ارائه مدل مدیریت توسعه فناوری‌های نوظهور مبتنی بر پایدارسازی زنجیره‌های تامین در صنعت کشاورزی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران

2 استادیار گروه مدیریت صنعتی. واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.(نویسنده مسئول)

چکیده

پژوهش حاضر با هدف ارائه مدل مدیریت توسعه فناوری‌های نوظهور مبتنی بر پایدارسازی زنجیره‌های تامین در صنعت کشاورزی است، نوع تحقیق به لحاظ هدف، کاربردی و از نظر پارادایمی، ترکیبی_اکتشافی می‌باشد. در گام اول، عوامل مؤثر از طریق مرور نظام‌مند پیشینه تحقیق استخراج و از طریق مصاحبه نیمه‌ساختاریافته با 15 نفر از خبرگان دانشگاهی و مدیران جهاد کشاورزی به روش دلفی، تأیید شدند. خروجی این مرحله 184 مؤلفه و 34 مقوله فرعی بود که در شش بُعد براساس روش کیفی نظریۀ برخاسته از داده‏ها دسته‌بندی شدند. در گام دوم، ابعاد با روش معادلات ساختاری با نرم افزار Amos برازش و مدل مورد تأیید قرار گرفت و معلوم گردید که انتخاب مفاهیم، مولفه‌ها و شاخص‌ها از دقت بالایی برخوردار بوده و نتایج بخش کمی یافته‌های بخش کیفی را تأیید می‌کند. شرایط مداخله‌گر، شرایط زمینه‌ای و پدیده محوری به صورت غیرمستقیم با پیامدها و شرایط علی به طور غیر مستقیم با پیامدها ارتباط مثبت و معنی‌دار دارد. همچنین شرایط علی به صورت غیرمستقیم بر راهبردهای مدل مدیریت توسعه فناوری‌های نوظهور مبتنی بر پایدارسازی زنجیره‌های تامین تاثیر مثبت دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Presenting a management model for the development of emerging technologies based on the stabilization of supply chains in the agricultural industry

نویسندگان [English]

  • Seyed Amirali didegah 1
  • Tahmoores Sohrabi 2
1 PhD Student Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.
2 Assistant Professor of Industrial Management Department. Central Tehran Branch, Islamic Azad University, Tehran, Iran. (Corresponding author)
چکیده [English]

The purpose of this research is to provide a management model for the development of emerging technologies based on the stabilization of supply chains in the agricultural industry. The type of research is applied in terms of purpose and exploratory-mixed in terms of paradigm. In the first step, the effective factors were extracted through a systematic review of the research background and confirmed through a semi-structured interview with 15 university experts and managers of the agricultural jihad using the Delphi method. The output of this stage was 184 components and 34 subcategories, which were categorized into six dimensions based on the qualitative method of the theory arising from the data. In the second step, the dimensions were verified by the structural equation method with Amos software, and it was found that the selection of concepts, the results of the quantitative part confirmed the findings of the qualitative part. Intervening conditions, background conditions and central phenomenon indirectly have a positive and significant relationship with the consequences and causal conditions indirectly with the consequences. Also, the causal conditions indirectly have a positive effect on the management model strategies for the development of emerging technologies based on the stabilization of supply chains.

کلیدواژه‌ها [English]

