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ELECTRONIC WORD OF MOUTH (EWOM) AND ITS EFFECT ON CONSUMERS' DECISIONS TO BUY PRODUCTS AND SERVICES IN TRADITIONAL STORES IN JORDAN.

ABSTRACT

Although buying over the internet is not common in Jordan, available internet technology and infrastructure has enabled Jordanians to utilize the internet to communicate with the virtual world using social networks and blogs. This research investigates how best to utilize electronic Word of Mouth (eWOM) to affect future consumer purchases in traditional stores and to explore the factors that contribute to the success of this phenomenon. The paper begins by defining 'word of mouth' and investigating the differences between traditional word-of-mouth (WOM) and electronic word-of-mouth (eWOM) in Jordan. The paper then examines those factors that affect the diffusion and effectiveness of eWOM. Research was implemented using a sample of 1600 undergraduate students. Variables, such as message source credibility, level of product involvement, message content, and homophily, were found to play an important role in eWOM acceptance and effectiveness. Several findings were found and recommendations made that could benefit both academics and business owners. Suggestions for future research were given.

Keywords: consumers' buying decisions, marketing, Jordan

INTRODUCTION

The diffusion of information technology and the adoption of the internet in our everyday activities affect the way people spend their time and the way they interact with others. One form of interaction that has developed in the last few years and which has had a tremendous effect on peoples' social interaction is the use of social networks. Virtual communities like Facebook, Twitter and social blogs constitute important mediums of communication. In these virtual communities, people tend to build close groups, which they trust and with whom they share their opinions and interests. The sharing of groups' ideas affects the way people think, negotiate, express their feelings and make decisions. This interpersonal communication between people over the internet and through the use of different electronic devices is known as electronic Word of Mouth (eWOM) (Henning-Thrau et al., 2004). eWOM has an important influence on consumers' evaluation of products and buying decision. Consumers visit review websites, social networks and social blogs with questions about products and services before buying a product. This makes eWOM an important factor in the buying decision and a major source of information (Duan et al., 2008). Marketers and online business owners have realized the power of eWOM in motivating and influencing consumers' decisions and preferences, especially when it comes to communication between people with no prior relationship (O'Reilly & Marx, 2011).

Current studies have concentrated on investigating the influence of eWOM in the western world and very limited, if any, attention has been paid to investigating this phenomenon in the Middle East. The limited amount of investigation of eWOM effect on consumer behavior in Middle Eastern countries has motivated the researcher to investigate this area of research. This research will help toward gaining an understanding of how eWOM can enable decision-makers to better communicate their messages and ideas to prospects by using social media and online communities, with the intention of changing their minds and affecting their decisions. This study will also help marketers and business owners understand the best way to build close trusted relationships with prospects through understanding those factors that affect building such a relationship, which will enable decision makers to better anticipate changes in peoples' decisions and prepare them to be proactive.

This paper is organized as follows: first, the researcher reviews the literature on electronic word of mouth (eWOM) and the factors affecting the effectiveness of eWOM. Second, the researcher introduces the research hypotheses and methodology. Lastly, the researcher lists findings and discusses both the academic and practical implications of the study.

Importance and Purpose of this Research

In Jordan, the widespread use of the internet continues to grow. Despite the difficulties reported by some researchers such as trust, security and technology acceptance in Jordan, the number of people using the internet has been increasing dramatically (Abbad et al., 2011; Yasin & Yavas, 2007). The Department of Statistics (2013) reported that Jordan has now 4.3 million internet users, which constitutes about 62% of the country's seven million population. Another study conducted by the Telecommunication Organizing Commission of Jordan (TOC) ( Alsardia & Hartini, 2013) shows that the number of cell phones subscriptions sold in the Kingdom has exceeded nine million and includes a spread of third and fourth generation services (3G+ and 4G+ technology). Mobile phones are in demand due to low rates offered by telecommunication companies who operate in a highly competitive environment strictly governed by government regulations.

