Understanding Responses to Contradictory Information About Products

Although prior literature has examined reactions to drastic negative news, we examine the situation in which decision makers receive contradictory information about products and they have to decide whether to persist with or abandon product usage. We investigate physician reactions to conflicting information concerning the cardiovascular risk of Avandia, a diabetes drug. We examine how beliefs about both drug effectiveness and drug safety are updated and speculate that experience, expertise, and self-efficacy impact how such information is integrated with current quality beliefs. Unlike previous Bayesian learning models, we consider that some signals, such as positive and negative news releases and the firm's marketing effort, may be biased in that they provide an opinionated point of view. The results show interesting differences in how physician types specialists, hospital-based primary care physicians, heavy and light prescribers update their beliefs and the information sources they use to do so. We find evidence that safety issues about Avandia resulted in spillover concern to close competitor Actos. The results have implication for determining who should be targeted and what vehicles should be used if a firm is faced with a situation where consumers are in a quandary because of receiving conflicting messages.

[1]  M. Keane,et al.  Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets , 1996 .

[2]  Tülin Erdem,et al.  Learning Models: An Assessment of Progress, Challenges and New Developments , 2011 .

[3]  M. Pillutla,et al.  Impact of Product-Harm Crises on Brand Equity: The Moderating Role of Consumer Expectations , 2000 .

[4]  Pradeep Chintagunta,et al.  Information, learning, and drug diffusion: The case of Cox-2 inhibitors , 2008 .

[5]  T. Hoff,et al.  Characteristics and work experiences of hospitalists in the United States. , 2001, Archives of internal medicine.

[6]  Xinlei Chen,et al.  Informing, Transforming, and Persuading: Disentangling the Multiple Effects of Advertising on Brand Choice Decisions , 2008, Mark. Sci..

[7]  Peter E. Rossi,et al.  Response Modeling with Nonrandom Marketing-Mix Variables , 2004 .

[8]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[9]  Puneet Manchanda,et al.  Quantifying the Benefits of Individual-Level Targeting in the Presence of Firm Strategic Behavior , 2009 .

[10]  Peter E. Rossi,et al.  The Value of Purchase History Data in Target Marketing , 1996 .

[11]  Rohini Ahluwalia How Prevalent Is the Negativity Effect in Consumer Environments , 2002 .

[12]  Sunil Gupta,et al.  The Shopping Basket: A Model for Multicategory Purchase Incidence Decisions , 1999 .

[13]  D. Thompson,et al.  A case-control study of the effectiveness of bicycle safety helmets. , 1989, The New England journal of medicine.

[14]  Jack E. Thomas Current drug information: European medicines agency confirms positive benefit-risk balance of pholcodine-containing cough medicines , 2012 .

[15]  M. Dekimpe,et al.  The Impact of a Product-Harm Crisis on Marketing Effectiveness , 2007 .

[16]  A. Bandura Self-efficacy mechanism in human agency. , 1982 .

[17]  Marilyn E. Gist,et al.  Self-Efficacy: A Theoretical Analysis of Its Determinants and Malleability , 1992 .

[18]  B. Psaty,et al.  Rosiglitazone and cardiovascular risk. , 2007, The New England journal of medicine.

[19]  M. Dekimpe,et al.  Weathering product-harm crises , 2008 .

[20]  Chakravarthi Narasimhan,et al.  Treatment Effectiveness and Side Effects: A Model of Physician Learning , 2013 .

[21]  Baohong Sun,et al.  Learning and Acting on Customer Information: A Simulation-Based Demonstration on Service Allocations with Offshore Centers , 2011 .

[22]  W. Wong,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[23]  Andrew T. Ching,et al.  Consumer Learning and Heterogeneity: Dynamics of Demand for Prescription Drugs after Patent Expiration , 2001 .

[24]  Sridhar Narayanan,et al.  Heterogeneous Learning and the Targeting of Marketing Communication for New Products , 2009, Mark. Sci..

[25]  S. Nissen,et al.  Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. , 2007, The New England journal of medicine.

[26]  Pradeep K. Chintagunta,et al.  Temporal Differences in the Role of Marketing Communication in New Product Categories , 2005 .

[27]  S. Chib,et al.  Understanding the Metropolis-Hastings Algorithm , 1995 .

[28]  R. E. Burnkrant,et al.  Consumer Response to Negative Publicity: The Moderating Role of Commitment , 2000 .