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Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews

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Abstract

This research examines whether the written contents of online reviews can generate systematic differences in the review’s perceived helpfulness even with identical ratings. In addition, this research explores which underlying psychological mechanism creates the systemic differences related to helpfulness. Specifically, the results from our two experiments demonstrate that, when an online hotel review has a positive rating, written contents containing both positive and negative information is perceived as more helpful than reviews with only positive written content. In contrast, when an online hotel review has a negative rating, written contents that contain only negative information is perceived as more helpful than reviews with written content containing both positive and negative information. Importantly, our study shows that the degree of information diagnosticity in online reviews behaves as an underlying psychological mechanism in the process. Our findings not only contribute to the extant literature but also provide useful insights and practical implications for travel websites.

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References

  • Agnihotri A, Bhattacharya S (2016) Online review helpfulness: role of qualitative factors. Psychol Mark 33(11):1006–1017

    Google Scholar 

  • Anderson C, Han S (2016) Hotel performance impact of socially engaging with consumers. Cornell Hosp Rep 16(10):3–9

    Google Scholar 

  • Bowerman BL, O’Connell RT (1990) Linear statistical models: an applied approach. Brooks/Cole, Pacific Grove

    Google Scholar 

  • Cao Q, Duan W, Gan Q (2011) Exploring determinants of voting for the “helpfulness” of online user reviews: a text mining approach. Decis Support Syst 50(2):511–521

    Google Scholar 

  • Chang HH, Tsai YC, Wong KH, Wang JW, Cho FJ (2015) The effects of response strategies and severity of failure on consumer attribution with regard to negative word-of-mouth. Decis Support Syst 71:48–61

    Google Scholar 

  • Chatterjee S (2020) Drivers of helpfulness of online hotel reviews: a sentiment and emotion mining approach. Int J Hosp Manag 85:102356

    Google Scholar 

  • Chen MY (2016) Can two-sided messages increase the helpfulness of online reviews? Online Inf Rev 40(3):316–332

    Google Scholar 

  • Chen CC, Tseng YD (2011) Quality evaluation of product reviews using an information quality framework. Decis Support Syst 50(4):755–768

    Google Scholar 

  • Cheung CMY, Sia CL, Kuan KK (2012) Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. J Assoc Inf Syst 13(8):2

    Google Scholar 

  • Chevalier JA, Mayzlin D (2006) The effect of word of mouth on sales: online book reviews. J Mark Res 43(3):345–354

    Google Scholar 

  • Chua AY, Banerjee S (2017) Analyzing review efficacy on Amazon.com: does the rich grow richer? Comput Hum Behav 75:501–509

    Google Scholar 

  • Feldman JM, Lynch JG (1988) Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. J Appl Psychol 73(3):421

    Google Scholar 

  • Field AP (2018) Discovering statistics using IBM SPSS statistics, 5th edn, Sage

  • Filieri R (2015) What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. J Bus Res 68(6):1261–1270

    Google Scholar 

  • Filieri R (2016) What makes an online consumer review trustworthy? Ann Tour Res 58:46–64

    Google Scholar 

  • Fiske ST, Linville PW (1980) What does the schema concept buy us? Personal Soc Psychol Bull 6(4):543–557

    Google Scholar 

  • Forman C, Ghose A, Wiesenfeld B (2008) Examining the relationship between reviews and sales: the role of reviewer identity disclosure in electronic markets. Inf Syst Res 19(3):291–313

    Google Scholar 

  • Godes D, Mayzlin D (2009) Firm-created word-of-mouth communication: evidence from a field test. Mark Sci 28(4):721–739

    Google Scholar 

  • Hao Y, Ye Q, Li Y, Cheng Z (2010) How does the valence of online consumer reviews matter in consumer decision making? Differences between search goods and experience goods. In: 2010 43rd Hawaii international conference on system sciences. IEEE, New York, pp 1–10

  • Hayes MH (2009) Statistical digital signal processing and modeling. Wiley, New York

