The tremendous growth ofsocial media and consumer-generated content on the Internet has inspired thedevelopment of the so-called big data analytics to understand and solvereal-life problems. However, while a handful of studies have employed new datasources to tackle important research problems in hospitality, there has notbeen a systematic application of big data analytic techniques in these studies.This study aims to explore and demonstrate the utility of big data analytics tobetter understand important hospitality issues, namely the relationship betweenhotel guest experience and satisfaction. Specifically, this stu,dy applies atext analytical approach to a large quantity of consumer reviews extracted fromExpedia.com to deconstruct hotel guest experience and examine its associationwith satisfaction ratings. The findings reveal several dimensions of guestexperience that carried varying weights and, more importantly, have novel,meaningful semantic compositions. The association between guest experience andsatisfaction appears strong, suggesting that these two domains of consumerbehavior are inherently connected. This study reveals that big data analyticscan generate new insights into variables that have been extensively studied inexisting hospitality literature. In addition, implications for theory andpractice as well as directions for future research are discussed.
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