International Research Journal of Social Sciences______________________________________ ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci. International Science Congress Association 53 Analyzing the Effect of Electronic Word of Mouth on Tourists’ attitude toward Destination and Travel Intention Zarrad H. and Debabi M.2 National Institute of Applied Sciences and Technology, University of Carthage, TUNISIA High School of Business, University of Manouba, TUNISIAAvailable online at: www.isca.in Received 18th January 2015, revised 28th February 2015, accepted 27th March 2015 Abstract This research was aimed to identify the theoretical arguments and hypotheses about the interrelationships between electronic word of mouth (eWOM) and tourists’ attitudes towards specific destinations and actual travel intentions. To this end, we conducted a structural equation model (SEM) to test the relationship between our research variables. An empirical test of the model is reported using data collected from a sample of 219 foreign tourists who participated in online communities and travelled to Tunisia throughout the research period. Our results illustrate that eWOM communication has a credible influence on both attitude and intention to revisit Tunisia as a destination. Some further theoretical and marketing implications are discussed in this study.Keywords: eWOM, Consumer behavior, Tourists’ attitudes, Travel intention, SEM. Introduction Word of mouth (WOM) is the communication between consumers about a specific product, service, or a company in which the sources are considered independent of commercial influence. WOM refers to informal communication directed at other consumers about the ownership, usage, or characteristics of particular goods and services or their sellers. Research indicates that word of mouth play an increasingly important role in shaping consumers’ attitudes and purchase behaviors. In the growing online social communications, electronic word of mouth (eWOM) has been an important topic to business and marketing researchers. Recent studies have examined the influence of Internet-based eWOM on product success, virtual consumer community and explored how the process of WOM communication influences customer decisions and behavior in an online environment2,3. In the tourism industry, the effect of eWOM is especially strong. Intangibles such as tourism services cannot be evaluated in advance of use. Hence, purchasing intangible products and services involves higher risk. Then, customers are more dependent on the online interpersonal influence and eWOM4,5. Attitude significantly influences tourists’ behavioral intention to visit a destination. The relationship between eWOM, tourist attitude toward destination and travel intention is therefore significant. Several studies showed that the influence of user reviews has a particularly significance on the experience goods, as their quality is frequently unknown before consumption and consumers need to rely on WOM and online reviews to make decisions. In fact, most tourists use internet and online resources as their major information source. In the light of the growth rate of e-WOM’s reach and influence, it is very interesting to examine what makes certain opinions more influential than others. In addition, marketers are becoming increasingly interested in making use of eWOM as a new communication tool10. Furthermore, behavioral intention has been assumed to be a key factor which strongly correlates with observed behaviour11. eWOM affects tourists’ attitudes and travel intentions towards certain destinations12,13. In addition, there is a significant relationship between individual tourists’ attitudes and travel intentions. Figure-1 shows the conceptual framework drawn for this study. Figure-1 Theoretical Research Model International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 54 In the current study, we empirically examine the relationships between eWOM and tourist attitudes towards Tunisia and travel intentions. Hypothesis: eWOM and tourism: WOM can play a key role for service providers, as intangibility makes the pre-purchase trial of services impossible. WOM as a source of consumer information has become a particularly important and influential concept within services than in the goods context due to their intangibility and higher perceived risk14. Research has widely demonstrated that service consumers were confident in personal sources of information. Indeed, personal information has a greater impact