Abstract
The adoption of organic agriculture in developing countries is a complex decision, as it involves considering various factors. Multicriteria decision analysis (MCDA) methods can be suitable for this type of decision, as evidenced in the literature. The Best–Worst Method (BWM) is an MCDA tool that has proven useful due to its simplicity and computational capability. This research aims to test the applicability of this method to a population with low levels of education and determine whether a questionnaire with a continuous visual aid, a slider, is more suitable than the standard questionnaire with digits. Moreover, it aims to ascertain which factors the consistency of the responses depends on. To achieve this, 217 farmers in Paraguay were surveyed, and the consistency of the results was measured. We found that the questionnaires with digits were more consistent. Then we investigated possible causes of these differences, observing that respondents with sliders tended to concentrate their responses more heavily on the extreme values of the scale (1 and 9). A regression analysis of the consistency values with respect to various socioeconomic variables found only a slight effect of total farm incomes to be significant. These results demonstrate the feasibility of using this sophisticated method in this type of population and suggest that using sliders is not advisable.
This is a preview of subscription content, log in via an institution to check access.
Source: Authors’ own elaboration
Source: Authors’ own elaboration
Source: Authors’ own elaboration
Source: Authors’ own elaboration
Source: Authors’ own elaboration
Source: Authors’ own elaboration
Similar content being viewed by others
Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Ada, E., Sagnak, M., Uzel, R. A., & Balcıoğlu, İ. (2022). Analysis of barriers to circularity for agricultural cooperatives in the digitalization era. International Journal of Productivity and Performance Management, 71(3), 932–951. https://doi.org/10.1108/IJPPM-12-2020-0689
Adebiyi, J. A., & Olabisi, L. S. (2022). Participatory causal loop mapping of the adoption of organic farming in Nigeria. Environmental Management, 69(2), 410–428. https://doi.org/10.1007/s00267-021-01580-w
Adebiyi, J. A., Olabisi, L. S., Richardson, R., Liverpool-Tasie, L. S. O., & Delate, K. (2020). Drivers and constraints to the adoption of organic leafy vegetable production in Nigeria: A livelihood approach. Sustainability (switzerland), 12(1), 1–21. https://doi.org/10.3390/SU12010096
Aghaloo, K., & Chiu, Y. R. (2020). Identifying optimal sites for a rainwater-harvesting agricultural scheme in Iran using the Best-Worst Method and fuzzy logic in a GIS-based decision support system. Water, 12(7), 1913. https://doi.org/10.3390/W12071913
Aghaloo, K., & Sharifi, A. (2023). A GIS-based agroecological model for sustainable agricultural production in arid and semi-arid areas: The case of Kerman Province, Iran. Current Research in Environmental Sustainability, 6, 100230. https://doi.org/10.1016/J.CRSUST.2023.100230
Aghasafari, H., Karbasi, A., Mohammadi, H., & Calisti, R. (2020). Determination of the best strategies for development of organic farming: A SWOT–fuzzy analytic network process approach. Journal of Cleaner Production, 277, 124039. https://doi.org/10.1016/J.JCLEPRO.2020.124039
Akram, M. W., Akram, N., Hongshu, W., Andleeb, S., Ur Rehman, K., & Hassan, F. (2022). Investigating the leading drivers of organic farming: A survival analysis. Ciencia Rural. https://doi.org/10.1590/0103-8478CR20200781
Aliyev, S. T., Mammadova, E. B., Hamidova, L. A., Dunyamaliyeva, V. R., & Hurshudov, S. N. (2022). Prospects and threats for developing organic agriculture: The example of Azerbaijan. Journal of Eastern European and Central Asian Research (JEECAR), 9(6), 1046–1054. https://doi.org/10.15549/JEECAR.V9I6.1204
Ávila Storer, A. (2005). El saber matemático de los analfabetos. Origen y desarrollo de sus estrategias de cálculo. Revista Latinoamericana De Estudios Educativos, 35(3–4), 179–219.
