Impact of adopting quick response and agility on supply chain competition with strategic customer behavior

Document Type : Article

Authors

1 Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, 424 Hafez Avenue, Tehran, Iran

2 - Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, P.O. Box : 48518/718195, Iran - Departamento de Ingenieria Industrial, Tecnologico de Monterrey, Puebla Campus, 72453, Mexico

Abstract

A growing trend towards computerization and competition in supply chains results in uncertainty and quick variability that make the decisions difficult for both levels of retailers and manufacturers. In this paper, two Bi-Level Stackelberg models are developed under non- and agile conditions in the presence of strategic customers. Our main novelty approach in this paper is to consider both levels competing with each other in a sequential game to determine the optimal production and order quantities and prices with and without agile abilities. In addition, both proposed models are simplified single-level using the Karush-Kuhn-Tucker (KKT) approach. Then, they are remodeled by the Robust Optimization technique due to existing uncertain parameters. To have a better assessment of the models’ efficiency and applicability, they have been implemented in a real case and finally, the results are compared and analyzed.

Keywords

References

References:
1. Suri, R., It's About Time: The Competitive Advantage M. Kaviyani-Charati et al./Scientia Iranica, Transactions E: Industrial Engineering 29 (2022) 387-411 407 of Quick Response Manufacturing, CRC Press (2010).
2. Ma, J., Zhang, D., Dong, J., and Tu, Y. "A supply chain network economic model with time-based competition", European Journal of Operational Research, 280(3), pp. 889-908 (2020).
3. Cachon, G.P. and Swinney, R. "The value of fast fashion: Quick response, enhanced design, and strategic consumer behavior", Management Science, 57(4), pp. 778-795 (2011).
4. Yang, D., Ershi, Q., and Yajiao, L. "Quick response and supply chain structure with strategic consumers", Omega, 52, pp. 1-14 (2015).
5. Dubey, R. and Angappa, G. "Agile manufacturing: framework and its empirical validation", The International Journal of Advanced Manufacturing Technology, 76(9-12), pp. 2147-2157 (2015).
6. Gunasekaran, A., Agile Manufacturing: The 21st Century Competitive Strategy, Elsevier (2001).
7. Nakano, M. "Responsiveness-oriented strategy", In Supply Chain Management, Springer, Singapore, pp. 109-151 (2020).
8. Choi, T. and Sethi, T. "Innovative quick response programs: a review", International Journal of Production Economics, 127(1), pp. 1-12 (2010).
9. Cheng, T.E. and Choi, T.M., Innovative Quick Response Programs in Logistics and Supply Chain Management, Springer Science & Business Media (2010).
10. Choi, T.M. "Inventory service target in quick response fashion retail supply chains", Service Science, 8(4), pp. 406-419 (2016).
11. Cachon, G.P. and Swinney, R. "Purchasing, pricing, and quick response in the presence of strategic consumers", Management Science, 55(3), pp. 497-511 (2009).
12. Dong, J. and Wu, D.D. "Two-period pricing and quick response with strategic customers", International Journal of Production Economics, 215, pp. 165- 173 (2019).
13. Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., and Zacharia, Z.G. "Defining supply chain management", Journal of Business Logistics, 22(2), pp. 1-25 (2001).
14. Yin, S., Nishi, T., and Grossmann, I.E. "Optimal quantity discount coordination for supply chain optimization with one manufacturer and multiple suppliers under demand uncertainty", The International Journal of Advanced Manufacturing Technology, 76(5-8), pp. 1173-1184 (2015).
15. Feng, Y., Zhang, Z., Tian, G., Zhihan L., Tian, S., and Jia, H. "Data-driven accurate design of variable blank holder force in sheet forming under interval uncertainty using sequential approximate multi-objective optimization", Future Generation Computer Systems, 86, pp. 1242-1250 (2018).
16. Sahinidis, N.V. "Optimization under uncertainty: state-of-the-art and opportunities", Computers & Chemical Engineering, 28(6-7), pp. 971-983 (2004).
17. Choi, T.M., Zhang, J., and Cheng, T.C.E. "Quick response in supply chains with stochastically risk sensitive retailers", Decision Sciences, 49(5), pp. 932- 957 (2018).
