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مدل تلفیقی دلفی–DANP فازی برای اولویت‌بندی چالش‌های زنجیره تأمین دیجیتال در صنعت لبنی | ||
| مدیریت زنجیره ارزش راهبردی | ||
| دوره 2، شماره 2 - شماره پیاپی 5، مرداد 1404، صفحه 117-139 اصل مقاله (963.63 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/svcm.2025.38675.1040 | ||
| نویسندگان | ||
| ندا نادرنیا* 1؛ سید محمد علی خاتمی فیروزآبادی2 | ||
| 1کارشناسی ارشد مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران. | ||
| 2استاد گروه مدیریت عملیات و فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران. | ||
| تاریخ دریافت: 25 مرداد 1404، تاریخ بازنگری: 30 شهریور 1404، تاریخ پذیرش: 02 مهر 1404 | ||
| چکیده | ||
| دیجیتال‌سازی زنجیره تأمین به‌عنوان محرکی کلیدی برای افزایش کارایی، کاهش هزینه‌ها و ارتقای رقابت‌پذیری صنایع به ویژه صنعت لبنی در سال‌های اخیر مورد توجه پژوهشگران و مدیران قرار گرفته است. با وجود مزایای بالقوه، اجرای موفق تحول دیجیتال با چالش‌های متعدد مدیریتی، دانشی و فناورانه مواجه است که می‌تواند تحقق اهداف استراتژیک سازمان‌ها را به تأخیر اندازد. هدف این پژوهش، شناسایی و اولویت‌بندی موانع دیجیتال‌سازی زنجیره تأمین در صنعت لبنی با استفاده از رویکرد علمی و تلفیقی دلفی–DANP فازی و ارزیابی پایداری نتایج از طریق تحلیل حساسیت است. این مطالعه از نوع پژوهش کاربردی و توصیفی–تحلیلی می‌باشد. فرآیند پژوهش شامل سه مرحله اصلی بود: (۱) استخراج موانع کلیدی از طریق مرور نظام‌مند ادبیات و مصاحبه با خبرگان صنعت؛ (۲) تعیین اهمیت موانع با استفاده از دلفی فازی و وزن‌دهی دقیق با روش DANP فازی؛ و (۳) سنجش پایداری و اعتبار نتایج از طریق تحلیل حساسیت، که امکان بررسی تأثیر تغییرات وزن موانع بر اولویت‌بندی کلی را فراهم کرد. این ترکیب روش‌شناسی، علاوه بر افزایش دقت، قابلیت اعتماد مدل را تضمین می‌کند. نتایج نشان می‌دهد که موانع مدیریتی و فناورانه بیشترین تأثیر را بر موفقیت دیجیتال‌سازی زنجیره تأمین دارند و تغییرات وزن آن‌ها می‌تواند اولویت‌بندی نهایی را تحت تأثیر قرار دهد. تحلیل حساسیت تأیید کرد که مدل ارائه‌شده از پایداری و قابلیت اعتماد بالایی برخوردار است. یافته‌ها همچنین امکان شناسایی موانع بحرانی و ارائه راهکارهای استراتژیک برای مدیران صنعت لبنی را فراهم می‌سازد. | ||
| کلیدواژه‌ها | ||
| دیجیتال‌سازی زنجیره تأمین؛ موانع تحول دیجیتال؛ روش دلفی فازی؛ روش DANP فازی؛ صنعت لبنی | ||
| عنوان مقاله [English] | ||
| An Integrated Fuzzy Delphi–DANP Model for Prioritizing Digital Supply Chain Challenges in the Dairy Industry | ||
| نویسندگان [English] | ||
| Neda Nadernia1؛ Seyed Mohammad Ali Khatami Firouzabadi2 | ||
| 1Master of Science in Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran. | ||
| 2Professor, Department of Operations and IT Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran. | ||
| چکیده [English] | ||
| In recent years, digitalization of supply chains has emerged as a key driver for enhancing operational efficiency, reducing costs, and improving the competitiveness of industries, particularly the dairy sector. Despite its potential benefits, successful implementation of digital transformation faces multiple managerial, knowledge-related, and technological barriers, which may delay the achievement of strategic objectives. This study aims to identify and prioritize the barriers to digital supply chain transformation in the dairy industry using a rigorous Fuzzy Delphi–DANP approach and to assess the robustness of the results through sensitivity analysis. This research is applied and descriptive–analytical in nature. The study was conducted in three main phases: (1) extraction of key barriers through a systematic literature review and expert interviews; (2) assessment of the importance of barriers using the Fuzzy Delphi method and precise weighting via the Fuzzy DANP approach; and (3) evaluation of the robustness and reliability of the results through sensitivity analysis, which enabled examination of the impact of variations in barrier weights on the overall