Factors affecting the use of climate-smart agricultural technologies among wheat farmers in Alborz province with a planned behavior approach
محورهای موضوعی :
Agriculture Marketing and Commercialization
Seyed Mohamad Khademi Noshabadi
1
,
Maryam Omidi Najafabadi
2
,
Mehdi Mirdamadi
3
1 - Department of Economics, Agricultural Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Agricultural Economics, Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Economics, Agricultural Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran.
تاریخ دریافت : 1402/04/12
تاریخ پذیرش : 1402/07/05
تاریخ انتشار : 1402/09/10
کلید واژه:
Climate Change,
Theory of planned behavior,
Climate-smart agriculture,
چکیده مقاله :
The increase of greenhouse gases such as methane and carbon dioxide in the earth's atmosphere has caused global warming and climate change. The effects of climate change, such as increasing temperatures and changes in rainfall, have threatened food security and reduced crop production. Therefore, it is necessary to use climate-smart agricultural (CSA) technologies for adaptation and resilience to these effects. The purpose of this study was to investigate the factors influencing the intention to use CSA technologies for climate-smart crop production using the theory of planned behavior. The method of this research was quantitative and research data has been collected through a questionnaire. The path analysis method was used to test the model. The statistical population of this research was 800 wheat farmers of Nazarabad city in Alborz province. The sample size was determined by Cochran's formula of 260 people and the sampling method was proportional stratified random. The results showed that the variables of attitude, subjective norms, and perceived behavioral control could predict 25.3% of the variance of the intention to use CSA technologies. The importance of these variables on the intention variable was respectively: subjective norms (0.340), perceived behavioral control (0.188), and attitude (0.148).
منابع و مأخذ:
Abdollahzadeh, G., Sharifzadeh, M. S., Sklenička, P., & Azadi, H. (2023). Adaptive capacity of farming systems to climate change in Iran: Application of composite index approach. Agricultural Systems, 204, 103537. https://doi.org/10.1016/j.agsy.2022.103537
Ahmmadi, P., Rahimian, M., & Movahed, R. G. (2021). Theory of planned behavior to predict consumer behavior in using products irrigated with purified wastewater in Iran consumer. Journal of Cleaner Production, 296, 126359. https://doi.org/10.1016/j.jclepro.2021.126359
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. 2002. Constructing a TPB questionnaire: Conceptual and methodological considerations.
Alborz Agricultural Jihad Organization (2022). https://alborz.maj.ir/page-alborzmain/FA/98/form/pId15634. Accessed 28 March 2022.
Ali, M. R., Shafiq, M., & Andejany, M. (2021). Determinants of consumers’ intentions towards the purchase of energy efficient appliances in Pakistan: An extended model of the theory of planned behavior. Sustainability, 13(2), 565. https://doi.org/10.3390/su13020565
Aryal, J. P., Jat, M. L., Sapkota, T. B., Khatri-Chhetri, A., Kassie, M., Rahut, D. B., & Maharjan, S. (2018). Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. International Journal of Climate Change Strategies and Management, 10(3), 407-427. https://doi.org/10.1108/IJCCSM-02-2017-0025
Asrari, A., Omidi Najafabadi, M., & Farajollah Hosseini, J. (2022). Modeling resilience behavior against climate change with food security approach. Journal of Environmental Studies and Sciences, 12(3), 547-565. https://doi.org/10.1007/s13412-022-00763-z
Atta-Aidoo, J., Antwi-Agyei, P., Dougill, A. J., Ogbanje, C. E., Akoto-Danso, E. K., & Eze, S. (2022). Adoption of climate-smart agricultural practices by smallholder farmers in rural Ghana: An application of the theory of planned behavior. PLOS Climate, 1(10), e0000082. https://doi.org/10.1371/journal.pclm.0000082
Bandari, M., Sarmad Saeedi, S., & Ghasemi, B. (2019). Identifying and modeling attitudinal factors associated with e-commerce purchase intention Case Study: Shahrvand Online Stores. Agricultural Marketing and Commercialization Journal, 3(2), 1-13, 2019. https://dorl.net/dor/20.1001.1.2676640.2019.3.2.1.3
