Zhou Zhi-Chao, Su Yi-Kun, Zheng Zhi-Zhe, Wang Yi-Lin
College of Civil Engineering and Transportation, Northeast Forestry University, Harbin , 150040, Heilongjiang, China.
Sci Rep. 2023 Nov 7;13(1):19339. doi: 10.1038/s41598-023-46241-6.
This study aims to investigate the factors that influence the willingness of highway construction enterprises in China to adopt intelligent construction technology. Based on the existing literature, a TOSE framework was proposed, and four dimensions and 15 hypothesized influencing factors were identified through expert interviews. By using a combination of PLS-SEM and ANN, 513 survey data were analyzed to determine the linear and non-linear relationships of the influencing factors on the willingness to adopt. The results showed that all 14 hypothesized factors had varying degrees of positive or negative effects on the willingness to adopt, except for organizational culture, which was found to have no significant impact. Specifically, technology cost was found to be the most influential negative factor, while market demand and organizational structure were the most influential positive factors. The findings of this study have important reference value for decision makers and participants in highway construction enterprises, as well as other construction companies when considering the adoption of smart construction technologies. The originality of this research lies in the novel application of the TOSE framework to investigate smart construction technology adoption, and the combined use of PLS-SEM and ANN to examine both linear and nonlinear relationships between variables for the first time.
本研究旨在探讨影响中国公路建设企业采用智能施工技术意愿的因素。基于现有文献，提出了一个TOSE框架，并通过专家访谈确定了四个维度和15个假设影响因素。通过结合使用PLS-SEM和ANN，对513份调查数据进行分析，以确定影响因素与采用意愿之间的线性和非线性关系。结果表明，除组织文化被发现没有显著影响外，所有14个假设因素对采用意愿都有不同程度的正向或负向影响。具体而言，技术成本被发现是最具影响力的负向因素，而市场需求和组织结构是最具影响力的正向因素。本研究的结果对公路建设企业的决策者和参与者以及其他建筑公司在考虑采用智能施工技术时具有重要的参考价值。本研究的创新性在于首次将TOSE框架创新性地应用于智能施工技术采用的研究，并结合使用PLS-SEM和ANN来检验变量之间的线性和非线性关系。
