Incentive Management

Abstract

Most existing Social Computing approaches model humans as computing elements fitting into existing computational models, as opposed to modeling (computational) processes to fit human elements. We argue that an effective inclusion of humans in socio-technical systems can only succeed if a combination of hard and soft controllability approaches is used. In practice this means redesigning the way we manage the human element in executable processes by relaxing strict constraints to fit the inherent unreliability of humans and embracing the uncertainty that comes with it. The creativity, versatility and sociability of humans should be leveraged to perform runtime adaptations, fix incorrect results and even produce unexpected ones. This is achieved through soft controllability approaches such as incentives, social influence and self-achievement. In this chapter we introduce the field of automated incentive management and present our research in the area. We build upon the theoretical basis to design and present a complete methodology and a software framework prototype for automated incentive management in socio-technical systems applicable to Smart City environments.