Bacon, C. M., Flores Gomez, M. E., Shin, V., Ballardo, G., Kriese, S., McCurry, E., Martinez, E., & Rivas, M. (2023). Beyond the bean: Analyzing diversified farming, food security, dietary diversity, and gender in Nicaragua’s smallholders coffee cooperatives. Agroecology and Sustainable Food Systems, 47(4), 579–620. https://doi.org/10.1080/21683565.2023.2171172
Bai, W., Yan, L., Zhang, L., & Ye, L. (2023). Practice, pathways, and performance for resource utilization of crop straw: A case study of Xinyang City in China. Environmental Science and Pollution Research, 30(4), 10812–10829. https://doi.org/10.1007/S11356-022-22840-0
Belasco, E., & Schahczenski, J. (2021). Is organic farming risky? An evaluation of WFRP in organic and conventional production systems. Agricultural and Resource Economics Review, 50(1), 63–75. https://doi.org/10.1017/AGE.2020.13
Brainy, J. R. V. J., Suganthi, K. D. N., Narayanamoorthy, S., Ilakiya, U., Innab, N., Alshammari, A., Ahmadian, A., & Jeon, J. (2023). A perspective study for the assessment of field robots in agriculture: An enhanced fuzzy MADM approach. Computers and Electronics in Agriculture, 214, 108296. https://doi.org/10.1016/J.COMPAG.2023.108296
Brañas-Garza, P., Ciacci, R., & Ramírez, E. G. R. (2022). Anchors matter: Eliciting maternal expectations on educational outcomes. Journal of Economic Psychology, 90, 102510. https://doi.org/10.1016/J.JOEP.2022.102510
Bruns, S., Hermann, D., & Mußhoff, O. (2022). Investigating inconsistencies in complex lotteries: The role of cognitive skills of low-numeracy subjects. Journal of Behavioral and Experimental Economics, 97, 101840. https://doi.org/10.1016/J.SOCEC.2022.101840
Burtscher-Schaden, H., Durstberger, T., & Zaller, J. G. (2022). Toxicological comparison of pesticide active substances approved for conventional vs. organic agriculture in Europe. Toxics, 10(12), 753. https://doi.org/10.3390/TOXICS10120753
Carmona-Torres, C., Parra-López, C., Hinojosa-Rodríguez, A., & Sayadi, S. (2014). Farm-level multifunctionality associated with farming techniques in olive growing: An integrated modeling approach. Agricultural Systems, 127, 97–114. https://doi.org/10.1016/J.AGSY.2014.02.001
Chitsaz, N., & Azarnivand, A. (2017). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233–250. https://doi.org/10.1007/S11269-016-1521-5
Colley, A., Mayer, S., & Henze, N. (2019). Investigating the effect of orientation and visual style on touchscreen slider performance. Conference on Human Factors in Computing Systems—Proceedings, 189(1–189), 9. https://doi.org/10.1145/3290605.3300419
Danner, M., Vennedey, V., Hiligsmann, M., Fauser, S., Gross, C., & Stock, S. (2016). How well can analytic hierarchy process be used to elicit individual preferences? Insights from a survey in patients suffering from age-related macular degeneration. Patient, 9(5), 481–492. https://doi.org/10.1007/S40271-016-0179-7
Davies, A., Lockstone-Binney, L., & Holmes, K. (2018). Who are the future volunteers in rural places? Understanding the demographic and background characteristics of non-retired rural volunteers, why they volunteer and their future migration intentions. Journal of Rural Studies, 60, 167–175. https://doi.org/10.1016/J.JRURSTUD.2018.04.003
DeCastellarnau, A. (2018). A classification of response scale characteristics that affect data quality: A literature review. Quality and Quantity, 52(4), 1523–1559. https://doi.org/10.1007/S11135-017-0533-4
Dhumras, H., & Bajaj, R. K. (2023). Modified EDAS method for MCDM in robotic agrifarming with picture fuzzy soft Dombi aggregation operators. Soft Computing, 27(8), 5077–5098. https://doi.org/10.1007/S00500-023-07927-1
Di Bene, C., Gómez-López, M. D., Francaviglia, R., Farina, R., Blasi, E., Martínez-Granados, D., & Calatrava, J. (2022). Barriers and opportunities for sustainable farming practices and crop diversification strategies in mediterranean cereal-based systems. Frontiers in Environmental Science, 10, 1–16. https://doi.org/10.3389/fenvs.2022.861225
Dixit, A., Suvadarshini, P., & Pagare, D. V. (2022). Analysis of barriers to organic farming adoption in developing countries: A grey-DEMATEL and ISM approach. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-06-2022-0111
Effah, D., Bai, C., Asante, W. A., & Quayson, M. (2023). The role of artificial intelligence in coping with extreme weather-induced Cocoa supply chain risks. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2023.3289258
Emeana, E. M., Trenchard, L., Dehnen-Schmutz, K., & Shaikh, S. (2019). Evaluating the role of public agricultural extension and advisory services in promoting agro-ecology transition in Southeast Nigeria. Agroecology and Sustainable Food Systems, 43(2), 123–144. https://doi.org/10.1080/21683565.2018.1509410
Ertunç, E., & Uyan, M. (2022). Land valuation with Best Worst Method in land consolidation projects. Land Use Policy, 122, 106360. https://doi.org/10.1016/J.LANDUSEPOL.2022.106360
Estepa-Mohedano, L., & Espinosa, M. P. (2023). Comparing risk elicitation in lotteries with visual or contextual aids. Journal of Behavioral and Experimental Economics, 103, 101974. https://doi.org/10.1016/J.SOCEC.2022.101974
Estepa-Mohedano, L., Jorrat, D., Orozco, V., & Rascón-Ramirez, E. (2022). Beans vs. Slider: Eliciting probabilities in the field. Mimeo.