prioritization. This integrated methodology enhances both the accuracy and the credibility of the findings. The findings indicate that managerial and technological barriers exert the greatest influence on the success of digital supply chain transformation. Sensitivity analysis demonstrated that changes in the weights of these barriers can affect the overall prioritization, while confirming that the proposed model maintains high robustness and reliability. Moreover, the results provide valuable insights for identifying critical barriers and formulating strategic recommendations for decision-makers in the dairy industry . | ||
| کلیدواژه‌ها [English] | ||
| Supply Chain Digitalization, Digital Transformation Barriers, Fuzzy Delphi Method, Fuzzy DANP, Dairy Industry | ||
| مراجع | ||
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مهدی‌پور، پژواک، قدیکلایی، احمد سعید، لجمـی، حسن فـرید، و آقاجانی، حسن‌علی. (1403). سنجش زنجیره تامین دیجیتال در صنایع تولیدی (مورد مطالعه: صنعت کالای خواب). فصلنامه پژوهش‌های مدیریت در ایران، 26(1). پورباقر، م., پور، پ. و.، و انکاری، م. (1402). بررسی عوامل موثر بر پذیرش اینترنت اشیا (IoT) در زنجیره تامین دیجیتال پوشاک با استفاده از تکنیک FUZZY AHP و WASPAS فصلنامه علوم و فناوری نساجی و پوشاک، 12(4). سلیمی زاویه، سیدقاسم، و شمس، سعیده. (1400). واکاوی مدیریت زنجیره تأمین دیجیتال (روند توسعه آینده). نشریه صنعت لاستیک ایران، 25(102)، 49.
Ageron, B., … O. B.-S. chain forum: A., & 2020, undefined. (2020). Digital supply chain: challenges and future directions. Taylor & FrancisB Ageron, O Bentahar, A GunasekaranSupply Chain Forum: An International Journal, 2020•Taylor & Francis, 21(3), 133–138. https://doi.org/10.1080/16258312.2020.1816361 Ajmera, D., Kharub, M., Krishna, A., & Gupta, H. (2024). Navigating the challenges of AI-enabled circular economy in the food and beverage sector: strategies for sustainable transformation. International Journal of Logistics Management, 36(2), 611–646. https://doi.org/10.1108/IJLM-09-2023-0408/FULL/XML Annosi, M. C., Brunetta, F., Bimbo, F., & Kostoula, M. (2021). Digitalization within food supply chains to prevent food waste. Drivers, barriers and collaboration practices. Industrial Marketing Management, 93, 208–220. https://doi.org/10.1016/j.indmarman.2021.01.005 Brintrup, A., Kosasih, E., … B. M.-T. D. S., & 2022, undefined. (n.d.). Digital supply chain surveillance: concepts, challenges, and frameworks. Elsevier. Retrieved March 8, 2025, from https://www.sciencedirect.com/science/article/pii/B9780323916141000228 Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157–177. https://doi.org/10.1016/j.compind.2018.02.010 Cabrera, V. E., Bewley, J., Breunig, M., Breunig, T., Cooley, W., De Vries, A., Fourdraine, R., Giordano, J. O., Gong, Y., Greenfield, R., Hu, H., Lenkaitis, A., Niu, M., Noronha, E. A. F., & Sullivan, M. (2025). Data Integration and Analytics in the Dairy Industry: Challenges and Pathways Forward. Animals 2025, Vol. 15, Page 329, 15(3), 329. https://doi.org/10.3390/ANI15030329 Cannas, V. G., Ciccullo, F., Pero, M., & Cigolini, R. (2020). Sustainable innovation in the dairy supply chain: enabling factors for intermodal transportation. International Journal of Production Research, 58(24), 7314–7333. https://doi.org/10.1080/00207543.2020.1809731 Chatterjee, S., Chaudhuri, R., Vrontis, D., & Galati, A. (2024). Digital transformation using industry 4.0 technology by food and beverage companies in post COVID-19 period: from DCV and IDT perspective. European Journal of Innovation Management, 27(5), 1475–1495. https://doi.org/10.1108/EJIM-07-2022-0374/FULL/XML Chen, S. H., & Lin, W. T. (2018). Analyzing determinants for promoting emerging technology through intermediaries by using a DANP-based MCDA framework. Technological Forecasting and Social Change, 131, 