The dissemination and impacts of deceptive eWOM: a dynamic process perspective

References

• Ahmad, W., and J. Sun. 2018. “Modeling Consumer Distrust of Online Hotel Reviews.” International Journal of Hospitality Management 71: 77–90.
   Web of Science ®Google Scholar
• Ajzen, I. 1991. “The Theory of Planned Behavior.” Organizational Behavior and Human Decision Processes 50 (2): 179–211.
   Web of Science ®Google Scholar
• Akerlof, G. A. 1970. “The Market for “Lemons”: Quality Uncertainty and the Market Mechanism.” The Quarterly Journal of Economics 84 (3): 488–500.
   Web of Science ®Google Scholar
• Amazeen, M. A., and E. P. Bucy. 2019. “Conferring Resistance to Digital Disinformation: The Inoculating Influence of Procedural News Knowledge.” Journal of Broadcasting & Electronic Media 63 (3): 415–432.
   Web of Science ®Google Scholar
• Anderson, C. A. 1983. “Abstract and Concrete Data in the Perseverance of Social Theories: When Weak Data Lead to Unshakeable Beliefs.” Journal of Experimental Social Psychology 19 (2): 93–108.
   Web of Science ®Google Scholar
• Anderson, M., and J. Magruder. 2012. “Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database.” The Economic Journal 122 (563): 957–989.
   Web of Science ®Google Scholar
• Baek, H., S. Oh, H.-D. Yang, and J. Ahn. 2017. “Electronic Word-of-Mouth, box Office Revenue and Social Media.” Electronic Commerce Research and Applications 22: 13–23.
   Web of Science ®Google Scholar
• Bambauer-Sachse, S., and S. Mangold. 2013. “Do Consumers Still Believe What is Said in Online Product Reviews? A Persuasion Knowledge Approach.” Journal of Retailing and Consumer Services 20 (4): 373–381.
   Google Scholar
• Bhattacherjee, A., and G. Premkumar. 2004. “Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test.” MIS Quarterly 28 (2): 229–254.
   Web of Science ®Google Scholar
• Boisvert, J. 2016. “Reciprocal Transfer of Brand Associations Between Service Parent Brands and Upward Line Extensions: An Accessibility-Diagnosticity Perspective.” Journal of Service Theory and Practice 26 (2): 222–243.
   Web of Science ®Google Scholar
• Bond, S. D., S. X. He, and W. Wen. 2019. “Speaking for “Free”: Word of Mouth in Free-and Paid-Product Settings.” Journal of Marketing Research 56 (2): 276–290.
   Web of Science ®Google Scholar
• Boush, D. M., M. Friestad, and P. Wright. 2009. Deception in the Marketplace: The Psychology of Deceptive Persuasion and Consumer Self-Protection. New York: Routledge.
   Google Scholar
• Brandt, T., and D. Neumann. 2015. “Chasing Lemmings: Modeling IT-Induced Misperceptions About the Strategic Situation as a Reason for Flash Crashes.” Journal of Management Information Systems 31 (4): 88–108.
   Web of Science ®Google Scholar
• Burke, R. R., W. S. DeSarbo, R. L. Oliver, and T. S. Robertson. 1988. “Deception by Implication: An Experimental Investigation.” Journal of Consumer Research 14 (4): 483–494.
   Web of Science ®Google Scholar
• Campbell, M. C., and A. Kirmani. 2000. “Consumers' Use of Persuasion Knowledge: The Effects of Accessibility and Cognitive Capacity on Perceptions of an Influence Agent.” Journal of Consumer Research 27 (1): 69–83.
   Web of Science ®Google Scholar
• Cavazza, N., and M. Guidetti. 2014. “Fake Online Reviews: A Study on eWOM Influence When Suspicions Arise.” Psicologia Sociale 9 (1): 71–82.
   Google Scholar
• Chang, H. H., and S.-S. Chuang. 2011. “Social Capital and Individual Motivations on Knowledge Sharing: Participant Involvement as a Moderator.” Information & Management 48 (1): 9–18.
   Web of Science ®Google Scholar
• Chin, W. W. 1998. “The Partial Least Squares Approach to Structural Equation Modeling.” In Modern Methods for Business Research, edited by G. A. Marcoulides, 295–336. New York: Psychology Press.
