 224
9.3.2 Use of different facilitators (potential users) to follow the SCM2 ......................... 224
9.3.3 Validation of the usability of the SCM2 .................................................................. 225
9.4 Implication for further research and practice ................................................................ 225
9.5 Chapter summary ............................................................................................................ 227

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References................................................................................................................................... 229
Appendix A Principles/observations made in the design of the SCM2 ...................................... 251
Appendix B Actual practice to be modelled (BeerCO development case) ................................ 260
Appendix C Actual practice to be modelled (CarCO development case) .................................. 263
Appendix D Illustrations of model components to be developed into a computer model....... 266
Appendix E Example process flow diagrams for the BeerCo development case ...................... 268
Appendix F Flowchart of the CoffeePotCo computer simulation model .................................. 270
Appendix G Comparison of practice to be modelled and CoffeePotCo computer model ........ 271
Appendix H Evaluation of how information is used and provided in the preliminary validation
case ................................................................................................................................ 275
Appendix I Issues for testing the ‘usability’ of the SCM2 ......................................................... 277

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List of figures in thesis
Figure 1.1 Overview of the thesis structure and research programme .................................... 20
Figure 2.1 Classification of supply chain simulation approaches.............................................. 34
Figure 3.1 Overview of research programme ........................................................................... 64
Figure 6.1 Example of SCOR inputs and outputs to a decomposed business process............ 124
Figure 7.1 Overview of the SCM2 ............................................................................................ 133
Figure 7.2 Structure and flows in the BeerCo development case........................................... 137
Figure 7.3 A simplified diagram of CarCo’s supply chain ........................................................ 138
Figure 7.4 ‘Reliability’ metric structure with an example of a level 3 metric ......................... 147
Figure 7.5 Calculation and data collection needs for RL.2.1 % of orders delivered in full ..... 148
Figure 7.6 Extract of the SCOR descriptions of best practices ................................................ 151
Figure 7.7 Example of the inputs of a source process element described in SCOR ................ 154
Figure 7.8 Process elements, inputs, source process element and suggested source actor .. 155
Figure 7.9 Extract of the list of inputs considered for S1.1 in the CarCo development case . 156
Figure 7.10 Extract of how phase four was completed for the CarCo development case ....... 157
Figure 7.11 Extract of the output from phase four that is transferred (in step 5.1) ................ 160
Figure 7.12 Extract of phase five from the BeerCo development case for the Wholesaler ..... 163
Figure 7.13 Template used to check the linkages between processes in the CarCo development
case......................................................................................................................... 165
Figure 7.14 Tracing back the inputs of included processes from a data source ....................... 166
Figure 7.15 ‘Phantoms’ in the CarCo development case (inputs shown for D1.10 SS) ............ 168
Figure 7.16 Extract of actual practice descriptions in the BeerCo development case ............. 169
Figure 7.17 Extract of how actual practices can be ‘consolidated’ for the CarCo development
case......................................................................................................................... 170
Figure 8.1 Graphical illustration of CoffeePotCo supply problem .......................................... 185
Figure 8.2 Interconnection identified for each process element in the model ...................... 190
Figure 8.3 Formulation of the model boundary (CoffeePotCo) .............................................. 191
Figure 8.4 Promoted, core and simplified process elements for the CoffeePotCo validation
case......................................................................................................................... 194
Figure E.1 Retailer plan and place order in BeerCo development case .................................. 268
Figure E.2 Fulfil order in BeerCo development case ............................................................... 269
Figure F.1 Flowchart of computer simulation program for CoffeePotCo ............................... 270

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List of tables in thesis
Table 2.1 Selection of contributions that meet search terms in each academic database ......... 29
Table 2.2 Classification of simulation approaches....................................................................... 35
Table 3.13 Similarities between an iterative triangulation and grounded theory method .......... 61
Table 3.24 Design questions and issues to address the requirements ......................................... 71
Table 3.3 5 Criteria for assessing a process framework or methodology ...................................... 73
Table 3.4 6 Summary of cases used to develop and validate the methodology............................ 76
Table 4.17 Approaches to conceptual modelling .......................................................................... 81
Table 4.28 Research contributions on simulation model simplification (advice and methods) ... 84
Table 4.39 Potential pitfalls in simulation related to conceptual modelling ................................ 86
Table 4.410 Reasons for increasing complexity (some consideration in the SCM domain) ............ 87
Table 4.511 Methods used to document CM with examples in the SCM literature ....................... 90
Table 5.1 Four requirements for a conceptual model ................................................................. 96
Table 5.2 Platts (1994) characteristics of successful strategy formulation methodologies ...... 100
Table 5.3 Identification of the complexity of a supply problem ................................................ 103
Table 5.4 Identification of the detail of supply chain improvements ........................................ 104
Table 5.5 Aims and requirements for the SCM2 ........................................................................ 106
Table 6.1 Proposed stages for conceptual modelling in general suggested in the literature ... 110
Table 6.2 Incorporating model simplification advice and methods into a methodology .......... 114
Table 6.3 Documentation and validation requirements for the SCM2 ...................................... 116
Table 6.4 Role of domain knowledge in conceptual modelling ................................................. 117
Table 6.5 Comparison of supply chain process reference models ............................................ 120
Table 6.6 Domain knowledge offered by SCC SCOR model ....................................................... 121
Table 6.7 Examples of two typical supply chain problems ........................................................ 122
Table 6.8 Example of SCOR detail extracted for improvements ............................................... 122
Table 6.9 Example of extracting SCOR performance measures ................................................ 123
Table 6.10 Key concepts to be included in the design of the SCM2 ............................................ 126
Table 6.11 Linking key concepts, conceptual modelling process with phases in the SCM2 ........ 128
Table 6.12 Outline of the methodology: Phases, inputs and outputs......................................... 130
Table 7.1 Detailed steps for phase one of the SCM2 ................................................................. 140
Table 7.2 Description of the objective(s) of study ..................................................................... 141
Table 7.3 Illustration of the description of the improvements selected ................................... 142
Table 7.4 Illustration of the description of the supply problem setting .................................... 143
Table 7.5 Illustration of how each improvement could achieve each objective ....................... 143
Table 7.6 Detailed steps for phase two of the SCM2 ................................................................. 146
Table 7.7 Description of the supply chain metrics..................................................................... 147
Table 7.8 Description of calculation and data source requirements for each metric ............... 149
Table 7.9 Description of the nature of measurement for each metric in both development cases
.................................................................................................................................... 149
Table 7.10 Detailed steps for phase three of business methodology ......................................... 150
Table 7.11 List of processes at three levels of process detail that represent each SCIO ............ 152
Table 7.12 List of actors associated with each business process ................................................ 152
Table 7.13 Detailed steps for Phase 4 of the SCM2 ..................................................................... 154
Table 7.14 Detailed steps for phase 5 of the SCM2 ..................................................................... 159
Table 7.16 Model components, definitions and examples (in the BeerCo development case) . 171
Table 7.18 Aligning the SCM2 to meet the requirements for an ‘effective’ model ..................... 178
Table 7.19 Meet the requirements of ‘good’ methodologies ..................................................... 180
Table 7.20 Meet the requirements for CM of supply chain problems........................................ 181
Table 8.1 Statement of the supply problem (CoffeePotCo) ...................................................... 186
Table 8.2 Statement of each objective to be measured (CoffeePotCo) .................................... 188