Basir, S., AzadehDel, M., & Ooshaksaraei, M. (2023). The role of social media on the purchase intention of customers with IR-MCI numbers (Case of study: Iranian tea). Agricultural Marketing and Commercialization Journal, 7(1), 68-77. https://dorl.net/dor/20.1001.1.2676640.2023.7.1.17.5
Brüssow, K., Faße, A., & Grote, U. (2017). Implications of climate-smart strategy adoption by farm households for food security in Tanzania. Food security, 9, 1203-1218. https://doi.org/10.1007/s12571-017-0694-y
Chaudhary, R., & Bisai, S. (2018). Factors influencing green purchase behavior of millennials in India. Management of Environmental Quality: An International Journal, 29(5), 798-812. https://doi.org/10.1108/MEQ-02-2018-0023
Correia, E., Sousa, S., Viseu, C., & Leite, J. (2022). Using the theory of planned behavior to understand the students’ pro-environmental behavior: a case-study in a Portuguese HEI. International Journal of Sustainability in Higher Education, 23(5), 1070-1089. https://doi.org/10.1108/IJSHE-05-2021-0201
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Dunnett, A., Shirsath, P. B., Aggarwal, P. K., Thornton, P., Joshi, P. K., Pal, B. D., ... & Ghosh, J. (2018). Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions. Ecological modelling, 381, 23-35. https://doi.org/10.1016/j.ecolmodel.2018.04.008
Gao, J., Shahid, R., Ji, X., & Li, S. (2022). Climate Change resilience and sustainable tropical agriculture: Farmers’ perceptions, reactive adaptations and determinants of reactive adaptations in Hainan, China. Atmosphere, 13(6), 955. https://doi.org/10.3390/atmos13060955
IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (Eds.)]. IPCC, Geneva, Switzerland, 151 pp.
Iran Statistical Center website (2022). https://www.amar.org.ir/english/Iran-Statistical-Yearbook. Accessed 27 March 2022.
Jiang, L., Zhang, J., Wang, H. H., Zhang, L., & He, K. (2018). The impact of psychological factors on farmers’ intentions to reuse agricultural biomass waste for carbon emission abatement. Journal of Cleaner Production, 189, 797-804. https://doi.org/10.1016/j.jclepro.2018.04.040
Karami, A., Araghi, V. R. M., & Mobasheri, M. (2019). Investigating Factors Affecting Customer Acceptance in Using Applications in the Digital Product Marketing Platform. Agricultural Marketing and Commercialization Journal, 3(1), 82-94, 2019.
Li, J., Liu, G., Chen, Y., & Li, R. (2023). Study on the influence mechanism of adoption of smart agriculture technology behavior. Scientific Reports, 13(1), 8554. https://doi.org/10.1038/s41598-023-35091-x
Lipper, L., McCarthy, N., Zilberman, D., Asfaw, S., & Branca, G. (2017). Climate smart agriculture: building resilience to climate change (P. 630). Springer Nature.
Ma, J., Yin, Z., Hipel, K. W., Li, M., & He, J. (2021). Exploring factors influencing the application accuracy of the theory of planned behavior in explaining recycling behavior. Journal of Environmental Planning and Management, 1-26. https://doi.org/10.1080/09640568.2021.2001318
Macovei, O. I. (2015). Applying the theory of planned behavior in predicting proenvironmental behaviour: The case of energy conservation. Acta Universitatis Danubius. Œconomica, 11(4), 15-32.
Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and social psychology Bulletin, 18(1), 3-9. https://doi.org/10.1177/0146167292181001
Mirkhani, R., Vaezi, A., & Rezaei, H. (2020). Using soil properties to estimate the irrigated wheat yield in agricultural lands of Nazarabad region in Alborz province. Iranian journal of soil and water research, 51(5), 1227-1237.
Moradnezhadi, H., Aliabadi, V., Gholamrezai, S., & Mahdizade, H. (2023). Investigating determinants of intentions and behaviours of farmers towards a circular economy for water recycling in paddy field. Local Environment, 1-19. https://doi.org/10.1080/13549839.2022.2155940
Mutengwa, C. S., Mnkeni, P., & Kondwakwenda, A. (2023). Climate-Smart Agriculture and Food Security in Southern Africa: A Review of the Vulnerability of Smallholder Agriculture and Food Security to Climate Change. Sustainability, 15(4), 2882. https://doi.org/10.3390/su15042882
Narimisa, M. R., & Narimisa, M. R. Climate Change and Global Warming; Climate Change Vulnerability in local.
