طراحی الگوی قیمت گذاری زنجیره تامین سبز با رویکرد تصمیم گیری چند معیاره و نظریه بازی(مورد مطالعه: صنعت لوازم خانگی)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مدیریت صنعتی(مالی)، گروه مدیریت، واحد دهاقان، دانشگاه آزاد اسلامی، دهاقان، ایران

2 دانشیار گروه مدیریت ،واحد دهاقان ،دانشگاه ازاد اسلامی ،دهاقان ،ایران.

3 گروه مهندسی صنایع و آینده پژوهی، دانشکده فنی، دانشگاه اصفهان، اصفهان، ایران

10.22091/jemsc.2024.11144.1191

چکیده

هدف از پژوهش حاضر طراحی الگوی قیمت گذاری زنجیره تامین سبز با رویکرد تصمیم گیری چند معیاره و نظریه بازی(مورد مطالعه: صنعت لوازم خانگی) است. در این پژوهش، پس از مطالعه‌ی کتابخانه‌ای و شناسایی شاخص‌های کلیدی در پیش بینی قیمت‌گذاری زنجیره تأمین سبز، با استفاده از روش دلفی‌فازی، غربالگری شاخص ها طی سه مرحله انجام شد و از بین 20 شاخص بر اساس نظرات 13 خبره، 13 شاخص انتخاب شد و براساس رویکرد شاخص انتخاب ارجحیت شرکت D به دلیل اینکه بالاترین اولویت را به خود اختصاص داد، به عنوان شرکت رهبر وارد نظریه بازی شد. در نهایت بر اساس تئوری بازی سناریو میان 4 عضو زنجیره تامین ارزیابی وتحلیل انجام شد و برترین و بدترین سناریو‌ها نیز معرفی شدند. همچنین به منظور آزمون اعتبار ساختاری مدل پیشنهادی نیز اطلاعات مربوط به زنجیره تأمین سبز 9 شرکت لوازم خانگی منتخب با استفاده از نرم افزار متلب به اجرا درآمد. نتایج نشان داد که سناریو هفتم به عنوان برترین سناریو و سناریو پنجم به عنوان بدترین سناریو معرفی شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Designing a green supply chain pricing model with a multi-criteria decision-making approach and game theory (case study: home appliance industry)

نویسندگان [English]

  • somayeh sazegari 1
  • sayyed mohammadreza davoodi 2
  • alireza goli 3
1 , Department of Management, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran
2 Associate Professor, Department of Management, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran.
3 Department of Industrial Engineering and Future Studies, Faculty of Engineering, University of Isfahan, Isfahan, Iran.
چکیده [English]

The purpose of the current research is to design a green supply chain pricing model with a multi-criteria decision-making approach and game theory (case study: home appliance industry). In this research, after library study and identification of key indicators in predicting green supply chain pricing, using the fuzzy Delphi method, the screening of indicators was done in three stages, and out of 20 indicators, based on the opinions of 13 experts, 13 indicators were selected and based on the priority selection index approach, company D entered the game theory as the leader company because it had the highest priority. Finally, based on the game theory, the scenario between 4 members of the supply chain was evaluated and analyzed, and the best and worst scenarios were also introduced. Also, in order to test the structural validity of the proposed model, information related to the green supply chain of 9 selected home appliance companies was implemented using MATLAB software.

کلیدواژه‌ها [English]

