Coordinating Marketing and Production with Asymmetric Costs: Theory and Estimation
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RESEARCH ARTICLE
Coordinating Marketing and Production with Asymmetric Costs: Theory and Estimation Sharan Jagpal 1 & Feihong Xia 2 Published online: 24 May 2019 # Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract This paper proposes a theoretical framework for decision making when the firm needs to make marketing and production/order decisions simultaneously before demand uncertainty is resolved. We discuss the theoretical properties of the framework for single and multi-product firms; in addition, we show that the framework can be extended to allow for competitive reaction in a duopoly setting. We propose an empirical method to operationalize the model and compare the results to those from extant methods. The empirical results for both single and multi-product firms show that the proposed method outperforms decision making using standard econometric methods. In particular, depending on customer lifetime value (CLV) and other error costs and price elasticities, the loss in potential profits by using the standard regression-based methodology or quantile regression can be considerable. Keywords Asymmetric costs . Profit maximization . Marketing-production interface . Demand uncertainty
1 Introduction Firms often need to make marketing and production/order decisions simultaneously before demand uncertainty is resolved. This paper has two goals. First, we examine the conditions under which decision making using standard econometric methods are optimal. Second, we propose a theoretical and empirical framework which is more appropriate given the firm’s goal to maximize economic rather than accounting profit (these terms are defined later). Firms often use sales response models to choose marketing policies. Policy decisions based on sales response models typically use a regression-based methodology. First, estimate the parameters of a sales response function using a standard loss function (e.g., least squares or some variant thereof such as generalized least squares). Second, substitute these estimated
* Feihong Xia [email protected] Sharan Jagpal [email protected] 1
Rutgers Business School, 1 Washington Park, Newark, NJ 07102, USA
2
College of Business Administration, University of Rhode Island, 233 Ballentine Hall, Kingston 02881, RI, USA
parameters into a profit function and choose marketing policy based on the estimated profit function. This procedure is intuitive. However, as this paper shows, for certain scenarios, choosing marketing and production policies based on this approach can result in poor decisions which reduce profitability. Practitioners are keenly aware of this. For example, Nielsen provides a realtime database for retailers to find the surpluses and shortages of thousands of products with universal product codes (UPC) within a certain geographical radius of their location.1 The moot question is as follows: Under what conditions are standard methods for analyzing aggregate data appropriate when marketing and production decisions are made simultaneously? We show
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