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35Copyright © 2021 by Cherkas Global University
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Published in the the USA
International Journal of Media and Information Literacy Has been issued since 2016. E-ISSN: 2500-106X 2021. 6(2): 453-463
DOI: 10.13187/ijmil.2021.2.453 https://ijmil.cherkasgu.press
Towards an Integrated Model of Electronic Word of Mouth Communication
Safeena Yaseen a, Ibtesam Mazahir a, Jeyasushma Veeriah b, Iqra Iqbal c , *
a Bahria University, Pakistan b Xiamen University Malaysia, Malaysia c University of Central Punjab, Pakistan
Abstract
The term electronic word of mouth has witnessed a constant evolution due to the technological advancements and increased internet mediated consumer conversations. The topic has become a subject of interest for both business professionals and academic scholars with its growing importance in business research. Past studies mostly discussed the dynamic nature of eWOM under the strong influence of emerging concepts and technological innovations. However, very few research studies have viewed its extensive evolution in the context of a basic model of communication. In this research paper, a theoretical review was conducted to systematically organize the literature findings to develop an eWOM communication model. From participants' classification and motivation to generate eWOM to its influence on receivers, the model elaborates all the basic elements of communication process which also include content type and transmitting platform. This paper significantly contributes to elaborate the basic eWOM communication process by the extensive analyzation of the existing body of knowledge which will help in building a strong foundation of the topic for future studies.
Keywords: eWOM, communication model, communication process, literature analysis.
1. Introduction
The oral interpersonal uncommercialized form of communication is traditionally referred to as a word of mouth (WOM) (Arndt, 1967). Since its emergence, the term has witnessed a constant evolution and has been widely discussed in social sciences, business studies and digital disciplines, however, the scope of this research paper is limited to the systematic review of electronic word of mouth (eWOM) studies in business research. The frequently quoted definition of electronic word of mouth (eWOM) in the literature states that "it is a positive or negative statement made by potential, actual, and former customers about a product or a company via the Internet" (Hennig-Thurau et al., 2004). Technological advancements have shown a rapid increase in eWOM communication since the growing consumer base now has more opportunities to interact with Web 2.0 tools (Lee et al., 2008).
The researches available on eWOM confirmed that it influences the customer's decision-making process on digital platforms such as forums (Stephen, Galak, 2012), review sites (Archak et al., 2011), blogs (Onishi, Manchanda, 2012), social networks (Hennig-Thurau et al., 2015) and collective sources available online (King et al., 2014), which shows that eWOM certainly has a prevailing marketing power and provides consumers with the opportunity to interact is a
* Corresponding author
E-mail addresses: [email protected] (I. Iqbal)
computer-mediated environment where they can exchange their product-centered views to make informed purchase decision (Blazevic et al., 2013).
Due to its increasing relevance, a recent shift towards an explosive growth of literature encompassing the efficacy of eWOM have been witnessed (Chevalier, Mayzlin, 2006). Over the years, the emergence of extensive research discussing the variety of platforms and several types of eWOM communication, accompanied with various methods have left the diverse literature available on the topic scattered and inconclusive (King et al., 2014). Market level analysis and individual level analysis are the two main approaches has widely been used to analyze the eWOM phenomenon and its impact on consumers (Lee et al., 2008). Products and sales are the two important parameters on which market-level analysis have been conducted, mostly on objective panel data extracted from online review sites to determine how eWOM influences sales (Chen, Xie, 2005; Chevalier, Mayzlin, 2006; Zhu, Zhang, 2010). On the other hand, individual-level analysis caters to the communication process between sender and receiver about influencing purchase decisions (Cheung et al., 2009; Park, Kim, 2008; Zhang, Watts, 2008).
In this research paper, a theoretical review has been conducted to systematically organize the literature findings to develop an eWOM communication model. From participants' classification and motivation to generate eWOM to its influence on receivers, the model elaborates all the basic elements of the communication process which also include content type and transmitting platform. This paper significantly contributes to elaborate the basic eWOM communication process by the extensive analyzation of the existing body of knowledge which will help in building a strong foundation of the topic for future studies.