    Google Scholar 

  • Herr PM, Kardes FR, Kim J (1991) Effects of word-of-mouth and product-attribute information on persuasion: an accessibility-diagnosticity perspective. J Consum Res 17(4):454–462

    Google Scholar 

  • Hong Y, Huang N, Burtch G, Li C (2016) Culture, conformity, and emotional suppression in online reviews. J Assoc Inf Syst 17(11):737–758

  • Hong H, Xu D, Wang GA, Fan W (2017) Understanding the determinants of online review helpfulness: a meta-analytic investigation. Decis Support Syst 102:1–11

    Google Scholar 

  • Hu YH, Chen K (2016) Predicting hotel review helpfulness: the impact of review visibility, and interaction between hotel stars and review ratings. Int J Inf Manag 36(6):929–944

    Google Scholar 

  • Ito TA, Larsen JT, Smith NK, Cacioppo JT (1998) Negative information weighs more heavily on the brain: the negativity bias in evaluative categorizations. J Personal Soc Psychol 75(4):887–900

    Google Scholar 

  • Jensen ML, Averbeck JM, Zhang Z, Wright KB (2013) Credibility of anonymous online product reviews: a language expectancy perspective. J Manag Inf Syst 30(1):293–324

    Google Scholar 

  • Kempf DS, Smith RE (1998) Consumer processing of product trial and the influence of prior advertising: a structural modeling approach. J Mark Res 35(3):325–338

    Google Scholar 

  • Kim Jong Min, Han J, Jun M (2020) Differences in mobile and nonmobile reviews: the role of perceived costs in review-posting. Int J Electron Commer 24(4):450–473

    Google Scholar 

  • Kostyra DS, Reiner J, Natter M, Klapper D (2016) Decomposing the effects of online customer reviews on brand, price, and product attributes. Int J Res Mark 33(1):11–26

    Google Scholar 

  • Lee PJ, Hu YH, Lu KT (2018) Assessing the helpfulness of online hotel reviews: a classification-based approach. Telemat Inform 35(2):436–445

    Google Scholar 

  • Li C, Cui G, Peng L (2017) The signaling effect of management response in engaging customers: a study of the hotel industry. Tour Manag 62:42–53

    Google Scholar 

  • Mizerski RW (1982) An attribution explanation of the disproportionate influence of unfavorable information. J Consum Res 9(3):301–310

    Google Scholar 

  • Mudambi S, Schuff D (2010) What makes a helpful review? A study of customer reviews on Amazon. com. 185–197. MIS Q 34(1):185–200

    Google Scholar 

  • Pan Y, Zhang JQ (2011) Born unequal: a study of the helpfulness of user-generated product reviews. J Retail 87(4):598–612

    Google Scholar 

  • Park S, Nicolau JL (2015) Asymmetric effects of online consumer reviews. Ann Tour Res 50:67–83

    Google Scholar 

  • Peeters G (1971) The positive–negative asymmetry: on cognitive consistency and positivity bias. Eur J Soc Psychol 1(4):455–474

    Google Scholar 

  • Preacher KJ, Hayes AF (2004) SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput 36(4):717–731

    Google Scholar 

  • Preacher KJ, Hayes AF (2008) Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 40(3):879–891

    Google Scholar 

  • Qazi A, Syed KBS, Raj RG, Cambria E, Tahir M, Alghazzawi D (2016) A concept-level approach to the analysis of online review helpfulness. Comput Hum Behav 58:75–81

    Google Scholar 

  • Qiu L, Pang J, Lim KH (2012) Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: the moderating role of review valence. Decis Support Syst 54(1):631–643

    Google Scholar 

  • Racherla P, Friske W (2012) Perceived ‘usefulness’ of online consumer reviews: an exploratory investigation across three services categories. Electron Commer Res Appl 11(6):548–559

    Google Scholar 

  • Reyes-Menendez A, Saura JR, Filipe F (2019a) The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review. Peer J Comput Sci 5:e219

