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Advances in Project Development and Construction Management—2nd Edition
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Advances in Project Development and Construction Management—2nd Edition

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 3698

Special Issue Editors

Prof. Dr. Wenzhe Tang

E-Mail Website
Guest Editor
School of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: construction management; energy management; engineering-procurement-construction (EPC) project delivery; construction standards; project investment; partnering; cooperative risk management; international project management
Special Issues, Collections and Topics in MDPI journals
Dr. Jianli Hao

E-Mail Website
Guest Editor
Department of Civil Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
Interests: green buildings assessment; carbon emission; construction waste management; waste-to-energy; waste valorization; cost and benefit analysis of recycled materials; life cycle assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The second edition of the Special Issue “Advances in Project Development and Construction Management” aims to publish research that addresses advances related to construction engineering and management. This Special Issue covers the themes of engineering project planning, design, procurement, construction, project delivery, operation, sustainable project development, green buildings, construction waste management, and information technologies. We welcome papers on new theoretical and technological advancements and practical approaches that help achieve the many objectives of engineering projects associated with economic, social, and environmental sustainability.

Prof. Dr. Wenzhe Tang
Dr. Jianli Hao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • project planning
  • design
  • procurement
  • construction
  • project delivery
  • operation
  • sustainable project development
  • green buildings
  • construction waste management
  • information technologies

