Academy of Strategic Management Journal (Print ISSN: 1544-1458; Online ISSN: 1939-6104)

Research Article: 2020 Vol: 19 Issue: 2

How Consumers Engage in & Utilize the Source of Electronic Word-of-Mouth (e-WOM)?

Jinbong Choi, Sungkonghoe University

Abstract

This research aims to determine how people are engaging in and utilizing the source of electronic word-of-mouth (e-WOM). The total sample of this research is 667 respondents. As a research method, this study aims to measure the participants’ use and opinions of online reviews (e-WOM) with relation to the following categories: information seeking; general credibility; information processing; susceptibility to online product reviews; and transmission of online product reviews. The result of this research shows that many people visit online review sites before purchasing a product and seek more e-WOM when purchasing expensive products. However, unlike the previous research where consumers utilize e-WOM due to credibility of information, the personal experiences and opinions of the people around them can be more important factors in influencing their purchasing decisions than e-WOM. This result affirms that consumers choose what they think are the right products and brands with the help of e-WOM when dealing with ultimate purchase intentions.

Keywords

e-WOM, Laptop Computer, Shampoo, Information Credibility, Transmission.

Introduction

Word-of-mouth (WOM) is defined as oral communication between two or more people concerning a certain brand name, product, or service on a non-commercial basis (Huang et al., 2009; Lee & Youn, 2009; Park & Kim, 2008). Zaltman & Wallendorf (1983) defined word-of-mouth as an informal channel that exchanges positive and negative information without consumers seeking to profit from each other. Similarly, it can be defined as the exchange of consumption experiences among consumers (Borgida & Nisbett, 1977).

Product information that is communicated through WOM often has an added layer of credibility, as consumers tend to be more trusting of one another compared to the level of trust between consumers and profit-oriented companies (Bickart & Schindler, 2001; Huang et al., 2009; Karakaya & Barnes, 2010; Kim, 2003). Therefore, consumers tend to share their own consumption experiences with other consumers, and utilize such experiences to reduce risk by searching for helpful information to gain confidence in purchasing a product (Peterson & Maria, 2003).

With the emergence of the Internet, e-WOM (electronic word-of-mouth) has become a significant information source in consumers’ purchasing decisions (Gu et al., 2012). The term e-WOM is defined as informal communications through Internet-based technology concerning the usage or the characteristics of particular goods and services, or their sellers or providers (Huang et al., 2009). It is particularly significant to the current generation because of its growing dependency on electronic information. The influence of e-WOM on consumer habits is steadily increasing, as users have devised new and innovative ways to disseminate and receive product information and experiences on specific products (Karakaya & Barnes, 2010; Lee & Youn, 2009; Jones et al., 2009).

The subject of e-WOM is essential for research not only because of the underlying relations between interacting consumers, but also because of the influence of the phenomenon on marketing and public relations. It has been found that customers are more trusting and sympathetic toward e-WOM than the commercial information provided by companies, so online word-of-mouth plays an important role in the success or failure of the marketing strategy (Bickart & Schindler, 2001). Since then, e-WOM has had a significant impact on the business of marketing due to the direct relation between electronically based engagement and product sales. The more information marketers have on e-WOM, the higher the chance these professionals will benefit from increasing company sales by understanding how it works. Marketers will be able to increase sales based on company reputation and image, which is related to public relations. Due to the ease with which consumers now have to influence the image and reputation of a particular company through digital communications; e-WOM has had a powerful impact on the practice of public relations. The more information public relations practitioners have on e-WOM, the better they can understand the phenomenon and manage it to their benefit. Since product sales are directly related to the image and reputation of a company, the use of e-WOM by both marketers and public relations practitioners are interconnected. Thus, the study of e-WOM is especially beneficial to both practices, and should be further examined as such.

The main purpose of this study is to determine the means in which people are engaging in and utilizing the source of e-WOM. The researchers of this study are also interested in the credibility of the phenomenon, as it relates to the quality of online product reviews and ultimate purchase intentions. Lastly, this study will serve as an evaluation of the transmission of e-WOM; essentially, how and to what extent is e-WOM transferred from one user to another. The findings of this study will culminate in a compilation of suggestions and recommendations for marketing and public relations practitioners.

