Decision-making criteria under uncertainty and risk in the agricultural sector

Authors

DOI:

https://doi.org/10.51599/is.2023.07.04.06

Keywords:

agricultural sector, decision making criteria, uncertainty, risk, payoff matrix, risk management.

Abstract

Purpose. The objective of this research is to find out and analyze the standards that farmers, policymakers, and other significant stakeholders in the agriculture sector use to make decisions under conditions of risk and uncertainty. Our objective is to contribute to the body of knowledge in agricultural economics by critically examining these standards and offering comprehensive analysis that can contribute to more adaptable and resilient decision-making.

Results. The importance of decision-making in light of risk and uncertainty was clearly emphasized to predict and illustrate the understanding of the variables that affect decision-making in the agricultural industry. Important patterns, trends and variables that have a significant impact on decision outcomes were detected by combining quantitative analysis with qualitative assessments. With several alternatives, internal and external conditions and many possibilities, criteria that help make the right decision, maximize return or minimize the cost of risk and uncertainty were highlighted for stakeholders seeking to improve decision-making processes and adaptability to changing obstacles, while trying to abandon the scientific basis in modeling the reality of the agricultural sector.

Scientific novelty. This study advances the subject by providing a wide and relatively new perspective on the criteria that used in agricultural decision-making in the face of uncertainty and risk. Although decision-making in agricultural situations has been studied in the literature before, our study is distinguished by its focus on the criteria that are used when there is uncertainty and risk. We hope to shed light on new ideas that can improve agricultural economics theory and methods by exploring this area.

Practical value. The study has a wide range of practical applications. A more detailed understanding of the decision-making factors found in this study will be useful for farmers, legislators, and agribusiness experts. Given an ever-changing environment, simulate realistic obstacles and identify available alternatives under various conditions, the ultimate practical value of more resilient and sustainable agricultural practices is enhanced through risk management measures, resource allocation and policy formulation.

References

Ahmed, F. (2022). Economic impacts of risk and uncertainty on food security and crop composition in Egyptian agriculture during the period (2019–2022). Studies, 23(3). https://doi.org/10.21608/JPSA.2022.249962.

Akhtar, S., Li, Gu-C., Nazir, A., Razzaq, A., Ullah, R., Faisal, M., … & Haseeb, R. M. (2019). Maize production under risk: the simultaneous adoption of off-farm. Journal of Integrative Agriculture, 18(2), 460–470. https://doi.org/10.1016/S2095-3119(18)61968-9.

Alp, Ç., & Aktürk, D. (2016). Perceptions of risk and uncertainty in agricultural production. Journal of Agriculltural faculty of Uludag University, 30, 45–54. Available at: https://www.cabidigitallibrary.org/doi/pdf/10.5555/20173246042.

AscoughII, J. C., Hoag, D. L., & Engler-Palma, A. (2002). Evaluating agricultural systems for environmental sustainability using an impact matrix approach. 1st International Congress on Environmental Modeling and Software (pp. 514–519). Lugano Switzerland: Brigham Young University; BYU Scholars Archive. Available at: https://scholarsarchive.byu.edu/iemssconference/2002/all/109.

Babaker, M. (2007). Schedule of Benefits. Available at: https://www.arab-api.org/Files/Training/programs/1/2018/38_C16-5.pdf.

Backus, G., Eidman, V., & Dijkhuizen, A. (1997). Farm decision making under risk and uncertainty. Netherlands Journal of Agricultural Sciences, 45, 307–328. https://doi.org/10.18174/njas.v45i2.520.

Bressy, G., & Konkuyt, C. (2018). Management et économie des entreprises, 12e éd. Paris. Available at: https://www.eyrolles.com/Entreprise/Livre/management-et-economie-des-entreprises-9782247179121.

Capitanio, F. (2022). Risk, uncertainty, crises management and public intervention in agriculture. Italian Review of Agricultural Economics, 77(2), 3–14. https://doi.org/10.36253/rea-13774.

Fagundesa, M., Teles, E., De Melo, S., & Freires, F. (2020). Decision-making models and support systems for supply chain risk: literature mapping and future research agenda. European Research on Management and Business Economics, 26(2), 63–70. https://doi.org/10.1016/j.iedeen.2020.02.001.

Gilles, B., & Konkuyt, C. (2011). Management et économie des entreprises. Paris: Edition Sirey. Available at: https://www.eyrolles.com/Entreprise/Livre/management-et-economie-des-entreprises-9782247179121.

Gomez, J., Montero, A. S., Guzmán, G., & Soriano, M.-A. (2021). In-depth analysis of soil management and farmers’ perceptions of related risks in two olive grove areas in southern Spain. International Soil and Water Conservation Research, 9(3), 461–473. https://doi.org/10.1016/j.iswcr.2021.01.003.

