درآمدی بر زنجیره تأمین پایدار و تحقیقات لجستیک: تحلیل کتابسنجی
محورهای موضوعی : مدیریتندا اکبرزاده 1 , سحر رضایی 2 , یاسمین طاهری 3 , امیر گلاب زایی 4
1 - دانشگاه خوارزمی
2 - دانشگاه خوارزمی
3 - دانشگاه خوارزمی
4 - دانشگاه آزاد اسلامی
کلید واژه: زنجیره تأمین پایدار , لجستیک , مدیریت زنجیره تأمین , لجستیک معکوس , اقتصاد دایره ای,
چکیده مقاله :
تحقیق حاضر به بررسی زنجیره تأمین پایدار و لجستیک از منظر علمی و تجزیه و تحلیل شبکه کتابسنجی می‌پردازد. با توجه به تحولات سریع فناوری و نیازهای رو به رشد بازار، مدیریت زنجیره تأمین به یکی از حیاتی‌ترین جنبه‌های عملکرد سازمان‌ها تبدیل شده است. این پژوهش به شناسایی و تجمیع رویکردها و روش‌های تصمیم‌گیری و مدل‌سازی در حوزه مدیریت زنجیره تأمین و لجستیک می‌پردازد. داده‌های علمی مرتبط با موضوع از پایگاه داده وب آو ساینس استخراج و تحلیل علم‌سنجی برای کشف ساختار فکری در ادبیات موجود استفاده شد. نتایج این مطالعه نشان می‌دهد که زنجیره تأمین پایدار و لجستیک به‌عنوان یک حوزه پژوهشی، بر جنبه‌های مختلفی مانند لجستیک معکوس، طراحی شبکه، اقتصاد دایره‌ای، و پایداری تأکید دارد. بر اساس تحلیل هم‌رخدادی و هم‌نگاری، چهار خوشه اصلی در میان مقالات شناسایی شد: چارچوب‌ها و لجستیک، لجستیک معکوس و پایداری، فناوری‌های نوظهور و دیجیتالیزه‌سازی، و مدیریت ریسک. این خوشه‌ها نشان‌دهنده تمرکز پژوهشی فعلی و مسیرهای احتمالی تحقیقات آینده در حوزه مدیریت زنجیره تأمین پایدار هستند. این تحقیق همچنین به شناسایی شکاف‌های موجود در ادبیات علمی پرداخته و پیشنهاداتی برای تحقیقات آینده ارائه می‌دهد. از جمله این شکاف‌ها می‌توان به نیاز به بررسی بیشتر درباره ادغام فناوری‌های نوین با مدیریت زنجیره تأمین و ارزیابی تأثیرات زیست‌محیطی و اجتماعی آن‌ها اشاره کرد. همچنین، نتایج حاکی از آن است که روش‌های تصمیم‌گیری و مدل‌سازی فعلی نیاز به بهبود و تطبیق با نیازهای جدید محیط زیست و جامعه دارند. در نهایت، این پژوهش با ارائه خط مشی برای توسعه آینده مدیریت زنجیره تأمین پایدار، مدیران را به درک بهتر از اهمیت مدیریت جامع و پایدار زنجیره تأمین و نیاز به انطباق با تغییرات محیطی سوق می‌دهد.
The current research examines the sustainable supply chain and logistics from a scientific point of view and analyzes the bibliographic network. Due to rapid technological developments and growing market needs، supply chain management has become one of the most critical aspects of organizations\' performance.
This research deals with the identification and consolidation of decision-making and modeling approaches and methods in the field of supply chain management and logistics. Scientific data related to the topic were extracted from the Web of Science database and scientometric analysis was used to discover the intellectual structure in the existing literature.
The results of this study show that sustainable supply chain and logistics، as a research field، emphasize various aspects such as reverse logistics، network design، circular economy، and sustainability. Based on co occurrence and co occurrence analysis، four main clusters were identified among the articles: frameworks and logistics، reverse logistics and sustainability، emerging technologies and digitization، and risk management.
These clusters indicate the current research focus and possible future research directions in the field of sustainable supply chain management. This research also identifies gaps in the scientific literature and provides suggestions for future research. Among these gaps، we can point out the need for more research on the integration of new technologies with the supply chain.
Management and the assessment of their environmental and social impacts. Also، the results indicate that the current decision-making and modeling methods need to be improved and adapted to the new needs of the environment and society.
Finally، by providing a policy for the future development of sustainable supply chain management، this research leads managers to a better understanding of the importance of comprehensive and sustainable supply chain management and the need to adapt to environmental changes..
Aryee, R. (2024). Theoretical perspectives in reverse logistics research. The International Journal of Logistics Management.
Arlbjørn, J.S., Paulraj, A. (2013). Special topic forum on innovation in business networks from A supply chain perspective: current status and opportunities for future research. J. Supply Chain Manag. 49 (4), 3–11. https://doi.org/10.1111/JSCM.12034.
Barraza, M. F. S., Davila, J. M. A., & Garcia, C. F. V. (2016). Supply chain value stream mapping: a new tool of operation management. Int. J. Qual. Reliab. Manag, 33(4), 518-534.
Bastas, A., & Liyanage, K. (2018). Sustainable supply chain quality management: a systematic review. Journal of Cleaner Production, 181, 726–744.
Behl, A., Jayawardena, N., Pereira, V., Jabeen, F., Jain, K., & Gupta, M. (2023). Engaging and motivating crowd-workers in gamified crowdsourcing mobile apps in the context of logistics and sustainable supply chain management. Annals of Operations Research, 1-31.