The internet has become a major part of the average Jordanian's life. Though electronic commerce is still facing difficulties in Jordan (Abbad et al., 2011) and the adoption of internet buying is still a challenge for many Jordanians (Alkailani & Kumar, 2010), which could be attributed to " non-people" factors, Jordanians still use the internet heavily at work and at home. They use it for banking, emailing, making travel reservations, watching videos and social networking. Jordanians are also active users of social networks, such as Facebook, Twitter and social blogs. Jordanians are exposed to many sources of information on a daily basis, such as Mobile SMS messaging from companies with offers to buy different products, advertising about products and services over website portals, search engines and word of mouth spread daily over social networks and social blogs.

This study represents one of few research papers in the area of eWOM and its effect on consumer decision making in Jordan. It explores the relationship and effect of electronic Word of Mouth on peoples' intention to buy products sold in traditional stores. It also sets out to familiarize marketers, business people, private and public decision makers and academic researchers with the role that eWOM can play in changing the Jordanian peoples' attitudes and decisions. The study establishes a solid model for the relationship between eWOM and peoples' intention to make decisions that can be useful for future research. Finally, recommendations are made that will help marketers and business owners spread positive WOM about their products and services that will influence consumer buying decisions.

LITERATURE REVIEW

In this section, the differences between Word of Mouth (WOM) and electronic Word of Mouth (eWOM) and how they influence purchasing decisions are discussed. The researcher also reviews some of the factors that affect the eWOM phenomena.

From Word of Mouth (WOM) to Electronic Word of Mouth (eWOM)

Research into Word of Mouth (WOM) in general and electronic Word of Mouth (eWOM) in particular is new. Thus, most definitions and terminology related to this phenomenon still overlap. Word of Mouth (WOM) is considered to have a prevailing, persistent and credible impact on consumer behavior, which is the result of social communication, also known as "Buzz Marketing" and "Viral Marketing," where consumers depend on other consumers' opinions when making decisions (Goldsmith & Horowitz, 2006). WOM is defined as the communication between two parties; namely, the receiver and the sender whom the receiver trusts and thus considers that the message received is authentic and credible (Sundaram et al., 1998). Similarly, Westbrook (1987) has defined WOM as "all informal communication directed at other consumers about the ownership, usage, or characteristics of particular goods and services or their sellers." When it comes to making decisions, WOM is considered one of the most influential sources of information that affects peoples' opinions and attitudes (Breazeale, 2008; Cheung et al., 2008). In marketing, WOM is defined as the act of exchanging marketing information among consumers, which can lead to changing consumer attitudes and behaviors related to products and services (Chu & Kim, 2011). WOM has also been proven to have an influence on perceptions of products and services that lead to changes in buying behavior and the decision making process (Sweeney et al., 2008), affect consumer purchases (Doh & Hwang, 2007) and have more influence on consumers than traditional marketing activities (Vilpponen et al., 2006; Trusof et al., 2009).

The emergence of the internet, information technology and mobile technology has created new ways of communication between people, and the communication process between people has therefore changed (Vilpponen et al., 2006). Instead of face-to-face communication, people now are communicating virtually with people they have never met or even known. This, and other factors, has led to the emergence of electronic Word of Mouth (eWOM). eWOM is 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). In the context of marketing, eWOM refers to the act of exchanging marketing information among consumers online, which can be done through emailing, discussion forms, instant messaging, blogs, review sites, online virtual communities, chat rooms and social networking sites such as Facebook.com and Twitter (Goldsmith & Horowitz, 2006). eWOM becomes "viral" when the message is convincing and sounds persuasive to the recipients (Leskovc et al., 2008). Individuals can now provide their personal judgment, reactions and opinions and have them accessible by anyone who has access to the internet (Chrysanthos, 2003).

Although WOM and eWOM differ in certain aspects, they both enable consumers to know about other consumers' positive and negative experiences related to products and services purchased (Henning-Thurau et al., 2004). However, eWOM differs from traditional WOM in multiple ways. WOM usually takes place face-to-face, while eWOM takes place using the internet between people who have never met (Fong & Burton, 2006). eWOM is more influential than traditional WOM because participants using eWOM share similar interest (Kozinets, 1999). eWOM communication is thought to provide more authentic and unbiased information because of its anonymous nature (Steffes & Burgee, 2009). Research has also shown that motives for WOM communication are different from eWOM communication (Henning-Thurau et al., 2004). Some researchers (Bickart & Schnider, 2001) think that the effect of eWOM is more credible and has more reliance than traditional WOM. Using internet technologies means that eWOM is faster in diffusing and sharing information between groups than traditional WOM. In addition, eWOM is more measurable than traditional WOM and the format, quantity and persistence of eWOM communications is more observable and vaster in quantity compared to information obtained from traditional contacts in the offline world (Chatterjee, 2011; Resnick, Zeckhauser, & Avery, 1995; Li & Hitt, 2010; Dellarocas, 2001; Steffes & Burgee, 2009).