Everest, T., Savaşkan, G. S., Or, A., & Özcan, H. (2022a). Suitable site selection by using full consistency method (FUCOM): A case study for maize cultivation in northwest Turkey. Environment, Development and Sustainability. https://doi.org/10.1007/S10668-022-02787-5
Everest, T., Sungur, A., & Özcan, H. (2022b). Applying the Best–Worst Method for land evaluation: A case study for paddy cultivation in northwest Turkey. International Journal of Environmental Science and Technology, 19(4), 3233–3246. https://doi.org/10.1007/S13762-021-03373-4
Fernandez Portillo, L. A., Nekhay, O., & Estepa Mohedano, L. (2019). Use of the ANP methodology to prioritize rural development strategies under the LEADER approach in protected areas. The case of Lagodekhi, Georgia. Land Use Policy, 88, 104121. https://doi.org/10.1016/j.landusepol.2019.104121
Ferreiro, E. (1983). Los adultos no alfabetizados y sus conceptualizaciones del sistema de escritura. Cuadernos De Investigación Educativa, 10, 1–147.
Firoozzare, A., Saghaian, S., Bahraseman, S. E., & Dehghani Dashtabi, M. (2023). Identifying the best strategies for improving and developing sustainable rain-fed agriculture: An integrated SWOT-BWM-WASPAS approach. Agriculture, 13(6), 1215. https://doi.org/10.3390/AGRICULTURE13061215
Flynn, D., Van Schaik, P., & Van Wersch, A. (2004). A comparison of multi-item likert and visual analogue scales for the assessment of transactionally defined coping function. European Journal of Psychological Assessment, 20(1), 49–58. https://doi.org/10.1027/1015-5759.20.1.49
Fritz, M., Grimm, M., Keilbart, P., Laksmana, D. D., Luck, N., Padmanabhan, M., Subandi, N., & Tamtomo, K. (2021). Turning Indonesia organic: Insights from transdisciplinary research on the challenges of a societal transformation. Sustainability, 13(23), 13011. https://doi.org/10.3390/SU132313011
Garcia-Retamero, R., & Cokely, E. T. (2017). Designing visual aids that promote risk literacy: A systematic review of health research and evidence-based design heuristics. Human Factors, 59(4), 582–627. https://doi.org/10.1177/0018720817690634
Gerlak, A. K., Guido, Z., Owen, G., McGoffin, M. S. R., Louder, E., Davies, J., Smith, K. J., Zimmer, A., Murveit, A. M., Meadow, A., Shrestha, P., & Joshi, N. (2023). Stakeholder engagement in the co-production of knowledge for environmental decision-making. World Development, 170, 106336. https://doi.org/10.1016/J.WORLDDEV.2023.106336
Gómez-Limón, J. A., Arriaza, M., & Guerrero-Baena, M. D. (2020). Building a composite indicator to measure environmental sustainability using alternative weighting methods. Sustainability, 12(11), 4398. https://doi.org/10.3390/SU12114398
Gruber, M. (2022). The integration of local actors in policy implementation: The case of organic farming in Costa Rica. Sustainability (switzerland), 14(12), 1–23. https://doi.org/10.3390/su14127265
Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23–31. https://doi.org/10.1016/J.KNOSYS.2017.01.010
Gutiérrez García, G. A., Gutiérrez-Montes, I., Hernández Núñez, H. E., Suárez Salazar, J. C., & Casanoves, F. (2020). Relevance of local knowledge in decision-making and rural innovation: A methodological proposal for leveraging participation of Colombian cocoa producers. Journal of Rural Studies, 75, 119–124. https://doi.org/10.1016/J.JRURSTUD.2020.01.012
Hafezalkotob, A., Hami-Dindar, A., Rabie, N., & Hafezalkotob, A. (2018). A decision support system for agricultural machines and equipment selection: A case study on olive harvester machines. Computers and Electronics in Agriculture, 148, 207–216. https://doi.org/10.1016/J.COMPAG.2018.03.012
Han, G., & Grudens-Schuck, N. (2022). Motivations and challenges for adoption of organic grain production: A qualitative study of Iowa organic farmers. Foods, 11(21), 3512. https://doi.org/10.3390/FOODS11213512
Heck, N., Paytan, A., Potts, D. C., Haddad, B., & Petersen, K. L. (2017). Management priorities for seawater desalination plants in a marine protected area: A multi-criteria analysis. Marine Policy, 86, 64–71. https://doi.org/10.1016/J.MARPOL.2017.09.012
Hilbert, S., Küchenhoff, H., Sarubin, N., Nakagawa, T. T., & Bühner, M. (2016). The influence of the response format in a personality questionnaire: An analysis of a dichotomous, a Likert-type, and a visual analogue scale. TPM—Testing, Psychometrics, Methodology in Applied Psychology, 23(1), 3–24. https://doi.org/10.4473/TPM23.1.1
Hoang, V., & Nguyen, V. (2023). Determinants of small farmers’ participation in contract farming in developing countries: A study in Vietnam. Agribusiness, 39(3), 836–853. https://doi.org/10.1002/AGR.21795.
Kallas, Z., Serra, T., & Gil, J. M. (2010). Farmers’ objectives as determinants of organic farming adoption: The case of Catalonian vineyard production. Agricultural Economics, 41(5), 409–423. https://doi.org/10.1111/j.1574-0862.2010.00454.x
Karim, R., Lindberg, L., Wamala, S., & Emmelin, M. (2018). Men’s perceptions of women’s participation in development initiatives in rural Bangladesh. American Journal of Men’s Health, 12(2), 398–410. https://doi.org/10.1177/1557988317735394
Kaur, A., & Toor, M. S. (2015). Organic farming: Status and constraints. Indian Journal of Economics and Development, 11(1), 333. https://doi.org/10.5958/2322-0430.2015.00037.2
Kharola, S., Ram, M., Kumar Mangla, S., Goyal, N., Nautiyal, O. P., Pant, D., & Kazancoglu, Y. (2022). Exploring the green waste management problem in food supply chains: A circular economy context. Journal of Cleaner Production, 351, 131355. https://doi.org/10.1016/J.JCLEPRO.2022.131355
Kilcher, L. (2007). How organic agriculture contributes to sustainable development. Journal of Agriculture and Rural Development in the Tropics and Subtropics, 89, 31–49.
