طراحی زنجیره تأمین معکوس در صنعت مد سریع برای مدیریت ارتباط با مشتری با استفاده از داده‌کاوی و مدل‌سازی ریاضی

موسویان, سیده غزل; زینال نژاد, معصومه

طراحی زنجیره تأمین معکوس در صنعت مد سریع برای مدیریت ارتباط با مشتری با استفاده از داده‌کاوی و مدل‌سازی ریاضی

نوع مقاله : پژوهشی

نویسندگان

¹ کارشناسی ارشد گروه مهندسی صنایع، دانشکده فنی و مهندسی، واحد تهران غرب، دانشگاه آزاد اسلامی، تهران، ایران

² استادیار، گروه مهندسی صنایع، دانشکده فنی و مهندسی، واحد تهران غرب، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

ازآنجاکه چرخه عمر کوتاه، عدم قطعیت در تقاضا و سرعت در پاسخگویی از مهم‌ترین ویژگی‌های مد سریع است، بهبود مدیریت ارتباط با مشتری از اهمیت ویژه‌ای در این صنعت برخوردار است. تحولات اخیر در صنعت پوشاک جهان موجب ایجاد بازار رقابتی گردیده و اصلاح ساختار چنین زنجیره تأمین انعطاف‌پذیری، اهمیتی دوچندان پیدا می‌کند. هدف تحقیق حاضر یکپارچه‌سازی سیاست‌های مدیریت ارتباط با مشتری و طراحی زنجیره تأمین معکوس در حوزه مد سریع به‌منظور کاهش هزینه‌ها و افزایش رضایت‌مندی مشتریان است. طی دو سال، تحلیل اطلاعات آخرین خرید، تداوم خریدها و ارزش ریالی خرید 659 هزار رکورد واقعی مرتبط با مشتریان 21 فروشگاه زنجیره‌ای پوشاک در تهران با استفاده از الگوریتم K-means منجر به خوشه‌بندی مشتریان در 5 گروه و تعیین میزان تخفیف هر گروه گردید. جهت تعیین مکان بهینه مرکز تعمیرات و مراکز ترکیبی جمع‌آوری کالاهای مرجوعی، مدل ریاضی طراحی و با روش بهینه‌سازی تصادفی به‌صورت سناریومحور حل شد. نتایج نشان داد مراکز ترکیبی لزوماً در منطقه فروشگاه‌های با فروش بیشتر قرار نمی‌گیرند، بلکه بایستی نرخ مرجوعی کالا و میزان تقاضا به‌طور هم‌زمان لحاظ گردند. مطابق نمودار پارتو مدل، دوتایی مقادیر تابع هدف هزینه و رضایت‌مندی بین اعداد 7/4 میلیارد ریال برای هزینه و 2185 برای رضایت‌مندی، و 2/6 میلیارد ریال برای هزینه و 3156 برای رضایت‌مندی متغیر است. بازه حداقل و حداکثر تخفیفات برای خرید کالای جدید 5% تا 30% و برای تخفیف تعمیر کالا 10% تا 60% محاسبه شد. مدل ارائه‌شده در این پژوهش، عمومیت استفاده در صنایع خرده‌فروشی تندگردش از جمله کالاهای فاسدشدنی را دارد.

کلیدواژه‌ها

20.1001.1.20089198.1401.24.76.3.4

موضوعات

طراحی و توسعه شبکه زنجیره تأمین/ لجستیک

عنوان مقاله [English]

Reverse Supply Chain Design in the Fast Fashion Industry for Customer Relationship Management Using Data Mining and Mathematical Modeling

نویسندگان [English]

Seyedeh Ghazal Mousavian ¹
Masoomeh Zeinalnezhad ²

¹ Department of Industrial Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran.

² Department of Industrial Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran.

چکیده [English]

Since the short life cycle, uncertainty in demand, and speed in response are the most important characteristics of fast fashion, improving customer relationship management (CRM) is of particular importance in this industry. Recent developments in the world's clothing industry have created a competitive market, and reforming the structure of flexible supply chains in this field has become very important. This research aims to integrate CRM policies and reverse supply chain design in the field of fast fashion in order to reduce costs and increase customer satisfaction. The analysis of 659 thousand real records related to the information of the last purchase, the continuity of purchases and the value of purchases related to the customers of 21 clothing chain stores in Tehran during two years using the K-means algorithm led to the clustering of customers into 5 groups and then the amount of discount for each group were determined. In order to determine the optimal location of the repair center and combined centers for the collection of returned goods, a mathematical model was designed and solved using the random optimization method in a scenario-oriented manner. The results showed that combined centers are not necessarily located in the area of stores with higher sales, but the return rate of goods and the amount of demand should be taken into account at the same time. According to the Pareto model diagram, the binary values of the objective function of cost and satisfaction vary between the numbers of 4.7 billion Rials for cost and 2185 for satisfaction, and 6.2 billion Rials for cost and 3156 for satisfaction. The range of minimum and maximum discounts for the purchase of new goods was calculated from 5% to 30% and for the repair of goods from 10% to 60%. The model presented in this research is generally used in fast-moving retail industries, including perishable goods.