   Google Scholar
• Chin, W. W. 2010. “How to Write up and Report PLS Analyses.” In Handbook of Partial Least Squares, edited by V. E. Vinzi, W. W. Chin, J. Henseler, and H. Wang, 655–690. Berlin: Springer.
   Google Scholar
• Cialdini, R. B. 1988. Influence: Science and Practice. New York: Harper Collins.
   Google Scholar
• Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. New York: Routledge.
   Google Scholar
• Coker, B. L. 2012. “Seeking the Opinions of Others Online: Evidence of Evaluation Overshoot.” Journal of Economic Psychology 33 (6): 1033–1042.
   Web of Science ®Google Scholar
• Cui, G., H.-K. Lui, and X. Guo. 2012. “The Effect of Online Consumer Reviews on new Product Sales.” International Journal of Electronic Commerce 17 (1): 39–58.
   Web of Science ®Google Scholar
• Davis, F. D., R. P. Bagozzi, and P. R. Warshaw. 1989. “User Acceptance of Computer Technology: A Ccomparison of two Theoretical Models.” Management Science 35 (8): 903–1028.
   Web of Science ®Google Scholar
• De Meyer, C. F., and D. J. Petzer. 2014. “Product Involvement and Online Word-of-Mouth in the South African Fast Food Industry.” Journal of Global Business and Technology 10 (1): 16–24.
   Google Scholar
• Deutsch, M., and H. B. Gerard. 1955. “A Study of Normative and Informational Social Influences upon Individual Judgment.” The Journal of Abnormal and Social Psychology 51 (3): 629–636.
   PubMedGoogle Scholar
• Duan, W., B. Gu, and A. B. Whinston. 2009. “Informational Cascades and Software Adoption on the Internet: An Empirical Investigation.” MIS Quarterly 33 (1): 23–48.
   Web of Science ®Google Scholar
• East, R., K. Hammond, and M. Wright. 2007. “The Relative Incidence of Positive and Negative Word of Mouth: A Multi-Category Study.” International Journal of Research in Marketing 24 (2): 175–184.
   Web of Science ®Google Scholar
• Erjavec, J., and A. Manfreda. 2022. “Online Shopping Adoption During COVID-19 and Social Isolation: Extending the UTAUT Model with Herd Behavior.” Journal of Retailing and Consumer Services 65: 102867.
   Web of Science ®Google Scholar
• Festinger, L. 1962. A Theory of Cognitive Dissonance (Vol. 2). Stanford, CA: Stanford University Press.
   Google Scholar
• Fishbein, M., and I. Ajzen. 1975. Belief, Attitude, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison Wessley.
   Google Scholar
• Fornell, C., and F. L. Bookstein. 1982. “Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory.” Journal of Marketing Research 19 (4): 440–452.
   Web of Science ®Google Scholar
• Fornell, C., and D. F. Larcker. 1981. “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research 18 (1): 39–50.
   Web of Science ®Google Scholar
• Friestad, M., and P. Wright. 1994. “The Persuasion Knowledge Model: How People Cope with Persuasion Attempts.” Journal of Consumer Research 21 (1): 1–31.
   Web of Science ®Google Scholar
• Gailey, J. A. 2013. “Attribution of Responsibility for Organizational Wrongdoing: A Partial Test of an Integrated Model.” Journal of Criminology 2013: 1–10.
   Google Scholar
• Guo, B., and S. Zhou. 2016. “Understanding the Impact of Prior Reviews on Subsequent Reviews: The Role of Rating Volume, Variance and Reviewer Characteristics.” Electronic Commerce Research and Applications 20: 147–158.
   Web of Science ®Google Scholar
• Hair, J. F., W. C. Black, and B. J. Babin. 2009. Multivariate Data Analysis: A Global Perspective (7th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
   Google Scholar
• Hair, J. F., C. M. Ringle, and M. Sarstedt. 2011. “PLS-SEM: Indeed a Silver Bullet.” Journal of Marketing Theory and Practice 19 (2): 139–152.
   Google Scholar
• Hair, J. F., M. Sarstedt, C. M. Ringle, and J. A. Mena. 2012. “An Assessment of the use of Partial Least Squares Structural Equation Modeling in Marketing Research.” Journal of the Academy of Marketing Science 40: 414–433.
   Web of Science ®Google Scholar
• Hajli, N. 2015. “Social Commerce Constructs and Consumer's Intention to buy.” International Journal of Information Management 35 (2): 183–191.
