Stochastic Option Bundling and Bundle Pricing

In many production and services industries, bundling is the widespread practice of offering a number of products or services in a single package at an attractive price. In the automobile industry, a basic car model is offered along with options such as air conditioning, sun-roof, metallic exterior colors, and so forth, so-called free-choice or free-flow options. In general, the customer is able to purchase option packages which consist of a number of single options offered at a reduced bundle price. As far as most customer segments are concerned, equipment sales are the manufacturer’s main source of profit. Thus, it is vital to decide on the pricing and the initial selection of free-choice options to be offered by the manufacturer. Due to substantial product and process development lead times, this task has to be carried out at least several months before production actually starts. Currently, accurate forecasting of demand for particular car types or option combinations is extremely difficult. The car manufacturer can hedge his risk of not matching the individual preferences of the customers for the car bundles offered, by providing a wide selection of free-choice options. However, from a manufacturing perspective, this product strategy is rather questionable. Moreover, variant-dependent costs are primarily determined by the number and the design of option combinations a customer can purchase with his basic car. Economies of scope exist among complementary options, e.g., a front door can be equipped with a power mirror more easily if it also has a power window. However, these cost synergies can only be exploited if customers do select (by chance) certain option combinations.

[1]  Ralph Fuerderer Option and Component Bundling under Demand Risk , 1996 .

[2]  J. Dieudonne Foundations of Modern Analysis , 1969 .

[3]  George L. Nemhauser,et al.  Note--On "Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms" , 1979 .

[4]  J. B. Rosen The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints , 1960 .

[5]  Ward Hanson,et al.  Optimizing Multinomial Logit Profit Functions , 1996 .

[6]  G. Nemhauser,et al.  Exceptional Paper—Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms , 1977 .

[7]  M. S. Bazaraa,et al.  Nonlinear Programming , 1979 .

[8]  Paul E. Green,et al.  An Application of a Product Positioning Model to Pharmaceutical Products , 1992 .

[9]  Janet L. Yellen,et al.  Commodity Bundling and the Burden of Monopoly , 1976 .

[10]  Ward Hanson,et al.  Optimal bundle pricing , 1990 .

[11]  R. Kellogg,et al.  Pathways to solutions, fixed points, and equilibria , 1983 .

[12]  J. B. Rosen The gradient projection method for nonlinear programming: Part II , 1961 .

[13]  Eppen Gd,et al.  Bundling--new products, new markets, low risk. , 1991 .

[14]  G. Dobson,et al.  Heuristics for pricing and positioning a product-line using conjoint and cost data , 1993 .

[15]  R. Kohli,et al.  Heuristics for Product-Line Design Using Conjoint Analysis , 1990 .

[16]  Richard Schmalensee,et al.  Gaussian Demand and Commodity Bundling , 1984 .