Factors Affecting the Degree of Influence of eWOM

The importance of eWOM has been established by different researchers in different areas of interest, i.e., in customer value and loyalty (Gruen et al., 2006), Web reputation (Park & Lee, 2009), product information inference (Lee & Lee, 2009), interactivity of blogs (Thorson & Rodgers, 2007), consumer behavioral intention (Park & Lee, 2009) and in consumer engagement in networking sites (Chu & Kim, 2011). Research on eWOM mainly focuses on the effect of eWOM on buying intentions over the internet. However, in the case of buying intention, in Jordan, acceptance of internet buying is limited due to cultural barriers (Alkailani & Kumar, 2011), though Jordanians are very active users of social networks and emailing. This research investigates how best to utilize eWOM to affect future consumer purchases in traditional stores in Jordan and explores the factors that contribute to the success of this phenomenon.

eWOM has been effective on the internet since Websites, social blogs, etc. were established. Through these sites, customers can read posts every time they review product information (Haubl & Trifts, 2000). eWOM is incorporated into different electronics platforms, such as Amazon.com and ebay.com, where consumers post their positive and negative experiences, as well as rate and review ratings and reviews (Liu, 2006). In the marketing communication process, both verbal and non-verbal, the sender encodes the message and delivers that message through a communication medium to the recipient. The recipient decodes the message to get meaningful information.

In non-verbal communication, especially when communication takes place in a virtual world, the credibility of both the sender and the message is very important (Park & Kim, 2008), especially when face-to-face communication is preferred for cultural reasons (Alkailani et al., 2012). Globalization, education and the use of the internet and related electronic devices and applications have facilitated the acceptance of virtual non-face-to-face communication among the new generation (Adam et al., 1997).

Trust and perceived risk are very critical factors in the internet environment. Virtual environments are usually characterized by lack of trust and high perceived risk (Alkailani & Kumar, 2011). Perceived risk refers to the fact that consumers make purchase decisions with a degree of uncertainty often stemming from inadequate, inaccurate information. When consumers perceive a degree of risk when buying over the internet, they try to minimize the level of risk by collecting more information about the product and the vendor from credible sources, such as their virtual friends (Wangeheim & Bayoun, 2004). In eWOM communication, the sender is unknown (virtual) and trust is a major factor when it comes to credibility and trustworthiness. The competence and credibility of the source affects both the audience perception of the message and the way the audience will respond (First, 2002). Source credibility refers to how much the receiver believes in the sender. It is the attitude towards the source that affects the receiver's level of belief about what the source claims (West, 1994). It is also defined as the extent to which an information source is perceived to be believable, competent and trustworthy by receivers (Petty & Cacioppo, 1986). The persuasiveness of a message depends on the number of positive attributes the sender possesses. Information provided by highly credible sources is perceived to be useful and reliable and thereby facilitates knowledge transfer (Ko et al., 2005). For the information message to be convincing the source should be credible and the message should be persuaded by its content (Park & Lee, 2009; Bickart & Schindler, 2001; Kiecker & Cowles, 2001). Credibility of the source depends on the degree of sufficient knowledge about the product the sender has (Cowls, 2000). This leads to the following hypothesis:
H1: The higher the credibility of the source, the more effective the
eWOM.


Consumers usually seek more information when the product is of high involvement. High involvement products are characterized by a need for an intensive amount of information and takes more time and effort before making the buying decision (Kotler & Armstrong, 2012) the individual level of involvement affects the decision-making process and the persuasive effects of the EWOM message appeal, type and message source credibility vary with the individual level of involvement. Involvement can be situational or enduring (Celsi & Olson, 1988). Situational involvement is a temporary involvement with a product when making a purchasing decision. Enduring involvement is a stable involvement with a product over a long period of time, due to personal interest. Customers with higher levels of involvement are motivated to read more reviews and recommendations. This leads to the second research hypothesis:
H2: The higher the levels of product involvement, the more customers
are affected by eWOM.