Knook, J., Eastwood, C., Mitchelmore, K., & Barker, A. (2023). Wellbeing, environmental sustainability and profitability: Including plurality of logics in participatory extension programmes for enhanced farmer resilience. Sociologia Ruralis, 63(S1), 141–162. https://doi.org/10.1111/SORU.12413
Kolagar, M. (2019). Adherence to urban agriculture in order to reach sustainable cities: A BWM–WASPAS approach. Smart Cities, 2(1), 31–45. https://doi.org/10.3390/smartcities2010003
Kumar, A., Mangla, S. K., Kumar, P., & Song, M. (2021). Mitigate risks in perishable food supply chains: Learning from COVID-19. Technological Forecasting and Social Change, 166, 120643. https://doi.org/10.1016/J.TECHFORE.2021.120643
Kumar, G., Bhujel, R. C., Aniket, A., Gupta, D., Yadav, A., & Asjad, M. (2023). Analyzing the barriers for aquaponics adoption using integrated BWM and fuzzy DEMATEL approach in Indian context. Environmental Science and Pollution Research, 30(16), 47800–47821. https://doi.org/10.1007/S11356-023-25561-0
Kumar, P., Rajesh Singh, K., & Singh, R. K. (2022). Strategic framework for developing resilience in agri-food supply chains during COVID 19 pandemic. International Journal of Logistics Research and Applications, 25(11), 1401–1424. https://doi.org/10.1080/13675567.2021.1908524
Laurillau, Y., Nguyen, V. B., Coutaz, J., Calvary, G., Mandran, N., Camara, F., & Balzarini, R. (2018). The TOP-slider for multi-criteria decision making by non-specialists. In ACM International Conference Proceeding Series (pp. 642–653). https://doi.org/10.1145/3240167.3240185
Lengerer, F., Steinführer, A., & Haartsen, T. (2022). To participate, or not to participate—That is the question. (Non-)participation of older residents in rural communities. Journal of Rural Studies, 91, 47–57. https://doi.org/10.1016/J.JRURSTUD.2022.02.008
Liang, D., Tang, W., & Fu, Y. (2023). Sustainable modern agricultural technology assessment by a multistakeholder transdisciplinary approach. IEEE Transactions on Engineering Management, 70(3), 1061–1075. https://doi.org/10.1109/TEM.2021.3097333
Liang, F., Brunelli, M., & Rezaei, J. (2020). Consistency issues in the best worst method: Measurements and thresholds. Omega, 96, 102175. https://doi.org/10.1016/J.OMEGA.2019.102175
Lim, J. Y., How, B. S., Teng, S. Y., Leong, W. D., Tang, J. P., Lam, H. L., & Yoo, C. K. (2021). Multi-objective lifecycle optimization for oil palm fertilizer formulation: A hybrid P-graph and TOPSIS approach. Resources, Conservation and Recycling, 166, 105357. https://doi.org/10.1016/J.RESCONREC.2020.105357
Luria, A. R. (1976). The cognitive development: Its cultural and social foundations. Harvard University Press.
Maffioli, E. M., & Mohanan, M. (2018). Touching beliefs: Using touchscreen technology to elicit subjective expectations in survey research. PLoS ONE, 13(11), e0207484. https://doi.org/10.1371/JOURNAL.PONE.0207484
Mahdavi, H., Allahyari, M. S., Damalas, C. A., & Dunn, E. S. (2020). Drivers and barriers for organic rice (Oryza sativa L.) production in northern Iran: Experts’ consensus using the Delphi method. Biological Agriculture and Horticulture, 36(2), 96–106. https://doi.org/10.1080/01448765.2019.1698464
Mangan, P., Pandi, D., Haq, M. A., Sinha, A., Nagarajan, R., Dasani, T., Keshta, I., & Alshehri, M. (2022). Analytic hierarchy process based land suitability for organic farming in the arid region. Sustainability (switzerland), 14(8), 4542. https://doi.org/10.3390/SU14084542
Marsh-Richard, D. M., Hatzis, E. S., Mathis, C. W., Venditti, N., & Dougherty, D. M. (2009). Adaptive visual analog scales (AVAS): A modifiable software program for the creation, administration, and scoring of visual analog scales. Behavior Research Methods, 41(1), 99–106. https://doi.org/10.3758/BRM.41.1.99
Matejka, J., Glueck, M., Grossman, T., & Fitzmaurice, G. (2016). The effect of visual appearance on the performance of continuous sliders and visual analogue scales. In Conference on human factors in computing systems-proceedings (pp. 5421–5432). https://doi.org/10.1145/2858036.2858063