Literature Review

Consumers collect product information through different sources. They may obtain information on products not only from advertisements in mass media, but also through exchanging consumption experiences with fellow consumers. As advertising is provided for commercial purposes, such as increasing sales or enhancing corporate image, consumers treat such information with potential mistrust. However, word-of-mouth communication is accepted as neutral in terms of non-commercial information exchange among consumers (William & Aaker, 2002; Voss, 1984). Kim (2003) explained why word-of-mouth communication is more effective compared to advertising. Advertising through mass media in the form of massive information laced by vast amounts of advertising has its limitations in its efficiency as a tool of marketing communication. Furthermore, the lack of credibility due to commerciality, the flow of one-sided messages, and the difficulty of reaching the representative object by targeting many heterogeneous, unspecified subjects can be pointed out as problems in communication through the mass media. However, word-of-mouth information is neutral in terms of non-commercial information, and can, therefore, be trusted. Neilson (2007) also highlighted that WOM is widely considered as more reliable than advertisements and other product information generated by sellers.

In particular, with the advent of new media, opinions on product information among consumers began to surface online, and many researchers began to develop an interest in the effects of e-WOM. Huang et al. (2009) conducted a study in which they specifically analyzed e-WOM from the perspective of pass-along emails. By using social capital theory and social cognitive theory as foundation, researchers developed a model involving social enablers and personal cognition factors to explore e-WOM behavior and its efficacy. Factors such as message involvement, social interaction ties, affection outcome expectations, and message forwarding self-efficacy exert significant influences on pass-along email intentions. Phelps et al. (2004) also analyzed the pass-along email aspect of e-WOM, where it was found that infrequent senders might have an especially noteworthy impact due to approaches that are more targeted, personalized, and motivated when sending emails to the members of their network. As a result, researchers suggest that message developers with messages that spark strong emotion (humor, fear, sadness, or inspiration) are more likely to be forwarded. It is suggested that these messages must be consistent with those particularly viral strains that are most appropriate to the objective of the pass-along sender.

Many researchers have noted how word-of-mouth messages affect consumers' purchasing behavior. Karakaya & Barnes (2010) examined the impact of customer care experiences that were expressed online on the consumer’s brand or company preference when purchasing products and services. This study was executed by including the level of usage of these sites, and consumer opinions on whether or not their comments would make a difference on the actions of the companies. Results indicated that consumer opinions on customer care in socially based websites affect consumer opinions and consumer engagement and, consequently, the consumer’s choice of brand or company when making purchases. They also found that the websites themselves (including government/consumer advocacy information sites, company web sites, and information found through search engines) are not considered important in terms of influencing consumer behavior. Park & Kim (2008) focused specifically on the aspect of online consumer reviews through e-WOM in their research. Two types of review structure were considered for this study: the type and the number of reviews. By utilizing the cognitive fit theory, the researchers showed that the type of reviews could be a key moderating variable when explaining the inconsistent relationship between consumer expertise and WOM in previous research. The research from this study examines which type of reviews cognitively presents consumers with a high or low level of expertise. The results from this study indicate that the effect of the cognitive fit (the type of reviews) on purchase intention is stronger among experts than among novices, while the effect of the number of reviews on purchase intention is stronger among novices than among experts.

Moreover, Lee & Youn (2009) examined whether or not different online platforms on which e-WOM communication is posted influence the consumers’ judgments of reviewed products and how they are influenced by such type of communication. This study also analyzed the moderating role of the valence of e-WOM on the platforms’ consumer product-judgment relationship. This study indicated that participants who were exposed to a review posted on a personal blog were more likely to attribute the review to circumstances and were less likely to recommend the product to friends than those who were exposed to a review either on an independent review website or the brand’s website. The effect of e-WOM platforms on consumer willingness to recommend the product to friends was found only when the review was positive. When the review was negative, there were detrimental effects on consumer willingness to recommend the product to friends (regardless of the e-WOM platform). In contrast, Ahuwalia et al. (2000) and Doh & Hwang (2009) argued that consumers respond more sensitively to negative information than positive information, resulting in a larger impact on consumer attitudes and purchasing intentions. People tend to regard the truthfulness of negative information more highly than positive information (Chatterjee, 2001; Herr et al., 1991). Due to uncertainty or unfamiliarity on particular products, consumers perceive a negative word-of-mouth as a stronger message compared to a positive one (Ahuwalia, et al., 2000; Richins, 1983). Also, Jones et al. (2009) explored the influence of previous related experience, online advertising, and comments from discussion groups (both positive and negative in tone) on Internet commerce judgments. The following observations were indicated: when past personal experience is favorable, an ad alone is sufficient to produce a favorable brand evaluation; when personal experience is unfavorable, electronic word-of-mouth influences brand attitude, though neither advertising nor word-of-mouth has any impact on purchase intentions; when personal experience is not available, there is a positivity bias toward e-WOM communications; and exclusively positive word-of-mouth posts, combined with advertising, stand out distinctly from advertising combined with either uniformly negative or mixed (positive and negative) word-of-mouth or advertising alone. The importance of e-WOM with regard to Internet trade is emphasized and supported in this study.

