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2022 | OriginalPaper | Chapter

4. Fast Fashion Demand Forecasting Models: A Comparative Study

Authors : Xiong Yu, Lei Lin

Published in: Operations Management in the Era of Fast Fashion

Publisher: Springer Nature Singapore

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Abstract

Fast fashion is a well-established and timely business model in the fashion industry. The common characteristics of fast fashion include a short product life cycle and the need for quick production and distribution of highly trendy products. In order to support the fast fashion business model, fast fashion companies have to conduct quick predictions of the highly volatile demand of a lot of stock keeping units (SKUs). In this chapter, we first examine a carefully selected set of computational models which can be applied for fast fashion demand forecasting. Supported by real data analysis, insights regarding the strengths and weaknesses of these versatile models are discussed. Then, a panel data-based interval forecasting model that can effectively reflect the uncertainties in the forecasting results for decision makers is proposed. By conducting comparison studies with popularly used ELM-based interval forecasting model, some important conclusions are generated.

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Asian S, Nie X (2014) Coordination in supply chains with uncertain demand and disruption risks: existence, analysis, and insights. IEEE Trans Syst Man Cybern: Syst. https://doi.org/10.1109/TSMC.2014.2313121

Au KF, Choi TM, Yu Y (2008) Fashion retail forecasting by evolutionary neural networks. Int J Prod Econ 114:615–630CrossRef

Box GEP, Jenkins GM, Reinsel GC (2008) Time series analysis: forecasting and control, 4th edn, John Wiley

Cachon G, Swinney R (2011) The value of fast fashion: quick response, enhanced design, and strategic consumer behavior. Manage Sci 57(4):778–795CrossRef

Cao Y, Yu W, Ren W, Chen G (2013) An overview of recent progress in the study of distributed multi-agent coordination. IEEE Trans Ind Inf 9(1):427–438CrossRef

Caro F, Gallien J (2007) Dynamic assortment with demand learning for seasonal consumer goods. Manage Sci 53(2):276–292CrossRef

Caro F, Gallien J (2010) Inventory management of a fast-fashion retail network. Oper Res 58(2):257–273CrossRef

Chan HK, Chan FTS (2006) Early order completion contract approach to minimize the impact of demand uncertainty on supply chains. IEEE Trans Industr Inf 2(1):48–58CrossRef

Chan HK, Choi TM, Yue X (2014) Recent development in big data analytics for industrial risk and operations management. In: Working paper

Chen J, Bell PC (2011) Coordinating a decentralized supply chain with customer returns and price-dependent stochastic demand using a buyback policy. Eur J Oper Res 212(2):293–300CrossRef

Chen FL, Ou TY (2009) Gray relation analysis and multilayer functional link network sales forecasting model for perishable food in convenience store. Expert Syst Appl 36(3):7054–7063CrossRef

Choi TM (2011) Coordination and risk analysis of VMI supply chains with RFID technology. IEEE Trans Industr Inf 7(3):497–504CrossRef

Choi TM, Hui CL, Ng SF, Yu Y (2012) Color trend forecasting of fashionable products with very few historical data. IEEE Trans Syst Man Cybern—Part c: Appl Rev 42(6):1003–1010CrossRef

Choi TM, Yu Y, Au KF (2011a) A hybrid SARIMA wavelet transform method for sales forecasting. Decis Support Syst 51(1):130–140

Choi TM, Hui CL, Yu Y (2011b) Intelligent time series fast forecasting for fashion sales: A research agenda. In: Proceedings of the 2011b international conference on machine learning and cybernetics, pp 1010–1014

Choi TM (Ed.) (2014) Fast fashion systems: theories and applications. CRC Press

Choi TM, Hui CL, Yu Y (Eds.) (2014) Intelligent fashion forecasting systems. Models and Applications, Springer

Deng JL (1989) Introduction to grey system theory. J Grey Syst 1(1):1–24

Duan L, Xu LD (2012) Business intelligence for enterprise systems: a survey. IEEE Trans Industr Inf 8(3):679–687CrossRef

Gaukler GM (2011) Item-level RFID in a retail supply chain with stock-out-based substitution. IEEE Trans Industr Inf 7(2):362–370CrossRef

Ghemawat P, Nueno JL (2003) ZARA: fast fashion. In: Harvard business school case (9-703-497), pp 1–35

Hamzaçebia C, Akay D, Kutay F (2009) Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting. Expert Syst Appl 36(2):3839–3844CrossRef

Ho DKY, Choi TM (2014) Collaborative planning forecasting replenishment schemes in apparel supply chain systems: Cases and research opportunities. In: Choi et al. (eds) Intelligent fashion forecasting systems: models and applications, pp 29–40

Hsu LC, Wang CH (2007) Forecasting the output of integrated circuit industry using a grey model improved by the Bayesian analysis. Technol Forecast Soc Chang 74(6):843–853CrossRef

Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70(1–3):489–501CrossRef

Huang GB, Zhu QY, Siew CK (2004) Extreme learning machine: a new learning scheme of feedforward neural networks. In: Neural networks, 2004. Proceedings. 2004 IEEE international joint conference, vol 2, pp 985–990

