Document Type : Original Article

Authors

1 Master of Entrepreneurship Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Business Administration, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

Abstract

The purpose of this article is to analyze the robustness strategies for businesses that intend to have a successful performance in the future of Iran's smart agriculture sector. For this purpose, using an integrated foresight method based on scenario development, alternative futures for Iran's agriculture were extracted for a ten-year period (2032). The methods of Global Business Network (GBN), Cross Impact Analysis (CIA) and MICMAC were used. Four main drivers were identified, which are cooperation and participation through Strong national and local institutions, versus lobby and pressure groups, as well as the development of technological infrastructure and innovation growth versus the immaturity of the innovation ecosystem. With the meaningful combination of drivers, three possible and meaningful paths to the future of Iran's agriculture were extracted according to the opinion of experts: smart agriculture, state agriculture and traditional agriculture. For the developed scenarios, a set of strategies were analyzed by in-depth interviews with experts as well as a library search that can guarantee strategic robustness in any scenario in the next 10 years. The main result at the macro level is that cooperation and partnership play a major role in shaping the future of Iran's agriculture, as well as strategic robustness, due to their key role in integrating resources and capabilities. Finally, by applying robustness criteria, the robustness strategies were ranked. Strategic collaborations and the development of practical innovations were the most robustness strategies, and independent investment and the development of advanced innovations were recognized as the weakest strategies.

Keywords

[1]    FAO. Climate-smart agriculture-sourcebook. 2013.
[2]    FAO. Climate-smart agriculture case studies 2021 – Projects from around the world. Rome. 2021.
[3]    WORLD BANK. Climate-smart agriculture (CSA) is an integrated approach to managing landscapes—cropland, livestock, forests and fisheries--that address the interlinked challenges of food security and climate change. 2021.
[4]    Schwenker, Burkhard. Wulf, Torsten. Scenario based strategic planning, Springer Fachmedien Wiesbaden, 2013.
[5]    Daim, T.U., Yoon, B.-S., Lindenberg, J., Grizzi, R., Estep, J. and Oliver, T., “Strategic roadmapping of robotics technologies for the power industry: a multicriteria technology assessment”, Technological Forecasting and Social Change, 2018, Vol. 131, pp. 49-66.
[6]    Vilkkumaa, E., Liesio¨, J., Salo, A. and Ilmola-Sheppard, L., “Scenario-based portfolio model for building robust and proactive strategies”, European Journal of Operational Research, 2018, Vol. 266 No. 1, pp. 205-220.
[7]    7-Chermack, T.J., Foundations of Scenario Planning: The Story of Pierre Wack, Routledge, Abingdon, 2017.
[8]    Thomas, C. and Chermack, T., Using Scenario Planning to Supplement Supply Chain Risk Assessments, Revisiting Supply Chain Risk, Springer, Berlin, 2019, pp. 37-51.
[9]    Alizadeh, Reza. Soltanisehat, L., Stay competitive in 2035: a scenario-based method to foresight in the design and manufacturing industry. Emerald Publishing Limited. 2019, VOL. 22 NO. 3 2020, pp. 309-330.
[10]    Mihailova, M. The state of agriculture in Bulgaria – PESTLE analysis. Bulgarian Journal of Agricultural Science, 2020, 26 (No 5) 2020, 935–943.
[11]    Gorli, R. Future of Smart Farming with Internet of Things. Journal of Information Technology and Its Applications Volume 2 Issue 1, 2017.
[12]    Saiz-Rubio, V., Rovira-Más, F. From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management. 2020, Agronomy 2020, 10, 207.
[13]    Despoudi, Stella. Spanaki, Konstantina. Rodriguez-Espindola, Oscar. D. Zamani, Efpraxia. Agricultural Supply Chains and Industry 4.0. Springer Nature Switzerland, 2021.
[14]    Balafoutis, Athanasios T. Van Evert, Frits K. Fountas, Spyros. Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness. 2020, Agronomy 2020, 10, 743.
[15]    Baskaran-Makanju, Shruthi. The Digital Agriculture Revolution Will Take More than Innovation. BCG. 2021.
[16]    Matos, F. and Jacinto, C., “Additive manufacturing technology: mapping social impacts”, Journal of Manufacturing Technology Management, 2019, Vol. 30 No. 1, pp. 70-97.
[17]    Varum, C.A. and Melo, C. “Directions in scenario planning literature–a review of the past decades”, Futures, 2010, Vol. 42 No. 4, pp. 355-369.
[18]    Mack, O. Khare, A. Krämer, A. Burgartz, Thomas. Editors. Managing in a VUCA World. Springer International Publishing Switzerland, 2016.
[19]    Kok, Jacobus. Van den Heuvel, Steven C. Editors. Leading in a VUCA World. Springer Open eBook, 2019.
[20]    Martelli, Antonio. Models of Scenario Building and Planning, Palgrave Macmillan on Applied computer and applied computational science. 2014, pp. 215-220.
[21]    Grupp, H. and Linstone, H.A. “National technology foresight activities around the globe: resurrection and new paradigms”, Technological Forecasting and Social Change, 1999, Vol. 60 No. 1, pp. 85-94.
[22]    BusinessLine, Technological disruption of India’s agriculture ecosystem, Oct 05, 2021.
[23]    Khodadad H, Hamid. Azizi, H. “Strategic Planning and Management.” 4TH Edition, Tehran, Saffar Publishing, 2017.
[24]    Azar, Adel. Khosravani, F. Jalali, R. “Soft Operational Research.” 1TH Edition, Tehran. Industrial Management Organization Publishing. 2013.
[25]    Rahsepar, Z. Salehi, K, Ezati, M, Zolfagharzadeh, M. “"Identification and structural analysis of the mutual influence of drivers of change in the field of education".Educational Innovation Quarterly, Year 18, 2018, No. 70, pp. 101-126.