Building photovoltaic integration (BIPV) technology can effectively solve the urban energy shortage, environmental damage, and other environmental problems, which is of great significance to the sustainable development of the urban. However, the practical application of BIPV technology has been very slow, and BIPV projects have encountered numerous obstacles and risks in the process of promotion and construction. Although some researchers have conducted qualitative studies on these obstacles and risks, systematic risk assessment methods for BIPV projects are missing. This study aims to systematically develop a framework to assess the risk of BIPV projects to address this gap. First, a comprehensive risk indicator system is established using literature analysis and expert interview methods. Second, DEMATEL (decision-making trial and evaluation laboratory) is used to calculate constant rights. Then, the risk assessment is carried out from the perspective of four-dimensional risk including severity, possibility, urgency, and uncontrollability. The variable weight theory is used to calculate variable weight. The data fusion and risk level determination are realized by the matter-element extension model. Finally, a case study is conducted to verify the feasibility and applicability of the BIPV project risk assessment framework. The results show that the comprehensive risk grade of the BIPV project in Qingdao is III, which belongs to medium risk. In addition, some suggestions are made based on the evaluation results. This study can enrich the methods in the field of risk assessment, and the results can provide a valuable reference for BIPV project investors and decision-makers.
Safety and health have been one of the major issues in the construction industry worldwide for decades, and the relevant research has correspondingly drawn much attention in the academic field. Considering the expanding size and increasing heterogeneity of this research field, this paper proposes the topic modeling approach to cluster latent topics, extract coherent keywords, and discover evolving trends over the past three decades. Focusing on a total of 1984 articles published in 27 different journal sources until February 2023, this paper applied both unsupervised topic modeling techniques—Latent Dirichlet Allocation (LDA) and Correlation Explanation (CorEx)—and their semi-supervised versions—Guided LDA and Anchored CorEx. The evolving trends and inter-relationship of 15 research topics generated by the Anchored CorEx model (the best-performing model) were analyzed. Top-listed documents of major topics were analyzed to discuss their standalone research focuses. The results of this paper provided helpful insights and implications of existing research and offered potential guides for future research on construction safety and health by helping researchers (1) select research topics of interest and clearing decaying topics; (2) extract the top words of each research topic using systematic approaches; and (3) explore the interconnection of different research topics as well as their standalone focuses.
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.