Matching supply and demand in a sharing economy: Classification, computational complexity, and application

The sharing economy, i.e., the cooperative consumption of goods and services offered by private households or companies via online market places, gains more and more attention. Most sharing platforms coordinate transactions by generating each consumer an individual list of suited and available resources to choose from. If plenty online requests arrive rather simultaneously and compete for the scarce shared resources, however, an optimization-based coordination of supply and demand promises much better matches (e.g., more satisfied requests). This paper focuses deterministic matching problems and provides a classification scheme for the resulting optimization problems occurring in different areas of the sharing economy. These matching problems vary, for instance, if immobile (e.g., parking space) or mobile resources (e.g., vehicles of a car sharing provider) are shared. With the help of this classification, we give a detailed overview on known and novel complexity results. Furthermore, we apply the example of sharing parking space and explore the potential contribution of deterministic matchings when applied in a dynamic, uncertain, and opportunistic environment.