Why Not All Managerial Responses Are Created Equal: A Causal Investigation of Their Effect on Online Review Systems’ Users

Published Online:https://doi.org/10.1287/serv.2024.0160

References

  • Ahluwalia R (2002) How prevalent is the negativity effect in consumer environments? J. Consumer Res. 29(2):270–279.CrossrefGoogle Scholar
  • Ansari S, Gupta S (2021) Customer perception of the deceptiveness of online product reviews: A speech act theory perspective. Internat. J. Inform. Management 57(C):102286. Google Scholar
  • Bian Q, Forsythe S (2012) Purchase intention for luxury brands: A cross cultural comparison. J. Bus. Res. 65(10):1443–1451.CrossrefGoogle Scholar
  • Chen W, Gu B, Ye Q, Zhu KX (2019) Measuring and managing the externality of managerial responses to online customer reviews. Inform. Systems Res. 30(1):81–96.LinkGoogle Scholar
  • Chevalier JA, Dover Y, Mayzlin D (2018) Channels of impact: User reviews when quality is dynamic and managers respond. Marketing Sci. 37(5):688–709.LinkGoogle Scholar
  • Cummings JJ, Wertz B (2022) Capturing social presence: Concept explication through an empirical analysis of social presence measures. J. Comput.-Mediated Comm. 28(1):11–14.CrossrefGoogle Scholar
  • Deng C, Ravichandran T (2016) Managerial Response to Online Compliments: Helpful or Harmful? ICIS 2016 Proceedings, 11 (November 21), https://aisel.aisnet.org/icis2016/SocialMedia/Presentations/11.Google Scholar
  • Farivar S, Yuan Y, Turel O (2016) Understanding social commerce acceptance: The role of trust, perceived risk, and benefit. AMCIS 2016 Proceedings, 13 (July 12), https://aisel.aisnet.org/amcis2016/DigitalComm/Presentations/13.Google Scholar
  • 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.CrossrefGoogle Scholar
  • Foreh MR, Grier S (2003) When is honesty the best policy? The effect of stated company intent on consumer skepticism. J. Consumer Psych. 13(3):349–356.CrossrefGoogle Scholar
  • Friestad M, Wright P (1994) The persuasion knowledge model: How people cope with persuasion attempts. J. Consumer Res. 21(1):1–31.CrossrefGoogle Scholar
  • Gao Y, Rui H, Sun S (2023) The power of identity cues in text-based customer service: Evidence from Twitter. MIS Quart. 47(3):983.CrossrefGoogle Scholar
  • Gefen D (2000) E-commerce: The role of familiarity and trust. Omega (Westport) 28(6):725–737.CrossrefGoogle Scholar
  • Gefen D, Straub DW (2004) Consumer trust in B2C e-commerce and the importance of social presence: Experiments in e-products and e-services. Omega (Westport) 32(6):407–424.CrossrefGoogle Scholar
  • Gefen D, Karahanna E, Straub DW (2003) Trust and TAM in online shopping: An integrated model. MIS Quart. 27(1):51–90.CrossrefGoogle Scholar
  • Gefen D, Rigdon EE, Straub D (2011) Editor’s comments: An update and extension to SEM guidelines for administrative and social science research. MIS Quart. 35(2):iii–xiv.CrossrefGoogle Scholar
  • Gu B, Ye Q (2014) First step in social media: Measuring the influence of online management responses on customer satisfaction. Production Oper. Management 23(4):570–582.CrossrefGoogle Scholar
  • Hawkes M (2023) Local consumer review survey 2023. BrightLocal (February 7), https://www.brightlocal.com/research/local-consumer-review-survey-2023/.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. Consumer Res. 17(4):454–462.CrossrefGoogle Scholar
  • Huang J, Boh WF, Goh KH (2017) A temporal study of the effects of online opinions: Information sources matter. J. Management Inform. Systems 34(4):1169–1202.CrossrefGoogle Scholar
  • Huang Y, Jin Y, Huang J (2021) Impact of managerial responses on product sales: Examining the moderating role of competitive intensity and market position. J. Assoc. Inform. Systems 22(2):544–570.Google Scholar
  • Jiang Z, Benbasat I (2007) Research note—Investigating the influence of the functional mechanisms of online product presentations. Inform. Systems Res. 18(4):454–470.LinkGoogle Scholar
