Evaluating the sustainability risk level of public-private partnership (PPP) projects can reduce project risk incidents and achieve the sustainable development of the organization. However, the existing studies about PPP projects risk management mainly focus on exploring the impact of financial and revenue risks but ignore the sustainability risks, causing the concept of "sustainability" to be missing while evaluating the risk level of PPP projects. To evaluate the sustainability risk level and achieve the most important objective of providing a reference for the public and private sectors when making decisions on PPP project management, this paper constructs a factor system of sustainability risk of PPP projects based on an extensive literature review and develops a mathematical model based on the methods of fuzzy comprehensive evaluation model (FCEM) and failure mode, effects and criticality analysis (FMECA) for evaluating the sustainability risk level of PPP projects. In addition, this paper conducts computational experiment based on a questionnaire survey to verify the effectiveness and feasibility of this proposed model. The results suggest that this model is reasonable for evaluating the sustainability risk level of PPP projects. To our knowledge, this paper is the first study to evaluate the sustainability risk of PPP projects, which would not only enrich the theories of project risk management, but also serve as a reference for the public and private sectors for the sustainable planning and development.
Indirect carbon emissions account for a large ratio of the total carbon emissions in processes to make the final products, and this implies indirect carbon emission flow across industries. Understanding these flows is crucial for allocating a carbon allowance for each industry. By combining input-output analysis and complex network theory, this study establishes an indirect carbon emission flow network (ICEFN) for 41 industries from 2005 to 2014 to investigate the interrelationships among different industries. The results show that the ICEFN was consistent with a small-world nature based on an analysis of the average path lengths and the clustering coefficients. Moreover, key industries in the ICEFN were identified using complex network theory on the basis of degree centrality and betweenness centrality. Furthermore, the 41 industries of the ICEFN were divided into four industrial subgroups that are related closely to one another. Finally, possible policy implications were provided based on the knowledge of the structure of the ICEFN and its trend.
The construction industry has played an important role in reducing carbon emissions. Various policies have been implemented to stimulate construction enterprises to reduce carbon emissions, but the effects of emission reduction are not obvious, for they do not directly benefit the enterprises. This paper employs a modified Shapley value method to study benefit allocation in a construction supply chain considering carbon emissions. Four correction factors are proposed for modifying the initial allocation, namely the contribution rate of inputs, the risk-sharing coefficient, the degree of cooperation and the contribution rate of carbon emissions. We analyze carbon emissions based on an illustrative example of a concrete supply chain consisting of a cement manufacturer, a concrete manufacturer and a construction enterprise, and present our findings. First, the enterprises intend to cooperate to achieve the greatest benefit, and second, the benefit allocation is greatly affected by carbon emissions. Participants that produce more carbon emissions have higher carbon tax costs, which reduce profits. Further suggestions are also presented, which may help enterprises reduce carbon emissions. And policy makers should arrive at a suitable level of carbon tax to promote the smooth progress of projects and to improve the emission reduction effect.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.