  • Development management
  • emerging technologies
  • agriculture
  • supply chain
Akkaş, M.A. & Sokullu, R. (2017). An IoT-based greenhouse monitoring system with Micaz motes. Procedia Computer Science, 113, 603–608. https://doi.org/10.1016/j.procs.2017.08.300.
Behrooznia, A.H.G., & Hashezadeh khoorasgani, G.H., & Radfar, R. (2021). Explain the development of technology in the field of pharmaceutical industry and its role in sustainable social and economic development. Journal of Iranian Social Development Studies, 13(52), 277-290. [In Persian] htpp://doi.org/10.30495/jisds.2022.56207.11359.
Dehghani, B. (2020). Emerging technologies in agriculture and food with a supply chain approach. Tehran, Iarn: tarbiate modir publication.
Didegah, S.A., & Tahmurt, S. (2022). Identifying and leveling the factors affecting the development of emerging technologies in agriculture with a supply chain approach. Journal of Industry and University, 51(4), 187-207. [In Persian] htpp://doi.org/20.1001.1.27170446.1400.14.51.3.0.
Dong, Y., Hou, J., Zhang, N., & Zhang, M. (2020). Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence. CComplexity, 1, 1-10. https://doi.org/10.1155/2020/1680845.
Dorri, A., Kanhere, S.S., Jurdak, R., & Gauravaram, P. A. (2019). Lightweight Scalable Blockchain for IoT security and anonymity. Journal of Parallel and Distributed Computing, 134, 180–19. https://doi.org/10.1016/j.jpdc.2019.08.005.
FAO. (2017). The future of food and agriculture–Trends and challenges. Annual Report. Retrieved from https://reliefweb.int/report/world/future-food-and-agriculture-trends-and-challenges?gad_source=1&gclid=CjwKCAjwqf20BhBwEiwAt7dtdcnwtIf3frBjzR2qBnM4uPqge0gBtqekrwdzddSq77CGPWogXI8BDxoCBs0QAvD_BwE
Francisco, G.E., ́Htuna, N.N., Schlenzb, F., Kasimatic, A., & Verberta, K. (2019). A Review of Visualisations in Agricultural Decision Support Systems: an HCI Perspective. Computers and electronics in agriculture, 163, 104844. https://doi.org/10.1016/j.compag.2019.05.053.
Ghisellini, P., Cialani, C., & Ulgiati, S. (2016). A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner Production, 114, 11–32. htpp://doi.org/10.1016/j.jclepro.2015.09.007
Gholamnejad, M., Movahedi, M., Manteghi, M., & AliYari, S. (2022). Presenting a Model for Measuring the Success of Technology Transfer in Iran's Petrochemical Industry. Journal of Technology Development Management, 9(4), 75-99. [In Persian] htpp://doi.org/10.22104/jtdm.2022.4880.2788
Gilchrist, A. (2018). The supply chain in the industrial revolution, from warehouse shelves to expansion in the world. Translated by Ahmad Jafaranjad, Ramin Najizadeh, Reza Karimi. Tehran, Iran: Industrial Management Organization publication. [In Persian]
Hassan, S. I., Alam, M. M., Illahi, U., Al Ghamdi, M. A., Almotiri, S. H., & Su’ud, M. M. (2021). A Systematic Review on Monitoring and Advanced Control Strategies in Smart Agriculture. IEEE Access, 9, 32517–32548. htpp://doi.org/10.1109/ACCESS.2021.3057865.
Hatami, P., & Hosseini, A. (2018). The role of Internet of Things in promoting the agricultural industry in the field of smart irrigation (and analysis of its results in Iran). Master's thesis. Qazvin, Iran: Ghiyasuddin Jamshid Kashani University. [In Persian]
Mohammadian, A., Heidary Dahooie, J., & Ghorbani, A. (2020). Prioritizing the Applications of Internet of Things in the Agriculture by Using Sustainable Development Indicators. Iranian journal of agricultural economics and development research, 51(4), 745-759. [In Persian] htpp://doi.org/10.22059/IJAEDR.2020.282000.668759.
Jamshidi, B., & Dehghani Sanij, H. (2019). Big data based on Internet of Things from the perspective of smart agriculture. Technological growth, 16(63), 12-22. [In Persian] htpp://doi.org/10.52547/jstpi.20875.16.63.12
Kagermann, H. (2015). Change through digitization—value creation in the age of Industry 4.0. Management of Permanent Change, 23–45. htpp://doi.org/10.1007/978-3-658-05014-6_2.
Kasinathan, T. Singaraju, D., & Srinivasulu-Reddy, U. (2020). Insect classification and detection in field crops using modern machine learning. Information Processing in Agriculture, 8(3), 446-457. https://doi.org/10.1016/j.inpa.2020.09.006.
Korhonen, J., Nuur, C., Feldmann, A., & Birkie, S.E. (2018). Circular economy as an Essen tially contested concept. Journal of Cleaner Production, 175, 544–552. htpp://doi.org/10.1016/j.jclepro.2017.12.111.
Lasi, H., Fettke, P., Kemper, H.G., Feld, T. and Hoffmann, M. (2014) Industry 4.0. Business & Information Systems Engineering, 6, 239-242. https://doi.org/10.1007/s12599-014-0334-4.
