“Seeing through consumers’ eyes”: exploring online restaurant selection behaviors using eye-tracking technology

Abstract

With the advancement of the Internet and information technology, consumers have access to a massive amount of information before purchase. In the hospitality industry, consumers frequently search online information to make decisions. However, there has been limited hospitality research exploring the actual information search behaviors in the online setting. The purpose of this research was to assess the actual information search behaviors of consumers when choosing restaurants through consumer review websites. To accomplish the purpose, three mixed-methods were used including eye-tracking experiments (Phase I), qualitative, retrospective think-aloud (RTA) interviews (Phase II), and a scenario-based survey (Phase III). In the eye-tracking experiments, 30 participants were recruited and instructed to conduct restaurant search tasks. Variables included fixation duration, fixation count, and visit count, indicating how long and how often consumers’ attention had been attracted to certain information areas. The eye-tracking data was also visualized through heat maps and gaze plots. Following eye-tracking experiments, RTA interviews were conducted to investigate the underlying thinking process of consumers. A playback of the recorded eye-tracking video was presented to each participant while participants verbalized their thinking process and reasoning of information search behaviors. The interviews were recorded, transcribed, and analyzed through grounded-theory model to identify important information elements. To overcome the limited generalizability of the eye-tracking experiments and interviews, a scenario-based survey was created, and seven hypotheses were developed to evaluate impacts of online reviews, images, and advertisements on consumers’ interests and restaurant visit intentions based on the results of Phases I and II. Restaurant selection scenarios were provided to the participants to look through screenshots of webpages in order to mimic the online environment. The online survey company Amazon MTurk was used for data collection. A total of 406 usable survey responses were collected and analyzed using descriptive statistics, one-sample Chi-square tests, and visualized heat maps. Eye-tracking experiment results revealed that images, consumer reviews, and filter functions were the top information areas to which consumers paid considerable attention. Advertisements in Yelp also received much attention from participants, but during RTA interviews, advertisements were found to be less impactful for consumers’ decision-making than the number of reviews, images with food items, and consumer reviews. Five out of seven hypotheses in Phase III were supported, indicating that it was mostly consistent with findings of the eye-tracking experiments and interviews (Phase I and II). Specifically, consumers’ interests and intentions to visit restaurants were greater for restaurants with a higher number of reviews, food images, and without advertisements. Consumers also were more interested in extremely rated reviews and preferred evenly-distributed image groups. This study contributes to the existing hospitality literature related to consumer behavior with the utilization of the innovative, combined methods of eye-tracking technology, RTA interviews, and scenario-based survey. This approach allowed the researcher to obtain a holistic view of actual consumer behavior, thinking process accompanying the behavior as well as the verification with large sample. Consumer review websites and restaurateurs were provided with specific recommendations to enhance the online user experience and improve customer satisfaction, respectively.