The impact of ethical commitments on the intention to adopt digital agricultural technologies.
Developed norm activation model
Digital agriculture
Ethical commitments
Food security
Perceived risk
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
03 10 2024
03 10 2024
Historique:
received:
20
02
2024
accepted:
30
08
2024
medline:
4
10
2024
pubmed:
4
10
2024
entrez:
3
10
2024
Statut:
epublish
Résumé
Sustainable food security is a critical global concern and an urgent priority in developing countries such as Iran. Digital agricultural technologies (DAT) represent significant solutions in this regard, yet their adoptions and development in Iran face limitations. Theoretical studies have underscored the importance of ethical commitments in the adoption process. This study aims to investigate whether ethical commitments regarding food security can influence the intention to adopt digital technologies by farmers. The study employed the Norm Activation Model and integrated two additional components, namely perceived risk and social capital. We applied this framework to examine research works on farmers of Kermanshah Province in the west of Iran, using survey data (sample n = 384). Data analyses were done through structural equation modeling (SEM). Based on the results, the developed Norm Activation Model can be used to predict the adoption intention of DAT by farmers; with the model explaining 65% of total variance. Feeling guilt exhibited the highest direct effect, followed by feeling proud. Furthermore, ethical norms had a direct and indirect impact on intention through the mediating variables of feeling proud and Feeling guilt. The findings of this study contribute to facilitating innovation adoption strategies. It is recommended that, in order to facilitate and stabilize farmers' adoption of innovation, their sense of guilt should first be aroused. After stimulating the farmers' sense of pride toward the adoption; emphasis should be placed on ethical commitments. Ultimately, the introduction of technology and the facilitation of infrastructure should be pursued.
Identifiants
pubmed: 39362979
doi: 10.1038/s41598-024-71723-6
pii: 10.1038/s41598-024-71723-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
23035Informations de copyright
© 2024. The Author(s).
Références
Adeniyi, D. A. & Dinbabo, M. F. Factors influencing household food security among irrigation smallholders in North West Nigeria. J. Rev. Glob. Econ. 8, 291–304. https://doi.org/10.6000/1929-7092.2019.08.25 (2019).
doi: 10.6000/1929-7092.2019.08.25
Lajoie-O’Malley, A., Bronson, K., van der Burg, S. & Klerkx, L. The future(s) of digital agriculture and sustainable food systems: An analysis of high-level policy documents. Ecosyst. Serv. 45, 1–13. https://doi.org/10.1016/j.ecoser.2020.101183 (2020).
doi: 10.1016/j.ecoser.2020.101183
Paslakis, G., Dimitropoulos, G. & Katzman, D. K. A call to action to address COVID-19–induced global food insecurity to prevent hunger, malnutrition, and eating pathology. Nutr. Rev. 79, 114–116 (2021).
doi: 10.1093/nutrit/nuaa069
pubmed: 32651592
Misselhorn, A. et al. A vision for attaining food security. Curr. Opin. Environ. Sustain. 4, 7–17. https://doi.org/10.1016/j.cosust.2012.01.008 (2017).
doi: 10.1016/j.cosust.2012.01.008
World Bank. Poverty and Equity Database. http://povertydata.worldbank.org (2020).
Campos, A., Villani, C., Davis, B. & Takagi, M. Ending extreme poverty in rural areas - Sustaining livelihoods to leave no one behind. FAO (2018).
Bai, J., Seale, J.L., J. R. & Wahl, T. I. Meat demands in China: to include or not to include meat away from home? Aust. J. Agric. Resour. Econ. 64, 150–170. https://doi.org/10.1007/s11213-019-09506-8 (2020).
Motaghi, M. & Shabanali Fami, H. The Role of nutrition-sensitive agriculture in food security and nutrition. Sci. Prom. Q. 23, 252–269. https://doi.org/10.22034/POPSCI.2021.283133.1086 (2021).
doi: 10.22034/POPSCI.2021.283133.1086
Zobeidi, T., Yazdanpanah, M., Komendantova, N., Sieber, S. & Lohr, K. Factors affecting smallholder farmers’ technical and non-technical adaptation responses to drought in Iran. J. Environ. Manag. 298, 113552. https://doi.org/10.1016/j.jenvman.2021.113552 (2021).
doi: 10.1016/j.jenvman.2021.113552
Bellon Maurel, V., Brossard, L., Garcia, F., Mitton, N. & Termier, A. Agriculture and digital technology: Getting the most out of digital technology to contribute to thetransition to sustainable agriculture and food systems. 1–185. https://doi.org/10.17180/wmkb-ty56-en (2022).
