An encompassing view on markdown pricing strategies: an analysis of the Austrian mobile phone market

Fierce competition and rapid technological progress have considerably reduced the life cycle length for mobile phones in the last decade. Once a new mobile phone is launched, providers on the market under consideration practice a markdown strategy. Profits of the providers are generated mainly via the monthly (base plus variable) fees accruing during contract duration whereas the mobile phones are over large parts of their life cycle sold below the constant purchase price charged by the OEM supplier. The problem of applying such markdown strategies has recently been further emphasized by an increased competition among the providers cutting back revenues generated by the contracts. Although providers frequently complain about this situation of pre- and cross financing the mobile phones, none of them has yet risked stopping the practiced markdown pricing strategies. In our contribution, we investigate a new model for the analysis of the effects of alternative (markdown) pricing strategies. Building on previous research that has investigated the dynamics and feedbacks between pricing and inventory decisions caused by delays and inaccurate forecasts, we develop a more encompassing view on the market considering the dependency and dynamics between customer satisfaction, loyalty, and repeat purchase rates. Furthermore, we explicitly model price and reference price effects and their impact on the attraction of new customers. Various data sources are employed to calibrate a system dynamics model for one of the providers and its interrelation with a typical supplier and the customers. Our model indicates that a reduction of the currently practiced markdown strategy would reduce the provider’s overall profit for contract customers. In contrast, the results for prepaid customers could be improved by a careful reduction of markdowns.

[1]  Georgios I. Doukidis,et al.  Virtual store layout: an experimental comparison in the context of grocery retail , 2004 .

[2]  Joseph M. Kamen,et al.  Psychophysics of Prices , 1970 .

[3]  N. Repenning,et al.  Unanticipated side effects of successful quality programs: exploring a paradox of organizational improvement , 1997 .

[4]  John J. Neale,et al.  The Role of Inventory in Superior Supply Chain Performance , 2004 .

[5]  E. Anderson,et al.  The Antecedents and Consequences of Customer Satisfaction for Firms , 1993 .

[6]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[7]  John D. Sterman,et al.  Business dynamics : systems thinking and modelling for acomplex world , 2002 .

[8]  J. D. Hess,et al.  Emerging trends in retail pricing practice: implications for research , 2007 .

[9]  John D. Sterman,et al.  System Dynamics: Systems Thinking and Modeling for a Complex World , 2002 .

[10]  Bhaba R. Sarker,et al.  A Review of:“Factory Physics: Foundations of Manufacturing Management” Wallace J. Hopp and Mark L. Spearman Richard D. Irwin, Inc., 1996 , 1997 .

[11]  Russell S. Winer,et al.  A reference price model of brand choice for frequently purchased products. , 1986 .

[12]  Murali K. Mantrala,et al.  A Decision-Support System that Helps Retailers Decide Order Quantities and Markdowns for Fashion Goods , 2001 .

[13]  Vijay Mahajan,et al.  Chapter 8 New-product diffusion models , 1993, Marketing.

[14]  A. W. Coats,et al.  The Principles of Political Economy and Taxation. , 1935 .

[15]  Robert C. Blattberg,et al.  Sales Promotion: Concepts, Methods, and Strategies , 1990 .

[16]  Wallace J. Hopp,et al.  Factory physics : foundations of manufacturing management , 1996 .

[17]  P. K. Kannan,et al.  Dynamic Pricing on the Internet: Importance and Implications for Consumer Behavior , 2001, Int. J. Electron. Commer..

[18]  Jens J. Dahlgaard,et al.  On measurement of customer satisfaction , 1992 .

[19]  Joseph M. Kamen,et al.  “Psychophysics of Prices”: A Reaffirmation , 1971 .

[20]  John J. Neale,et al.  The practice of supply chain management : where theory and application converge , 2004 .

[21]  Richard A. Briesch,et al.  A High-Tech Product Market Share Model with Customer Expectations , 1995 .

[22]  Pinar Keskinocak,et al.  Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions , 2003, IEEE Engineering Management Review.

[23]  F. Bass A new product growth model for consumer durables , 1976 .

[24]  Valerie Belton,et al.  Adding value to performance measurement by using system dynamics and multicriteria analysis , 2002 .

[25]  D. Sterman,et al.  Misperceptions of Feedback in a Dynamic Decision Making Experiment , 1989 .