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Growing Science » International Journal of Industrial Engineering Computations » A dynamic decision-making framework for a hybrid production system for decayed merchandise with shortages in traditional and electronic markets

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International Journal of Industrial Engineering Computations
ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 13 Issue 3 pp. 385-404, 2022

A dynamic decision-making framework for a hybrid production system for decayed merchandise with shortages in traditional and electronic markets Pages 385-404 Right click to download the paper Download PDF

Authors: Liang-Tu Chen, Guo-Ciang Wu, Cher-Hung Tseng, Ren-Zong Kuo

📋 Author Affiliations:
Liang-Tu Chen¹, Ren-Zong Kuo¹, Guo-Ciang Wu², Cher-Hung Tseng³
¹ Department of Commerce Automation and Management, National Pingtung University, Taiwan, N/A
² Department of Marketing and Distribution Management, National Pingtung University, Taiwan, N/A
³ Department of Business Administration, National Pingtung University, Taiwan, N/A
doi 10.5267/j.ijiec.2022.1.004
Crossmark
2 Source: Scopus
Crossref 1 Source: CrossRef

🔑 Keywords: Dynamic hybrid production, Closed-loop supply chain, Merchandise decay, Electronic markets, Shortages

Abstract: This research proposes a dynamic decision-making framework for a hybrid production system that incorporates manufacturing and remanufacturing procedures into a closed-loop supply chain network with merchandise substitution and shortages within traditional markets (TM) and electronic markets (EM). In particular, we develop models of profit maximization and equilibrium analysis by using calculus with dynamic programming under four business schemes, including a manufacturing-only model within TM/EM and a hybrid remanufacturing model within TM/EM. Dynamic decision-making planning was taken for brand-new and like-new decayed merchandise in hybrid production systems. The results demonstrate that solutions generated within EMs surpass those within TMs in terms of maximizing profits. Further, the hybrid remanufacturing model did not surpass the manufacturing-only model under a general setting, but had better performance under certain conditions, including intense competition, a smaller remanufacturing cost, a larger brand-new merchandise market size, and a smaller like-new merchandise market size.


How to cite this paper
APA: Chen, L., Wu, G., Tseng, C & Kuo, R. (2022). A dynamic decision-making framework for a hybrid production system for decayed merchandise with shortages in traditional and electronic markets. International Journal of Industrial Engineering Computations, 13(3), 385-404.
Chicago/Turabian: Chen, L., Wu, G., Tseng, C & Kuo, R. 2022. "A dynamic decision-making framework for a hybrid production system for decayed merchandise with shortages in traditional and electronic markets." International Journal of Industrial Engineering Computations 13, no. 3 (2022): 385-404.
AMA: Chen, L., Wu, G., Tseng, C & Kuo, R. A dynamic decision-making framework for a hybrid production system for decayed merchandise with shortages in traditional and electronic markets. International Journal of Industrial Engineering Computations. 2022;13(3):385-404.

