A Fuzzy OPARA-Based Group Decision-Making Approach: Application to Sustainable Solutions Assessment
Volume 36, Issue 1 (2025), pp. 33–63
Pub. online: 26 February 2025
Type: Research Article
Open Access
Open Access
Received
1 November 2024
1 November 2024
Accepted
1 February 2025
1 February 2025
Published
26 February 2025
26 February 2025
Abstract
Sustainable practices are essential for long-term societal development, minimizing environmental impacts while promoting the efficient use of resources. Multi-criteria decision-making (MCDM) approaches can play a vital role in assessing and prioritizing sustainability solutions by considering diverse economic, social, and environmental factors. This study proposes a multi-criteria group decision-making approach based on the Objective Pairwise Adjusted Ratio Analysis (OPARA) method in a fuzzy environment and presents its application for the assessment of sustainable agriculture solutions. In the proposed approach, the evaluation criteria weights are determined by combining subjective weights from experts and objective weights obtained from the MEREC (Method Based on the Removal Effects of Criteria) method. The Relative Preference Relation (RPR) approach is employed for ranking fuzzy numbers and final evaluation. Sensitivity analysis and comparison with other methods are conducted to assess the robustness and validity of the proposed approach. The results demonstrate the effectiveness of the proposed approach in evaluating solutions. Based on the final evaluation from the case study, the most important criteria are “Availability and quality of water”, “Focus on immediate economic returns”, and “Financial incentives and access to credit”, while the most suitable solutions for advancing sustainable agriculture are “Financial and credit support”, “Education and enhancement of farmers’ knowledge”, and “Enhancement of research and development”.
References
Abrams, F., Hendrickx, L., Sweeck, L., Camps, J., Cattrysse, D., Van Orshoven, J. (2023). Accounting for uncertainty and disagreement in multi-criteria decision making using triangular fuzzy numbers and Monte Carlo simulation: a case study about selecting measures for remediation of agricultural land after radioactive contamination. In: Sahoo, L., Senapati, T., Yager, R.R. (Eds.), Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Springer Nature Singapore, Singapore, pp. 125–144.
Anusha, B.N., Babu, K.R., Kumar, B.P., Sree, P.P., Veeraswamy, G., Swarnapriya, C., Rajasekhar, M. (2023). Integrated studies for land suitability analysis towards sustainable agricultural development in semi-arid regions of AP, India. Geosystems and Geoenvironment, 2(2), 100131. https://doi.org/10.1016/j.geogeo.2022.100131.
Aycin, E., Cerci, M., Sonugelen, E. (2024). An evaluation of women’s human development level using multi criteria decision-making methods: a case study of OECD countries. Economic Computation and Economic Cybernetics Studies and Research, 58(4), 109–128. https://doi.org/10.24818/18423264/58.4.24.07.
Barbosa Junior, M., Pinheiro, E., Sokulski, C.C., Ramos Huarachi, D.A., de Francisco, A.C. (2022). How to identify barriers to the adoption of sustainable agriculture? A study based on a multi-criteria model. Sustainability, 14(20), 13277. https://doi.org/10.3390/su142013277.
Bathaei, A., Štreimikienė, D. (2023). A systematic review of agricultural sustainability indicators. Agriculture, 13(2), 241. https://doi.org/10.3390/agriculture13020241.
Bechar, I., Bechar, R., Benyettou, A. (2024). A novel score function for spherical fuzzy sets and its application to assignment problem. Economic Computation & Economic Cybernetics Studies & Research, 58(3), 210–224. https://doi.org/10.24818/18423264/58.3.24.13.
Biswas, T., Majumder, A., Dey, S., Mandal, A., Ray, S., Kapoor, P., Emam, W., Kanthal, S., Ishizaka, A. Matuka, A. (2024). Evaluation of management practices in rice–wheat cropping system using multicriteria decision-making methods in conservation agriculture. Scientific Reports, 14(1), 8600. https://doi.org/10.1038/s41598-024-58022-w.
Bozorgi, A., Roozbahani, A., Hashemy Shahdany, S.M., Abbassi, R. (2024). Developing a risk management framework for agricultural water systems using fuzzy dynamic Bayesian networks and decision-making models. Water Resources Management. https://doi.org/10.1007/s11269-024-03961-2.