on service purchase decisions15. Therefore, WOM can play a particularly significant role in those services that have significance in high credence qualities, such as the tourism industry. The literature indicated that WOM has an impact on the receiver’s awareness16, attention17, consideration18, brand attitudes19, intentions18, and expectations20. The advances of the Internet has allowed consumers to share product-related information, thereby increasing the potential and significant impact of WOM21,6. Recent tourism-related research has shown this tendency has an important impact on tourism-related products and services in various word countries22. eWOM is defined as "all informal communications directed at consumers through internet-based technology related to the usage or characteristics of particular goods and services or their sellers"22. The presence of eWOM communication with its characteristics that differ from traditional WOM has been given its distinctive characteristics by the available studies in tourism marketing, mainly with regard to the topic of tourist behavior. Many researchers in the tourism area have confirmed the influence of interpersonal communications in the tourism industry and identified how online travel communities can have influence on tourist destination choice23. They conclude that the volume of information on eWOM was significantly correlated with its impact on consumer behavior. Additionally, it was found that that eWOM plays a significant role in the tourism decision making process24,25. In the travel industry, eWOM is an important reference for travel decision-making, as well as on choice of travel products such as travel destinations, hotels and restaurants26. Prospective travellers rely on eWOM to facilitate the decision making process27. Research suggests that travelers consider eWOM to be more trustworthy than other information sources28,6. A number of studies related to e-WOM have identified a number of key indicators and effects of e-WOM, including factors influencing e-WOM intentions and the impact of the e-WOM affecting consumer decision making behavior. Although many factors have been investigated in different disciplinary areas including tourism, marketing and advertising23,29. Attitude towards the destination: Attitude refers to the person’s overall evaluation of performing the behaviour. Several studies have shown that the intention was determined by the attitude towards the behaviour30. Attitude toward a behavior has been defined as the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question31. In general, the more favorable the attitude toward the behavior, the stronger will be an individual’s intention to adopt the behavior31. It is assumed in the literature that attitude toward a behavior represents the perceived consequences of the behavior and the person’s evaluation of the significance of the consequences32. Another argument assumes that attitude is favorability or unfavorability feelings toward performing a behavior33; representing a person’s overall positive and negative beliefs and evaluations of the behavior34. Several studies have shown that behavioral intentions are a function of attitudes towards the destination. Furthermore, marketing literature has demonstrated that attitude has a strong positive effect on intentions35. In our case, the target behavior is the travel intentions tourists, and attitude is that towards visiting Tunisia. Interpersonal communications have long been influential in the tourism industry. Research has suggested that online WOM communication plays a major role in shaping attitudes and behaviours of consumers36. Indeed, an increase in online intention to review other consumers’ opinions about such service or product increases and improves awareness of travelers’ attitudes25,37. Hence, against these findings we propose the following hypothesis: : eWOM is positively related to tourists’ attitude towards the destination. H: There is a positive significant relationship between attitude and intention to choose a destination. Behavioral intention: Intentions are assumed to capture the motivational factors that influence a person’s behavior31. Thus, they represent how a person is willing to adopt a behavior, and how much effort he is likely to deploy toward that behavior. Behavioral intentions are an indication of the readiness to undertake a given behavior, and are assumed to precede actual behavior38. Behavioral intention has long been recognized as an important mediator in the