The Effect of Trust-based Management Strategy on Performance of Human-Machine Collaborative Team: A Dynamic Computational Model

Abstract

In human-machine collaborative teams, trust has an important effect on team performance. However, precisely how trust and trust-based management strategy influence team performance have remained elusive. This paper develops a method of trust-based team management to understand which managerial strategy has what impact on performance, and to discern decision alternatives. The method concentrates on providing a dynamic model of trust considering trust relationship initialization, updating trust based on experience and determining what trust should have an effect on. The model is used to explain how the trust-based management strategy caused the team to evolve in particular directions rather than others. Some prescriptions are put forward for the proper management of team. We argue that a human-machine collaborative team is a multi-agent system and team members are autonomous agents. Three computational experiments are conducted under different internal and external conditions for the artificial team, yielding the following results. (1) Under different difficulty of tasks, trust may produce either positive or negative effect on performance. (2) Trust-based management strategy dose has effect on performance under difficult task. (3) The results demonstrate the different effect of three trust-based management strategies on performance. The study method and findings presented herein are appropriate for other studies focusing on dynamic effects on team, laying the foundations for new ideas for studying team building and team development.