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Table 8.3 Statement of how each process represents each improvement (CoffeePotCo) ....... 189
Table 8.4 Promoted process elements and simplified inputs (CoffeePotCo) ............................ 192
Table 8.5 Candidate process elements promoted in each round (CoffeePotCo)....................... 193
Table 8.6 Summary of the feasibility criteria to be examined ................................................... 195
Table 8.7 Summary of the utility criteria to be examined ......................................................... 196
Table 8.8 Key observations from an analysis of the information requirements for the SCM2 .. 198
Table 8.9 Key observations from an analysis of the information provided from the SCM2 ...... 199
Table 8.10 Evaluation of ‘facilitation’ when using SCOR ............................................................. 203
Table 8.11 Summary of the usability criteria to be examined .................................................... 205
Table 8.12 Opportunities to automate aspects of the SCM2 ...................................................... 207
Table 9.1 Research contribution made by this thesis................................................................ 211
Table 9.2 SCM2: Procedure and key concepts for SCM applications ......................................... 214
Table 9.3 Summary of issues for future testing ......................................................................... 223
Table 9.4 Revisiting Robinson (2006a; 2006b) issues in CM ..................................................... 226
Table A.1 Principle/observations when designing phase one ................................................... 251
Table A.2 Principle/observations made that included the design of phase two ....................... 252
Table A.3 Principle/observations made that influenced the design of phase three ................. 253
Table A.4 Principle/observations made that influenced the design of phase four ................... 254
Table A.5 Principle/observations when designing phase five .................................................... 255
Table A.6 Principle/observations when designing phase six ..................................................... 257
Table A.7 Principle/observations when designing phase seven ................................................ 258
Table D.1 Model components for ‘Retailer plan and place order’ (BeerCo development case) 266
Table D.2 Model components for ‘Wholesaler Receive and fulfil order’ (BeerCo development
case) .................................................................................................................................... 267
Table G.1 AS-IS Scenario in CoffeePot Co validation case for the ‘Customer’ ........................... 271
Table G.2 AS-IS Scenario in CoffeePotCo validation case for the ‘Warehouse’ ......................... 272
Table G.3 AS-IS Scenario in CoffeePotCo validation case for the ‘Factory’ ................................ 273
Table G.4 TO-BE Scenario in CoffeePotCo validation case for the ‘Factory’ .............................. 274
Table H.1 Evaluation of how the SCM2 uses information........................................................... 275
Table I.1 Issues for testing the ‘usability’ of the SCM2 ............................................................. 277

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Chapter 1 Introduction
Chapter one discusses the context of the research project for the development, refinement and
preliminary validation of a simulation conceptual modelling methodology for supply chain
management applications (termed the ‘SCM2’). It describes the background to the research,
research objectives, questions and programme to address each objective, justification for
research focus, main body of the thesis, and the extent of the scope and definitions used in the
research project.

The research is bounded within the ‘simulation’ literature with a focus on the ‘conceptual
modelling’ stage of a simulation project in the context of ‘SCM’ applications. The research
objectives and questions address the need to form a specification for, develop and refine and
initially validate the feasibility and utility of the SCM2 proposed in this thesis. A five stage research
programme is designed to realise the aims and objectives of this research and address each of the
questions posed. This includes reviewing existing conceptual modelling practices (stage I,
presented in chapter four), forming the specification for the SCM2 (stage II, presented in chapter
five), outlining the design for the SCM2 (stage III, presented in chapter six), detailing and refining
the design for the SCM2 (stage IV, presented in chapter seven) and a preliminary validation of the
SCM2 (stage V, presented in chapter 8). The research programme adopts an iterative
triangulation method to systematically iterate between extensive literature review, existing case
evidence and intuition. Three typical and complex supply problems are used to refine and
preliminarily validate the methodology.

1.1 Research background
The research focuses upon the creation of simulation conceptual models for supply chain
applications. The methodology is developed within the supply chain management discipline for
participants undertaking the conceptual modelling stage as part of a simulation project. This
focus is original and significant because the need for a greater understanding of conceptual
modelling is required; particularly the development of structured approaches, as no simulation
conceptual modelling methodologies exists in the SCM domain. Both the wider discipline and the
particular focus of this thesis are briefly discussed to provide some background to the project.

The origins of the use of the term ‘supply chain management’ (SCM) can be traced back to the
early 1980s (Houlihan, 1987); over the last three decades the prominence and importance of the
discipline has grown at an escalating rate. During this period, similar terms such as ‘network
sourcing’, ‘supply pipeline management’ and ‘value chain management’ have been subjects of

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interest, for both theory and practice (Christopher, 2004; Hines, 1994; Lamming, 1996; Saunders,
1995, 1998; Croom, Romano and Giannakis, 2000).

There has also been some debate over whether supply chain management is itself a
distinguishable discipline in its own right (e.g. Croom et al., 2000; Harland, Lamming, Walker,
Phillips, Caldwell, Johnsen, Knight and Zheng, 2006). Harland et al., (2006) judged SCM to be an
emerging discipline, providing evidence that existing research contributions lack quality of
theoretical development, discussion and coherence. In relation to practice, there is widespread
agreement that SCM is critical to organisational performance (e.g. Tan, Kannan and Hardfield,
1999; Kannan and Tan, 2005; Li, Ragu-Nathan, B., Ragu-Nathan, T.S., and Subba-Roa, 2006).
Additionally as a field of study, it has gained significant momentum, as new opportunities exist to
develop new theories, concepts and tools that could be applied in practice.

