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Critical factors influencing the internet of things technology adoption behavior of construction companies: evidence from China

结构方程建模 独创性 知识管理 业务 技术接受模型 营销 实证研究 心理学 计算机科学 可用性 社会心理学 创造力 数学 统计 人机交互 机器学习
作者
Yaqi Zhao,Shengyue Hao,Chen Zhen,Xia Zhou,Lin Zhang,Zhaoyang Guo
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
被引量:8
标识
DOI:10.1108/ecam-01-2023-0045
摘要

Purpose Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior. Design/methodology/approach First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations. Findings External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB. Originality/value This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.
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