Maughan, C., & Anderson, C. R. (2023). “A shared human endeavor”: Farmer participation and knowledge co-production in agroecological research. Frontiers in Sustainable Food Systems, 7, 1162658. https://doi.org/10.3389/FSUFS.2023.1162658
Mena, Y., Nahed, J., Ruiz, F. A., Sánchez-Muñoz, J. B., Ruiz-Rojas, J. L., & Castel, J. M. (2012). Evaluating mountain goat dairy systems for conversion to the organic model, using a multicriteria method. Animal, 6(4), 693–703. https://doi.org/10.1017/S175173111100190X
Mishra, D., Muduli, K., Sevcik, L., Jana, S. K., & Ray, M. (2023). Combating of associated issues for sustainable agri-food sectors. Sustainability, 15(13), 10096. https://doi.org/10.3390/SU151310096
Mishra, D., & Satapathy, S. (2019). Intelligent decision-making approaches for agricultural sectors of Odisha in India. International Journal of Decision Support System Technology, 11(4), 67–95. https://doi.org/10.4018/IJDSST.2019100104
Mishra, D., & Satapathy, S. (2022). Sustainable agriculture: An evaluation using ANFIS. International Journal of Social Ecology and Sustainable Development, 13(1), 1–15. https://doi.org/10.4018/IJSESD.287124
Montemurro, F., Persiani, A., & Diacono, M. (2018). Environmental sustainability assessment of horticultural systems: A multi-criteria evaluation approach applied in a case study in mediterranean conditions. Agronomy, 8(7), 98. https://doi.org/10.3390/AGRONOMY8070098
Moslem, S. (2023). A novel parsimonious best worst method for evaluating travel mode choice. IEEE Access, 11, 16768–16773. https://doi.org/10.1109/ACCESS.2023.3242120
Mou, Q., Xu, Z., & Liao, H. (2016). An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making. Information Sciences, 374, 224–239. https://doi.org/10.1016/J.INS.2016.08.074
Muhaimin, A. W., Retnoningsih, D., & Pariasa, I. I. (2023). The role of women in sustainable agriculture practices: Evidence from East Java Indonesia. IOP Conference Series: Earth and Environmental Science, 1153(1), 012005. https://doi.org/10.1088/1755-1315/1153/1/012005
Nahed, J., Grande, D., Aguilar, J. R., & Sánchez, B. (2016). Possibilities for converting conventional cattle production to the organic model in the Grijalva River Basin, Mexico. Cogent Food & Agriculture, 2(1), 1153767. https://doi.org/10.1080/23311932.2016.1153767
Nahed-Toral, J., Sanchez-Muñoz, B., Mena, Y., Ruiz-Rojas, J., Aguilar-Jimenez, R., Castel, J. M., De Asis Ruiz, F., Orantes-Zebadua, M., Manzur-Cruz, A., Cruz-Lopez, J., & Delgadillo-Puga, C. (2013). Feasibility of converting agrosilvopastoral systems of dairy cattle to the organic production model in southeastern Mexico. Journal of Cleaner Production, 43, 136–145. https://doi.org/10.1016/J.JCLEPRO.2012.12.019
Nasirahmadi, A., & Hensel, O. (2022). Toward the next generation of digitalization in agriculture based on digital twin paradigm. Sensors, 22(2), 498. https://doi.org/10.3390/S22020498
Parra-López, C., Sayadi, S., Garcia-Garcia, G., Ben Abdallah, S., & Carmona-Torres, C. (2023). Prioritising conservation actions towards the sustainability of the dehesa by integrating the demands of society. Agricultural Systems, 206, 103613. https://doi.org/10.1016/J.AGSY.2023.103613
Pascoe, S. (2022). A simplified algorithm for dealing with inconsistencies using the analytic hierarchy process. Algorithms, 15(12), 442. https://doi.org/10.3390/A15120442
Pashaei Kamali, F., Borges, J. A. R., Meuwissen, M. P. M., de Boer, I. J. M., & Oude Lansink, A. G. J. M. (2017). Sustainability assessment of agricultural systems: The validity of expert opinion and robustness of a multi-criteria analysis. Agricultural Systems, 157, 118–128. https://doi.org/10.1016/J.AGSY.2017.07.013
Quisumbing, A., Cole, S., Elias, M., Faas, S., Galiè, A., Malapit, H., Meinzen-Dick, R., Myers, E., Seymour, G., & Twyman, J. (2023). Measuring women’s empowerment in agriculture: Innovations and evidence. Global Food Security, 38, 100707. https://doi.org/10.1016/J.GFS.2023.100707
Qureshi, M. R. N., Singh, R. K., & Hasan, M. A. (2018). Decision support model to select crop pattern for sustainable agricultural practices using fuzzy MCDM. Environment, Development and Sustainability, 20(2), 641–659. https://doi.org/10.1007/S10668-016-9903-7
