Disconfirmation Effect on Online Rating Behavior: A Structural Model

References

• Anderson EW (1998) Customer satisfaction and word of mouth. J. Service Res. 1(1):5–17.Crossref, Google Scholar
• Anderson EW, Sullivan MW (1993) The antecedents and consequences of customer satisfaction for firms. Marketing Sci. 12(2):125–143.Link, Google Scholar
• Bearden WO, Teel JE (1983) Selected determinants of consumer satisfaction and complaint reports. J. Marketing Res. 20(1):21–28.Crossref, Google Scholar
• Bhattacherjee A (2001) Understanding information systems continuance: An expectation-confirmation model. MIS Quart. 25(3):351–370.Crossref, Google Scholar
• Bolton RN, Drew JH (1991) A multistage model of customers’ assessments of service quality and value. J. Consumer Res. 17(4):375–384.Crossref, Google Scholar
• Chaiken S (1980) Heuristic versus systematic information processing and the use of source versus message cues in persuasion. J. Personality Soc. Psych. 39(5):752–766.Crossref, Google Scholar
• DeGroot MH (1970) Optimal Statistical Decisions (McGraw-Hill, New York).Google Scholar
• Dellarocas C (2006) Strategic manipulation of Internet opinion forums: Implications for consumers and firms. Management Sci. 52(10):1577–1593.Link, Google Scholar
• Dellarocas C, Narayan R (2006) A statistical measure of a population’s propensity to engage in post-purchase online word-of-mouth. Statist. Sci. 21(2):277–285.Crossref, Google Scholar
• Dellarocas C, Fan M, Wood C (2004) Self-interest, reciprocity, and participation in online reputation systems. Working paper, Boston University, Boston.Google Scholar
• Dellarocas C, Gao G, Narayan R (2010) Are consumers more likely to contribute online reviews for hit or niche products? J. Management Inform. Systems 27(2):127–158.Crossref, Google Scholar
• Dichter E (1966) How word-of-mouth advertising works. Harvard Bus. Rev. 44(6):147–160.Google Scholar
• Gelman A, Rubin DB (1992) Inference from iterative simulation using multiple sequences. Statist. Sci. 7(4):457–472.Crossref, Google Scholar
• Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2013) Bayesian Data Analysis, 3rd ed. (Chapman & Hall/CRC Press, Boca Raton, FL).Crossref, Google Scholar
• Gormley M (2013) NY attorney general cracks down on fake online reviews. NBC News (September 23), http://www.nbcnews.com/tech/internet/ny-attorney-general-cracks-down-fake-online-reviews-f4B11235875.Google Scholar
• Hennig-Thurau T, Gwinner KP, Walsh G, Gremler DD (2004) Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? J. Interactive Marketing 18(1):38–52.Crossref, Google Scholar
• Hoff PD (2009) A First Course in Bayesian Statistical Methods (Springer, New York).Crossref, Google Scholar
• Hu N, Pavlou PA, Zhang J (2006) Can online reviews reveal a product’s true quality?: Empirical findings and analytical modeling of online word-of-mouth communication. Proc. 7th ACM Conf. Electronic Commerce (ACM, New York), 324–330.Crossref, Google Scholar
• Koop G, Poirier DJ, Tobias L (2007) Bayesian Econometric Methods (Econometric Exercises) (Cambridge University Press, New York).Crossref, Google Scholar
• Lee YJ, Hosanagar K, Tan Y (2015) Do I follow my friends or the crowd? Information cascades in online movie ratings. Management Sci. 61(9):2241–2258.Link, Google Scholar
• Leggatt H (2011) 24% of consumers turned off after two negative online reviews 2011. BizReport (April 13), http://www.bizreport.com/2011/04/27-of-consumers-turned-off-by-just-two-negative-online-revie.html.Google Scholar
• Li X, Hitt LM (2008) Self-selection and information role of online product reviews. Inform. Systems Res. 19(4):456–474.Link, Google Scholar
• MarketingCharts (2007) Most consumers read and reply on online reviews; companies must adjust. (November 2). http://www.marketingcharts.com/online/most-consumers-read-and-rely-on-online-reviews-companies-must-adjust-2234/.Google Scholar
• McGlohon M, Glance N, Reiter Z (2010) Star quality: Aggregating reviews to rank products and merchants. Presentation, Internat. Conf. Weblogs Soc. Media, Washington, DC, 127–139.Google Scholar
• McKinney V, Yoon K, Zahedi FM (2002) The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Inform. Systems Res. 13(3):296–315.Link, Google Scholar
• Moe WW, Schweidel DA (2012) Online product opinions: Incidence, evaluation, and evolution. Marketing Sci. 31(3):372–386.Link, Google Scholar
• Netzer O, Lattin JM, Srinivasan V (2008) A hidden Markov model of customer relationship dynamics. Marketing Sci. 27(2):185–204.Link, Google Scholar
• Nielson (2007) Word-of-mouth the most powerful selling tool , http://nielsenmedia.co.nz/files/TrustinAdvertisingOct07.pdf.Google Scholar
• Oliver RL (1977) Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. J. Appl. Psych. 62(4):480–486.Crossref, Google Scholar
• Oliver RL (1980) A cognitive model of the antecedents and consequences of satisfaction decisions. J. Marketing Res. 17(4):460–469.Crossref, Google Scholar
• Rust RT, Inman JJ, Jia J, Zahorik A (1999) What you don’t know about customer-perceived quality: The role of customer expectation distributions. Marketing Sci. 18(1):77–92.Link, Google Scholar
• Schlosser AE (2005) Posting versus lurking: Communicating in a multiple audience context. J. Consumer Res. 32(2):260–265.Crossref, Google Scholar
• Shen W, Hu YJ, Ulmer JR (2015) Competing for attention: An empirical study of online reviewers’ strategic behavior. MIS Quart. 39(3):683–696.Crossref, Google Scholar
• Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A (2002) Bayesian measures of model complexity and fit. J. Royal Statist. Soc.: Ser. B, Statist. Methodology 64(4):583–639.Crossref, Google Scholar
• Sundaram DS, Mitra K, Webster C (1998) Word-of-mouth communications: A motivational analysis. Adv. Consumer Res. 25(1):527–531.Google Scholar
• Susarla A, Barua A, Whinston AB (2003) Understanding the service component of application service provision: Empirical analysis of satisfaction with ASP services. MIS Quart. 27(1):91–123.Crossref, Google Scholar
• Taylor SJ (2014) Don’t fall for fake online reviews. U.S. News World Rep. (July 8), http://money.usnews.com/money/personalfinance/articles/2014/07/08/dont-fall-for-fake-online-reviewsarticles/2014/07/08/dont-fall-for-fake-online-reviews.Google Scholar
• Ying Y, Feinberg F, Wedel M (2006) Leveraging missing ratings to improve online recommendation systems. J. Marketing Res. 43(3):355–365.Crossref, Google Scholar