Stochastic programming bilevel models for service provision with a balancing coordinator

This paper introduces a framework for the quantitative analysis of collaborative service platforms. Services built around platforms require the coordinated collaboration of several independent agents, each from a different field or area of expertise and each providing one or more components to the overall service. One of these agents takes the further role of platform coordinator, whose role consists in assembling the services from components provided by other agents and sharing the revenue between the participants. The agents decide which services to make a contribution to by selecting service portfolios that maximize their expected profit under constraints on risk and capacity. The coordinator selects the revenue-sharing scheme that balances the offers from other agents and ensures the functioning of the platform. We develop two stochastic optimization models with bilevel structure for the analysis of the collaborative service platform provision, analyse the properties of the solutions and provide numerical experiments that show the qualitative difference of the profit//risk trade-off in the multiagent case compared with the classical single agent case.