نقش هوش مصنوعی در چابکی زنجیره تامین بر اساس دیدگاه زنجیره تامین بشردوستانه
محورهای موضوعی : پردازش چند رسانه ای، سیستمهای ارتباطی، سیستمهای هوشمند
اسماعیل محبی کندسری
1
,
حسین بوداقی خواجه نوبر
2
*
,
بهارک یادگار جمشیدی
3
1 - دانشجوی دکتری، مدیریت بازرگانی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
2 - استادیار، گروه مدیریت، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
3 - دانشجوی دکتری، مدیریت دولتی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
کلید واژه: چابکی زنجیره تامین, زنجیره تامین بشردوستانه, نقش هوش مصنوعی.,
چکیده مقاله :
این پژوهش با هدف بررسی نقش هوش مصنوعی در چابکی زنجیره تامین بر اساس دیدگاه زنجیره تامین بشردوستانه اجرایی شد. در این تحقیق برای جمع‌آوری اطلاعات مربوط به تجزیه و تحلیل فرضیات از پرسشنامه به صورت پیمایشی استفاده گردید که این روش نیز به عنوان روش میدانی در این پژوهش مطرح می‌شود. جامعه آماری شامل کارکنان شرکتهای دانش بنیان مبتنی بر فناوریهای هوشمند در استان تهران بودند که بدلیل نامشخص بودن تعداد کل جامعه، نمونه بر اساس جدول مورگان 384 نفر در نظر گرفته شد و به همین تعداد پرسشنامه توزیع و جمع اوری شد. اطلاعات گردآوری‌شده توسط پرسشنامه‌ها به وسیله نرم‌افزار SPSS24 و AMOS24 با استفاده از مدل‌یابی معـادلات ساختاری مورد تجزیه و تحليل قرار گرفت. نتایج نشان داد همسویی اطلاعات اثر مثبت و معنی داری بر چابکی زنجیره تامین دارد. همکاری زنجیره تامین یک اثر میانجی و مثبتی بین همسویی اطلاعات و چابکی زنجیره تامین دارد. قابلیتهای تجزیه و تحلیل داده‌های بزرگ توسط هوش مصنوعی اثر تعدیل کننده و مثبتی بین همسویی اطلاعات و چابکی زنجیره تامین دارد. هوش مصنوعی نقش حیاتی در چابکی زنجیره تأمین بشردوستانه ایفا می‌کند. با استفاده از الگوریتم‌های پیشرفته و تحلیل داده‌ها، هوش مصنوعی می‌تواند به سازمان‌های بشردوستانه کمک کند تا به سرعت به تغییرات نیازها و شرایط محیطی پاسخ دهند. برای مثال، توانایی پیش‌بینی تقاضا و شناسایی الگوهای مصرف به این سازمان‌ها اجازه می‌دهد تا منابع را به طور مؤثرتری تخصیص دهند و از هدررفت جلوگیری کنند. این امر به ویژه در شرایط بحران، مانند بلایای طبیعی یا درگیری‌های انسانی، اهمیت بیشتری پیدا می‌کند.
Introduction: This research was carried out with the aim of investigating the role of artificial intelligence in the agility of the supply chain based on the perspective of the humanitarian supply chain.
Method: In this research, a survey questionnaire was used to collect information related to the analysis of hypotheses, and this method is also proposed as a field method in this research. The statistical population included the employees of knowledge-based companies based on smart technologies in Tehran province, and due to the uncertainty of the total population, the sample was considered to be 384 people based on Morgan's table, and the same number of questionnaires were distributed and collected. The information collected by questionnaires was analyzed by SPSS24 and AMOS24 software using structural equation modeling.
Results: The results showed that information alignment has a positive and significant effect on supply chain agility. Supply chain collaboration has a mediating and positive effect between information alignment and supply chain agility. Big data analysis capabilities by artificial intelligence have a positive moderating effect between information alignment and supply chain agility.
Discussion: Artificial intelligence plays a vital role in humanitarian supply chain agility. Using advanced algorithms and data analysis, artificial intelligence can help humanitarian organizations respond quickly to changing needs and environmental conditions. For example, the ability to forecast demand and identify consumption patterns allows these organizations to more effectively allocate resources and prevent waste. This is especially important in crisis situations, such as natural disasters or human conflicts.