کلیدواژه‌ها [English]

Reverse Supply Chain
Fast fashion Industry
Customer Relationship Management (CRM)
Data Mining
Uncertainty

مراجع

Malthouse, M. Haenlein, B. Skiera, E. Wage and M. Zhang, “Managing Customer Relationships in the Social Media Era: Introducing the Social CRM House,” J MARKETING, Vol. 27, 2013.
Soltani. “Fast fashion, the solution for the development of Iran's garment industry,” Textile Science and Technology Quarterly, Year 5, Number 1, Spring 2015. (In Persion)
Zhang and J. Feng, “Price of Identical Product with Gray Market Sales: An Analytical Model and Empirical Analysis,” INFORM SYST RES, Vol. 28, 2017.
Liang and Ch. Hai, “An Online Mall CRM Model Based on Data Mining,” QUANT Logic-Soft Computing. Springer International Publishing, 2017.
Bahari and M. Elayidom, “An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour,” ICICT, PP. 725-731, 2015.
Azizi and H. Fazlolahtabar, “Designing a reverse supply chain framework with exposure to potential failure modes,” The First International Conference on Industrial Engineering, Management and Accounting, 1394. (In Persion)
Moghadaspoor, M.S. Jebel Ameli and A. Bozorgi Amiri. “Providing a closed-loop supply chain model considering third-party factors: a case study,” Scientific journal of supply chain management, Year 22, Number 66, Spring 2019. (In Persion).
Mehrjoo and J. Pasek, “Risk assessment for the supply chain of fast fashion apparel industry: a system dynamics framework,” INT J PROD RES, Vol. 54, 2016.
Tang and L. Veelenturf, “The Strategic Role of Logistics in the Industry 4.0 era,” TRANSPORT RES E-LOG, Vol.129, PP. 1-11, 2019.
Richter, “The Growing Weight of Amazon’s Logistics Costs,” Statista, 2019.
Lee and M. Dong, “A heuristic approach to logistics network design for end-oflease computer products recovery,” TRANSPORT RES E, Vol. 44, 2018.
Desiderio, L. Garcia, D. Hall, A. Segre and M. Vittuari, “Social sustainability tools and indicators for the food supply chain: A systematic literature review,” SUSTAIN PRO CONS, Vol.30, PP. 527-540, 2022.
Wren, “Sustainable supply chain management in the fast fashion Industry: A comparative study of current efforts and best practices to address the climate crisis,” Cleaner Logistics and Supply Chain, Vol. 4, 2022.
Yadollahiniaa, E. Teimourya and M. Paydarb, “Tire forward and reverse supply chain design considering customer relationship management,” Resour Conserv & Recycl, Vol.138 PP. 215-228, 2018.
Koosha and S. Tabari, “Designing a customer relationship management evaluation system,” Scientific journal of supply chain management, Year 20, Number 61, Autumn 2017.
Zhang and J. Feng, “Price of Identical Product with Gray Market Sales: An Analytical Model and Empirical Analysis,” INFORM SYST RES, 2017.
Jahanbakhsh, H. Tohidi, “Competitive design of perishable goods logistics chain network based on optimizing demand and increasing customer satisfaction,” Scientific journal of supply chain management, Year 22, Number 69, Winter 2019. (In Persion)
Alfieri, A. DeMarco and E. Pastore, “Last mile logistics in Fast Fashion supply chains: a case study,” IFAC-Papers Online, Vol. 52, PP. 1693-1698, 2019.
Gabrielli, I. Baghi and V. Codeluppi, “Consumption practices of fast fashion products: a consumer-based approach,” J of Fashion Marketing and Management: An Intl J, Vol. 17(2), PP. 206-224, 2013.
Agrawal, S.A. Smith, “Optimal inventory management for a retail chain with diverse store demands,” Eur. J. Oper. Res, Vol. 225 (3), PP. 393–403, 2017.
Oliveira, G. Miranda, M. Dias, “Sustainable practices in slow and fast fashion stores: What does the customer perceive”, Cleaner Eng and Techno, Vol. 6, 2022.
Wang, L. Wei, L. Menghan, Y. Xianyi, W. Zhenfeng, Z. Zhenzhen and W. Liang, “Intelligent selection of delivery parties for fresh agricultural product based on third-party logistics in smart city,” SUSTAIN Energy Technologies and Assessments, Vol. 52, 2022.
Jauhar, S. Hassanzadeh and H. Zolfagharinia, A proposed method for third-party reverse logistics partner selection and order allocation in the cellphone industry,” COMPUT IND ENG, Vol. 162, 2021.
Venkatesh, “Reverse Logistics: An Imperative Area of Research for Fashion Supply Chain,” IUP Journal of Supply Chain Management, Vol. 7, PP. 77-89, 2010.
Caro, F. Babio and F. Pena, (2019). “Coordination of inventory distribution and price markdowns for clearance sales at zara,” In Operations in an Omnichannel World, PP. 311-339, 2019.
Yıldız and M. Hekimoglu, “Markdown optimization in apparel retail sector,” In International Conference on Advances in National Brand and Private Label Marketing, PP. 50-57, 2020.
Fares, M. Lebbar and N. Sbihi, “Quick response in fast fashion retail: An optimization supply chain responsiveness model,” INT Conference on Optimization and Applications, PP. 1-5, 2018.
Arrigo, “Customer relationships and supply chain management in the fast fashion industry,” In Diverse methods in customer relationship marketing and management, PP. 1-16, 2018.
Cai, T. Choi and T. Zhang, “Commercial used apparel collection operations in retail supply chains,” EUR J OPER RES, Vol. 298(1), PP. 169-181, 2022.
Wu, Y. Ran and S. Zhu, “Optimal pricing strategy: How to sell to strategic consumers?,” INT J PROD ECON, Vol. 244, 2022.
Zhang, J. Chen and J. Lin, “Market targeting with social influences and risk aversion in a co-branding alliance,” EUR J OPER RES, Vol. 297(1), PP. 301-318, 2022.
Yu and W. Solvang, “A carbon-constrained stochastic optimization model with augmented multi-criteria scenario-based risk-averse solution for reverse logistics network design under uncertainty,” J Cleaner Production, Vol.164, PP.1248-1267, 2017.
Gunantara, “A review of multi-objective optimization: Methods and its applications,” Cogent Engineering, 2018.