Disentangling Innovation Practices in Automation-Adopting Organizations: a Co-Performance Perspective

2026-08-17

AI Summary

This study addresses the ambiguity surrounding human-machine collaboration mechanisms in organizational automation adoption. Adopting a co-performance perspective, we examined airport automation practices through qualitative interviews and theoretical analysis. The research identifies critical tensions, including "automation-first" prioritization and "human-centric lag," and synthesizes five design principles to reconstruct the conceptual framework of automation. This revised framework emphasizes integrating employees as co-designers throughout the entire innovation lifecycle. By providing practical guidance on early human factors integration and iterative design for human-computer interaction research, this work effectively bridges the theoretical gap regarding collaborative limitations inherent in existing automation implementation processes.

Abstract

As organizations increasingly adopt automation, innovation practitioners are responsible for selecting, adapting, testing, and implementing externally sourced innovations. However, little is known about how these upstream practices shape worker-automation arrangements, limiting our ability to intervene in innovation practice to address automation adoption challenges. To disentangle this relationship, we interviewed nine innovation practitioners at a major European airport pursuing long-term autonomous operations and analyzed their practices through a co-performance lens. We synthesize five co-performance design principles and examine where current practices align or conflict. Our findings reveal tensions: innovation practitioners prioritize full-automation arrangements while postponing human considerations; contextual constraints shape solutions, but openness to reconfiguration remains limited; and co-learning rarely extends beyond pilot phases. These insights provide HCI research and practice with guidance for reframing the conceptualization of automation, particularly by encouraging earlier consideration of human roles, promoting iterative visions, and recognizing workers as co-designers throughout innovation pipelines.

Problem

• Automation Adoption
• Innovation Practices
• Worker-Automation Arrangements
• Co-Performance
• Human-AI Interaction

Innovation

• Co-Performance
• Automation Adoption
• Innovation Practices
• Human-Automation Arrangements
• Co-design