Leveraging behavioural economics in smart nudge design through data-driven prospect-theoretic modelling and context-aware intelligent reasoning: application to smart tip nudging.

Behavioural economics and nudge theory have attracted much attention for engineering design in a broader context of sociotechnical systems, which provides new perspectives for engineering design when systems have interactions with human. This paper deals with service system design with a particular application to smart tip nudging. The conventional tip nudging approach that uses a set of default tip options lacks context-awareness and sometimes suggests inappropriate tip options. To address this problem, and to also increase tip revenues potentially, this paper proposes a smart tip nudging mechanism based on prospect theoretic modelling of customer tipping behaviours. The model proposes to use joint prospect values of both customers and service providers, which mimics the trade-off that customers make between their own economic gains and losses and the service provided by service providers. Meanwhile, this study provides a data-driven approach to parameter estimation of the prospect theory model, and it enables tip nudging to be context-aware for tip option adjustment by using intelligent reasoning techniques. One field experiment is conducted to validate the proposed system. [ABSTRACT FROM AUTHOR]