  • green supply chain
  • pricing
  • game theory
  • home appliance company
  • preference selection index approach
  1. Abbasi, S., & Choukolaei, H. A. (2023). A systematic review of green supply chain network design literature focusing on carbon policy. Decision Analytics Journal6, 100189.‏ https://doi.org/10.1016/j.dajour.2023.100189
  2. Ansari, Z. N., and R. Kant.(2017). A State-of-Art Literature Review Reflecting 15 Years of Focus on Sustainable Supply Chain Management. Journal of Cleaner Production 142: 2524–2543. https://doi.org/10.1016/j.jclepro.2016.11.023
  3. Atabaki, M. S., Khamseh, A. A., & Mohammadi, M. (2019). A priority-based firefly algorithm for network design of a closed-loop supply chain with price-sensitive demand. Computers & industrial engineering135, 814-837.‏ https://doi.org/10.1016/j.cie.2019.06.054
  4. Aydin, R., Kwong, C. K., & Ji, P. (2016). Coordination of the closed-loop supply chain for product line design with consideration of remanufactured products. Journal of Cleaner Production114, 286-298.‏ https://doi.org/10.1016/j.jclepro.2015.05.116
  5. Büyüközkan, G., & Çifçi, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in industry62(2), 164-174.‏ https://doi.org/10.1016/j.compind.2010.10.009
  6. Calik, E., & Bardudeen, F. (2016). A measurement scale to evaluate sustainable innovation performance in manufacturing organizations. Procedia Cirp40, 449-454.‏ https://doi.org/10.1016/j.procir.2016.01.091
  7. Dai, Z., & Ye, C. (2022). Analysis and evaluation of key elements of optimal regulation of green supply chain from the perspective of low carbon. Wireless Communications and Mobile Computing2022, 1-11.‏  https://doi.org/10.1155/2022/8196756
  8. Feng, Z., & Chen, W. (2018). Environmental regulation, green innovation, and industrial green development: An empirical analysis based on the Spatial Durbin model. Sustainability10(1), 223.‏ https://doi.org/10.3390/su10010223
  9. Golini, R., Moretto, A., Caniato, F., Caridi, M., & Kalchschmidt, M. (2017). Developing sustainability in the Italian meat supply chain: an empirical investigation. International Journal of Production Research55(4), 1183-1209.‏ https://doi.org/10.1080/00207543.2016.1234724
  10. Gosling, J., Jia, F., Gong, Y., & Brown, S. (2016). The role of supply chain leadership in the learning of sustainable practice: toward an integrated framework. Journal of Cleaner Production, 137, 1458-1469. https://doi.org/10.1016/j.jclepro.2014.10.029
  11. Govindan, K.; Khodaverdi, R.; Jafarian, A. (2013). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. J. Clean Prod. 47, 345–354. https://doi.org/10.1016/j.jclepro.2012.04.014
  12. Grimm, J.H.; Hofstetter, J.S.; Sarkis, J. (2014). Critical factors for sub-supplier management: A sustainable food supply chains perspective. Int. J. Prod. Econ. 152, 159–173. https://doi.org/10.1016/j.ijpe.2013.12.011
  13. Guarnieri, P.; Sobreiro, V.A.; Nagano, M.S.; Serrano, A.L.M. (2015). The challenge of selecting and evaluating third-party reverse logistics providers in a multicriteria perspective: A Brazilian case. J. Clean Prod. 96, 209–219. https://doi.org/10.1016/j.jclepro.2014.05.040
  14. Hashemi, S.H.; Karimi, A.; Tavana, M. (2015). An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. Int. J. Prod. Econ. 159, 178–191. https://doi.org/10.1016/j.ijpe.2014.09.027
  15. Hou, G., Wang, Y., & Xin, B. (2019). A coordinated strategy for sustainable supply chain management with product sustainability, environmental effect and social reputation. Journal of Cleaner Production, 228, 1143-1156. https://doi.org/10.1016/j.jclepro.2019.04.096
  16. Hou, P., Wang, J., Zhang, Q., & Zhang, S. (2023). Implications of risk aversion behavior on the green product promotion strategy under manufacturer encroachment. Applied Mathematics and Computation447, 127911.‏ https://doi.org/10.1016/j.amc.2023.127911
  17. Hsu, C. C., Tan, K. C., & Mohamad Zailani, S. H. (2016). Strategic orientations, sustainable supply chain initiatives, and reverse logistics: Empirical evidence from an emerging market. International journal of operations & production management, 36(1), 86-110.‏ https://doi.org/10.1108/IJOPM-06-2014-0252
  18. Humphreys, P.; McIvor, R.; Chan, F. (2003). Using case-based reasoning to evaluate supplier environmental management performance. Expert Syst. Appl. 25, 141–153. https://doi.org/10.1016/S0957-4174(03)00042-3
  19. Jabbour, A.B., Jabbour, C., Govindan, K., Kannan, D., Arantes, A.F.,(2014). Mixed methodology to analyze the relationship between maturity of environmental management and the adoption of green supply chain management in Brazil. https://doi.org/10.1016/j.resconrec.2014.02.004
