Robust New Product Pricing

We study the pricing decision for a monopolist launching a new innovation. At the time of launch, we assume that the monopolist has incomplete information about the true demand curve. Despite the lack of objective information the firm must set a retail price to maximize total profits. To model this environment, we develop a novel two-period non-Bayesian framework, where the monopolist sets the price in each period based only on a non-parametric set of all feasible demand curves. Optimal prices are dynamic as prices in any period allow the firm to learn about demand and improve future pricing decisions. Our main results show that the direction of dynamic introductory prices (versus static) depends on the type of heterogeneity in the market. We find (1) when consumers have homogeneous preferences, introductory dynamic price is higher than the static price (2) when consumers have heterogeneous preferences and the monopolist has no ex-ante information, the introductory dynamic price is the same as the static price and (3) when consumers have heterogeneous preferences and the monopolist has ex-ante information, the introductory dynamic price is lower than the static price. Further, the degree of this initial reduction increases with the amount of ex-ante heterogeneity.

[1]  Geoff Vincent,et al.  —Managing— New-Product Development , 1989, Springer US.

[2]  Leonard J. Mirman,et al.  A Bayesian Approach to the Production of Information and Learning by Doing , 1977 .

[3]  W. Gartner,et al.  Factors affecting new product forecasting accuracy in new firms , 1993 .

[4]  G. Assmus New product forecasting , 1984 .

[5]  I. Janis,et al.  Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment , 1977 .

[6]  K. Arrow The Economic Implications of Learning by Doing , 1962 .

[7]  Oded Koenigsberg,et al.  The Design and Introduction of Product Lines When Consumer Valuations are Uncertain , 2014 .

[8]  Oded Koenigsberg,et al.  Research Note - The Role of Production Lead Time and Demand Uncertainty in Marketing Durable Goods , 2007, Manag. Sci..

[9]  D. Bergemann,et al.  Pricing Without Priors , 2007 .

[10]  Harikesh S. Nair Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games , 2007 .

[11]  Kenneth B. Kahn An exploratory investigation of new product forecasting practices , 2002 .

[12]  J. Berger Statistical Decision Theory and Bayesian Analysis , 1988 .

[13]  Bruce R. Robinson,et al.  Dynamic Price Models for New-Product Planning , 1975 .

[14]  Leonard J. Savage,et al.  The Theory of Statistical Decision , 1951 .

[15]  Leonard M. Lodish,et al.  Applied Dynamic Pricing and Production Models with Specific Application to Broadcast Spot Pricing , 1980 .

[16]  T. Lai Adaptive treatment allocation and the multi-armed bandit problem , 1987 .

[17]  Jörg Stoye,et al.  Axioms for minimax regret choice correspondences , 2011, J. Econ. Theory.

[18]  P. Green,et al.  Conjoint Analysis in Consumer Research: Issues and Outlook , 1978 .

[19]  Tyzoon T. Tyebjee,et al.  Behavioral biases in new product forecasting , 1987 .

[20]  Eli Cohen,et al.  Hotel Revenue-management Forecasting , 2004 .

[21]  David Lindley,et al.  Statistical Decision Functions , 1951, Nature.

[22]  Maurice Queyranne,et al.  Toward Robust Revenue Management: Competitive Analysis of Online Booking , 2009, Oper. Res..

[23]  James W. Roberts,et al.  Robust Firm Pricing with Panel Data , 2009 .

[24]  Americus Reed,et al.  Sticky Priors: The Perseverance of Identity Effects on Judgment , 2004 .

[25]  Sébastien Bubeck,et al.  Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , 2012, Found. Trends Mach. Learn..

[26]  Christos H. Papadimitriou,et al.  Games against nature , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).

[27]  M. Rothschild A two-armed bandit theory of market pricing , 1974 .

[28]  Birger Wernerfelt,et al.  A Special Case of Dynamic Pricing Policy , 1986 .

[29]  J. Michael Harrison,et al.  Bayesian Dynamic Pricing Policies: Learning and Earning Under a Binary Prior Distribution , 2011, Manag. Sci..

[30]  Lisa E. Bolton Stickier Priors: The Effects of Nonanalytic versus Analytic Thinking in New Product Forecasting , 2003 .

[31]  Omar Besbes,et al.  On the Minimax Complexity of Pricing in a Changing Environment , 2011, Oper. Res..

[32]  Charles F. Manski,et al.  Social Choice with Partial Knowledge of Treatment Response , 2020 .

[33]  Georgia Perakis,et al.  Robust Controls for Network Revenue Management , 2010, Manuf. Serv. Oper. Manag..

[34]  David J. Braden,et al.  Nonlinear Pricing to Produce Information , 1994 .

[35]  Günter J. Hitsch An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty , 2006 .

[36]  Dan Zhang,et al.  Dynamic Pricing Competition with Strategic Customers Under Vertical Product Differentiation , 2013, Manag. Sci..

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

[38]  John W. Mullins,et al.  New product decision making: How chance and size of loss influence what marketing managers see and do , 2002 .

[39]  Alessandro Bonatti,et al.  Menu Pricing and Learning , 2010 .

[40]  Dirk Bergemann,et al.  Robust Monopoly Pricing , 2008, J. Econ. Theory.

[41]  P. Goodwin,et al.  Judgmental forecasting: A review of progress over the last 25 years , 2006 .

[42]  Takashi Hayashi,et al.  Context dependence and consistency in dynamic choice under uncertainty: the case of anticipated regret , 2011 .

[43]  Omar Besbes,et al.  Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms , 2009, Oper. Res..

[44]  Ikujiro Nonaka,et al.  Managing the new product development process , 1985 .

[45]  Harikesh S. Nair,et al.  Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games , 2006 .

[46]  Frank Thomson Leighton,et al.  The value of knowing a demand curve: bounds on regret for online posted-price auctions , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..