Identifying consumers' information adoption criteria on various online consumer review platforms: a case of Thai hospitality factor

Abstract

The dynamics of use and adoption of information on various online review platforms remain elusive and complex, indicating the importance of more research on electronic word of mouth (eWOM) and online consumer reviews (OCRs). Existing theoretical models do not fully explicate the role of the influential factors and their interrelations in information adoption. This research offers a more holistic model of information adoption. The Information Adoption Model (IAM) and the Elaboration Likelihood Model (ELM) are utilised as the theoretical foundations for the conceptual model while examining the factors that influence consumers’ perceptions of and information adoption decisions from Independent and E-merchants’ websites. Information usefulness is employed as a mediator. This research examines various COPs (consumer opinion platforms) by categorising consumers into four groups on the basis of their engagement behaviour and investigating their information adoption decisions. The research undertook quantitative methodology and conducted a survey on 635 respondents from Thailand. All hypotheses were developed and tested using data collected via an online questionnaire and were analysed with Structural Equation Modelling (SEM), with multigroup analysis techniques. Additionally, the research used two step cluster analysis and identified four groups of consumers on the basis of their engagement behaviour Quicker, Explorer, Confidant and Passionate. The findings are 1) A positively significant relationship between information usefulness and information adoption has been approved 2) Consumer adopt different information adoption criteria for different types of COPs 3) Consumers’ assessment of different factors of OCRs varies due to the difference in the level of online engagement. The results offer useful implications for marketers by identifying and analysing the criteria that consumers adopt from specific platforms and underlining the effect of the level of consumer engagement on information adoption of OCRs.