Gumbi, N., Gumbi, L. & Twinomurinzi, H. Towards sustainable digital agriculture for smallholder farmers: A systematic literature review. Sustainability 15, 12530. https://doi.org/10.1038/nature10452 (2023).
doi: 10.1038/nature10452
Balasundram, S. K., Shamshiri, R. R., Sridhara, S. & Rizan, N. The role of digital agriculture in mitigating climate change and ensuring food security: An overview. Sustainability 15, 1–23. https://doi.org/10.3390/agriculture13081471 (2023).
doi: 10.3390/agriculture13081471
Bontsa, N. V., Mushunje, A. & Ngarava, S. Factors influencing the perceptions of smallholder farmers towards adoption of digital technologies in eastern cape province, South Africa. Agriculture 13, 1–16. https://doi.org/10.3390/agriculture13081471 (2023).
doi: 10.3390/agriculture13081471
Van der Burg, S., Bogaardt, M. J. & Wolfert, S. Ethics of smart farming: Current questions and directions for responsible innovation towards the future. NJAS Wageningen J. Life Sci. 90–91, 100289. https://doi.org/10.1016/j.njas.2019.01.001 (2019).
doi: 10.1016/j.njas.2019.01.001
Foley, J., Ramankutty, N. & Brauman, K. Solutions for a cultivated planet. Nature 478, 337–342 (2011).
doi: 10.1038/nature10452
pubmed: 21993620
Shepherd, M., Turner, J., Small, B. & Wheeler, D. Priorities for science to overcome hurdles thwarting the full promise of the ‘digital agriculture’ revolution. J. Sci. Food Agric. 100, 5083–5092. https://doi.org/10.1002/jsfa.9346 (2020).
doi: 10.1002/jsfa.9346
pubmed: 30191570
Soma, T. & Nuckchady, B. Communicating the benefits and risks of digital agriculture technologies: Perspectives on the future of digital agricultural education and training. Orig. Res. 6, 1–17. https://doi.org/10.3389/fcomm.2021.762201 (2021).
doi: 10.3389/fcomm.2021.762201
Wolfert, S., Ge, L., Verdouw, C. & Bogaardt, M. Big data in smart farming–a review. Agric. Syst. 153, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023 (2017).
doi: 10.1016/j.agsy.2017.01.023
Weersink, A., Fraser, E., Pannell, D., Duncan, E. & Rotz, S. Opportunities and challenges for big data in agricultural and environmental analysis. Annu. Rev. Resour. Econ. 10, 19–37. https://doi.org/10.1146/annurev-resource-100516-053654 (2018).
doi: 10.1146/annurev-resource-100516-053654
Basso, B. & Antle, J. Digital agriculture to design sustainable agricultural systems. Nat. Sustain. 3, 254–256. https://doi.org/10.1038/s41893-020-0510-0 (2020).
doi: 10.1038/s41893-020-0510-0
FAO. FAO’s Work on Agricultural Innovation: Sowing the seeds of transformation to achieve the SDGs. Rome (2018).
FAO. Nutrition-sensitive agriculture and food systems in practice options for intervention. http://www.fao.org/3/a-i7848e.pdf (2017).
Rose, D. & Chilvers, J. Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Front. Sustain. Food Syst. https://doi.org/10.3389/fsufs.2018.00087 (2018).
doi: 10.3389/fsufs.2018.00087
Atanga, S.N. Digitalization of Agriculture: How digital technology is transforming small-scale farming in Ghana [Masters]. International Institute of Social Studies. http://hdl.handle.net/2105/55705 (2020).
Newell, P. & Taylor, O. Contested landscapes: The global political economy of climate-smart agriculture. J. Peasant Stud. 45, 108–129. https://doi.org/10.1080/03066150.2017.1324426 (2018).
doi: 10.1080/03066150.2017.1324426
Abdulai, A. R. Toward digitalization futures in smallholder farming systems in Sub-Sahara Africa: A social practice proposal. Front. Sustain. Food Syst. https://doi.org/10.3389/fsufs.2022.866331 (2022).
doi: 10.3389/fsufs.2022.866331
Edwards, J. P., Kuhn-Sherlock, B., Dela Rue, B. T. & Eastwood, C. R. Short communication: Technologies and milking practices that reduce hours of work and increase flexibility through milking efficiency in pasture-based dairy farm systems. J. Dairy Sci. 103, 7172–7179. https://doi.org/10.3168/jds.2019-17941 (2020).
doi: 10.3168/jds.2019-17941
pubmed: 32505396
Colussi, J., Morgan, E. L., Schnitkey, G. D. & Padula, A. D. How Communication affects the adoption of digital technologies in soybean production: A survey in Brazil. Agriculture 12, 611. https://doi.org/10.3390/agriculture12050611 (2022).
doi: 10.3390/agriculture12050611
Savari, M. & Noushad, M. Factors influencing the improvement of food security in rural households: A case study of Hendijan county. Agric. Prod. Market. Econ. J. 1, 41–54 (2022).
