Rapid Modelling for Increasing Competitiveness (eBook)

Gerald Reiner studied Business Administration in Vienna after an education in Industrial Engineering. In 2001 he received his Doctorate in Business Administration (Quality Management and Production Management) at the Vienna University of Economics and Business Administration, where he later received his Habilitation (venia legendi). Between 1999 and 2006 he was Assistant Professor at the Department of Production Management at the Vienna University of Economics and Business Administration. He served as visiting professor at Aston Business School (UK) in March 2006 and also at the University of Lausanne (Switzerland) from March 2007 to June 2007. Since February 2007 Gerald Reiner has been a full professor at the Enterprise Institute at the University of Neuchâtel, Switzerland. His research interests lie in the fields of supply chain management, quality management and operations management. He has published articles in International Journal of Production Economics, International Journal of Production Research, International Journal of Operations and Production Management, Operations Management Research, and other leading journals, as well as books and numerous book chapters.

Foreword 5
Preface 9
Contents 12
List of Contributors 15
Part I Theory Pieces and Review 20
Chapter 1 Managerial Decision Making and Lead Times: The Impact of Cognitive Illusions 21
1.1 Introduction 22
1.2 Cognitive Illusions 22
1.3 Debiasing Techniques 28
1.4 Conclusions 30
References 30
Chapter 2 Queueing Networks Modeling Software for Manufacturing 33
2.1 Introduction 33
2.2 Queueing Networks Theory 34
2.3 Queueing Networks Software 35
2.4 Queueing Networks Software for Manufacturing 37
2.5 Further Remarks 38
References 39
Chapter 3 A Review of Decomposition Methods for Open Queueing Networks 42
3.1 Introduction 42
3.2 Jackson Networks 44
3.3 Generalised Jackson Networks 48
3.4 Other Classes of Networks 55
References 56
Part II Modelling and Simulation 60
Chapter 4 Parsimonious Modeling and Forecasting of Time Series drifted by Autoregressive Noise 61
4.1 Introduction 61
4.2 Extended Linear Growth Model for AR(p) Drifts 63
4.3 Estimation of the Parameters of the Extended Model 65
4.4 On Line Variance Learning 66
4.5 Forecast Function 66
4.6 Comments 67
References 67
Chapter 5 Forecast of the Traffic and Performance Evaluation of the BMT Container Terminal (Bejaia’s Harbor) 68
5.1 Introduction 68
5.2 Park with Containers and Motion of the Containers 69
5.3 Mathematical Models 71
5.4 Calculation of the Forecasts 71
5.5 Performance Evaluation of the BMT Terminal 73
5.6 Variation of the Arrival Rate 77
5.7 Conclusion 78
Chapter 6 A Dynamic Forecasting and Inventory Management Evaluation Approach 80
6.1 Introduction 80
6.2 A Simple Supply Chain Model with Demand Forecasting 82
6.3 Model Verification and Validation 86
6.4 Empirical Data Analysis 88
6.5 Conclusion 90
References 91
Chapter 7 Performance Evaluation of Process Strategies Focussing on Lead Time Reduction Illustrated with an Existing Polymer Supply Chain 94
7.1 Introduction 94
7.2 Theoretical Background 95
7.3 Illustration of the Supply Chain 97
7.4 Conclusion 102
References 104
Chapter 8 A Framework for Economic and Environmental Sustainability and Resilience of Supply Chains 106
8.1 Introduction 107
8.2 Prevalent Logistics Trends: Cost Perspective 108
8.3 New Logistics Trends: Integrated Perspective 109
8.4 Transport-Focused Framework for Dual Sourcing 112
8.5 Single-Period Dual Sourcing Model Including Emission Costs 114
8.6 Summary 117
References 118
Chapter 9 An Integrative Approach To Inventory Control 120
9.1 Introduction 121
9.2 Framework for Integrated Inventory Control 123
9.3 Empirical Data 124
9.4 Simulation Model 127
9.5 Simulation Results 128
9.6 Discussion 129
9.7 Conclusions 131
References 132
