Impacts of lead time reduction on fabric sourcing in apparel production with yield and environmental considerations
In apparel supply chains, manufacturers usually request a short lead time for fabric supplies. However, a short supply lead time would create environmental problems such as insufficient time for proper control of chemicals and material processing operations, and lead to a lower production yield of good quality supplies. Motivated by this observed industrial practice in fabric sourcing and apparel production, we build a stylized analytical model to investigate how lead time reduction in fabric sourcing affects performances of the fabric supplier and apparel manufacturer as well as the environment. To be specific, we first derive the optimal ordering quantity for the apparel manufacturer and find that it is a production yield scaled newsvendor fractile quantity. We then explore the expected values of lead time reduction, and derive the respective analytical conditions for the apparel manufacturer, fabric supplier and whole supply chain to be benefited by lead time reduction. From the conditions, we reveal that the prior demand mean (which also implies the relative prior demand uncertainty) plays a critical role in determining whether lead time reduction is beneficial. We illustrate how a win–win situation in the supply chain can be achieved by a properly designed deposit payment scheme. For the environment, we show that when the fabric supplier’s profit is improved under lead time reduction, the environment must be hurt. We further investigate how an environment tax can be imposed on the fabric supplier so as to entice it to invest in green technologies.
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Notes
The results are derived based on checking the first order condition of the EVLPs with respect to each major parameter.
The results are derived based on checking the first order derivative of \( EHTE^ \) with respect to each major parameter.(LTR)>
References
- Alizamir, S., de Véricourt, F., & Sun, P. (2016). Efficient feed-in-tariff policies for renewable energy technologies. Operations Research,64(1), 52–66. Google Scholar
- Amornpetchkul, T. B., Duenyas, I., & Şahin, Ö. (2015). Mechanisms to induce buyer forecasting: Do suppliers always benefit from better forecasting? Production and Operations Management,24(11), 1724–1749. Google Scholar
- Asian, S., & Nie, X. (2014). Coordination in supply chains with uncertain demand and disruption risks: Existence, analysis, and insights. IEEE Transactions on Systems, Man, and Cybernetics: Systems,44(9), 1139–1154. Google Scholar
- Basu, R. J., Subramanian, N., Gunasekaran, A., & Palaniappan, P. L. K. (2017). Influence of non-price and environmental sustainability factors on truckload procurement process. Annals of Operations Research,250(2), 363–388. Google Scholar
- Bi, G., Jin, M., Ling, L., & Yang, F. (2017). Environmental subsidy and the choice of green technology in the presence of green consumers. Annals of Operations Research,255(1–2), 547–568. Google Scholar
- Bruce, M., & Daly, L. (2011). Adding value: Challenges for UK apparel supply chain management—a review. Production Planning & Control,22(3), 210–220. Google Scholar
- Cachon, G., & Swinney, R. (2011). The value of fast fashion: Quick response, enhanced design, and strategic consumer behavior. Management Science,57, 778–795. Google Scholar
- Chan, H. L., Shen, B., & Cai, Y. J. (2017). Quick response strategy with cleaner technology in a supply chain: Coordination and win-win situation analysis. International Journal of Production Research. https://doi.org/10.1080/00207543.2016.1278283. ArticleGoogle Scholar
- Chaudhry, H., & Hodge, G. (2012). Postponement and supply chain structure: Cases from the textile and apparel industry. Journal of Fashion Marketing and Management: An International Journal,16(1), 64–80. Google Scholar
- Chen, W., Feng, Q., & Seshadri, S. (2013). Sourcing from suppliers with random yield for price-dependent demand. Annals of Operations Research,208(1), 557–579. Google Scholar
- Chen, W. & Tan, B. (2016). Dynamic procurement from multiple suppliers with random capacities. Annals of Operations Research. https://doi.org/10.1007/s10479-016-2285-2. ArticleGoogle Scholar
- Chen, L., Wang, L., Wu, X., & Ding, X. (2017). A process-level water conservation and pollution control performance evaluation tool of cleaner production technology in textile industry. Journal of Cleaner Production,143, 1137–1143. Google Scholar
- Chi, T. (2011). Building a sustainable supply chain: An analysis of corporate social responsibility (CSR) practices in the Chinese textile and apparel industry. Journal of the Textile Institute,102(10), 837–848. Google Scholar
- Choi, T. M. (2013). Local sourcing and fashion quick response system: The impacts of carbon footprint tax. Transportation Research Part E: Logistics and Transportation Review,55, 43–54. Google Scholar
- Choi, T.-M. (2014). Fashion retail supply chain management: A systems optimization approach. UK: CRC Press. Google Scholar
- Choi, T. M. (2016a). Inventory service target in quick response fashion retail supply chains. Service Science,8(4), 406–419. Google Scholar
- Choi, T. M. (2016b). Impacts of retailer’s risk averse behaviors on quick response fashion supply chain systems. Annals of Operations Research. https://doi.org/10.1007/s10479-016-2257-6. ArticleGoogle Scholar
- Choi, T. M., Chow, P. S., Lee, C. H., & Shen, B. (2018a). Used intimate apparel collection programs: A game-theoretic analytical study. Transportation Research Part E: Logistics and Transportation Review,109, 44–62. Google Scholar
- Choi, T. M. & Guo, S. (2017). Responsive supply in fashion mass customisation systems with consumer returns. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1292065. ArticleGoogle Scholar
- Choi, T. M., Yeung, W. K., Cheng, T. C. E., & Yue, X. (2018b). Optimal scheduling, coordination, and the value of RFID technology in garment manufacturing supply chains. IEEE Transactions on Engineering Management,65(1), 72–84. Google Scholar
- Choi, T. M., Zhang, J., & Cheng, T. C. E. (2018c). Quick response in supply chains with stochastically risk sensitive retailers. Decision Sciences. (in press).