Moreover, researchers have been interested in the scalability of consumers through word-of-mouth. Trusov et al. (2009) conducted a study that analyzed the effect of WOM marketing on member growth at an Internet social networking site, and compared such effect with traditional marketing vehicles. This study found that WOM referrals have substantially longer carryover effects than traditional marketing actions, and produce substantially higher response elasticity. Also, Li et al. (2010) identified potential influential nodes for efficiently spreading product measures through WOM. The researchers proposed a framework with mining techniques, a modified Pointwise Mutual Information (PMI) measure, and an adaptive Recency, Frequency, and Monetary (RFM) model to evaluate the influence of online reviewers. The proposed framework was verified by the data collected from Epinions.com, which is one of the most popular online product review websites. The proposed model found that it could accurately identify which reviewers were the influential nodes. It is implicated that this approach could be potentially exploited in effectively carrying out online word-of-mouth marketing. Cheung et al. (2008) aimed to investigate the extent to which opinion seekers are willing to accept and adopt online consumer reviews through e-WOM, and which factors encouraged adoption. The researchers developed an information adoption model to examine the factors affecting the information adoption of online opinion seekers in online customer communities. The results of this study suggested comprehensiveness and relevance as the most effective components of the argument quality construct of the research model, making them key influencers of information adoption. Furthermore, Chu & Kim (2011) examined how social relationship factors relate to e-WOM transmitted via online social websites. For this study, a conceptual model was developed and tested to identify tie strength, homophily, trust, and normative and informational interpersonal influence as important antecedents to e-WOM behavior in social networking sites. The results of this study indicated that tie strength, trust, and normative and informational influence were positively associated with the users’ overall e-WOM behavior, whilst a negative relationship was found with regard to homophily. Another significant finding from this research was that product-focused, e-WOM in social networking sites was a unique phenomenon with important social implications.

On the other hand, there are studies focusing on generational differences among people who use e-WOM through social media and email or users depending on specific devices such as PC computers and mobile devices. Strutton et al. (2011) investigated whether actionable differences existed between Generation X and Generation Y, with regard to electronically mediated marketing. The findings suggest that, although there are structural differences in the media used to spread e-WOM (with Gen Y more heavily engaged with social networking media, and Gen X more reliant on email), the motivations and behaviors of the two groups are strikingly similar. Another significant finding of this study was that there were few differences in technology skills or attitudes toward technology. Okazaki (2009) explored and compared e-WOM on PC computers versus e-WOM on mobile devices by utilizing a proposed causal model for consumer participation. With portability and location-based capabilities (which facilitate sending and receiving timely information at the right place), it is much easier for consumers to be continually connected online through mobile devices. It is posited by the researcher that social identity, motivations (purposive value, social enhancement, and intrinsic enjoyment), inherent novelty seeking, and opinion leadership as antecedents affect desire (individual-level driver) and social intention (group-level driver) to engage in e-WOM. Results from this study indicate that desire only partially mediates the effects on the social intention of social identity. Compared with PC e-WOM participants, mobile device e-WOM participants exhibited significantly higher perceptions of social intention, intrinsic enjoyment, and cognitive social identity.