18. Li, Y., Ye, F., and Lin, Q. "Optimal lead time policy for short life cycle products under conditional value-atrisk criterion", Computers & Industrial Engineering, 88, pp. 354-365 (2015).
19. Choi, T.M. "Quick response in fashion supply chains with retailers having boundedly rational managers", International Transactions in Operational Research, 24(4), pp. 891-905 (2017).
20. Zhang, J., Gou, Q., Zhang, J., and Liang, L. "Supply chain pricing decisions with price reduction during the selling season", International Journal of Production Research, 52(1), pp. 165-187 (2014).
21. Darwish, M.A., Alkhedher, M., and Alenezi, A. "Reducing the effects of demand uncertainty in singlenewsvendor multi-retailer supply chains", International Journal of Production Research, 57(4), pp. 1082-1102 (2019).
22. Khouja, M., Liu, X., and Zhou, J. "To sell or not to sell to an off-price retailer in the presence of strategic consumers", Omega, 90, p. 102002 (2020).
23. Sindhwani, R. and Malhotra, V. "A framework to enhance agile manufacturing system: a total interpretive structural modelling (TISM) approach", Benchmarking: An International Journal (2017).
24. Agarwal, A., Shankar, R., and Tiwari, M.K. "Modeling agility of supply chain", Industrial Marketing Management, 36(4), pp. 443-457 (2007).
25. Lalmazloumian, M., Wong, K.Y., Govindan, K., and Kannan, D. "A robust optimization model for agile and build-to-order supply chain planning under uncertainties", Annals of Operations Research, 240(2), pp. 435-470 (2016).
26. Lago, A., Martnez-de-Albniz, V., Moscoso, P., and Vall, A. "The role of quick response in accelerating sales of fashion goods", In Analytical Modeling Research in Fashion Business, pp. 51-78 (2016).
27. Mahmoodi, M. "A new multi-objective model of agile supply chain network design considering transportation limits", Production & Manufacturing Research, 7(1), pp. 1-22 (2019).
28. Cachon, G.P. and Netessine, S. "Game theory in supply chain analysis", In Models, Methods, and Applications for Innovative Decision Making, pp. 200-233 (2006).
29. Cheraghalipour, A., Paydar, M.M., and Hajiaghaei-Keshteli, M. "Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms", Computers and Electronics in Agriculture, 162, pp. 651-668 (2019).
30. Giri, B.C., Bardhan, S., and Maiti, T. "Coordinating a two-echelon supply chain with price and promotional effort dependent demand", Int J Oper Res, 23(2), pp. 181-199 (2015).
31. Mokhlesian, M. and Zegordi, S.H. "Pricing and advertising decisions in a dominant-retailer supply chain: A multi-follower bi-level programming approach", Scientia Iranica, 25(4), pp. 2254-2266 (2018).
32. Seyedhosseini, S.M., Hosseini-Motlagh, S.M., Johari, M., and Jazinaninejad, M. "Social price-sensitivity of demand for competitive supply chain coordination", Computers & Industrial Engineering, 135, pp. 1103- 1126 (2019).
33. Hassanpour, A., Bagherinejad, J., and Bashiri, J. "A robust bi-level programming model for designing a closed-loop supply chain considering government's collection policy", Scientia Iranica, 26(6), pp. 3747- 3764 (2019).
34. Seifbarghy, M., Nouhi, K., and Mahmoudi, A. "Contract design in a supply chain considering price and quality dependent demand with customer segmentation", International Journal of Production Economics, 167, pp. 108-118 (2015).
35. Ren, J., Bian, Y., Xu, X., and He, P. "Allocation of product-related carbon emission abatement target in a make-to-order supply chain", Computers & Industrial Engineering, 80, pp. 181-194 (2015).
36. Mahmoodi, A. and Eshghi, K. "Price competition in duopoly supply chains with stochastic demand", Journal of Manufacturing Systems, 33(4), pp. 604-612 (2014).
37. Golpira, H., Najafi, E., Zandieh, M., and Sadi-Nezhad, S. "Robust bi-level optimization for green opportunistic supply chain network design problem against uncertainty and environmental risk", Computers & Industrial Engineering, 107, pp. 301-312 (2017).
38. Yue, D. and You, F. "Stackelberg-game-based modeling and optimization for supply chain design and operations: A mixed integer bilevel programming framework", Computers & Chemical Engineering, 102, pp. 81-95 (2017).
39. Setak, M., Feizizadeh, F., Tikani, H., and Shaker Ardakani, E. "A bi-level stochastic optimization model for reliable supply chain in competitive environments: Hybridizing exact method and genetic algorithm", Applied Mathematical Modelling, 75, pp. 310-332 (2019).
