Consumer preferences and bid-price control for cloud services

Nowadays, instead of investing into large and expensive IT infrastructures, it is possible to buy computing environments or (complex) electronic services on-demand in order to perform certain business activities. This approach is typically known as Cloud Computing. For consumers, Cloud Computing embraces a service-oriented architecture (SOA) and implies potential for reduced total cost of ownership, great flexibility as well as reduced information technology overhead (Vouk, 2008). Consequently, one of the most relevant advantages is the increased technical and financial flexibility for Cloud Computing consumers. Consumers have various requirements regarding Cloud services depending on their industry and business, and hence are different with regard to their preferences and valuations. Providers of Cloud services can be limited in their resource capacities or flexibility, and they are exposed to the challenge of how to sell their services efficiently. To address distinctive consumer preferences, service providers can offer numerous classes of services according to service level agreements (SLA). These classes of services are priced differently. Furthermore, providers allocating their capacity to various types of consumers have incentives to maximize output, which is the revenue yielded by the sale of capacity units. Revenue Management deals with complex decision problems concerning sales, demand, and pricing of services from a provider’s perspective (Talluri and van Ryzin, 2004b). Recently, the consumer’s perspective also becomes increasingly important to enable an integrated view of the complex interaction between the provider and the consumer. In this thesis both views are examined. At first, the applicability of Revenue Management methods in Cloud Computing is discussed. The properties of Cloud services are analyzed and compared to the requirements of Revenue Management. Current literature does not consider Revenue Management in Clouds and how this may impact the design of services. Secondly, Revenue Management concepts like accept/reject policies, dynamic pricing or advance reservation are not always accepted by the consumers. Consumers in some domains are not used to dynamic prices and occasionally deny it. In 2000, Amazon for example failed to introduce dynamic pricing for the online store due to customer complaints about the frequent price changes (Weiss and Mehrotra, 2001). A survey as a part of this thesis was conducted to un-