More recently, Yan et al. (2018) investigated the impact of social media marketing activities in terms of mobile e-WOM on different dimensions of online CBBE (consumer based brand equity) and behavioral intentions towards online fast causal restaurant industry, using the S-O-R (stimulus-organism-response) consumer response model. The results of this study indicated that mobile e-WOM significantly influenced both consumer emotional, affective and cognitive responses. The emotional affective and cognitive responses significantly influenced behavioral responses. Thus, the findings of this study emphasized the importance of examining consumer response in terms of mobile e-WOM and CBBE. On the other hand, Anastasiei & Dospinescu (2019) tried to build a model that evaluates the influence of affective commitment, high-sacrifice commitment, and satisfaction on the customers’ word-of-mouth concerning an online retailer. In this research, two word-of-mouth dimensions were considered: volume and valence. The findings of this study showed that satisfaction and high-sacrifice commitment have an important impact on both word-of-mouth volume and valence, while affective commitment only influences word-of-mouth valence.

Research Questions and Hypotheses

Based on the literature review, the following research questions and hypotheses are as follows:

1. RQ1. How often do consumers rely on e-WOM?

2. RQ2. Do consumers believe that e-WOM is credible and accurate?

3. RQ3. How do consumers use e-WOM?

4. RQ4. Do consumers want to spread e-WOM with other people?

H1 Consumers use e-WOM more often when they buy expensive products than when they think about buying cheap items.

H2 e-WOM is a more influential factor in impacting purchase decision than people’s personal experience and opinion on the products.

H3 Negative e-WOM is more effective than positive e-WOM on consumer’s product reference.

The data for this study were collected by a participating researcher in the fall 2011 semester at Texas State University in San Marcos, TX. The students were chosen as the sample because they surf the Internet very frequently and are intense the Internet users. Two samples of students participated in this study: one sample consisted of 366 students, while the other sample consisted of 301 students. There were a total of 667 participating subjects from the two samples. All the participants were mass communication majors who were currently enrolled in either public relations or advertising classes. The students in the initial sample of 366 were given a questionnaire that was constructed to create a scenario for purchasing a laptop computer. The participating students were asked how they would use e-WOM, or any type of online recommendation. The other sample consisting of 301 students was given a questionnaire that was constructed to create a scenario for purchasing shampoo. The format of the questionnaires was identical, as they were both based on product purchase habits and intentions. The only difference between the two was the hypothetical product used in each survey. The majority of the questions used in the surveys were based on a 7-point Likert scale: 1 was used to indicate strong agreement, while 7 was used to indicate strong disagreement. The questions were used to measure the participants’ use and opinions of online reviews (e-WOM) with relation to the following categories: information seeking; general credibility; information processing; susceptibility to online product reviews; and transmission of online product reviews.

Results

RQ 1: How often do consumers rely on e-WOM?

The first research question delves on how often participants used e-WOM in the last month. A total of 417 participants (73.4%) visited review websites, while 151 participants (26.6%) did not use review websites. A total of 103 participants (18.1 ) visited consumer product review websites once to learn about the products. A total of 101 participants (17.8 ) visited review websites two times. A total of 65 participants (11.4%) visited consumer product review websites three times. A total of 148 respondents (26.1%) used consumer product review websites more than four times. This result indicates that consumers tend to visit product review websites before purchasing products (Table 1).

Table 1 Frequency of the use of e-Wom
Time Frequency Percent (%)
0 151 26.6
1 103 18.1
2 101 17.8
3 65 11.4
More than 4 148 26.1
Total 568 100.0

RQ 2: Do consumers believe that e-WOM is credible and accurate?

The second research question asks consumers if they believe that e-WOM is credible and accurate. Consumers think that online product reviews are relatively credible (t=-1.06, p> 0.05), and they trust online product reviews provided by other consumers (t=-0.86, p>0.05).

Moreover, consumers think online product reviews are accurate (t=-0.87, p>0.05).The findings are not significant between laptop computer and shampoo purchases. It means that people tend to believe e-WOM overall, regardless of the type of products. However, the level of credibility, trust, and accuracy is not that high. Respondents replied with an average value that is close to 4 of 7 points (Table 2).

Table 2 The General Credibility of e-WOM
Variables   N M SD t (df) p
Credible Computer 366 3.39 1.42 -1.06 (663) ns
Shampoo 299 3.51 1.49    
Trust Computer 366 3.40 1.50 -0.86 (661) ns
Shampoo 297 3.51 1.52    
Accurate Computer 366 3.51 1.39 -0.87 (664) ns
Shampoo 300 3.60 1.50    

RQ 3: How do consumers use e-WOM?

