Wang, X., Yang, Y., Darko, A., Chan, A. P. C., & Chi, H.-L. (2024). The impact of penalties, incentives, and monitoring costs on the stakeholders’ decision-making behaviors in non-compliance drone operations. Technology in Society, 77. https://doi.org/10.1016/j.techsoc.2024.102589
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Abstract
As an automated assistive tool, drones have revolutionized industrial activities and brought numerous potential benefits to society. However, irresponsible drone users often disregard compliance with regulations, leading to new challenges in drone usage. Although governments have implemented punishment and incentive mechanisms to prevent non-compliant drone operations, the extent to which they can effectively deter such activities remains unclear. To address this gap, the study employed evolutionary game theory to assess the impacts of penalties for non-compliance, incentives for public monitoring, and monitoring costs for the government on the multiple stakeholders' decision-making behaviors (SDBs). The study also used the Chinese construction market data to simulate how penalties, incentives, and monitoring costs influence SDBs. The numerical simulations reveal that penalties and incentives could reduce drone users' non-compliant operations, but this effect is useful only if the penalties and incentives exceed a certain value. In China, drone users' non-compliant operations can be controlled when penalties for drone users exceed 12,000 yuan, and incentives for the public's monitoring exceed 170 yuan/day. The current Chinese government's penalties that were administered for non-compliant drone operations have not achieved a deterrent effect, but the incentive is feasible. These findings provide a fresh insight into the decision-making behaviors of stakeholders in non-compliant drone operations. Additionally, the tripartite evolutionary game model developed in this study can assist other countries in determining optimal values for penalties, incentives, and monitoring costs to mitigate non-compliant drone operations effectively.
Debrah, C., Chan, A. P. C., Darko, A., Ries, R. J., Ohene, E., & Tetteh, M. O. (2024). Driving factors for the adoption of green finance in green building for sustainable development in developing countries: The case of Ghana. Sustainable Development., 1–22. https://doi.org/10.1002/sd.3022
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Abstract
While there are many motivating factors for green finance (GF) implementation, a comprehensive taxonomy of these variables is lacking in the literature, especially for green buildings (GBs). This study aims to analyze the criticality and interdependence of GF‐in‐GB's driving factors. This study develops a valid set of factors to justify the interrelationships among the drivers. The drivers of GF‐in‐GB are qualitative in nature, and uncertainties exist among them due to linguistic preferences. This study applies the fuzzy Delphi method to validate eight drivers under uncertainties. Fuzzy Decision‐Making Trial and Evaluation Laboratory (FDEMATEL) with qualitative information is used to determine the interrelationships among the drivers. The drivers were grouped under two categories: prominent drivers and cause‐effect drivers. The findings revealed that “increased awareness of GF models in GB” and “preferential capital requirements for low‐carbon assets” are the top two most prominent/important drivers of GF‐in‐GB. In Ghana, the top three cause group drivers are “climate commitment,” “improved access to and lower cost of capital,” and “favorable macroeconomic conditions and investment returns.” Drivers with the highest prominence values have the potential to affect and/or be affected by other drivers; therefore, managers and policymakers should prioritize promoting or pursuing these drivers in the short term. On the other hand, it is important to pay more than equal attention to the drivers with the highest net cause values because they have the largest long‐term impact on the entire system. The theoretical and practical implications of the study are discussed, enhancing understanding and decision‐making in GF‐in‐GB.
Keywords
fuzzy Delphi method; fuzzy DEMATEL; green building; green finance; sustainable development
Linyan Chen, Amos Darko, Mayowa I. Adegoriola, Albert P.C. Chan, Yang Yang, Mershack O. Tetteh, “Challenges to energy retrofitting of existing office buildings in high-rise high-density cities: The case of Hong Kong,” Energy and Buildings, Volume 312, 2024, 114220, ISSN 0378-7788, https://doi.org/10.1016/j.enbuild.2024.114220.
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Abstract
Achieving carbon neutrality by 2050 has become a global goal, sparking concerns regarding energy consumption and carbon emissions in building operations. Office buildings in high-rise high-density cities serve as central business districts, contributing significantly to the city’s economic activity and consuming a lot of energy. The process of retrofitting existing office buildings for energy efficiency in high-rise high-density cities tends to be challenging. However, there is a lack of comprehensive understanding of the challenges involved in office buildings’ energy retrofitting, as they have not been thoroughly explored. This study aims to investigate the challenges to the existing office building energy retrofitting (EOBER) in high-rise high-density cities with real cases in Hong Kong. Initially, a systematic literature review was undertaken to identify 49 potential EOBER challenges and categorized into seven groups: technical, financial, institutional, social, environmental, regulatory, and other categories. Afterward, 23 EOBER challenges were identified through 24 semi-structured interviews with 36 real office building energy retrofitting cases in Hong Kong. Moreover, these challenges were quantified by the Z-numbers-based Delphi survey and analysis. Results show that regulatory challenges are the primary challenges, followed by financial challenges. The lack of government incentives, policies, legislation and regulations significantly hinders practitioners’ ability to engage in energy retrofitting initiatives. The long payback period of building energy retrofitting poses a critical financial concern for practitioners embracing such initiatives. In the end, this research proposed integrated strategies to tackle these challenges and increase building energy efficiency, including launching financial and regulatory incentives, shortening the interval for mandatory energy audits, disseminating knowledge, and diversifying finance channels of building energy retrofitting. The findings contribute to the body of knowledge by employing systems thinking to identify and evaluate EOBER challenges in high-rise high-density cities through empirical methodologies. Moreover, this study provides valuable references for practitioners in navigating these challenges and minimizing risks associated with the retrofitting process.
