Internet of Things (IoT) conception has become a popular trend among industries. Many have already adopted the technology and put it into practice. IoT can incentive and change the way people conduct business in the construction industry. The objective of the research is to figure out the impact factors that influence practitioners’ willingness to adopt IoT in Taiwan’s construction industry. The hypothesis was developed based on a comprehensive literature review and the concept of the Unified Theory of Acceptance and Use of Technology (UTUAT). The UTUAT framework and hypotheses developed included 5 main hypotheses, 6 aspects and 33 stems. A pilot study aimed at experienced practitioners in the industry was carried out before the full-scale survey to adjust the stems. The adjusted questionnaire including 31 stems belonging to 7 aspects was then distributed to practitioners. A total of 282 valid questionnaires distributed were collected and 6 types of analysis (descriptive statistics, reliability, validity, t-test, one-way of variance, and structural equation modelling). The findings including (1) anticipated benefits significantly affect the users’ willingness to adopt IoT; (2) anticipated efforts significantly affect the users’ willingness to adopt IoT; (3) societal expectations significantly affect the users’ willingness to adopt IoT.

This study serves as a practical model for optimizing production planning, allocation of precast component storage, and transportation sites as well as for making timely adjustments for contracted projects. To ensure that the structure of the research model is reasonable and matches actual applications, the study uses a field survey to directly observe the largest precast concrete plants in Taiwan for a period of 6 months, followed by in-depth interviews with experts involved with the planning, design, installation, and manufacturing for precast projects. The mathematical model is then established and evaluated using the data containing over 90% of national production in Taiwan. The results show that the tested corporate profits increase by an impressive 38.4% and performance is significantly increased by 97.75%. The proposed model can not only make up for oversights in human decision-making but improve the decision-making process boosting corporate competitiveness.

This study puts forward a logical framework for green innovation network analysis, which includes a spatial dimension, a relational dimension, and a systems dimension. Here, we put forward some basic research ideas concerning the optimization and regulation of green innovation networks in terms of the systems dimension and we investigate the micro-dynamic mechanisms of green innovation network expansion using a spatial econometric model. Our main research results are as follows: The efficiency of green innovation in the Yangtze River Economic Belt has improved significantly, however, the gap between cities has gradually increased, and a problem of efficiency regression has emerged. The green innovation network has changed from the primary stage dominated by Edge Network to the rapid growth stage dominated by Supporting Network, and formed a complex network pattern with diversified hierarchical structure. Node symmetry is helpful in forming more extroverted connections and promoting the expansion of green innovation networks. Node proximity and connection symmetry inhibit the growth and development of networks, and knowledge flow cooperation networks can accelerate the evolution of green innovation networks. Finally, this paper holds that we should combine the actual development needs, emphasize the basic principles of differentiated development, and construct the development pattern of regional collaborative innovation. This can also provide a theoretical reference for enriching our understanding of green innovation networks while narrowing the gap between cities.