The third research question discusses how consumers use e-WOM. In order to answer this question, this study presents two hypotheses. First, this study stated that consumers use e-WOM more often when they buy expensive products than when they buy cheap items. The result shows that when people buy expensive products, they pay more attention to online reviews (M computer =3.34, M shampoo=4.20, t =-6.33, p<0.001). Thus, H1 was acceptable. Second, H2 stated that e-WOM is a more influential factor on purchase decisions than other people’s personal experiences and opinions on the products. Respondents would usually not only go to online product review websites (t e-WOM=-2.10, p<0.05), but also ask their neighbor’s personal experiences and opinions on the product (t acquaintances=-3.52, p<0.001). The finding is significant between laptop computer and shampoo purchases. However, some people prefer asking for acquaintances’ personal experiences and opinions on specific products than relying on online review websites (M e-WOM=3.61, SD=1.69, M acquaintance=2.98, SD=1.54). Thus, this finding did not support H2.

With the ultimate purchase intentions through e-WOM, respondents search online consumer product reviews to know which products or brands make good impressions on others (t =-1.17, p>0.05). In order to be sure about buying the right product and brand, respondents often read other consumers’ online product reviews (t= -1.76, p>0.05). Also, to help them choose the right product or brand, they often consult other consumers’ online product reviews (t=-1.73, p> 0.05). However, the results are not significant between laptop computer and shampoo purchases, which can be interpreted as people utilize e-WOM not only to obtain useful information but also to reduce product uncertainty by communicating with other consumers (Table 3).

Table 3 The Usage of e-WOM and Ultimate Purchase Intentions
Variables   N M SD t (df) p
Information processing Usage of e-WOM Computer 366 3.34 1.59 -6.33(663) 0.000***
Shampoo 299 4.20 1.95    
  Information processing e-WOM Computer 366 3.49 0.09 -2.10(665) 0.04*
Shampoo 301 3.76 0.10    
Acquaintances Computer 366 2.79 0.08 -3.52(663) 0.000***
Shampoo 299 3.21 0.09    
Susceptibility to online product review To know good
products
Computer 366 3.40 1.54 -1.17(663) ns
Shampoo 299 3.54 1.60    
To buy the right products Computer 366 3.34 1.52 -1.76(663) ns
Shampoo 299 3.56 1.67    
To help choose the right products Computer 366 3.40 1.62 -1.73(663) ns
Shampoo 299 3.63 1.71    

RQ 4: Do consumers want to spread e-WOM with other people?

This study attempted to determine how e-WOM affects an individual consumer’s product choice and how consumers share e-WOM with other people. Consumers replied that both positive and negative e-WOM significantly affected their product choice on buying a particular brand of laptop computer more than they did with shampoo purchases (t positive=-5.57, p<0.001, t negative=-0.4.95, p<0.001). Thus, this result did not support H3. In particular, e-WOM, regardless of the direction of the message, significantly affected a consumer’s product preference on expensive products (M negative=3.22, M positive=3.29). In contrast, in case of cheaper products, such as shampoo, consumers think that e-WOM hardly affected their product choice (M negative=3.88, M positive=4.02). It showed that the price of the products could be an important factor on whether to pay attention to e-WOM or not.

People would recommend the product or brand to their friends when they read positive online product reviews (M computer=3.27, M shampoo=3.45, t=-1.46, p>0.05). Also, respondents would not recommend the product or brand to their friends when they read negative online product reviews (M computer=3.15, M shampoo=3.33, t=-1.39, p>0.05). It indicated that consumers would want to recommend positive reviews and, at the same time, not to recommend negative ones to their friends regardless of the type of products. However, in general, participants rarely want to share online product reviews with other people (M computer=3.97, M=shampoo=3.85) (Table 4).

