شناسایی و بررسی روابط علی-معلولی معیارهای تاثیر گذار بر قیمت فروش در شبکه توزیع امنی-چنل با استفاده از روش دیمتل
محورهای موضوعی :
مدیریت صنعتی
Mehrdad Bahremand
1
(
Department of Industrial Engineering, Qeshm Branch, Islamic Azad University, Qeshm, Iran
)
Roya Soltani
2
(
Assistant professor, Department of Industrial Engineering, KHATAM University, Tehran, Iran
)
Rasoul Karimi
3
(
Department of Industrial Engineering, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran
)
تاریخ دریافت : 1401/07/05
تاریخ پذیرش : 1401/11/03
تاریخ انتشار : 1401/12/01
کلید واژه:
قیمت فروش,
دیمتل,
روابط علی-معلولی,
توزیع امنی-چنل,
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 (کانالهای متعدد ارتباطی به صورت همزمان و با اطلاعات یکسان). 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 دنیال بررسی روابط علی-معلولی معیارهای تاثیر گذار بر قیمت فروش 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 قطعیت‌های آتی را داشته باشد. نتایج نشان داد که مهم ترین عامل موثر در فرآیند قیمت گذاری در توزیع امنی چنل می‌توان به عامل موجودی محصول اشاره نمود. همچنین عامل ظرفیت توزیع نیز تاثیر بسزایی بر روی قیمت‌گذاری در سیستم توزیع امنی-چنل دارد.
چکیده انگلیسی:
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 in multiple ways at the same time (multiple communication channels at the same time and with the same information). 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 are investigating the cause-effect relationship of the criteria affecting the sales price in the Omni-Chanel distribution network using the DEMATEL method. Therefore, by using DEMETAL'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. The results showed that the most important effective factor in the pricing process in the safe distribution of the channel can be pointed to the product inventory factor. Also, the distribution capacity factor has a significant impact on the pricing in the Omni-Channel distribution system.
منابع و مأخذ:
Chen, X., Wu, S., Wang, X., & Li, D. (2018). Optimal pricing strategy for the perishable food supply chain. International Journal of Production Research, 1-14.
Chun, S. H., & Park, S. Y. (2019). Hybrid marketing channel strategies of a manufacturer in a supply chain: game theoretical and numerical approaches. Information Technology and Management, 1-16.
Du, S., Wang, L., & Hu, L. (2019). Omnichannel management with consumer disappointment aversion. International Journal of Production Economics, 215, 84-101.
Ettl, M. R., Harsha, P., & Subramanian, S. (2015). S. Patent Application No. 14/289,123.
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.
Gong, Y., & Hao, Y. (2018, August). The Construction of Rebate Network Channel in the Transformation and Upgrading of Entity Retailers. In 2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)(pp. 1-5). IEEE.
Hajikhani, A., Khalilzadeh, M., & Sadjadi, S. J. (2018). A fuzzy multi-objective multi-product supplier selection and order allocation problem in supply chain under coverage and price considerations: An urban agricultural case study. Scientia Iranica, 25(1), 431-449.
Harsha, P., Subramanian, S., & Uichanco, J. (2019). Dynamic Pricing of Omnichannel Inventories: Honorable Mention—2017 M&SOM Practice-Based Research Competition. Manufacturing & Service Operations Management, 21(1), 47-65.
Jiang, Y., Liu, L., & Lim, A. (2020). Optimal pricing decisions for an omni‐channel supply chain with retail service. International Transactions in Operational Research.
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.
Kienzler, M., & Kowalkowski, C. (2017). Pricing strategy: A review of 22 years of marketing research. Journal of Business Research, 78, 101-110.
Lei, Y. M., Jasin, S., Uichanco, J., & Vakhutinsky, A. (2018). Randomized product display (ranking), pricing, and order fulfillment for e-commerce retailers. Stefanus and Uichanco, Joline and Vakhutinsky, Andrew, Randomized Product Display (Ranking), Pricing, and Order Fulfillment for E-commerce Retailers (November 9, 2018).
Lei, Y., Jasin, S., & Sinha, A. (2018). Joint dynamic pricing and order fulfillment for e-commerce retailers. Manufacturing & Service Operations Management, 20(2), 269-284.
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 production, 172, 2931-2941.
Liu, J., & Xu, Q. (2020). Joint Decision on Pricing and Ordering for Omnichannel BOPS Retailers: Considering Online Returns. Sustainability, 12(4), 1539.
Modak, N. M., & Kelle, P. (2019). Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand. European Journal of Operational Research, 272(1), 147-161.
Quezada, L. E., López-Ospina, H. A., Palominos, P. I., & Oddershede, A. M. (2018). Identifying causal relationships in strategy maps using ANP and DEMATEL. Computers & Industrial Engineering, 118, 170-179.
Saha, S., Modak, N. M., Panda, S., & Sana, S. S. (2018). Managing a retailer’s dual-channel supply chain underprice-and delivery time-sensitive demand. Journal of Modelling in Management, 13(2), 351-374.
