数智化转型背景下建筑企业AI安全技术采纳的组态路径研究
Research on the Configurational Paths of AI Safety Technology Adoption in Construction Enterprises under the Background of Digital and Intelligent Transformation
摘要: 建筑业安全管理正经历由传统模式向人工智能(AI)驱动的数智化转型,但企业实践中普遍面临“高预期、低渗透”的采纳鸿沟。现有基于微观个体视角的理论难以解释复杂工程情境下的技术采纳逻辑。鉴于此,本研究引入“技术–组织–环境”(TOE)分析框架,重构了建筑施工企业AI安全技术采纳的影响因素模型。基于232份企业有效样本数据,运用模糊集定性比较分析(fsQCA)方法探究多维前因条件驱动技术采纳的复杂联动机制。研究表明:任何单一因素均无法构成高水平采纳的必要条件;驱动高水平采纳存在三条“殊途同归”的典型组态路径,即“技术系统驱动型”、“高管–易用双核驱动型”以及“低阻力–管理护航型”。研究揭示了多重约束下建筑企业的技术决策逻辑,为推动行业数智化转型及政府制定分类治理政策提供了坚实的理论依据与实践指导。
Abstract: Safety management in the construction industry is undergoing a digital and intelligent transformation from traditional models to artificial intelligence (AI)-driven approaches. However, enterprises commonly face an adoption chasm characterized by “high expectations and low penetration” in practice. Existing theories based on a micro-individual perspective struggle to explain the logic of technology adoption within complex engineering contexts. In view of this, this study introduces the “Technology-Organization-Environment” (TOE) framework to reconstruct the influencing factor model for AI safety technology adoption in construction enterprises. Based on valid sample data from 232 enterprises, the fuzzy-set qualitative comparative analysis (fsQCA) method is applied to explore the complex linkage mechanisms of multi-dimensional antecedent conditions driving technology adoption. The results indicate that: no single factor constitutes a necessary condition for high-level adoption; there are three typical configurational paths that drive high-level adoption, representing “different routes to the same destination”, namely the “technology-system driven” path, the “top management-ease of use dual-core driven” path, and the “low resistance-management safeguarded” path. This study reveals the technology decision-making logic of construction enterprises under multiple constraints, providing a solid theoretical foundation and practical guidance for promoting the industry’s digital and intelligent transformation and for the government to formulate classified governance policies.
文章引用:陶庆浩, 孙继德. 数智化转型背景下建筑企业AI安全技术采纳的组态路径研究[J]. 管理科学与工程, 2026, 15(3): 606-618. https://doi.org/10.12677/mse.2026.153059

参考文献

[1] 卢春房, 伍军, 王孟钧, 等. 高质量发展背景下中国建筑企业核心竞争力提升研究[J]. 中国工程科学, 2021, 23(4): 79-86.
[2] Abioye, S.O., Oyedele, L.O., Akanbi, L., Ajayi, A., Davila Delgado, J.M., Bilal, M., et al. (2021) Artificial Intelligence in the Construction Industry: A Review of Present Status, Opportunities and Future Challenges. Journal of Building Engineering, 44, Article 103299. [Google Scholar] [CrossRef
[3] Pan, Y. and Zhang, L. (2021) Roles of Artificial Intelligence in Construction Engineering and Management: A Critical Review and Future Trends. Automation in Construction, 122, Article 103517. [Google Scholar] [CrossRef
[4] Darko, A., Chan, A.P.C., Adabre, M.A., Edwards, D.J., Hosseini, M.R. and Ameyaw, E.E. (2020) Artificial Intelligence in the AEC Industry: Scientometric Analysis and Visualization of Research Activities. Automation in Construction, 112, Article 103081. [Google Scholar] [CrossRef
[5] 陈珂, 丁烈云. 我国智能建造关键领域技术发展的战略思考[J]. 中国工程科学, 2021, 23(4): 64-70.
[6] Nnaji, C. and Karakhan, A.A. (2020) Technologies for Safety and Health Management in Construction: Current Use, Implementation Benefits and Limitations, and Adoption Barriers. Journal of Building Engineering, 29, Article 101212. [Google Scholar] [CrossRef
[7] Chen, Y., Yin, Y., Browne, G.J., et al. (2019) Adoption of Building Information Modeling in Chinese Construction Industry: The Technology-Organization-Environment Framework. Engineering, Construction and Architectural Management, 26, 1878-1898. [Google Scholar] [CrossRef
[8] Tornatzky, L.G. and Fleischer, M. (1990) The Processes of Technological Innovation. Lexington Books.
[9] 杜运周, 贾良定. 组态视角与定性比较分析(QCA): 管理学研究的一项新道路[J]. 管理世界, 2017(6): 155-167.