Bensalem, A., & Kin, V. (2019, January). A bibliometric analysis of reverse logistics from 1992 to 2017. In Supply Chain Forum: An International Journal (Vol. 20, No. 1, pp. 15-28). Taylor & Francis.
Beske-Janssen, P., Schaltegger, S., & Liedke, S. (2019). Performance measurement in sustainable supply chain management: Linking research and practice. In Handbook on the Sustainable Supply Chain (pp. 331-356). Edward Elgar Publishing.
Boateng, A. (2019). Supply chain management in the ghanaian building construction industry: a lean construction perspective. 430–439. https://doi.org/10.3311/CCC2019-060.
Bouzon, M., & Govindan, K. (2015). Reverse logistics as a sustainable supply chain practice for the fashion industry: an analysis of drivers and the Brazilian Case. Sustainable fashion supply chain management: From sourcing to retailing, 85-104.
Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European journal of operational research, 233(2), 299-312.
Brandenburg, M., & Rebs, T. (2015). Sustainable supply chain management: A modeling perspective. Annals of Operations Research, 229, 213-252.
Chen, L., Duan, D., Mishra, A. R., & Alrasheedi, M. (2022). Sustainable third-party reverse logistics provider selection to promote circular economy using new uncertain interval-valued intuitionistic fuzzy-projection model. Journal of Enterprise Information Management, 35(4/5), 955-987.
Demir, E., Syntetos, A., & Van Woensel, T. (2022). Last mile logistics: Research trends and needs. IMA Journal of Management Mathematics, 33(4), 549-561.
Hsueh, C. F. (2015). A bilevel programming model for corporate social responsibility collaboration in sustainable supply chain management. Transportation Research Part E: Logistics and Transportation Review, 73, 84-95.
Jaklic, J., Trkman, P., Groznik, A., & Stemberger, M. I. (2006). Enhancing lean supply chain maturity with business process management. Journal of Information and Organizational Sciences, 30(2), 205–223.
Jajja, M. S. S., Asif, M., Shah, S. A. A., & Chatha, K. A. (2019). Supply chain innovation research: content analysis based review. Benchmarking: An International Journal, 27(2), 666-694.
Liaqait, R. A., Warsi, S. S., Agha, M. H., Zahid, T., & Becker, T. (2022). A multi-criteria decision framework for sustainable supplier selection and order allocation using multi-objective optimization and fuzzy approach. Engineering Optimization, 54(6), 928-948.
Liu, A., Zhu, Q., Xu, L., Lu, Q., & Fan, Y. (2021). Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model. Transportation Research Part E: Logistics and Transportation Review, 150, 102319.
Liu, M., & Zhao, L. (2007, December). A composite weighted multi-objective optimal approach for emergency logistics distribution. In 2007 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 968-972). IEEE.
Meneghetti, A., & Monti, L. (2015). Greening the food supply chain: an optimisation model for sustainable design of refrigerated automated warehouses. International Journal of Production Research, 53(21), 6567-6587.
Morgan, T. R., Tokman, M., Richey, R. G., & Defee, C. (2018). Resource commitment and sustainability: a reverse logistics performance process model. International Journal of Physical Distribution & Logistics Management, 48(2), 164-182.
Nakov, Z., Acevski, S., & Zareski, R. (2014). Implementation of supply chain management (scm) in pharmaceutical company, general principles and case study. Macedonian Pharmaceutical Bulletin, 60(2), 75–82. https://doi.org/10.33320/maced.pharm.bull.2014.60.02.008.
Nikseresht, A., Golmohammadi, D., & Zandieh, M. (2024). Sustainable green logistics and remanufacturing: A bibliometric analysis and future research directions. The International Journal of Logistics Management, 35(3), 755-803.
Rebs, T. (2018). Quantitative modeling of sustainability in interorganizational supply chains. Social and Environmental Dimensions of Organizations and Supply Chains: Tradeoffs and Synergies, 119-134.
Saberi, S. (2018). Sustainable, multiperiod supply chain network model with freight carrier through reduction in pollution stock. Transportation Research Part E: Logistics and Transportation Review, 118, 421-444.
Sgarbossa, F., & Russo, I. (2017). A proactive model in sustainable food supply chain: Insight from a case study. International Journal of Production Economics, 183, 596-606.
Sitek, P., & Wikarek, J. (2015). A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management. International Journal of Production Research, 53(21), 6611-6628.
Stindt, D., Sahamie, R., Nuss, C., & Tuma, A. (2016). How transdisciplinarity can help to improve operations research on sustainable supply chains—a transdisciplinary modeling framework. Journal of Business Logistics, 37(2), 113-131.
Ülkü, M. A., Akgün, M., Venkatadri, U., Diallo, C., & Chadha, S. S. (2020). Managing environmental and operational risks for sustainable cotton production logistics: system dynamics modelling for a textile company. Logistics, 4(4), 34.
Xia, Y., Zeng, W., Xing, X., Zhan, Y., Tan, K. H., & Kumar, A. (2023). Joint optimisation of drone routing and battery wear for sustainable supply chain development: A mixed-integer programming model based on blockchain-enabled fleet sharing. Annals of Operations Research, 1-39.
Zeidyahyaee, N., Shokouhyar, S., Motameni, A., Yazdani-Chamzini, A., Šaparauskas, J., & Turskis, Z. (2024). An integrated model for the exploration and evaluation of the obstacles of sustainable logistics in the manufacturing sector. Journal of Competitiveness, 16(2).