[1] Abedi, Akter, S., & Wamba, S. F. (2019). Big data and disaster management: a systematic review and agenda for future research. Annals of Operations Research, 283(1), 939–959. https://doi.org/10.1007/s10479-017-2584-2
[2] Bayati, R., & Vahabzadeh Menshi, S. (2023). Investigating the adoption of blockchain technology on operational risk management and supply chain in Iran's steel industry, 9th International Conference on Management and Accounting Sciences, Tehran. [Persian]
[3] Beltagui, A., Nathan, K. & Gold, S. (2019). The Role of 3D Printing and Open Design on Adoption of Socially Sustainable Supply Chain Innovation. International Journal of Production Economics, doi:10.1016/j.ijpe.2019.07.035.
[4] Cao, C., Liu, Y., Tang, O. and Gao, X. (2021). A fuzzy bi-level optimization model for multiperiod post-disaster relief distribution in sustainable humanitarian supply chains. International Journal of Production Economics, Vol. 235, p. 108081.
[5] Chen, H. Y., Das, A., & Ivanov, D. (2019). Building resilience and managing post-disruption supply chain recovery: Lessons from the information and communication technology industry. International Journal of Information Management, 49, 330–342. https://doi.org/10.1016/j.ijinfomgt.2019.06.002
[6] Chen, L., Hendalianpour, A., Feylizadeh, M.R. and Xu, H. (2023). Factors Affecting the Use of Blockchain Technology in Humanitarian Supply Chain: A Novel Fuzzy Large-Scale Group-DEMATEL. Group Decision and Negotiation, 32, 359–394.
[7] Corsini, L., Aranda-Jan, C. B., & Moultrie, J. (2022). The impact of 3D printing on the humanitarian supply chain. Production Planning & Control, 33(6-7), 692-704.
[8] Deparday, V., Gevaert, C.M., Giuseppe, M.M., Soden, R.J. & Balog-Way, S. (2019). Machine Learning for Disaster Risk Management. In.: World Bank.
[9] Dolgui, A., Ivanov, D., & Sokolov, B. (2020). Reconfigurable supply chain: The X-network. International Journal of Production Research, 58(13), 4138–4163. https://doi.org/10.1080/00207543.2020.1774679
[10] Dubey, R., Altay, N. and Blome, C. (2019). Swift trust and commitment: The missing links for humanitarian supply chain coordination?. Annals of Operations Research, Vol. 283 No. 1, pp. 159–177.
[11] Dubey, R., Bryde, D. J., Foropon, C., Tiwari, M., Dwivedi, Y., & Schiffling, S. (2021). An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain. International Journal of Production Research, 59(5), 1586–1605. https://doi.org/10.1080/00207543.2020.1865583
[12] Dubey, R., Bryde, D. J., Dwivedi, Y. K., Graham, G., & Foropon, C. (2022). Impact of artificial intelligence-driven big data analytics culture on agility and resilience in humanitarian supply chain: A practice-based view. International Journal of Production Economics, 250, 108618.
[13] Duong, L. N. K., & Chong, J. (2020). Supply chain collaboration in the presence of disruptions: a literature review. International Journal of Production Research, 58(11), 3488–3507. https://doi.org/10.1080/00207543.2020.1712491
[14] Farah Bakhsh Mohammadi, S.K. (2021). The relationship between blockchain technology and supply chain management performance (case study: Iran Khodro Company). Conference: International Conference on Management, Tourism and Technology, Tehran. [Persian]
[15] Gaurav, K., Ramesh, A., Vipul J., Pervaiz, A., (2022). Enterprise Information Management Barriers to Information and Digital Technologies Adoption in Humanitarian Supply Chain Management: A Fuzzy AHP Approach. Journal of Enterprise Information Management, 10, 1-34.
[16] Hald, K. and Kinra, A. (2019). How the blockchain enables and constrains supply chain performance. Preprint version of paper accepted for publication in the NOFOMA Special Issue of the International Journal of Physical Distribution & Logistics Management.