   Web of Science ®Google Scholar
• Ham, C.-D., and M. R. Nelson. 2019. “The Reflexive Persuasion Game: The Persuasion Knowledge Model (1994–2017).” In Advertising Theory . 2nd ed., edited by S. Rodgers, and E. Thorson, 124–140. New York: Routledge.
   Google Scholar
• Harmon-Jones, E., and J. Mills. 2019. “An Introduction to Cognitive Dissonance Theory and an Overview of Current Perspectives on the Theory.” In Cognitive Dissonance: Reexamining a Pivotal Theory in Psychology, edited by E. Harmon-Jones, 3–24. Washington, DC: American Psychological Association.
   Google Scholar
• Helson, H. 1947. “Adaptation-level as Frame of Reference for Prediction of Psychophysical Data.” The American Journal of Psychology 60 (1): 1–29.
   PubMed Web of Science ®Google Scholar
• Helson, H. 1964. “Current Trends and Issues in Adaptation-Level Theory.” American Psychologist 19 (1): 26–38.
   Web of Science ®Google Scholar
• Hennig-Thurau, T., G. Walsh, and G. Walsh. 2003. “Electronic Word-of-Mouth: Motives for and Consequences of Reading Customer Articulations on the Internet.” International Journal of Electronic Commerce 8 (2): 51–74.
   Web of Science ®Google Scholar
• Herr, P. M., F. R. Kardes, and J. Kim. 1991. “Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective.” Journal of Consumer Research 17 (4): 454–462.
   Web of Science ®Google Scholar
• Hu, N., I. Bose, N. S. Koh, and L. Liu. 2012. “Manipulation of Online Reviews: An Analysis of Ratings, Readability, and Sentiments.” Decision Support Systems 52 (3): 674–684.
   Web of Science ®Google Scholar
• Hu, Y.-H., and K. Chen. 2016. “Predicting Hotel Review Helpfulness: The Impact of Review Visibility, and Interaction Between Hotel Stars and Review Ratings.” International Journal of Information Management 36 (6): 929–944.
   Web of Science ®Google Scholar
• Johnston, K. 2013. Review websites try to thwart false customer ratings. Accessed July 23, 2021. https://www.bostonglobe.com/business/2013/09/24/fake-online-reviews-proliferate-fraud-detection-efforts-grow/aWsy3l5xQAfJxczMySMMKL/story.html.
   Google Scholar
• Kamlot, D., D. Botelho, and F. B. de Oliveira. 2013. “Reaction to Deceptive Advertising in Brazil.” International Journal of Advances in Management and Economics 3 (1): 25–33.
   Google Scholar
• Kent, R. J., and C. T. Allen. 1994. “Competitive Interference Effects in Consumer Memory for Advertising: The Role of Brand Familiarity.” The Journal of Marketing 58 (3): 97–105.
   Web of Science ®Google Scholar
• Kesharwani, A. 2020. “Do (how) Digital Natives Adopt a new Technology Differently Than Digital Immigrants?” A Longitudinal Study. Information & Management 57 (2): 103170.
   Web of Science ®Google Scholar
• Khare, A., L. I. Labrecque, and A. K. Asare. 2011. “The Assimilative and Contrastive Effects of Word-of-Mouth Volume: An Experimental Examination of Online Consumer Ratings.” Journal of Retailing 87 (1): 111–126.
   Web of Science ®Google Scholar
• Kim, S. S. 2009. “The Integrative Framework of Technology use: An Extension and Test.” Mis Quarterly 33 (3): 513–537.
   Web of Science ®Google Scholar
• Klein, J., and N. Dawar. 2004. “Corporate Social Responsibility and Consumers' Attributions and Brand Evaluations in a Product-Harm Crisis.” International Journal of Research in Marketing 21 (3): 203–217.
   Web of Science ®Google Scholar
• Kuan, K. K., Y. Zhong, and P. Y. Chau. 2014. “Informational and Normative Social Influence in Group-Buying: Evidence from Self-Reported and EEG Data.” Journal of Management Information Systems 30 (4): 151–178.
   Web of Science ®Google Scholar
• Lang, B., and K. F. Hyde. 2013. “Word of Mouth: What we Know and What we Have yet to Learn.” Journal of Consumer Satisfaction, Dissatisfaction & Complaining Behavior 26 (1): 1–18.