Cao, J., Solangi, Y.A. (2023). Analyzing and prioritizing the barriers and solutions of sustainable agriculture for promoting sustainable development goals in China. Sustainability, 15(10), 8317. https://doi.org/10.3390/su15108317.
Damjanović, S., Katanić, P., Zavadskas, E.K., Stević, Ž., Krsmanović, B., Djalić, N. (2024). Novel fuzzy MCDM model for comparison of programming languages. Studies in Informatics and Control, 33(4), 5–14. https://doi.org/10.24846/v33i4y202401.
De Marinis, P., Sali, G. (2020). Participatory analytic hierarchy process for resource allocation in agricultural development projects. Evaluation and Program Planning, 80, 101793. https://doi.org/10.1016/j.evalprogplan.2020.101793.
Ebad Ardestani, M., Sharifi Teshnizi, E., Babakhani, P., Mahdad, M., Golian, M. (2020). An optimal management approach for agricultural water supply in accordance with sustainable development criteria using MCDM (TOPSIS) (case study of Poldasht catchment in West Azerbaijan Province-Iran). Journal of Applied Water Engineering and Research, 8(2), 88–107. https://doi.org/10.1080/23249676.2020.1761896.
Erdoğan, M. (2022). Assessing farmers’ perception to Agriculture 4.0 technologies: a new interval-valued spherical fuzzy sets based approach. International Journal of Intelligent Systems, 37(2), 1751–1801. https://doi.org/10.1002/int.22756.
Godfray, H.C.J., Garnett, T. (2014). Food security and sustainable intensification. Philosophical Transactions of the Royal Society B: Biological Sciences, 369, 20120273. https://doi.org/10.1098/rstb.2012.0273. 1639.
Hayati, D., Ranjbar, Z., Karami, E. (2011). Measuring agricultural sustainability. In: Lichtfouse, E. (Ed.), Biodiversity, Biofuels, Agroforestry and Conservation Agriculture. Sustainable Agriculture Reviews, vol. 5. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9513-8_2.
Hoose, A., Yepes, V., Kripka, M. (2021). Selection of production mix in the agricultural machinery industry considering sustainability in decision making. Sustainability, 13(16), 9110. https://doi.org/10.3390/su13169110.
Ismail, M.M., Ibrahim, M., Sleem, A., Mohamed, M. (2024). Blending uncertainty theory innovative into decision support framework for selecting agricultural machinery suppliers. Optimization in Agriculture, 1, 115–128. https://doi.org/10.61356/j.oia.2024.1276.
Janker, J., Mann, S., Rist, S. (2019). Social sustainability in agriculture–a system-based framework. Journal of Rural Studies, 65, 32–42. https://doi.org/10.1016/j.jrurstud.2018.12.010.
Keshavarz-Ghorabaee, M. (2023a). Sustainable supplier selection and order allocation using an integrated ROG-based type-2 fuzzy decision-making approach. Mathematics, 11(9), 2014. https://doi.org/10.3390/math11092014.
Keshavarz-Ghorabaee, M. (2023b). Using SWARA II for subjective evaluation of transport emissions reduction policies. The Open Transportation Journal, 17(1), 1–13. https://doi.org/10.2174/0126671212271963230922093258.
Keshavarz-Ghorabaee, M. (2025). Supplementary data for “A fuzzy OPARA-based group decision-making approach: application to sustainable solutions assessment”. figshare. https://doi.org/10.6084/m9.figshare.28297904.
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4), 525. https://doi.org/10.3390/sym13040525.
Keshavarz-Ghorabaee, M., Rastegar, A., Amiri, M., Zavadskas, E.K., Antuchevičienė, J. (2024). Multi-criteria personnel evaluation and selection using an objective pairwise adjusted ratio analysis (OPARA). Economic Computation and Economic Cybernetics Studies and Research, 58(2), 23–45. https://doi.org/10.24818/18423264/58.2.24.02.
Keskes, M.A., Zouari, A., Houssin, R., Dhouib, D., Renaud, J. (2024). A new multi-criteria, multi-phase, and multi-decision makers’ approach to the agricultural sustainability problem. Environment Systems and Decisions, 44(2), 433–455. https://doi.org/10.1007/s10669-023-09946-7.