40. Shen, B., Choi, T.M., Wang, Y., and Lo, C.K.Y."The coordination of fashion supply chains with a risk-averse supplier under the markdown money policy", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43(2), pp. 266-276 (2013).
41. Ghasemy Yaghin, R., Torabi, S.A., and Fatemi Ghomi, S.M.T. "Integrated markdown pricing and aggregate production planning in a two echelon supply chain: A hybrid fuzzy multiple objective approach", Applied Mathematical Modelling, 36(12), pp. 6011-6030 (2012).
42. Tian, G., Zhang, G., Feng, Y., et al. "Operation patterns analysis of automotive components remanufacturing industry development in China", Journal of Cleaner Production, 164, pp. 1363-1375 (2017).
43. Forghani, A., Dehghanian, F., Salari, M., and Ghiami, Y. "A bi-level model and solution methods for partial interdiction problem on capacitated hierarchical facilities", Computers & Operations Research, 114, p. 104831 (2020).
44. Mahmoodi, A. "Stackelberg-Nash equilibrium of pricing and inventory decisions in duopoly supply chains using a nested evolutionary algorithm", Applied Soft Computing, 86, p. 105922 (2020).
45. Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M., Tian, G., et al. "An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem", Information Sciences, 512, pp. 1335-1359 (2020).
46. Kaviyani-Charati, M., Heidarzadeh Souraki, F., and Hajiaghaei-Keshteli. M. "A robust optimization methodology for multi-objective location-transportation problem in disaster response phase under uncertainty", International Journal of Engineering, 31(11), pp. 1953-1961 (2018).
47. Esmaeili, M., Aryanezhad, M.B., and Zeephongsekul, P. "A game theory approach in seller-buyer supply chain", European Journal of Operational Research, 195(2), pp. 442-448 (2009).
48. Chow, P.S., Choi, T.M., and Cheng, T.C.E. "Impacts of minimum order quantity on a quick response supply chain", IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 42(4), pp. 868-879 (2012).
49. Sinha, A., Malo, P., Frantsev, A., et al. "Finding optimal strategies in a multi-period multi-leader-follower Stackelberg game using an evolutionary algorithm", Computers & Operations Research, 41, pp. 374-385 (2014).
50. Mokhlesian, M. and Zegordi, S.H. "Application of  ultidivisional bi-level programming to coordinate pricing and inventory decisions in a multiproduct competitive supply chain", The International Journal of Advanced Manufacturing Technology, 71(9-12), pp. 1975-1989 (2014).
51. Shah, N.H., Widyadana, G.A., and Wee, H.M. "Stackelberg game for two-level supply chain with price markdown option", International Journal of Computer Mathematics, 91(5), pp. 1054-1060 (2014).
52. Christopher, M., Lowson, R., and Peck, H. "Creating agile supply chains in the fashion industry", International Journal of Retail & Distribution Management, (2004).
53. Zhang, G., Lu, J., and Gao, Y. "Bi-Level programming models and algorithms", In Multi-Level Decision Making, pp. 47-62 (2015).
54. Bard, J.F. and Falk, J.E. "An explicit solution to the multi-level programming problem", Computers & Operations Research, 9(1), pp. 77-100 (1982).
55. Bard, J.F. "Practical bilevel optimization: algorithms and applications", 30, Springer Science & Business Media (2013).
56. Shi, C., Lu, J., and Zhang, G. "An extended Kuhn- Tucker approach for linear bilevel programming", Applied Mathematics and Computation, 162(1), pp. 51- 63 (2005).
57. Allende, G.B. and Still, G. "Solving bilevel programs with the KKT-approach", Mathematical Programming,138(1-2), pp. 309-332 (2013). 
58. Vidal, C.J. and Goetschalckx, M. "A global supply chain model with transfer pricing and transportation cost allocation", European Journal of Operational Research, 129(1), pp. 134-158 (2001).
59. Mulvey, J.M., Vanderbei, R.J., and Zenios, S.A. "Robust optimization of large-scale systems", Operations Research, 43(2), pp. 264-281 (1995).
60. Yu, Ch.S. and Li, H.L. "A robust optimization model for stochastic logistic problems", International Journal of Production Economics, 64(1-3), pp. 385-397 (2000).
Scientia Iranica
Volume 29, Issue 1
Transactions on Industrial Engineering (E)
January and February 2022
Pages 387-411

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History

  • Receive Date: 03 June 2019
  • Revise Date: 11 April 2020
  • Accept Date: 15 June 2020

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