| Description |
1 online resource |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
Woodhead Publishing series in textiles ; number 179 |
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Woodhead publishing in textiles ; no. 179.
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| Note |
Includes index. |
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Online resource; title from PDF title page (ScienceDirect, viewed April 20, 2016). |
| Contents |
Front Cover; Information Systems for the Fashion and Apparel Industry; The Textile Institute and Woodhead Publishing; Related titles; Information Systems for the Fashion and Apparel Industry; Copyright; Contents; List of contributors; Woodhead Publishing Series in Textiles; Preface; 1 -- Introduction: key decision points and information requirements in fast fashion supply chains; 1.1 Introduction; 1.2 Key decision points; 1.3 Information requirements; 1.4 Concluding remarks; References; 2 -- The use of fuzzy logic techniques to improve decision making in apparel supply chains. |
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2.1 Introduction and background2.1.1 Fashion mass customization; 2.1.2 Human perception for human-centered design; 2.1.3 Sensory evaluation for acquiring human perception; 2.1.4 Decision making with the uncertainty related to human perception in the fashion design; 2.2 Fuzzy logic techniques; 2.2.1 Fuzzy sets theory; 2.2.2 Fuzzy decision tree; 2.2.3 Fuzzy cognitive map; 2.3 The target market selection in apparel supply chain using fuzzy decision making; 2.3.1 Perception, evaluation, and formalization; 2.3.2 Modeling. |
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2.3.3 Computation of the relevancy degrees for the perception of naked body shapes2.3.3.1 Computation of the relevancy degree REL(D, Y); 2.3.3.2 Computation of the relevancy degree REL(ti, D); 2.3.3.3 Computation of the relevancy degree REL(ti, BRY); 2.3.4 Computation of the relevancy degrees for the perception of body shapes with a garment; 2.3.4.1 Computation of the relevancy degree REL(dev, S); 2.3.4.2 Computation of the relevancy degree REL(D, sk); 2.3.4.3 Computation of the relevancy degree REL(ti, BRCA170("ev); 2.3.4.4 Computation of the relevancy degree REL(ti, BRY("ev). |
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2.3.5 Comparison of the two relevancy degrees2.3.6 Application and validation; 2.4 Conclusion; References; 3 -- Using radiofrequency identification (RFID) technologies to improve decision-making in apparel supply chains; 3.1 Introduction; 3.2 Literature review; 3.2.1 Descriptive case of RFID applications; 3.2.2 Examination of RFID investments and returns; 3.2.3 Exploration of the motivation and impact of RFID system adoption; 3.2.4 RFID-enabled systems development; 3.3 Case studies; 3.3.1 Zara1; 3.3.2 Marks and Spencer2; 3.3.3 American Apparel3; 3.3.4 Discussion. |
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3.4 Conclusions and future research directionsReferences; 4 -- Using big data analytics to improve decision-making in apparel supply chains; 4.1 Introduction; 4.2 Literature review; 4.2.1 A brief insight into big data in business; 4.2.2 Leveraging big data on cloud computing; 4.2.3 Big data-driven fashion supply chains; 4.3 Romanian clothing and fashion industry; 4.3.1 An overview of the actual stage; 4.3.2 Facing the global market: Romanian products and their competitive advantage; 4.4 Community-influenced decision-making: the answer is in the social cloud; 4.4.1 Big data tools and techniques. |
| Bibliography |
Includes bibliographical references and index. |
| Subject |
Clothing trade -- Information technology.
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BUSINESS & ECONOMICS -- Industries -- General.
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| Added Author |
Choi, Tsan-Ming, editor.
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| Other Form: |
Print version: Choi, Tsan-Ming Jason. Information Systems for the Fashion and Apparel Industry. : Elsevier Science, ©2016 9780081005712 |
| ISBN |
9780081005804 (electronic bk.) |
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0081005806 (electronic bk.) |
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0081005717 |
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9780081005712 |
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9780081005712 (print) |
| Standard No. |
AU@ 000061148159 |
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AU@ 000068473485 |
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CHNEW 001013514 |
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DEBSZ 482470267 |
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GBVCP 879393149 |
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