Despite the popularity of the term ‘SCM’ both in academia and in practice there has been
considerable confusion as to its meaning (Mentzer, Dewitt, Keebler, Min, Nix, Smith and Zacharia,
2001). Some authors have defined SCM in operational terms involving the flow of materials and
products, some view it as a management philosophy and some view it in terms of a management
process (Tyndall, Gopal, Patsch and Kamauff 1998). Mentzer et al., (2001) reviewed, categorised
and synthesised a view of what constitutes SCM from definitions used in both research and
practice in order to reduce this ambiguity. Mentzer et al., (2001, pg. 4) contended that a supply
chain can be defined as 'a set of three or more entities (organisations or individuals) directly
involved in the upstream and downstream flows of products, services, finances, and/or
information from a source to a customer'. This definition is similar to Christopher’s (2004)
definition as it highlights the structure, linkages and flows in a supply chain. In relation to
Christopher (2004) he also highlights how processes and activities ‘add value’ to a product and
service. From a strategic management perspective, ‘value’ concerns what Tan, Kannan and
Hanfield, (1998) describes as the utilisation of resources and capabilities to build competitive
advantage. The term ‘supply strategy’ has also been suggested as a way to move SCM from a
predominantly operational domain (relating to the flow of material and information) to one that
also considers strategic aspects (Harland, Lamming and Cousins, 1999).

Simulation has been used as a method to evaluate the complexity of supply chain problems (e.g.
Ridall, Bennet and Tipi, 2000; Huang, Lau and Mak, 2003; Van der Zee and Van der Vorst, 2005). It
is regarded as the proper means for supporting decision making on supply chain design (Van der
Zee and Van der Vorst, 2005). One important component of a simulation modelling process is the

15

need to create a conceptual model. However it is the least understood aspect in the process
(Law, 1991; Robinson, 2004a; 2004b, 2008a; 2008b). The need to formulate the problem
precisely has appeared in all descriptions of how to conduct a simulation project (e.g. Shannon,
1975; Law and Kelton, 2000), although perhaps the first use of the term ‘model conceptualisation’
can be found in Musselman (1994). After this period the term and discussions of conceptual
modelling practice have become more common (e.g. Robinson and Bhatia, 1995; Balci, 1997; Law,
2003) and, more recently, some definitions have been offered (e.g. Banks, 1999; Robinson, 2004a;
2004b; 2008a; 2008b).

A simulation model in the context of evaluating supply chain problems can be defined using Pidd’s
(1998) definition. A simulation model for SCM applications is a representation of the supply
system, used to investigate possible improvements and the effect of these improvements in the
real world setting of the supply problem. The conceptual model is a non-software specific
description of the simulation model to be developed (Robinson, 2004a; 2004b). It describes the
supply chain problem in terms of the objective of the study, improvements selected to improve
performance within its defined supply setting, the content of the model and any assumptions and
simplifications incorporated into the model. More specifically, using Banks’ (1991) terms, the
content concerns the relationships between the components and structure of the supply system.
These are described in terms of the scope (the components and relationships that need to be
included in the model to define its structure) and detail necessary to represent the actual
practices to be modelled.

1.2 Research aims, objectives and programme
The aim of the research presented in this thesis is to:

“Develop, refine and preliminarily validate a methodology that utilises domain-
knowledge combined with a procedure that can be followed to create a simulation
conceptual model for SCM applications”

This aim is fulfilled by achieving three research objectives:
1. Objective One – Document a specification of the requirements for creating simulation
conceptual models for SCM applications
2. Objective Two - Develop and refine a methodology that can meet the specification of the
requirements for creating simulation conceptual models for SCM applications
3. Objective Three – Preliminarily validate the initial feasibility and utility of the
methodology to create simulation conceptual models for SCM applications

16

A five stage research programme has been designed which contributes to the attainment of each
of the research objectives noted previously. An iterative triangulation method is justified to
ground theory development using existing case applications. This method is used to apply the
SCM2 to typical and complex supply problems to firstly refine and secondly preliminarily validate
the procedure to be followed that incorporates the use of domain-knowledge. The process
iterates between case evidence, reviewed literature and intuition to develop knowledge prior to
rigorous testing so that the SCM2 can be extended into a cohesive theory (testing is noted as
further work).

The first objective identifies a specification of the requirements for a simulation conceptual
modelling methodology for SCM applications. To achieve this two research questions are posed:

1. How are simulation conceptual models created in the context of supply chain
applications?
2. What is the specification of a simulation conceptual modelling methodology for evaluating
supply chain problems?

These questions form the basis of stage I (Review of existing conceptual modelling practice,
discussed in chapter four) and stage II (Required specification for the SCM2 to be developed,
discussed in chapter five) of the research programme. A review of existing conceptual modelling
practice in the domain of SCM demonstrates the need for a methodology that can be followed for
SCM applications. Following on from this, a specification is detailed for an effective conceptual
model, characteristics of a good methodology, and the requirements for evaluating supply chain
problems.

The second objective develops and refines a methodology that can meet the specification of the
requirements for creating simulation conceptual models for SCM applications. To achieve this
objective, one research question is posed:

3. Can a simulation conceptual modelling methodology be developed to meet the required
specification?

This question forms the basis for stage III (outline design for the methodology, discussed in
chapter six) and stage IV (detailed and refined design for the SCM2, discussed in chapter seven) of
the research methodological programme. The methodology is grounded in existing conceptual
modelling practice and ten key concepts are identified to be incorporated into a general process
for conceptual modelling. The methodology is refined through the application of two typical and

17

complex supply chain development cases before the revised design is aligned to show that it
meets the specification of the requirements.

The third and final objective provides a preliminary validation of the initial feasibility and utility of
the methodology to create simulation conceptual models for SCM applications. To achieve this
objective, one research question is posed:

4. Can the methodology be followed (feasibility) and aid a user (utility) to create a simulation
conceptual model for a SCM application?