  20. Kalina, I., Novykov, D., Leszczynski, V., Lavrukhina, K., Kukhta, P., & Nitsenko, V. (2022). ENTREPRENEURIAL STRUCTURES OF THE EXTRACTIVE INDUSTRY: FOREIGN EXPERIENCE IN ENVIRONMENTAL PROTECTION. Scientific Bulletin of National Mining University37(5).‏ https://doi.org/10.33271/nvngu/2022-5/136
  21. Kang, K., Gao, S., Gao, T., & Zhang, J. (2021). Pricing and Financing Strategies for a Green Supply Chain With a Risk-Averse Supplier. IEEE Access, 9, 9250-9261.‏ 1109/ACCESS.2021.3050130
  22. Kannan, D. (2018). Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. Int. J. Prod. Econ. 195, 391–418. https://doi.org/10.1016/j.ijpe.2017.02.020
  23. Li, B., Zhu, M., Jiang, Y., & Li, Z. (2016). Pricing policies of a competitive dual-channel green supply chain. Journal of Cleaner Production112, 2029-2042.‏ https://doi.org/10.1016/j.jclepro.2015.05.017
  24. Li, M., & Shan, M. (2023). Pricing and green promotion effort strategies in dual-channel green supply chain: considering e-commerce platform financing and free-riding. Journal of Business & Industrial Marketing38(11), 2310-2323.‏  https://doi.org/10.1108/JBIM-07-2022-0303
  25. Li, P., Rao, C., Goh, M., & Yang, Z. (2021). Pricing strategies and profit coordination under a double echelon green supply chain. Journal of Cleaner Production, 278, 123694. https://doi.org/10.1016/j.jclepro.2020.123694
  26. Li, Y., & Mathiyazhagan, K. (2018). Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector. Journal of cleaner production172, 2931-2941.‏ https://doi.org/10.1016/j.jclepro.2017.11.120
  27. Liu, P., & Zhang, F. J. (2022). Pricing strategies of dual-channel green supply chain considering Big Data information inputs. Soft Computing, 1-19.‏ https://doi.org/10.1007/s00500-021-06611-6
  28. Luthra, S., Garg, D., & Haleem, A. (2016). The impacts of critical success factors for implementing green supply chain management towards sustainability: An empirical investigation of Indian automobile industry. Journal of Cleaner Production, 121, 142–158. https://doi.org/10.1016/j.jclepro.2016.01.095
  29. Luthra, S., Garg, D., & Haleem, A. (2016). The impacts of critical success factors for implementing green supply chain management towards sustainability: An empirical investigation of Indian automobile industry. Journal of Cleaner Production, 121, 142–158. https://doi.org/10.1016/j.jclepro.2016.01.095
  30. Mahmoudi, A., Shishebori, D., & Sadegheih, A. (2020). Pricing for a multi-channel supply chain with the participation of a third-party logistics service: A game theory approach. Supply Chain Management22(67), 23-34. (In Persian ) DOR:20.1001.1.20089198.1399.22.67.2.1
  31. Maniya, K., & Bhatt, M. G. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials & Design31(4), 1785-1789.‏ https://doi.org/10.1016/j.matdes.2009.11.020
  32. Masrzadeh Oghaz, Pegah and Dehghanian, Farzad, (2023), Presenting a two-level model to determine the carbon tax in a green supply chain by considering price-sensitive demand and carbon emissions, 9th International Conference on Industrial and Systems Engineering, Mashhad. (In Persian )
  33. Mathivathanan, D., Kannan, D., & Haq, A. N. (2018). Sustainable supply chain management practices in Indian automotive industry: A multi-stakeholder view. Resources, Conservation and Recycling128, 284-305.‏ https://doi.org/10.1016/j.resconrec.2017.01.003
  34. mini, A., & Alinezhad, A. (2019). Developing Network DEA Model with Undesirable Outputs for Evaluation of Green Supply Chain Management. Supply Chain Management21(63), 51-63. 1001.1.20089198.1398.21.63.4.8
  35. Mousavi, P., Yousefizenouz, R., Hasanpoor, A. (2015). Identifying Organizational Information Security Risks Using Fuzzy Delphi. Journal of Information Technology Management, 7(1), 163-184. 22059/jitm.2015.53555
  36. Obeidat, S. M., Al Bakri, A. A., & Elbanna, S. (2020). Leveraging “green” human resource practices to enable environmental and organizational performance: Evidence from the Qatari oil and gas industry. Journal of Business Ethics, 164(2), 371-388. https://doi.org/10.1007/s10551-018-4075-z
  37. Palevich, R. (2011). Lean sustainable supply chain the: How to create a green infrastructure with lean technologies. Ft press.‏
  38. Rahmani, K., & Yavari, M. (2019). Pricing policies for a dual-channel green supply chain under demand disruptions. Computers & Industrial Engineering127, 493-510.‏ https://doi.org/10.1016/j.cie.2018.10.039
  39. Saffie, N. A. M., & Rasmani, K. A. (2016, July). Fuzzy delphi method: Issues and challenges. In 2016 International Conference on Logistics, Informatics and Service Sciences (LISS)(pp. 1-7). IEEE.‏  1109/LISS.2016.7854490