Wang, L., Chan, D. W. M., Darko, A., & Oluleye, B. I. (2024). A-state-of-the-art review of risk management process of green building projects. Journal of Building Engineering, 86. https://doi.org/10.1016/j.jobe.2024.108738
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Abstract
Green buildings (GB) have attracted significant attention for improving sustainability and reducing carbon emissions in the building sector. Like traditional projects, risk management plays a crucial role in green projects. The inadequacy of risk management may lead to diminished workforce performance, delays in project schedules, and poor quality in GB projects. To comprehend risk management in GB projects, it is essential to conduct a state-of-the-art review. This study applied the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method to select 52 records from the database ‘Scopus’ and ‘Web of Science’ (WoS). A bibliometric analysis indicated that the emphasis in risk management is on the identification and evaluation of risks in engineering projects. Subsequently, a thematic analysis displayed the research topics related to risk management, including (1) methods for identifying risks, (2) risk identification in special conditions, (3) risk assessment with fuzzy sets, social network analysis (SNA), and interpretive structural modeling (ISM), and (4) risk assessment with other technologies. This study focused on the research gaps within the risk management field, specifically in risk identification methods, risk evaluation methods, and risk-mitigating processes. Finally, with research gaps, this study also proposed related research directions for risk management in GB projects.
T.A.D.K. Jayasanka, Amos Darko, D.J. Edwards, Albert P.C. Chan, Farzad Jalaei, Automating building environmental assessment: A systematic review and future research directions, Environmental Impact Assessment Review, Volume 106, 2024, 107465, ISSN 0195-9255, https://doi.org/10.1016/j.eiar.2024.107465.
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Abstract
Building environmental assessment (BEA) is critical to improving sustainability. However, the BEA process is inefficient, costly, and often inaccurate. Because automation has the potential to enhance the efficiency and accuracy of the BEA process, studies have focused on automating BEA (ABEA). Updated until now, a comprehensive analysis of prevailing literature on ABEA remains absent. This study conducts the first comprehensive systematic analysis appraising the state-of-the-art of research on ABEA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guided to systematically analyse 91 relevant studies. Results uncover that only 29.7% of BEA systems worldwide have automated their processes, with the US LEED residing at the vanguard of automation efforts. The New Buildings scheme was mostly focused on, while largely ignoring other schemes, e.g., Existing Buildings. Five key digital approaches to ABEA were revealed, namely building information modelling (BIM) and plug-in software, BIM-ontology, data mining and machine learning, cloud-BIM, and digital twin-based approaches. Based on identified gaps, future research directions are proposed, specifically: using data mining and machine learning models for ABEA; development of a holistic cloud-based approach for real-time BEA; and digital twin for dynamic BEA. This study generates a deeper understanding of ABEA and its theoretical implications, such as major constructs and emerging perspectives, constitute a basis for holistic, and innovation in, BEA.
The new cohort of faculty have made a big impact in their initial time on campus. Please see the full story here. The cohort includes: Dr. Narjes Abbasabadi, an assistant professor in the Department of Architecture and affiliate data science faculty UW eScience Institute, studies computation and decarbonization of the built environment. Dr. Amos Darko, an assistant professor in Construction Management, studies how digital technologies can help people better monitor, assess, understand, and improve the sustainability performance of the built…
Dr. Darko brings with him a wealth of expertise and experience in sustainability, sustainable built environment, sustainable construction, green building, modular construction, project management, and digital technologies including building information modeling and artificial intelligence.
Dr. Darko earned his Ph.D. degree from The Hong Kong Polytechnic University (PolyU) in 2019, and his BSc degree (First Class Honors) from Kwame Nkrumah University of Science and Technology (KNUST) in 2014. Before joining the University of Washington, Dr. Darko was a Research Assistant Professor at PolyU.
Dr. Darko has published numerous papers in leading international peer-reviewed journals, conferences, and books. His papers have been rated as highly cited and hot papers by the Web of Science. His paper is the most cited paper of all time in the International Journal of Construction Management. He has also been ranked among the world’s top 2% most cited scientists by Elsevier BV and Stanford University. Dr. Darko has received several awards for his outstanding work, including the Green Talents Award from the German Federal Ministry of Education and Research in 2020, the Global Top Peer Reviewer Award from the Web of Science Group in 2019, the Outstanding Overseas Young Scholars Award from Central South University in 2019, and the Best Construction Technology and Management Student Award from KNUST in 2014.
Dr. Darko’s work has been supported by the Research Grants Council of Hong Kong, Chief Secretary for Administration’s Office of Hong Kong, and several internal grants.
Dr. Darko is an Associate Editor of Green Building and Construction Economics, an Associate Editor of Humanities and Social Sciences Communications, and an Academic Editor of Advances in Civil Engineering.
“I am excited to collaborate with colleagues from diverse disciplines to tackle the pressing challenges of sustainability and climate change, and to contribute to shaping a more just and beautiful world,” said Dr. Darko.