Replication data for: Drivers and necessary conditions for chatbot acceptance in the insurance industry. Analysis of policyholders’ and professionals’ perspectives.

The adoption of conversational robots (chatbots) for customer service is
expanding across many industries. In the insurance sector, where customer
interactions are essential to the use of policies, understanding chatbot
acceptance is particularly relevant. This study explores the factors and conditions influencing the acceptance of chatbots for insurance policy management via the unified theory of acceptance and use of technology (UTAUT)
framework. The analysis is conducted on two groups: ordinary policyholders
and policyholders who are also industry professionals. The explanatory
factors evaluated are performance expectancy, effort expectancy, social
influence, and trust. The findings indicate that effort expectancy, social
influence, and trust positively impact the behavioral intention to use chatbots. Additionally, all the variables are found to be necessary for acceptance.
The structural equation model assessment reveals that professional status do
not moderate the relationships between explanatory variables and behavioral intention; however, professionals demonstrate a greater intention to
use chatbots. Among ordinary policyholders, effort expectancy has the largest effect size on acceptance. For professionals, trust and performance
expectancy are the most impactful explanatory variables, with very large
effect sizes. These results emphasize that while all variables are essential for
acceptance, the relative importance of each variable varies between policyholders and professionals, offering insights for implementing chatbot solutions effectively within the insurance sector.