This question forms the final stage, stage V (preliminary validation of the SCM2, discussed in
chapter eight) of the research methodological programme. This addresses two of Platts (1993)
criteria for testing a methodology, process, or framework. It is argued that both the feasibility
and utility of the methodology can be initially validated by applying it to a different supply chain
problem. The validation case is a supply chain problem which has been evaluated by a simulation
approach and published in the academic literature (see Taylor, Love, Weaver and Stone, 2008). It
is used to compare the actual practices that have been identified by the methodology with the
model components and interconnections that are included in the computer model. The validation
case is also used to suggest how the feasibility and utility of the methodology should be further
tested and how further work should include tests for its ‘usability’. The discussion also identifies
and considers some opportunities to develop a web-based application tool to improve the
accessibility and efficiency of the methodology.

1.3 Justification for the research focus
Effective SCM is critical to any organisation’s ability to compete effectively (Stewart, 1997), which
has led to organisation’s seeking ways to improve supply chain performance. The difficulty when
evaluating supply chain problems is that they are inherently complex and dynamic systems (e.g.
Davis, 1993; Levy, 1994; Beamon, 1998). Simulation is one approach that is often cited as a
method that can be used to evaluate complex and dynamic systems (e.g. Ridall et al., 2000; Huang
et al., 2003; Van der Zee and Van der Vorst, 2005); the extent of research that has used simulation
as a method to evaluate supply chain problems is great.

In a typical supply chain project there is one stage that is often regarded as the most important:
the process of creating a conceptual model (Law, 1991). Robinson (2008b) points out that there is
surprisingly very little written on the subject; except in Robinson’s (2004b) simulation text. Even
when looking at this text only a handful of pages are dedicated to the subject and in the wider
literature there is a distinct lack of research contributions. Research can be identified on
18

understanding the importance of ways of thinking of tackling a simulation problem (e.g. Nance,
1994; Robinson, 1994; Brooks and Tobias, 1996). This has yet to deliver structured approaches for
creating a conceptual model. Although some guiding principles, methods for simplifications, and
frameworks for completing the stage as part of a simulation project can be found. In an attempt
to remedy this situation a stream was organised at the Operational Research Society Simulation
Workshop in 2006. Robinson (2008b) noted that this stream represented the highest number of
concentrations of papers on this topic in comparison to previous journals or conference papers.
This was a major motivation for this research, particularly as the majority of work was at a
conceptual (early) stage. In addition the majority of contributions was based on manufacturing
problems and had not explicitly addressed the needs of SCM.

This thesis demonstrates that the complexity and dynamic behaviour inherent in supply chains
presents a different set of requirements. The problems are not confined to a single organisation
and the improvements that an evaluator may wish to experiment with are much wider and, on
the whole, different from manufacturing problems. This thesis also suggests ten key concepts
that could form the basis of a methodology for creating simulation conceptual models for SCM
applications. In particular, the research argues that there is a significant opportunity to utilise
domain knowledge from a published supply chain process reference model (e.g. Supply Chain
Council SCOR model) aligned with a general process for conceptual modelling.

The intention of the work is to enable relevant and significant advances for conceptual modelling
as an area that requires further research, practice and the teaching of simulation. The
methodology requires further work to enable an application to be developed that incorporates
the methodology, made accessible for potential users to benefit from. In addition to this primary
contribution a number of secondary contributions are suggested that should provide avenues for
further study and advancement.

1.4 Outline of the thesis
The thesis is organised into nine chapters and four main parts, as depicted in figure 1.1. These
parts include the introduction, development of the research aim, objectives and programme,
research programme implementation and conclusions.

19

Introduction • Chapter 1: Introduction to research project

Development • Chapter 2: Research issues in simulation
of research conceptual modelling for SCM
applications
aim, objectives • Chapter 3: Research programme for
and developing, refining and preliminary
programme validating the SCM2

• Chapter 4: Stage I: Review of
existing simulation
conceptual modelling practice
• Chapter 5: Stage II: Forming
the specification for the SCM 2
• Chapter 6: Stage III: Outline
Research design for the SCM2
programme • Chapter 7: Stage IV: Detailed
implementation and refined design for the
SCM2
• Chapter 8: Stage V:
Preliminary validation of the
initial feasibility and utility of
the SCM2

• Chapter 9: Conclusions and future
Conclusion implications of the research

Figure 1.1 Overview of the thesis structure and research programme

The contribution of the remaining chapters in this thesis can be summarised:

Chapter 2 Discusses the research issues in simulation conceptual modelling for SCM
applications. It demonstrates that there is a gap for the development of the SCM2
and that is both original and significant. The importance of evaluating supply
chain problems to improve organisational performance is discussed. This is
followed by highlighting the complexity of evaluating supply problems.
Simulation is argued as one major approach that can address the complexity of
supply chain problems. An aspect of a simulation project that is not well
understood but is of crucial importance is the process of conceptual modelling.
There are no guidelines available to follow in order to create a conceptual model
for SCM applications, therefore the development of a methodology is argued as a
way to address this need. The benefits to both research and practice are
identified.

20

Chapter 3 Presents an overview of the research programme and methods to address the
aim and objectives of the research project. The stages that should be included in
the programme are justified and suitable methods are identified for each stage.

Chapter 4 Presents the implementation of stage I of the research programme by reviewing
existing simulation conceptual modelling practice in the context of SCM
applications. The chapter establishes the need for the methodology.
Approaches to conceptual modelling are identified and reviewed to show that no
methodology exists that delivers the aim of this research. It also discusses the
problems encountered in a simulation project that could benefit from a greater
understanding and structured methods for conceptual modelling. The methods
of communicating and representing the conceptual model and how conceptual
models have been validated are identified as two aspects that warrant greater
discussion.

Chapter 5 Presents the implementation of stage II of the research programme by forming a
specification for the SCM2. The methodology is founded upon existing conceptual
modelling practice and the requirements for, an effective conceptual model, a
good methodology and for conceptual modelling within the domain of SCM. The
specification is detailed so that the methodology can be developed to meet the
requirements.

Chapter 6 Presents the implementation of stage III of the research programme by outlining
a design for the SCM2. The chapter brings together and suggests ten key concepts
from a review of the design issues for each of the requirements identified in
chapter five. The proposition developed in the chapter is that a procedure for
the SCM2 can utilise domain knowledge from a supply chain process operations
model to enable a more focused and efficient process.

Chapter 7 Presents the implementation of stage IV of the research programme by detailing
a developed and refined design for the SCM2. Two typical and representative
supply chain development cases are used to refine the methodology. The ten key
concepts identified in chapter six are incorporated into a procedure for the
methodology. Each of the phases is discussed in turn so that the specific steps,
information needs, participation requirements and points of entry can be

21

detailed. The chapter concludes by aligning the detailed design to demonstrate
that the specification presented in chapter five has been met.