Mehrabi Besharabadi, H. & Ouhadi, A. H. Investigating factors affecting food security in Iran. Agric. Econ. J. 8, 111–121 (2014).
Jomani, D., Amini, A., Qader Morzi, H. & Tavakoli, J. Assessment of food security and exploring its challenges in rural areas: A case study of badr rural district, Ravansar county. J. Reg. Plan. 7, 87–102. https://doi.org/10.22067/geography.v14i2.63833 (2017).
doi: 10.22067/geography.v14i2.63833
Azadfar, M., Lashgarara, F., Farajollahi Hosseini, S. J., Omidinajafabadi, M. & Afshari, H. Identification and ranking of factors influencing food security improvement based on the role of nano technology. Agric. Extens. Educ. Res. J. 14, 1–16. https://doi.org/10.30495/JAEER.2022.19232 (2021).
doi: 10.30495/JAEER.2022.19232
Rezaeifar, M., Khalilian, S. & Najafi Alamdarloo, H. Spatial distribution of food insecurity in urban and rural areas of Iran. Agric. Econ. J. 16, 99–121. https://doi.org/10.22034/iaes.2022.540824.1881 (2022).
doi: 10.22034/iaes.2022.540824.1881
FAO. The state of food security and nutrition in the world 2018. Building climate resilience for food security and nutrition. (FAO), Rome, Italy (2018).
Savari, M. A proposed model for sustainable food security in drought conditions in Kurdistan province. J. Environ. Hazards Anal. 9, 81–104 (2023).
Akati, M., Ahmadpour Borazjani, M. & Sarani, V. Identifying factors affecting food security in rural areas: A case study of zehak region in sistan and baluchestan province. J. Rural Dev. Strateg. 7, 199–209. https://doi.org/10.22048/rdsj.2020.243527.1865 (2020).
doi: 10.22048/rdsj.2020.243527.1865
Li, J., Liu, G., Chen, Y. & Li, R. Study on the influence mechanism of adoption of smart agriculture technology behavior. Sci. Rep. 13, 1–13. https://doi.org/10.1038/s41598-023-35091 (2023).
doi: 10.1038/s41598-023-35091
pubmed: 36593249
pmcid: 9807638
Abdulai, A. R., Gibson, R. & Fraser, E. D. G. Beyond transformations: Zooming in on agricultural digitalization and the changing social practices of rural farming in Northern Ghana, West Africa. J. Rural Stud. 100, 1–10. https://doi.org/10.1016/j.jrurstud.2023.103019 (2023).
doi: 10.1016/j.jrurstud.2023.103019
Bolfe, E. L. et al. Precision and digital agriculture: Adoption of technologies and perception of Brazilian farmers. Agriculture 10, 653. https://doi.org/10.3390/agriculture10120653 (2020).
doi: 10.3390/agriculture10120653
Pivoto, D. et al. Factors influencing the adoption of smart farming by Brazilian grain farmers. Int. Food Agribus. Manag. Rev. 72, 62–148. https://doi.org/10.22004/ag.econ.290387 (2019).
doi: 10.22004/ag.econ.290387
Bobryk, C. W., Yost, M. A. & Kitchen, N. R. Field variability and vulnerability index to identify regional precision agriculture opportunity. Precis. Agric. 19, 589–605. https://doi.org/10.14279/depositonce-17552 (2018).
doi: 10.14279/depositonce-17552
Yazdi-Samadi, B. Application of future technologies in ensuring food security in Iran and the world. Strateg. Res. Agric. Sci. Nat. Resour. 2, 15–28 (2017).
Mirzaei, M. & Zand, E. Transformation in the Agricultural Sector with a Smart Approach: Experiences of Asian APO Member Countries (Agricultural Extension and Education Institute. Agricultural Education Publication, 2020).
Forouzanfar, M. H. & Molahosseini, A. Designing ethics-based model for technology Acceptance in SMEs. J. Ethics Sci. Technol. 13, 57–63 (2019).