   Google Scholar
• Lappas, T., G. Sabnis, and G. Valkanas. 2016. “The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry.” Information Systems Research 27 (4): 940–961.
   Web of Science ®Google Scholar
• Leary, M. R., and J. P. Tangney. 2002. Handbook of Self and Identity. New York: Guilford Press.
   Google Scholar
• Lee, S., and J. Y. Choeh. 2016. “The Determinants of Helpfulness of Online Reviews.” Behaviour & Information Technology 35 (10): 853–863.
   Web of Science ®Google Scholar
• Lee, J., and I. B. Hong. 2016. “Predicting Positive User Responses to Social Media Advertising: The Roles of Emotional Appeal, Informativeness, and Creativity.” International Journal of Information Management 36 (3): 360–373.
   Web of Science ®Google Scholar
• Lee, Y. L., and S. Song. 2010. “An Empirical Investigation of Electronic Word-of-Mouth: Informational Motive and Corporate Response Strategy.” Computers in Human Behavior 26 (5): 1073–1080.
   Web of Science ®Google Scholar
• Leo, X., and Y. E. Huh. 2020. “Who Gets the Blame for Service Failures? Attribution of Responsibility Toward Robot Versus Human Service Providers and Service Firms.” Computers in Human Behavior 113: 106520.
   Web of Science ®Google Scholar
• Lin, Z., and C.-S. Heng. 2015. “The Paradoxes of Word of Mouth in Electronic Commerce.” Journal of Management Information Systems 32 (4): 246–284.
   Web of Science ®Google Scholar
• Liu, Y. 2006. “Word of Mouth for Movies: Its Dynamics and Impact on box Office Revenue.” Journal of Marketing 70 (3): 74–89.
   Web of Science ®Google Scholar
• Lohmöller, J.-B. 1988. “The PLS Program System: Latent Variables Path Analysis with Partial Least Squares Estimation.” Multivariate Behavioral Research 23 (1): 125–127.
   PubMed Web of Science ®Google Scholar
• Luca, M., and G. Zervas. 2016. “Fake it Till you Make it: Reputation, Competition, and Yelp Review Fraud.” Management Science 62 (12): 3393–3672.
   Web of Science ®Google Scholar
• Ludden, G. D., H. N. Schifferstein, and P. Hekkert. 2012. “Beyond Surprise: A Longitudinal Study on the Experience of Visual-Tactual Incongruities in Products.” International Journal of Design 6 (1): 1–10.
   Web of Science ®Google Scholar
• Ma, H., J. M. Kim, and E. Lee. 2019. “Analyzing Dynamic Review Manipulation and its Impact on Movie box Office Revenue.” Electronic Commerce Research and Applications 35: 100840.
   Web of Science ®Google Scholar
• Magnini, V. P. 2011. “The Implications of Company-Sponsored Messages Disguised as Word-of-Mouth.” Journal of Services Marketing 25 (4): 243–251.
   Web of Science ®Google Scholar
• Manganari, E. E., and E. Dimara. 2017. “Enhancing the Impact of Online Hotel Reviews Through the use of Emoticons.” Behaviour & Information Technology 36 (7): 674–686.
   Web of Science ®Google Scholar
• Mayzlin, D. 2006. “Promotional Chat on the Internet.” Marketing Science 25 (2): 109–201.
   Web of Science ®Google Scholar
• Mayzlin, D., Y. Dover, and J. Chevalier. 2014. “Promotional Reviews: An Empirical Investigation of Online Review Manipulation.” American Economic Review 104 (8): 2421–2455.
   Web of Science ®Google Scholar
• Menold, N., and A. Tausch. 2016. “Measurement of Latent Variables with Different Rating Scales: Testing Reliability and Measurement Equivalence by Varying the Verbalization and Number of Categories.” Sociological Methods & Research 45 (4): 678–699.
   Web of Science ®Google Scholar
• Mittal, B. 1995. “A Comparative Analysis of Four Scales of Consumer Involvement.” Psychology & Marketing 12 (7): 663–682.
   Web of Science ®Google Scholar
• Montano, D. E., and D. Kasprzyk. 2015. “Theory of Reasoned Action, Theory of Planned Behavior, and the Integrated Behavioral Model.” In Health Behavior: Theory, Research and Practice, edited by K. Glanz, B. K. Rimer, and K. Viswanath, 95–124. San Francisco, CA: Jossey-Bass.