Simon, H., & Fassnacht, M. (2019). Price Management for Consumer Goods. In Price Management(pp. 389-416). Springer, Cham.
Taleizadeh, A. A., Akhavizadegan, F., & Ansarifar, J. (2019). Pricing and quality level decisions of substitutable products in online and traditional selling channels: game-theoretical approaches. International Transactions in Operational Research, 26(5), 1718-1751.
Wu, J., Zhao, C., Yan, X., & Wang, L. (2020). An Integrated Randomized Pricing Strategy for Omni-channel Retailing. International Journal of Electronic Commerce, 24(3), 391-418.
Zhu, X., Mukhopadhyay, S. K., & Yue, X. (2016). Mixed channels for apparel sales. In Analytical modeling research in fashion business(pp. 79-100). Springer, Singapore.
Zhuang, H., Leszczyc, P. T. P., & Lin, Y. (2018). Why is price dispersion higher online than offline? The impact of retailer type and shopping risk on price dispersion. Journal of Retailing, 94(2), 136-153.
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Chen, X., Wu, S., Wang, X., & Li, D. (2018). Optimal pricing strategy for the perishable food supply chain. International Journal of Production Research, 1-14.
Chun, S. H., & Park, S. Y. (2019). Hybrid marketing channel strategies of a manufacturer in a supply chain: game theoretical and numerical approaches. Information Technology and Management, 1-16.
Du, S., Wang, L., & Hu, L. (2019). Omnichannel management with consumer disappointment aversion. International Journal of Production Economics, 215, 84-101.
Ettl, M. R., Harsha, P., & Subramanian, S. (2015). S. Patent Application No. 14/289,123.
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.
Gong, Y., & Hao, Y. (2018, August). The Construction of Rebate Network Channel in the Transformation and Upgrading of Entity Retailers. In 2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS)(pp. 1-5). IEEE.
Hajikhani, A., Khalilzadeh, M., & Sadjadi, S. J. (2018). A fuzzy multi-objective multi-product supplier selection and order allocation problem in supply chain under coverage and price considerations: An urban agricultural case study. Scientia Iranica, 25(1), 431-449.
Harsha, P., Subramanian, S., & Uichanco, J. (2019). Dynamic Pricing of Omnichannel Inventories: Honorable Mention—2017 M&SOM Practice-Based Research Competition. Manufacturing & Service Operations Management, 21(1), 47-65.
Jiang, Y., Liu, L., & Lim, A. (2020). Optimal pricing decisions for an omni‐channel supply chain with retail service. International Transactions in Operational Research.
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.
Kienzler, M., & Kowalkowski, C. (2017). Pricing strategy: A review of 22 years of marketing research. Journal of Business Research, 78, 101-110.
Lei, Y. M., Jasin, S., Uichanco, J., & Vakhutinsky, A. (2018). Randomized product display (ranking), pricing, and order fulfillment for e-commerce retailers. Stefanus and Uichanco, Joline and Vakhutinsky, Andrew, Randomized Product Display (Ranking), Pricing, and Order Fulfillment for E-commerce Retailers (November 9, 2018).
Lei, Y., Jasin, S., & Sinha, A. (2018). Joint dynamic pricing and order fulfillment for e-commerce retailers. Manufacturing & Service Operations Management, 20(2), 269-284.
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 production, 172, 2931-2941.
Liu, J., & Xu, Q. (2020). Joint Decision on Pricing and Ordering for Omnichannel BOPS Retailers: Considering Online Returns. Sustainability, 12(4), 1539.
Modak, N. M., & Kelle, P. (2019). Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand. European Journal of Operational Research, 272(1), 147-161.
Quezada, L. E., López-Ospina, H. A., Palominos, P. I., & Oddershede, A. M. (2018). Identifying causal relationships in strategy maps using ANP and DEMATEL. Computers & Industrial Engineering, 118, 170-179.
Saha, S., Modak, N. M., Panda, S., & Sana, S. S. (2018). Managing a retailer’s dual-channel supply chain underprice-and delivery time-sensitive demand. Journal of Modelling in Management, 13(2), 351-374.
Simon, H., & Fassnacht, M. (2019). Price Management for Consumer Goods. In Price Management(pp. 389-416). Springer, Cham.
Taleizadeh, A. A., Akhavizadegan, F., & Ansarifar, J. (2019). Pricing and quality level decisions of substitutable products in online and traditional selling channels: game-theoretical approaches. International Transactions in Operational Research, 26(5), 1718-1751.
Wu, J., Zhao, C., Yan, X., & Wang, L. (2020). An Integrated Randomized Pricing Strategy for Omni-channel Retailing. International Journal of Electronic Commerce, 24(3), 391-418.
Zhu, X., Mukhopadhyay, S. K., & Yue, X. (2016). Mixed channels for apparel sales. In Analytical modeling research in fashion business(pp. 79-100). Springer, Singapore.
Zhuang, H., Leszczyc, P. T. P., & Lin, Y. (2018). Why is price dispersion higher online than offline? The impact of retailer type and shopping risk on price dispersion. Journal of Retailing, 94(2), 136-153.
