Factors Affecting the Willing to Join in Coffee Crop Insurance in Dak Lak Province, Vietnam: A Novel Application of Bayesian Model Averaging Approach

Abstract

Purpose of the study: this paper aims to determine factors affecting the willingness to join crop insurance. Besides, this paper is the purpose of developing a coffee tree insurance program.
 Methodology: The authors used a systematic random sampling technique. The authors used the Bayesian Model Average (BMA) that calculated the probability of all independent variables affecting the dependent variable with significance level 0.05. Besides, the data based on 480 coffee farmers in Dak Lak province, Vietnam.
 Main Findings: Authors calculated the probability of all independent variables affecting the dependent variable with significance level 0.05. Independent variables, including loans, drought risks, educational level, experiences, and productivity.
 Applications of this study: This result is a vital science document for insurance companies and managers to apply and suggest recommendations for developing coffee tree insurance in the future.
 Novelty/Originality of this study: Vietnam is an agricultural country, 60-70% of the population lives in rural areas, and agricultural insurance should have a considerable market. Farmers’ agrarian insurance cultivated the coffee trees that are currently underdeveloped and challenging.