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The Effects of Detailing on Prescribing Decisions under Two-Sided Learning

  • Ching, Andrew
  • Ishihara, Masakazu

A fundamental question in pharmaceutical marketing management is: How does the effectiveness of detailing change when additional information on drugs is revealed via patients' experiences during the product lifecycle? To address this question, we develop a model of detailing and prescribing decisions which incorporates uncertainty about the quality of drugs. Our model assumes that not only physicians/patients, but also drug manufacturers are uncertain about the qualities of drugs, and a representative opinion leader is responsible for updating the prior belief about these qualities. Physicians are heterogeneous in their information sets, and drug manufacturers use detailing as a means to increase/maintain the measure of well-informed physicians. We explicitly model physicians' forgetting by allowing the measure of well-informed physicians to depreciate over time. We estimate our model using product level data of ACE-inhibitor with diuretic in Canada. Our estimation approach allows us to control for the potential endogeneity of detailing. The results show that our model is able to fit the diffusion pattern very well, the effectiveness of detailing depends on the current information set and the measure of well-informed physicians, and the role of detailing-in-utility is minimal. Using our parameter estimates, we examine how a public awareness campaign, which encourages physicians/patients to report their drug experiences, would affect managerial incentives to detail.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4935.

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Date of creation: 10 Sep 2007
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Handle: RePEc:pra:mprapa:4935
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  1. Ernst R. Berndt & Linda T. Bui & David H. Lucking-Reiley & Glen L. Urban, 1996. "The Roles of Marketing, Product Quality, and Price Competition in the Growth and Composition of the U.S. Antiulcer Drug Industry," NBER Chapters, in: The Economics of New Goods, pages 277-328 National Bureau of Economic Research, Inc.
  2. Pierre Azoulay, 2002. "Do Pharmaceutical Sales Respond to Scientific Evidence?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 11(4), pages 551-594, December.
  3. James J. Heckman, 1981. "Heterogeneity and State Dependence," NBER Chapters, in: Studies in Labor Markets, pages 91-140 National Bureau of Economic Research, Inc.
  4. Sendhil Mullainathan, 2002. "A Memory-Based Model Of Bounded Rationality," The Quarterly Journal of Economics, MIT Press, vol. 117(3), pages 735-774, August.
  5. Ernst R. Berndt & Robert S. Pindyck & Pierre Azoulay, 2003. "Consumption Externalities and Diffusion in Pharmaceutical Markets: Antiulcer Drugs," Journal of Industrial Economics, Wiley Blackwell, vol. 51(2), pages 243-270, 06.
  6. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2004. "Role of Forgetting in Memory-Based Choice Decisions: A Structural Model," Quantitative Marketing and Economics, Springer, vol. 2(2), pages 107-140, June.
  7. Dirk Bergemann & Juuso Valimaki, 1996. "Market Diffusion with Two-Sided Learning," Cowles Foundation Discussion Papers 1138, Cowles Foundation for Research in Economics, Yale University.
  8. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
  9. Ching, Andrew, 2008. "Consumer Learning and Heterogeneity: Dynamics of Demand for Prescription Drugs after Patent Expiration," MPRA Paper 7265, University Library of Munich, Germany.
  10. Andrew T. Ching, 2010. "A Dynamic Oligopoly Structural Model For The Prescription Drug Market After Patent Expiration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(4), pages 1175-1207, November.
  11. Günter J. Hitsch, 2006. "An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty," Marketing Science, INFORMS, vol. 25(1), pages 25-50, 01-02.
  12. Andrew Ching, 2000. "Dynamic Equilibrium in the US Prescription Drug Market After Patent Expiration," Econometric Society World Congress 2000 Contributed Papers 1242, Econometric Society.
  13. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
  14. Nair, Harikesh S. & Manchanda, Puneet & Bhatia, Tulikaa, 2006. "Asymmetric Peer Effects in Physician Prescription Behavior: The Role of Opinion Leaders," Research Papers 1970, Stanford University, Graduate School of Business.
  15. Becker, Gary S & Murphy, Kevin M, 1993. "A Simple Theory of Advertising as a Good or Bad," The Quarterly Journal of Economics, MIT Press, vol. 108(4), pages 941-64, November.
  16. Dirk Bergemann & Juuso Välimäki, 2006. "Dynamic Pricing of New Experience Goods," Journal of Political Economy, University of Chicago Press, vol. 114(4), pages 713-743, August.
  17. J. Miguel Villas-Boas, 2006. "Dynamic Competition with Experience Goods," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 15(1), pages 37-66, 03.
  18. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
  19. Venkataraman, S. & Stremersch, S., 2007. "The Debate on Influencing Doctors’ Decisions: Are Drug Characteristics the Missing Link?," ERIM Report Series Research in Management ERS-2007-056-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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