Using Online Auctions for Optimal Product Configuration

Product design involves choosing from a vast array of components and subcomponents. By developing modular platforms and communicating with multiple suppliers each product becomes a bundle of attributes. The multitude of potential product configurations poses a challenge in identifying optimal configurations to offer customers. For most companies, the greatest challenge is measuring consumers’ marginal value for enhanced attributes. If this data were available, companies would offer those configurations with the highest margin. To date, consumers’ value for product attributes has been estimated using decision analysis techniques, surveys or conjoint analysis. This research proposes a different methodology for measuring consumers’ value. The emergence of active auction markets for a wide variety of products and services provides a venue for calibrating customer preferences. By offering different bundles of attributes a company can measure the marginal increase in auction price obtained from enhanced attributes. Coupled with cost data, this information facilitates the identification of efficient configurations. This provides a recommended assortment of products, within a product line. Data Envelopment Analysis is used in this context to define the efficient frontier. The methodology is assessed on auction data for used laptop computers. Analysis of auction results indicates that auction participants do value better attributes, and the incremental value of enhancements varies across attributes. Estimating cost differences from online posted-prices provides a foundation for estimating the efficient frontier of optimal bundles of attribute levels; in a cost-value space. As online auction markets expand and evolve, this methodology could be implemented for in developing product assortment, for many products and services. Examples include many consumer electronics, travel packages and communication services.