Evaluación de los robots conversacionales en la comunicación asegurado-asegurador en el mercado español con un modelo de aceptación tecnológica

Jorge de Andres Sanchez; Jaume Gene-Albesa; Laura González-Vila Puchades

doi:10.26360/2023_6

Authors

Jorge de Andres Sanchez Universidad Rovira i Virgili https://orcid.org/0000-0002-7715-779X
Jaume Gene-Albesa Universitat Rovira i Virgili https://orcid.org/0000-0001-7156-8304
Laura González-Vila Puchades Universidad de Barcelona https://orcid.org/0000-0003-4824-5894

DOI:

https://doi.org/10.26360/2023_6

Keywords:

Insurtech, conversational bots, Technology Acceptance Model, insurance procedures, structural equation modelling

Abstract

This paper analyzes the perception of 63 professionals in the insurance industry regarding the usefulness of conversational robots (chatbots) in customer interactions with insurers regarding current policies. To explain this perception, a Technology Acceptance Model (TAM) is used that includes perceived usefulness, ease of use, and confidence in chatbots as variables. In addition, two open-ended questions are used to explore the advantages and disadvantages of using this technology. Thus, a quantitative analysis is carried out using a Structural Equation Model estimated by Partial Least Squares (PLS-SEM), and a Qualitative Analysis of the open-ended responses.

The results of the PLS-SEM analysis show a good fit of the TAM to the survey used in the research, and reveal a significant direct influence of perceived usefulness on the acceptance of conversational bots, as well as a significant impact of ease of use and confidence, but mediated by perceived usefulness. Overall, the attitude of the respondents towards conversational robots is negative. Various reasons were identified related to difficulty in interacting with them, the need to resort to the help of a human operator, the lack of emotional skills such as empathy, concern about job destruction, low reliability, and a lack of perceived advantages in terms of the impact of reducing administrative costs on product improvements.

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