Going Crazy for Reviewing: The Drivers Spreading e-WOM

Going Crazy for Reviewing: The Drivers Spreading e-WOM

Matteo Devigili, Tommaso Pucci, Niccolò Fiorini, Lorenzo Zanni
DOI: 10.4018/978-1-5225-8575-6.ch010
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Abstract

Word-of-mouth (WoM) has always exerted a great effect on consumers' behaviors and intentions. With the advent of internet, this influence has grown both in terms of potential audience reachable and of potential effect led to firms' sales and reputation. Hence, the marketing literature has recently started to investigate motivations and drivers able to foster/hinder electronic-WOM (e-WOM). Therefore, this research aims to explore the effect on the propensity to share comments and reviews online (active WOM) of the following three drivers: (1) propensity to rely on passive WOM; (2) expected service quality; (3) propensity to spend. The authors tested their hypotheses on the fashion industry, collecting 1454 usable answers from Italian consumers. The results indicate that both passive WOM and propensity to spend are drivers able to foster the spread of e-WOM. On the other hand, expected service quality shows a significant negative direct effect and a significant positive indirect effect on active e-WOM: these two effects compensate each other. Thus, the total effect is negligible.
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Introduction

Recent studies have highlighted the astonishing influence of reviews and comments on consumers’ intentions to purchase and repurchase (Eisingerich et al., 2014; Bigne et al., 2018). Indeed, 92% of consumers rely on recommendations from people they know more than any other form of advertising (Nielsen, 2012), thus crowning WoM the most valuable form of marketing (Whitler, 2014). WoM can be defined as “the communication between consumers about a product, service, or a company in which the sources are considered independent of commercial influence” (Litvin et al., 2008, p.459). It is the perceived independence that makes WoM more credible than any other traditional marketing leverage (Trusov et al., 2009). Additionally, 70% of consumers completely trust “opinions posted online”, more than newspapers, brand websites and so forth (Nielsen, 2012). Indeed, consumers trust online information exchanges because they perceived the information offered as timely, reliable and non-biased (Bigne et al., 2018). Therefore, given the astonishing potentiality the Internet and Social Media offers to organizations (Sogari et al, 2017; Dixit et al., 2019), the focus of the marketing literature has shifted towards eWoM defined as “any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the internet” (Henning-Thurau et al., 2004, p. 39). Compared to traditional WoM, eWoM show a peculiar feature: they can be accessed for an indefinite period of time (Khern-am-nuai et al., 2018). Additionally, eWoM are expected to have a larger effect than traditional WoM (Jeong and Jang, 2011), and to affect not only purchase intention (Yusuf et al., 2018), but also future consumers evaluation (Reimer and Benkenstein, 2016). For these reasons, both academicians and practitioners need to understand not only “ways to intervene in the generation of eWoM” (Dixit et al., 2019, p.112), but also the reason people share reviews and comments (see among the other: Litvin et al., 2008; Wu et al., 2016; Dixit et al., 2019). Indeed, previous research has highlighted self-enhancement (De Angelis et al., 2012), consumer power (Wu et al., 2016), problem-solving support and relaxation (Labsomboonsiri et al., 2017), the necessity to balance inequitable relationships (Belarmino and Koh, 2018), monetary incentives (Khern-am-nuai et al., 2018), and taking vengeance (Dixit et al., 2019) as possible underlying motivations. Although vast attention has been dedicated to understanding motivation behind consumers’ engagement with eWoM, much more research is still needed to deepen knowledge on drivers able to foster or hinder participation in online platforms (Labsomboonsiri et al., 2017). That is why, this research stream is still attracting many scholars (among which: Bigne et al., 2018; Khern-am-nuai et al., 2018; Saleem et al., 2018; Anastasiei and Dospinescu, 2019; Wang et al., 2019), requiring further investigation combining both functional/non-functional and offline/online drivers. Briefly, our research aims to investigate: (i) the relationship between passive WoM (read or heard) and active eWoM (propensity to write a review); (ii) the influence consumers’ expectations concerning service quality have on active eWoM; (iii) the influence the propensity to spend on a single purchase has on active eWoM. The research questions and hypotheses have been tested on a sample of 1454 Italian consumers in the fashion industry. Fashion and luxury are considered pillars of the Italian economy, generating a trade surplus of 18.4 billion dollars in 2012 (Fortis, 2016). In 2016, the Italian fashion industry produced a turnover of 66.1 billion euro, 4% of the national GDP (Micheli, 2018).

Key Terms in this Chapter

Discriminant Validity: It is the ability of a construct to differentiate from the others.

Fashion Industry: The fashion industry includes both apparel and accessories.

CB-SEM: A structural equation modeling based on the covariance matrix.

Structural Equation Modeling (SEM): It is a multivariate technique allowing to study relationships between variables and latent constructs, and between latent constructs.

High-Engagement: Refers to those products whose choice requires a high effort in terms of time and emotions for each phase of the purchase process.

Internal Reliability: It denotes the items’ ability to represent a latent construct.

Convergent Validity: It concerns the extent to which the items of a construct share variance.

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