Beyond the Human Touch: Exploring the Dynamics of Employees’ Trust in Human and Robotic Managers

Abstract

As artificial intelligence reshapes managerial roles, understanding how employees evaluate human and robotic managers has become increasingly important in hospitality. Through a scenario-based experiment, this study investigates how managerial skill level (high vs. low) interacts with manager type (human, human-like robot, machine-like robot) to shape employees’ perceived, affective, and cognitive trust. Drawing on trust theory and anthropomorphism theory, the findings reveal a competence-contingent embodiment effect: differences between human and robotic managers are magnified when high skill is displayed and minimized when skill is low. While human managers activate holistic trust that encompasses both affective and cognitive dimensions, human-like managers evoke moderated trust and machine-like managers elicit narrowly bounded competence-based trust. These results clarify the threshold conditions under which artificial agents can generate credibility as leaders, showing that the effectiveness of robotic management depends on the joint influence of demonstrated competence and perceived social legitimacy.