[10] Davis, F.D. (1989) Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340. [Google Scholar] [CrossRef
[11] Ajzen, I. (1991) The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. [Google Scholar] [CrossRef
[12] Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003) User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27, 425-478. [Google Scholar] [CrossRef
[13] Zeithaml, V.A. (1988) Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52, 2-22. [Google Scholar] [CrossRef
[14] Yap, J.B.H., Lam, C.G.Y., Skitmore, M. and Talebian, N. (2022) Barriers to the Adoption of New Safety Technologies in Construction: A Developing Country Context. Journal of Civil Engineering and Management, 28, 120-133. [Google Scholar] [CrossRef
[15] Oesterreich, T.D. and Teuteberg, F. (2016) Understanding the Implications of Digitisation and Automation in the Context of Industry 4.0: A Triangulation Approach and Elements of a Research Agenda for the Construction Industry. Computers in Industry, 83, 121-139. [Google Scholar] [CrossRef
[16] Hambrick, D.C. and Mason, P.A. (1984) Upper Echelons: The Organization as a Reflection of Its Top Managers. The Academy of Management Review, 9, 193-206. [Google Scholar] [CrossRef
[17] Won, J., Lee, G., Dossick, C. and Messner, J. (2013) Where to Focus for Successful Adoption of Building Information Modeling within Organization. Journal of Construction Engineering and Management, 139, Article 04013014. [Google Scholar] [CrossRef
[18] Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18, 509-533. [Google Scholar] [CrossRef
[19] Barney, J. (1991) Firm Resources and Sustained Competitive Advantage. Journal of Management, 17, 99-120. [Google Scholar] [CrossRef
[20] Thong, J.Y.L. (1999) An Integrated Model of Information Systems Adoption in Small Businesses. Journal of Management Information Systems, 15, 187-214. [Google Scholar] [CrossRef
[21] DiMaggio, P.J. and Powell, W.W. (1983) The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields. American Sociological Review, 48, 147-160. [Google Scholar] [CrossRef
[22] Wang, Y.M., Wang, Y.S. and Yang, Y.F. (2010) Understanding the Determinants of RFID Adoption in the Manufacturing Industry. Technological Forecasting and Social Change, 77, 803-815. [Google Scholar] [CrossRef
[23] Zhu, K., Kraemer, K.L. and Xu, S. (2006) The Process of Innovation Assimilation by Firms in Different Countries: A Technology Diffusion Perspective on E-Business. Management Science, 52, 1557-1576. [Google Scholar] [CrossRef
[24] Cao, D., Wang, G., Li, H., Skitmore, M., Huang, T. and Zhang, W. (2015) Practices and Effectiveness of Building Information Modelling in Construction Projects in China. Automation in Construction, 49, 113-122. [Google Scholar] [CrossRef
[25] Xue, H., Zhang, S., Yin, Y., et al. (2022) Effects of Organizational Elements on Emerging Information and Construction Management Technology Implementation in Building Professionals. Journal of Management in Engineering, 38, Article 04021074.
[26] Ahuja, R., Sawhney, A., Jain, M., Arif, M. and Rakshit, S. (2018) Factors Influencing BIM Adoption in Emerging Markets—The Case of India. International Journal of Construction Management, 20, 65-76. [Google Scholar] [CrossRef
[27] Pan, M. and Pan, W. (2019) Determinants of Adoption of Robotics in Building Construction. Journal of Construction Engineering and Management, 145, Article 04019054.
[28] 蔡雯怡. 建筑施工企业智能建造技术采纳意愿影响因素研究[D]: [硕士学位论文]. 西安: 长安大学, 2021.
[29] Cheng, M., Chong, H.Y., Xu, Y., et al. (2024) Novel Blockchain Deep Learning Framework to Ensure Video Security and Lightweight Storage for Construction Safety Management. Advanced Engineering Informatics, 60, Article 102434.
[30] Zhang, J., Yin, J., Li, H., et al. (2022) A New Perspective to Evaluate the Antecedent Path of Adoption of Digital Technologies in Major Projects of Construction Industry: A Case Study in China. Engineering, Construction and Architectural Management, 29, 2636-2661.
[31] 吴芊凝. 人工智能在智慧工地中的应用研究[D]: [硕士学位论文]. 南京: 东南大学, 2022.
[32] Rihoux, B. and Ragin, C.C. (2009) Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques. Sage Publications.
[33] Ram, S. and Sheth, J.N. (1989) Consumer Resistance to Innovations: The Marketing Problem and Its Solutions. Journal of Consumer Marketing, 6, 5-14. [Google Scholar] [CrossRef
[34] Iacovou, C.L., Benbasat, I. and Dexter, A.S. (1995) Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology. MIS Quarterly, 19, 465-485. [Google Scholar] [CrossRef
[35] Ragin, C.C. (2008) Redesigning Social Inquiry: Fuzzy Sets and beyond. University of Chicago Press.
[36] Ragin, C.C. (2006) Set Relations in Social Research: Evaluating Their Consistency and Coverage. Political Analysis, 14, 291-310. [Google Scholar] [CrossRef
[37] Fiss, P.C. (2011) Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research. Academy of Management Journal, 54, 393-420. [Google Scholar] [CrossRef