Ramírez-Peña, M., Cerezo-Narváez, A., Pastor-Fernández, A., Otero-Mateo, M., & Ballesteros-Pérez, P. (2023). Determination of requirements for the improvement of occupational safety in the cleaning of vertical tanks of petroleum products. Safety, 9(1), 6. https://doi.org/10.3390/SAFETY9010006
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126–130. https://doi.org/10.1016/J.OMEGA.2015.12.001
Rezvanfar, A., Eraktan, G., & Olhan, E. (2011). Determine of factors associated with the adoption of organic agriculture among small farmers in Iran. African Journal of Agricultural Research, 6(13), 2950–2956. https://doi.org/10.5897/AJAR11.105
Rivera-Garrido, N., Ramos-Sosa, M. P., Accerenzi, M., & Brañas-Garza, P. (2022). Continuous and binary sets of responses differ in the field. Scientific Reports, 12(1), 1–10. https://doi.org/10.1038/s41598-022-17907-4
Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26. https://doi.org/10.1016/0377-2217(90)90057-I
Sabir, M., Ali, Y., Abdullah Ali, A., Khan, J., & Ur Rehman, Z. U. (2022). The choice between organic and inorganic farming: Lessons from Pakistan. Renewable Agriculture and Food Systems. https://doi.org/10.1017/S1742170522000072
Salimi, N. (2023). Opportunity recognition for entrepreneurs based on a business model for sustainability: A systematic approach and its application in the Dutch dairy farming sector. IEEE Transactions on Engineering Management, 70(11), 3728–3744. https://doi.org/10.1109/TEM.2021.3082872
Sapbamrer, R., & Thammachai, A. (2021). A systematic review of factors influencing farmers’ adoption of organic farming. Sustainability, 13(7), 3842. https://doi.org/10.3390/SU13073842
Sarı, F., & Koyuncu, F. (2021). Multi criteria decision analysis to determine the suitability of agricultural crops for land consolidation areas. International Journal of Engineering and Geosciences, 6(2), 64–73. https://doi.org/10.26833/ijeg.683754
Seufert, V., Austin, S. E., Badami, M. G., Turner, S., & Ramankutty, N. (2023). The diversity of organic farmer motivations and livelihoods in the Global South—A case study in Kerala, India. Geoforum, 138, 103670. https://doi.org/10.1016/J.GEOFORUM.2022.103670
Shaloo Singh, R. P., Bisht, H., Jain, R., Suna, T., Bana, R. S., Godara, S., Shivay, Y. S., Singh, N., Bedi, J., Begam, S., Tamta, M., & Gautam, S. (2022). Crop-suitability analysis using the analytic hierarchy process and geospatial techniques for cereal production in North India. Sustainability (switzerland), 14(9), 1–21. https://doi.org/10.3390/su14095246
Sharifi, O., Sadati, S. A., Ghobadi, F. R., Sadati, S. A., Mohamadi, Y., & Del, P. T. T. (2010). Barriers to conversion to organic farming: A case study in Babol County in Iran. African Journal of Agricultural Research, 5(16), 2260–2267.
Sisto, R., Fernández-Portillo, L. A., Yazdani, M., Estepa-Mohedano, L., & Torkayesh, A. E. (2022). Strategic planning of rural areas: Integrating participatory backcasting and multiple criteria decision analysis tools. Socio-Economic Planning Sciences. https://doi.org/10.1016/j.seps.2022.101248
Smith, O. M., Jocson, D. M. I., Lee, B. W., Orpet, R. J., Taylor, J. M., Davis, A. G., Rieser, C. J., Clarke, A. E., Cohen, A. L., Hayes, A. M., Auth, C. A., Bergeron, P. E., Marshall, A. T., Reganold, J. P., Crowder, D. W., & Northfield, T. D. (2022). Identifying farming strategies associated with achieving global agricultural sustainability. Frontiers in Sustainable Food Systems, 6, 882503. https://doi.org/10.3389/FSUFS.2022.882503
Sobkow, A., Fulawka, K., Tomczak, P., Zjawiony, P., & Traczyk, J. (2019). Does mental number line training work? The effects of cognitive training on real-life mathematics, numeracy, and decision making. Journal of Experimental Psychology: Applied, 25(3), 372–385. https://doi.org/10.1037/XAP0000207
Soltani, S., Azadi, H., Mahmoudi, H., & Witlox, F. (2014). Organic agriculture in Iran: Farmers’ barriers to and factors influencing adoption. Renewable Agriculture and Food Systems, 29(2), 126–134. https://doi.org/10.1017/S1742170513000069