2. Materials and methods
There is a vast literature available on eWOM, but the scope of this study is limited to three journals - Journal of Consumer Research, Journal of Marketing and Journal of Marketing Research. the significant articles were searched and identified first, later their analysis was done. It was crucial to set a search strategy for identifying the relevant papers. The keywords used for searching the articles from digital databases include "eWOM", "online reviews", online discussions", "customer reviews" and "virality". The papers with the keywords mentioned earlier were extracted from high impact factor journals i.e. Journal of Consumer Research, Journal of Marketing and Journal of Marketing Research to ensure that no important eWOM research articles were skipped.
As per the guiding principles of conventional systematic review methodology, the inclusion and exclusion criteria were set for the initial sorting of the articles. This was done to make sure that the chosen articles are relevant and appropriate for the analysis of the current research. The included articles were academic and peer-reviewed in nature and eWOM was the core subject of discussion in business to consumer settings. However, the papers entirely based on the theoretical and conceptual background without any research design were excluded from the current research.
The digital advancements and emergence of Web 2.0 have enabled customers to influence each other at individual and market-level through user-generated content tools i.e., social networking platforms, microblogging sites, personal blogs and closed or open groups. Therefore, the research studies addressing the impact of eWOM communication can be categorized into market-level analysis and individual- level analysis (Lee, 2009). During the literature review, it was found that the majority of the eWOM research studies were focused around an individual's decision-making process and analysis of consumer reviews on rating platforms, e-commerce websites and discussion forums. The papers selected for this study were focused on both market level and individual level analysis approaches to bring a broader perspective of eWOM research into context.
The 17 articles selected for this study were published between 1967 and 2018. The majority of articles were from the last decade. The timeline review is summarized in Figure 1. To observe the evolution of electronic word of mouth, it was important to include the first paper published on the topic in 1967.
Fig. 1. Timeline Review of the Selected Papers
Among the selected 17 articles, 7 articles followed the market level approach, which constitutes 38.8 % of the total papers, 7 articles adopted the individual level approach, which constitutes the remaining 38.8 % of the selected papers and 3 articles followed both the market-level analysis and individual level analysis approach constitute 22.4 % of the total selected articles, summarized in Figure 2.
Analysis Approcah in the Selected Papers
Fig. 2. Analysis Approach in the Selected Papers
During the literature review, it was observed that the term eWOM is constantly evolving with the unprecedented expansion of digital platforms. A slight variation in the context of the study and the difference of its source platform or change in stimuli results in altogether a different eWOM type. As per the findings of the review, the different types of eWOM are summarized in Table 1.
Table 1. Summarized findings of Figure 1 and Figure 2
Types of eWOM Year Analysis Type Study
Product Related Conversations 1967 Individual Level Analysis Arndt, 1967
Negative Word of Mouth (NWOM) 2006 Individual Level Analysis Voorhees, 2006
Consumer Reviews, Community Content, 2006 Market Level Analysis Chevalier, Mayzlin, 2006
Word of Mouth Communication 2009 Individual Level Analysis Lam et al., 2009
Negative Word of Mouth (NWOM), 2010 Individual Level Analysis Cheema, Kaikati, 2010
Positive Word of Mouth (PWOM) 2011 Market Level Analysis Chen et al., 2011
Rumor 2011 Individual Level Analysis Dubois et al., 2011
Negative Content, Positive Content 2012 Both Market Level & Individual Level Analysis Berger, Milkman, 2012
Braggarts, Gossips, Negative Word of Mouth (NWOM), Positive Word of Mouth (PWOM) 2012 Individual Level Analysis De Angelis et al., 2012
Online Customer Reviews (OCRs), 2013 Market Level Analysis Ho-Dac et al., 2013
Negative Online Reviews, Positive Online Reviews 2013 Both Market Level & Individual Level Analysis Chen, Lurie, 2013
Word of Mouth Communication 2013 Market Level Analysis Lovett et al., 2013
Microblogging Word of Mouth (MWOM) 2014 Market Level Analysis Hennig-Thurau et al., 2015
Broadcasting, Narrowcasting 2014 Individual Level Analysis Barasch, Berger, 2014
Consumer Reviews 2017 Both Market Level & Individual Level Analysis Yin et al., 2017
Electronic Word of Mouth (eWOM) 2018 Market Level Analysis Liu et al., 2018
Word of Mouth Spikes 2018 Market Level Analysis Gelper et al., 2018
The theories identified in the eWOM literature are presented in Tab. 2. It was observed that most of the theories applied in selected studies were adopted from sociology, psychology and economics. Although the scope of this systematic review study is limited to the business research only, a single study has adopted the Organic Interconsumer Influence Model, Linear Marketer Influence Model, and Network Coproduction Model.
