Computing as Utility: Managing Availability, Commitment, and Pricing Through Contingent Bid Auctions
Journal of Management Information Systems
Economic aspects of a utility computing service
Proceedings of the first international conference on Networks for grid applications
An Analysis of Usage-Based Pricing Policies for Smart Products
Electronic Markets
Electronic Commerce Research and Applications
Risk Management of Contract Portfolios in IT Services: The Profit-at-Risk Approach
Journal of Management Information Systems
Utility computing-based framework for e-governance
Proceedings of the 2nd international conference on Theory and practice of electronic governance
Risk aversion and information asymmetry in the pricing of capacity-on-demand and pay-per-use computing products
Buyer Uncertainty and Two-Part Pricing: Theory and Applications
Management Science
Autonomic metered pricing for a utility computing service
Future Generation Computer Systems
IT project portfolio optimization: a risk management approach to software development governance
IBM Journal of Research and Development
Towards assessing performance in service computing
ICSOC'10 Proceedings of the 2010 international conference on Service-oriented computing
An Interdisciplinary Perspective on IT Services Management and Service Science
Journal of Management Information Systems
Profit-maximizing firm investments in customer information security
Decision Support Systems
Pricing and Resource Allocation in a Cloud Computing Market
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Selection of optimal countermeasure portfolio in IT security planning
Decision Support Systems
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Whereas most companies use the century-old cost-plus pricing, this pricing method is especially inadequate for services on demand because these services have uncertain demand, high development costs, and a short life cycle. In this paper we propose a novel methodology, Price-at-Risk, that explicitly takes into account uncertainty in the pricing decision. By explicitly modeling contingent factors, such as uncertain rate of adoption or demand elasticity, the methodology can account for risk before the pricing decision is taken. The methodology optimizes the expected "net present value," subject to financial performance constraints, and thus improves on both the cost-based and value-based approaches found in the marketing literature.