Modeling the factors affecting farmers' Intention to implement the land consolidation plan

Document Type : Research

Authors

1 Associate Prof., Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran.

2 PhD, Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran.

3 PhD Student of Sustainable Agricultural Extension and Education, Agricultural Science and Natural Resources University of Khuzestan. Mollasani, Iran

Abstract

The theory of planned behavior was used in this study to model the factors affecting farmers' intention to implement the land consolidation plan. For this purpose, use was made of a descriptive-correlation method based on the structural equation model. The statistical population included farmers in Miyanab District of Shushtar County (N=1400). A sample size of 301 people was adopted based on the Krejci and Morgan table while sampling was carried out using a stratified-random method. The data collection tool was a questionnaire, whose validity was confirmed based on expert opinion by university academic members and its reliability was endorsed through Cronbach's alpha. Also, the average variance extracted (AVE) index was used to determine construct validity while composite reliability (CR) and homogeneity reliability (Rho) indices were used to determine model reliability. The data collected were analyzed using SPSS26 and Smart PLS3 software. The results of the structural equation model showed that the variables attitude, subjective norms, and perceived behavioral control predicted 63% of the changes in farmers' intention to implement the land consolidation plan. In addition, farmer attitude and subjective norms explain 47% of the changes in perceived behavioral control and the subjective norm variable explains 37% of the changes in farmer attitude towards implementing the land consolidation plan.

Keywords

References

  1. Abdulkarim, B., Yacob, M. R., Abdullahi, A. M., & Radam, A. (2017). Farmers’ perceptions and attitudes toward forest watershed conservation of the North Selangor Peat Swamp Forest. Journal of sustainable forestry, 36(4), 309-323.

 https://doi.org/10.1080/10549811.2017.1300539

  1. Ahmadpour, A., Feli, S. and Soltani, Sh. (2015). Factors affecting the non-participation of rice farmers in Mazandaran province in the land consolidation plan, Journal of Rural and Development, 18(2). 1-18. (In Persian).
  2. Alibegi, A. Ghambarali, R. (2014). Investigating farmers' attitudes towards the effects of land consolidation in Kermanshah province: Application of Q methodology, Iranian Journal of Agricultural Extension and Education Sciences, 10 (1); 75-88. (In Persian)
  3. Amobegi, A. Hayati, D. (2009). Land integration: a challenge for advancing rural and agricultural development projects, Third National Congress of Agricultural Extension and Education Sciences, University of Mashhad, March 11-12, Mashhad. (In Persian)
  4. Bagheri, A. Shahpasand, M.R. (2010). Studying the attitude of potato farmers in the Ardabil plain towards sustainable agricultural practices, Iranian Agricultural Economics and Development Research, 41(2); 231-242. (In Persian)
  5. Bagheri, A., Bondori, A., Allahyari, M. S., & Surujlal, J. (2021). Use of biologic inputs among cereal farmers: application of technology acceptance model. Environment, Development and Sustainability, 23, 5165-5181. https://doi.org/10.1007/s10668-020-00808-9
  6. Bakhshi Moghadam, A., Mahmoudi, S., Hajinejad, A. (2022). Analysis of factors affecting the success of the agricultural land integration plan (example: Chobar village, Shaft county), Scientific Journal of Geographical Studies of Coastal Areas, 3(9), pp. 49-68.

 (In Persian).

  1. Bakhshi, M. and Rezqi, M. (2018). Analysis of the factors inhibiting and promoting farmers' participation in the implementation of the agricultural land integration plan (case study: villages in Nehbandan County), Geographical Studies of Arid Regions, 9(34), pp. 25-41. (In Persian).
  2. Bayranvand, M. B., Rahimian, M., Savari, M., Molavi, H., & Movahed, R. G. (2025). Predictors of ranchers’ Protection Behaviors in the Use of Pastures through Protection Motivation Theory. Rangeland Ecology & Management, 98, 576-587.

https://doi.org/10.1016/j.rama.2024.11.001

  1. Corbelle-Rico, E., Santé-Riveira, I., & Crecente-Maseda, R. (2018). A decision support system for farmland preservation: integration of past and present land use. Spatial Analysis and Location Modeling in Urban and Regional Systems, 173-192.1007/978-3-642-37896-6_8
  2. Derak, M., Cortina, J., & Taiqui, L. (2017). Integration of stakeholder choices and multi-criteria analysis to support land use planning in semiarid areas. Land use policy, 64, 414-428. https://doi.org/10.1016/j.landusepol.2017.03.006
  3. Eldredge, L. K. B., Markham, C. M., Ruiter, R. A., Fernández, M. E., Kok, G., & Parcel, G. S. (2016). Planning health promotion programs: an intervention mapping approach. John Wiley & Sons.
  4. Empidi, A. V. A., & Emang, D. (2021). Understanding Public Intentions to Participate in Protection Initiatives for Forested Watershed Areas Using the Theory of Planned Behavior: A Case Study of Cameron Highlands in Pahang, Malaysia. Sustainability, 13(8), 4399. https://doi.org/10.3390/su13084399
  5. 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