Chapter 8 Presents the implementation of stage V of the research programme by
preliminarily validating the initial feasibility and utility of the SCM2 to a different
supply chain problem. The validation case is used to walkthrough the steps to
demonstrate that they can be followed to create a simulation conceptual model.
The validation only considers the phases up to the point that the actual practices
to be included in the model are detailed, after this point existing modelling
practice is adopted. It also enables a comparison between a successful computer
model, which has been published in the literature, to be compared to a list of
actual practices identified by the methodology. Issues for future testing are
discussed and an opportunity to simplify and automate aspects of the process in a
tool that utilises published domain knowledge is considered.

Chapter 9 Concludes the thesis and discusses the future implications for the research. It
details the primary and secondary contributions made by this thesis. The
research aim and objective is reviewed to demonstrate that they have been met
and that the research programme was both suitable and rigorous. Limitations of
the work are described and implications for further study are identified.

1.5 Delimitation of scope and definitions
The research focuses upon the creation of simulation conceptual models for supply chain
applications rather than conceptual modelling in general. The implication of this is that the
methodology presented in this thesis is intended for participants who are undertaking a
simulation project with a supply chain problem. The analysis and information provided by the
methodology would be different in other domains (e.g. manufacturing, service). Nevertheless,
outside this scope the research has many implications for the key concepts incorporated into the
methodology that could be applied in other domains (e.g. how to formulate the model boundary).
Within this scope there are a number of considerations that need to be raised:
1. Definition of a supply problem
2. What constitutes a simulation conceptual model for SCM applications
3. Limitations of the research programme

22

The term ‘supply problem’ is used to incorporate the improvements that have been selected to
improve performance for a given objective within the setting of the supply problem. This term is
used as it identifies that a supply problem can be made up of a range of improvements (e.g.
improve supply chain visibility), to achieve a range of supply chain performance measures (e.g.
responsiveness, cost) within the setting of the supply problem (e.g. linkages between suppliers
and customers). In relation to the latter, conceptual modelling involves formulating an
understanding of what should be included within the simulation study. This presents an issue of
determining only the necessary model components and interconnections that represent the
actual practices of the real world problem. The term should not be confused with the term supply
“chain”, or even “network”. A supply chain/network has a specific definition which includes the
‘entities directly involved in the upstream and downstream flows of products, services, finances,
and/or information from a source to the customer’ (Mentzer et al., 2001, pg. 4). This
demonstrates that the term ‘supply problem’ defines more than the structure and flows in a
supply system but also how it is to be improved and how performance will be measured.

The research is bounded within the ‘simulation’ literature with a focus on the ‘conceptual
modelling’ stage of a simulation project. Definitions do exist for conceptual modelling in general
but there is considerable debate into what is described by a simulation conceptual model
(discussed in section 2.1). The majority of the work in this thesis is underpinned by the major
advances made by Robinson, most notably in his 2004 text on ‘simulation practice and
application’ and associated publications. These have considered effective conceptual modelling
(Robinson, 1994) issues for conceptual modelling research and practice (2006a; 2006b; 2008a)
and the development of a general framework (Robinson, 2004a; 2004b; 2006a; 2006b) which has
until recently been illustrated (Robinson, 2008b). Robinson’s definition for a conceptual model is
adopted in this thesis and used to further a definition for what constitutes a methodology that
can be followed to create a conceptual model for SCM applications.

A conceptual model is defined as:
‘...a non-software specific description of the simulation model that is to be developed,
describing the objectives, inputs, outputs, content, assumptions and simplifications of the
model’
Robinson (2004b, pg. 65)
In the context of this thesis the methodology delivers:
‘A methodology that offers a prescribed procedure that guides the participants
undertaking the conceptual modelling stage of a simulation project, to create a non-
software specific description of the simulation model to be developed, in the context of
SCM applications’

23

The definitions provide some useful distinctions that have shaped this research project. This
includes that the definitions view the process of conceptual modelling as independent from
particular simulation software. The intention of this research is to not be biased by any particular
software used by the researcher. However, when describing the model components a modeller
may have a particular simulation worldview (Pidd, 2004b; Owen, Love and Albores, 2008) which
will have a bearing on the way in which the computer model to be developed is described. For
this reason the methodology incorporates general terms and practice for describing the
components in the model. The implication of this is that only the original aspects of the
methodology are applied and tested.

The preliminary validation is used to illustrate the initial feasibility and the utility of the
methodology. The actual practices to be included in the computer model are compared to the
components and interconnections that form the design of the computer model presented in
Taylor et al., (2008). The supply problem evaluated in Taylor et al., (2008) is simulated using a
discrete-event simulation approach. The research notes to be able to generalise the feasibility
and utility of the methodology it would require further applications in different industrial contexts
and with actual participants. This would also involve testing the general usability of the
methodology.

1.6 Chapter summary
The aim of this research is to develop, refine and preliminarily validate the initial feasibility and
utility of a simulation conceptual modelling methodology for SCM applications. The research
objectives are designed to realise this aim. These include:
Documenting a specification of the requirements for creating simulation conceptual
models for SCM applications

Developing and refining a design of the methodology that meets the specification

Validating the initial feasibility and utility of the methodology.

The research focuses on creating conceptual models that describe how a supply problem can be
described so that a computer model can be developed. This is identified as an original and
significant area for research as no methodologies exist that can meet the research aim.
Particularly there is a need to develop structured approaches that can guide participants through
the process of conceptual modelling as part of a simulation project within the domain of SCM.

24

A five stage programme has been designed to achieve the aim and objectives set out in this thesis.
This includes a review of existing conceptual modelling practice (stage I, implemented in chapter
4), forming the specification for the SCM2 (stage II, implemented in chapter 5), outlining a design
for the SCM2 (stage III, implemented in chapter 6), detailing and refining the design of the SCM2
(stage IV, implemented in chapter 7) and a preliminary test of the SCM2 (stage V, implemented in
chapter 8). An iterative triangulation research approach is adopted to iterate between an
extensive literature review, application of the methodology to three representative and typical
supply chain problems and intuition. Two existing cases are used in the design and refinement
stages, and one to illustrate the initial feasibility and utility of the methodology.