Mohammadi, A. & Yaghobi, S. Technology acceptance model with emphasis on cultural conditions in Iran. Technol. Dev. Q. 24, 25–34 (2014).
Hagh Parast, R., Hedayatinia, S., Khosrawipour, B. & Ghanian, M. Structural equation for effective factors on ICT acceptance among graduate students in agriculture department of Ramin Ahwaz. Agric. Educ. Manag. Q. 29, 49–62 (2014).
Fahami, R. & Zarea, H. Factors affecting the acceptance of new technologies in remote education using the technology acceptance model (Case study: Payame noor university of Isfahan). New Approach Train. Manag. Q. 4, 67–80 (2013).
Gebrezgabher, S. A., Meuwissen, P. M., Kruseman, G., Lanker, D. & Lansink, A. G. Factors influencing adoption of manure separation technology in the Netherlands. J. Environ. Manag. 150, 1–8 (2015).
doi: 10.1016/j.jenvman.2014.10.029
Ozbek, V., Alniacik, U., Koc, F., Akkilic, M. E. & Kas, E. The impact of personality on technology acceptance: A study on smart phone users. Procedia- Soc. Behav. Sci. 150, 541–551 (2014).
doi: 10.1016/j.sbspro.2014.09.073
Turaga, R. M. R., Howarth, R. B. & Borsuk, M. E. Pro-environmental behavior. Ann. N. York Acad. Sci. 1185, 211–224. https://doi.org/10.1111/j.1749-6632.2009.05163.x (2010).
doi: 10.1111/j.1749-6632.2009.05163.x
Chen, S. H., Liang, M. & Yang, W. Does digital financial inclusion reduce china’s rural household vulnerability to poverty: An empirical analysis from the perspective of household entrepreneurship?. SAGE Open https://doi.org/10.1177/21582440221102423 (2022).
doi: 10.1177/21582440221102423
Baptista, F. et al. Which are the best practices for MSc programmes in sustainable agriculture?. J. Clean. Prod. 303, 126914 (2021).
doi: 10.1016/j.jclepro.2021.126914
Nicholls, E., Ely, A., Birkin, L., Basu, P. & Goulson, D. The contribution of small-scale food production in urban areas to the sustainable development goals: A review and case study. Sustain. Sci. https://doi.org/10.1007/s11625-020-00792-z (2020).
doi: 10.1007/s11625-020-00792-z
Klockner, C. A. A comprehensive model of the psychology of environmental behaviour. A meta-analysis. Glob. Environ. Change 23, 1028–1038. https://doi.org/10.1016/j.gloenvcha.2013.05.014 (2013).
doi: 10.1016/j.gloenvcha.2013.05.014
Harland, P., Staats, H. & Wilke, H. A. Situational and personality factors as direct or personal norm mediated predictors of pro-environmental behavior: Questions derived from norm-activation theory. Basic Appl. Soc. Psychol. 29, 323–334. https://doi.org/10.1080/01973530701665058 (2007).
doi: 10.1080/01973530701665058
De Groot, J. I. M. & Steg, L. Relationships between value orientations, self-determined motivational types and pro-environmental behavioural intentions. J. Environ. Psychol. 30, 368–378. https://doi.org/10.1016/j.jenvp.2010.04.002 (2010).
doi: 10.1016/j.jenvp.2010.04.002
Onwezen, M. C., Antonides, G. & Bartels, J. The norm activation model: An exploration of the functions of anticipated pride and guilt in pro-environmental behaviour. J. Econ. Psychol. 39, 141–153. https://doi.org/10.1016/j.joep.2013.07.005 (2013).
doi: 10.1016/j.joep.2013.07.005
Abrahamse, W., Steg, L., Gifford, R. & Vlek, C. Factors influencing car use for commuting and the intention to reduce it: A question of self-interest or morality?. Transp. Res. F Traffic Psychol. Behav. 12, 317–324. https://doi.org/10.1016/j.trf.2009.04.004 (2009).
doi: 10.1016/j.trf.2009.04.004
De Groot, J. I. & Steg, L. Morality and prosocial behavior: The role of awareness, responsibility, and norms in the norm activation model. J. Soc. Psychol. 149, 425–449. https://doi.org/10.3200/SOCP.149.4.425-449 (2009).
doi: 10.3200/SOCP.149.4.425-449
pubmed: 19702104
Park, J. & Ha, S. Understanding consumer recycling behavior: Combining the theory of planned behavior and the norm activation model. Fam. Consum. Sci. Res. J. 42, 278–291. https://doi.org/10.1111/fcsr.12061 (2014).
