%0 Journal Article
%T Exploring Big Data Applied in the Hotel Guest Experience
%A Chieh-Heng Ko
%J Open Access Library Journal
%V 5
%N 10
%P 1-17
%@ 2333-9721
%D 2018
%I Open Access Library
%R 10.4236/oalib.1104877
%X <div style="text-align:justify;">
	<span style="line-height:1.5;">The tremendous growth of
social media and consumer-generated content on the Internet has inspired the
development of the so-called big data analytics to understand and solve
real-life problems. However, while a handful of studies have employed new data
sources to tackle important research problems in hospitality, there has not
been a systematic application of big data analytic techniques in these studies.
This study aims to explore and demonstrate the utility of big data analytics to
better understand important hospitality issues, namely the relationship between
hotel guest experience and satisfaction. Specifically, this stu</span><span style="line-height:1.5;">dy applies a
text analytical approach to a large quantity of consumer reviews extracted from
Expedia.com to deconstruct hotel guest experience and examine its association
with satisfaction ratings. The findings reveal several dimensions of guest
experience that carried varying weights and, more importantly, have novel,
meaningful semantic compositions. The association between guest experience and
satisfaction appears strong, suggesting that these two domains of consumer
behavior are inherently connected. This study reveals that big data analytics
can generate new insights into variables that have been extensively studied in
existing hospitality literature. In addition, implications for theory and
practice as well as directions for future research are discussed.</span>
</div>
%K Big Data
%K Text Analytics
%K Guest Experience
%K Hotel Management
%U http://www.oalib.com/paper/5299635