The Study of The Relationships Among Word of Mouth, Trust and Technology Acceptance Model (TAM) In Consumers’ Intention to Purchase Insurance Online

  • นิลเนตร แก้วโรจน์
Keywords: technology acceptance model, behavioral intentions, online insurance

Abstract

The objectives of this study were 1) to examine the integrated model designed to predict factors such as the perceived ease of use, perceived usefulness, attitudes towards using, word of mouth, and trust that influence online insurance purchase intentions. 2) to study the causal relationships between perceived ease of online insurance purchase and word of mouth on online insurance towards behavioral intentions in online insurance purchase with perceived usefulness of online insurance purchase, attitude towards insurance purchase, and trust in insurance purchase as mediator variables. Through convenience sampling method, data was collected from 380 samples with previous purchase experience of any insurance policies in Bangkok to be used for an analysis of descriptive statistics. The processing framework to evaluate the significance of the relationships amongst the variables involves Structural Equation Model (SEM) analyzed by Partial Least Square with M-Plus Program. The results indicated that most of them are male of 31 - 40 years of age, married status, bachelor's degree of highest education level, private business owners and company employees, and with average monthly income of Baht 15,000 - 35,000. The structural equation model that represents the relationship between those variables in the model were found to be consistent with empirical data. The influence of various variables in the model can be explained with influence coefficients of statistically significant level 0.05 on all paths. The hypothesis test results by structural equation model analysis concluded that the relationship between variables were in accordance with the conceptual framework. Therefore, the results from this research can be used to plan and develop marketing strategies with target customers who are likely to purchase insurance online.

Published
2020-01-30