Table 4 The Transmission of e-WOM
Variables N M SD t (df) p
Product choice Positive reviews Computer 366 3.29 1.57 -5.57(663) 0.000***
Shampoo 299 4.02 1.79    
Negative reviews Computer 366 3.22 1.59 -4.95(665) 0.000***
Shampoo 301 3.88 1.87    
Recommend Positive reviews Computer 366 3.27 1.57 -1.46(665) ns
Shampoo 301 3.45 1.61    
Not recommend Negative reviews Computer 366 3.15 1.63 -1.39(665) ns
  Shampoo 301 3.33 1.61    
Share e-WOM Computer 366 3.97 1.72 0.919(664) ns
Shampoo 300 3.85 1.81 0.914(624)  

Discussion

This study determined how people are engaging in and utilizing the source of e-WOM. This study also evaluated the transmission of e-WOM; essentially, how and to what extent is e-WOM transferred from one user to another.

With the use of e-WOM, most of the participants visited product review websites before deciding on purchasing a product: 73.4% of participants visited online review websites more than once in the last month. As shown in previous studies (Peterson & Maria, 2003), it can be interpreted that consumers use online reviews on products as important information before making a reasonable purchase decision, so they become more active in searching for information on product consumption experiences and reviews provided by other consumers.

Regarding the information credibility of e-WOM, respondents think that e-WOM is relatively reliable and accurate. Trusov et al. (2009) explained that in the case of off-line oral communication, the scope of delivery is limited because it is limited to family members or friends as sources of information, but the scope of online communication is not limited. The range of e-WOM is much larger. Also, compared to other types of communication, such as between consumers and companies, consumers tend to trust e-WOM than other types of communication (Bickart & Schindler, 2001; Huang et al., 2009; Karakaya & Barnes, 2010; Kim, 2003; Nielson, 2007). Therefore, consumers generally rely on word-of-mouth rather than other sources of information in relation to their purchasing decisions. However, respondents did not wholly trust online reviews. The response to the questions on trust was close to the average value of 4 to 7 points. They utilized product review websites often, but they regarded those kinds of information as not entirely credible. This result is probably due to the increasing number of channels from which consumers can obtain many kinds of information via the Internet. In contrast, they may think that there is no guarantee that such information is reliable. Schiffman & Kanuk (2000) are also worried that someone might believe that word-of-mouth could be manipulated.

Moreover, in this study, respondents tend to believe the experiences and opinions of acquaintances, such as friends or family, more than online reviews. This is because word-of-mouth obtained from an acquaintance is likely to increase information credibility, making it easier for the recipient to accept the information. It can be interpreted as reliable information from trustworthy people was judged as more important than the amount of oral information provided by unknown people. On the other hand, people can get more information through e-WOM, though they cannot be absolutely sure if such information is reliable. This finding shows that people would like to rely on fewer but reliable messages. Based on this point of view, McKnight & Kacmar (2006) also insisted that information credibility is a crucial factor in the adoption of online WOM. Chu & Kim (2011) also noted that trust is positively associated with a user’s overall e-WOM behavior. Nielsen’s findings can also support the finding of this research. According to Nielsen’s latest Global Trust in Advertising report, 92 percent of the respondents are more reliant on personal referrals from their friends and family than any other ads, and about 70 percent of consumers trust brands based on the information they receive through online consumer review sites. It indicates that it is important to build trust to reduce a consumer’s uncertainty with online reviews.

Participants visited product review websites when they are thinking of purchasing expensive products more than they do with cheap items. The price of the product influences the consumer’s involvement. In general, consumers want to satisfy their desires and values when purchasing goods. Especially, the higher the involvement, the more consumers seek information that they can trust to reduce product risk because they want to check whether their decision is prudent or not. Therefore, people attempt to search for other consumers’ reviews of products in order to confirm their decisions. With the ultimate purchase intentions through the help of e-WOM, respondents replied that they communicated with other people regarding product information through e-WOM because they want to establish more trust on the product before their purchase, and to make sure they are buying the right product and brand. In the case of expensive products, the risk on cost is high when consumers make a mistake, so they should check their options carefully before making a decision. On the other hand, the risk on cost of cheap items is low, so consumers can choose from alternative products more easily even if they think they made a mistake with their initial purchase.