   Google Scholar
• Moore, G. A. 2014. Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers. 3rd ed. New York: Harper Collins.
   Google Scholar
• Moore, S. G., and K. C. Lafreniere. 2020. “How Online Word-of-Mouth Impacts Receivers.” Consumer Psychology Review 3 (1): 34–59.
   Google Scholar
• Mukherjee, A., B. Liu, and N. Glance. 2012. Spotting fake reviewer groups in consumer reviews. Proceedings of the 21st international conference on World Wide Web, Lyon, France.
   Google Scholar
• Munzel, A. 2016. “Assisting Consumers in Detecting Fake Reviews: The Role of Identity Information Disclosure and Consensus.” Journal of Retailing and Consumer Services 32: 96–108.
   Web of Science ®Google Scholar
• Nejad, M. G., D. L. Sherrell, and E. Babakus. 2014. “Influentials and Influence Mechanisms in New Product Diffusion: An Integrative Review.” The Journal of Marketing Theory and Practice 22 (2): 185–208.
   Google Scholar
• Nestler, S. 2010. “Belief Perseverance: The Role of Accessible Content and Accessibility Experiences.” Social Psychology 41 (1): 35–41.
   Web of Science ®Google Scholar
• Newman, M. L., J. W. Pennebaker, D. S. Berry, and J. M. Richards. 2003. “Lying Words: Predicting Deception from Linguistic Styles.” Personality and Social Psychology Bulletin 29 (5): 665–675.
   PubMed Web of Science ®Google Scholar
• Oliver, R. L. 2014. Satisfaction: A Behavioral Perspective on the Consumer . 2nd ed. New York: Routledge.
   Google Scholar
• Olson, J. C., and P. A. Dover. 1978. “Cognitive Effects of Deceptive Advertising.” Journal of Marketing Research 15 (1): 29–38.
   Web of Science ®Google Scholar
• Ott, M., Y. Choi, C. Cardie, and J. T. Hancock. 2011. Finding deceptive opinion spam by any stretch of the imagination. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1, Stroudsburg, PA, USA.
   Google Scholar
• Pan, Y., and J. Q. Zhang. 2011. “Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews.” Journal of Retailing 87 (4): 598–612.
   Web of Science ®Google Scholar
• Park, D.-H., J. Lee, and I. Han. 2007. “The Effect of on-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement.” International Journal of Electronic Commerce 11 (4): 125–148.
   Web of Science ®Google Scholar
• Park, S., and J. L. Nicolau. 2015. “Asymmetric Effects of Online Consumer Reviews.” Annals of Tourism Research 50: 67–83.
   Web of Science ®Google Scholar
• Pfeffer, J., and G. R. Salancik. 2007. The External Control of Organizations: A Resource Dependence Perspective. Stanford, CA: Stanford Business Books.
   Google Scholar
• Podsakoff, P. M., S. B. MacKenzie, J.-Y. Lee, and N. P. Podsakoff. 2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” Journal of Applied Psychology 88 (5): 879–903.
   PubMed Web of Science ®Google Scholar
• Preston, I. L. 1977. “The FTC's Handling of Puffery and Other Selling Claims Made “by Implication”.” Journal of Business Research 5 (2): 155–181.
   Web of Science ®Google Scholar
• Reinartz, W., M. Haenlein, and J. Henseler. 2009. “An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM.” International Journal of Research in Marketing 26 (4): 332–344.
   Web of Science ®Google Scholar
• Rogers, E. M. 2010. Diffusion of Innovations. New York: Simon and Schuster.
   Google Scholar
• Rönkkö, M., and J. Ylitalo. 2011. PLS marker variable approach to diagnosing and controlling for method variance. ICIS 2011 Proceedings, https://aisel.aisnet.org/icis2011/proceedings/researchmethods/8.
   Google Scholar
• Rosario, A. B., K. de Valck, and F. Sotgiu. 2020. “Conceptualizing the Electronic Word-of-Mouth Process: What we Know and Need to Know About eWOM Creation, Exposure, and Evaluation.” Journal of the Academy of Marketing Science 48: 422–448.
   Web of Science ®Google Scholar
• Ross, C. K., G. Frommelt, L. Hazelwood, and R. W. Chang. 1987. “The Role of Expectations in Patient Satisfaction with Medical Care.” Journal of Health Care Marketing 7 (4): 16–26.
