Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences

Sun, Tao; Youn, Seounmi; Wu, Guohua; Kuntaraporn, Mana

doi:10.1111/j.1083-6101.2006.00310.x

Cited by 486 publications

(398 citation statements)

References 57 publications

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“…There is consensus in the literature that negative O-WOM is an influential behavioral determinant (Brown et al, 2007;Sun, 2006). Due to the spread and adoption of new consumer-empowering technologies such as social media and mobile devices complaints and dissatisfied experiences can be communicated and distributed instantly within a huge network of other consumers (Van Noort & Willemsen, 2011).…”

Section: Negative O-wommentioning

confidence: 99%

Negative online word-of-mouth: Behavioral indicator or emotional release?

Verhagen

Nauta

Feldberg

2013

Computers in Human Behavior

169

125

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The influence of negative online word-of-mouth on the behavior of those receiving it has been addressed extensively in the academic literature. Remarkably, the question whether negative online word-of-mouth should also be seen as a behavioral indicator of its sender remains unaddressed. Answering this question is relevant as it provides companies with insight into the need to engage in interaction with those who negatively express themselves online or whether these expressions should be seen as temporary emotional releases without any future conduct. To fill the existing research gap, this research paper proposes and empirically tests a sender-oriented model, investigating the influence of emotions, negative online word-of-mouth on repatronage and switching behavior. As disclosing negative feedback online may also reflect the sender's motivation to inform the consumer community or to provide constructive feedback to the company responsible for the dissatisfying consumption, community usefulness and company usefulness are included as behavioral moderators. The results of an empirical survey conducted amongst real senders of negative information confirm that negative online word-of-mouth is directly driven by positive and negative emotions and is strongly predictive for the sender's future conduct. The motivation to help other consumers was demonstrated to function as behavioral moderator. The paper concludes with theoretical and managerial implications, and suggests avenues for further research.

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Section: Negative O-wommentioning

confidence: 99%

Negative online word-of-mouth: Behavioral indicator or emotional release?

Verhagen

Nauta

Feldberg

2013

Computers in Human Behavior

169

125

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“…Another distinctive characteristic of online communications is the asynchronicity (Henderson and Gilding 2004;Hung and Li 2007), which makes it easier for consumers to obtain information at their convenience (Sun et al 2006). Another advantage of E-WOM communications is that most of it is archived and available in the future (Hennig-Thurau et al 2004;Herr, Kardes, and Kim 1991;Hung and Li 2007).…”

Section: Electronic Word Of Mouthmentioning

confidence: 99%

Investigating E-Servicescape, Trust, E-WOM, and Customer Loyalty

Tran

Strutton

2016

Celebrating America’s Pastimes: Baseball, Hot Dogs, Apple Pie and Marketing?

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titles.Old Spice cleverly used a handsome actor to play the Old Spice Man character for a Super Bowl commercial in 2010. After the game, this Old Spice commercial was viewed more than 13 million times on YouTube, a social media video-sharing site. This viral marketing campaign, also known as electronic word-of-mouth (E-WOM), propelled the Old Spice brand into the forefront of consumers' minds, increased brand awareness, and inspired people to share the video links with their family, friends, and co-workers.The rapid growth of E-WOM is an indication of consumers' increased willingness to convey marketing messages to others. However, despite this development, marketing academics and practitioners do not fully understand this powerful form of marketing. This dissertation enriches our understanding of E-WOM and how e-servicescape may lead to E-WOM. To that end, stimulus-organism-response theory and the network co-production model of E-WOM are applied to investigate the relationships between e-servicescape, trust, E-WOM intentions, customer loyalty, and purchase intentions. Two forms of E-WOM were examined, namely emails and social network postings. E-servicescape is defined as the online environmental factors of a marketer's website. E-servicescape is composed of three main dimensions, including aesthetic appeal, financial security, and layout and functionality. This study used cross-sectional customer data from a single e-tailer. Structural equation modeling was used to analyze the responses. Customer reviews was added as an additional subdimension of e-servicescape. The findings suggest e-servicescape positively impacts trust, which in turn positively influences E-WOM and customer loyalty. Moreover, two groups of customers were compared using multi-group analysis, where one group of users received emails and the other group received social network postings from the same e-tailer. Overall, the results indicated emails had a stronger impact on e-servicescape, E-WOM, and customer loyalty. Social networking site postings had slightly greater influence on trust, and two sub-dimensions of eservicescape, i.e., interactivity and ease of payment.These findings contribute to the marketing research on E-WOM theory and electronic commerce shopping behavior. In particular, the sub-dimension of customer reviews is added to e-servicescape. This study yields practical implications for marketers in understanding consumers' perceptions of websites and how to better design sites. In addition, these findings add to knowledge on how to engender consumers' trust and customer loyalty online. Finally, this research provides suggestions for firms wanting to create marketing campaigns that will lead to E-WOM. Overview of E-WOM E-WOM is defined as "forwarding actions through email, instant messaging or other communication media that are of high 'addressability'" (Ho and Dempsey 2010, p. 1000). E-WOM communication is traditional word-of-mouth (WOM) behavior evolved and adapted to electronic media, where individuals often convey messages in...

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“…Furthermore, by using search engines, customers can seek out the opinions of strangers. This rarely occurs in classic WOM contexts where opinion providers are embedded in social networks, and well-known people might be more credible (Sun et al 2006). Another important attribute of an eWOM is its speed, accessibility, oneto-many reach and its lack of face-to-face human pressure (Phelps et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail

Olmedilla

Torres

Toral

2015

Technology Analysis & Strategic Management

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Nowadays electronic word-of-mouth (eWOM) communities symbolise a significant source of information that helps customers to make informed purchasing decisions. Through eWOM communities, a great audience of users is able to acquire knowledge from reviews concerning products and services that are less popular to the majority. The Long Tail effect is a manifestation of such redistribution of demand from popular products to niche products. In this paper, a new methodology that mathematically fits the relationship between the power-law distribution and the Long Tail from an eWOM community is developed. In addition, this paper defines a tool for finding niche products inaccessible through conventional channels. The results are consistent in showing that not all the categories fitting a power-law distribution are characterised by the Long Tail phenomenon, and conversely some of those having a Long Tail do not fit a power-law distribution.ARTICLE HISTORY

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Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences

Cited by 486 publications

References 57 publications

Negative online word-of-mouth: Behavioral indicator or emotional release?

Negative online word-of-mouth: Behavioral indicator or emotional release?

Investigating E-Servicescape, Trust, E-WOM, and Customer Loyalty

Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail

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