relationship between behavior and International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 55 attitude31,39. The literature concerning the pre-purchasing stages in the receiver’s decision-making process show that the receiving WOM affect the receiver’s awareness, attitudes, product evaluations, intentions, and expectations40. Furthermore, positive WOM leads to more intensive intention to purchase a specific product than negative WOM41. Researchers examined the impacts of online product reviews on the relative sales of two online book shops using publicly available data from two leading online booksellers42. The findings of their research illustrate that such an online communication significantly affects other consumers' purchasing behavior. In addition, it was found that online know-how forums had an impact on purchase behavior. Previous studies have indicated that online consumer reviews as eWOM has a direct impact on behavioral intentions 43,44. Other research has shown that the influence of eWOM information quantity on purchase intention was significant45,46. eWOM information can help consumers make purchase decisions10,47. We therefore hypothesize that: : eWOM has positive influence on travel intention. Methodology Sample design and data collection: To test our research hypotheses, a field survey was conducted in Tunisia. As a well-established tourist destination, Tunisia disposes of a beautiful Mediterranean setting with wide, sandy, attractive beaches. This country unites various geographical, climatic and cultural characteristics which are ideal for resort tourism, and stimulate the interest of many international tour operators. The study’s target population was international visitors. Quantitative approach with self-administered questionnaire method has been used in order to collect empirical data. A total number of 219 respondents based on cluster sampling were participated in this study. The questionnaires were collected at international hotels in the most known touristic towns in Tunisia (Gammarth, Hammamet, Djerba and Mahdia). Data collection was done June and September 2014. Majority of the respondents were female and they contributed 63.3% of the total respondents. In terms of level of education achieved by respondents, 47.3% reported high school education, 13.2% primary school, and the remaining 29.6% achieved college level education. Furthermore, our study covered different nationalities. Italian and French (34.7% of the sample) were the most dominant nationalities Most respondents were higher than 40 years of age (43.8%). With regard to visiting frequency, 52.2% of respondents were first timers in the destination and 47.8% were re-visiting. Finally, most respondents travelled to Tunisia during their holidays (67.9%). Measurement scale: To ensure content validity of the scales, the selected items are mainly adapted from previous studies. The survey covered the following parts: eWOM, tourists’ attitudes toward destination (Tunisia), travel intentions and demographic characteristics of tourists.We measured eWOM through six items48. The second section presents the scale of attitude with six items (very bad/very good, very worthless/very valuable, and very unpleasant/very pleasant) that were modified to suit the tourist context49. Finally, travel intentions were measured with three items. The final questionnaire included a total of 12 items, and the format was a five-point Likert type scale ranging from strongly disagree (1) to strongly agree (5). Data analyses: Confirmatory Factor Analysis (CFA) was performed to examine the reliability and validity of the measurement, and the structural equation modeling techniques (Amos 17) were used to evaluate the casual model. CFA is used to specify which indicators define each latent construct50. We assessed several Goodness-Of-Fit (GOF) measures, such as Chi-square statistic (), normed chi-square statistic (/df), goodness-of-fit index (GFI), root mean square error of approximation (RMSEA), comparative fit index (CFI) and standardized root mean squarer residual (SRMR). (/df) is less than 3.051, while SRMR value should small (lower than 0.05) in a well fitting model lower than 0.0552. An RMSEA less than 0.08 and a CFI greater than 0.95 represents a good-fittingmodel53,54. Internal consistency was estimated using Cronbach's alpha coefficient and convergent validity was evaluated using the Average Variance Extracted (AVE). The Cronbach alpha value which is greater than 0.7 is acceptable55,56. AVE