References
Al-Mashari, M., Al-Mudimigh, A., & Zairi, M. (2003). Enterprise resource planning: A taxonomy of critical factors. European Journal of Operational Research, 146(2), 352-364.
Alsaad, A., Mohamad, R., & Ismail, N. A. (2017). The moderating role of trust in business to business electronic commerce (B2B EC) adoption. Computers in Human Behavior, 68, 157-169.
Assid, M., Gharbi, A., & Hajji, A. (2019). Production planning of an unreliable hybrid manufacturing–remanufacturing system under uncertainties and supply constraints. Computers & Industrial Engineering, 136, 31-45.
Assid, M., Gharbi, A., & Hajji, A. (2021). Production planning and control of unreliable hybrid manufacturing-remanufacturing systems with quality-based categorization. Journal of Cleaner Production, 312, Article ID 127800. https://doi.org/10.1016/j.jclepro.2021.127800
Battini, D., Bogataj, M., & Choudhary, A. (2017). Closed Loop Supply Chain (CLSC). Economics, Modelling, Management and Control. International Journal of Production Economics, 183, 319-321.
Benedito, E., & Corominas, A. (2013). Optimal manufacturing policy in a reverse logistic system with dependent stochastic returns and limited capacities. International Journal of Production Research, 51(1), 189-201.
Bhatia, M. S., & Srivastava, R. K. (2019). Antecedents of implementation success in closed-loop supply chain: an empirical investigation. International Journal of Production Research, 57(23), 7344-7360.
Chae, B., McHaney, R., & Sheu, C. (2020). Exploring social media use in B2B supply chain operations. Business Horizons, 63(1), 73-84.
Chandak, S., Kumar, N., & Dalpati, A. (2019). The impact of e-business on supply chain performance in the context of indian automobile industry. The IUP Journal of Supply Chain Management, 16(2), 7-24.
Chang, H. H., & Wong, K. H. (2010). Adoption of e-procurement and participation of e-marketplace on firm performance: trust as a moderator. Information & Management, 47(5-6), 262-270.
Chang, K. P., & Graham, G. (2012). E-business strategy in supply chain collaboration: an empirical study of B2B e-commerce project in Taiwan. International Journal of Electronic Business Management, 10(2), 101-112.
Chong, W. K., Bian, D., & Zhang, N. (2016). E-marketing services and e-marketing performance: the roles of innovation, knowledge complexity and environmental turbulence in influencing the relationship. Journal of Marketing Management, 32(1-2), 149-178.
Fallah, H., Eskandari, H., & Pishvaee, M. S. (2015). Competitive closed-loop supply chain network design under uncertainty. Journal of Manufacturing Systems, 37, 649-661.
Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58-71.
Gao, T., Huang, M., Wang, Q., Yin, M., Ching, W. K., Lee, L. H., & Wang, X. (2018). A systematic model of stable multilateral automated negotiation in e-market environment. Engineering Applications of Artificial Intelligence, 74, 134-145.
Govindan, K., & Soleimani, H. (2017). A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus. Journal of Cleaner Production, 142, 371-384.
Gunasekaran, A., Subramanian, N., & Papadopoulos, T. (2017). Information technology for competitive advantage within logistics and supply chains: A review. Transportation Research Part E: Logistics and Transportation Review, 99, 14-33.
Haddadsisakht, A., & Ryan, S. M. (2018). Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax. International Journal of Production Economics, 195, 118-131.
He, Y. (2017). Supply risk sharing in a closed-loop supply chain. International Journal of Production Economics, 183, 39-52.
Hong, X., Xu, L., Du, P., & Wang, W. (2015). Joint advertising, pricing and collection decisions in a closed-loop supply chain. International Journal of Production Economics, 167, 12-22.
Hu, Z.H., Li, Q., Chen, X.J., & Wang, Y.F. (2014). Sustainable rent-based closed-loop supply chain for fashion products. Sustainability, 6(10), 7063-7088.
Ingene, C.A., & Parry, M.E. (1995). Channel coordination when retailers compete. Marketing Science, 14(4), 360-377.
Jabbarzadeh, A., Haughton, M., & Khosrojerdi, A. (2018). Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industrial Engineering, 116, 178-191.
Jean, R. J. B. 2014. “What makes export manufacturers pursue functional upgrading in an emerging market? A study of Chinese technology new ventures.” International Business Review 23(4). 741-749.
Ketchen Jr., D. J., & Hult, G. T. M. (2007). Bridging organization theory and supply chain management: The case of best value supply chains. Journal of Operations Management, 25(2), 573-580.
Khor, K.S., Thurasamy, R., Ahmad, N. H., Halim, H. A., & May-Chiun, L. (2015). Bridging the Gap of Green IT/IS and Sustainable Consumption. Global Business Review, 16(4), 571-593.
Khorshidvand, B., Soleimani, H., Sibdari, S., & Esfahani, M. M. S. (2021). A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands. Computers & Industrial Engineering, 157, Article ID 107326. https://doi.org/10.1016/j.cie.2021.107326
Koch, H. (2010). Developing dynamic capabilities in electronic marketplaces: A cross-case study. The Journal of Strategic Information Systems, 19(1), 28-38.