Aimin, H. (2010). Uncertainty, Risk Aversion and Risk Management in Agriculture. Agriculture and Agricultural Science Procedia, 1, 152–156. https://doi.org/10.1016/j.aaspro.2010.09.018.

Mao, H., Quan, Yu-r., & Fu, Y. (2023). Risk preferences and the low-carbon agricultural technology adoption: evidence from rice production in China. Journal of Integrative Agriculture, 22(8), 2577–2590. https://doi.org/10.1016/j.jia.2023.07.002.

Kahan, D. (2013). Farm management extension guide. Rome: FAO. Available at: https://www.fao.org/3/i0411e/i0411e.pdf.

Kast, R. (2002). La theorie de la decision. Paris: La decouverte et Syros. https://doi.org/10.3917/dec.kast.2002.01.

Kuzman, B., Prodanovic, R., & Subić, J. (2017). Risks and uncertainty management in agriculture holding. In Risk in the food economy – theory and practice (pp. 133–147). Institute of Agricultural and Food Economics – National Research Institute, Warsaw. Available at: http://repository.iep.bg.ac.rs/250.

Larson, J. A. (2008). Risk and uncertainty at the farm level. Farm Foundation Conference Transition to a Bioeconomy: Risk, Infrastructure and Industry Evolution Conference Sponsored by the Farm Foundation, June 24–25, 2008 (pp. 40–60). Available at: https://www.farmfoundation.org/wp-content/uploads/attachments/365-J.A.%20Larson.pdf.

Metzger, O., & Spengler, T. (2019). Modeling rational decisions in ambiguous situations: a multi-valued logic approach. Business Research, 12, 271–290. https://doi.org/10.1007/s40685-019-0087-5.

Nelson, A. G. (1987). How farm managers make risky decisions. In E. N. Castle, M. H. Becker, & A. G. Nelson (Eds.), Farm business management: the decision making process (pp. 35–39). New York, Macmillan.

Pazek, K., & Rozman, Č. (2009). Decision making under conditions of uncertainty in agriculture: a case study of oil crops. Poljoprivreda Osijek, 15(1). Available at: https://hrcak.srce.hr/file/61873.

Rasoulzadeh, M., Edalatpanah, S. A., Fallah, M., & Najafi, S. E. (2022). A multi-objective approach based on Markowitz and DEA cross-efficiency models for the intuitionistic fuzzy portfolio selection problem. Decision Making: Applications in Management and Engineering, 5(2), 241–259. https://doi.org/10.31181/dmame0324062022e.

Ray, P. (2021). Agricultural supply chain risk management under price and demand uncertainty. International Journal of System Dynamics Applications, 10(2), 17–32. http://doi.org/10.4018/IJSDA.2021040102.

Raybould, A. (2010). Reducing uncertainty in regulatory decision-making for transgenic crops: more ecological research or clearer environmental risk assessment? GM Crops, 1(1), 25–31. https://doi.org/10.4161/gmcr.1.1.9776.

Simangusong, E., Hendry, L., & Stevenson, M. (2012). Supply chain uncertainty: a review and theoretical foundation for future. International Journal of Production Research, 50(16), 4493–4523. http://doi.org/10.1080/00207543.2011.613864.

Smyth, S. J., & Phillips, P. W. (2014). Risk, regulation and biotechnology: the case of GM crops. GM Crops & Food, 5(3), 170–177. https://doi.org/10.4161/21645698.2014.945880.

Sraïri, M. T., & Ghabiyel (2017). Coping with the work constraints in crop-livestock farming systems. Annals of Agricultural Sciences, 62(1), 23–32. https://doi.org/10.1016/j.aoas.2017.01.001

Temesgen, T., Kenini, G., Sefera, T., & Jarso, M. (2015). Yield stability and relationships among stability parameters in faba bean (Vicia faba L.) genotypes. The Crop Journal, 3(3), 258–268. https://doi.org/10.1016/j.cj.2015.03.004.

Yusuf, S. A., Abdul-Qader, M., & Lawal, J. O. (2014). Determinants of risk and uncertainty in oil palm nursery. Journal of Economics and Sustainable Development, 5(11), 174–186. Available at: https://www.iiste.org/Journals/index.php/JEDS/article/view/13870/14129.

Zhai, T., Wang, D., Zhang, Q., Saeidi, P., & Mishra, A. R. (2022). Assessment of the agriculture supply chain risks for investments of agricultural small and medium-sized enterprises (SMEs) using the decision support mode. Economic Research – Ekonomska Istraživanj, 36(2), 2126991. https://doi.org/10.1080/1331677X.2022.2126991.

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Published

2023-12-30

How to Cite

Gheddar, R. (2023). Decision-making criteria under uncertainty and risk in the agricultural sector. Journal of Innovations and Sustainability, 7(4), 06. https://doi.org/10.51599/is.2023.07.04.06

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Section

Economic sciences