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

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Research

15 pages, 799 KiB  
Article
Safety Climate in High-Rise Construction
by Igal M. Shohet, Roi Naveh and Fadi Shahin
Buildings 2025, 15(9), 1398; https://doi.org/10.3390/buildings15091398 - 22 Apr 2025
Viewed by 195
Abstract
This study examines safety climate perceptions in construction using two models: the Safety Climate Model (SCM) and the Nordic Safety Climate Questionnaire (NOSACQ-50). Data from 20 projects of various sizes (ranging from 11 to 50 floors) and company years of experience (1-25+) were [...] Read more.
This study examines safety climate perceptions in construction using two models: the Safety Climate Model (SCM) and the Nordic Safety Climate Questionnaire (NOSACQ-50). Data from 20 projects of various sizes (ranging from 11 to 50 floors) and company years of experience (1-25+) were analyzed using the 5-point Likert scale and ANOVA tests. SCM and NOSACQ-50 contained 10 and 7 questions, respectively. Responses were gathered from safety officers and supervisors. Results revealed insights into safety culture and the impact of management practices on safety perceptions in high-rise construction. The study found that safety climate perceptions were relatively poor, with a score of 3.865 for the SCM and 3.600 for NOSACQ-50. The findings emphasize the need for stronger safety practices at higher organizational levels, particularly in management, expressed by the findings of 3.3 and 3.5 in means of management commitment and safety climate fostering in NOSACQ-50 and the relatively large variance in the NOSACQ-50 model (0.23), control, and leadership. Cronbach’s alpha values were 0.935 and 0.943 for SCM and NOSACQ-50, respectively, indicating internal adherence of the models to safety practices. A moderate positive correlation of 0.470 between the two models suggests that both measures overlap but there exist distinct aspects of safety perceptions. In SCM, the highest-rated factors were safety equipment availability and employee participation in safety training, and employees feel the company prioritizes their well-being, highlighting the importance of resources and engagement. Current work pace does not compromise safety measures and protocols received the lowest score. In NOSACQ-50, the highest scores were for management’s commitment to safety and safety communication, while the lowest scores were found for management actions, reflecting their commitment to worker safety management and employees’ shared responsibility, suggesting areas for future improvement. The study underscores that project size and company years of experience do not significantly affect safety perceptions, but effective safety communication, management commitment, and employee engagement are crucial. The findings indicate that the NOSACQ-50 better elucidates safety climate core performance as depicted by the larger coefficient of variance (0.23 compared to 0.16). Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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27 pages, 7637 KiB  
Article
Generative AI and Prompt Engineering: Transforming Rockburst Prediction in Underground Construction
by Muhammad Kamran, Muhammad Faizan, Shuhong Wang, Bowen Han and Wei-Yi Wang
Buildings 2025, 15(8), 1281; https://doi.org/10.3390/buildings15081281 - 14 Apr 2025
Viewed by 375
Abstract
The construction industry is undergoing a transformative shift through automation, with advancements in Generative AI (GenAI) and prompt engineering enhancing safety and efficiency, particularly in high-risk fields like underground construction, geotechnics, and mining. In underground construction, GenAI-powered prompts are revolutionizing practices by enabling [...] Read more.
The construction industry is undergoing a transformative shift through automation, with advancements in Generative AI (GenAI) and prompt engineering enhancing safety and efficiency, particularly in high-risk fields like underground construction, geotechnics, and mining. In underground construction, GenAI-powered prompts are revolutionizing practices by enabling a shift from reactive to predictive approaches, leading to advancements in design, project planning, and site management. This study explores the use of Google Gemini, a recent advancement in GenAI, for the prediction of rockburst intensity levels in underground construction. The Python programming language and the Google Gemini tool are combined with prompt engineering to generate prompts that incorporate essential variables related to rockburst. A comprehensive database of 93 documented rockburst cases is compiled. Subsequently, a systematic method is established that involves the categorization of intensity levels through data visualization and factor analysis in order to identify a reduced number of unobservable underlying factors. Furthermore, K-means clustering is utilized to identify data patterns. The gradient boosting classifier is then employed to predict the intensity levels of rockburst. The results demonstrate that GenAI and prompt engineering offers an effective approach for accurately predicting rockburst events, achieving an accuracy rate of 89 percent. Through predictive modeling with GenAI, construction engineering experts can proactively evaluate the likelihood of rockburst, allowing for improved risk management, optimized excavation strategies, and enhanced safety protocols. This approach enables the automation of complex analyses and provides a powerful tool for real-time decision-making and predictive insights, offering significant benefits to industries reliant on underground construction. However, despite the considerable potential of GenAI and prompt engineering in the construction sector, challenges related to output accuracy, the dynamic nature of projects, and the need for human oversight must be carefully addressed to ensure effective implementation. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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22 pages, 2038 KiB  
Article
Innovation and Cost Influence of Environmental Regulation Policies on Megaprojects
by Li Ma, Jonathan Musonda and Azhar Ali
Buildings 2025, 15(7), 1012; https://doi.org/10.3390/buildings15071012 - 21 Mar 2025
Viewed by 212
Abstract
The indispensable significance of megaprojects to a nation’s economy, society, and infrastructure demands ongoing efforts to alleviate the environmental consequences they produce. Nonetheless, the adoption of sustainable practices and legislation is infrequent in developing countries, chiefly due to the substantial expenses linked to [...] Read more.
The indispensable significance of megaprojects to a nation’s economy, society, and infrastructure demands ongoing efforts to alleviate the environmental consequences they produce. Nonetheless, the adoption of sustainable practices and legislation is infrequent in developing countries, chiefly due to the substantial expenses linked to sustainable construction methods. The fundamental goal of this quantitative research is to establish a framework for the execution of sustainable practices and regulations. It aims to provide indicators for these rules, examine their relationship with these dimensions, and ultimately explore the moderating influence of cost. Data from the Zambian construction sector were acquired and evaluated using the partial least squares approach. The analysis indicated that the indicators were ideal for implementing rules and sustainable practices to mitigate the environmental impacts of megaprojects, primarily because of their strong correlation with the variables. Secondly, they enhanced the correlation between sustainable construction and the reduction of environmental damage. Third, the adverse impact of elevated expenses in this relationship obstructs the implementation of these policies. The results demonstrate that elevated expenses hinder the execution of certain regulations. A reduced expense for sustainable construction would significantly promote the implementation of these regulations. This study lays out a framework for the construction industry to adopt and follow environmentally friendly rules and practices. These recommendations will lessen the damage that big projects do to the environment and improve the connection between sustainable construction and the environment. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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24 pages, 7345 KiB  
Article
Sustainable Building Project Management in Algeria: Challenges, Strategies, and Future Directions for Environmentally Friendly Construction
