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This paper presents the systematic process framework to develop the suitable crop insurance for each agriculture farming region which has individual differences of associated crop, climate condition, including applicable technology to be implemented in crop insurance practice. This paper also studies the adoption of new insurance scheme to assess the willingness to join crop insurance program.

Crop insurance development has been performed through IDDI conceptual framework to illustrate the specific crop insurance diagram. Area-yield insurance as a type of index-based insurance advantages on reducing basis risk, adverse selection and moral hazard. This paper therefore aims to develop area-yield crop insurance, at a provincial level, focusing on rice insurance scheme for the protection of flood. The diagram demonstrates the structure of area-yield rice insurance associates with selected machine learning algorithm to evaluate indemnity payment and premium assessment applicable for Jasmine 105 rice farming in Ubon Ratchathani province. Technology acceptance model (TAM) is used for new insurance adoption testing.

The framework produces the visibly informative structure of crop insurance. Random Forest is the algorithm that gives high accuracy for specific collected data for rice farming in Ubon Ratchathani province to evaluate the rice production to calculate an indemnity payment. TAM shows that the level of adoption is high.

This paper originates the framework to generate the viable crop insurance that suitable to individual farming and contributes the idea of technology implementation in the new service of crop insurance scheme.

The purpose of this paper is to explore the adoption of a mobile insurance claim system (M-insurance) and develops a framework for the adoption of M-insurance by consumers.

This study assesses mobile technology for claim management through the lens of the technology acceptance model (TAM) and diffusion of innovation (DOI) models as a major guideline, using exploratory research through in-depth interviews with four executive experts who are first movers in mobile claim motor insurance in Thailand. Semi-structured interviews and open-ended questions were used to conduct group interviews of insurance consumers who mostly use smartphones. The data were collected in a qualitative research approach from Thai insurance consumers (n=177), and contents were classified and analysed to gain strong insights into respondent opinions, comments, attitudes, behaviour, and experiences.

The results indicate that the external (social) factors influence attitude and behaviour of consumers which link to their intention to adopt M-insurance. These external factors include: preference for face-to-face service; confidence of insurers in accepting claim; and risk of claim knowledge that might cause legal issues among others. In application, the findings shall meaningfully enhance insurer firms’ improvement of adoption rate and development of future features and functions of M-insurance.

This study is based on insurance consumers in each region of Thailand but focuses only on mobile claim management for motor insurance. Although the findings bring new insight and understanding of consumer preferences and behaviours, they were not tested statistically.

The study has practical implications for motor insurance claimants who are concerned over the complicated policy conditions, the perspective risk of claim knowledge and fault admission, and the on-site investigation by surveyor for another party. These are the guidance impediments to overcome M-insurance adoption improvement.

Previously, TAM and DOI approaches have been employed to study general adoption of M-banking by quantitative research which confirmed descriptive data and tested the hypothesis, but neglected crucial data. However, M-insurance is different from M-banking in term of features and functions, purpose and process of usage, and legal liability. Therefore, this study is one of a few empirical studies that attempt to identify insightful factors to consumer uptake of M-insurance which is in its early stage and lacks an underpinning TAM model. This study contributes by identifying insights of “pull” factors to successfully develop M-insurance in Thailand.

The purpose of this paper is to investigate the role that weather shocks can play in the livestock mortality microinsurance take-up when the insured risk has a prevalent covariant component.

The sample consists of 360 rural Ethiopian households. Data were collected in a panel-structure at the end of three agricultural seasons (2011-2013). In the questionnaire, a specific section on insurance was meant to collect information on the farmer’s willingness-to-pay (WTP) for a set of insurance products, including livestock mortality insurance. Two OLS regression models and a quantile regression model were employed to estimate the impact of weather anomalies on the WTP for the insurance product.

The authors find that weather anomalies contribute to changes in the WTP to a large extent. Negative (positive) changes in precipitation (temperature) anomalies can lead to more than a 30 percent reduction in the WTP. This general finding is complemented with the analysis of the conditional distribution of the WTP, which shows that other elements can prevail for low values of the conditional distribution. In this case, the WTP seems to be represented more by the interviewee’s age and basic knowledge of insurance, and village fixed-effects. Basic knowledge of insurance, in particular, can increase WTP by about 60 percent.

This paper has straightforward implications from a policy perspective. It suggests that farmers would prefer an insurance premium that follows the changes in the systemic component. On the contrary, insurance as well as reinsurance companies are usually reluctant to frequently revise their premiums. Financial education programs, farmer-driven design, trust building, and bundling insurance with other financial and non-financial products can increase the value proposition perceived by the farmers. From a marketing perspective, the overall findings suggest that continuous fine-tuning of the contract, transparency, and targeted information campaigns can contribute to increase and stabilize potential customers’ WTP.

To the best of the authors’ knowledge, this is the first paper that considers the impact of weather shocks on the WTP for a livestock mortality insurance product. Livestock is one of the most strategic assets of poor rural households in Africa. This study contributes to the theoretical and empirical literature on the determinants of weather insurance take-up in developing countries and, in particular, the role of spatiotemporal adverse selection and basis risk (e.g. Jensen et al., 2016).