The methodology is developed for the purpose of creating a conceptual model for supply chain
applications, not for general purposes. The preliminary validation is used to illustrate that the
actual practices to be represented in the computer model can be derived by following the steps as
laid down in the methodology. The components and relationships between them, that form the
description of the computer model developed in Taylor et al., (2008) are compared to the actual
practices described by following the methodology to discuss any similarities, omissions or
significant differences. Future testing is outlined in this thesis to improve the validity and wider
applicability of the methodology in different applications and involvement of potential users.

25

Chapter 2 Research issues in conceptual modelling for SCM
applications
This chapter identifies and discusses the relevant research issues in conceptual modelling for SCM
applications. The aim is to demonstrate that a gap exists for a simulation conceptual modelling
methodology for SCM applications that is original and significant. This gap is filled by developing
and preliminary validating a simulation conceptual modelling methodology for SCM applications.

This chapter is structured to demonstrate this gap by considering the following research issues:
Scope and selection of contributions in literature review (section 2.1) – States that the
research is bounded within the simulation conceptual modeling literature with a
particular focus on SCM applications
Importance of evaluating supply chain problems (section 2.2) - Discusses the importance
of evaluating supply problems as one significant way to improve performance
Complexity of evaluating supply chain problems (section 2.3) – Demonstrates that
evaluating supply chain problems is extremely complex
Role of simulation to evaluate supply problems (section 2.4) – Identifies that simulation
is one approach that can address the complexity of supply problems. The range of
approaches used in simulation is overwhelming and the amount of research using
simulation is great.
Role of conceptual modelling in simulation projects (section 2.5) - Identifying that
conceptual modelling is an important and critical aspect in a simulation modelling
process.
Understanding of conceptual modelling for SCM applications (section 2.6) -
Demonstrating that conceptual modelling is the least understood aspect of a simulation
project and no guidelines exist for SCM applications. A gap exists in the literature that can
be filled by the aim and focus of this thesis.
Usefulness of a conceptual modelling methodology for SCM applications (section 2.7) -
Proposes that a methodology would be a useful way to guide participants through a
complex supply problem to describe how it could be modelled
Benefits of developing a conceptual modelling methodology for SCM applications
(section 2.8) - Showing that a methodology would yield benefits to practitioner users

26

2.1 Scope and selection of contributions in literature review
The scope of the literature review gathers contributions on ‘conceptual modelling’ for ‘simulation’
purposes within the domain of ‘SCM applications’. The term ‘conceptual modelling’ has however
been used much more widely in the general management literature. In general a conceptual
model is a ‘set of concepts, with or without propositions, used to represent or describe (but not
explain) an event, object, or process’ (Meredith, 1993). The description is also used as a means of
communicating a set of requirements between stakeholders involved in a project. Using this
general definition there are a number of application areas that have used the term ‘conceptual
modelling’; examples include:
Architecture, engineering and construction – e.g. Krause, Luddeman and Striepe (1995)
for industrial design; Turk (2001) on conceptual product modeling; Shane (2005) on
conceptual modeling in urban design and city theory
Business management – e.g. Carrol (1979) for conceptual modeling of corporate
performance and Parasuraman (1985) describe a conceptual model of service quality
Computing and web engineering – e.g. Thompson (1991) personal computer utilisation
Information systems development – e.g. Olive (2007) for conceptual modelling of
information systems; Mendes et al., (2006) for conceptual modelling of web applications
and Schewe and Thalheim (2005) for conceptual modelling of web information systems
Research methods – e.g. Meredith (1993) discuss theory building through conceptual
methods; Hair et al., (2007) discuss conceptualisation and research design in general.

There are three notable differences that distinguish ‘simulation conceptual modelling’ from the
application areas noted above. This includes the domain to be represented, scope and level of
abstraction and the process to be followed to create a conceptual model. For instance, an
architectural conceptual model could include a model replica of a bridge to a particular scale. In
simulation conceptual modeling the requirement is to describe the computer model to be built.
This includes the inputs, outputs, content (involves determining the scope and level of detail),
assumptions and simplifications (Robinson, 2004). The process to identify these requirements
moves from a problem situation, through model requirements to a definition of what is going to
be modeled and how it is to be done (Robinson, 2008a). A procedure for simulation conceptual
modeling must provide guidelines on how this is to be achieved, which is heavily dependent upon
the domain (e.g. supply chain) being represented.

One particular approach that has been used in the context of simulation conceptual modeling
includes Checkland (1981) ‘soft system methodology’ (SSM) to determine the simulation study
27

objectives (see Kotiadis, 2007). SSM includes a stage for building a conceptual model to describe
activities and processes from a root definition (problem statement). In this instance, the
conceptual model is represented as a rich picture that captures a human system of issues, actors,
problems, processes, relationships, conflicts and motivations. Kotiadis (2007) argues that the
study objectives are the most critical part of a simulation study which benefits from using SSM as
a problem structuring method. This is however, only the first step of the process of creating a
simulation conceptual model. SSM does not explicitly guide a modeller through the decisions
necessary to determine the scope and level of detail (model content) or even incorporate any
necessary assumptions and simplifications into the model design (e.g. specific techniques such as
aggregate model components).

The literature review selection criterion has focused upon conceptual modelling for the purposes
of simulation, particularly in the SCM domain using the terms shown in table 2.1. It was also
necessary to include a wider search for operations management research as this is often used as
an umbrella term. The key words ‘supply chain’ were adopted over ‘supply chain management’ to
provide a more exhaustive list. Secondly, more specific searches were undertaken to establish a
more focused body of knowledge that discusses ‘conceptual modelling’. The term ‘conceptual
model’ was also searched recognising that ‘conceptual modelling’ relates to the process that
creates a ‘conceptual model’. The literature was searched in four primary academic databases
used in management research along with the WinterSim conference (annual simulation
conference) and a dedicated Workshop that addressed a call for more research into simulation
conceptual modelling (Operational Research Society Simulation Workshop, 2006). The
conference contributions accounted for some of the earlier and latest contributions on simulation
conceptual modeling.