Table 2. Theories identified in eWOM literature
Theory Year Study
Riesman's Theoretical Formulations 1967 Arndt, 1967
Equity theory, Expectancy Disconfirmation, Signaling Theory, Adaptation Theory, Recency Effect, 2006 Voorhees, 2006
Regret, Negative Bias
Positive Bias, Negative Bias 2006 Chevalier, Mayzlin, 2006
Hofstede's Four Cultural Dimension Theory (1980) 2009 Lam et al., 2009
Social Exchange Theory 2010 Cheema, Kaikati, 2010
Information Cascade Theory, Accessibility-Diagnosticity Model 2011 Chen et al., 2011
Information Transmission, Belief Certainty 2011 Dubois et al., 2011
Psychological and Sociological Approaches 2012 Berger, Milkman, 2012
Self-Enhancement Theory 2012 De Angelis et al., 2012
Signaling Theory, Prospect Theory 2013 Ho-Dac et al., 2013
Negativity Bias, Temporal Contiguity and Causal Attributions 2013 Chen, Lurie, 2013
Social, Emotional and Functional Drivers 2013 Lovett et al., 2013
Negativity Bias, Diagnosticity of Information, Prospect Theory 2014 Hennig-Thurau et al., 2015
Social Impact Theory 2014 Barasch, Berger, 2014
Expressed Emotional Arousal 2017 Yin et al., 2017
Agglomeration Theory 2018 Liu et al., 2018
Social Network Theory 2018 Gelper et al., 2018
The following components of an eWOM communication model have emerged while reviewing eWOM literature which includes Participants' Motivation, Participants' Classification, Influence on Consumer Behavior, Transmitting Platform and Content Types. Table 3 elaborates the major findings.
Table 3. Components of eWOM Model
Category Subcategory Publication
Trustworthiness Hennig-Thurau et al., 2015
Personal Factor Gelper et al., 2018 Hennig-Thurau et al., 2015 Liu et al., 2018 Voorhees, 2006
Environmental Factors Voorhees, 2006
Participants' Social Factors Arndt, 1967 Liu et al., 2018 Lovett et al., 2013 Voorhees, 2006
Motivation Emotional State Berger, Milkman, 2012 Lovett et al., 2013 Yin et al., 2017
Functional Drivers Lovett et al., 2013
Perceived Regret Voorhees, 2006
Self-Presentation Barasch, Berger, 2014 Liu et al., 2018
Sharer Focus Barasch, Berger, 2014
Information Arndt, 1967
Chen et al., 2011 Chevalier, Mayzlin, 2006 De Angelis et al., 2012 Gelper et al., 2018 Ho-Dac et al., 2013
Certainty Dubois et al., 2011
Helpfulness Yin et al., 2017
Experience Chen, Lurie, 2013 De Angelis et al., 2012
Cultural Values Lam et al., 2009
Uniqueness of Possessions Cheema, Kaikati, 2010
Barasch, Berger, 2014 Cheema, Kaikati, 2010
Age De Angelis et al., 2012 Lam et al., 2009 Voorhees, 2006
Gender Arndt, 1967 Barasch, Berger, 2014 Cheema, Kaikati, 2010 De Angelis et al., 2012 Lam et al., 2009 Voorhees, 2006
Participants' Classification Education Arndt, 1967 Cheema, Kaikati, 2010 Dubois et al., 2011 Lam et al., 2009 Liu et al., 2018 Voorhees, 2006 Yin et al., 2017
Ethnicity Lam et al., 2009 Liu et al., 2018 Lovett et al., 2013 Voorhees, 2006
Culture Lam et al., 2009
Non-Complainers Voorhees, 2006
Audience Size Barasch, Berger, 2014
Proximity Barasch, Berger, 2014
Opinion Holders Hennig-Thurau et al., 2015
Cheema, Kaikati, 2010
Correct Choice Chen, Lurie, 2013 Hennig-Thurau et al., 2015 Yin et al., 2017
Re-purchase Intention Voorhees, 2006
Intention to Pass On Barasch, Berger, 2014 De Angelis et al., 2012 Dubois et al., 2011
Influence on Receivers Lovett et al., 2013 Voorhees, 2006
Virality Berger, Milkman, 2012
Sales Arndt, 1967 Chen et al., 2011 Chevalier, Mayzlin, 2006 Gelper et al., 2018 Ho-Dac et al., 2013
Product Adoption and Diffusion Lam et al., 2009
Increased Consumer Consideration Set Liu et al., 2018
Company Website/Social Media Berger, Milkman, 2012
Twitter Gelper et al., 2018 Hennig-Thurau et al., 2015
Blogs Gelper et al., 2018