Also, this study found that the price of the product implies a larger influence on the acceptance of e-WOM regardless of message direction. In general, people would recommend positive online product reviews to their friends, and, also, they would not recommend negative online product reviews to their friends. Lee & Yoon (2009) also found that the message direction of e-WOM affects the word-of-mouth intention. However, in this study, the price of the product has proven to be of more importance. The tone of the messages, whether positive or negative, did not matter. The price of the products mattered. While e-WOM has a major effect in product selection when purchasing expensive products, it rarely affects the purchase of cheap items. As the price of the goods rises, people want to employ e-WOM regardless of message orientation. As the price of the products decreases, they rarely rely on online reviews. It indicates that consumers are more willing to seek information when buying expensive products. Additionally, respondents are more likely to recommend products that have been evaluated well to their friends, while they would not recommend products to their friends if such products garnered negative reviews. However, in general, participants hardly share e-WOM with other consumers.

Conclusion

Few people open their wallets without looking for any information before purchasing expensive goods or planning a nice meal with their family. Most of the time, they seek the opinions of other people around them, or search the Internet to obtain useful information to aid in their decision-making (Peterson & Maria, 2003). As such, in the modern society where the Internet and smartphones have become so accessible, e-WOM plays an important role in consumer decision-making. This is the reason both consumers and companies are paying attention to online word-of-mouth. This is also the reason research on the spread of information and the acceptance of information among consumers has been increasing recently (Lee et al., 2006). Based on this point of view, this study provides several practical implications to marketing and public relations practitioners.

The finding of this study on e-WOM being an influential factor has left the task of marketing or PR practitioners to seeking ways to increase consumer’s confidence in online reviews. In reality, there are some people who think that word-of-mouth is artificial because the circulation of specific messages or product reviews is initiated by companies. Since consumers are more likely to believe that e-WOM is more trustworthy than advertising messages relayed via mass media, it is sometimes manipulated by companies pushing their own agenda. However, genuine e-WOM marketing is not manipulation, but it is a type of service based on people’s own experiences and exchange of opinions generated by other customers. It is a marketing strategy that encourages and promotes personal referrals. Marketing and PR practitioners must be aware that consumers want reliable information to help them in their purchasing decisions. Therefore, it is important to know the product reviews of general consumers, though the active use of professional reviewers must also be considered. Utilizing e-WOM with the help of specialists who are experts on a particular product or category will provide information that will increase consumer confidence.

Recently, amid the development of the Internet, the number of SNS users has increased and the social influence of consumers has become stronger. Social media has a strong ripple effect that enables even strangers to exchange opinions instantly, thus, specific information is spreading widely within a short period of time. It also means that negative reviews for a particular product or service can spread quite promptly. Given that negative messages have a greater impact, the ripple effects triggered by social media buzz cannot be overlooked by companies. Thus, marketers should turn to a system that fits the social media environment by moving away from the usual means of ignoring or blocking unfavorable statements from customers. Instead, they should collect and conduct a more thorough investigation of various online communications created in social media, and devise ways to solve problems after listening to consumer complaints. By doing so, the consumer could change their opinion toward a company in a positive way. This approach will also help corporations in crisis management. In short, effective management of e-WOM will help not only the company’s profits, but also its image and reputation in the long run.

However, since the sample of this research is limited to college students, there is a limitation in terms of generalization. Particularly, in the case of people in their 40-50s, it may present a different result because people in those ages may not be as familiar with the Internet or use computers as often as their younger counterparts. Thus, in future research, it is necessary to analyze various types of consumers. Moreover, since this study only investigated e-WOM concerning computer and shampoo purchase intentions, further research must also explore various products that can benefit from e-WOM. Additionally, this research did not analyze the context of acquisition decisions and reviews, so future research must study the nature of the decision task and which type of information directly affects an acquisition decision. The scope of the research must also be expanded. Although many consumers obtain e-WOM via social media, this study only analyzed the experience of using e-WOM obtained via online review sites.

