The ethics of automation: How the degree of robot adoption shapes unethical consumer behavior

Abstract

Recent developments in AI and service robotics are significantly reshaping frontline services, offering operational efficiencies and enhanced customer experiences. However, the increasing degree of robot adoption (DRA) introduces new challenges, including unethical consumer behavior (UCB). This research investigates how UCB varies across different DRA—low (services fully provided by humans), medium (services co-delivered by humans and robots), and high (services entirely provided by robots)—and identifies the underlying mechanisms driving these behaviors. Across three studies, we demonstrate that UCB follows an inverted U-shaped pattern as DRA increases, with medium DRA fostering the highest likelihood of UCB. This effect is mediated by perceived social pressure and perceived electronic monitoring. Low DRA elicits high social pressure, high DRA evokes strong electronic monitoring, while medium DRA minimizes both, creating conditions conducive to UCB. Additionally, we integrate entitativity theory to answer a competing hypothesis that medium DRA combines the suppressive effects of social pressure and monitoring. Instead, we show that low perceived entitativity under medium DRA fragments group cohesion, diminishing suppressive mechanisms, and leading to increased UCB. Finally, we demonstrate that social rewards-punishments mitigate the inverted U-shaped relationship, fostering ethical behavior regardless of DRA. This study enhances the comprehension of UCB within the context of robotic services by presenting DRA as a new antecedent, identifying key mediating mechanisms, and applying entitativity theory to hybrid human-robot service teams. Our findings offer actionable insights for managing robotic services, cautioning against hybrid models unless supplemented with effective behavioral controls.