doi: 10.1111/fcsr.12061
Yazdanpanah, M. & Mardasi, Gh. R. Predicting the use of safety helmets among motorcycle farmers using psychological models in Shushtar County. Rural Res. Q. 8, 675–688. https://doi.org/10.22059/jrur.2017.221195.1018 (2017).
doi: 10.22059/jrur.2017.221195.1018
Han, H. The norm activation model and theory-broadening: Individuals’ decision-making on environmentally-responsible convention attendance. J. Environ. Psychol. 40, 462–471. https://doi.org/10.1016/j.jenvp.2014.10.006 (2014).
doi: 10.1016/j.jenvp.2014.10.006
Steg, L. & De Groot, J. Explaining prosocial intentions: Testing causal relationships in the norm activation model. Br. J. Soc. Psychol. 49, 725–743. https://doi.org/10.1348/014466609X477745 (2010).
doi: 10.1348/014466609X477745
pubmed: 20021707
Savari, M., Eskandari Damaneh, H., Eskandari Damaneh, H. & Cotton, M. Integrating the norm activation model and theory of planned behaviour to investigate farmer Pro-environmental behavioural intention. Sci. Rep. 13(5584), 1–14. https://doi.org/10.1038/s41598-023-32831-x (2023).
doi: 10.1038/s41598-023-32831-x
Mohammadi, S. Z., Mohammadzadeh, S. & Yazdanpanah, M. Predicting the factors affecting the behavior of palm farmers in the production cooperative of Dashtestan city in the field of water conservation by comparing the model of planned behavior and the norm-activating model. Coop. Agric. 28, 104–136 (2017).
Hamid, F., Yazdanpanah, M., Khalilmoghadam, B. & Azadi, H. Understanding the environmental behavior of farmers in Ramshir region regarding the application of nitrogen fertilizer and its influencing factors. J. Agric. Extens. Educ. Sci. Iran 1, 53–70. https://doi.org/10.22034/IAEEJ.2020.189059.1433 (2021).
doi: 10.22034/IAEEJ.2020.189059.1433
Klockner, C. A. & Blobaum, A. A comprehensive action determination model: Toward a broader understanding of ecological behaviour using the example of travel mode choice. J. Environ. Psychol. 4, 574–586. https://doi.org/10.1016/j.jenvp.2010.03.001 (2010).
doi: 10.1016/j.jenvp.2010.03.001
Sallis, J. F., Owen, N. & Fisher, E. Ecological models of health behavior. Health Behav. Theor. Res. Pract. 5, 43–64 (2015).
Hurlimann, A., Dolnicar, S. & Meyer, P. Understanding behaviour to inform water supply management in developed nations–a review of literature, conceptual model and research agenda. J. Environ. Manag. 1, 47–56. https://doi.org/10.1016/j.jenvman.07.014 (2009).
doi: 10.1016/j.jenvman.07.014
Moller, M., Haustein, S. & Bohlbro, M. S. Adolescents’ associations between travel behaviour and environmental impact: A qualitative study based on the Norm-Activation Model. Travel Behav. Soc. 11, 69–77. https://doi.org/10.1016/j.tbs.2017.12.005 (2018).
doi: 10.1016/j.tbs.2017.12.005
Kaiser, F. G. & Scheuthle, H. Two challenges to a moral extension of the theory of planned behavior, Moral norms and just world beliefs in conservationism. Personal. Indiv. Diff. 5, 1033–1048. https://doi.org/10.1016/S0191-8869(02)00316-1 (2003).
doi: 10.1016/S0191-8869(02)00316-1
Montazeri, M. & Zamani, G. H. Developing an environmental behavior model for farmers in Shiraz province. Iran. J. Agric. Sci. Technol. 2, 63–75 (2012).
Sentosa, I. & Mat, N. K. N. Examining a theory of planned behavior (TPB) and technology acceptance model (TAM) in internet purchasing using structural equation modeling. J. Arts Sci. Commerced 2, 62–77 (2012).
Braakhuis, J. Predicting pro environmental behavior. Master thesis, Utrecht University.
Ajzen, I., Fishbein, M. 1980. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall (2016).
