IDEAS home Printed from https://ideas.repec.org/p/pdn/dispap/10.html
   My bibliography  Save this paper

The Signaling Effect of Critics: Do Professionals outweigh Word-of-Mouth? Evidence from the Video Game Industry

Author

Listed:
  • Daniel Kaimann

    (University of Paderborn)

  • Joe Cox

    (Portsmouth Business School)

Abstract

Experience goods are characterized by information asymmetry and a lack of ex ante knowledge of product quality, such that reliable external signals of product quality are likely to be highly valued. Two potentially credible sources of such information are reviews from professional critics with expert reputations, as well as ‘word-of-mouth’ reviews from other consumers. This paper makes a direct comparison between the relative influence of both critic and user reviews on the sales of video games software. In order to empirically estimate and separate the effects of the two signals, we analyze a sample of 1,480 video games and their sales figures between 2004 and 2010. We find clear evidence to suggest that reviews from professional critics have a significantly positive influence on sales that outweighs word-of-mouth reviews. Consequently, we support the hypothesis that professional critics adopt the role of an influencer whereas word-of-mouth opinion acts merely as a predictor of sales.

Suggested Citation

  • Daniel Kaimann & Joe Cox, 2014. "The Signaling Effect of Critics: Do Professionals outweigh Word-of-Mouth? Evidence from the Video Game Industry," Working Papers Dissertations 10, Paderborn University, Faculty of Business Administration and Economics.
  • Handle: RePEc:pdn:dispap:10
    as

    Download full text from publisher

    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP10.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ravid, S Abraham, 1999. "Information, Blockbusters, and Stars: A Study of the Film Industry," The Journal of Business, University of Chicago Press, vol. 72(4), pages 463-492, October.
    2. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2007. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Working Papers 07-36, NET Institute.
    3. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    4. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    5. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    6. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    7. Arthur De Vany & W. David Walls, 2002. "Does Hollywood Make Too Many R-Rated Movies? Risk, Stochastic Dominance, and the Illusion of Expectation," The Journal of Business, University of Chicago Press, vol. 75(3), pages 425-452, July.
    8. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Peter Boatwright & Suman Basuroy & Wagner Kamakura, 2007. "Reviewing the reviewers: The impact of individual film critics on box office performance," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 401-425, December.
    10. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tom Hamami, 2019. "Network Effects, Bargaining Power, and Product Review Bias: Theory and Evidence," Journal of Industrial Economics, Wiley Blackwell, vol. 67(2), pages 372-407, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers Dissertations 13, Paderborn University, Faculty of Business Administration and Economics.
    2. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers CIE 84, Paderborn University, CIE Center for International Economics.
    3. Joe Cox & Daniel Kaimann, 2013. "The Signaling Effect of Critics - Evidence from a Market for Experience Goods," Working Papers CIE 68, Paderborn University, CIE Center for International Economics.
    4. Dominik Gutt, 2018. "In the Eye of the Beholder? Empirically Decomposing Different Economic Implications of the Online Rating Variance," Working Papers Dissertations 40, Paderborn University, Faculty of Business Administration and Economics.
    5. Kun Chen & Peng Luo & Huaiqing Wang, 2017. "Investigating transitive influences on WOM: from the product network perspective," Electronic Commerce Research, Springer, vol. 17(1), pages 149-167, March.
    6. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    7. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    8. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    9. Daniel Kaimann, 2014. "Combining Qualitative Comparative Analysis and Shapley Value Decomposition: A Novel Approach for Modeling Complex Causal Structures in Dynamic Markets," Working Papers Dissertations 12, Paderborn University, Faculty of Business Administration and Economics.
    10. Peiyu Chen & Lorin M. Hitt & Yili Hong & Shinyi Wu, 2021. "Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application," Information Systems Research, INFORMS, vol. 32(4), pages 1470-1489, December.
    11. Steffen Zimmermann & Philipp Herrmann & Dennis Kundisch & Barrie R. Nault, 2018. "Decomposing the Variance of Consumer Ratings and the Impact on Price and Demand," Information Systems Research, INFORMS, vol. 29(4), pages 984-1002, December.
    12. Daniel Kaimann, 2020. "Behind the Review Curtain: Decomposition of Online Consumer Ratings in Peer-to-Peer Markets," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
    13. Lifang Peng & Qinyu Liao & Xiaorong Wang & Xuanfang He, 2016. "Factors affecting female user information adoption: an empirical investigation on fashion shopping guide websites," Electronic Commerce Research, Springer, vol. 16(2), pages 145-169, June.
    14. Yang Liu & Juan Feng & Xiuwu Liao, 2017. "When Online Reviews Meet Sales Volume Information: Is More or Accurate Information Always Better?," Information Systems Research, INFORMS, vol. 28(4), pages 723-743, December.
    15. Yogesh V. Joshi & Andres Musalem, 2021. "When Consumers Learn, Money Burns: Signaling Quality via Advertising with Observational Learning and Word of Mouth," Marketing Science, INFORMS, vol. 40(1), pages 168-188, January.
    16. Daniel Kaimann & Joe Cox, 2021. "A Comparative Analysis of Consumption: Evidence from a Cultural Goods Market," Sustainability, MDPI, vol. 13(23), pages 1-21, November.
    17. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    18. Mingfeng Lin & Yong Liu & Siva Viswanathan, 2018. "Effectiveness of Reputation in Contracting for Customized Production: Evidence from Online Labor Markets," Management Science, INFORMS, vol. 64(1), pages 345-359, January.
    19. Yabing Jiang & Hong Guo, 2015. "Design of Consumer Review Systems and Product Pricing," Information Systems Research, INFORMS, vol. 26(4), pages 714-730, December.
    20. Jürgen Neumann & Dominik Gutt & Dennis Kundisch, 2018. "The Traveling Reviewer Problem – Exploring the Relationship between Offline Locations and Online Rating Behavior," Working Papers Dissertations 44, Paderborn University, Faculty of Business Administration and Economics.

    More about this item

    Keywords

    Signaling Theory; Information Asymmetry; Critics; Word-of-Mouth; Video Game Industry;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pdn:dispap:10. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: WP-WiWi-Info (email available below). General contact details of provider: https://edirc.repec.org/data/fwpadde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.