[17] Hashemi Petrudi, S. H., & Jalali, R. (2022). Studying the human barriers to swift trust in the humanitarian supply chain. Journal of Sustainable Human Resource Management, 4(6), 160-143. [Persian]
[18] Hitt, M. A., Carnes, C. M., & Xu, K. (2016). A current view of resource-based theory in operations management: A response to Bromiley and Rau. Journal of Operations Management, 41(10), 107–109.
[19] Holmström, J. & Partanen, J. (2014). Digital Manufacturing-Driven Transformations of Service Supply Chains for Complex Products. Supply Chain Management: An International Journal, (4), 421. doi:10.1108/SCM-10-2013-0387.
[20] Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904–2915. https://doi.org/10.1080/00207543.2020.1750727
[21] Javadian N., Khani, M. and Mahdavi, I. (2021). Identifying effective factors on supply chain performance and improving them by using system dynamics techniques, Case study in Darugar Company Case study in darugar company. Management Research in Iran, 16(3), 39-58. [Persian]
[22] John, L., Gurumurthy, A., Soni, G and Jain, V. (2019). Modelling the inter-relationship between factors affecting coordination in a humanitarian supply chain: a case of Chennai flood relief. Annals of Operations Research, 283, 1227–1258.
[23] Kabra, G., Ramesh, A., Jain, V. and Akhtar, P. (2023). Barriers to information and digital technology adoption in humanitarian supply chain management: a fuzzy AHP approach. Journal of Enterprise Information Management, 36(2), 505-527.
[24] Kaplan, A. & Haenlein, M. (2019). Siri, Siri, in my Hand: Who’s the Fairest in the Land? On the Interpretations, Illustrations, and Implications of Artificial Intelligence. Business Horizons, 62 (1), 15–25. doi:10.1016/j.bushor.2018.08.004.
[25] Khajavi, S. H., Partanen, J. & Holmström, J. (2014). Additive Manufacturing in the Spare Parts Supply Chain. Computers in Industry, 65 (1), 50–63. doi:10.1016/j.compind.2013.07.008.
[26] Kovacs, G., & Spens, K. M. (2009). Identifying challenges in humanitarian logistics. International Journal of Physical Distribution & Logistics Management, 39, 506–528.
[27] Kunz, N., Reiner, G., and Gold, S. (2014). Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness. International Journal of Production Economics, 157, 261-272.
[28] Kwateng, K.O., Tetteh, F.K., Asare, N. Manu, D. (2022). Can intercluster coordination mediate the relationship between supply chain flexibility and humanitarian supply chain performance? Journal of Humanitarian Logistics and Supply Chain Management, 12(3), 449-470.
[29] L'Hermitte, C., Tatham, P., Bowles, M., & Brooks, B. (2016). Developing organisational capabilities to support agility in humanitarian logistics: An exploratory study. Journal of Humanitarian Logistics and Supply Chain Management. Vol. 6 No. 1, pp. 72-99.
[30] Merdivenci, F. A. H. R. İ. Y. E., Tekin, M. A. K. B. E. R., & Toraman, Y. (2024). Reverse Logistics Practices In Humanitarian Supply Chain Management: A Content Analysis. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 24(4).
[31] Momeni, M., Jafarnejad, A., & Hosseinzadeh, S. A. A. (2024). Presenting the Humanitarian Supply Chain Resilience Model in Epidemic Diseases (Similar to Coronavirus). Journal of Executive Management, 16(31), 271-291. [Persian]
[32] Mozaffari, M. M., & Ajalli, M. (2018). Critical Success Factors for Information Technology Implementation in Humanitarian Supply Chain Management. Business Intelligence Management Studies, 6(23), 5-32. [Persian]
[33] Pereira, E. T., & Shafique, M. N. (2024). The Role of Artificial Intelligence in Supply Chain Agility: A Perspective of Humanitarian Supply Chain. Engineering Economics, 35(1), 77-89.
