شناسایی و بررسی روابط علی-معلولی معیارهای تاثیر گذار زمان تدارک، هزینه و رضایتمندی مشتری در شبکه توزیع امنی-چنل با استفاده از روش دیمتل
محورهای موضوعی : مدیریت صنعتی
Seyed Ghiasuddin Taheri
1
,
Mehrzad Navabakhsh
2
,
Hamid Tohidi
3
,
Davood Mohammaditabar
4
1 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Engineering, South Tehran Branch, Islamic
Azad University, Tehran, Iran
4 - Assistant Professor, Department of Industrial Engineering, Islamic Azad University, Tehran, Iran.
کلید واژه: توزیع امنی-چنل, دیمتل, روابط علی-معلولی, زمان تدارک, هزینه و رضایتمندی مشتری,
چکیده مقاله :
امنی-چنل یک مدل کسب و کار بر اساس کانال متقابل است که شرکت‌ها برای افزایش و بهبود ارتباط با مشتری استفاده می‌کنند. شرکت‌هایی که از امنی-چنل استفاده می‌کنند، بر این باورند که ارزش‌های مشتری، توانایی تماس مداوم آن با شرکت از طریق راههای متعدد در یک زمان است. در امنی-چنل کلیه رفتارهای مشتری در تمامی کانال‌های ارتباطی و نقاط تماس کاملاً پیش‌بینی و حمایت می‌شود به طوری که اگر در طی پروسه خرید، مشتری از یک کانال به کانال ارتباطی دیگری تغییر مسیر دهد هیچ تأثیر و کاستی در نتیجه خریدش شاهد نخواهد بود. در این پژوهش به دنبال بررسی روابط علی-معلولی معیارهای تاثیر گذار بر زمان تدارک، هزینه و رضایتمندی مشتری در شبکه توزیع امنی-چنل با استفاده از روش دیمتل می‌باشیم. لذا با استفاده از روش دیمتل روابط علی-معلولی معیارهای تاثیرگذار بر آن، انجام می‌شود تا علاوه بر فرایند برنامه‌ریزی بلندمدت، توانایی مقابله با عدم قطعیت-های آتی را داشته باشد. با توجه به محاسبات و تحلیل های انجام شده مشخص شد که معیارهای موجودی محصول، قابلیت پاسخگویی، مسئولیت پذیری، ارتباط با مشتری، شناسایی و انتخاب توزیع‌کنندگان، توانمندی فن‌آوری اطلاعات، انتظارات مشتری، در فرآیند بهبود زمان تدارک، هزینه و رضایتمندی مشتری در شبکه توزیع امنی-چنل به عنوان عوامل معلول می‌تواند نقش بسیار تاثیرگذاری در جذب مشتری و افزایش سهم بازار در بازارهای رقابتی ایفا نماید. نتایج نشان داد که از مهم ترین عامل‌های موثر در بهبود زمان تدارک، هزینه و رضایتمندی مشتری در شبکه توزیع امنی-چنل می‌توان به عوامل نرخ بازگشت مشتری و قوانین دولتی، اشاره نمود.
Omni-channel is a cross-channel business model that companies use to increase and improve customer relationships. Companies that use Omni-channel believe that the customer's value is the ability to continuously contact the company through multiple ways at the same time. In Omni-channel, all customer behaviors are fully predicted and supported in all communication channels and contact points, so that if during the purchase process, the customer changes direction from one communication channel to another, there will be no impact or deficiency in the result of his purchase. In this research, we seek to investigate the cause-effect relationships of the criteria affecting procurement time, cost, and customer satisfaction in Omni-channel distribution network using DEMATEL method. Therefore, by using DEMATEL’s method, the criteria affecting the causal relationships are carried out so that, in addition to the long-term planning process, it has the ability to deal with future uncertainties. According to the calculations and analysis, it was found that the criteria of product inventory, responsiveness, responsibility, communication with the customer, identification and selection of distributors, information technology capability, customer expectations, in the process of improving the procurement time, cost and customer satisfaction in Omni-channel distribution network as handicap factors can play a very effective role in attracting customers and increasing market share in competitive markets. The results showed that among the most important effective factors in improving the procurement time, cost and customer satisfaction in Omni-channel distribution network, the factors of customer return rate and government laws can be mentioned.
1. Abdulkader, M. M. S., Gajpal, Y., & ElMekkawy, T. Y. (2018). Vehicle routing problem in omni-channel retailing distribution systems. International Journal of Production Economics, 196, 43-55.
2. Ailawadi, K. L., & Farris, P. W. (2017). Managing multi-and omni-channel distribution: metrics and research directions. Journal of retailing, 93(1), 120-135.
3. Akter, S., Hossain, M. I., Lu, S., Aditya, S., Hossain, T. M. T., & Kattiyapornpong, U. (2019). Does service quality perception in omnichannel retailing matter? A systematic review and agenda for future research. In Exploring Omnichannel Retailing (pp. 71-97). Springer, Cham.