94–110. https://doi.org/10.1016/J.TECHFORE.2017.09.019 Deepu, T. S., & Ravi, V. (2022). Modelling of interrelationships amongst enterprise and inter-enterprise information system barriers affecting digitalization in electronics supply chain. Business Process Management Journal, 28(1), 178–207. https://doi.org/10.1108/BPMJ-12-2020-0554/FULL/HTML Derakhti, A., Santibanez Gonzalez, E. D. R., & Mardani, A. (2023). Industry 4.0 and Beyond: A Review of the Literature on the Challenges and Barriers Facing the Agri-Food Supply Chain. Sustainability 2023, Vol. 15, Page 5078, 15(6), 5078. https://doi.org/10.3390/SU15065078 Hammi, B., Zeadally, S., & Nebhen, J. (2023). Security Threats, Countermeasures, and Challenges of Digital Supply Chains. ACM Computing Surveys, 55(14 S). https://doi.org/10.1145/3588999 Hassoun, A., Garcia-Garcia, G., Trollman, H., Jagtap, S., Parra-López, C., Cropotova, J., Bhat, Z., Centobelli, P., & Aït-Kaddour, A. (2023). Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives. Current Research in Food Science, 7, 100535. https://doi.org/10.1016/J.CRFS.2023.100535 Jamali, A., Robati, M., Nikoomaram, H., Farsad, F., & Aghamohammadi, H. (2023). Urban Resilience Assessment Using Hybrid MCDM Model Based on DEMATEL-ANP Method (DANP). Journal of the Indian Society of Remote Sensing, 51(4), 893–915. https://doi.org/10.1007/S12524-023-01670-8/METRICS Karwasra, K., Soni, G., Mangla, S. K., & Kazancoglu, Y. (2021). Assessing dairy supply chain vulnerability during the Covid-19 pandemic. International Journal of Logistics Research and Applications. https://doi.org/10.1080/13675567.2021.1910221 Khanna, A., Jain, S., Burgio, A., Bolshev, V., & Panchenko, V. (2022). Blockchain-Enabled Supply Chain platform for Indian Dairy Industry: Safety and Traceability. Foods 2022, Vol. 11, Page 2716, 11(17), 2716. https://doi.org/10.3390/FOODS11172716 Kumar, R., & Kumar, D. (2023). Blockchain-based smart dairy supply chain: catching the momentum for digital transformation. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-07-2022-0141 Kumar, U., & Shankar, R. (2024). Smart dairy: Unleashing emerging ICT-enabled lean dairy supply chains through data-driven decision-making. International Journal of Information Management Data Insights, 4(2), 100297. https://doi.org/10.1016/J.JJIMEI.2024.100297 Malik, M., Gahlawat, V. K., Mor, R. S., & Hosseinian-Far, A. (2024). Towards white revolution 2.0: challenges and opportunities for the industry 4.0 technologies in Indian dairy industry. Operations Management Research 2024 17:3, 17(3), 811–832. https://doi.org/10.1007/S12063-024-00482-4 Menzies, J., Sabert, B., Hassan, R., & Mensah, P. K. (2024). Artificial intelligence for international business: Its use, challenges, and suggestions for future research and practice. Thunderbird International Business Review, 66(2), 185–200. https://doi.org/10.1002/tie.22370 Montgomery, H., Haughey, S., Security, C. E.-G. F., & 2020, undefined. (n.d.). Recent food safety and fraud issues within the dairy supply chain (2015–2019). Elsevier. Retrieved March 8, 2025, from https://www.sciencedirect.com/science/article/pii/S2211912420301012 Pandey, P., Jha, S., Res, S. S.-I. J. S. S. E., & 2017, undefined. (2019). Effectiveness of dairy based entrepreneurial developmental programmes. Ijsser.OrgP Pandey, SK Jha, S SinhaInt J Soc Sci Econ Res, 2017•ijsser.Org. https://ijsser.org/files_2019/ijsser_04__76.pdf Queiroz, M. M., Ivanov, D., Dolgui, A., & Fosso Wamba, S. (2022). Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of Operations Research, 319(1), 1159–1196. https://doi.org/10.1007/s10479-020-03685-7 Queiroz, M. M., Pereira, S. C. F., Telles, R., & Machado, M. C. (2019). Industry 4.0 and digital supply chain capabilities: A framework for understanding digitalisation challenges and opportunities. Benchmarking, 28(5), 1761–1782. https://doi.org/10.1108/BIJ-12-2018-0435/FULL/HTML Rahman, M., Emon, M. E. H., Antor, M. H., Haque, S. A., & Talapatra, S. (2024). Identification and prioritization of barriers to Industry 4.0 adoption in the context of food and beverage industries of Bangladesh. Benchmarking, 32(2), 757–783. https://doi.org/10.1108/BIJ-06-2023-0371/FULL/XML Rejeb, A., Rejeb, K., Keogh, J. G., & Zailani, S. (2022). Barriers to Blockchain Adoption in the Circular Economy: A Fuzzy Delphi and Best-Worst Approach. Sustainability 2022, Vol. 14, Page 3611, 14(6), 3611. https://doi.org/10.3390/SU14063611 Salahudin, M., Baihaqi, I., AKUNTANSI, Y. L.-:, DAN, B., & 2024, undefined. (n.d.). Opportunities and Challenges of Digital Supply Chain: A Systematic Literature Review Using SCOR Framework. Transpublika.Co.IdMS Salahudin, I Baihaqi, YC LiuTRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN, 2024•transpublika.Co.Id. Retrieved March 8, 2025, from https://transpublika.co.id/ojs/index.php/Transekonomika/article/view/717 Sanders, N. R., Boone, T., Ganeshan, R., & Wood, J. D. (2019). Sustainable Supply Chains in the Age of AI and Digitization: Research Challenges and Opportunities. Journal of Business Logistics, 40(3), 229–240. https://doi.org/10.1111/JBL.12224 Serrano-Torres, G. J., López-Naranjo, A. L., Larrea-Cuadrado, P. L., & Mazón-Fierro, G. (2025). Transformation of the Dairy Supply Chain Through Artificial Intelligence: A Systematic Review. Sustainability (Switzerland), 17(3), 982. https://doi.org/10.3390/SU17030982/S1 Shakur, M. S., Lubaba, M., Debnath, B., Bari, A. B. M. M., & Rahman, M. A. (2024). Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy. Logistics 2024, Vol. 8, Page 27, 8(1), 27. https://doi.org/10.3390/LOGISTICS8010027 Sharma, M., Joshi, S., & Govindan, K. (2023). Overcoming barriers to implement digital technologies to achieve sustainable production and consumption in the food sector: A circular economy perspective. Sustainable Production and Consumption, 39, 203–215. https://doi.org/10.1016/J.SPC.2023.04.002 Shambayati, H., & Qahremani, F. (2024). Journal of Strategic Value Chain Management Factors Affecting the Adoption of Digital Technology in The Healthcare Value Chain in Neutrosophic Conditions in Semnan Province. Journal of Strategic Value Chain Management, 1(1), 51–71. https://doi.org/10.22075/svcm.2025.35409.1012 Torres Vergara, J. I., Saucedo Martínez, J. A., & Olivo Lucio, D. (2024). Resilient and sustainable supply chain criteria for performance evaluation: selection and ranking through fuzzy Delphi. Benchmarking, 31(3), 799–823. https://doi.org/10.1108/BIJ-05-2022-0283/FULL/XML Wang, L., He, Y., & Wu, Z. (2022). Design of a Blockchain‐Enabled Traceability System Framework for Food Supply Chains. Foods, 11(5). https://doi.org/10.3390/foods11050744 Wang, M., Islam, S., & Yang, W. (2025). Supply chain risks in the dairy industry. Benchmarking, ahead-of-print(ahead-of-print). https://doi.org/10.1108/BIJ-12-2023-0874/FULL/XML
Translated References [In Persian] Pourbagher, M., Pour, P. V., & Enkari, M. (2023). Investigating factors affecting the adoption of Internet of Things (IoT) in the digital supply chain of apparel using FUZZY AHP and WASPAS techniques. Journal of Textile and Apparel Science and Technology, 12(4). [In Persian] Mehdipour, P., Ghadikolaee, A. S., Lajimi, H. F., & Aghajani, H. A. (2024). Measuring digital supply chain in manufacturing industries (Case study: Bedding industry). Iranian Journal of Management Research, 26(1). [In Persian] Salimi-Zavieh, S., & Shams, S. (1400). Evaluation of digital supply chain management (Future development trend). Iran Rubber Industry Journal, 25(102), 49. [In Persian] | ||
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