Transmitting Platform Online/Offline (Surveys/Interviews/Experiment Settings) Arndt, 1967 Barasch, Berger, 2014 Cheema, Kaikati, 2010 De Angelis et al., 2012 Dubois et al., 2011 Lam et al., 2009 Voorhees, 2006
Barnesandnoble.com Chevalier, Mayzlin, 2006
Amazon.com Chen et al., 2011 Chevalier, Mayzlin, 2006 Ho-Dac et al., 2013
Yelp.com Chen, Lurie, 2013 Liu et al., 2018
Apple's App Store, Yin et al., 2017
Tweets Hennig-Thurau et al., 2015
Online Complains Voorhees, 2006
New York Times Articles Berger, Milkman, 2012
Online/Offline WOM (Verbal/Written/Oral) Arndt, 1967 Barasch, Berger, 2014 De Angelis et al., 2012 Gelper et al., 2018 Lam et al., 2009 Lovett et al., 2013
Content Type Customer/Consumer Reviews Chen, Lurie, 2013 Chen et al., 2011 Chevalier, Mayzlin, 2006 Ho-Dac et al., 2013 Liu et al., 2018 Yin et al., 2017
Recommendation Cheema, Kaikati, 2010
Star Rating Chen et al., 2011 Chevalier, Mayzlin, 2006 Yin et al., 2017
Rumors Dubois et al., 2011
3. Discussion and results
Consumers articulate their views on opinion-based platforms. Various studies have been conducted to analyze the motivation behind sharing their thoughts and experiences (Fine et al., 2017; Hennig-Thurau et al., 2003). However, in the context of our study, this category is based on a holistic theme identified in all the papers about participants' motivation to create and share eWOM content. Only the active participants have been put into the category due to their higher motivation to disseminate eWOM. The information has been observed as the most motivating factor (Arndt, 1967; Chen et al., 2011; Chevalier, Mayzlin, 2006; De Angelis et al., 2012; Gelper et al., 2018; Ho-Dac et al., 2013) followed by personal, social and emotional factors respectively. Self-presentation and sharer focus has also been reported as an important factor of participants' motivation (Barasch, Berger, 2014; Liu et al., 2018). In addition to this, trustworthiness, environmental factors, functional drivers, certainty, helpfulness, experience and cultural values were exhibited as equally important contributors of the theme as reported in the eWOM literature. Contrary to the findings of motivating factors, perceived regret was holding participants back from engaging in eWOM activities (Buttle, Groeger, 2017; Voorhees, 2006). On the other hand, the uniqueness of possessions motivates participants to discuss the product detail, but make them less willing to recommend the product to the public (Cheema, Kaikati, 2010; Chen et al., 2018).
The participants' classification is defined as a set of characteristics on the basis of the participants of eWOM communication have been classified into various groups. This theme is based on certain factors identified in the papers selected for this study. Education was the most common factor used by various researchers to classify their participants. It was observed that for most of the researches the participants were students (Arndt, 1967; Cheema, Kaikati, 2010; Dubois et al., 2011; Lam et al., 2009; Liu et al., 2018; Voorhees, 2006; Yin et al., 2017), which was largely followed by other demographic factors such as gender (Arndt, 1967; Barasch, Berger, 2014; Cheema, Kaikati, 2010; De Angelis et al., 2012; Lam et al., 2009), age (Barasch, Berger, 2014; Cheema, Kaikati, 2010; De Angelis et al., 2012; Lam et al., 2009; Voorhees, 2006), and ethnicity (Lam et al., 2009; Liu et al., 2018; Lovett et al., 2013; Voorhees, 2006) respectively. It has been observed that the scope of the study influences the participants' classification. These specific study-based classifications to refine methodology include culture (Lam et al., 2009), opinion holders (Hennig-Thurau et al., 2015), audience size, proximity (Barasch, Berger, 2014) and non-complainers (Voorhees, 2006).