Lei M, Feng Z (2012) A proposed grey model for short-term electricity price forecasting in competitive power markets. Int J Electr Power Energy Syst 43(1):531–538CrossRef

Li W, Xie H (2014) Geometrical variable weights buffer GM(1,1) model and its application in forecasting of China’s energy consumption. J Appl Math. https://doi.org/10.1155/2014/131432CrossRef

Li J, Choi TM, Cheng TCE (2014) Mean-variance analysis of fast fashion supply chains with returns policy. IEEE Trans Syst Man Cybern: Syst 44(4):422–434CrossRef

Li X, Kong F, Liu Y, Qin Y (2011) Applying GM (1,1) model in China's apparel export forecasting. In: Proceedings of the fourth international symposium on computational intelligence and design, pp 245–247

Lin YH, Lee PC (2007) Novel high-precision grey forecasting model. Autom Constr 16(6):771–777CrossRef

Liu N, Ren S, Choi TM, Hui CL, Ng SF (2013) Sales forecasting for fashion retailing service industry: a review. Math Problems Eng (2013)

Mostard J, Teunter R, de Koster R (2011) Forecasting demand for single-period products: a case study in the apparel industry. Eur J Oper Res 211(1):139–147CrossRef

Mukhopadhyay SK, Zhu X, Yue X (2008) Optimal contract design for mixed channels under information asymmetry. Prod Oper Manag 17:641–650CrossRef

Nenni ME, Giustiniano L, Pirolo L (2013) Demand forecasting in the fashion industry: a review. Int J Eng Bus Manag 5:1–6CrossRef

Ning A, Lau HCW, Zhao Y, Wong TT (2009) Fulfillment of retailer demand by using the MDL-optimal neural network prediction and decision policy. IEEE Trans Industr Inf 5(4):495–506CrossRef

Ren S, Choi TM, Liu N (2014) Fashion sales forecasting with a panel data-based particle-filter model. IEEE Trans Syst Man Cybern–Syst

Rong HJ, Ong YS, Tan AH, Zhu Z (2008) A fast pruned-extreme learning machine for classification problem. Neurocomputing 72(1–3):359–366CrossRef

Serel DA (2014) Flexible procurement models for fast fashion retailers. In: Choi (ed) Fast fashion systems: theories and applications, pp 59–76

Štěpnička M, Cortez P, Donate JP, Štěpničková L (2013) Forecasting seasonal time series with computational intelligence: on recent methods and the potential of their combinations. Expert Syst Appl 40(6):1981–1992CrossRef

Sun ZL, Choi TM, Au KF, Yu Y (2008) Sales forecasting using extreme learning machine with applications in fashion retailing. Decis Support Syst 46(1):411–419CrossRef

Sun ZL, Au KF, Choi TM (2007) A neuro-fuzzy inference system through integration of fuzzy logic and extreme learning machines. IEEE Trans Syst Man Cybern–Part B: Cybern 37(5):1321–1331

Thomassey S (2014) Sales forecasting in apparel and fashion industry: a review. In: Choi et al. (ed) Intelligent fashion forecasting systems: models and applications, pp 9–27

Wan C, Xu Z, Pinson P, Dong ZY, Wong KP (2014) Optimal prediction intervals of wind power generation. IEEE Trans Power Syst 29(3):1166–1174

Wang D (2012) Robust data-driven modeling approach for real-time final product quality prediction in batch process operation. IEEE Trans Industr Inf 7(2):371–377CrossRef

Wang ZX (2014) Nonlinear grey prediction model with convolution integral NGMC and its application to the forecasting of China’s industrial emissions. J Appl Math. https://doi.org/10.1155/2014/580161CrossRef

Wang K, Gou Q, Yang L, Shan S (2014) Coordination of a fast fashion supply chain with profit-loss sharing contract. In: Choi (ed) Fast fashion systems: theories and applications, pp 77–94

Xia M, Wong WK (2014) A seasonal discrete grey forecasting model for fashion retailing. Knowl-Based Syst 57:119–126CrossRef

Xia M, Zhang Y, Weng L, Ye X (2012) Fashion retailing forecasting based on extreme learning machine with adaptive metrics of inputs. Knowl-Based Syst 36:253–259CrossRef

Xiong T, Bao Y, Hu Z (2014) Interval forecasting of electricity demand: a novel bivariate EMD-based support vector regression modeling framework. Int J Electr Power Energy Syst 63:353–362CrossRef

Yesil E, Kaya M, Siradag S (2012) Fuzzy forecast combiner design for fast fashion demand forecasting. In: International symposium on innovations in intelligent systems and applications, pp 1–5

Zhu X, Mukhopadhyay SK, Yue X (2011) Role of forecast effort on supply chain profitability under various information sharing scenarios. Int J Prod Econ 129(2):284–291CrossRef

Title: Fast Fashion Demand Forecasting Models: A Comparative Study
Authors: Xiong Yu
Lei Lin
Publisher: Springer Nature Singapore
Book: Operations Management in the Era of Fast Fashion
Print ISBN: 978-981-19-1176-7

Electronic ISBN: 978-981-19-1177-4

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-981-19-1177-4_4