values above 0.50 are considered to be adequate57. Results and DiscussionResults: The results indicate that eWOM positively impact tourists’ attitudes and travel intentions towards Tunisia. Additionally, there is a positive and significant relationship between attitude toward visiting the destination and intention to revisit.Table-1 presents indicator loadings, critical ratios, Cronbach’s alpha and AVE of each variable. Cronbach’s alpha values of all the variables were higher than 0.70 and were ranged from 0.771 (electronic WOM) to 0.802 (travel intentions). The AVE of the factors is higher than 0.05, ranging from 0.739 (eWOM) to 0.787 (attitude toward the destination). Table-2 shows the interfactor correlation analysis between each construct. They ranged from 0.558 (between eWOM and attitude toward the tourist destination) to 0.645 (between travel intentions and eWOM) and correlation is significant (0.01). International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 56 Table-1 Indicator loadings, critical ratios, Cronbach’s alpha and average variance extracted VariableIndicator Loadings Critical AVE Electronic word of mouth (6 items) (eWOM1) I often consult other tourists’ online travel reviews to help choose an attractive destination. 0.525 5.232 (eWOM2) When I travel to a destination, tourists’ online travel reviews make me confident in travelling to the destination. 0.623 5.639 (eWOM3) I frequently gather information from tourists’ online travel reviews before I travel to a certain destination. 0.687 6.936 0.771 0.739 (eWOM4) I often read other tourists’ online travel reviews to know what destinations make good impressions on others. 0.596 5.289 (eWOM5) If I don’t read tourists’ online travel reviews when I travel to a destination, I worry about my decision. 0.512 5.479 (eWOM6) To make sure I choose the right destination, I often read other tourists’ online travel reviews. 0.498 5.688 Attitude of Tourist (3 items)As a tourism destination, I think that Tunisia is: (ATT1) very bad/very good 0.578 5.692 (ATT2) very worthless/very valuable 0.683 6.129 0.795 0.772 (ATT3) very unpleasant/very pleasant 0.611 - Travel intentions (3items) (IT1) I predict I will visit Tunisia in the future.0.587 5.045 (IT2) I would visit Tunisia rather than any other tourism destination. 0.579 5.147 0.802 0.787 (IT3) If everything goes as I think, I will plan to visit Tunisia in the future. 0.855 - Table-2 Correlations of constructs Latent variablesElectronic word of mouthAttitudes towards the tourist destination Travel intentions Electronic word of mouth - 0.558* 0.645* Attitudes towards the tourist destination 0.558* - 0.602* Travel intentions 0.645* 0.602* - *indicates significance at the 0.01 level In the next step, we used SEM. The results of a maximum likelihood estimation indicated that the model fits well the data = 69.713, d.f = 81, normed = 1.221, 0.05, RMSEA = 0.009, CFI = 0.988, GFI =0.945, RMR = 0.38). Overall, model fit of the three-factor model improved significantly, indicating that the three-factor model fit the data well. Results as indicated in table-3 supported the hypothesized relationships between eWOM, Attitude of tourist, and Travel intentions. Consequently, hypotheses H, H, and H were confirmed. Specifically, eWOM represents a factor predicting tourists’ attitudes toward a destination (H1: = 0.854, t = 4.372, 0.001), and electronic WOM has a significant correlation with travel intentions (H: = 0.695, t = 3.920, 0.05). In fact, the empirical results from the structural model indicate that eWOM positively influences tourist attitude and intention to travel. In addition, attitudes toward the tourist destination had a significant positive relationship with travel intentions (H: = 0.884, t = 6.771, 0.05). International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 57 Table-3 Structural equation modeling: Hypothesized models with fitted coefficients Hypothesis Independent Variable Dependent variable EstimateStandardized estimate Standard error t-statistic EWOM Attitudes towards the tourist destination 0.766 0.854 0.142 4.372 ** EWOM Travel intentions 0.547 0.695 0.131 3.920 0.022* Attitudes towards the tourist destination Travel intentions 0.501 0.884 0.145 6.771 0.013* Structural model Cut-off value   =69.713 - df=81 - -value 0.05 - Normed  = 1.221 1.0-3.0 Model fit Statistics GFI= 0.945 � 0.90 AGFI= 0.912 � 0.90 CFI= 0.988 � 0.90 RMR= 0.38 0.50 RMSEA= 0.029 0.08: good fit Notes: n=219; **indicates significance at the 0.001 level and *indicates