In the context of this review, the receivers are those who receive word of mouth messages generated by the participants. Several studies have proved that receivers' prior knowledge and experiences shape and moderate the impact of word of mouth communication (Li et al., 2016; Moore, Lafreniere, 2020; Rosario et al., 2020), hence it is important to analyze how eWOM communication influences the receivers. Under this category, the impact of eWOM on receivers' behaviour has been identified. eWOM communication empowers consumers to make suggestions, sharing opinions and experiences when it comes to adopting new product, ideas and innovations (Li et al., 2016; Roy et al., 2020; Zhou et al., 2021) therefore, the correct choice, intention to pass on and sales are found as the most common factors contributing to the theme (Barasch, Berger, 2014; Cheema, Kaikati, 2010; Dubois et al., 2011; Gelper et al., 2018; Hennig-Thurau et al., 2015; Ho-Dac et al., 2013). In addition, the research endorses that eWOM influences purchase intention (Voorhees, 2006), triggers virality (Berger, Milkman, 2012) and helps receivers to expand their brand consideration set (Liu et al., 2018) through adoption and diffusion (Lam et al., 2009) especially in case of new products.
An eWOM message needs a platform to travel that results in the emergence of the transmitting platform category. In the reviewed papers, it was observed that the message transmitting platforms for the papers followed market-level analysis approach were based on company websites (Berger, Milkman, 2012; Yin et al., 2017), microblogging and blogging sites (Gelper et al., 2018; Hennig-Thurau et al., 2015), review sites (Chen, Lurie, 2013; Liu et al., 2018), e-commerce website (Chen et al., 2011; Chevalier, Mayzlin, 2006; Ho-Dac et al., 2013). However, in the papers where individual-level analysis approach has been used, the unit of analysis were mostly students, and the transmitting platforms were included survey forms, interviews, and messages initiated in the experimental settings (Arndt, 1967; Barasch, Berger, 2014; Berger, Milkman, 2012; Cheema, Kaikati, 2010; Chen, Lurie, 2013; Dubois et al., 2011; Lam et al., 2009; Voorhees, 2006; Yin et al., 2017).
For this research, the content type is referred to the eWOM content taken from different online sources and collected during experimental settings. This is another theme found common in all the papers selected for the systemic review. Customer or consumer reviews (Chen, Lurie, 2013; Chevalier, Mayzlin, 2006; Liu et al., 2018) and online or offline word of mouth (Arndt, 1967; Gelper et al., 2018; Lam et al., 2009) were found to be the most prevailing content type used to examine eWOM in the available literature (Liu et al., 2019; Xu, Lee, 2020; Zhao et al., 2019). The star rating factor was also used either own its own or in combination with other content types to give meaning to an eWOM communication (Chen et al., 2011; Chevalier, Mayzlin, 2006; Yin et al., 2017). Other than that tweets (Hennig-Thurau et al., 2015), online complaints (Voorhees, 2006), newspaper articles (Berger, Milkman, 2012), recommendations (Cheema, Kaikati, 2010) and rumours (Dubois et al., 2011) have also significantly contributed to the theme. It has also been observed that papers in which both market and individual level analysis were conducted mostly used mixed methodology technique (Berger, Milkman, 2012; Chen, Lurie, 2013; Yin et al., 2017), and experiments were conducted to endorse the findings of market analysis mostly, however, no particular pattern was found among a particular content type and analysis technique.
Fig. 3. Graphical Presentation of eWOM Communication Model
4. Conclusion
The prime objective of this systematic review paper is to analyze the eWOM communication process and to present the literature findings as an eWOM communication process. As discussed earlier, both individual level and market analysis papers have been reviewed in this study. After analyzing the literature, a basic eWOM communication model has been developed. The model elaborates participants' motivation and classification, content type, transmitting platform and its influence on receivers. This model provides a basic foundation for future studies.
There were a few limitations, which should be noted. The analyses and categorization are limited to the few impact factor journals fulfilling our selection criteria. Moreover, we have included both the market level and individual level studies in our literature analysis, and more extensive findings can be comprehended by selecting studies addressing either on market level or individual level approach. Our systematic review is based on only 17 papers; therefore, we are unable to perform empirical verification of our findings.
Future research on the topic should include more research papers so that it can be verified empirically. The eWOM model that has been developed in this study is very basic and future research can explore it further in a detail.
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