28

Table 2.1 Selection of contributions that meet search terms in each academic database
Search terms
Simulation Simulation Simulation Simulation
Academic Simulation AND AND AND AND
Simulation Simulation
literature AND “conceptual “conceptual “Conceptual “Conceptual
AND Supply AND
database “conceptual modelling” modelling” model” AND model” AND
chain Operation
modelling”1 AND AND supply Operation “Supply chain”
operation chain
ABI/Inform
Global 499 226 11 0 1 9 1
Proquest
EBSCO
(Business
408 313 9 2 2 12 1
Source
Complete)
Emerald 88 50 7 1 1 2 1
Science
45 56 161 19 1 44 17
Direct
Informs
727 1,720 72 32 16 131 60
online2

2.2 Importance of evaluating supply chain problems
Managing supply-chain operations is critical to any company’s ability to compete effectively
(Stewart, 1997). Over the past two decades there has been an acceleration of interest in the
analysis, management and control of supply chains (e.g. Gattorna and Walters, 1996; Beamon,
1998; Petrovic, 2001; Christopher and Towill, 2002; Persson and Olhager, 2002; Shepherd and
Gunter, 2006; Gunasekaran and Ngai, 2008; Fildes, Goodwin, Lawrence and Nickolopoulos, 2009).
Whether it is by coordination of activities through the supply chain or by recognising the
capabilities of immediate suppliers, understanding supply chain dynamics has a significant impact
on performance (e.g. Tan et al., 1999; Kannan and Tan, 2005; Li et al., 2006).

Supply chain management represents one of the most significant paradigm shifts of modern
business management by recognising that individual businesses no longer compete as solely
autonomous entities, but rather as supply chains (Christopher, 1992, 1998; Lambert and Cooper,
2000; Spekman, Spear and Kamauff, 2002; Cousins and Spekman, 2003; Chen and Paulraj, 2004).
This has led both researchers and practitioners, to consider improvements and practices outside
the boundaries of an organisation (with suppliers and customers in a network, chain or
partnership) and ways to effectively manage and control the supply chain. The term ‘supply
strategy’, coined by Harland (1997), has been one significant attempt to move away from a
traditional view of the flows between suppliers and customers to one that considers a more
holistic approach to managing the entire supply network. As a field of study and practice there
has been a whole host of other attempts to move research from an embryonic stage (suggested

1
UK spelling is ‘modelling’ while in US dictionary it is spelt ‘modeling’; accounted for in the search
2
Wintersim and Operational Research Society Simulation Workshop (accessed via www.informs-sim.org)

29

by Handfield and Melnyk, 1998; Chen and Paulraj, 2004); to one that has more scientific
development and recognition as a discipline in its own right (Croom et al., 2000).

There has also been a considerable interest to describe supply chain management, its activities,
practices and ways to measure supply chain performance. In earlier years this was a distinct issue
in SCM (New, 1997; Tan, 2001) but has been dramatically improved with recent research
contributions. Most notably the advent of supply chain process frameworks developed by the
Global Supply Chain Forum (e.g. Cooper, Lambert and Pagh, 1997; Croxton, Garcia-Dastugue,
Lambert and Rogers, 2001; Lambert et al., 2005) and the Supply Chain Council (SCOR v.9, 2008)
with considerable input from industry may have been a catalyst. These frameworks have been
used to describe, analyse and evaluate improvements to a supply system in order to improve
decision-making on ways to improve supply chain performance (e.g. Arns, Fischer, Kemper and
Tepper, 2002; Bolstorff and Rosenbaum, 2003; Wang, Huang and Dismukes, 2004; Ball, Love and
Albores, 2008; Persson and Araldi, 2009).

The ability to evaluate the potential performance of supply chain opportunities is a critical
component of the supply chain improvement process. The challenge companies’ face is how best
to evaluate the potential of the host of supply chain improvement options that could be pursued
(Weaver, Love and Albores, 2006; 2007). Many of these improvement options have been
discussed in the literature (e.g. Supply Chain Council 2008; Van der Vorst and Beulens 2002;
Christopher, 1998; Berry et al., 1994). The fact that the Supply Chain Council suggests 420
different improvement options, demonstrates the considerable scope of the evaluation challenge.
Even when this number is reduced (e.g. Van der Vorst and Beulens (2002) presents a generic list
of 21 supply chain redesign options) it still presents a challenge to identify the most suitable
options based on the improvements in performance an organisation would realise.

Companies have far too often attempted to optimise their own value chains, without considering
the effect of these decisions on their suppliers or customers (Chopra and Meindl, 2004). For
instance, Cooper et al., (1997) have shown that sub-optimisation of a company’s own
performance rather than optimising the performance of the entire supply network, by integrating
its goals and activities with other organisations, can destroy value-creating opportunities.
Approaches (e.g. methods, frameworks, methodologies) that could aid in the process of
evaluating the value-creating potential of implementing alternative supply chain improvements
for an organisation and its members in a supply network would be useful. They could help to

30

maximise an organisation’s performance and the benefits received up (towards the ultimate
customer) and down the supply chain.

2.3 Complexity of evaluating supply chain problems
A definition of a supply system was offered in section 1.1. It recognised that the entities comprise
a number of actor (or roles, facilities) that make up the structure of the supply and demand chain
in which an organisation (e.g. manufacturing, retail or third sector) sits between. The complexity
of the supply chain arises from the number of echelons in the chain and the number of actors in
each echelon (Beamon, 1998).

The supply system can vary in complexity (e.g. size). Harland (1997) identified different levels of
supply, consisting of supply within the boundary of the firm (a process view), supply in dyadic
relationships, supply in an inter-organisational chain and supply in an inter-organisational
network, each of these levels involve different degrees of complexity. The complexity is also
compounded by the way in which actors within a dyad, chain or network can interact. As Levy
(1994) points out that the interactions are strategic in sense as a decision made by one actor take
into account anticipated reactions by others, thus it reflects recognition of interdependence. This
highlights that inter-organisation behaviour can also increase the complexity of a supply system
(e.g. interconnectedness between actors).

Over the years the research and practice of supply chain management has grown in meaning
through what Harland et al., (1999) describes as an externalisation beyond the boundary of the
organisation. Traditionally purchasing and supply management has been viewed as a firm-based
set of activities dealing with transactions between customer and supplier relationships (Baily and
Farmer, 1985). Later work in the 1980s attempted to elevate the purchasing function from being
considered operational and clerical, to a strategic level (e.g. Spekman, 1981; Caddick and Dale,
1987). A supply strategy involves more than just material, transaction and information flow, it
should take more of a holistic approach to managing the entire supply network (Harland et al,
1999). Harland et al., (1999) further points out that this would include aspects such as
interrelationships between organisational roles, network configurations, governance, integration
and collaboration.

