Efficient Contracting in Cloud Service Markets with Asymmetric Information - A Screening Approach

Increasing popularity of cloud-based services has led to the emergence of cloud marketplaces where services from different providers are offered, usually in the form of a catalog. The customers´ decision about buying offered services is based on idiosyncratic preferences regarding non-functional service attributes, e.g., price, provider reputation, and quality of service. The customers´ preferences are not necessarily known to providers at the time the service (including pricing) is defined in the marketplace´s service catalog. Thus, from a microeconomic perspective, we have to deal with information asymmetry on incomplete markets. On such markets, finding the optimal contracts (i.e., non-functional characteristics and prices) that maximize the provider´s profit is challenging due to information uncertainty. This paper presents a generic economic framework based on contract theory which solves the above-mentioned optimization for cloud-based services offered at a marketplace. The contribution is threefold: (i) we analyze and select from providers´ perspective non-functional attributes considered by customers when deciding which services to buy, (ii) we implement a holistic contracting framework that grants providers maximal profit through optimal combination of potential values of the chosen attributes and (iii) we present a study of a desktop service use case. The contracting framework addresses the phenomenon of adverse selection by leveraging the screening technique.