在采用自动化的组织中拆解创新实践：一种协同绩效视角
Disentangling Innovation Practices in Automation-Adopting Organizations: a Co-Performance Perspective
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中文总结 AI 辅助
本研究以欧洲某大型机场9名创新从业者为对象，通过协同绩效视角拆解自动化采用组织中创新实践与工人-自动化安排的关系，提出5项设计原则，揭示相关张力，为HCI领域提供自动化概念重构的指导。
中文摘要 AI 辅助
随着组织日益采用自动化，创新从业者负责选择、调整、测试和实施外部来源的创新。然而，人们对这些上游实践如何塑造工人与自动化的安排知之甚少，这限制了我们干预创新实践以解决自动化采用挑战的能力。为拆解这种关系，我们采访了一家致力于长期自主运营的欧洲大型机场的9名创新从业者，并通过协同绩效视角分析他们的实践。我们综合出5项协同绩效设计原则，考察当前实践与这些原则的契合或冲突之处。研究结果揭示了张力：创新从业者优先考虑全自动化安排，却推迟考虑人的因素；情境约束塑造了解决方案，但对重新配置的开放性仍然有限；协同学习很少延伸到试点阶段之外。这些发现为人机交互（HCI）研究与实践提供了指导，以重新构建对自动化的概念化，特别是鼓励更早考虑人的角色、推动迭代愿景，并将工人视为整个创新流程的共同设计者。
英文摘要
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.