Davis, F. D. Perceived usefulness, perceived ease of use, and user acceptance of informationtechnology. Manag. Inf. Syst. Q. 3, 319–340. https://doi.org/10.2307/249008 (1998).
doi: 10.2307/249008
Micheels, E. T. & Nolan, J. F. Examining the effects of absorptive capacity and social capital on the adoption of agriculturalinnovations: A canadian prairie case study. Agric. Syst. 145, 127–138. https://doi.org/10.1016/j.agsy.2016.03.010 (2016).
doi: 10.1016/j.agsy.2016.03.010
Pigg, K. E. & Crank, L. D. Building community social capital: The potential and promise of information and communications technologies. J. Community Inform. 1, 58–73. https://doi.org/10.15353/joci.v1i1.2062 (2004).
doi: 10.15353/joci.v1i1.2062
Hunecke, C., Engler, A., Jara-Rojas, R. & Poortvliet, P. M. Understanding the role of social capital in adoption decisions: An application to irrigation technology. Agric. Syst. 153, 221–231. https://doi.org/10.1016/j.agsy.2017.02.002 (2017).
doi: 10.1016/j.agsy.2017.02.002
Van Rijn, F., Bulte, E. & Adekunle, A. Social capital and agricultural innovation in sub-saharan Africa. Agric. Syst. 108, 112–122. https://doi.org/10.1016/j.agsy.2011.12.003 (2012).
doi: 10.1016/j.agsy.2011.12.003
Lambrecht, I., Vanlauwe, B., Merckx, R. & Maertens, M. Understanding the process of agricultural technology adoption: Mineral fertilizer in eastern DR Congo. World Dev. 59, 132–146. https://doi.org/10.1016/j.worlddev.2014.01.024 (2014).
doi: 10.1016/j.worlddev.2014.01.024
Michelini, J. J. Small farmers and social capital in development projects: Lessons from failures in Argentina’s rural periphery. J. Rural. Stud 30, 99–109. https://doi.org/10.1016/j.jrurstud.2013.01.001 (2013).
doi: 10.1016/j.jrurstud.2013.01.001
Sanginga, P. C., Kamugisha, R. N. & Martin, A. M. Conflicts management, social capital and adoption of agroforestry technologies: Empirical findings from the highlands of southwestern Uganda. Agrofor. Syst. 69, 67–76. https://doi.org/10.1007/s10457-006-9018-5 (2007).
doi: 10.1007/s10457-006-9018-5
Chirwa, E. W. Adoption of fertiliser and hybrid seeds by smallholder maize farmers in Southern Malawi. Dev. South. Afr. 22, 1–12. https://doi.org/10.1080/03768350500044065 (2005).
doi: 10.1080/03768350500044065
Isham, J. The effect of social capital on fertiliser adoption: Evidence from rural Tanzania. J. Afr. Econ. 11, 39–60 (2002).
doi: 10.1093/jae/11.1.39
Yazdanpanah, M., Klein, K., Zobeidi, T., Sieber, S. & Lohr, K. Why have economic incentives failed to convince farmers to adopt drip irrigation in southwestern Iran?. Sustainability 14, 1–15. https://doi.org/10.3390/su14042055 (2022).
doi: 10.3390/su14042055
Yazdanpanah, M. et al. What factors contribute to conversion to organic farming? Consideration of the Health Belief Model in relation to the uptake of organic farming by Iranian farmers. J. Environ. Plan. Manag. 65, 907–929. https://doi.org/10.1080/09640568.1917348 (2022).
doi: 10.1080/09640568.1917348
Jones, N., Sophoulis, C. M., Iosifides, T., Botetzagias, I. & Evangelinos, K. The influence of social capital on environmental policy instruments. Environ. Polit. 4, 595–611. https://doi.org/10.1080/09644010903007443 (2009).
doi: 10.1080/09644010903007443
Azadkhani, P., Hosseinzadeh, J. & Karami, F. Investigating the role of social capital in environmental protection in Ilam city. Environ. Sci. Technol. 9, 1–16. https://doi.org/10.22034/JEST.2021.30803.3926 (2020).
doi: 10.22034/JEST.2021.30803.3926
Thomas, M. L. The Influence of Social Class and Cultural Variables Sociology of Education (Greenwood Press, 2013).
Gorgi karsami, A., Radneya, H., Safari, R. & Asadi Rad, A. Investigate the relationship between social capital and citizen participation in environmental man-agement and urban health. The first conference national and urban and environmental services, Mashhad (2013).