  • Kelley HH (1973) The processes of causal attribution. Amer. Psych. 28(2):107–128.CrossrefGoogle Scholar
  • Kim DJ, Ferrin DL, Rao HR (2009) Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Inform. Systems Res. 20(2):237–257.LinkGoogle Scholar
  • Kline RB (2015) Principles and Practice of Structural Equation Modeling (Guilford Publications, New York).Google Scholar
  • Kumar N, Benbasat I (2006) Research note: The influence of recommendations and consumer reviews on evaluations of websites. Inform. Systems Res. 17(4):425–439.LinkGoogle Scholar
  • Kumar N, Qiu L, Kumar S (2018) Exit, voice, and response on digital platforms: An empirical investigation of online management response strategies. Inform. Systems Res. 29(4):849–870.LinkGoogle Scholar
  • Lee CH, Cranage DA (2012) Toward understanding consumer processing of negative online word-of-mouth communication. J. Hospitality Tourism Res. 38(3):330–360.CrossrefGoogle Scholar
  • Lee K, Lee B, Oh W (2015) Thumbs up, sales up? The contingent effect of Facebook likes on sales performance in social commerce. J. Management Inform. Systems 32(4):109–143.CrossrefGoogle Scholar
  • Lee YJ, Xie K, Besharat A (2016) Management response to online WOM: Helpful or detrimental? Am. Conf. Inf. Syst. (Association of Information Systems, Atlanta, GA), 13.Google Scholar
  • Liu QB, Karahanna E, Watson RT (2011) Unveiling user-generated content: Designing websites to best present customer reviews. Bus. Horizons 54(3):231–240.CrossrefGoogle Scholar
  • Lui TW, Bartosiak M, Piccoli G, Sadhya V (2018) Online review response strategy and its effects on competitive performance. Tourism Management 67:180–190.CrossrefGoogle Scholar
  • Marth S, Hartl B, Penz E (2022) Sharing on platforms: Reducing perceived risk for peer‐to‐peer platform consumers through trust‐building and regulation. J. Consumer Behav. 21(6):1255–1267.CrossrefGoogle Scholar
  • Moradi M, Zihagh F (2022) A meta‐analysis of the elaboration likelihood model in the electronic word of mouth literature. Internat. J. Consumer Stud. 46(5):1900–1918.CrossrefGoogle Scholar
  • Morris MW, Larrick RP (1995) When one cause casts doubt on another: A normative analysis of discounting in causal attribution. Psych. Rev. 102(2):331.CrossrefGoogle Scholar
  • Mudambi SM, Schuff D (2010) Research note: What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Quart. 34(1):185–200.CrossrefGoogle Scholar
  • Oberski D (2014) lavaan.survey: An R package for complex survey analysis of structural equation models. J. Statist. Software 57(1):1–27.CrossrefGoogle Scholar
  • Ou CX, Pavlou PA, Davison RM (2014) Swift Guanxi in online marketplaces: The role of computer-mediated communication technologies. MIS Quart. 38(1):209–230.CrossrefGoogle Scholar
  • Palese B, Piccoli G (2018) Effective use of systems beyond the firm’s control: The case of online review systems. Int. Conf. Inf. Syst. (Louisiana State University, Baton Rouge, LA).Google Scholar
  • Palese B, Piccoli G, Lui TW (2021) Effective use of online review systems: Congruent managerial responses and firm competitive performance. Internat. J. Hospitality Management 96:102976.CrossrefGoogle Scholar
  • Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quart. 31(1):105–136.CrossrefGoogle Scholar
  • Petty RE, Cacioppo JT (2012) Communication and Persuasion: Central and Peripheral Routes to Attitude Change (Springer Science & Business Media, New York).Google Scholar
  • Piccoli G (2016) Triggered essential reviewing: The effect of technology affordances on service experience evaluations. Eur. J. Inform. Systems 25(6):477–492.CrossrefGoogle Scholar
  • Piccoli G, Ott M (2014) Impact of mobility and timing on user-generated content. MIS Q. Executive 13(3):147–157.Google Scholar
  • Preacher KJ, Selig JP (2012) Advantages of Monte Carlo confidence intervals for indirect effects. Comm. Methods Measures 6(2):77–98.CrossrefGoogle Scholar
  • Proserpio D, Zervas G (2017) Online reputation management: Estimating the impact of management responses on consumer reviews. Marketing Sci. 36(5):645–665.LinkGoogle Scholar
