The Effect of Tournament Horizon, Faultline and Group Performance Relationships under Decentralized System - Frida Fanani Rohma; Indah Shofiyah; Abdus Salam Junaedi (Faculty of Economics and Business, Universitas Gadjah Mada, 2023)
Introduction/Main Objectives: This research integrates the self-categorization and contagion theories to analyze faultlines due to a decentralization system. Besides, this research investigates the inducement of tournament incentives as a control mechanism to mitigate the harmful effects of a faultline on group performance. Background Problems: Fiscal decentralization has a crucial role as it stimulates economic growth, enhances the quality of decision-making and escalates performance. However, decentralization by one local government, which consists of various local government departments, may trigger a faultline. This research argues that patterned diversity convenes faultlines that split up a group into antagonistic sub-groups following the attributes affecting the aggregate group performance. Novelty: This research provides a new insight, in that decentralization appears to be a double-edged sword. It can elevate the quality of local decision-making, and trigger faultlines between local government departments at other times, affecting the local government’s aggregate performance. Research Methods: This research uses a laboratory experimental method with a 2×3 between-subjects factorial design. The research design uses the dyad analysis level. Finding/Results: The results found that the induction of a tournament scheme with the use of a cumulative ordinal scale for determining group performance encourages the social cognitive activation of individuals, thus encouraging cognitive orientation to optimize compensation and minimize categorization and antagonism. Conclusion: A tournament incentive scheme can be induced as a management control mechanism and to encourage the sub-groups to be winners. This resolution is expected to mitigate antagonistic behavior due to faultlines and enhance the optimization of aggregate performance