Chapter 10 Rapid Modeling of Express Line Systems for ImprovingWaiting Processes 134
10.1 Introduction 134
10.2 Tools for Analyzing Express Line Systems 135
10.3 Objective Functions for Operating Express Line Systems 141
10.4 Optimization of the Waiting Process 142
10.5 Conclusions 143
References 144
Chapter 11 Integrating Kanban Control with Advance Demand Information: Insights from an Analytical Model 145
11.1 Introduction 145
11.2 Kanban Control System with ADI 146
11.3 Markov Chain Analysis 148
11.4 System Comparison 150
11.5 Conclusions and OngoingWork 154
References 155
Chapter 12 Rapid Modelling in Manufacturing System Design Using Domain Specific Simulators 156
12.1 Simulation in Manufacturing System Design 156
12.2 Rapid Modelling in Manufacturing Systems Design 158
12.3 Case Applications 160
12.4 Discussion of the Cases 164
12.5 Conclusions 165
References 166
Chapter 13 The Best of Both Worlds - Integrated Application of Analytic Methods and Simulation in Supply Chain Management 168
13.1 Combination of Analytic Methods and Simulation 168
13.2 Hybrid Models for Complex Supply Chains 170
13.3 Application in Supply Chain Management 171
13.4 Conclusion 174
Chapter 14 Rapid Modeling In A Lean Context 176
14.1 Introduction 176
14.2 The Quantification Of Lean 177
14.3 Conclusion 184
References 185
Part III Case Study and Action Research 187
Chapter 15 The Impact of Lean Management on Business Level Performance and Competitiveness 188
15.1 Introduction 189
15.2 The Research Framework 189
15.3 Methodology 194
15.4 Conclusion 205
References 206
Chapter 16 Reducing Service Process Lead-Time Through Inter-Organisational Process Coordination 210
16.1 Introduction 210
16.2 Research Objectives and Literature Review 211
16.3 Lead-Time Related Problem Analysis 213
16.4 Discussion 216
References 218
Chapter 17 Is There a Relationship Between VC Firm Business Process Flow Management and Investment Decisions? 219
17.1 Introduction 219
17.2 Research Method 220
17.3 Results 225
17.4 Discussion and Conclusion 226
References 228
Chapter 18 What Causes Prolonged Lead-Times in Courts of Law? 231
18.1 Introduction 231
18.2 Case Organizations 232
18.3 Process Improvement Projects and Data Collection 235
18.4 Analyzing the Factors Behind the Process Inefficiencies and Prolonged Lead-Times 236
18.5 Conclusions 239
References 240
Chapter 19 Logistics Clusters - How Regional Value Chains Speed Up Global Supply Chains 242
19.1 Introduction 242
19.2 Competitive Advantages through Clusters 244
19.3 Research Framework 246
19.4 Empirical Analysis 248
19.5 Further Research and Outlook 251
19.6 Appendix 251
References 252
Part IV Survey and Longitudinal Research 255
Chapter 20 Measuring the Effects of Improvements in Operations Management 256
20.1 Introduction 256
20.2 Literature Review 257
20.3 Research Questions, Sample Selection, and Methodology 260
20.4 Empirical Analysis, Results and Discussion 262
20.5 Summary and Conclusions 267
References 270
Chapter 21 Managing Demand Through the Enablers of Flexibility: The Impact of Forecasting and Process Flow Management 272
21.1 Introduction 272
21.2 The “Concept” of Flexibility 273
21.3 Objectives and Methodology 276
21.4 Empirical Analysis 277
21.5 Discussion 280
References 281
Chapter 22 Threats of Sourcing LocallyWithout a Strategic Approach: Impacts on Lead Time Performances 284
22.1 Introduction 284
22.2 Literature Review 285
22.3 Research Objectives and Methodology 287
22.4 Results 290
22.5 Discussion 294
22.6 Conclusion 296
References 296
Chapter 23 Improving Lead Times Through Collaboration With Supply Chain Partners: Evidence From Australian Manufacturing Firms 300
23.1 Introduction 300
23.2 Literature Review 301
23.3 Research Method 304
23.4 Data Analysis Procedures and Results 305
23.5 Discussion 309
23.6 Conclusion 310
References 310
Appendix A International Scientific Board 313
Appendix B Sponsors 314