  40. Sawik, T. (2016). On the risk-averse optimization of service level in a supply chain under disruption risks. Int. J. Prod. Res. 54, 98–113. https://doi.org/10.1080/00207543.2015.1016192
  41. Seuring & Müller, (2008)`.`From a literature review to a conceptual framework for sustainable supply chain management,'' J. Cleaner Prod., vol. 16, no. 15, pp. 16991710, Oct. https://doi.org/10.1016/j.jclepro.2008.04.020
  42. Sharma, V. K., Chandna, P., & Bhardwaj, A. (2017). Green supply chain management related performance indicators in agro industry: A review. Journal of Cleaner Production, 141, 1194-1208. https://doi.org/10.1016/j.jclepro.2016.09.103
  43. Shoaeinaeini, M., Govindan, K., & Rahmani, D. (2022). Pricing policy in green supply chain design: the impact of consumer environmental awareness and green subsidies. Operational Research, 1-40.‏ https://doi.org/10.1007/s12351-021-00680-z
  44. Shoja,Mehdi,Hosseinzadeh Lotfi,Farhad,Gholam Abri,Amir,Rashidi Komijan,Alireza. (2020) .Efficiency of 4 stage supply chain in presence of non discretionary , undesirable and negative factors Using SBM model in DEA .Economic  Modeling ,51,73-98. 30495/eco.2020.1899015.2357
  45. Tariq, A., Badir, Y. F., Tariq, W., & Bhutta, U. S. (2017). Drivers and consequences of green product and process innovation: A systematic review, conceptual framework, and future outlook. Technology in Society51, 8-23.‏ https://doi.org/10.1016/j.techsoc.2017.06.002
  46. Tomislav, K. (2018). The concept of sustainable development: From its beginning to the contemporary issues. Zagreb International Review of Economics & Business21(1), 67-94.‏ https://doi.org/10.2478/zireb-2018-0005
  47. Tseng, M.-L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145–162. https://doi.org/10.1016/j.resconrec.2018.10.009
  48. Tseng, M.L.; Chiu, A.S.F. (2013). Evaluating firm’s green supply chain management in linguistic preferences. J. Clean Prod. 2013, 40, 22–31. https://doi.org/10.1016/j.jclepro.2010.08.007
  49. Wang, S., Liu, L., & Wen, J. (2024). Product pricing, green effort decisions and coordination in a dynamic three-echelon green supply chain. Journal of Industrial and Management Optimization, 0-0.‏  Doi: 3934/jimo.2024033
  50. Xu, J., & Zhu, Y. (2011). Dynamic pricing model for the operation of closed-loop supply chain system. Intelligent control and automation2(4), 418-423.‏ DOI:4236/ica.2011.24048 
  51. Yeh, W.C.; Chuang, M.C. (2011). Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Syst. Appl. 38, 4244–4253. https://doi.org/10.1016/j.eswa.2010.09.091
  52. Yi, S., & Wen, G. (2023). Game model of transnational green supply chain management considering government subsidies. Annals of Operations Research, 1-22.‏ https://doi.org/10.1007/s10479-023-05420-4
  53. Yu, C., Wenxin, L., Khan, S. U., Yu, C., Jun, Z., Yue, D., & Zhao, M. (2020). Regional differential decomposition and convergence of rural green development efficiency: evidence from China. Environmental Science and Pollution Research27, 22364-22379.‏ https://doi.org/10.1007/s11356-020-08805-1
  54. Zaid, A. A., Jaaron, A. A., & Bon, A. T. (2018). The impact of green human resource management and green supply chain management practices on sustainable performance: An empirical study. Journal of Cleaner Production, 204, 965–979. https://doi.org/10.1016/j.jclepro.2018.09.062
  55. Zhang, C. T., & Wang, Z. (2021). Production mode and pricing coordination strategy of sustainable products considering consumers’ preference. Journal of Cleaner Production296, 126476.‏ https://doi.org/10.1016/j.jclepro.2021.126476
  56. Zhang, R., Liu, J., & Qian, Y. (2023). Wholesale-price vs cost-sharing contracts in a green supply chain with reference price effect under different power structures. Kybernetes52(5), 1879-1902.‏ https://doi.org/10.1108/K-11-2021-1096
  57. Zhu, Q., & Rass, S. (2018, October). Game theory meets network security: A tutorial. In Proceedings of the 2018 ACM SIGSAC conference on computer and communications security (pp. 2163-2165).‏ https://doi.org/10.1145/3243734.3264421
  58. Zhu, Q., Feng, Y., & Choi, S. B. (2017). The role of customer relational governance in environmental and economic performance improvement through green supply chain management. Journal of Cleaner Production, 155, 46-53. https://doi.org/10.1016/j.jclepro.2016.02.124
  59. Zhu, Q., Feng, Y., & Choi, S. B. (2017). The role of customer relational governance in environmental and economic performance improvement through green supply chain management. Journal of Cleaner Production, 155, 46-53. https://doi.org/10.1016/j.jclepro.2016.02.124
CAPTCHA Image