Makate, C. (2019). Effective scaling of climate smart agriculture innovations in African smallholder agriculture: A review of approaches, policy and institutional strategy needs. Environmental Science & Policy, 96, 37–51. htpp://doi.org/10.1016/j.envsci.2019.01.014.
Mars, M.M., & Ball, A.L. (2016). Ways of Knowing, Sharing, and Translating Agricultural Knowledge and Perspectives: Alternative Epistemologies across Non-formal and Informal Settings Journal of Agricultural Education, 57(1), 56-72. htpp://doi.org/10.5032/jae.2016.010 .
Martinez-Mosquera, D., Navarrete, R., & Lujan-Mora, S. (2020). Modeling and Management Big Data in Databases—A Systematic Literature Review. Sustainability, 12(2), 634. htpp://doi.org/10.3390/su12020634.
Jha, N., Prashar, D., Khalaf, O.I., Alotaibi, Y., Alsufyani, A., & Alghamdi, S. (2021). Blockchain Based Crop Insurance: A Decentralized Insurance System for Modernization of Indian Farmers. Sustainability, 13, 8921. https://doi.org/10.3390/su13168921.
Park, A., & Li, H. (2021). The effect of blockchain technology on supply chain sustainability performances. Sustainability, 13(4), 1726. htpp://doi.org/10.3390/su13041726.
Reddy Maddikunta, P. K., Hakak, S., Alazab, M., Bhattacharya, S., Gadekallu, T. R., Khan, W. Z., & Pham, Q.-V. (2021). Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements, and Challenges. IEEE Sensors Journal, 21(16), 17608–17619. htpp://doi.org/10.1109/JSEN.2021.3049471.
Said Mohamed, E., Belal, A., Kotb Abd-Elmabod, S., El-Shirbeny, M. A., Gad, A., & Zahran, M. B. (2021). Smart farming for improving agricultural management. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 971-981. htpp://doi.org/10.1016/j.ejrs.2021.08.007.
Schmidt, C. G., & Wagner, S. M. (2019). Blockchain and supply chain relations: A transaction cost theory perspective. Journal of Purchasing and Supply Management, 25(4), 100552. htpp://doi.org/10.1016/j.pursup.2019.100552.
Shoaib-Farooq, M., Riaz, S., Abid, A., Abid, K., & AzharNaeem, M. (2019). A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming. IEEE Access, 7, 1-10. htpp://doi.org/10.1109/ACCESS.2019.2949703.
Stindt, D. (2017). A generic planning approach for sustainable supply chain management-How to integrate concepts and methods to address the issues of sustainability?. Journal of cleaner production, 153, 146-163. htpp://doi.org/10.1016/j.jclepro.2017.03.126.
Su, Y., & Wang, X. (2021). Innovation of agricultural economic management in the process of constructing smart agriculture by big data. Sustainable Computing: Informatics and Systems, 31, 100579. htpp://doi.org/10.1016/j.suscom.2021.100579.
Tao, W., Zhao, L., Wang, G., & Liang, R. (2021). Review of the internet of things communication technologies in smart agriculture and challenges. Computers and Electronics in Agriculture, 189, 106352. htpp://doi.org/10.1016/j.compag.2021.106352.
Totin, E., Segnon, A., Schut, M., Affognon, H., Zougmoré, R., Rosenstock, T., & Thornton, P. (2018). Institutional Perspectives of Climate-Smart Agriculture: A Systematic Literature Review. Sustainability, 10(6), 1990. htpp://doi.org/10.3390/su10061990.
Vogel-Heuser, B., Hess, D. (2016). Guest editorial Industry 4.0–prerequisites and visions. IEEE Trans. Autom. Automation Science and Engineering. 13(2), 411–413. htpp://doi.org/10.1109/TASE.2016.2523639.
Walsh, D., Ting-Fung, M., Hon, I., & Zhu, J. (2019). Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses. Transboundary and Emerging Diseases, 66(6), 2537-2545. htpp://doi.org/10.1111/tbed.13318.
Wang, J., Bell, M., Liu, X., & Liu, G. (2020). Machine-Learning Techniques Can Enhance DairyCow Estrus Detection Using Location andAcceleration Data. Animals, 10(7), 1160. htpp://doi.org/10.3390/ani10071160.
Yadav, V. S., Singh, A. R., Raut, R. D., Mangla, S. K., Luthra, S., & Kumar, A. (2022). Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: a systematic literature review. Computers & Industrial Engineering, 169, 108304. htpp://doi.org/10.1016/j.cie.2022.108304.
Zhang, L., Ibiba, K., & Brown, W.L. (2018). Internet of Things applications for agriculture" in Internet of Things A to Z: Technologies and Applications. First Edition. Edited by Qusay F. Hassan. By The Institute of Electrical and Electronics Engineers, Inc. Published 2018 by John Wiley & Sons, Inc. htpp://doi.org/10.1002/9781119456735.
Zhai, Z., Martínez, J.F., Beltran, V., Lucas, N., & Martínez, N.L. (2020). Decision support systems for agriculture 4.0: Survey and challenges. Computers and Electronics in Agriculture, 170, 105256. htpp://doi.org/10.1016/j.compag.2020.105256.
Zhu, Y., Wu, D., & Li, S. (2013). Cloud computing and agricultural development of china: theory and practice. Agricultural and Food Sciences, Computer Science.  10(1) 7-12. htpp://doi.org/10.26438/ijcse/v8i1.159165.