References

  1. Ahuwalia, R., Burnkrant, R.E., & Unnava, R.H. (2000). Consumer response to negative publicity: The moderating role of commitment, Journal of Marketing Research, 16-28.
  2. Anastasiei, B., & Dospinescu, A. (2019). Electronic word-of-mouth for online retailers: Predictors of volume and valence. Sustainability, 11(3), 814-832.
  3. Bickart, B., & Schindler, R. (2001). Internet forums as influential sources of consumer information. Journal of Interactive Marketing, 15(3), 31-40.
  4. Borgida, E., & Nisbett, R. (1977). The differential impact of abstract vs concrete information in decision. Applied Social Psychology, 7(3), 258-271.
  5. Chatterjee, P. (2001). Online reviews: Do consumers use them? Advance in Consumer Research, 28, 129-133.
  6. Cheung, C., Lee, M., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229-247.
  7. Chu, S., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (e-WOM) in social networking sites. International Journal of Advertising, 30(1), 47-75.
  8. Doh, S.J., & Hwang, J.S. (2009). How consumers evaluate e-WOM (Electronic Word-of-Mouth) messages, Cyber Psychology & Behavior, 12(2), 193-197.
  9. Gu, B., Park, J., & Konana, P. (2012). The impact of external word-of-mouth sources on retailer sales of high-involvement products. Information Systems Research, 23(1), 182-196.
  10. Herr, P.M., Kardes, F.R., & Kim, J (1991). Effect of word of mouth and product attitude information on persuation: An accessibility-diagnosticity perspective. Journal of Consumer Research, 17, 454-462.
  11. Huang, C., Lin, T., & Lin, K. (2009). Factors affecting pass-along email intentions (PAEIs): Integrating the social capital and social cognition theories. Electronic Commerce Research and Applications, 8, 160-169.
  12. Jones, S., Aiken, K.D., & Boush, D. (2009). Integrating experience, advertising, and electronic word of mouth. Journal of Internet Commerce, 8, 246-267.
  13. Karakaya, F., & Barnes, N. (2010). Impact of online reviews of customer care experience on brand or company selection. Journal of Consumer Marketing, 27(5), 447-457.
  14. Kim, S.H. (2003). The influence of product involvement and knowledge on Internet WOM. The Korean Journal of Advertising, 14(1), 257-280.
  15. Lee, M., & Youn, S. (2009). Electronic word of mouth (e-WOM): How e-WOM platforms influence consumer product judgment. International Journal of Advertising, 28(3), 473-499.
  16. Li, Y., Lin, C., & Lai, C. (2010). Identifying influential reviewers for word-of-mouth marketing. Electronic Commerce Research and Applications, 9, 294-304.
  17. McKnight, H., & Kacmar, C. (2006). Factors on information credibility for an internet advice site. HICSS’ 06/ Proceedings of the 39th Annual Hawaii International Conference.
  18. Neilson. (2007). WOM the most powerful selling tool: Nielsen global survey.
  19. Okazaki, S. (2009). Social influence model and electronic word of mouth: PC versus mobile internet. International Journal of Advertising, 28(3), 439-472.
  20. Park, D., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7, 399-410.
  21. Peterson, R.A., & Maria, C.M. (2003). Consumer information search behavior and the Internet. Psychology and Marketing, 20(2), 99-121.
  22. Phelps, J., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004). Viral marketing or electronic word-of-mouth advertising: examining consumer responses and motivations to pass along email. Journal of Advertising Research, 333-348.
  23. Richins, M. L. (1983). Negative Word of mouth by dissatisfied consumer: A pilot study, Journal of Marking, 68-78.
  24. Schiffman, L.G. & Kanuk, L.L. (2000). Consumer behavior. Wisconsin: Prentice Hall.
  25. Strutton, D., Taylor, D., & Thompson, K. (2011). Investigating generational differences in e-WOM behaviours: For advertising purposes, does X = Y? International Journal of Advertising, 30(4), 559-586.
  26. Trusov, M., Bucklin, R., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73, 90-102.
  27. Voss Jr, P. (1984). Status shifts to peer influence. Advertising Age, 17(10), 1-10.
  28. Williams, P., & Aaker, J.L. (2002). Can mixed emotions peacefully coexist? Journal of Consumer Research, 28, 636-649.
  29. Yan, X., Shah, A., Zhai, L., Khan, S., & Shah, A. (2018). Impact of mobile electronic word of mouth (EWOM) on consumers purchase intentions in the fast-causal restaurant industry in Indonesia. Proceedings of the 51st Hawaii International Conference on System Sciences.
  30. Zaltman, G., & Wallendorf, M. (1983). Consumer behavior: Basic findings and management implications. NY: John Wisley & Sons.
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