The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews

Park, Do-Hyung; Kim, Sara

doi:10.1016/j.elerap.2007.12.001

Cited by 646 publications

(455 citation statements)

References 38 publications

(21 reference statements)

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“…There is a general agreement that the message valence of eWOM plays a key role in determining eWOM effect (De Matos and Vargas 2008;Dellarocas and Narayan 2006;Lee et al 2008;Park and Kim 2008;Park and Lee 2009). Over the past years of research on eWOM, a number of issues have appeared; some of which remain controversial in spite of message valence of eWOM.…”

Section: Introductionmentioning

confidence: 99%

“…The mixed findings suggest that there is a need to further specify the situations in which eWOM valence will cause various effects. As product type and consumer knowledge have been found to greatly affect information search and information processing (Berger and Schwartz 2011;Dhar and Wertenbroch 2000;Klein 1998;Park and Kim 2008;Park and Lee 2009;Park et al 2007;Ratchford et al 2003), the present study hopes to gain a better understanding of how eWOM valence, product type, and consumer knowledge will co-work to generate eWOM richness perception. Thus, the objective of this study is to examine how eWOM message valence and product type will produce various levels of information richness when consumers exhibit different levels of product knowledge in the eWOM context.…”

Section: Introductionmentioning

confidence: 99%

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Education, Educational Services and their Quality

Dulaimi¹

2016

JMM

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Rich information facilitates consumer buying judgment and decision-making, and therefore enhances marketing communication effectiveness. Drawing on the information richness theory, this study attempts to address how valence of electronic word-of-mouth (eWOM), product type and consumer knowledge will yield different levels of eWOM richness perception for experience goods versus search goods. The results based on a three-way experimental study with 156 valid responses suggest that negative eWOM has a stronger effect in producing eWOM information richness than does positive eWOM, and such effect is more pronounced for a leisure farm tour (experience goods) than for digital camera (search goods). The tendency that negative eWOM will provide richer information for the leisure farm tour is more evident for high-knowledge consumers than for low-knowledge consumers. The study's results caution against the aggravated harm of negative eWOM incurred from the dissatisfactory experience of a leisure farm tour. The managerial implications for the practitioners are provided.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Education, Educational Services and their Quality

Dulaimi¹

2016

JMM

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“…website traffic, the rate and the valence of consumer reviews) (Zhu -Zhang 2010). On the other hand, individual-level analyses postulate eWOM as a process of personal influence, in which communications between a communicator (sender) and a receiver can influence consumer purchase decisions (Park -Kim 2008). In this respect, studies focus on the understanding of antecedents and consequences that determine WOM communications, along three research streams.…”

Section: Introductionmentioning

confidence: 99%

“…In the case of online WOM -because most of the time no direct face-to-face communications appear -opinions and referrals are unsolicited and will only be evaluated if it attracts the attention of prospective adopters and they find them (Park -Kim 2008).…”

Section: Introductionmentioning

confidence: 99%

Are opinion leaders more satisfied? Results of a SEM model about the relationship between opinion leadership and online customer satisfaction

Nagy

Kemény

Szűcs

et al. 2017

Soc Ec

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More and more research is dedicated to address the phenomenon of online word-of-mouth (WOM).Concerning electronic WOM, three major underlying motives can be differentiated: opinion seeking, opinion giving and opinion passing (Flynn et al. 1996, Sun et al. 2006. The main aim of the research is to analyse the relationship between these three dimensions and the level of customer satisfaction.The research is based on a representative sample of 1000 respondents living in Hungary. According to the hypothesized Structural Equation Model (SEM), we can conclude that online opinion seeking behaviour has a significant positive impact on levels of customer satisfaction, as well as on opinion giving and opinion passing. This implies that opinion leaders not just share, but also collect enormous amounts of information about products and services and raise their expectations according to feedback. By doing so, their prior expectations are in relation to the true customer value of online stores and products. This means that customer satisfaction -measured using the disconfirmation paradigm -will reach a higher level, so it is advisory for online retailers to encourage customers to give feedback, write reviews, because it will affect the customer satisfaction level in a positive manner.

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“…The results show good reviews and good business reputation has a positive effect on the increase in sales revenue of merchants. Park [2] (2008) studied the influence of the quality, direction and type of Internet word-of-mouth on the effectiveness of Internet word-of-mouth communication. From the perspective of customer awareness, Li Dongjun [3] proposed the interaction between word of mouth and customer perception from the perspective of customer awareness.…”

Section: Introductionmentioning

confidence: 99%

Research on Online Word-of-Mouth Spread Mechanism based on the Node Properties and Word-of-Mouth Type

Qian¹,

Zhao²,

Zhang³

2018

Proceedings of the 4th Annual International Conference on Management, Economics and Social Development (ICMESD 2018)

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Abstract. In this paper, we studied that how node properties and word-of-mouth type influenced the spread of word of mouth. First of all, according to previous research, we embedded all kinds of influencing factors like word-of-mouth type and customer recognition in the word-of-mouth spread model on the basis of SIR virus propagation model. Then, we made a simulation with the word-of-mouth model. According to the simulation, we could draw a graph of node density to examine how these factors affected the change of the node density, which reached a spread mechanism based on the principle and path of word-of-mouth spread. Finally, we give some practical proposals for enterprise marketing.

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The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews

Cited by 646 publications

References 38 publications

Education, Educational Services and their Quality

Education, Educational Services and their Quality

Are opinion leaders more satisfied? Results of a SEM model about the relationship between opinion leadership and online customer satisfaction

Research on Online Word-of-Mouth Spread Mechanism based on the Node Properties and Word-of-Mouth Type

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