- Donohue, K. L. (2000). Efficient supply contract for fashion goods with forecast updating and two production modes. Management Science,46, 1397–1411. Google Scholar
- Fang, T., Gunterberg, C., & Larsson, E. (2010). Sourcing in an increasingly expensive China: Four Swedish cases. Journal of Business Ethics,97(1), 119–138. Google Scholar
- Fisher, M., & Raman, A. (1996). Reducing the cost of demand uncertainty through accurate response to early sales. Operations Research,44, 87–99. Google Scholar
- Gereffi, G. (2001). Global sourcing in the US apparel industry. Journal of Textile and Apparel, Technology and Management,2(1), 1–5. Google Scholar
- Gong, X., & Zhou, S. X. (2013). Optimal production planning with emissions trading. Operations Research,61(4), 908–924. Google Scholar
- Guo, S., Zhao, L., & Xu, X. (2016). Impact of supply risks on procurement decisions. Annals of Operations Research,241(1–2), 411–430. Google Scholar
- Hines, T. (2002). Developing an iceberg theory of cost comparisons in relation to sourcing decisions by UK fashion retailers. Journal of the Textile Institute,93(3), 3–14. Google Scholar
- Iyer, A. V., & Bergen, M. E. (1997). Quick response in manufacturer-retailer channels. Management Science,43, 559–570. Google Scholar
- Köksal, D., Strähle, J., Müller, M., & Freise, M. (2017). Social sustainable supply chain management in the textile and apparel industry—A literature review. Sustainability,9(1), 100. Google Scholar
- Kraiselburd, S., Pibernik, R., & Raman, A. (2011). The manufacturer’s incentive to reduce lead times. Production and Operations Management,20(5), 639–653. Google Scholar
- Krishnan, H., Kapuscinski, R., & Butz, D. A. (2010). Quick response and retailer effort. Management Science,56(6), 962–977. Google Scholar
- Lee, C. H., Choi, T. M., & Cheng, T. C. E. (2015). Selling to strategic and loss-averse consumers: Stocking, procurement, and product design policies. Naval Research Logistics,62(435–453), 2015. Google Scholar
- Li, X. (2017). Optimal procurement strategies from suppliers with random yield and all-or-nothing risks. Annals of Operations Research,257(1–2), 167–181. Google Scholar
- Li, Y., Guo, H., & Zhang, Y. (2017). An integrated location-inventory problem in a closed-loop supply chain with third-party logistics. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1338781. ArticleGoogle Scholar
- Li, X., Li, Y., & Govindan, K. (2014). An incentive model for closed-loop supply chain under the EPR law. Journal of the Operational Research Society,65(1), 88–96. Google Scholar
- Lin, Y. T., & Parlakturk, A. (2012). Quick response under competition. Production and Operations Management,21(3), 518–533. Google Scholar
- Liu, Z., & Nagurney, A. (2013). Supply chain networks with global outsourcing and quick-response production under demand and cost uncertainty. Annals of Operations Research,208(1), 251–289. Google Scholar
- Nadvi, K., Thoburn, J. T., Thang, B. T., Ha, N. T. T., Hoa, N. T., Le, D. H., et al. (2004). Vietnam in the global garment and textile value chain: Impacts on firms and workers. Journal of International Development,16(1), 111–123. Google Scholar
- Nathan, C. N. (1996). Global sourcing for new commodity yarn and fabric production. Journal of the Textile Institute,87(3), 60–97. Google Scholar
- Nie, X., Boyacı, T., Gümüş, M., Ray, S., & Zhang, D. (2017). Joint procurement and demand-side bidding strategies under price volatility. Annals of Operations Research,257(1–2), 121–165. Google Scholar
- Ozturk, E., Karaboyacı, M., Yetis, U., Yigit, N. O., & Kitis, M. (2015). Evaluation of integrated pollution prevention control in a textile fiber production and dyeing mill. Journal of Cleaner Production,88, 116–124. Google Scholar
- Perry, P., Wood, S., & Fernie, J. (2015). Corporate social responsibility in garment sourcing networks: Factory management perspectives on ethical trade in Sri Lanka. Journal of Business Ethics,130(3), 737–752. Google Scholar
- Ray, P., & Jenamani, M. (2016). Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach. Annals of Operations Research,237(1–2), 237–262. Google Scholar
- Reimann, M. (2015). Accurate response with refurbished consumer returns. Decision Sciences,47(1), 31–59. Google Scholar
