Abstract
Identifying external information and factors that are likely to influence the selection of information to inform decision-making has become a critical issue for customers in the hospitality industry. It is well established that evaluation of information’s attributes in influencing customers’ decision-making provides essential guidance in developing marketing strategies. In the restaurant industry, which is perceived as one of the most competitive industries, there are two categories of information available on the Internet: marketer-generated content (MGC) and user-generated content (UGC). This study aims to investigate how visitors adopt online information from restaurant websites (i.e., MGC) and restaurant review websites (i.e., UGC) to inform their restaurant selection in a destination. In this study, UK visitors are given to be potential visitors for Thailand’s restaurant market because the number of British tourists has retained the top ranks of Thailand’s total tourists’ arrivals. They have been considered one of the largest spenders. Specifically, the study critically evaluates the information attributes of restaurant websites and review websites affecting British visitors in their restaurant selection in Thailand. Also, it develops a new model, which is named as Information Credibility Acceptance Model (ICAM), based on the Information Acceptance Model (IACM) The new model can assist in examining factors affecting information credibility and assessing information adoption from restaurant MGC and UGC sites that lead to behavioural intention.
To achieve the research goals, a sequential exploratory mixed method was adopted. In the qualitative stages, the eye-tracking technique and semi-structured interviews were conducted with 28 participants. The data were analysed using heat-map data and Thematic analysis to investigate the information attributes perceived attention, usefulness, credibility, and their antecedents. These antecedents of online information credibility on restaurant websites and restaurant review websites were used to inform the development of scales employed in the quantitative stage, along with literature sources. The questionnaire was administered an online to 617 respondents recruited from a crowdsourcing website, Amazon Mturk. Partial Least Squares SEM (PLS-SEM) was employed to analyse the data in this stage.
The present study makes several contributions as it employs an exploratory sequential mixed methods design, and a holistic approach looking at both UGC and MGC whereas previous research has been conducted intensively but has solely focused individually on UGC rather than investigating or comparing the influence of both UGC and MGC. Very little existing literature has been found examining information search behaviour on marketer-generated content. Thus, the study has developed and refined the theory of information search behaviour based on inductive (i.e., eye tracking and semi-structured interview) and deductive approaches (i.e., online survey). As such, it has contributed towards a deeper understanding of restaurant information search behaviour in a number of ways.