Kumar, A., Pramanik, M., Chaudhary, S., Negi, M.S. (2021). Land evaluation for sustainable development of Himalayan agriculture using RS-GIS in conjunction with analytic hierarchy process and frequency ratio. Journal of the Saudi Society of Agricultural Sciences, 20(1), 1–17. https://doi.org/10.1016/j.jssas.2020.10.001.
Lefranc, G., Cabrera, M.P., Comparan, R.O., López-Juárez, I. (2025). Advanced decision-making strategies and technologies for manufacturing: case studies, and future research directions. International Journal of Computers, Communications and Control, 20(1), 6906. https://doi.org/10.15837/ijccc.2025.1.6906.
Martos, V., Ahmad, A., Cartujo, P., Ordoñez, J. (2021). Ensuring agricultural sustainability through remote sensing in the era of Agriculture 5.0. Applied Sciences, 11(13), 5911. https://doi.org/10.3390/app11135911.
Mokarram, M., Mohammadi-Khoramabadi, A., Zarei, A.R. (2023). Fuzzy AHP-based spatial distribution of fig tree cultivation in Zaprionus indianus infection risk for sustainable agriculture development. Environmental Science and Pollution Research, 30(6), 16510–16524. https://doi.org/10.1007/s11356-022-23326-9.
Montgomery, D.R. (2007). Soil erosion and agricultural sustainability. Proceedings of the National Academy of Sciences, 104(33), 13268–13272. https://doi.org/10.1073/pnas.0611508104.
Nagy, M., De Miranda, J.L., Popescu-Bodorin, N. (2024). Decision making and robust optimization for information systems oriented to emergency events. International Journal of Computers, Communications & Control, 19(6), 6861. https://doi.org/10.15837/ijccc.2024.6.6861.
Namiotko, V., Galnaityte, A., Krisciukaitiene, I., Balezentis, T. (2022). Assessment of agri-environmental situation in selected EU countries: a multi-criteria decision-making approach for sustainable agricultural development. Environmental Science and Pollution Research, 29(17), 25556–25567. https://doi.org/10.1007/s11356-021-17655-4.
Nguyen, P.-H., Tran, T.-H., Nguyen, L.-A.T. (2024). Overcoming barriers: a multi-level spherical fuzzy MCDM approach to digital transformation in Vietnam’s agricultural supply chain. In: Kahraman, C., Cevik Onar, S., Cebi, S., Oztaysi, B., Tolga, A.C., Ucal Sari, I. (Eds.), Intelligent and Fuzzy Systems. INFUS 2024, Lecture Notes in Networks and Systems, Vol. 1090. Springer, Cham. https://doi.org/10.1007/978-3-031-67192-0_45.
Prabhjyot, K., Kaur, S., Dhir, A., Kaur, H., Vashisht, B.B. (2024). Agro-eco-resource zonation (AERZ) for sustainable agriculture using GIS and AHP techniques in Indian Punjab. Theoretical and Applied Climatology, 155(8), 8047–8066. https://doi.org/10.1007/s00704-024-05104-4.
Pretty, J. (2008). Agricultural sustainability: concepts, principles and evidence. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1491), 447–465. https://doi.org/10.1098/rstb.2007.2163.
Pretty, J., Benton, T.G., Bharucha, Z.P., Dicks, L.V., Flora, C.B., Godfray, H.C.J., Goulson, D., Hartley, S., Lampkin, N., Morris, C., Pierzynski, G., Vara Prasad, P.V., Reganold, J., Rockström, J., Smith, P., Thorne, P., Wratten, S. Morris, C. (2018). Global assessment of agricultural system redesign for sustainable intensification. Nature Sustainability, 1(8), 441–446. https://doi.org/10.1038/s41893-018-0114-0.
Puška, A., Božanić, D., Nedeljković, M., Janošević, M. (2022). Green supplier selection in an uncertain environment in agriculture using a hybrid MCDM model: Z-numbers–fuzzy LMAW–fuzzy CRADIS model. Axioms, 11(9), 427. https://doi.org/10.3390/axioms11090427.
Puška, A., Nedeljković, M., Dudić, B., Štilić, A., Mittelman, A. (2024). Improving agricultural sustainability in Bosnia and Herzegovina through renewable energy integration. Economies, 12(8), 195. https://doi.org/10.3390/economies12080195.
Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., Pamučar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13(5), 774. https://doi.org/10.3390/sym13050774.
Radmehr, A., Bozorg-Haddad, O., Loáiciga, H.A. ((2022).l). Developing strategies for agricultural water management of large irrigation and drainage networks with fuzzy MCDM. Water Resources Management, 36(13), 4885–4912. https://doi.org/10.1007/s11269-022-03192-3.
Rani, P., Mishra, A.R., Saha, A., Pamucar, D. (2021). Pythagorean fuzzy weighted discrimination-based approximation approach to the assessment of sustainable bioenergy technologies for agricultural residues. International Journal of Intelligent Systems, 36(6), 2964–2990. https://doi.org/10.1002/int.22408.
Rockström, J., Williams, J., Daily, G., Noble, A., Matthews, N., Gordon, L., Wetterstrand, H., DeClerck, F., Shah, M., Steduto, P., de Fraiture, C., Hatibu, N., Unver, O., Bird, J., Sibanda, L., Smith, J. (2017). Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio, 46, 4–17. https://doi.org/10.1007/s13280-016-0793-6.
Rouyendegh, B.D., Savalan, Ş. (2022). An integrated fuzzy MCDM hybrid methodology to analyze agricultural production. Sustainability, 14(8), 4835. https://doi.org/10.3390/su14084835.
Roy, S., Hazra, S., Chanda, A., Das, S. (2022). Land suitability analysis using AHP-based multi-criteria decision model for sustainable agriculture in red and lateritic zones of West Bengal, India. Journal of Earth System Science, 131(4), 201. https://doi.org/10.1007/s12040-022-01941-x.
Singh, V., Dube, M., Nagasampige, M., Trivedi, R. (2024). TOPSIS-based factor analytic model for the assessment of agricultural development in the state of Uttar Pradesh, India. OPSEARCH. https://doi.org/10.1007/s12597-024-00778-w.
Tao, Y., Muneeb, F.M., Wanke, P.F., Tan, Y., Yazdi, A.K. (2024). Revisiting the critical success factors of entrepreneurship to promote Chinese agriculture systems: a multi-criteria decision-making approach. Socio-Economic Planning Sciences, 94, 101951. https://doi.org/10.1016/j.seps.2024.101951.
Thompson, P.B. (2007). Agricultural sustainability: what it is and what it is not. International Journal of Agricultural Sustainability, 5(1), 5–16. https://doi.org/10.1080/14735903.2007.9684809.
Tork, H., Javadi, S., Hashemy Shahdany, S.M. (2021). A new framework of a multi-criteria decision making for agriculture water distribution system. Journal of Cleaner Production, 306, 127178. https://doi.org/10.1016/j.jclepro.2021.127178.
Tran, T.-H., Nguyen, P.-H., Nguyen, L.-A.T. (2024). Strategic insights into post-harvest losses: a spherical fuzzy Delphi-DEMATEL investigation of the Vietnamese agricultural supply chain. In: Kahraman, C., Cevik Onar, S., Cebi, S., Oztaysi, B., Tolga, A.C., Ucal Sari, I. (Eds.), Intelligent and Fuzzy Systems, INFUS 2024, Lecture Notes in Networks and Systems, Vol. 1090. Springer, Cham. https://doi.org/10.1007/978-3-031-67192-0_42.
Tuan, N.H., Canh, T.T. (2023). Proposing solutions to develop sustainable agriculture to adapt to climate change using the T-FANP model. International Journal of the Analytic Hierarchy Process, 15(3), 1–32. https://doi.org/10.13033/ijahp.v15i3.1028.
Wang, Y.-J. (2015). Ranking triangle and trapezoidal fuzzy numbers based on the relative preference relation. Applied Mathematical Modelling, 39(2), 586–599. https://doi.org/10.1016/j.apm.2014.06.011.
Wang, Y.-J., Lee, H.-S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers & Mathematics with Applications, 53(11), 1762–1772. https://doi.org/10.1016/j.camwa.2006.08.037.
Wang, Y.-M., Yang, J.-B., Xu, D.-L., Chin, K.-S. (2006). On the centroids of fuzzy numbers. Fuzzy Sets and Systems, 157(7), 919–926. https://doi.org/10.1016/j.fss.2005.11.006.
