Determinants of future crop insurance purchase decisions among pepper growers in the South Hill Zone of Karnataka, India

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Type of the article: Research Article

Abstract
The Indian agricultural system is diverse, monsoon-dependent, and smallholder-driven. In this context, crop insurance is a suitable protective measure for farmers, though it has not been widely adopted. This study aims to examine the influence of demographic factors, economic factors, farm-related factors, risk perception factors, insurance-related factors, and institutional factors on future crop insurance purchase decisions among pepper-growing farmers in the south Hill Zone of Karnataka, India. To conduct an empirical investigation, a total of 407 samples were collected using a multistage sampling technique. Logistic regression models were employed to analyze the influence of the considered factors on farmers’ future crop insurance purchase decisions. The results show that all considered variables do not influence farmers’ future crop insurance purchase decisions except the Size of landholding (β = 0.3334, p = 0.034). Among the variables included in the model, size of landholding was the only variable that showed a statistically significant positive association with farmers’ future crop insurance purchase decisions. The findings imply that farmers’ future crop insurance purchase decisions are likely to be affected by structural and resource factors. To improve the effectiveness and inclusiveness of crop insurance, the government should strengthen the scheme with greater emphasis on supporting small and medium-sized landholders.

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    • Figure 1. The study area (South Hill Zone of Karnataka)
    • Figure 2. Classification matrix of the binary logistic regression model
    • Table 1. The results of the logit model
    • Table 2. Model diagnostic results
    • Table 3. Matrix of the binary logistic regression model
    • Table A1. Factors influencing crop insurance: impact of agricultural income and indemnity settlements on agricultural sustainability
    • Table A2. Influencing factors on crop insurance purchase decision in the future (using a five-point rating scale ranging from very strongly agree to strongly disagree)
    • Table A3. Respondents’ results
    • Formal Analysis
      Manukumari M. S., Abhilash Abhilash
    • Funding acquisition
      Manukumari M. S.
    • Investigation
      Manukumari M. S., Abhilash Abhilash
    • Project administration
      Manukumari M. S.
    • Resources
      Manukumari M. S., Veena Kumari B. K.
    • Supervision
      Manukumari M. S.
    • Validation
      Manukumari M. S., Veena Kumari B. K.
    • Visualization
      Manukumari M. S.
    • Writing – review & editing
      Manukumari M. S., Veena Kumari B. K., Abhilash Abhilash
    • Conceptualization
      Veena Kumari B. K.
    • Data curation
      Veena Kumari B. K.
    • Methodology
      Veena Kumari B. K., Abhilash Abhilash
    • Software
      Veena Kumari B. K., Abhilash Abhilash
    • Writing – original draft
      Veena Kumari B. K., Abhilash Abhilash