Optimizing User's Utility from Cloud Computing Services in a Networked Environment

Cloud Computing customers are looking for the best utility for their money. Research shows that functional aspects are considered more important than service prices in customer buying decisions. Choosing the best service provider might be complicated since each provider may sell three kinds of services organized in three layers: SaaS (Software as a service), PaaS (Platform as a service) and IaaS (Infrastructure as a service). This research targets the problem of optimizing consumers' utility, using conjoint analysis methodology. Providers currently offer software services as bundles belonging to the same layer, or to underlying layers. Bundling services prevent customers from splitting their service purchases between a provider of software and a different provider of the underlying layers. This research assumes that in the future will exist a free competitive market, in which consumers will be free to switch their services to different providers, eliminating the negative biases of bundling, during making their buying decisions. This research proposes a mathematical model and three possible strategies for implementation in organizations, and illustrates its advantages compared to existing utility maximization practices. Current conjoint analysis method chooses the best utility in a traditional cloud architecture in which one provider offers a bundle of all three layers. The proposed model assumes a networked cloud architecture in which a customer may choose services from any provider, building for himself the best basket of services maximizing his/her total utility. This research outlines three business models which will assist organizations shift gradually from current CC architecture to the future networked architectures, thus maximizing their utility. Keywords—Utility Optimization; Cloud Computing; Consumer preferences; Conjoint Analysis