Contents
List of contributors ix
Woodhead Publishing Series in Textiles xi
Preface xix
1 Introduction: key decision points and information requirements in fast fashion supply chains 1
T.-M. Choi
1.1 Introduction 1
1.2 Key decision points 2
1.3 Information requirements 3
1.4 Concluding remarks 5
References 7
2 The use of fuzzy logic techniques to improve decision making in apparel supply chains 9
L. Wang, X. Zeng, Y. Chen, L. Koehl
2.1 Introduction and background 9
2.2 Fuzzy logic techniques 12
2.3 The target market selection in apparel supply chain using fuzzy decision making 20
2.4 Conclusion 36
References 38
3 Using radiofrequency identification (RFID) technologies to improve decision-making in apparel supply chains 41
H.-L. Chan
3.1 Introduction 41
3.2 Literature review 42
3.3 Case studies 49
3.4 Conclusions and future research directions 55
References 57
4 Using big data analytics to improve decision-making in apparel supply chains 63
L. Banica, A. Hagiu
4.1 Introduction 63
4.2 Literature review 65
4.3 Romanian clothing and fashion industry 69
4.4 Community-influenced decision-making: the answer is in the social cloud 80
4.5 Conclusions 88
Appendix A: The evolution of the Romanian investments during 2008e2012 89
Appendix B: The evolution of Romanian exports and imports 90
Appendix C: The evolution of clothing sector exports during 2008e2012 91
Appendix D: The strategy to promote the Romanian exports 92
References 92
5 Using artificial neural networks to improve decision making in apparel supply chain systems 97
P.C.L. Hui, T.-M. Choi
5.1 Introduction 97
5.2 Decision process involved in the apparel supply chain 98
5.3 Applications of ANN in apparel supply chain to improve their decision 100
5.4 Conclusion and limitations of using ANNs in apparel supply chain systems 104
References 105
6 Smart systems for improved customer choice in fashion retail outlets 109
B. Pan
6.1 Context overview 109
6.2 Research parameter 112
6.3 Model proposition 114
6.4 Deploying smart systems compilation of customers’ choice through modular customization model 116
6.5 Conclusion 116
References 119
7 Intelligent procurement systems to support fast fashion supply chains in the apparel industry 121
D.A. Serel
7.1 Introduction 121
7.2 Two-period models with reordering during the selling season 124
7.3 Multiple-order models with all orders placed before the selling season 130
7.4 Conclusion 140
References 141
8 Intelligent demand forecasting systems for fast fashion 145
Brahmadeep, S. Thomassey
8.1 Introduction 145
8.2 Fashion and fast fashion sales forecasting 146
8.3 Sales forecasting methods for fast fashion retailing 148
8.4 Intelligent system based on sales forecasting and replenishment modules 150
8.5 Conclusion 158
References 159
9 Fashion design using evolutionary algorithms and fuzzy set theory e a case to realize skirt design customizations 163
P.Y. Mok, J. Xu, Y.Y. Wu
9.1 Introduction 163
9.2 Style classification and style feature database 169
9.3 Sketch design using fuzzy numbers and IGA 169
9.4 Intelligent pattern designs 183
9.5 Results and discussions 189
9.6 Conclusions and future research 195
Acknowledgments 195
References 195
10 Intelligent systems for managing returns in apparel supply chains 199
Y. Li, F. Xu, X. Li
10.1 Introduction 199
10.2 Literature review 200
10.3 Critical factors of returns management in apparel supply chains 202
10.4 Quantity model for managing returns in apparel supply chains 205
10.5 Intelligent system implementation for managing returns in apparel supply chains 211
10.6 Conclusions and future direction 216
Acknowledgments 216
References 217
11 Vendor-managed inventory systems in the apparel industry 221
H. Chaudhry, G. Hodge
11.1 Introduction 221
11.2 Vendor-managed inventory research 222
11.3 Research design 224
11.4 Case data 225
11.5 Discussion 230
11.6 Conclusion and future research 233
References 233
12 Enterprise resource planning systems for use in apparel supply chains 235
Brahmadeep, S. Thomassey
12.1 Introduction 235
12.2 Enterprise resource planning systems in the apparel industry: review 236
12.3 Case studies 254
12.4 Conclusion 260
References 260
13 Intelligent demand forecasting supported risk management systems for fast fashion inventory management 263
T.-M. Choi, S. Ren
13.1 Introduction and background 263
13.2 Demand forecasting supported inventory control 264
13.3 Inventory models with risk considerations 266
13.4 An intelligent fast fashion demand forecasting supported risk minimization inventory control model 267
13.5 Concluding remarks and future research 268
Acknowledgment 269
References 269
Index 273