Understanding Customer Satisfaction With Services by Leveraging Big Data: The Role of Services Attributes and Consumers’ Cultural Background

Abstract

User-generated content and online reviews (ORs) are becoming an increasingly relevant source of information for online customers who use them for purchasing decisions. This paper examines the impact of services attributes and consumers' cultural background on customer satisfaction with services in an online setting using big data. First, almost half a million expedia.com hotel ORs related to hotel properties located in five different countries (U.S., U.K., Italy, Spain, and Russia) were retrieved. Second, the resulting dataset was used to investigate if and to what extent the overall customer satisfaction with a service is affected by the evaluation of specific hotel services' attributes (operationalized based on an established typology of attributes) and by the consumers' cultural background (operationalized by means of Hoftstede's framework). Comprehensive multivariate regression analysis is carried out to test the formulated literaturedriven hypotheses. In particular, the analysis reveals that critical service attributes, such as hotel condition, room comfort, service and staff, and cleanliness, positively affect the overall online satisfaction ratings. The cultural dimensions of power distance, individualism, and uncertainty avoidance negatively affect the overall online satisfaction, while long-term orientation and indulgence positively affect online satisfaction. Masculinity seems not to play a significant role. We also observe that reviews' text length exerts a negative impact on online ratings. Theoretical and practical implications are discussed.INDEX TERMS Big data, online reviews, online rating, expedia.com, hotel, cultural differences.

Online Review Helpfulness and Firms’ Financial Performance: An Empirical Study in a Service Industry

“…Further research might look at budget hotels (such as one-star and two-star) as well, provided that good quality financial data will become available. Fifth, our study did not control for reviewer-level factors such as reviewers' cultural background [100] and submission device used for the review [99]: these factors might be taken into account in future studies to understand if and to what extent they drive online reviewing behavior and ultimately eWOM and performance. Last, our study focuses on a single destination that, though relevant from a national and international point of view, is not necessarily representative of hotel populations in other destinations.…”

Does cultural distance affect online review ratings? Measuring international customers’ satisfaction with services leveraging digital platforms and big data

“…In hospitality marketing literature, only a handful of studies have analysed the role of national culture on eWOM in online settings (e.g. Mariani et al 2019b;Mariani and Predvoditeleva 2019). All these studies embrace a "direct measurement approach" (Huang and Crotts 2019) to the examination of cultural factors on consumer behavior.…”

“…Until now, researchers have disregarded the role of cultural factors in the online assessment of hospitality services, with the exception of a few studies (e.g. Gao et al 2018;Mariani et al 2019b;Mariani and Predvoditeleva 2019). For instance, Gao et al (2018) examine the association of power distance with online review ratings and find that the higher the power distance of the online customer, the lower the online ratings.…”

“…The online review data of Booking.com was retrieved by the researchers via big data stemming from online reviews, to generate big data analytics (Davenport 2017; Mariani 2019; Mariani and Fosso Wamba 2020) to shed light on consumers' online evaluations of the main hospitality services. Being a popular e-commerce platform for hospitality services, Booking.com encompasses the highest share of certified online reviews globally (Mariani et al 2019b) and has been identified in previous research as an appropriate data source (as well as Expedia.com) for eWOM research in hospitality (e.g. Gao et al 2018;Mariani and Borghi 2018).…”

Big Data and analytics in tourism and hospitality: a perspective article

“…For instance, tourists' location data tracked by means of GPS sensors embedded in smartphones can provide destination marketers with meaningful insights about the most popular routes and attractions in a destination; when matched with social media data, location data allow marketing firms to create location-specific offers based on the preferences and behaviors that the consumer has revealed on social media in the past, thus allowing businesses to interact in real time with potential customers based on the opinions and actions that they share and on the history of their preferences and tastes. Furthermore, Online Travel Agencies (OTAs) can leverage on large volumes of structured and unstructured data stemming from online travel reviews to better understand tourists' online behaviours by means of digital data analytics (Mariani, Di Fatta and Di Felice, 2019). This work looks retrospectively at the way this overabundance of travel and tourism related data, namely Big Data (BD), has been made sense of, and examined in T&H literature and illustrates future research directions.…”