Message content and characteristics, such as valence, volume and rating of communication, have been receiving a lot of attention (Sweeney, Soutar, & Mazzard, 2007). However, eWOM is more measurable and observable. Some researchers have extracted eWOM messages directly from websites and used the panel data to examine the impact of eWOM messages on product sales (Cheung, 2010). For the message to be persuasive, it should be rich. Richness of the message content refers to the depth, intensity and vividness of the message itself. Richness includes content aspects, such as the language used and the degree of storytelling or depth of information involved in the message (Wixom & Todd, 2005).
H3: The higher the message content richness, the more effective the
eWOM.


Tie strength refers to the level and intensity of the social relationship between consumers. It varies greatly across a consumer's social network. Consumers have a wide range of relationship ties within social networks ranging from strong ties, e.g., close friends and family members, to weak ties. Tie strength is highly associated with homophily, which refers to the similarities in characteristics of individuals in relationships, such as age, gender, education and social status (Rogers, 1983). Homophily leads to rapport, which is the perceived level of similarity between eWOM readers and senders. Rapport is an affective bond that a person feels toward another person that arises from shared preferences, tastes and lifestyles (Smith et al., 2005). Rapport affects interpersonal communication and customer trust (Gilly et al., 1998). The ability of WOM to operate within a consumer network is influenced by the tie strength of social relationships between consumers (Bansal & Voyer, 2000) and by similar or dissimilar consumers (Steward & Conway, 1996). This leads to the next hypothesis:
H4: The more similar the personal characteristics between the sender
and receiver,  the more effective the eWOM.


Data Collection Procedure

Students participating in this research received an announcement in their classes about the study through their professors. Students were directed as to how to participate in the online study. Students completed the study by clicking a link which took the participant to an online survey where they could fill the survey out at their convenience. All participants were entered into a drawing for five gift cards of $50 each for the Carfure store in Jordan. The approximate time it took to complete the survey was 15 minutes. The entire data collection period was six months starting on June 1, 2013 and ending December 30, 2013.

METHODOLOGY

Procedures and Samples

The population of this study consisted of all students studying for their undergraduate degrees at Business schools at both public and private universities in Jordan (15000 students). A random convenience sample of 2000 students was chosen from this population. Data was collected using an online survey. The survey was emailed to university professors teaching undergraduate courses at different universities. Professors, in turn, forwarded the survey link to their students and encouraged them to fill out the survey. 1600 completed questionnaires were used in this study.

Table (1) shows sample characteristics in terms of Gender (male, female), University Type (public, private) and Place of Residence (city, suburban). The final sample size was 1600, including 845 males (53%) and 755 females (47%). The respondents came from public universities (60%) and private universities (40%). Most of the participants reside in major cities (75%).

Survey Development

This research studied four variables: Message source credibility, message content, level of product involvement, and homophily. The researcher utilized scales and items from previous research studies to build the survey for measuring these constructs (Wangeheim & Bayoun, 2007; Bickart & Schindler, 2001; Sweeney et al., 2008; Cheung & Thadani, 2012 ; Wixom & Todd, 2005; Smith et al., 2005; Bansal & Voyer, 2000).

Data Analysis and Results

Preliminary regression analysis was conducted using mean of items representing the variables being studied in this research. The preliminary multiple regression tests allowed us to check for outliers and influential cases. The test included Mahalanobis distance, Cook's D, leverage standardized DFBeta, and standardized residuals. Cases that exceeded the limit on more than one measure were discarded (Hair et al., 2007). Inspection of these measures resulted in deleting 20 surveys. The cases that were deleted had residuals greater than 3.5 and Mahalanobis distance greater than 30 (Hair et al., 2006). The final number of usable questionnaires was 1600.

