Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Modeling competitive bidding: a critical essay
Management Science
Information rules: a strategic guide to the network economy
Information rules: a strategic guide to the network economy
Computing Partitions with Applications to the Knapsack Problem
Journal of the ACM (JACM)
Virtual worlds: fast and strategyproof auctions for dynamic resource allocation
Proceedings of the 4th ACM conference on Electronic commerce
Combinatorial Auctions: A Survey
INFORMS Journal on Computing
Managing Online Auctions: Current Business and Research Issues
Management Science
Pricing and Allocation for Quality-Differentiated Online Services
Management Science
Computing as Utility: Managing Availability, Commitment, and Pricing Through Contingent Bid Auctions
Journal of Management Information Systems
Journal of Management Information Systems
Market Segmentation Within Consolidated E-Markets: A Generalized Combinatorial Auction Approach
Journal of Management Information Systems
A Market Design for Grid Computing
INFORMS Journal on Computing
Net Neutrality and Vertical Integration of Content and Broadband Services
Journal of Management Information Systems
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We develop three auction-based pricing and allocation solution methods for the case where a capacity-constrained online service provider offers multiple classes of unique, one-time services with differentiated quality. Consumers desire exactly one of the many service classes offered. We call such a setting a vertically integrated online services market. Examples of these services are webcasting of special events over the Internet, provision of video-on-demand, and allocation of grid computing resources. We model the pricing and allocation decision faced by firms in such a setting as a knapsack problem with an added preference elicitation dimension. We present a variety of computational solution approaches based on adaptations of the traditional greedy heuristic for knapsack problems. The solution approaches vary in efficacy depending on whether bidders are restricted to bid in one service class or allowed to bid in multiple service classes, as well as on the overall variability of the demand. In the case bidders can bid in multiple classes but are interested in consuming only one service class, a direct application of the heuristics developed for the single service case results in a nonfair allocation. We develop a novel data structure to eliminate the unfair allocation while maintaining the original computation complexity of the simpler setting. The paper contributes by presenting a menu of auction clearing mechanisms for selling vertically integrated online services.