4. Badhotiya, G. K., Soni, G., & Mittal, M. L. (2019). Fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain. The International Journal of Advanced Manufacturing Technology, 102(1-4), 635-645.
5. Bagheri, M. H., F. Fthian, & T. Mahmoudpour Neychalani. 2015. Groundwater level modeling using system dynamics approach to investigate the sinkhole events (Case study: Abarkuh County Watershed, Iran). International Journal of Hydrology Science and Technology, 1-19.
6. Bala, B. K., Arshad, F. M., & Noh, K. M. (2017). System dynamics. Springer Texts in Business and Economics.
7. Cummins, S., Peltier, J. W., & Dixon, A. (2016). Omni-channel research framework in the context of personal selling and sales management: A review and research extensions. Journal of Research in Interactive Marketing, 10 (1), 2-16.
8. Beck, N., & Rygl, D. (2015). Categorization of multiple channel retailing in Multi-, Cross, and Omni‐Channel Retailing for retailers and retailing. Journal of Retailing and Consumer Services, 27, 170-178.
9. Bernon, M., Cullen, J., & Gorst, J. (2016). Online retail returns management: integration within an omni-channel distribution context. International Journal of Physical Distribution & Logistics Management, 46(6/7), 584-605.
10. Cummins, S., Peltier, J. W., & Dixon, A. (2016). Omni-channel research framework in the context of personal selling and sales management: a review and research extensions. Journal of Research in Interactive Marketing, 10(1), 2-16.
11. Galipoglu, E., Kotzab, H., Teller, C., Yumurtaci Hüseyinoglu, I. Ö., & Pöppelbuß, J. (2018). Omni-channel retailing research–state of the art and intellectual foundation. International Journal of Physical Distribution & Logistics Management, 48(4), 365-390.
12. De Carvalho, J. L. G., & Campomar, M. C. (2014). Multichannel at retail and Omni-channel: Challenges for Marketing and Logistics. Business and Management Review, 4(3), 103-113.
13. Gawor, T., & Hoberg, K. (2019). Customers’ valuation of time and convenience in e-fulfillment. International Journal of Physical Distribution & Logistics Management, 49(1), 75-98.
14. Ge, C., & Zhu, J. (2023). Effects of BOPS implementation under market competition and decision timing in Omni channel retailing. Computers & Industrial Engineering, 179, 109227.
15. Hagberg, J., Sundstrom, M., & Egels-Zandén, N. (2016). The digitalization of retailing: an exploratory framework. International Journal of Retail & Distribution Management, 44(7), 694-712.
16. Hosseini, S., Merz, M., Röglinger, M., & Wenninger, A. (2018). Mindfully going omni-channel: An economic decision model for evaluating Omni-channel strategies. Decision Support Systems, 2018, 7, 39-53.
17. Hübner, A., Kuhn, H., & Wollenburg, J. (2016). Last mile fulfilment and distribution in omni-channel grocery retailing: A strategic planning framework. International Journal of Retail & Distribution Management, 44(3), 228-247.
18. Hübner, A., Wollenburg, J., & Holzapfel, A. (2016). Retail logistics in the transition from multi-channel to omni-channel. International Journal of Physical Distribution & Logistics Management, 46(6/7), 562-583.
19. Huré, E., Picot-Coupey, K., & Ackermann, C. L. (2017). Understanding omni-channel shopping value: A mixed-method study. Journal of Retailing and Consumer Services, 39, 314-330.
20. Ishfaq, R., Defee, C. C., Gibson, B. J., & Raja, U. (2016). Realignment of the physical distribution process in Omni-channel fulfillment. International Journal of Physical Distribution & Logistics Management, 46(6/7), 543-561.
21. Jensen, E. (2018). Omni Channel Retailing in Large Size Businesses: An Exploratory Case Study of a Swedish Fast Fashion Retailer.
22. Kang, J. Y. M. (2019). What drives Omni channel shopping behaviors? Fashion lifestyle of social-local-mobile consumers. Journal of Fashion Marketing and Management: An International Journal.
23. Kembro, J. H., Norrman, A., & Eriksson, E. (2018). Adapting warehouse operations and design to Omni-channel logistics: A literature review and research agenda. International Journal of Physical Distribution & Logistics Management, 48(9), 890-912.
24. Kim, J. C., & Chun, S. H. (2018). Cannibalization and competition effects on a manufacturer's retail channel strategies: Implications on an Omni-channel business model. Decision Support Systems, 109, 5-14.
25. Krasonikolakis, I., & Chen, C. H. S. (2023). Unlocking the shopping myth: Can smartphone dependency relieve shopping anxiety? A mixed-methods approach in UK Omnichannel retail. Information & Management, 60(5), 103818.
