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Strategy Fads and Competitive Convergence: An Empirical Test for Herd Behavior in Prime‐Time Television Programming

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  • Robert E. Kennedy

Abstract

The economics literature contains many theoretical analyses of imitation and differentiation strategies but relatively few empirical studies of these topics. This paper aims to address that shortcoming. I analyze program introductions by television networks and then compare the payoffs to imitative and differentiated introductions. The analysis indicates that the networks imitate each other when introducing new programs and that, on average, imitative introductions underperform differentiated introductions. These results are consistent with theoretical models of herd behavior but are difficult to explain using standard models of spatial competition or the possibility of omitted variable bias.

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  • Robert E. Kennedy, 2002. "Strategy Fads and Competitive Convergence: An Empirical Test for Herd Behavior in Prime‐Time Television Programming," Journal of Industrial Economics, Wiley Blackwell, vol. 50(1), pages 57-84, March.
    • Handle: RePEc:bla:jindec:v:50:y:2002:i:1:p:57-84
    DOI: 10.1111/1467-6451.00168
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    Cited by:

    1. Fernando E. Alvarez & Francesco Lippi & Luigi Paciello, 2011. "Optimal Price Setting With Observation and Menu Costs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 1909-1960.
    2. Jungwon Yeo, 2017. "The Weekend Effect in Television Viewership and Prime-Time Scheduling," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 51(3), pages 315-341, November.
    3. Richard D. Wang & J. Myles Shaver, 2016. "The Multifaceted Nature of Competitive Response: Repositioning and New Product Launch as Joint Response to Competition," Strategy Science, INFORMS, vol. 1(3), pages 148-162, September.
    4. Dominic Rohner & Anna Winestein & Bruno S. Frey, 2006. "Ich Bin Auch ein Lemming: Herding and Consumption Capital in Arts and Culture," IEW - Working Papers 270, Institute for Empirical Research in Economics - University of Zurich.
    5. Stoneman, Paul, 2011. "Soft Innovation: Economics, Product Aesthetics, and the Creative Industries," OUP Catalogue, Oxford University Press, number 9780199697021.
    6. Jerker Denrell & Christina Fang, 2010. "Predicting the Next Big Thing: Success as a Signal of Poor Judgment," Management Science, INFORMS, vol. 56(10), pages 1653-1667, October.
    7. Marion Debruyne & David J. Reibstein, 2005. "Competitor See, Competitor Do: Incumbent Entry in New Market Niches," Marketing Science, INFORMS, vol. 24(1), pages 55-66, December.
    8. Bogaçhan Çelen & Shachar Kariv, 2004. "Distinguishing Informational Cascades from Herd Behavior in the Laboratory," American Economic Review, American Economic Association, vol. 94(3), pages 484-498, June.
    9. Elizabeth L. Rose & Kiyohiko Ito, 2009. "Past Interactions and New Foreign Direct Investment Location Decisions," Management International Review, Springer, vol. 49(5), pages 641-669, October.
    10. Andrea Fronzetti Colladon & Maurizio Naldi, 2019. "Predicting the performance of TV series through textual and network analysis: The case of Big Bang Theory," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-20, November.
    11. Jeffery S. McMullen & Dean A. Shepherd & Holger Patzelt, 2009. "Managerial (In)attention to Competitive Threats," Journal of Management Studies, Wiley Blackwell, vol. 46(2), pages 157-181, March.
    12. Olga M. Khessina & Samira Reis, 2016. "The Limits of Reflected Glory: The Beneficial and Harmful Effects of Product Name Similarity in the U.S. Network TV Program Industry, 1944–2003," Organization Science, INFORMS, vol. 27(2), pages 411-427, April.
    13. Morone, Andrea & Sandri, Serena & Fiore, Annamaria, 2009. "On the absorbability of informational cascades in the laboratory," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(5), pages 728-738, October.
    14. Feri, Francesco & Meléndez-Jiménez, Miguel A. & Ponti, Giovanni & Vega-Redondo, Fernando, 2011. "Error cascades in observational learning: An experiment on the Chinos game," Games and Economic Behavior, Elsevier, vol. 73(1), pages 136-146, September.
    15. Kelchtermans, Stijn & Neicu, Daniel & Teirlinck, Peter, 2020. "The role of peer effects in firms’ usage of R&D tax exemptions," Journal of Business Research, Elsevier, vol. 108(C), pages 74-91.
    16. Pastine, Tuvana & Pastine, Ivan, 2005. "Signal Accuracy and Informational Cascades," CEPR Discussion Papers 5219, C.E.P.R. Discussion Papers.
    17. Qihua Liu & Shan Huang & Liyi Zhang, 2016. "The influence of information cascades on online purchase behaviors of search and experience products," Electronic Commerce Research, Springer, vol. 16(4), pages 553-580, December.
    18. Pastine, Tuvana, 2005. "Social Learning in Continuous Time: When are Informational Cascades More Likely to be Inefficient?," CEPR Discussion Papers 5120, C.E.P.R. Discussion Papers.
    19. , & ,, 2011. "On the strategic use of attention grabbers," Theoretical Economics, Econometric Society, vol. 6(1), January.
    20. P.J. Lamberson, 2016. "Winner-take-all or long tail? A behavioral model of markets with increasing returns," System Dynamics Review, System Dynamics Society, vol. 32(3-4), pages 233-260, July.
    21. Alicia Barroso & Marco S. Giarratana & Samira Reis & Olav Sorenson, 2016. "Crowding, satiation, and saturation: The days of television series' lives," Strategic Management Journal, Wiley Blackwell, vol. 37(3), pages 565-585, March.

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