This article examines strategic behavior of e-Service suppliers that offer electronic services in complex Service Value Networks (SVNs). In SVNs, consumers request a bundle of e-Services, and the SVN acts as an aggregator of single service instances, automatically configuring services from different e-Service suppliers into a complex service bundle, which is then offered to the consumers. In this context, e-Service suppliers who want to maximize their business success need to configure their services according to the (for them unknown) preferences of the consumers. Current literature, however, does not offer much guidance on how to find a fitting service offer in this situation, especially when the suppliers are faced with a changing consumer base. For this reason, we study two specific learning regimes that are able to capture and deal with the inherent complexity of the corresponding strategy space. Besides finding beneficial service offers, e-Service suppliers might also learn collusive behavior if it aligns with individual incentives. The potential occurrence of such behavior is the second aim of our work. Our results show that even with relatively simple learning regimes, e-Service suppliers are able to find beneficial offers and learn to collude tacitly (and presumably legally), which increases their profits.
- multiagent systems
- service value networks
- strategic learning
ASJC Scopus subject areas
- Information Systems
- Sociology and Political Science
- Organizational Behavior and Human Resource Management