  • Qiao D, Lee SY, Whinston AB, Wei Q (2020) Financial incentives dampen altruism in online prosocial contributions: A study of online reviews. Inform. Systems Res. 31(4):1361–1375.LinkGoogle Scholar
  • Rosseel Y (2012) Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). J. Statist. Software 48(2):1–36.CrossrefGoogle Scholar
  • Shao Z, Zhang L, Pan Z, Benitez J (2023) Uncovering the dual influence processes for click-through intention in the mobile social platform: An elaboration likelihood model perspective. Inform. Management 60(5):103799.CrossrefGoogle Scholar
  • Shimul AS, Cheah I, Khan BB (2022) Investigating female shoppers’ attitude and purchase intention toward green cosmetics in South Africa. J. Global Marketing 35(1):37–56.CrossrefGoogle Scholar
  • Silic M, Ruf C (2018) The effects of the elaboration likelihood model on initial trust formation in financial advisory services. Internat. J. Bank Marketing 36(3):572–590.CrossrefGoogle Scholar
  • Snead KC Jr, Magal SR, Christensen LF, Ndede-Amadi AA (2015) Attribution theory: A theoretical framework for understanding information systems success. Systemic Practice Action Res. 28(3):273–288.CrossrefGoogle Scholar
  • Sparks BA, Browning V (2011) The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management 32(6):1310–1323.CrossrefGoogle Scholar
  • Tian Y, Zhang H, Jiang Y, Yang Y (2022) Understanding trust and perceived risk in sharing accommodation: An extended elaboration likelihood model and moderated by risk attitude. J. Hospitality Marketing Management 31(3):348–368.CrossrefGoogle Scholar
  • Tong Y, Wang X, Tan CH, Teo HH (2013) An empirical study of information contribution to online feedback systems: A motivation perspective. Inform. Management 50(7):562–570.CrossrefGoogle Scholar
  • Wang Y, Wang J, Yao T (2019) What makes a helpful online review? A meta-analysis of review characteristics. Electronic Commerce Res. 19(2):257–284.CrossrefGoogle Scholar
  • Wilson EJ, Sherrell DL (1993) Source effects in communication and persuasion research: A meta-analysis of effect size. J. Acad. Marketing Sci. 21(2):101–112.CrossrefGoogle Scholar
  • Xie KL, So KKF, Wang W (2017) Joint effects of management responses and online reviews on hotel financial performance: A data-analytics approach. Internat. J. Hospitality Management 62:101–110.CrossrefGoogle Scholar
  • Xie KL, Zhang Z, Zhang Z (2014) The business value of online consumer reviews and management response to hotel performance. Internat. J. Hospitality Management 43:1–12.CrossrefGoogle Scholar
  • Xu X, Wang X, Li Y, Haghighi M (2017) Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors. Internat. J. Inform. Management 37(6):673–683.CrossrefGoogle Scholar
  • Yin D, Bond SD, Zhang H (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Quart. 38(2):539–560.CrossrefGoogle Scholar
  • Zhang X, Lee SK, Maeng H, Hahn S (2023) Effects of failure types on trust repairs in human–robot interactions. Internat. J. Soc. Robotics 15(9):1619–1635.CrossrefGoogle Scholar
  • Zhang Z, Li H, Meng F, Li Y (2019) The effect of management response similarity on online hotel booking. Internat. J. Contempory Hospitality Management 31(7):2739–2758.CrossrefGoogle Scholar
  • Zhang X, Qiao S, Yang Y, Zhang Z (2020) Exploring the impact of personalized management responses on tourists’ satisfaction: A topic matching perspective. Tourism. Management 76:103953.CrossrefGoogle Scholar
  • Zhou C, Yang S, Chen Y, Zhou S, Li Y, Qazi A (2023) How does topic consistency affect online review helpfulness? The role of review emotional intensity. Electronic Commerce Res. 23(4):2943–2978.CrossrefGoogle Scholar
  • Zou H, Qureshi I, Fang Y, Sun H, Lim KH, Ramsey E, McCole P (2022) Investigating the nonlinear and conditional effects of trust—The new role of institutional contexts in online repurchase. Inform. Systems J. 33(3):486–523.CrossrefGoogle Scholar
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