Dizon, J. P. M., Enoch-Stevens, T. & Huerta, A. H. Carcerality and education: Toward a relational theory of risk in educational institutions. Am. Behav. Sci. 66, 1319–1341. https://doi.org/10.1177/00027642211054828 (2022).
doi: 10.1177/00027642211054828
Ahsan, D. A. & Roth, E. Farmers’ perceived risks and risk management strategies in an emerging mussel aquaculture industry in Denmark. Mar. Resour.Econ. 3, 309–323. https://doi.org/10.5950/0738-1360-25.3.309 (2010).
doi: 10.5950/0738-1360-25.3.309
Blesia, J. U., Iek, M., Ratang, W. & Hutajulu, H. Developing an entrepreneurship model to increase student’s entre-preneurial skills: An action research project in a higher education institution in Indonesia. Syst. Pract. Action Res. 34, 53–70. https://doi.org/10.1016/j.jclepro.2021.126914 (2021).
doi: 10.1016/j.jclepro.2021.126914
Zeng, Z., Zhong, W. & Shumaila, N. Can environmental knowledge and risk perception make a difference? The role of environmental concern and pro-environmental behavior in fostering sustainable consumption behavior. Sustainability 15, 4791. https://doi.org/10.3390/su15064791 (2023).
doi: 10.3390/su15064791
Yazdanpanah, M., Hayati, D. & Zamani, G. H. Investigating agricultural professionals’intentions and behaviours towards water conservation: Using a modified theory of planned behaviour. Environ. Sci. 1, 1–22 (2011).
Adger, W. N. et al. Are there social limits to adaptation to climate change?. Clim. Change 3, 335–354. https://doi.org/10.1007/s10584-008-9520-z (2009).
doi: 10.1007/s10584-008-9520-z
Moser, S. C. Communicating climate change: History, challenges, process and future directions. WIREs Clim. Change 1, 31–53. https://doi.org/10.1002/wcc.11 (2010).
doi: 10.1002/wcc.11
Ghobadi Aliabadi, S., Agah, H. & Farhadian, H. Investigating the effective factors on farmers’ perception of climate change risk and the effect of these factors on their adaptive behaviors (The case of Kermanshah Township). J. Reg. Plan. 46, 333–347 (2021).
Maqsoom, A. et al. Adopting green behaviors in the construction sector: The role of behavioral intention, motivation, and environmental consciousness. Buildings 13, 1–20. https://doi.org/10.3390/buildings13041036 (2023).
doi: 10.3390/buildings13041036
Wang, W., Zhao, X., Li, H. & Zhang, Q. Will social capital affect farmers’ choices of climate change adaptation strategies? Evidences from rural households in the Qinghai-Tibetan Plateau, China. J. Rural Stud. 83, 127–137. https://doi.org/10.1016/j.jrurstud.2021.02.006 (2021).
doi: 10.1016/j.jrurstud.2021.02.006
Krejcie, R. V. & Morgan, D. W. Determining sample size for research activities. Educ. Psychol. Meas. 30, 607–610. https://doi.org/10.1177/001316447003000308 (1970).
doi: 10.1177/001316447003000308
Akbari, M. R., Pishbahar, I. & Dashti, Q. Identification of factors affecting food insecurity in rural households of Iran: Application of extended logit latent class model. Iran. J. Appl. Econ. Stud. 9, 91–125. https://doi.org/10.22084/AES.2020.21656.3058 (2020).
doi: 10.22084/AES.2020.21656.3058
Bagherzadeh Azar, F. et al. Estimation and comparison of food security status and the impact of economic variables on it in Iranian provinces. J. Appl. Econ. Theor. 4, 47–76 (2016).
Shokri, N. & Asari Arani, A. Evaluation of factors affecting food security in Kermanshah province: Application of multiple regression method. Agric. Econ. Res. 1, 181–202 (2020).
Khanzadi, A., Karimi, M. S. & Shakouri, N. Estimation of food security in Kermanshah province with emphasis on FSI index. Agric. Econ. Dev. J. 1, 69–82. https://doi.org/10.22067/JEAD2.V32I1.68939 (2018).
doi: 10.22067/JEAD2.V32I1.68939
De Groot, J. I. M., Steg, L. & Dicke, M. Morality and reducing car use: Testing the norm activation model of prosocial behavior. Transportation Research Trends. New York, NY: NOVA (2007).