Yang, Z., Solangi, Y.A. (2024). Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China. Journal of Cleaner Production, 450, 141862. https://doi.org/10.1016/j.jclepro.2024.141862.
Yazdani, M., Gonzalez, E.D.R.S., Chatterjee, P. (2021). A multi-criteria decision-making framework for agriculture supply chain risk management under a circular economy context. Management Decision, 59(8), 1801–1826. https://doi.org/10.1108/MD-10-2018-1088.
Zamani, R., Ali, A.M.A., Roozbahani, A. (2020). Evaluation of adaptation scenarios for climate change impacts on agricultural water allocation using fuzzy MCDM methods. Water Resources Management, 34(3), 1093–1110. https://doi.org/10.1007/s11269-020-02486-8.
Zhai, T., Wang, D., Zhang, Q., Saeidi, P., Raj Mishra, A. (2023). Assessment of the agriculture supply chain risks for investments of agricultural small and medium-sized enterprises (SMEs) using the decision support model. Economic Research-Ekonomska Istraživanja, 36(2), 2126991. https://doi.org/10.1080/1331677X.2022.2126991.
Zhen, L., Routray, J.K. (2003). Operational indicators for measuring agricultural sustainability in developing countries. Environmental Management, 32, 34–46. https://doi.org/10.1007/s00267-003-2881-1.
Zimmermann, H.J. (2010). Fuzzy set theory Wiley Interdisciplinary Reviews: Computational Statistics, 2(3), 317–332. https://doi.org/10.1002/wics.82.
Zkik, K., Belhadi, A., Rehman Khan, S.A., Kamble, S.S., Oudani, M., Touriki, F.E. (2023). Exploration of barriers and enablers of blockchain adoption for sustainable performance: implications for e-enabled agriculture supply chains. International Journal of Logistics Research and Applications, 26(11), 1498–1535. https://doi.org/10.1080/13675567.2022.2088707.
Biographies
Keshavarz-Ghorabaee Mehdi
M. Keshavarz-Ghorabaee is an assistant professor in the Department of Management at Gonbad Kavous University, Gonbad Kavous, Iran. He earned his BS in electrical engineering from the University of Guilan in 2010, followed by an MS in production management and a PhD in operations research from Allameh Tabataba’i University in 2013 and 2017, respectively. He has published numerous papers in leading international journals, contributing significantly to his field. His research interests encompass multi-criteria decision making (MCDM), fuzzy MCDM, multi-objective programming, inventory control, supply chain management, sustainability, and reliability engineering.
Mohammadi-Ostadkalayeh Amin
A. Mohammadi-Ostadkalayeh is an assistant professor in the Department of Range and Watershed Management at Gonbad Kavous University, Iran. He received his BS and MSc degrees in Range and Watershed Management from Gorgan University of Agricultural Sciences and Natural Resources in 1999 and 2003, respectively. In 2013, he completed his PhD in geography and rural planning at Tehran University. He has authored numerous research articles published in reputable scientific journals. His primary research interests include rural development, sustainability, the socio-economic impacts of development projects, and post-disaster resettlement strategies.
Amiri Maghsoud
M. Amiri is a professor in the Department of Industrial Management at Allameh Tabataba’i University in Tehran, Iran. He received his PhD in industrial engineering from Sharif University of Technology in Tehran. He has published numerous papers in prestigious academic journals. His research interests include multi-criteria decision-making (MCDM), data envelopment analysis (DEA), design of experiments (DOE), response surface methodology (RSM), fuzzy MCDM, inventory control, supply chain management, simulation, and reliability engineering.
Antucheviciene Jurgita
J. Antucheviciene is a professor in the Department of Construction Management and Real Estate at Vilnius Gediminas Technical University, Lithuania. She received her PhD in civil engineering from Vilnius Gediminas Technical University in 2005. She is a member of IEEE SMC Technical Committee on Grey Systems, and of two EURO Working Groups: Multicriteria Decision Aiding (EWG-MCDA) and Operations Research in Sustainable Development and Civil Engineering (EWG-ORSDCE). She is associate editor of Applied Soft Computing, editorial board member of Engineering Applications of Artificial Intelligence, and others. Her main research interests include multi-criteria decision making (MCDM), civil engineering and management, and sustainable development.
