IDEAS home Printed from https://ideas.repec.org/p/pdn/dispap/13.html
   My bibliography  Save this paper

The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry

Author

Listed:
  • Daniel Kaimann

    (University of Paderborn)

  • Joe Cox

    (Portsmouth Business School)

Abstract

Customers continuously evaluate the credibility and reliability of a range of signals both separately and jointly. However, existing econometric studies pay insufficient attention to the interactions and complex combinations of these signals, and are typically limited as a result of difficulties controlling for multicollinearity and endogeneity in their data. We develop a novel theoretical approach to address these issues and study different signaling effects (i.e., word-of-mouth, brand reputation, and distribution strategy) on customer perceptions. Using data on the US video games market, we apply a fuzzy set qualitative comparative analysis (fsQCA) to account for cause-effect relationships. The results of our study address a number of key issues in the economics and management literature. First, our results support the contention that reviews from professional critics act as a signal of product quality and therefore positively influence unit sales, as do the discriminatory effects of prices and restricted age ratings. Second, we find evidence to support the use of brand extension strategies as marketing tools that create spillover effects and support the launch of new products.

Suggested Citation

  • 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.
  • Handle: RePEc:pdn:dispap:13
    as

    Download full text from publisher

    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP13.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van Horen, Femke & Pieters, Rik, 2012. "Consumer evaluation of copycat brands: The effect of imitation type," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 246-255.
    2. Pham, Michel Tuan & Geuens, Maggie & De Pelsmacker, Patrick, 2013. "The influence of ad-evoked feelings on brand evaluations: Empirical generalizations from consumer responses to more than 1000 TV commercials," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 383-394.
    3. 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.
    4. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    5. 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.
    6. Park, Joo Heon & MacLachlan, Douglas L. & Love, Edwin, 2011. "New product pricing strategy under customer asymmetric anchoring," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 309-318.
    7. 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.
    8. De Vany, A. & Walls, W.D., 1999. ""Uncertainty in the Movies: Does Star Power Reduce the Terror of the Box Office?"," Papers 98-99-10, California Irvine - School of Social Sciences.
    9. 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.
    10. 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.
    11. East, Robert & Hammond, Kathy & Lomax, Wendy, 2008. "Measuring the impact of positive and negative word of mouth on brand purchase probability," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 215-224.
    12. Gierl, Heribert & Huettl, Verena, 2010. "Are scarce products always more attractive? The interaction of different types of scarcity signals with products' suitability for conspicuous consumption," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 225-235.
    13. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
    14. Randy Nelson & Robert Glotfelty, 2012. "Movie stars and box office revenues: an empirical analysis," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 141-166, May.
    15. Kevin Lane Keller & Donald R. Lehmann, 2006. "Brands and Branding: Research Findings and Future Priorities," Marketing Science, INFORMS, vol. 25(6), pages 740-759, 11-12.
    16. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    17. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    18. Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
    19. Riefler, Petra, 2012. "Why consumers do (not) like global brands: The role of globalization attitude, GCO and global brand origin," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 25-34.
    20. Schlereth, Christian & Skiera, Bernd, 2012. "Measurement of consumer preferences for bucket pricing plans with different service attributes," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 167-180.
    21. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773, December.
    22. Moldovan, Sarit & Goldenberg, Jacob & Chattopadhyay, Amitava, 2011. "The different roles of product originality and usefulness in generating word-of-mouth," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 109-119.
    23. Nelson, Randy A, et al, 2001. "What's an Oscar Worth?," Economic Inquiry, Western Economic Association International, vol. 39(1), pages 1-16, January.
    24. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    25. 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.
    26. 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.
    27. Chakravarty, Anindita & Liu, Yong & Mazumdar, Tridib, 2010. "The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 185-197.
    28. Joseph E. Stiglitz, 2002. "Information and the Change in the Paradigm in Economics," American Economic Review, American Economic Association, vol. 92(3), pages 460-501, June.
    29. Sattler, Henrik & Völckner, Franziska & Riediger, Claudia & Ringle, Christian M., 2010. "The impact of brand extension success drivers on brand extension price premiums," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 319-328.
    30. 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.
    31. Leenders, Mark A.A.M. & Eliashberg, Jehoshua, 2011. "The antecedents and consequences of restrictive age-based ratings in the global motion picture industry," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 367-377.
    32. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
    33. Gierl, Heribert & Huettl, Verena, 2011. "A closer look at similarity: The effects of perceived similarity and conjunctive cues on brand extension evaluation," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 120-133.
    34. 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.
    35. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    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. Yaokuang Li & Li Ling & Daru Zhang & Juan Wu, 2021. "Lead investors and information disclosure: A test of signaling theory by fuzzy‐set qualitative comparative analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 836-849, 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 CIE 84, Paderborn University, CIE Center for International Economics.
    2. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    3. 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.
    4. 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.
    5. 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.
    6. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    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. 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.
    9. Christoph Schneider & Markus Weinmann & Peter N.C. Mohr & Jan vom Brocke, 2021. "When the Stars Shine Too Bright: The Influence of Multidimensional Ratings on Online Consumer Ratings," Management Science, INFORMS, vol. 67(6), pages 3871-3898, June.
    10. 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.
    11. Fan, Liu & Zhang, Xiaoping & Rai, Laxmisha, 2021. "When should star power and eWOM be responsible for the box office performance? - An empirical study based on signaling theory," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    12. 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.
    13. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
    14. 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.
    15. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    16. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    17. Agnieszka Zablocki & Bodo Schlegelmilch & Michael J. Houston, 2019. "How valence, volume and variance of online reviews influence brand attitudes," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 61-77, June.
    18. Hyunwoo Hwangbo & Jonghyuk Kim, 2019. "A Text Mining Approach for Sustainable Performance in the Film Industry," Sustainability, MDPI, vol. 11(11), pages 1-16, June.
    19. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    20. S. Cicognani & P. Figini & M. Magnani, 2016. "Social Influence Bias in Online Ratings: A Field Experiment," Working Papers wp1060, Dipartimento Scienze Economiche, Universita' di Bologna.

    More about this item

    Keywords

    Signaling Theory; Information Asymmetry; Interactions; Fuzzy sets; Qualitative Comparative Analysis; Video Game Industry;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • 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:13. 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.