significance at the 0.05 level Discussion: This study is an attempt to contribute to the knowledge on online travel communities by identifying tourists’ destination choice process. Based on reviewing previous studies, a research model was developed containing two key indicators of the tourist’s travel intention: eWOM and attitude toward visiting the destination (Tunisia). The current study validates the proposed model and the results support our research hypotheses. Results support both hypotheses 1 and 2, indicating that eWOM communication influences tourist attitude and travel intention. Indeed, in the eWOM communication studies, factors related to a receiver's psychological state, such as attitude and purchase intention are the most commonly investigated outcomes (responses) of eWOM communication. Consistent with H, attitude is confirmed as an important predictor of travel intention. Thus,tourists' behavioral intentions are directly related to their attitudes.Conclusion In a context marked by consumers’ lack of trust to organizations and advertising, eWOM offers a way to obtain a significant competitive advantage. The emergent role of eWOM is highly emphasized as a powerful marketing tool due to its powerful effect on customer decision-making59. This research attempted to explain how eWOM influences attitude and tourists’ future travelling intention.The survey result finds that eWOM was positively associated with tourists’ future travelling intention towards visiting Tunisia and emphasize the relevance of online user-generated reviews to business performance in tourism. Different types of eWOM contents are exchanged among potential and experienced travelers through multiple media platforms such as E-mails, online travel communities, blogs, and online travel reviews. However, most recent studies on the impact of eWOM examine the role of online travel review for its possible impact on tourists’ decision making59. By considering the effects of eWOM on tourists’ attitudes toward destination and revisit intention, we were able to explain the decision-making process, which included the motivation for the tourist behaviour in online travel communities. While the present study has shed some light on online travel community, it has several limitations. Firstly, the convenience sampling method used to select participants for the experiment does not produce findings that are representative of all international tourists. Secondly, the questions used in the questionnaire were very simple and qualitative data on the principal information sources was not collected. Open-ended questions would be helpful in order to provide further information sources of tourists. In the context of tourism, it is very important for destination managers to realize how travelers search for and review information at the various steps of their travel decision making process60. The information posted in online travel communities International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 58 is an influential eWOM form of communication that is being utilized by today’s travelers in their travel decision making. Further, promoting travel destinations online is today a successful business and many travel developers extract information to tourists interested in leisure destinations. Tourism Marketers should be conscious that their potential consumers are increasingly using online sources and they consequently should consider it seriously in their marketing strategies. The study will contributes to the knowledge of marketers by providing insights into consumers' attitudes and intention, which can potentially be used by marketers to better respond to, and target, these consumers in order to surmount barriers to consumer choice. References 1.Silverman G., The Secrets of Word-of-Mouth Marketing: How to Trigger Exponential Sales Through Runaway Word-of-Mouth, Amacom Books, New York (2001)2.Sen S. and Lerman D., Why are you telling me this? An examination into negative consumer reviews on the web, Journal of Interactive Marketing, 21(4), 76-94 (2007)3.Park Y.A. and Gretzel U., Success factors for destination marketing web sites: a qualitative meta-analysis, Journal of Travel Research, 46(1), 46-63 (2007)4.Lewis R.C. and Chambers R.E., Marketing Leadership in Hospitality. Foundations and Practices, 3rd ed., Wiley, New York (2000)5.Albarq A.N., Measuring the Impacts of Online Word-of-Mouth on Tourists’ Attitude and Intentions to Visit Jordan: An Empirical Study, International Business Research, 7(1), 14-22 (2014)6.Jalilvand M.R. and Samiei N., The Effect of Word of Mouth on Inbound Tourists Decision for Travelling to Isfahan as a Tourism Destination in an Islamic Republic, Journal of Islamic Marketing, 3(1), 12-21 (2012)7.Klein L.R., Evaluating the potential of interactive media through a new lens: search versus experience goods, Journal Business Research, 41(3), 195- 203 (1998)8.Nelson P., Information and Consumer Behavior, Journal of Political Economy, 78(20), 311-329 (1970) 9.Gursoy D and McCleary KW, An integrative model of tourists’ information search behavior, Annals of Tourism Research, 31, 353–373 (2004)10.Gruen T.W., Osmonbekov T. and Czaplewski A.J., EWOM: the impact of customer-tocustomer online know-how exchange on customer value and loyalty, Journal of Business Research, 59 (4), 449-56 (2006)11.Baloglu S., A path-analytical model of visitation intention involving information sources, socio-psychological motivations and destination images, In: Woodside (2000)12.Alegre J. and Cladera M., Analysing the effect of satisfaction and previous visits on tourist intentions to return, European Journal of Marketing, 43(5/6), 670-685 (2009)13.Fakharyan M., Jalilvand M., Elyasi M. and Mohammadi M., The influence of online word of mouth communications on tourists’ attitudes toward Islamic destinations and travel intention: Evidence from Iran, Afr. Journal of Business Management,6(38), 10381–10388 (2012)14.Zeithaml V., Berry L.L. and Parasuraman A., The behavioral consequences of service quality, Journal of Marketing, 60 (2), 31-46 (1996)15.Murray K.B., A test of services marketing theory: consumer information acquisition activities, Journal of Marketing, 55(1), 10-25 (1991)16.Sheth J.N., Word-of-mouth in low-risk innovations, Journal of Advertising Research,11(3), 15-8 (1971)17.Mikkelsen M., Van Durme J. and Carrie D.G., Viewers talking about television advertising: a supplementary measure of advertising effectiveness, paper presented at the 32nd EMAC, Glasgow (2003)18.Grewal R., Cline T.W. and Davies A., Early-entrant advantages, word of mouth communication, brand similarity, and the consumer’s decision-making process, Journal of Consumer Psychology, 13(3), 187-97 (2003)19.Herr P.M., Kardes F.R. and Kim J., Effects of word of mouth and product-attribute information on persuasion: an accessibility-diagnosticity perspective, Journal of Consumer Research, 17(3) 454-62 (1991)20.Webster C., Influences upon consumer expectations of services, The Journal of Services Marketing, 5(1), 5-17 (1991)21.Hennig-Thurau, T., Gwinner, K.P., Walsh, G. et Gremler, D.D., Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet?, Journal of International Marketing, 18 (1), 38-52 (2004)22.Litvin S.W., Goldsmith R.E. and Pana P., Electronic word-of-mouth in hospitality and tourism management, Tourism Management, 29(3) 458-68 (2008)23.Zhu M. and Lai, S. (2009), A study about the WOM influence on tourism destination choice, paper presented at the International Conference on Electronic Commerce and Business Intelligence (ECBI), Beijing (2009)24.Gretzel U. and Yoo K., Use and impact of online travel reviews, in O’Connor, P., Hpken,W. and Gretzel, U. International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 59 (Eds), Information and Communication Technologies in Tourism, Springer-Verlag, Wien, NY, 35-46 (2008)25.Vermeulen I.E. and Seegers D., Tried and tested: the impact of online hotel reviews on consumer consideration, Tourism Management, 30(1), 123-7 (2009)26.Tucker T., Online word of mouth: Characteristics of Yelp.com reviews, The Elon Journal of Undergraduate Research in Communications,2(1), 37–42 (2011)27.Goldenberg J., Libai B. and Muller E., Talk of the network: A complex systems look at the underlying process of word-of-mouth, Journal of Marketing Letter, 12(3), 211–223 (2001)28.Ye Q., Law R., Gu B. and Chen W., The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings, Computers in Human Behavior, 27(4),634–639 (2011)29.Laczniak R.N., DeCarlo T.E. and Ramaawani S.N., Consumers’ responses to negative word-of-mouth communication: an attribution theory perspective, Journal of Consumer Psychology., 11(1), 57-73 (2001)30.Kraus S.J., Attitudes and the prediction of behavior: a meta-analysis of the empirical literature, Personality and Social Psychology Bulletin, 21(1), 58-75 (1995)31.Ajzen I, Attitudes, Annual Review of Psychology, 52, 27-58 (2001)32.Eagry A.H. and Chailen, S., Psychology of attitudes, Fort Worth, TX: Harcourt Brace Jovanovich (1993)33.Chou C.J., Chen K.S. and