26. Li, Q., Luo, H., Xie, P. X., Feng, X. Q., & Du, R. Y. (2015). Product whole life-cycle and omni-channels data convergence oriented enterprise networks integration in a sensing environment. Computers in Industry, 70, 23-45.
27. Li, Z., Guan, X., & Mei, W. (2023). Coupon promotion and its cross-channel effect in omnichannel retailing industry: A time-sensitive strategy. International Journal of Production Economics, 258, 108778.
28. Lim, S. F. W., Jin, X., & Srai, J. S. (2018). Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution & Logistics Management, 48(3), 308-332.
29. Liu, P., Hendalianpour, A., Feylizadeh, M., & Pedrycz, W. (2022). Mathematical modeling of Vehicle Routing Problem in Omni-Channel retailing. Applied Soft Computing, 131, 109791.
30. Marchet, G., Melacini, M., Perotti, S., Rasini, M., & Tappia, E. (2018). Business logistics models in omni-channel: a classification framework and empirical analysis. International Journal of Physical Distribution & Logistics Management, 48(4), 439-464.
31. Mena, C., & Bourlakis, M. (2016). Retail logistics special issue. International Journal of Physical Distribution & Logistics Management, 46(6/7).
32. Murfield, M., Boone, C. A., Rutner, P., & Thomas, R. (2017). Investigating logistics service quality in omni-channel retailing. International Journal of Physical Distribution & Logistics Management, 47(4), 263-296.
33. Park, S., & Lee, D. (2017). An empirical study on consumer online shopping channel choice behavior in Omni-channel environment. Telematics and Informatics, 34(8), 1398-1407.
34. Paul, J., Agatz, N., Spliet, R., & De Koster, R. (2019). Shared Capacity Routing Problem− An omni-channel retail study. European Journal of Operational Research, 273(2), 731-739.
35. Pruyt, E. (2013). Small system dynamics models for big issues: Triple jump towards real-world complexity. Delft: TU Delft Library.
36. Rao, S., Goldsby, T. J., Griffis, S. E., & Iyengar, D. (2011). Electronic logistics service quality (e‐LSQ): its impact on the customer’s purchase satisfaction and retention. Journal of Business Logistics, 32(2), 167-179.
37. Ryu, M. H., Cho, Y., & Lee, D. (2019). Should small-scale online retailers diversify distribution channels into offline channels? Focused on the clothing and fashion industry. Journal of Retailing and Consumer Services, 47, 74-77.
38. Sankaranarayanan, H. B., & Lalchandani, J. (2019). Smart Omni channel Architecture for Air Travel Applications Using Big Data Techniques. In International Conference on Computer Networks and Communication Technologies (pp. 661-669). Springer, Singapore.
39. Sharma, M., Gupta, M., & Joshi, S. (2020). Adoption barriers in engaging young consumers in the Omni-channel retailing. Young Consumers, 21(2), 193-210.
40. Sosnowska, J., Hofmans, J., & De Fruyt, F. (2019). Relating emotional arousal to work vigor: A dynamic systems perspective. Personality and Individual Differences, 136, 178-183.
41. Tao, Z., Zhang, Z., Wang, X., & Shi, Y. (2018, November). Simulation Analysis of Omni-channel Strategy Based on System Dynamics: A Case Study of Company X. In IOP Conference Series: Materials Science and Engineering, 439, 3:03239, IOP Publishing.
42. Vasilyev, A., Maier, S., & Seifert, R. W. (2023). Assortment optimization using an attraction model in an Omni channel environment. European Journal of Operational Research, 306(1), 207-226.
43. Von Briel, F. (2018). The future of Omni channel retail: A four-stage Delphi study. Technological Forecasting and Social Change, 132, 217-229.
44. Wang, Q., McCalley, J. D., Zheng, T., & Litvinov, E. (2016). Solving corrective risk-based security-constrained optimal power flow with Lagrangian relaxation and Benders decomposition. International Journal of Electrical Power & Energy Systems, 75, 255-264.
45. Wollenburg, J., Holzapfel, A., Hübner, A., & Kuhn, H. (2018). Configuring retail fulfillment processes for Omni-channel customer steering. International Journal of Electronic Commerce, 22(4), 540-575.
46. Wollenburg, J., Hübner, A., Kuhn, H., & Trautrims, A. (2018). From bricks-and-mortar to bricks-and-clicks: Logistics networks in Omni-channel grocery retailing. International Journal of Physical Distribution & Logistics Management, 48(4), 415-438.
47. Zhang, M., Ren, C., Wang, G. A., & He, Z. (2018). The impact of channel integration on consumer responses in Omni-channel retailing: The mediating effect of consumer empowerment. Electronic Commerce Research and Applications, 28, 181-193.
48. Zhao, Y., Li, Y., Yao, Q., & Guan, X. (2023). Dual-channel retailing strategy vs. omni-channel buy-online-and-pick-up-in-store behaviors with reference freshness effect. International Journal of Production Economics, 108967.