    Google Scholar 

  • Reyes-Menendez A, Saura JR, Martinez-Navalon JG (2019b) The impact of e-WOM on hotels management reputation: exploring TripAdvisor review credibility with the ELM model. IEEE Access. https://doi.org/10.1109/access.2019.2919030

    Article  Google Scholar 

  • Rozin P, Royzman EB (2001) Negativity bias, negativity dominance, and contagion. Personal Soc Psychol Rev 5(4):296–320

    Google Scholar 

  • Rucker DD, Preacher KJ, Tormala ZL, Petty RE (2011) Mediation analysis in social psychology: current practices and new recommendations. Soc Personal Psychol Compass 5(6):359–371

    Google Scholar 

  • Schlosser AE (2011) Can including pros and cons increase the helpfulness and persuasiveness of online reviews? The interactive effects of ratings and arguments. J Consum Psychol 21(3):226–239

    Google Scholar 

  • Sen S, Lerman D (2007) Why are you telling me this? An examination into negative consumer reviews on the web. J Interact Mark 21(4):76–94

    Google Scholar 

  • Skowronski JJ, Carlston DE (1989) Negativity and extremity biases in impression formation: a review of explanations. Psychol Bull 105(1):131–142

    Google Scholar 

  • Srivastava V, Kalro AD (2019) Enhancing the helpfulness of online consumer reviews: the role of latent (content) factors. J Interact Mark 48:33–50

    Google Scholar 

  • Tang T, Fang E, Wang F (2014) Is neutral really neutral? The effects of neutral user-generated content on product sales. J Mark 78(4):41–58

    Google Scholar 

  • Taylor SE (1991) Asymmetrical effects of positive and negative events: the mobilization-minimization hypothesis. Psychol Bull 110(1):67–85

    Google Scholar 

  • Wang Y, Chaudhry A (2018) When and how managers’ responses to online reviews affect subsequent reviews. J Mark Res 55(2):163–177

    Google Scholar 

  • Willemsen LM, Neijens PC, Bronner F, De Ridder JA (2011) “Highly recommended!” The content characteristics and perceived usefulness of online consumer reviews. J Comput Mediat Commun 17(1):19–38

    Google Scholar 

  • Wright P (1974) The harassed decision maker: time pressures, distractions, and the use of evidence. J Appl Psychol 59(5):555–561

    Google Scholar 

  • Wu PF (2013) In search of negativity bias: an empirical study of perceived helpfulness of online reviews. Psychol Mark 30(11):971–984

    Google Scholar 

  • Wu PF, Van der Heijden H, Korfiatis N (2011) The influences of negativity and review quality on the helpfulness of online reviews. In: International conference on information systems

  • Xie HJ, Miao L, Kuo PJ, Lee BY (2011) Consumers’ responses to ambivalent online hotel reviews: the role of perceived source credibility and pre-decisional disposition. Int J Hosp Manag 30(1):178–183

    Google Scholar 

  • Xie KL, Zhang Z, Zhang Z (2014) The business value of online consumer reviews and management response to hotel performance. Int J Hosp Manag 43:1–12

    Google Scholar 

  • Yin D, Bond SD, Zhang H (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Q 38(2):539–560

    Google Scholar 

  • Yin D, Bond SD, Zhang H (2017) Keep your cool or let it out: nonlinear effects of expressed arousal on perceptions of consumer reviews. J Mark Res 54(3):447–463

    Google Scholar 

  • Zhou Yusheng, Shuiqing Yang, Yixiao Li, Yuangao Chen, Yao Jianrong, Qazi Atika (2020) Does the review deserve more helpfulness when its title resembles the content? Locating helpful reviews by text mining. Inf Process Manag 57(2):102179

    Google Scholar 

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Correspondence to Jeongsoo Han.

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Kim, M., Han, J. & Jun, M. Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews. Inf Technol Tourism 22, 563–591 (2020). https://doi.org/10.1007/s40558-020-00191-1

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  • DOI: https://doi.org/10.1007/s40558-020-00191-1

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