Binchao Deng

Dr. Binchao Deng

teacher and researcher
orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 November 2022 in Buildings
Verified
Journal Article
Open access
PDF file
WXWenwen Xie
Wenwen Xie
Binchao DengBinchao Deng
Binchao Deng
YYYilin Yin
Yilin Yin
WXWENWEN XIE
WENWEN XIE
ZDZhenhua Deng
Zhenhua Deng
Construction industries have poor cost performance in terms of finishing projects within a budget. A fuzzy model for evaluating the critical factors of cost overrun for construction projects in China is developed by identifying, classifying and ranking cost overrun factors of the construction industries. Sixty-five cost overrun factors are identified and classified into four clusters (project macro, project management, project environment, and core stakeholders) through a detailed literature review process and a discussion with experts from the Chinese construction industry. A questionnaire survey was conducted for data collection to calculate an index of the project-influenced factors and clusters in the construction industry in China. With the help of the proposed model, it is possible to guide project managers and decision makers to make better informative decisions such as project macro, project management, project environment, and core stakeholders.

26 February 2021 in Sustainability
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Journal Article
Open access
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Binchao DengBinchao Deng
Binchao Deng
DZDongjie Zhou
Dongjie Zhou
JZJiachen Zhao
Jiachen Zhao
YYYilin Yin
Yilin Yin
XLXiaoyu Li
Xiaoyu Li
Public Private Partnership (PPP) projects have attracted wide attention from academia and industry over the past 20 years, however, they have been plagued by certain factors. This study identified, classified, and evaluated the success factors that may affect PPP projects for achieving sustainability. First, a list of 32 critical success factors were categorized into 3 groups, then a questionnaire survey was conducted, with 108 responses received from experts, researchers, and PPP project managers in China. Second, using a fuzzy synthetic evaluation (FSE) method, stakeholder relationships (A1–A10), external environmental (B1–B8), and project management of a special purpose vehicle (C1–C14) collected data at three different factor group locations in PPP projects were used in this evaluation. The results obtained nine top factors: private sector financing capacity, government credit, government commitment or guarantee, completeness of legal framework, available financial markets, the feasibility study report and implementation, effectiveness of risk management, project investment, and cost control and revenue distribution. It was demonstrated that fuzzy synthetic evaluation techniques are quite appropriate techniques for PPP projects. The research findings should impact on policy development towards PPP and Private Finance Initiative (PFI) project governance.

1 January 2021 in Complexity
Verified
Journal Article
Open access
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Binchao DengBinchao Deng
Binchao Deng
WXWenwen Xie
Wenwen Xie
FCFan Cheng
Fan Cheng
JDJiaojiao Deng
Jiaojiao Deng
LLLiang Long
Liang Long
Intra‐organization and inter‐organization collaboration and governance are becoming increasingly important for megaprojects. Different stakeholders form intricate links in a network structure. This study explores the role and effect of hybrid governance on complex network projects, such as urban rail transit projects. This included conducting a questionnaire survey with 116 professionals from organizations involved in urban rail transit projects and adopting structural equation modelling to analyze the data. The results analyzed the levels of intra‐organization and inter‐organization trust under the conditions of power asymmetry and power sharing. A higher level of power asymmetry was associated with lower hybrid governance performance. In contrast, a higher level of power sharing is associated with better hybrid governance performance. The results are generalizable to other projects with complicated organizational and network relationships.

30 January 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
LZLihong Zhang
Lihong Zhang
Saeed Reza MohandesSaeed Reza Mohandes
Saeed Reza Mohandes
JTJiawei Tong
Jiawei Tong
Mohamed AbadiMohamed Abadi
Mohamed Abadi
Saeed BanihashemiSaeed Banihashemi
Saeed Banihashemi
Binchao DengBinchao Deng
Binchao Deng
Though a relatively large number of studies on sustainable project governance (SPG) have been undertaken, the existing corpus of literature is bereft of a comprehensive review paper that scientometrically analyses the materials published hitherto and puts forward the research gaps and the corresponding future works to be conducted. To fill this knowledge gap, this study undertakes a bibliometric review and scientometric analysis by meticulously delving into the relevant body of knowledge of sustainable governance reported in different databases. From the results obtained using CiteSpace software, the following conclusions can be drawn: (1) most of the keywords with high centrality rankings are related to the environment, (2) “participation” and “land use” are the most important clusters, (3) the United Kingdom and the United States are by far the most advanced countries in the concerned field, (4) the hot topics within the defined clusters are “industry”, “transition management”, “property rights”, and “natural resources”, and (5) the two salient keywords are “public participation” and “insight”. The attained findings lay out a solid foundation for researchers and practitioners towards fostering the area of SPG, by focusing on land use, community participation, politics, climate change, and the water–energy–food nexus and finding ways to tackle the elaborated shortcomings.

19 May 2022 in Buildings
Verified
Journal Article
Open access
PDF file
XLXIAOYU LI
XIAOYU LI
Binchao DengBinchao Deng
Binchao Deng
YYYilin Yin
Yilin Yin
YJYu Jia
Yu Jia
At present, the construction industry in China has problems such as low production efficiency, low technical efficiency, low management efficiency of the construction project, delayed delivery, budget overruns, and unreasonable risk allocation. Value management can address these issues by enhancing the value of construction projects in China, reducing construction costs, and ensuring significant investment returns. This study uses literature analysis to identify the critical obstacles to adopting value management and uses questionnaires and surveys, structural equation modeling, and factor analysis to prioritize the critical obstacles to adopting value management. What is more, the main contribution of this research is to identify the critical obstacles to the adoption of value management, which provides a new perspective for related research and has specific positive significance for practice summary and reform direction. The research was limited to the region of Tianjin and its surrounding cities. The critical survey respondents for this study are architects, quantity surveyors, contractors, civil engineers, and service engineers with rich experience in construction management. The research results show that the key obstacles to implementing value management in the construction industry in China are mainly divided into four categories: Environmental Factors; Stakeholder and Management Factors; Technological Factors; Information Factors. In addition, the researchers found that the level of the adoption of value management in the construction industry in China is deficient. Value management was not used in most of the organizations surveyed, and project teams did not practice its concept.

1 January 2012 in Abstract and Applied Analysis
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Journal Article
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Binchao DengBinchao Deng
Binchao Deng
TCTong Chen
Tong Chen
Baogui XinBaogui Xin
Baogui Xin
Let be N quasi‐nonexpansive mappings defined on a closed convex subset C of a real Hilbert space H. Consider the problem of finding a common fixed point of these mappings and introduce the parallel and cyclic algorithms for solving this problem. We will prove the strong convergence of these algorithms.