by Mina Merzouk, Jie Zhao and Zhao Xu
Buildings 2025, 15(6), 883; https://doi.org/10.3390/buildings15060883 - 12 Mar 2025
Viewed by 734
Abstract
The effective integration of green project management practices is crucial for promoting sustainable construction in Algeria while ensuring cost efficiency. This study proposes a structured framework to modify traditional project management approaches throughout the project life cycle, focusing on early interdisciplinary collaboration, integrated [...] Read more.
The effective integration of green project management practices is crucial for promoting sustainable construction in Algeria while ensuring cost efficiency. This study proposes a structured framework to modify traditional project management approaches throughout the project life cycle, focusing on early interdisciplinary collaboration, integrated design, and continuous training. Key barriers to implementation include limited awareness, high costs, and inadequate government support, all of which hinder the widespread adoption of sustainable practices. The findings reveal inconsistencies in the application of green construction methods, emphasizing the need for robust policy incentives, financial support, and active community participation. Additionally, the study highlights the urgency of educational initiatives to bridge knowledge gaps and advocates for incorporating sustainability into urban planning. Addressing these challenges will enable Algeria to advance its sustainable construction sector, positioning it as a model for other developing nations seeking to balance economic growth with environmental responsibility. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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13 pages, 227 KiB  
Article
Psychometric Validation of the CD-RISC-10 Among Chinese Construction Project High-Place Workers
by Ruiming Fan, Yang Li, Ruoxi Zhang, Jingqi Gao and Xiang Wu
Buildings 2025, 15(5), 822; https://doi.org/10.3390/buildings15050822 - 5 Mar 2025
Viewed by 443
Abstract
Individuals with high psychological resilience cope with stress more effectively. It is crucial to select a suitable psychological resilience tool for workers in high-risk industries to identify and help those with lower resilience early on, protecting their health and reducing accidents. The CD-RISC-10 [...] Read more.
Individuals with high psychological resilience cope with stress more effectively. It is crucial to select a suitable psychological resilience tool for workers in high-risk industries to identify and help those with lower resilience early on, protecting their health and reducing accidents. The CD-RISC-10 is widely used, and this study assessed its validity and reliability among Chinese construction workers, focusing on workers on elevated platforms. A total of 325 valid CD-RISC-10 scales were collected and analyzed using statistical methods, such as exploratory factor analysis, confirmatory factor analysis, and K-means cluster analysis. The results show that the CD-RISC-10 can effectively measure psychological resilience with a high scale reliability of 0.857, and it had an acceptable model fit (CFI = 0.947) and good item discrimination. About 17.23% of the measured sample of Chinese workers working at height were identified as having resilience impairments, and demographic variables such as age, length of service, educational level, and accident experience had a significant impact on the level of resilience, revealing the heterogeneity of the workers. This study validated the measurement validity of the CD-RISC-10 scale among Chinese high-place workers, and the analysis results were conducive to conducting psychological resilience assessments, improving workers’ occupational health, and promoting the sustainable development of construction enterprises. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
22 pages, 2798 KiB  
Article
Data Augmentation Approaches for Estimating Curtain Wall Construction Duration in High-Rise Buildings
by Sang-Jun Park, Jin-Bin Im, Hye-Soon Yoon and Ju-Hyung Kim
Buildings 2025, 15(4), 583; https://doi.org/10.3390/buildings15040583 - 13 Feb 2025
Viewed by 602
Abstract
Reliable project management during planning stages of a building project is a meticulous process typically requiring sufficient precedencies. Typical construction duration estimation is based on previous cases of similar projects used to validate construction duration proposals from contractors, plan overall project duration, and [...] Read more.
Reliable project management during planning stages of a building project is a meticulous process typically requiring sufficient precedencies. Typical construction duration estimation is based on previous cases of similar projects used to validate construction duration proposals from contractors, plan overall project duration, and set a standard for project success or failure. In cases of high-rise buildings exceeding 200 m, insufficient data commonly arise from the rarity of such projects, leading to a rough estimation of construction duration. Therefore, in this study, oversampling and data augmentation techniques derived from engineering principles, such as parametric optimization and data imbalance problems, are explored for curtain wall construction for high-rise buildings. The study was conducted in two phases. First, oversampling and data augmentation techniques, including Latin Hypercube, optimal Latin Hypercube, simple Monte Carlo, descriptive Monte Carlo, Sobol Monte Carlo, synthetic minority oversampling technique (SMOTE), and SMOTE–Tomek, were applied to 15 raw datasets collected from previous projects. The dataset was split into 8:2 for training and testing, where the mentioned techniques were applied to generate 500 virtual samples from the training data. Second, support vector regression was applied to forecast construction duration, where statistical performance criteria were applied for evaluation. The results showed that SMOTE and SMOTE–Tomek best represented the original dataset based on box plot analysis showcasing data distribution. Moreover, according to statistical performance criteria, it was found that the oversampling techniques improved the prediction performance, where Pearson correlation for linear, polynomial, and RBF increased by 0.611%, 4.232%, and 0.594%, respectively, for the best-performing sampling method. Finally, for the prediction models, probabilistic oversampling methods outperformed other methods according to the statistical performance criteria. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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14 pages, 395 KiB  
Article
Predicting the Effectiveness of Resilient Safety in the Building Construction Sector of Rwanda Using the ANN Model
by Esperance Umuhoza and Sung-Hoon An
Buildings 2025, 15(2), 237; https://doi.org/10.3390/buildings15020237 - 15 Jan 2025
Viewed by 629
Abstract
Most construction projects encounter safety issues that may affect project effectiveness and the lives of workers. Although various studies have investigated these factors, in some countries, such as Rwanda, there is still little empirical evidence regarding the important aspects that contribute to safety [...] Read more.
Most construction projects encounter safety issues that may affect project effectiveness and the lives of workers. Although various studies have investigated these factors, in some countries, such as Rwanda, there is still little empirical evidence regarding the important aspects that contribute to safety effectiveness. Therefore, this study was carried out to predict the resilient safety effectiveness in the Rwandan building construction sector via the artificial neural network (ANN) model. Through a literature review, resilient safety variables that may be relevant in the Rwandan construction sector were identified. Data were collected through questionnaires. Moreover, the levels of importance of resilient-safety-effectiveness-related factors were pinpointed and assessed using the analytical hierarchy process (AHP). Consecutively, an ANN model that could predict the effectiveness of resilient safety was developed. This study contributes to the awareness of key factors that may affect the effectiveness of resilient safety, and it helps to forecast the effectiveness of resilient safety not only in Rwanda, but also in other low- and middle-income countries with different conditions by stressing the importance of reducing safety-related risks in building construction projects. Full article
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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