Srinivasan, K., Yadav, V. K., Kumar, A., Margabandu, B., Selvaraj, J., & Kumar, A. (2023). Prioritizing the mitigation strategies to lean and green barriers using fuzzy BWM-FTOPSIS method in the food supply chain: An empirical case study. International Journal of Lean Six Sigma, 14(5), 901–946. https://doi.org/10.1108/IJLSS-10-2021-0171
Studer, R. (2012). Does it matter how happiness is measured? Evidence from a randomized controlled experiment. Journal of Economic and Social Measurement, 37(4), 317–336. https://doi.org/10.3233/JEM-120364
Tan, Y., Wang, X., Liu, X., Zhang, S., Li, N., Liang, J., Xu, D., & Yang, Q. (2023). Comparison of AHP and BWM methods based on ArcGIS for ecological suitability assessment of Panax notoginseng in Yunnan Province, China. Industrial Crops and Products, 199, 116737. https://doi.org/10.1016/J.INDCROP.2023.116737
Thakur, N., Nigam, M., Tewary, R., Rajvanshi, K., Kumar, M., Shukla, S. K., Mahmoud, G. A. E., & Gupta, S. (2022). Drivers for the behavioural receptiveness and non-receptiveness of farmers towards organic cultivation system. Journal of King Saud University-Science, 34(5), 102107. https://doi.org/10.1016/J.JKSUS.2022.102107
Tiede, K. E., & Gaissmaier, W. (2023). How do people process different representations of statistical information? Insights into cognitive effort, representational inconsistencies, and individual differences. Medical Decision Making, 43(7–8), 803–820. https://doi.org/10.1177/0272989X231202505
Uyan, M., Janus, J., & Ertunç, E. (2023). Land use suitability model for grapevine (Vitis vinifera L.) cultivation using the best worst method: A case study from Ankara/Türkiye. Agriculture, 13(9), 1722. https://doi.org/10.3390/AGRICULTURE13091722
van de Kaa, G., Fens, T., & Rezaei, J. (2019). Residential grid storage technology battles: A multi-criteria analysis using BWM. Technology Analysis and Strategic Management, 31(1), 40–52. https://doi.org/10.1080/09537325.2018.1484441
Yang, L. (2012). Empowered or disempowered? Women’s participation in a development project in rural China. Asian Journal of Women’s Studies, 18(3), 38–67. https://doi.org/10.1080/12259276.2012.11666131
Yazdani, M., Torkayesh, A. E., Chatterjee, P., Fallahpour, A., Montero-Simo, M. J., Araque-Padilla, R. A., & Wong, K. Y. (2022). A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain. Socio-Economic Planning Sciences, 82, 101257. https://doi.org/10.1016/J.SEPS.2022.101257
Yeleliere, E., Antwi-Agyei, P., & Nyamekye, A. B. (2023). Mainstreaming indigenous knowledge systems and practices in climate-sensitive policies for resilient agricultural systems in Ghana. Society & Natural Resources, 36(6), 639–659. https://doi.org/10.1080/08941920.2023.2183446
Yin, R. K. (2018). Case study research and applications sixth edition. Angewandte Chemie International Edition, 6(11), 951–952.
Yu, N., Ouyang, Z., & Wang, H. (2022). Study on smart home interface design characteristics considering the influence of age difference: focusing on sliders. Frontiers in Psychology, 13, 828545. https://doi.org/10.3389/FPSYG.2022.828545
Zhang, X., Zhang, L., & Nie, T. (2023). Study on the impact of social capital on farmers’ decision-making behavior of adopting trusteeship services. Sustainability, 15(6), 5343. https://doi.org/10.3390/SU15065343.
Zvobgo, L., Johnston, P., Olagbegi, O. M., Simpson, N. P., & Trisos, C. H. (2023). Role of Indigenous and local knowledge in seasonal forecasts and climate adaptation: A case study of smallholder farmers in Chiredzi, Zimbabwe. Environmental Science & Policy, 145, 13–28. https://doi.org/10.1016/J.ENVSCI.2023.03.017
Funding
This work was supported by the Agencia Española de Cooperación Internacional para el Desarrollo, AECID (Spanish Agency for International Development Cooperation), [grant number 2020/PRYC/000982].
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Fernández-Portillo, L.A., Estepa-Mohedano, L. & Demir, G. The use of continuous visual aid in the Best–Worst Method: an experiment with organic farmers in Paraguay. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04648-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10668-024-04648-9