[34] Pournader, M., Ghaderi, H., Hassanzadegan, A., & Fahimnia, B. (2021). Artificial intelligence applications in supply chain management. International Journal of Production Economics, 241, 108250. https://doi.org/10.101 6/j.ijpe. 2021.108250
[35] Radianti, J., Dokas, I., Boersma, K., Saad Noori, N., Belbachir, N. & Stieglitz, S. (2019). Enhancing Disaster Response for Hazardous Materials Using Emerging Technologies: The Role of AI and a Research Agenda. Paper presented at theEngineering Applications of Neural Networks, Cham.
[36] Rezaei, Q. & Rajabzadeh, Z. (2022). Examining the barriers to implementing a sustainable supply chain using the BWM method (case study: South Pars Energy Special Economic Zone Organization). The fifth conference of interdisciplinary studies in management and accounting. [Persian]
[37] Rodríguez-Espíndola, O., Chowdhury, S., Beltagui, A., & Albores, P. (2020). The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing. International Journal of Production Research, 58(15), 4610-4630.
[38] Rodríguez-Espíndola, O., Chowdhury, S., Beltagui, A., & Albores, P. (2020). The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing. International Journal of Production Research, 58(15), 4610–4630. https://doi.org/10.1080/00207543.2020.1761565
[39] Sadeghi Moghadam, M. R., Taghizadeh Yazdi, M. R., & Noferesti, R. (2022). Designing a Humanitarian Supply Chain Coordination Model for Housing Reconstruction after Floods: An Agent-Based Simulation. Industrial Management Journal, 13(3), 467-491. [Persian]
[40] Sajadiian, F., karimi takalo, S., & shoul, A. (2023). Analysis of using blockchain in the sustainable supply chain of the health sector. Health Information Management, 20(1), 14-21. [Persian]
[41] Schiffling, S., Hannibal, C., Tickle, M., & Fan, Y. (2020). The implications of complexity for humanitarian logistics: A complex adaptive systems perspective. Annals of Operations Research, 1–32. https://doi.org/10.1007/s10479-020- 03658-w
[42] Sharma, S. K., Misra, S. K., & Singh, J. B. (2020). The role of GIS-enabled mobile applications in disaster management: A case analysis of cyclone Gaja in India. International Journal of Information Management, 51, 102030. https://doi.org/10.1016/j.ijinfomgt.2019.10.015
[43] Sheikh Aghajani, M. & Ramezanian, M.R. (2019). Investigating the Impact of Supply Chain Dynamic Capacities on Its Performance by Mediating Supply Chain Resilience. Journal of Development & Evolution Mnagement, 36, 55-65. [Persian]
[44] Srinivasan, R., & Swink, M. (2018). An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Production and Operations Management, 27(10), 1849– 1867. https://doi.org/10.1111/poms.12746
[45] Sucipto, H. (2024). The Impact of Artificial Intelligence (AI) on Human Resource Management Practices. Management Studies and Business Journal (PRODUCTIVITY), 1(1), 138-145.
[46] Ţigu, G. and Călăreţu, B. (2013). Supply Chain Management Performance in Tourism. Continental Hotels Chain Case. Amfiteatru Economic, 15(33), 103-115.
[47] Tisnasasmita, B. J., Muafi, M., Isfianadewi, D., & Prajogo, W. (2023). Role of Supply Chain Collaboration and Organizational Agility on Promoting Relational Rents: A Literature Review. International Conference on Business and Technology.https://doi.org/10.1007/978-3-031-08093-7_50
[48] Tizroo, A. (2014). Modeling Agility of Supply Chain. Supply Chain Management, 15(42), 4-17. [Persian]
[49] Wu, I.L. and Chiu, M.L. (2018). Examining supply chain collaboration with determinants and performance impact: Social capital, justice, and technology use perspectives. International Journal of Information Management, 39, 5–19.
[50] Yadav, D. K. & Barve, A. (2018). Segmenting critical success factors of humanitarian supply chains using fuzzy Dematel. Benchmarking an International Journal, 25(2), 400-425.
[51] Zhang, C., Xue, L. and Dhaliwal, J. (2016). Alignments between the depth and breadth of inter-organizational systems deployment and their impact on firm performance. Information & Management, 53(1), 79–90.
[52] Zhu, Z., Zhao, J. and Bush, A.A. (2020). The effects of e-business processes in supply chain operations: Process component and value creation mechanisms. International Journal of Information Management, 50, 273–285.