- Şen, A. (2008). The US fashion industry: A supply chain review. International Journal of Production Economics,114(2), 571–593. Google Scholar
- Shen, B., Chan, H.-L., Chow, P.-S., & Thoney-Barletta, K. A. (2016). Inventory management research in the fashion industry. International Journal of Inventory Research,3(4), 297–317. Google Scholar
- Shen, B., Ding, X., Chen, L., & Chan, H. L. (2017). Low carbon supply chain with energy consumption constraints: Case studies from China’s textile industry and simple analytical model. Supply Chain Management: An International Journal,22(3), 258–269. Google Scholar
- Shen, B., Li, Q. Y., Dong, C. W., & Quan, V. (2015). Design outsourcing in fashion supply chain: OEM v.s. ODM. Journal of the Operational Research Society,67(2), 259–268. Google Scholar
- Shen, B., Wang, Y., Lo, K. Y., & Shum, M. (2012). The impact of ethical fashion on consumer purchase behaviour. Journal of Fashion Marketing and Management,16(2), 234–245. Google Scholar
- Shen, B., Zheng, J., Chow, P. S., & Chow, K. Y. (2014). Perception of fashion sustainability in online community. Journal of the Textile Institute,105(9), 971–979. Google Scholar
- Sheu, J. B. (2016). Buyer behavior in quality-dominated multi-sourcing recyclable-material procurement of green supply chains. Production and Operations Management,25(3), 477–497. Google Scholar
- Song, M., Wang, S., & Wu, K. (2016). Environment-biased technological progress and industrial land-use efficiency in China’s new normal. Annals of Operations Research. https://doi.org/10.1007/s10479-016-2307-0. ArticleGoogle Scholar
- Song, M. L., Zhang, W., & Qiu, X. M. (2015). Emissions trading system and supporting policies under an emissions reduction framework. Annals of Operations Research,228(1), 125–134. Google Scholar
- Song, M., & Zheng, W. (2016). Computational analysis of thermoelectric enterprises’ environmental efficiency and Bayesian estimation of influence factors. The Social Science Journal,53(1), 88–99. Google Scholar
- Su, J. G. V. B., Gargeya, V. B., & Richter, S. J. (2005). Global sourcing shifts in the US textile and apparel industry: A cluster analysis. Journal of the Textile Institute,96(4), 261–276. Google Scholar
- Tokatli, N. (2008). Global sourcing: insights from the global clothing industry—the case of Zara, a fast fashion retailer. Journal of Economic Geography,8(1), 21–38. Google Scholar
- Wang, M., Liu, J., Chan, H. L., Choi, T. M., & Yue, X. (2016a). Effects of carbon tariffs trading policy on duopoly market entry decisions and price competition: Insights from textile firms of developing countries. International Journal of Production Economics,181, 470–484. Google Scholar
- Wang, S., Sun, P., & de Véricourt, F. (2016b). Inducing environmental disclosures: A dynamic mechanism design approach. Operations Research,64(2), 371–389. Google Scholar
- Xiao, T., & Jin, J. (2011). Coordination of a fashion apparel supply chain under lead-time-dependent demand uncertainty. Production Planning & Control,22(3), 257–268. Google Scholar
- Yeung, D. W. (2014). Dynamically consistent collaborative environmental management with production technique choices. Annals of Operations Research, 220(1), 181–204. Google Scholar
- Zhang, Y., Zhang, C., & Liu, Y. (2016). An AHP-based scheme for sales forecasting in the fashion industry. In T. M. Choi (Ed.), Analytical modeling research in fashion business (pp. 251–267). Singapore: Springer. Google Scholar
- Zhang, T., Zhu, X., & Gou, Q. (2017). Demand forecasting and pricing decision with the entry of store brand under various information sharing scenarios. Asia-Pacific Journal of Operational Research, 34(2), 1740018. Google Scholar
- Zhao, L., Qian, Y., Huang, R., Li, C., Xue, J., & Hu, Y. (2012). Model of transfer tax on transboundary water pollution in China’s river basin. Operations Research Letters,40(3), 218–222. Google Scholar
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Authors and Affiliations
- Business Division, Institute of Textiles and Clothing, Room ST740, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Tsan-Ming Choi & Ya-Jun Cai
- Tsan-Ming Choi