   PubMedGoogle Scholar
• Sarstedt, M., C. M. Ringle, and J. F. Hair. 2017. “Partial Least Squares Structural Equation Modeling.” In Handbook of Market Research (Vol. 26, pp. 1-40), edited by C. Homburg, M. Klarmann, and A. Vomberg. Cham: Springer.
   Google Scholar
• Savage, D., X. Zhang, X. Yu, P. Chou, and Q. Wang. 2015. “Detection of Opinion Spam Based on Anomalous Rating Deviation.” Expert Systems with Applications 42 (22): 8650–8657.
   Web of Science ®Google Scholar
• Sedera, D., S. Lokuge, M. Atapattu, and U. Gretzel. 2017. “Likes—the key to my Happiness: The Moderating Effect of Social Influence on Travel Experience.” Information & Management 54 (6): 825–836.
   Web of Science ®Google Scholar
• Sen, S., and D. Lerman. 2007. “Why are you Telling me This? An Examination Into Negative Consumer Reviews on the web.” Journal of Interactive Marketing 21 (4): 76–94.
   Web of Science ®Google Scholar
• Shen, F., and Q. Chen. 2007. “Contextual Priming and Applicability: Implications for Ad Attitude and Brand Evaluations.” Journal of Advertising 36 (1): 69–80.
   Web of Science ®Google Scholar
• Shimp, T. A., and I. L. Preston. 1981. “Deceptive and Nondeceptive Consequences of Evaluative Advertising.” The Journal of Marketing 45 (1): 22–32.
   Web of Science ®Google Scholar
• Souppouris, A. 2013. Samsung fined $340,000 for faking online comments. Accessed Dec, 24. http://www.theverge.com/2013/10/24/5023658/samsung-fined-340000-for-posting-negative-htc-reviews.
   Google Scholar
• Sparks, B. A., and V. Browning. 2011. “The Impact of Online Reviews on Hotel Booking Intentions and Perception of Trust.” Tourism Management 32 (6): 1310–1323.
   Web of Science ®Google Scholar
• Streitfeld, D. 2012. “The Best Book Reviews Money Can buy.” The New York Times 25 (08): 1–7.
   Google Scholar
• Sun, H. 2013. “A Longitudinal Study of Herd Behavior in the Adoption and Continued use of Technology.” MIS Quarterly 37 (4): 1013–1041.
   Web of Science ®Google Scholar
• Sun, H., and Y. Fang. 2010. “Toward a Model of Mindfulness in Technology Acceptance.” ICIS 2010 Proceedings. https://aisel.aisnet.org/icis2010_submissions/121.
   Google Scholar
• Susarla, A., J.-H. Oh, and Y. Tan. 2016. “Influentials, Imitables, or Susceptibles? Virality and Word-of-Mouth Conversations in Online Social Networks.” Journal of Management Information Systems 33 (1): 139–170.
   Web of Science ®Google Scholar
• Tao, D., T. Wang, T. Wang, T. Zhang, X. Zhang, and X. Qu. 2020. “A Systematic Review and Meta-Analysis of User Acceptance of Consumer-Oriented Health Information Technologies.” Computers in Human Behavior 104: 106147.
   Web of Science ®Google Scholar
• Tenenhaus, M., V. E. Vinzi, Y.-M. Chatelin, and C. Lauro. 2005. “PLS Path Modeling.” Computational Statistics & Data Analysis 48 (1): 159–205.
   Web of Science ®Google Scholar
• Trenz, M., J. Huntgeburth, and D. Veit. 2018. “Uncertainty in Cloud Service Relationships: Uncovering the Differential Effect of Three Social Influence Processes on Potential and Current Users.” Information & Management 55 (8): 971–983.
   Web of Science ®Google Scholar
• Van Vaerenbergh, Y., C. Orsingher, I. Vermeir, and B. Larivière. 2014. “A Meta-Analysis of Relationships Linking Service Failure Attributions to Customer Outcomes.” Journal of Service Research 17 (4): 381–398.
   Web of Science ®Google Scholar
• Vedadi, A., and M. Warkentin. 2020. “Can Secure Behaviors be Contagious? A two-Stage Investigation of the Influence of Herd Behavior on Security Decisions.” Journal of the Association for Information Systems 21 (2): 428–459.