SPSS 18.0 was used to complete a multiple regression analysis of the survey results. The model was tested using [beta] values for all participants (n = 1600), as shown in the model below. The study results showed that message source credibility has the most significant effect on perceived eWOM effectiveness ([beta] = 0.68**, R2= 0.44). The results also showed product involvement has an impact on eWOM effectiveness. Customers who are more involved with a product are more likely to accept and use positive eWOM ([beta] = 0.25*, R2= 0.18). Results also showed that message content also constitutes an important factor on eWOM effectiveness ([beta] = 0.45*, R2= = 0.10). Customers are more willing to accept information posted when they share similar characteristics with the sender. However, homophily had a smaller effect on eWOM effectiveness ([beta] = 0.32**, R2= 0.07). Based on the results, we accept all the hypotheses listed (H1, H2, H3 and H4).

Table 2 shows the bi-variat correlation coefficients between variables. The findings demonstrate that all variables in the model are positively correlated with each other and are sizable and significant.

DISCUSSION AND CONCLUSIONS

This study investigated the effect of eWOM on non-online buying behavior. The study developed and tested a theoretical model that contributes to the eWOM phenomenon. This research also extended the concept and literature of eWOM. The findings contribute to an understanding of factors affecting the effectiveness of eWOM in Jordan in several ways. First, the study proposed a theoretical model which explains eWOM determinants and added valuable information to the existing body of literature. Second, the study provided empirical support of message source credibility. Message content, product involvement, and homophily have an important impact on eWOM effectiveness. Among all the variables listed, message source credibility showed the most significant effect followed by message content. Results indicate that the more credible the source of the message and the more authentic the message content are, the higher the influence eWOM has on consumers' decisions to buy a company's products and services. So, business owners and marketers should take these two variables into consideration and emphasize positive product image and attributes to customers. Satisfied customers will, indeed, spread positive eWOM over social blogs and networks to share with others.

Marketers should also pay attention to any negative information that might be posted or communicated to customers via emails, social blogs and social network sites. Businesses should get involved in online communities in one way or another to provide customers with relevant and accurate information about a company, its products and services.

Product involvement was also shown to be a factor of influence on eWOM effectiveness due to the high price, effort and time associated with high involvement products. Customers look on these types of products as risky and that sufficient information should be gathered from experienced people before a decision is made. Unexpectedly, homophily showed the least effect on eWOM effectiveness. This could be attributed to the virtual nature of the internet and how people now easily communicate with people they have never before met or seen with confidence. In conclusion, businesses should pay attention to the fact that eWOM is not only a powerful tool for communication, but it is as powerful as traditional communication strategies. A positive eWOM will affect consumer perception about a company, its products and services. For managers seeking to use eWOM as a promotional tool, this study provides some insights for them. Although most of the variables under study are beyond the control of the marketing management, study shows that information represent a major effecting factor when customers evaluate and decide if they need more information to decide which products to buy. To get maximum benefits from using eWOM, management should invest heavily in electronic customer relationship management (eCRM) and effective digital promotional tools.

LIMITATIONS AND FUTURE RESEARCH

This research raises some important issues that present an avenue for future research. While previous research has mainly focused on western cultures, mostly individualist, the present study investigates a new collectivist culture. Previous research also has investigated the effect of eWOM on online buying purchases, while this study investigates the effect of an online phenomenon (eWOM) on a non-online behavior (buying in traditional stores) and provided suggestions on how effectively utilize it.

This research has several limitations. First, a convenience sample from Jordanian students was used. Although this restriction does not necessarily bias results, it indeed affects its general izability. Second, a translated online survey was used to collect data and students were asked to consider only those situations where they needed to consult others about their future purchases. Third, the model was simplified and some of the intervening and moderating variables were not included. The model did not consider the moderating effects of some important demographic variables, such as gender. Fourth, only positive eWOM experiences were considered and, finally, this research considered only some of the factors that affect eWOM effectiveness.

Future research is needed that includes more variables and to verify the study results for other samples. The researcher urges future researchers to consider more variables (intervening and moderating) to investigate the effectiveness of eWOM in new settings and environments and to consider the limitations of the present study for future research.

REFERENCES

Abbad, M., Abbad, R., & Saleh, M. (2011). Limitations of e-commerce in developing countries: Jordan case. Electronic Business and Society: Contemporary Middle-Eastern Issues, 4(4), 280-291.

Adam, N., Awrebuch, B., Sloinm, J., Wegner, P., & Yesha, Y. (1997). Globalizing business, education, and culture through the internet. Communications of the ACM, 40(2).