As part of developing a supply strategy an organisation will adopt and implement one or many of
the various supply chain improvement options, within the boundaries of the organisation and
between suppliers and customers within the supply network. A supply problem is therefore made
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up of these selected supply chain improvements, to achieve a supply chain objective, within the
supply setting that is specific to the actual organisation undertaking a study. Evaluating supply
problems is inherently complex and presents challenges in terms of the scope and level of detail
in which they should be analysed (Albores, et al., 2006; Weaver, et al., 2006). Owing to, for
example, a great variety of policies, conflicting objectives, and the inherent uncertainty of the
business environment, this is not an easy task (Alfieri & Brandimarte, 1997).

2.4 Role of simulation to evaluate supply chain problems
Simulation has often been cited as a method that could present the greatest potential in studying
supply chain as its complexity obstructs analytical evaluation (e.g. Ridall et al., 2000, Huang et al.,
2003, Van der Zee and Van der Vorst, 2005). It is often regarded as the proper means for
supporting decision making on supply chain design (Van der Zee and Van der Vorst, 2005). One
reason for this is that it may be used to support the quantification of the benefits resulting from
supply chain management (Kleijnen, 2005).

A simulation model is a representation of the system of interest, used to investigate possible
improvements in the real system, or to discover the effect of different policies on that system
(Pidd, 1998). In this context, the system is a supply chain or network and simulation is used to
evaluate the impact of different sets of supply chain improvements on the potential performance
of that system within its supply setting.

The benefits of using simulation as a means to evaluate supply chain problems have often been
cited. These include that simulation is the only approach that can holistically model the supply
chain (Tang, Nelson, Benton, Love, Albores, Ball, MacBryde, Boughton and Drake, 2004) and can
handle stochastic properties (Hae Lee, Cho, Kim and Kim, 2002; Persson and Olhager, 2002). This
is because it can be used to understand the overall supply chain process and characteristics using
graphics/animation (i.e. model elements and relationships), able to capture system dynamics and
facilitate decision-making by minimising the risk of making changes without fully understand the
impact of various alternatives on performance (Chang and Makatsoris, 2001; Van der Zee and Van
der Vorst, 2005). For instance, simulation is good for modelling the impact of variation such as
forecast error, supplier reliability and quality variance (Biswas and Narahari, 2004). A classic
example of understanding the effect of dynamic behaviour (e.g. process delays, lead times,
planning policies) in the amplification of demand signal, often known as the ‘bullwhip effect’ first
described by Forrester (1961).

32

2.4.1 Range of approaches used in simulation
The range of approaches used in supply chain simulation is overwhelming. Van der Zee and Van
der Vorst (2005) point out that in the past decade, a large number of simulation tools for supply
chain analysis have been developed internally (e.g. CSCAT in Ingalls and Kasales, 1999),
commercially (e.g. e-SCOR in Barnett and Miller, 2000; Albores et al., 2006), or concern
applications of general-purpose simulation languages (e.g. Arena in both Kelton, Sadowski and
Sadowski, 1998 and in Persson and Araldi, 2009).

There are a number of classifications of both modelling and simulation approaches suggested in
the SCM literature (e.g. Hicks, 1997; Beamon, 1998; Min and Zhou, 2002; Kim, Tannock, Byrne,
Cao and Er, 2004; Kleijnen, 2005; Weaver et al., 2006; Owen et al., 2008). Min and Zhou (2002)
present a detailed taxonomy of modelling and simulation techniques building upon previous work
by Beamon (1998). Kim et al., (2004) used Min and Zhou’s (2002) taxonomy to review techniques
for modelling supply chain in an extended enterprise, although they focused upon supply chain
management software and how these might be selected.

A study by Kleijnen (2005) provides a more specific survey of supply chain simulation tools and
techniques and a discussion of some methodological issues. Kleijnen (2005) found that there are
four main simulation types for supply chain management: spreadsheet simulation, system
dynamics, discrete-event and business games. On the other hand a discussion by Owen, et al.,
(2008) did not include spreadsheet simulation or business games but detailed how agent based
modelling is an emerging approach for evaluating supply chain problems. In more recent years,
new tools and techniques have been made available commercially largely due to the rise in
popularity of the SCOR process reference model. These have predominantly focused upon DES
(e.g. Gensym eSCOR; see Barnett and Miller, 2000; Albores et al., 2006; Persson and Araldi, 2009)
and adding simulation capabilities to existing static process modelling enterprise management
suites (e.g. Mote Carlo capabilities in Proforma and Aris process enterprise modelling suites; see
Poluha, 2007).

In relation to DES tools, these can be distinguished into identifiable classes that include process,
enterprise, manufacturing and supply chain specific simulation tools or techniques. Albores et al.,
(2006) and Weaver et al., (2007) showed that each of these classes have different competences
when evaluating supply chain problems. It is important to distinguish these as tools specific to
supply chain management are emerging, while a lot of research is conducted using existing
process (e.g. Process 2000 used in Benton, 2009), enterprise (e.g. suggested by Tang et al., 2004)

33

and manufacturing led packages (e.g. Witness used in Albores et al, 2006; Arena in Persson and
Araldi, 2009) which have been established for many years.

Figure 2.1 presents a classification of the different simulation approaches in light of the above
discussion.

Supply chain simulation approaches

Multi-agent based
Spreadsheet System dynamics Discrete-event
simulation Business games
simulation (SD) (DES)
modelling

Business process Manufacturing Supply chain wide Enterprise wide
DES wide DES DES DES

Figure 2.1 Classification of supply chain simulation approaches
Source: Synthesised and extended from past contributions by Beamon (1998); Min and Zhou (2002) and Kleijnen (2005); Albores et al.,
2006; Weaver et al., 2007; Owen et al., (2008)

2.4.2 Extent and usage of simulation for research
The amount of research to evaluate supply problems using simulation approaches is great. It is
evident that simulation is not only a useful tool for evaluating supply problems, but has been
extensively used in the literature for research purposes. Table 2.2 lists each of the approaches
identified in section 2.3.3 and shows representative examples of the approaches being used
specifically for SCM applications. The majority of examples that could be identified used discrete-
event approaches, followed by system dynamic and some recent examples of multi-agent based
modelling. The approaches are described in this section in the context of how they have been
used to analyse supply problems.

34

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