Do Hotel Responses Matter?: A Comprehensive Perspective on Investigating Online Reviews

Do Hotel Responses Matter?: A Comprehensive Perspective on Investigating Online Reviews

Wenlong Liu (Nanjing University of Aeronautics and Astronautics, China) and Rongrong Ji (Nanjing University of Aeronautics and Astronautics, China)
Copyright: © 2019 |Pages: 20
DOI: 10.4018/IRMJ.2019070104
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Abstract

This article aims to examine how hotel responses to online reviews influence how potential consumers perceived the helpfulness of the online reviews. Response length and voice were employed to measure the hotel's response quality. 637 reviews with responses were used for empirical analysis. The study identified three different types of response voices: disputed voice, professional voice, and empathetic voice. The results show that both response length and response voice have significant effects on the helpfulness perceived by potential consumers. Moreover, they also have some interaction effects with star ratings, review length, and review image. This study suggests that hotels should strategically respond to both positive and negative online reviews so as to both create a positive interaction atmosphere and resolve consumer complaints. The findings of this study can, to some extent, help manage word of mouth reputations.
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Introduction

Research Background

Marketing studies have long shown that word of mouth (WOM) can influence consumers’ decision-making in purchasing (Kim & Kardes, 1992). With the development of information technology and easy access to the internet, consumers’ face-to-face or offline communication has been replaced by multiform electronic-word-of-mouth (eWOM).

According to Hu and Chen (2016), eWOM is defined as “all informal communications directed at consumers through Internet-based technology related to the usage or characteristics of particular goods and service, or their sellers.” In shaping consumer behavior and influencing their purchase decision, online reviews are the most influential eWOM (Hu & Chen, 2016). Online review is a type of product information generated by consumers based on their personal experience (Purnawirawan, Pelsmacker, & Dens, 2012). According to a survey named ‘Global Trust in Advertising’ released by AC Nielsen in 2015, about 83% respondents say they completely or somewhat trust the recommendations of friends and family while 66% say they trust consumer opinions posted online, which is the third-most-trusted format. Consumers regard the information provided by the merchant as the means to promote their products while believing that online review is deserved to be trusted as it is provided by customers who have consumed the product or service, and it is independent of merchant’s marketing action (Lu et al., 2013). This phenomenon is obvious especially in experimental product or service, such as the hospitality industry. It is hard for consumers to not know about the environment, establishment, service or other information indeed or in the round until they arrive at the hotel they booked. In this case, they tend to turn to the online reviews for help. There are amounts of important information contained in online reviews which may reduce the degree of perceived uncertainty between merchants and consumers (Shan, 2016).

The popularity of online reviews makes many researchers pay attention to this subject. Previous studies have focused mainly on two main perspectives, merchants, and consumers. From merchants’ perspective, studies center on product sales or revenues (e.g., Duverger, 2013; Cui, Lui, & Guo, 2012; Zhu & Zhang, 2010; Ogut & Tas, 2011; Ghose & Ipeirotis, 2011), product types (e.g., Lee & Shin, 2014; Chua & Banerjee, 2016), brand reputation (Marchiori & Cantoni, 2012) and marketing strategies (e.g., Lu et al., 2013; Nieto, Hemandezmaestro, & Munozgallego, 2014) while from the consumers’ perspective, studies focus on consumer’s behavior, including information adoption (e.g., Filieri & Mcleay, 2013; Lee & Yang, 2015), purchase intentions (e.g., Jimenez & Mendoza, 2013; Zhao, Wang, & Guo, 2015; Sparks, So, & Bradley, 2011) and decision-making (e.g., Zhang et al., 2014).

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