  1. Ertunç, E., Janus, J., & Uyan, M. (2023). Prioritization of land consolidation projects using the multi-criteria Best-Worst Method: a case study from Poland. Environmental Monitoring and Assessment, 195(9), 1045. https://doi.org/10.1007/s10661-023-11712-w
  2. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  3. Gedefaw, A. A., Atzberger, C., Seher, W., & Mansberger, R. (2019). Farmer willingness to participate in voluntary land consolidation in Gozamin District, Ethiopia. Land, 8(10), 148. https://doi.org/10.3390/land8100148
  4. Gessesse, A. T., Li, H., He, G., & Berhe, A. A. (2018). Study on farmer land consolidation adaptation intention: A structural equation modeling approach, the case of Sichuan province, China. China Agricultural Economic Review, 10(4), 666-682.

https://doi.org/10.1108/CAER-09-2016-0142

  1. Greaves, M., Zibarras, L. D., & Stride, C. (2013). Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. Journal of Environmental Psychology, 34, 109-120. https://doi.org/10.1016/j.jenvp.2013.02.003
  2. Hartvigsen, M., Versinskas, T., Vidar, M., Mittic, K., Arsova, F. V., & Gorgan, M. (2019). FAO Recommendations on Land Consolidation Legislation. In World Bank Conference on Land and Poverty, Washington, DC.
  3. Holt, J. R., Butler, B. J., Borsuk, M. E., Markowski-Lindsay, M., MacLean, M. G., & Thompson, J. R. (2021). Using the Theory of Planned Behavior to Understand Family Forest Owners’ Intended Responses to Invasive Forest Insects. Society & Natural Resources, 34(8), 1001-1018. https://doi.org/10.1080/08941920.2021.1924330
  4. Hong, C., Jin, X., Fan, Y., Xiang, X., Cao, S., Chen, C., & Zhou, Y. (2020). Determining the effect of land consolidation on agricultural production using a novel assessment framework. Land Degradation & Development, 31(3), 356-371.

https://doi.org/10.1002/ldr.3454

  1. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 20(2), 195-204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7
  2. Kolis, K., Hiironen, J., Ärölä, E., & Vitikainen, A. (2015). Profitability of Forest Land Consolidation–a Finnish Case Study. In FIG Working Week 2015, Sofia, Bulgaria, 1721 May 2015. FIG-International Federation of Surveyors.
  3. La Croix, S. (2015). Land confiscations and land reform in natural-order states. In Sustainable Economic Development(pp. 189-200). Academic Press.

https://doi.org/10.1016/B978-0-12-800347-3.00011-X

  1. Li, H., Jin, X., McCormick, B. P., Tittonell, P., Liu, J., Han, B., & Zhou, Y. (2023). Analysis of the contribution of land consolidation to sustainable poverty alleviation under various natural conditions. Land Use Policy, 133, 106871.

 https://doi.org/10.1016/j.landusepol.2023.106871

  1. MacKenzie, S. B., Podsakoff, P. M., & Jarvis, C. B. (2005). The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions. Journal of applied psychology, 90(4), 710. https://doi.org/10.1037/0021-9010.90.4.710
  2. Mazhary, M. E., & Poodat, F. (2019). The Role of Rituals in the Structure of Traditional City (The Case Study: Shushtar City). Quarterly Journal of Social Development (Previously Human Development), 13(4), 178-208.
  3. Mehmetoglu, (2012). Partial least squares approach to structural equation modeling for tourism research. In Advances in Hospitality and leisure (pp. 43-61). Emerald Group Publishing Limited. https://doi.org/10.1108/S1745-3542(2012)0000008007
  4. Popa, B., Niță, M. D., & Hălălișan, A. F. (2019). Intentions to engage in forest law enforcement in Romania: An application of the theory of planned behavior. Forest Policy and Economics, 100, 33-43. https://doi.org/10.1016/j.forpol.2018.11.005
  5. Raziuddin, K., Vaithianathan, S. (2018). A fresh look at understanding green consumer behavior among young urban Indian consumers through the lens of Theory of Planned Behavior. J. Clean. Prod. 183, 46–55. https://doi.org/10.1016/j.jclepro.2018.02.09
  6. Sánchez, M., López-Mosquera, N., Lera-López, F., & Faulin, J. (2018). An extended planned behavior model to explain the willingness to pay to reduce noise pollution in road transportation. Journal of cleaner production, 177, 144-154.

 https://doi.org/10.1016/j.jclepro.2017.12.210

  1. Savari, M., & Khaleghi, B. (2024). Factors influencing the application of forest conservation behavior among rural communities in Iran. Environmental and Sustainability Indicators, 21, 100325. https://doi.org/10.1016/j.indic.2023.100325
  2. Savari, M., & Khaleghi, B. (2025). Promoting safe and pro-environmental behaviors for sustainable forest management: Integrating technology acceptance model and the norm activation model. Socio-Economic Planning Sciences, 98, 102158.

