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Home▶ Journals▶ Indian Journal of Extension Education▶Archive▶Vol. 61 No. 4 (2025)▶Modeling of Farmers’ Preferences towards Climate-Smart…
Indian Journal of Extension Education
Research Article

Modeling of Farmers’ Preferences towards Climate-Smart Agriculture Using Conjoint Analysis

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Bhartendu Yadav — Assistant Professor, Department of Agricultural Economics and Extension, Lovely Professional University, Phagwara-144411, Punjab, India
Bhavesh — Ph.D. Scholar, Western Sydney University, Australia
Abhilash Singh Maurya — Subject Matter Specialist (Agricultural Extension), Krishi Vigyan Kendra, Raebareli-II (Palti Khera), Uttar Pradesh, India
Sarju Narain — Associate Professor, Department of Agricultural Extension, BNPG College, Rath, Hamirpur-210431, Uttar Pradesh, India
Joginder Singh Malik — Professor, Department of Agricultural Extension Education, CCS HAU, Hisar-125004, Haryana, India
Published 3 Oct 2025 Vol. 61 No. 4 (2025), pp. 106-111 ● Open access
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Abstract

Climate change poses a significant threat to agricultural productivity, particularly for smallholder farmers in India. The study utilized a mixed-method approach, which involved 150 farmers and expert consultations from Punjab and Uttar Pradesh states related to the domain in the year 2024-25. Farmers’ preferences were studied using CSA attributes: productivity, adaptation, and mitigation, deploying the conjoint analysis. It was found that the farmers are continuously affected by the dynamic weather conditions, causing irregular rainfall to impact crop health and eventually crop yield. Although awareness related to CSA was present but its adoption was very low due to the absence of infrastructure and technology. A gap was found between the recommendation of the experts related to integrated and efficient nutrient management and the farmers’ adoption level. As a result of the conjoint analysis, it was found that the adaptation attribute was highly favoured by the farmers, followed by the other two, i.e., mitigation and productivity. The reliability of the model was supported by Pearson’s R (0.934) and Kendall’s tau (0.856), which revealed a strong connection between the prediction and the actual preferences. 

 

KeywordsConjoint analysisFarmer’s preferencesClimate smart agriculture (CSA)AdaptationSustainable agriculture.

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