Integrated project delivery (IPD) is a new emerging delivery system, contributes to increase value to the owner, reduces waste and maximizes efficiency in the life cycle of projects. However, IPD system has not yet shifted from pilot-alike or particular-purposed cases to large-scale applications.The huge advantages of building information modeling (BIM) are far from being exploited, which directly leads to the delivered outcomes below expectations, thereby causing obstacles to widespread application of IPD system. The reasons impeding the successful application of BIM has been a hot topic. Previous studies suggested that moral hazard behavior is a critical inducer leading to the undesirable outcomes. However, very few studies have studied the evolution mechanism of moral hazard behavior for BIM application. To fill this knowledge gap, this study proposed a novel model, aiming to capture dynamically the interactive behavior of BIM-based strategy selections using evolutionary game theory. Five parameters of monitoring cost, proprietary cost, incentive payment, punishment and speculative benefit are extracted and defined in the proposed model. Numerical simulations are conducted with MATLAB 2016a. The simulation results showed that when incentive payment is higher than the sum of speculative benefit and proprietary cost, interactive behavior of both game players will move toward the optimal portfolio strategy. Incentive payment and punishment have negative correlations with the probability of moral hazard behavior for BIM application. Parameters of speculative benefit and proprietary cost affect positively implementation probability of moral hazard behavior of employing BIM. This study can provide theoretical and managerial implications for integrated project managers and related government department to improve implementation of BIM and IPD system, and also contribute to its sustainable development.
Integrated Project Delivery (IPD) has become increasingly popular in the architecture, engineering, and construction industries. However, the current practice status by the construction industry fails to deliver the desired results. In that backdrop, how to promote cooperation within and improve the overall performance of integrated project team has received wide attention. Herein, knowledge-sharing plays a critical role in cooperation and overall performance. However, to the best of our knowledge, the research on knowledge-sharing strategy interaction and evolutionary mechanism is rare. To make up for the deficiency of the studies existing, a novel model is proposed by taking advantage of evolutionary game theory, to capture the interaction behavior of knowledge-sharing and explore its evolutionary mechanism. Six parameters of knowledge stock, knowledge-sharing degree, heterogeneous knowledge proportion, synergy effect, knowledge absorption coefficient, and knowledge-sharing cost efficient that are critical to knowledge-sharing are extracted and defined. The payoff matrix is constructed by analyzing the benefits and costs of knowledge-sharing. Then, a replicator dynamic system is established based on payoff matrix, to determine the evolutionary tendency of knowledge-sharing behavior. Finally, numerical simulations are conducted to explore the influences of all parameters on the knowledge-sharing strategy. The findings in this research reveal that strategy interaction behavior is significantly influenced by proportion of strategy of choosing to share knowledge in both game players. The authors also find that strategy interaction behavior has a strong negative correlation with knowledge-sharing cost efficient, but has a positive correlation with knowledge stock, heterogeneous knowledge proportion, degree of knowledge-sharing, knowledge absorption coefficient, and synergetic effect coefficient. This research can provide the evolutionary mechanism and broaden our understanding of relationship between project performance and knowledge-sharing and can offer valuable guidance on improving cooperation and performance of project teams.
Critical infrastructures are tightly connected and extremely fragile multilayer coupled networks. This paper discusses the cross-networks impact of subnetworks and global network of networks on robustness by taking a critical infrastructures with three-layer interdependent networks as an example. The percolation theory is applied to capture the flow characteristics of cascading failures and evaluate the robustness of multilayer networks. And further discuss and compare the situation of each subnetwork affecting or being affected. The quantitative evaluation model of the interaction of multilayer networks is proposed based on cascading failures, where the influence expansion matrix and the dependency matrix are obtained. The results show that the power network has a high influence on other networks, and it is difficult to be affected. Meanwhile the influence ability of water network and gas network is limited.
The power grid is a critical component of city infrastructure. If it is damaged by an earthquake, there can be a huge impact on the safety and well-being of society and individuals. Identifying nodes in the grid that are highly vulnerable to earthquake damage is significant for effective pre-earthquake damage prevention, emergency response, and post-earthquake relief. Three indicators, the probability of node disconnection, the node hierarchical level, and the node critical threshold, were chosen, and their combined ability to represent node vulnerability to damage from an earthquake event was analyzed. A variable fuzzy clustering model was used to classify and order the nodes in the grid. The 20-node power grid of a city was used as an example to show how highly vulnerable nodes were identified, and how the reasons for the high vulnerability of these nodes were drawn out of the analysis. Countermeasures were given to reduce network vulnerability. The variable fuzzy clustering method used in this paper offers a new perspective on network vulnerability, and it quantifies the vulnerability of grid nodes more comprehensively than existing methods of assessing grid vulnerability. This research is significant as a baseline reference for future studies of grid vulnerability.
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