Wang Y.Y., Green practices in the restaurant industry from an innovation adoption perspective: Evidence from Taiwan, International Journal of Hospitality Management, 31, 703- 711 (2012)34.Cheng S., Lam T. and Hsu C.H.C., Testing the sufficiency of the theory of planned behavior: a case of customer dissatisfaction responses in restaurants, International Journal of Hospitality Management, 24 (4), 475-92 (2005)35.Ajzen I, The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), 179-211 (1991)36.Castaneda J.A., Rodriguez M.A. and Luque T., Attitudes’ hierarchy of effects in online user behavior, Online Information Review, 33(1), 7-21 (2009)37.Dennis C., Merrilees B., Jayawardhena C. and Wright L., E-consumer behavior, European Journal of Marketing, 43(10), 1121–1139 (2009)38.Ajzen I., Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior, Journal of Applied Social Psychology,32(4), 665-83 (2002)39.Ajzen I. and Fishbein M., Understanding Attitudes and Predicting Social Behavior, Prentice-Hall, Englewood Cliffs, NJ (1980)40.Soderlund M. and Rosengren S., Receiving word-of-mouth from the service customer: an emotion-based effectiveness assessment, Journal of Retailing and Consumer Services, 14(2), 123-36 (2007)41.Ying H.L. and Chung C.M.Y., The effects of single-message single-source mixed word-of mouth on product attitude and purchase intention, Asia Pacific Journal of Marketing19(1), 75-86 (2007)42.Chevalier J. and Mayzlin D., Promotional chat on the Internet, Marketing Science, 25(2), 155-63 (2006)43.Chatterjee P., Online reviews: do consumers use them?, Advances in Consumer Research,28(1), 129-33 (2001)44.Chen Y. and Xie J., Online consumer review: word-ofmouth as a new element of marketing communication mix, Management Science,54(3), 477-91 (2008)45.Godes D. and Mayzlin D., Using online conversations to study word-of-mouth communication, Marketing Science, 23(4), 545-60 (2004)46.Dellarocas C., The digitization of word of mouth: promise and challenges of online feedback mechanisms, Management Science, 49(10), 1407-24 (2003)47.Lin T.M.Y., Luarn P. and Huang Y.K., Effect of Internet book reviews on purchase intention: a focus group study, The Journal of Academic Librarianship, 31(5), 461-8 (2005)48.Bambauer-Sachse S. and Mangold S., Brand equity dilution through negative online word-of-mouth communication, Journal of Retailing and Consumer Services, 18 (1), 38-45 (2011)49.Kassem N.O., Lee, J.W., Modeste N.N. and Johnston P.K., Understanding soft drink consumption among female adolescents using the theory of planned behavior, Health Education Research, 18(3), 278-91 (2010)50.Hair J., Black W., Babin B., Anderson R. and Tatham, R., Multivariate data analysis (6th ed.), Upper Saddle River, New Jersey: Pearson Education, Inc (2006)51.Abbas A., Suleiman A. and Almualla A., Using structural equation modeling for beginner, Jordan, Amman: Ithraa, Inc (2013)52.Byrne B.M., Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming, Lawrence Erlbaum Associates, Mahwah, NJ (1998)53.Bentler P.M., Comparative fit indexes in structural models, Psychological Bulletin, 107, 238–246 (1990) International Research Journal of Social Sciences____________________________________________________ISSN 2319–3565Vol. 4(4), 53-60, April (2015) Int. Res. J. Social Sci.International Science Congress Association 60 54.Hu L.T. and Bentler P.M., Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives, Structural Equation Modeling, 6(1), 1-55 (1999)55.Nunnally J.C., Bernstein I.H., Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY (1994)56.Karunanidhi S. and Chitra T., Influence of Select Psychosocial Factors on the Psychological Well-being of Policewomen, International Research Journal of Social Sciences, 2(8), 5-14 (2013)57.Kline R., Principles and Practice of Structural Equation Modeling, 2nd ed, The Guilford Press, New York (2005)58.Barbara Z. and Vesna Z., Examination of co-operative norms, beliefs in interpersonal trustworthiness, complementary capabilities and realized competitive advantages in business to-business relationships, Economic and Business Review for Central and South, 8(1), 11–19 (2006) 59.Lee G. and Tussyadiah I.P., Textual and visual information in eWOM: A gap between preferences in information search and diffusion, Information Technology and Tourism, 12, 351-361 (2011) 60.Choi S.J., Letho X.Y. and O'Leary J.T., What does the consumer want from a DMO website? A study of US and Canadian tourists' perspectives, International Journal of Tourism Research, , 59-72 (2007)