بازطراحی شبکه زنجیره تامین خرده فروشی بر اساس قابلیت‌های چندگانه بازگشت پذیری

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکترای مدیریت صنعتی، پردیس البرز، دانشگاه تهران، تهران، ایران

2 استاد، دانشکده مهندسی صنایع، پردیس دانشکده‌‌‌های فنی، دانشگاه تهران، تهران، ایران

چکیده

روند رو به افزایش اختلالات زنجیره‌های تامین، اهمیت بررسی استراتژی‌های بازگشت‌‌پذیری را بیشتر نموده است. پژوهش حاضر یک مدل برنامه ریزی تصادفی دو مرحله‌ای عدد صحیح سناریو-محور برای رویارویی با ریسک‌های عملیاتی و اختلال در یک شبکه زنجیره تامین خرده‌فروشی ارائه می‌نماید. مدل پیشنهادی تصمیمات قبل و بعد از بروز اختلال را در نظر می‌گیرد. پنج استراتژی بازگشت‌پذیری در برگیرنده ابعاد مختلف قابلیت‌های بازگشت‌پذیری اعم از پیش‌کنشی، واکنشی و کیفیت طراحی زنجیره (شامل مستحکم‌سازی تسهیلات، نگهداری موجودی احتیاطی، ایجاد ظرفیت اضافی در برخی گره‌های شبکه، استفاده از سیاست تحویل مستقیم به فروشگاهها و پوشش چندگانه فروشگاهها)، در نظر گرفته شده است. مدل ارائه شده برای یک مطالعه موردی در صنعت خرده‌فروشی بکار گرفته شده است. تحلیل حساسیت روی پارامترهای اصلی انجام شده و رهنمودهای مدیریتی از آنها استخراج شده است. نتایج مدل نشان دهنده تاثیر مثبت بکارگیری استراتژی‌های بازگشت‌پذیری در کاهش هزینه کل در طراحی شبکه زنجیره تامین خرده‌فروشی می‌باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Retail supply chain network redesign based on multiple resilience capabilities

نویسندگان [English]

  • Reza Alikhani 1
  • Seyed Ali Torabi 2
1 Ph.D. Student of Industrial Management, Alborz Campus, University of Tehran, Tehran, Iran
2 Professor, School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
چکیده [English]

The increasing trend of supply chain disruptions in the recent decades has increased the importance of considering resilience strategies in supply chain network design/redesign problems. The present study provides a scenario-based mixed integer two-stage stochastic programming model for dealing with operational and disruption risks in a retail supply chain network redesign problem. The mode covers both pre-disruption and post-disruption decisions jointly. Five resilience strategies, including proactive, reactive, and chain design quality aspects (i.e. facility fortification, safety stock inventory holding, using excess capacity at some critical nodes of the network, using the direct to store delivery as the shipping strategy and multiple covering of retail stores), are considered. The model is applied for a case study in the retail industry. Several sensitivity analyses are carried out from which useful managerial insights are drawn to be used by top managers. The results show the positive effect of applying resilience strategies on the total cost reduction.

کلیدواژه‌ها [English]

  • Retail supply chain network redesign
  • Resilience strategies
  • Two-stage stochastic programming

[1]    Knemeyer A., Zinn M. W., Eroglu C. "Proactive planning for catastrophic events in supply chains." Journal of operations management, 27, no. 2 (2009): 141-153.

[2]    Craighead C. W., Blackhurst J., Rungtusanatham M. J., Handfield, R. B. "The severity of supply chain disruptions: design characteristics and mitigation capabilities." Decision Sciences, 38, no. 1 (2007): 131-156.

[3]    Hendricks K., Singhal V. R. "The effect of supply chain disruptions on long-term shareholder value, profitability, and share price volatility." Supply Chain Magazine, (2005).

[4]    Narasimhan R.,Talluri S. "Perspectives on risk management in supply chains." (2009): 114-118.

[5]    Wright J. "Taking a broader view of supply chain resilience." Supply Chain Management Review, 17, no. 2 (2013): 26-31.

[6]    Chopra S., Sodhi M. M. "Reducing the risk of supply chain disruptions." MIT Sloan Management Review, 55, no. 3 (2014): 72-80.

[7]    Jüttner U., Maklan S. "Supply chain resilience in the global financial crisis: an empirical study." Supply Chain Management: An International Journal, 16, no. 4 (2011): 246-259.

[8]    Ebrahimi M., Safari H., Sadeghi Moghadam M. R. “A Mathematical Model for Power Generation Expansion Planning with Considering Distributed Generation Units and Decreasing Carbon Dioxide,” Industrial Management Journal, vol. 9, no. 4, (2017): 563–586,.

[9]    Azaron A., Brown K. N., Tarim S. A., Modarres M. "A multi-objective stochastic programming approach for supply chain design considering risk." International Journal of Production Economics, 116, no. 1 (2008): 129-138.

[10]  Chowdhury M. M. H., Quaddus M. "Supply chain resilience: Conceptualization and scale development using dynamic capability theory." International Journal of Production Economics 188 (2017): 185-204.