Alkailani, M., Athamneh, A., & Azzam, I. (2012). Replicating Hofstede in Jordan: Ungeneralized, reevaluating the Jordanian culture. International Business Research, 5(4).

Alkailani, M, & Kumar, R. (2011). Investigating uncertainty avoidance and perceived risk for impacting internet buying: A study of three cultures. International Journal of Business and Management, 6(5), 76-92.

Alsardia, S., & Hartini, A. (2013). The moderating effect of role stressor on the influence of evolutionary process change factors in internal customer satisfaction in telecommunication in Jordan. Asian Social Science, 10(4).

Awad, N., & Ragowsky, A. (2008). Establishing trust in electronic commerce though online word of mouth: An examination across genders. Journal of Management Information Systems, 24(2)101-121.

Bansal, H., & Voyer, P. (2000). Word-of-mouth processes within a services purchase decision context. Journal of Service Research, 3(2), 166-177.

Bickart, B., & Schindler, R. (2001). Internet forums as influential sources of consumer: Information. Journal of Interactive Marketing, 15(3), 31-40.

Breazeale, M. (2008). Word of mouse: An assessment of electronic word-of-mouth research. International Journal of Market Research, 51(3), 297-318.

Celsi, R., & Olson, J. (1988). The role of involvement in attention and comprehension processes. Journal of Consumer Research, 15(2), 210-224.

Chatterjee, P. (2011). Drivers of new product recommending and referral behavior on social network sites. International Journal of Advertising: The Review of Marketing Communications, 30(1), 77-101.

Cheung, C., & Thadani, D. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54 (1), 461-470.

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), 229-47.

Cheung, M., Luo, C., Choon, L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9-38.

Chrysanthos, D. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms.

Chu, S., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 301(1), 47-75.

Doh, S., & Hwang, J. (2007). How consumers evaluate eWOM (electronic word of mouth) messages. Cybersycology and Behavior, 12(2), 193-197.

Dellarocas, C. (2001). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 1407-1424.

Duan, W., Gu, B., & Whinston, A. (2008). The dynamics of online word-of-mouth and product sales-an empirical investigation of the movie industry. Journal of Retailing, 84(2), 233-244.

Fong, J., & Burton, S. (2006). Electronic word of mouth: A comparison of stated and revealed behavior on electronic discussion boards. Journal of Interactive Advertising, 6(2), 53-62.

Gilly, M., Graham, J., Wolfinbarger, M., & Yale, L. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26, (2), 83-100.

Goldsmith, R., & Clark, E. (2008). An analysis of factors affecting fashion opinion leadership and fashion opinion seeking. Journal of Fashion Marketing & Management, 12(3), 308-322.

Goldsmith, R., & Horowitz, E. (2006). Measuring motivations for online opinion seeking. Journal of Interactive Advertising, 6(2).

Gruen, T., Osmonbekov, T., & Chaplewski, A. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business Research, 59(4), 449-456.

Haubl, G., & Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Science, 19(1), 4-21.

Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of Services Research, 13(3), 311-330.

Henning-Thurau, T., Qwinner, K., Walsh, G., & Gremier, D. (2004). Electronic word of mouth via consumer opinions platforms: What motivates consumers to articulate themselves on the internet. Journal of interactive Marketing, 18(1), 38-52.

Jansen, B., Zhang, M., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Science and Technology, 60(11), 2169-2188.

Kamtrain, M. (2012). The effect of electronic word of mouth, trust and perceived value on behavioral intention from the perspective of consumers. International Journal of Academic Research in Economics and Management, 1(4).

Kotler, P., & Armstrong, G. (2012). Principles of marketing. New Jersey: Prentice Hall.

Kozinets, R. (1999). E-tribalized marketing? The strategic implications of virtual communities of consumption. European Management Journal, 17(3), 252- 264.

Leskovc , J., Adamic, L., & Huberrman, B. (2008). The dynamics of viral marketing. ACM Transactions on the Web (TWEB), 1(1).

Lee, J., & Lee, J. (2009). Understanding the product information inference process in electronic word-of-mouth: An objectivity-subjectivity dichotomy perspective. Information and Management, 46(5), 302-311.

