A system and learning perspective on human–robot collaboration

Abstract

Purpose

The process of introducing a new robotic technology into a service system is complex, and its impacts on work practices can be challenging. By adopting a system perspective, this study investigates how human–robot collaboration (HRC) transforms work practices (i.e. customer care).

Design/methodology/approach

We conducted a two-year longitudinal analysis of an international company specializing in natural health products, examining changes in customer care practices following the introduction of chatbots. The study leverages expansive learning theory, which emphasizes activity systems and the transformations that occur within them, to trace the integration of robots and their effects on work practices.

Findings

The findings reveal that HRC enhances customer care practices by creating a human–robot activity system organized around shared goals. This system, mediated by tools, rules and the community, evolves through expansive learning dynamics. The process begins by identifying and addressing the contradictions and tensions between current human work practices and robotic capabilities, often revealing challenges and opportunities to improve HRC.

Originality/value

This research offers a novel conceptualization of the systemic and dynamic nature of HRC by placing it within broader frames of activity systems and expansive learning. Collaborations between humans and robots entail an expansive performativity that extends beyond the traditional roles or tasks of either actor or actant. It spans a diverse range of objects, tools, procedures and institutional setups, culminating in transformations of customer care practices.