Unlocking the Synergy: Increasing productivity through Human-AI collaboration in the industry 5.0 Era

IF 6.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2025-02-01 Epub Date: 2024-10-16 DOI:10.1016/j.cie.2024.110657
Xue Sun , Yu Song
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Abstract

The prevailing trajectory of technological evolution emphasizes the sustainable development of human-AI collaboration. In this study, we employ the coupling coordination degree model to evaluate the dynamics of human-AI collaboration in China and match it with listed companies. Through panel models, the study not only quantifies the contribution of such collaboration to enhancing company input–output efficiency but also explores how it serves as a catalyst for technological catch-up. Our findings indicate that the integration of human capital with AI emerges as a potent driver of company efficiency, with the extent of the impact also tied to organizational characteristics. Furthermore, the scale of investment and organizational size play a crucial role in the effectiveness of HIC, underscoring the adaptability of human-AI collaboration strategies to various organizational contexts and the importance of tailored implementation. Our research highlights the inherent collaborative potential of AI within the Industry 5.0 framework, advocating for the fusion of human creativity with AI precision to foster a development paradigm that is resource-efficient, cost-effective, and human-centric.
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释放协同效应:在工业 5.0 时代通过人机协作提高生产力
技术演进的主流轨迹强调人类与人工智能协作的可持续发展。在本研究中,我们采用耦合协调度模型来评估中国人与人工智能协作的动态,并将其与上市公司进行匹配。通过面板模型,本研究不仅量化了这种合作对提高企业投入产出效率的贡献,而且探讨了它如何成为技术追赶的催化剂。我们的研究结果表明,人力资本与人工智能的整合成为公司效率的有力驱动力,其影响程度也与组织特征有关。此外,投资规模和组织规模在HIC的有效性中起着至关重要的作用,强调了人类-人工智能协作战略对各种组织环境的适应性以及量身定制实施的重要性。我们的研究强调了工业5.0框架下人工智能固有的协作潜力,倡导将人类创造力与人工智能精度融合在一起,以培育一种资源高效、成本效益高、以人为本的发展模式。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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