No abstract

With the development of building information technology, Building Information Modeling (BIM) has become an important way to effectively solve the cross-organization information collaboration of Public-Private Partnership (PPP) projects, and how to promote the adoption of BIM in PPP projects has become a realistic problem to be solved urgently. This study discusses the adoption of BIM among stakeholders in PPP projects based on prospect theory and evolutionary game theory. A tripartite evolutionary game model including governments, social capitals, and contractors is established. The behavioral evolution mechanism of each stakeholder on BIM adoption is explored by analyzing the evolutionary equilibrium, and the key influencing factors of equilibrium strategy are analyzed by using numerical simulation. The results demonstrate that first, the degree of the cost to all stakeholders involved in the adoption of BIM, as well as the punishment for governments’ passive promotion of BIM, the punishment for social capitals’ passive adoption of BIM and the reward for contractors’ active application of BIM are the key factors affecting evolutionary stability. Second, according to prospect theory, the main stakeholders usually make decisions through subjective judgment and perceived value which ultimately lead to deviation in their behaviors. The deviations will hinder the establishment of ESS point (1, 1, 1) and make the system difficult to converge to the optimal state. Finally, from the perspective of governments, social capitals, and contractors, countermeasures and management implications are put forward to effectively promote the adoption of BIM in PPP projects.

Innovations can overcome constraints posed by resources depletion, increasing environmental and ecological protection concerns. There is considerable amount of innovation that occurs in the construction industry. Accordingly, construction innovation is receiving increasing attention in China. However, the provincial development level of construction innovation remains unclear. To address this gap, the present study employs data-driven measurement for the level of construction innovation. A total of 25 alternative indexes were selected based on the innovation ecosystem theory. Then, text preprocessing, statistical methods, and search statistics were employed to acquire index data. The indexes weights were determined through expert scoring and a cloud model. The quantitative measurement of the level of construction innovation was nally performed. Additionally, the exploratory results were revealed with the analyses of the overall, regional and cluster. The results revealed that overall level of construction innovation in China is not high and regional distribution is uneven. Simultaneously, the level of construction innovation is consistent with local economic strength and it is most sensitive to innovation output in regional level. Moreover, the spatial distribution of the level of construction innovation in China was showed, which similarity with the characteristics of geographical location is. The measurement system this study represents breakthroughs over traditional methods that rely on statistics, cases or questionnaires, which can be applied to other research elds. IntroductionThe construction industry, one of the largest economic sectors, is critical to the functioning of a domestic economy in China (Murray and Langford, 1998). The construction industry has a wide range of responsibilities, include improving living standards of people, boosting employment and protecting environment (Manseau, 1998). However, buildings consume 46.5% of Chinese energy, produce more than 1.8 billion tons of the waste, and contribute 51.3% of CO 2 emissions (China Building Energy Research Report 2018). It is widely accepted that the productive activities of the construction industry consume signi cant amounts of resources and negatively impact the ecological balance (Peter et al., 2012). Innovation promotes sustainable development and bene ts, such as: energy consumption reductions, environment protections and productivity advancements (Sexton and Barrett, 2003). Construction innovation, which has drawn wide attention within the world, is a determinant of the sustainable development of this industry and national growth. (Panuwatwanich and Stewart, 2012).Construction innovation, which includes product, process, marketing and organizational innovation, represents the changes through something new and can bring bene ts or improvements in cost, time, quality, safety and environment (Maria and Victor, 1995;Pierce and Delbecq, 1977;Bygballe and Ingemansson, 2014;Bassioni et al., 2004;). The innovation in the construction industry is...

Innovations can overcome constraints posed by resources depletion, increasing environmental and ecological protection concerns. There is considerable amount of innovation that occurs in the construction industry. Accordingly, construction innovation is receiving increasing attention in China. However, the provincial development level of construction innovation remains unclear. To address this gap, the present study employs data-driven measurement for the level of construction innovation. A total of 25 alternative indexes were selected based on the innovation ecosystem theory. Then, text preprocessing, statistical methods, and search statistics were employed to acquire index data. The indexes weights were determined through expert scoring and a cloud model. The quantitative measurement of the level of construction innovation was finally performed. Additionally, the exploratory results were revealed with the analyses of the overall, regional and cluster. The results revealed that overall level of construction innovation in China is not high and regional distribution is uneven. Simultaneously, the level of construction innovation is consistent with local economic strength and it is most sensitive to innovation output in regional level. Moreover, the spatial distribution of the level of construction innovation in China was showed, which similarity with the characteristics of geographical location is. The measurement system this study represents breakthroughs over traditional methods that rely on statistics, cases or questionnaires, which can be applied to other research fields.