[11]  Kamalahmadi M., Mellat Parast M. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research." International Journal of Production Economics, 171 (2016): 116-133.

[12]  Ribeiro J. P., Barbosa-Povoa A."Supply Chain Resilience: Definitions and quantitative modelling approaches–A literature review." Computers & Industrial Engineering, 115 (2018): 109-122.

[13]  Rahimian M. M. Rajabzadeh Ghatari A. “Measuring Supply Chain Resilience using Complex Adaptive Systems approach; Case Study: Iranian Pharmaceutical Industry,” Modern Researches in Decision Making, vol. 2, no. 2, (2017): 155–195.

[14]  Pettit T. J., Croxton K. L., Fiksel, J. "Ensuring supply chain resilience: development and implementation of an assessment tool" Journal of business logistics, 34, no. 1 (2013): 46-76.

[15]  Fakoor Sagihe A., Olfat L., Feizi K., Amiri M. 'A model of Supply chain resilience for competitiveness in Iranian automotive companies', Journal of Production and Operations Management, 5(1), (2014): 143-164.

[16]  Rice, J. B., & Caniato, F.  "Building a secure and resilient supply network." Supply Chain Management Review, V. 7, NO. 5 (SEPT./OCT. 2003), P. 22-30: ILL(2003).

[17]  Sheffi Y., & Rice Jr J. B."A supply chain view of the resilient enterprise." MIT Sloan management review, 47, no. 1 (2005): 41.

[18]  Sahebjamnia N., Torabi S. A., Mansouri S. A. "Integrated business continuity and disaster recovery planning: Towards organizational resilience." European Journal of Operational Research, 242, no. 1 (2015): 261-273.

[19]  Ponomarov S. Y., Holcomb M. C.  "Understanding the concept of supply chain resilience." The international journal of logistics management, 20, no. 1 (2009): 124-143.

[20]  Kim Y., Chen Y. S., Linderman K. "Supply network disruption and resilience: A network structural perspective." Journal of operations Management, 33 (2015): 43-59.

[21]  Rezapour S., Zanjirani Farahani R, Pourakbar M. "Resilient supply chain network design under competition: a case study." European Journal of Operational Research, 259, no. 3 (2017): 1017-1035.

[22]  Lim M. K., Mak H. Y., Shen Z. J. M."Agility and proximity considerations in supply chain design." Management Science, 63, no. 4 (2016): 1026-1041.

[23]  Sadghiani N. S., Torabi S. A., Sahebjamnia N. "Retail supply chain network design under operational and disruption risks." Transportation Research Part E: Logistics and Transportation Review, 75 (2015): 95-114.

[24]  Jabbarzadeh A., Fahimnia B., Sheu J. B., Moghadam H. S. "Designing a supply chain resilient to major disruptions and supply/demand interruptions." Transportation Research Part B: Methodological, 94 (2016): 121-149.

[25]  Baghalian A., Rezapour S., Farahani R. Z. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case." European Journal of Operational Research, 227, no. 1 (2013): 199-215.

[26]  Fattahi M., Govindan K., Keyvanshokooh E. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers." Transportation Research Part E: Logistics and Transportation Review, 101 (2017): 176-200.

[27]  Snyder L. V., Daskin, M. S."Reliability models for facility location: the expected failure cost case." Transportation Science, 39, no. 3 (2005): 400-416.

[28]  Schmitt A. J., Singh M. "A quantitative analysis of disruption risk in a multi-echelon supply chain." International Journal of Production Economics, 139, no. 1 (2012): 22-32.

[29]  Liberatore F., Scaparra M. P., Daskin M. S. "Hedging against disruptions with ripple effects in location analysis." Omega, 40, no. 1 (2012): 21-30.

[30]  Losada C., Scaparra M. P., O’Hanley J. R. "Optimizing system resilience: a facility protection model with recovery time." European Journal of Operational Research, 217, no. 3 (2012): 519-530.

[31]  Lim M. K., Bassamboo A., Chopra S., Daskin M. S.  "Facility location decisions with random disruptions and imperfect estimation." Manufacturing & Service Operations Management, 15, no. 2 (2013): 239-249.

[32]  Hasani A., Khosrojerdi A. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study." Transportation Research Part E: Logistics and Transportation Review, 87 (2016): 20-52.

[33]  Govindan K., Fattahi M., Keyvanshokooh E. "Supply chain network design under uncertainty: A comprehensive review and future research directions." European Journal of Operational Research, 263, no. 1 (2017): 108-141.

[34]  Lücker F., Seifert R. W."Building up resilience in a pharmaceutical supply chain through inventory, dual sourcing and agility capacity." Omega, 73 (2017): 114-124.

[35]  Cutter, C. “The inside story of what it took to keep a Texas grocery chain running in the chaos of Hurricane Harvey | Chip Cutter | Pulse | LinkedIn,” 2017. [Online]. Available: https://www.linkedin.com/pulse/inside-story-what-took-keep-texas-grocery-chain-running-chip-cutter. [Accessed: 14-Sep-2017].