Are Online Reviews Helpful for Consumers?: Big Data Evidence From Services Industry

Introduction

The advent of online communication channels, such as web-based opinion platforms, has led to marketers increasingly focusing their attention on electronic word of mouth (eWOM) (e.g. Liu et al. 2018, Roy et al. 2018, Chevalier & Mayzlin, 2006; Hennig-Thurau, Gwinner, Walsh, & Gremler, 2004). eWOM has been defined as “any positive or negative statement made by potential, actual or former customers about a product or company […] made available to a multitude of people and institutions via the internet” (Hennig-Thurau et al., 2004, p. 39). Filieri and McLaey (2014) suggested that, given that reviews consist of “comments published by travelers on the tourism products, services and brands they experience” (p. 1), online reviews are an example of eWOM.

It is difficult to evaluate the products and services within the tourism and hospitality domain, because they are mainly intangible goods. Consequently, consumers’ online reviews play a critical role (Del Chiappa et al., 2018, Schuckert et al., 2015; Liu and Park, 2015) and have important consequences from a managerial viewpoint. When communicating the company’s products and services, customers become “objective voices” (Vermeulen and Seegers, 2009), with more than 75% of consumers taking peer reviews into account when planning a holiday (Xie et al., 2014). Peers’ feedbacks are, in fact, perceived as more trustworthy and credible than company-generated information (Filieri et al., 2015; Park, Lee and Han, 2007), which is one of the major reasons why potential customers read online reviews to inform their decision-making processes (Zhu & Zhang, 2010).

Reviews’ usefulness can facilitate consumers’ decision-making and is therefore important (Lee, 2013). This metric, which is available on the majority of online platforms such as Tripadvisor, suggests how many times others have marked a review as useful. Previous research has investigated the determinants of usefulness by focusing, for instance, on the score rating, the reviewer’s background, and the service providers’ response (Filieri et al., 2018).

Nevertheless, which of reviews’ linguistic attributes stimulate consumers to mark them as useful? And, is there a connection between the language used in the reviews and their usefulness perception?

We analyze a sample of Tripadvisor reviews by means of automated text analysis and linguistic analysis to answer these questions. Identifying the factors affecting perceived usefulness − measured as the number of helpful votes that a review received − is indeed crucial in the tourism and hospitality domain, as well as in marketing. These votes allow online platforms to provide travelers and consumers with greater value and to assist their decision-making processes (Sussman & Siegal, 2003).