Palombi, L., & R. Sessa. (2013). Climate-smart agriculture: sourcebook. Food and Agriculture Organization of the United Nations, Rome.
Park, J., & Ha, S. (2014). Understanding consumer recycling behavior: Combining the theory of planned behavior and the norm activation model. Family and consumer sciences research journal, 42(3), 278-291. https://doi.org/10.1111/fcsr.12061
Rahimi, J., Malekian, A., & Khalili, A. (2019). Climate change impacts in Iran: assessing our current knowledge. Theoretical and Applied Climatology, 135, 545-564. https://doi.org/10.1007/s00704-018-2395-7
Rahman, K. M., & Noor, N. A. M. (2016). Exploring organic food purchase intention in Bangladesh: An evaluation by using the theory of planned behavior. International Business Management, 10(18), 4292-4300.
Reboita, M. S., Kuki, C. A. C., Marrafon, V. H., de Souza, C. A., Ferreira, G. W. S., Teodoro, T., & Lima, J. W. M. (2022). South America climate change revealed through climate indices projected by GCMs and Eta-RCM ensembles. Climate Dynamics, 58(1-2), 459-485. https://doi.org/10.1007/s00382-021-05918-2
Rezaei, E. E., Ghazaryan, G., Moradi, R., Dubovyk, O., & Siebert, S. (2021). Crop harvested area, not yield, drives variability in crop production in Iran. Environmental Research Letters, 16(6), 064058. https://doi.org/10.1088/1748-9326/abfe29
Safaeian, S., Falahatkar, S., & Tourian, M. J. (2023). Satellite observation of atmospheric CO2 and water storage change over Iran. Scientific Reports, 13(1), 3036.
https://doi.org/10.1038/s41598-023-28961-x
Saputra, W., & Pasaribu, L. H. (2023). Analysis of Factors Influencing Consumer Behavior on Plant-Based Foods Products through Theory of Planned Behavior and Green Marketing Approach. Budapest International Research and Critics Institute-Journal (BIRCI-Journal), 6(1), 269-280. https://doi.org/10.33258/birci.v6i1.7427
Sheeran, P., Conner, M., & Norman, P. (2001). Can the theory of planned behavior explain patterns of health behavior change? Health psychology, 20(1), 12. https://psycnet.apa.org/doi/10.1037/0278-6133.20.1.12
Soorani, F., & Ahmadvand, M. (2019). Determinants of consumers’ food management behavior: Applying and extending the theory of planned behavior. Waste management, 98, 151-159. https://doi.org/10.1016/j.wasman.2019.08.025
Teixeira, S. F., Barbosa, B., Cunha, H., & Oliveira, Z. (2022). Exploring the antecedents of organic food purchase intention: An extension of the theory of planned behavior. Sustainability, 14(1), 242. https://doi.org/10.3390/su14010242
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS quarterly, 125-143. https://doi.org/10.2307/249443
Thornton, P. K., Whitbread, A., Baedeker, T., Cairns, J., Claessens, L., Baethgen, W.... & Keating, B. (2018). A framework for priority-setting in climate smart agriculture research. Agricultural Systems, 167, 161-175. https://doi.org/10.1016/j.agsy.2018.09.009
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540
Xu, Z., Shan, J., Li, J., & Zhang, W. (2020). Extending the theory of planned behavior to predict public participation behavior in air pollution control: Beijing, China. Journal of Environmental Planning and Management, 63(4), 669-688. https://doi.org/10.1080/09640568.2019.1603821
Yadav, R., & Pathak, G. S. (2017). Determinants of consumers' green purchase behavior in a developing nation: Applying and extending the theory of planned behavior. Ecological economics, 134, 114-122. https://doi.org/10.1016/j.ecolecon.2016.12.019
Yao, L., Li, X., Zheng, R., & Zhang, Y. (2022). The impact of air pollution perception on urban settlement intentions of young talent in China. International journal of environmental research and public health, 19(3), 1080. https://doi.org/10.3390/ijerph1903108