   Web of Science ®Google Scholar
• Venkatesh, V., and H. Bala. 2008. “Technology Acceptance Model 3 and a Research Agenda on Interventions.” Decision Sciences 39 (2): 273–315.
   Web of Science ®Google Scholar
• Verlegh, P. W., G. Ryu, M. A. Tuk, and L. Feick. 2013. “Receiver Responses to Rewarded Referrals: The Motive Inferences Framework.” Journal of the Academy of Marketing Science 41 (6): 669–682.
   Web of Science ®Google Scholar
• Vinzi, V. E., W. W. Chin, J. Henseler, and H. Wang. 2010. Handbook of Partial Least Squares. Berlin: Springer.
   Google Scholar
• Walden, E. A., and G. J. Browne. 2009. “Sequential Adoption Theory: A Theory for Understanding Herding Behavior in Early Adoption of Novel Technologies.” Journal of the Association for Information Systems 10 (1): 31–62.
   Web of Science ®Google Scholar
• Wang, J.-N., J. Du, Y.-L. Chiu, and J. Li. 2018a. “Dynamic Effects of Customer Experience Levels on Durable Product Satisfaction: Price and Popularity Moderation.” Electronic Commerce Research and Applications 28: 16–29.
   Web of Science ®Google Scholar
• Wang, Q., X. Yang, and W. Xi. 2018b. “Effects of Group Arguments on Rumor Belief and Transmission in Online Communities: An Information Cascade and Group Polarization Perspective.” Information & Management 55 (4): 441–449.
   Web of Science ®Google Scholar
• Wang, Y., and C. Yu. 2017. “Social Interaction-Based Consumer Decision-Making Model in Social Commerce: The Role of Word of Mouth and Observational Learning.” International Journal of Information Management 37 (3): 179–189.
   Web of Science ®Google Scholar
• Weiner, B. 1985. Human Motivation. New York: Springer.
   Google Scholar
• Wessel, M., F. Thies, and A. Benlian. 2016. “The Emergence and Effects of Fake Social Information: Evidence from Crowdfunding.” Decision Support Systems 90: 75–85.
   Web of Science ®Google Scholar
• Wyer, R. S., and R. Adaval. 2009. “Social Psychology and Consumer Psychology: An Unexplored Interface.” In Social Psychology of Consumer Behavior, edited by M. Wänke, 19–61. New York: Psychology Press.
   Google Scholar
• Xiao, B., and I. Benbasat. 2011. “Product-related Deception in e-Commerce: A Theoretical Perspective.” MIS Quarterly 35 (1): 169–196.
   Web of Science ®Google Scholar
• Yan, Q., Q. Wang, and X. Liu. 2014. “Research on the Interactive Effects of Online Scores.” Electronic Commerce Research and Applications 13 (6): 402–408.
   Web of Science ®Google Scholar
• Ylitalo, J. 2009. Controlling for Common Method Variance with Partial Least Squares Path Modeling: A Monte Carlo Study. Research Project. Helsinki University of Technology.
   Google Scholar
• Young, H. P. 2009. “Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning.” American Economic Review 99 (5): 1899–1924.
   Web of Science ®Google Scholar
• Zehrer, A., J. C. Crotts, and V. P. Magnini. 2011. “The Perceived Usefulness of Blog Postings: An Extension of the Expectancy-Disconfirmation Paradigm.” Tourism Management 32 (1): 106–113.
   Web of Science ®Google Scholar
• Zhang, D., L. Zhou, J. L. Kehoe, and I. Y. Kilic. 2016. “What Online Reviewer Behaviors Really Matter? Effects of Verbal and Nonverbal Behaviors on Detection of Fake Online Reviews.” Journal of Management Information Systems 33 (2): 456–481.
   Web of Science ®Google Scholar
• Zhou, Z., Y. Fang, D. R. Vogel, X.-L. Jin, and X. Zhang. 2012. “Attracted to or Locked in? Predicting Continuance Intention in Social Virtual World Services.” Journal of Management Information Systems 29 (1): 273–306.
   Web of Science ®Google Scholar
• Zhuang, M., G. Cui, and L. Peng. 2018. “Manufactured Opinions: The Effect of Manipulating Online Product Reviews.” Journal of Business Research 87: 24–35.
   Web of Science ®Google Scholar