Li, X., & Hitt, M.(2010). Price effects in online product reviews: An analytical model and empirical analysis. MIS Quarterly, 34(4),809-831.

Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenues. Journal of Marketing, 70, 74-89.

Miao, Y., & Fan, Y. (2012). Effect of electronic word-of-mouth on consumer purchase intention: The perspective of gender differences. International Journal of Electronic Business Management, 10(3), 175-181.

Nabi, R., & Hendriks, A. (2003). The persuasive effect of host and audience reaction shots in television talk shows. Journal of Communications, 53(3), 527-543.

O'Reilly, K., & Marx, S. (2011). How young, technical consumers assess online WOM credibility. Qualitative Market Research: An International Journal, 14(4), 330-359.

Park, C., & Lee, T. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(l),61-67.

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(4), 399-410.

Resnick, P, Zeckhauser, R., & Avery, C. (1995). Roles for electronic brokers in toward a competitive telecommunication industry: Selected papers from the 1994 telecommunications policy research conference. G. W. Brock (Ed.). Mahwah, NJ: Lawrence Erlbaum Associates, pp. 289-304.

Smith, D., Menon, S. & Sivakumar, K. (2005). Online peer and editorial recommendations, trust, and choice in virtual markets. Journal of Interactive Marketing, 19(3), 15-37.

Steffes, E., & Burgee, L. (2009). Social ties and online word of mouth. Internet Research, 19(1), 42-59.

Sun, T., Youn, S., Wu, G, & Kuntaraporn, M. (2006). Online word-of-mouth (or mouse): An exploration of its antecedents and consequences. Journal of Computer-Mediated Communication, 11(4), 1104-27.

Sundaram, D., Mitra, K, & Webster, C. (1998). Word of mouth communication: A motivational analysis. Advances in Consumer Research, 25, 527-53.

Sussman, S., & Siegel, W. (2003). Informational influence in organizations: An integrated approaches to knowledge adoption inform. Systems Research, 14(1), 47-65.

Sweeney, J., Soutar, G., & Mazzarol, T. (2008). Factors influencing word of mouth effectiveness: Receiver perspectives. European Journal of Marketing, 42(3/4), 344-364.

Thorson, K., & Rodgers, S. (2007). Relationships between blogs as eWOM and interactivity, perceived interactivity, and parascoial interaction. Journal of Interactive Advertising, 6(2), 34-44.

Trusov, M., Bucklin, R., & Pauwel, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73(5), 90-102.

Vilpponen, A., Winter, S., & Sundqvist, S. (2006). Electronic word-of-mouth in online environments: Exploring referral networks structure adoption behavior. Journal of Interactive Advertising, 6(2), 63-77. 35 (2), 233-249

Wangeheim, F., & Bayoum, T. (2007). The chain from customer satisfaction via word-of-mouth referrals to new customer acquisition. Journal of the Academy of Marketing Science.

Wathen, C., & Burkell, J. (2002). Believe it or not: Factors influencing credibility on the web. Journal of the American Society for Information Science and Technology, 53(2), 134-144.

Westbrook, R. A. (1987). Product/consumption-based effective responses and post purchase processes. Journal of Marketing Research, 24, 258-270.

Wixom, B., & Todd, P. (2005). A theoretical integration of user satisfaction and technology acceptance. Information System Research, 16(1), 85-102.

Yasin, M., & Yavas, U. (2007). An analysis of e-business practices in the Arab culture. Cross Cultural Management-An International Journal, 14(1), 68-73
TABLE 1
Descriptive statistics

Demographics            Frequency %
Gender        Male       845      53
              Female     755      47
University    Public     960      60
Type          Private    640      40
Place of      City      1200      75
Residence     Suburban   400      25

TABLE 2
Zero-order Correlations between Variables

1.eWOM effectiveness    -
2. Message Source
Credibility                0.533**
3. Product Involvement  ** 0.269   ** 0.269    -
4. Message Content      ** 0.546   ** 0.27     0.546**      -
5. Homophily               0.244**    0.289**  0.395**   ** 0.533    -

**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
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Author:Alkailani, Mahmud
Publication:Journal of Competitiveness Studies
Date:Dec 22, 2016
Words:5451
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