Krings, W., Palmer, R., & Inversini, A. (2021). Industrial marketing management digital media optimization for B2B marketing. Industrial Marketing Management, 93, 174-186.
Lariviere, M. A. (1999). Supply chain contracting and coordination with stochastic demand. In S. Tayur, R. Ganeshan and M. Magazine, eds. Quantitative Models for Supply Chain Management. Boston: Kluwer Academic.
Lee, C. K. M., and Lam, J. S. L. (2012). Managing reverse logistics to enhance sustainability of industrial marketing. Industrial Marketing Management, 41(4), 589-598.
Li, S., Jayaraman, V., Paulraj, A., & Shang, K. H. (2016). Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry. International Journal of Production Research, 54(7), 2136-2151.
Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., & Subba Rao, S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), 107-124.
Liao, S. H., Hu, D. C., & Ding, L. W. (2017). Assessing the influence of supply chain collaboration value innovation, supply chain capability and competitive advantage in Taiwan's networking communication industry. International Journal of Production Economics, 191, 143-153.
Liu, W., Qin, D., Shen, N., Zhang, J., Jin, M., Xie, N., ... & Chang, X. (2020). Optimal pricing for a multi-echelon closed loop supply chain with different power structures and product dual differences. Journal of Cleaner Production, 257, 120281.
Zhang, Y., & Chen, W. (2021). Optimal production and financing portfolio strategies for a capital constrained closed-loop supply chain with OEM remanufacturing. Journal of Cleaner Production 257, Article ID 120281. https://doi.org/10.1016/j.jclepro.2020.120281
Mitra, S. (2013). Periodic review policy for a two-echelon closed-loop inventory system with correlations between demands and returns. OPSEARCH, 50(4), 604-615.
Mitra, S., & Webster, S. (2008). Competition in remanufacturing and the effects of government subsidies. International Journal of Production Economics, 111(2), 287-298.
Modak, N. M., Modak, N., Panda, S., & Sana, S. S. (2018). Analyzing structure of two-echelon closed-loop supply chain for pricing, quality and recycling management. Journal of Cleaner Production, 171, 512-528.
Özelkan, E. C., Lim, C., & Adnan, Z. H. (2018). Conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing. International Journal of Production Economics, 200, 207-223.
Petruzzi, N. C., & Dada, M. (1999). Pricing and the newsvendor problem: A review with extensions. Operations Research, 47(2), 183-194.
Petty, D. J., Stirling, M. D., Travis, L. C., & Bennett, R. (2000). Conditions for the successful implementation of finite capacity/MRPII hybrid control systems. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 214(9), 847-851.
Qiang, Q., Ke, K., Anderson, T., & Dong, J. (2013). The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega, 41(2), 186-194.
Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225-246.
Rajan, A., Steinberg, R., & Steinberg, R. (1992). Dynamic pricing and ordering decisions by a monopolist. Management Science, 38, 240-262.
Sahebjamnia, N., Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2019). Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks. Journal of Cleaner Production, 196, 273-296.
Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2009). Designing and managing the supply chain: concepts, strategies, and case studies. McGraw-Hill.
Tsao, Y. C., Linh, V. T., & Lu, J. C. (2017). Closed-loop supply chain network designs considering RFID adoption. Computers & Industrial Engineering, 113, 716-726.
Ullah, M., Asghar, I., Zahid, M., Omair, M., AlArjani, A., & Sarkar, B. (2021). Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production, 290, Article ID 125609. https://doi.org/10.1016/j.jclepro.2020.125609
Wan, N., & Hong, D. (2019). The impacts of subsidy policies and transfer pricing policies on the closed-loop supply chain with dual collection channels. Journal of Cleaner Production, 224, 881-891.
Wang, Q., Wu, J., Zhao, N., & Zhu, Q. (2019). Inventory control and supply chain management: A green growth perspective. Resources, Conservation and Recycling, 145, 78-85.
Wang, Y., Jiang, L., & Shen, Z. J. (2004). Channel performance under consignment contract with revenue sharing. Management Science, 50, 34-47.
Zhang, J., Liu, X., & Tu, Y. L. (2011). A capacitated production planning problem for closed-loop supply chain with remanufacturing. International Journal of Advanced Manufacturing Technology, 54(5), 757-766.
Zhang, Y., & Chen, W. (2021). Optimal production and financing portfolio strategies for a capital constrained closed-loop supply chain with OEM remanufacturing. Journal of Cleaner Production, 279, Article ID 123467. https://doi.org/10.1016/j.jclepro.2021.127800
Zhu, X., Ren, M., Chu, W., & Chiong, R. (2019). Remanufacturing subsidy or carbon regulation? An alternative toward sustainable production. Journal of Cleaner Production, 239, Article ID 117988. https://doi.org/10.1016/j.jclepro.2019.117988
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Journal: International Journal of Industrial Engineering Computations | Year: 2022 | Volume: 13 | Issue: 3 | Views: 1748 | Reviews: 0

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