https://doi.org/10.1016/j.seps.2025.102158

  1. Savari, M., Amghani, M. S., & Malekian, A. (2025a). Factors influencing the use of treated wastewater for irrigation in the agricultural sector: evidence from Iran. Cleaner Engineering and Technology, 100901. https://doi.org/10.1016/j.clet.2025.100901
  2. Savari, M., Damaneh, H. E., & Damaneh, H. E. (2024b). Managing the effects of drought through the use of risk reduction strategy in the agricultural sector of Iran. Climate Risk Management, 45, 100619. https://doi.org/10.1016/j.crm.2024.100619
  3. Savari, M., Damaneh, H. E., & Damaneh, H. E. (2025b). Discover the determining factors of the use of mangrove forests conservation behaviors. Journal for Nature Conservation, 83, 126768. https://doi.org/10.1016/j.jnc.2024.126768
  4. Savari, M., Khaleghi, B., & Sheheytavi, A. (2024c). Iranian farmers' response to the drought crisis: How can the consequences of drought be reduced?. International Journal of Disaster Risk Reduction, 114, 104910. https://doi.org/10.1016/j.ijdrr.2024.104910
  5. Savari, M., Sheheytavi, A., & Amghani, M. S. (2023). Factors underpinning Iranian farmers’ intention to conserve biodiversity at the farm level. Journal for Nature Conservation, 73, 126419. https://doi.org/10.1016/j.jnc.2023.126419
  6. Savari, M., Zhoolideh, M., & Limuie, M. (2024a). The combination of climate information services in the decision-making process of farmers to reduce climate risks: application of social cognition theory. Climate Services, 35, 100500.

https://doi.org/10.1016/j.cliser.2024.100500

  1. Shahabinejad, M., Yousefi, A. and Amini, A. (2015). Investigating the factors affecting farmers' willingness to participate in land consolidation projects in Meimeh district of Isfahan province, Journal of Applied Research in Geographical Sciences, 15(37), pp. 7-24. (In Persian)
  2. Sharifi, M. Sardarshahraki, A. Dadash, M. Asgari, M. (2019). Studying the process of agricultural land consolidation and its economic effects. Case study: Rice farmers in Guilan province. Journal of Agricultural Economics Research, 11 (1); 217-236. (In Persian)
  3. Shokati Amghani, M., Mojtahedi, M., & Savari, M. (2023). An economic effect assessment of extension services of agricultural extension model sites for the irrigated wheat production in Iran. Scientific Reports, 13(1), 16947. https://doi.org/10.1038/s41598-023-44290-5
  4. Si, H., Shi, J. G., Tang, D., Wen, S., Miao, W., & Duan, K. (2019). Application of the theory of planned behavior in Environmental Science: A comprehensive bibliometric analysis. International journal of environmental research and public health, 16(15), 2788. https://doi.org/10.3390/ijerph16152788
  5. 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
  6. Strydom, W. F. (2018). Applying the theory of planned behavior to recycling behavior in South Africa. Recycling, 3(3), 43.https://doi.org/10.3390/recycling3030043
  7. Tajeri Moghadam, M., Pouralimardan, S. and Raheli, H. (2016). Measuring farmers’ willingness to participate in the land consolidation plan in the central part of Arzoiyeh County, Kerman Province, Quarterly Journal of Rural Development Strategies, 3(2), pp. 255-265. (In Persian).
  8. Tong, W., Lo, K., & Zhang, P. (2020). Land consolidation in rural China: Life satisfaction among resettlers and its determinants. Land, 9(4), 118.

https://doi.org/10.3390/land9040118

  1. Tran, D., Vu, H. T., & Goto, D. (2022). Agricultural land consolidation, labor allocation and land productivity: A case study of plot exchange policy in Vietnam. Economic Analysis and Policy, 73, 455-473. https://doi.org/10.1016/j.eap.2021.11.017
  2. Ullah, S., Abid, A., Aslam, W., Noor, R. S., Waqas, M. M., and Gang, T. (2021). Predicting behavioral intention of rural inhabitants toward economic incentive for deforestation in Gilgit-Baltistan, Pakistan. Sustainability, 13(2), 617. https://doi.org/10.3390/su13020617
  3. 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
  4. Wang, W., Lan, Y., & Wang, X. (2021). Impact of livelihood capital endowment on poverty alleviation of households under rural land consolidation. Land Use Policy, 109, 105608. https://doi.org/10.1016/j.landusepol.2021.105608
  5. Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195. https://doi.org/10.2307/20650284
Land Management Journal
Volume 13, Issue 1
July 2025
Pages 43-58

Files

Share

How to cite

Statistics