Chan, R. Y. K. & Lau, L. B. Y. Explaining green purchasing behavior. J. Int. Consum. Mark. 14, 9–40. https://doi.org/10.1300/J046v14n02_02 (2002).
doi: 10.1300/J046v14n02_02
Norris, E. & Myers, L. Determinants of personal protective equipment (PPE) use in UK motorcyclists: Exploratory research applying an extended theory of planned behaviour. Accid. Anal. Prev. 60, 219–230. https://doi.org/10.1016/j.aap.2013.09.002 (2013).
doi: 10.1016/j.aap.2013.09.002
pubmed: 24076303
Jiang, L., Zhang, J., Wang, H. H., Zhang, L. & He, K. The impact of psychological factors on farmers’ intentions to reuse agricultural biomass waste for carbon emission abatement. J. Clean. Prod. 189, 797–804. https://doi.org/10.1016/j.jclepro.2018.04.040 (2018).
doi: 10.1016/j.jclepro.2018.04.040
Yazdanpanah, M., Hayati, D., Hochrainer-Stigler, S. & Zamani, G. H. Understanding farmers’ intention and behavior regarding water conservation in the Middle-East and North Africa: A case study in Iran. J. Environ. Manag. 135, 63–72. https://doi.org/10.1016/j.jenvman.2014.01.016 (2014).
doi: 10.1016/j.jenvman.2014.01.016
Setiawan, R., Santosa, W. & Sjafruddin, A. Entegration of theory of planned behavior and norm activation model on student behavior model using cars for traveling to campus. Civil Eng. Dimens. 2, 117–122. https://doi.org/10.9744/CED.16.2 (2014).
doi: 10.9744/CED.16.2
Bamberg, S., Hunecke, M. & Blobaum, A. Social context, personal norms and the use of publictransportation: Two field studies. J. Environ. Psychol. 3, 190–203. https://doi.org/10.1016/j.jenvp.2007.04.001 (2007).
doi: 10.1016/j.jenvp.2007.04.001
Pepper, M. & Leonard, R. How ecotheological beliefs vary among Australian churchgoers and consequences for environmental attitudes and behaviors. Rev. Relig. Res. 58, 101–124. https://doi.org/10.1007/s13644-015-0234-1 (2016).
doi: 10.1007/s13644-015-0234-1
Marquart-Pyatt, S. T. Public opinion about the environment: Testing measurement equivalence across countries. Int. J. Sociol. 45, 309–326. https://doi.org/10.1080/00207659.2015.1098268 (2015).
doi: 10.1080/00207659.2015.1098268
Wan, Q. & Du, W. Social capital, environmental knowledge, and pro-environmental behavior. Int. J. Environ. Res. Public Health 2022(19), 1443. https://doi.org/10.3390/ijerph19031443 (2022).
doi: 10.3390/ijerph19031443
Petzold, J. & Ratter, B. Climate change adaptation under a social capital approach—An analytical framework for small island. Ocean Coast. Manag. 112, 36–43. https://doi.org/10.1016/j.ocecoaman.2015.05.003 (2015).
doi: 10.1016/j.ocecoaman.2015.05.003
Hua, Y., Dong, F. & Goodman, J. Howtoleveragetheroleofsocialcapitalinpro-environmental behavior: Acasestudy of residents’ express waste recycling behavior in China. J. Clean. Prod. 280, 124376. https://doi.org/10.3389/fenvs.2022.922711 (2021).
doi: 10.3389/fenvs.2022.922711
Smith, M. D. & Meade, B. Who Are the World’s Food Insecure? Identifying the Risk Factors of Food Insecurity around the World. Amber Waves: The Economics of Food, Farming, Natural Resources, and Rural America, 2019(1490–2020–721) (2019).
Erinle, K. O. et al. Impacts of COVID-19 on agriculture and food security in developing countries: Potential mitigation strategies. South Asia 30, 13. https://doi.org/10.1079/PAVSNNR202116016 (2021).
doi: 10.1079/PAVSNNR202116016
Bandura, A. Theoretical perspectives. Self-Efficacy the Exercise of Control. 31–35 (1997).
Ashouri, D., Allahyari, M. S. & Damalas, C. A. Adoption of conservation farming practices for sustainable rice production among small-scale paddy farmers in northern Iran. Paddy Water Environ. 15, 237–248. https://doi.org/10.1007/s10333-016-0543-1 (2017).
doi: 10.1007/s10333-016-0543-1
Azami, A., Suleimani, A. & Aghai, H. Assessment of rural satisfaction with rural cooperative companies in Kermanshah province. Reg. Plan. J. 2, 15–26 (2011).
Rahmani Fazli, A. & Kavyani, Y. Performance evaluation of the agricultural bank in the allocation of rural micro credits. J. Appl. Res. Geogr. Sci. 14, 125–143 (2009).
Doustmohammadi, H. & Alavian, M. The analysis of social capital condition in Iran, in bass of post modernism theories of Michel Foucault. Biq. J. Sociol. Soc. Inst. 13, 39–66. https://doi.org/10.22080/SSI.2019.13637.1378 (2019).
doi: 10.22080/SSI.2019.13637.1378