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…
Department: Construction Management
Amos Darko
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.
Applicability of Smart Construction Technology: Prioritization and Future Research Directions
Ahn, H., Lee, C., Kim, M., Kim, T., Lee, D., Kwon, W., & Cho, H. (2023). Applicability of smart construction technology: Prioritization and future research directions. Automation in Construction., 153. https://doi.org/10.1016%2Fj.autcon.2023.104953
Abstract
The potential for facilitating faster, safer, and more sustainable construction processes through the adoption of smart construction technologies is widely recognized. However, the limited adoption of these technologies in construction projects highlights the significance of identifying the technological needs of major stakeholders and the prioritization of research and development investment. In this study, the quality function deployment technique is employed to extract and prioritize the required technologies (RTs) from various stakeholders, while a thematic literature review is conducted to identify challenges and future research directions. The findings improve the efficiency of resource allocation, allowing policymakers to strategically address pressing issues. This can facilitate collaboration and communication among researchers, stakeholders, and the wider community, fostering a shared vision and understanding of future research goals and outcome. Prioritizing smart construction technologies can enhance their applicability. The top nine of technologies were prioritized by using quality function deployment. Thematic review was conducted for each of the top nine technologies. The challenges and future research directions were presented by review.
Keywords
Fourth industrial revolution (4IR); Prioritization; Quality function deployment (QFD); Smart construction technologies; Technology innovation
Minju Kim
Affiliate Instructor, Construction Management
Population Health Initiative awards multiple College of Built Environments teams planning grants
The Population Health Initiative announced 12 climate change planning grant awardees. Of those 12 teams, 4 include College of Built Environments researchers. Descriptions of their projects are below. Read the CBE News story here. Linking Climate Adaptation and Public Health Outcomes in Yavatmal, Maharashtra Investigators Sameer H. Shah, Environmental and Forest Sciences Celina Balderas Guzmán, Landscape Architecture Pronoy Rai, Portland State University Project abstract This proposal collects primary interview data with landed and landless agriculturalists in Yavatmal district in…
Campus Sustainability Fund selects College of Built Environments researchers for 2022-2023 work
The Campus Sustainability Fund selected College of Built Environments PhD student Daniel Dimitrov, along with Associate Dean for Research Carrie Sturts Dossick, to receive funding for the project described below. Energy, Information, and the New Work of Building Operations in the Digital Age Amount Awarded: $19,833 Funding Received: 2022-2023 Project Summary: The built environment industry is in the midst of a data revolution paired with a drive for sustainable campus operations. Innovation, information, communication access, and integration provide an opportunity…
Statistical Analysis and Representation Models of Working-Days Liquidated Damages
Abdel Aziz, A. M. (2023). Statistical Analysis and Representation Models of Working-Days Liquidated Damages. Journal of Construction Engineering and Management, 149(7). https://doi.org/10.1061/JCEMD4.COENG-13330
Abstract
Contractors tend to challenge the enforceability of liquidated damages (LDs), claiming they are unreasonable, excessive, penalty statements, or concurrently caused. States customarily assert that the LD rates are a genuine reflection of the expenses expected to be suffered when a project gets delayed due to noncompletion. While there are common practices among the states for articulating LD specifications, which generally follow the Federal Code of Regulations, there are no published studies that assist states in comparing their LD rates to those of other states so that the LD rates might be defended. Further, there are no studies that offer models that would uncover the relationship between the LD rates and the contract sizes so that the LD rates might be justified. This work addresses such gaps in the body of knowledge (BOK) in LDs. With emphasis on the working-days (WD) LD rate schedules, the objectives of this work are to characterize the LD rate schedules across the states and to model a formula(s) that would represent the relationship between the WD LD rates and the contract amounts. The data set for the work represents the LD schedules in the standard specifications of all departments of transportation in the United States. Descriptive and cluster statistical analyses were used for the LD rate characterization. For model development, several linear and nonlinear regression models were employed. The results highlighted considerable LDs variability in the smaller contract sizes and exceptional LD rates stability in the larger sizes. Despite the economic differences among the states, it is found that the LD rate is, on average, 0.02 ¢/$ for projects $20 million or above. Below that, the rate increases between 0.03 ¢/$ and 0.18 ¢/$ until the contracts reach $750,000. LD rates tend to decrease sharply with the increase in contract sizes, forming an L or reverse J shape. This pattern proved complex, and only nonlinear regression with transformed variables successfully modeled it. Credible models were obtained after satisfying the least-squares regression assumptions. The work contributes to the BOK by adding a new statistical dimension to understanding LDs and developing regression model(s) that explain the relationships between the LD rates and the contract sizes. The work should help SHAs create, evaluate, and justify their LD rates.
Don’t take concrete for granite: the secret research life of CBE Department of Construction Management Assistant Professor and concrete materials researcher Fred Aguayo
Concrete can sequester carbon, and the cement that glues its components together has been used since antiquity. Now, CBE professor Fred Aguayo is introducing students to the complex world of concrete research.
Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-Level Construction Worker Fatigue: a Logistic Regression Approach
Lee, Wonil; Lin, Ken-Yu; Johnson, Peter W.; Seto, Edmund Y.W. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-Level Construction Worker Fatigue: a Logistic Regression Approach. Engineering, Construction, and Architectural Management, 29(8), 2905–23.
Abstract
The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors.
Keywords
Technology, management, construction safety, information and communication technology (ICT) applications
ACT²: Time–Cost Tradeoffs from Alternative Contracting Methods
Choi, Kunhee, Bae, Junseo, Yin, Yangtian, and Lee, Hyun Woo. (2014). ACT²: Time–Cost Tradeoffs from Alternative Contracting Methods. Journal of Management in Engineering, 37(1).
Abstract
Incentive/disincentive (I/D) and cost-plus-time (A+B) are two of the most widely used alternative contracting methods (ACMs) for accelerating the construction of highway infrastructure improvement projects. However, little is known about the effects of trade-offs in terms of project schedule and cost performance. This study addresses this problem by creating and testing a stochastic decision support model called accelerated alternative contracting cost-time trade-off (ACT2). This model was developed by a second-order polynomial regression analysis and validated by the predicted error sum of square statistic and paired comparison tests. The results of a descriptive trend analysis based on a rich set of high-confidence project data show that I/D is effective at reducing project duration but results in higher cost compared to pure A+B and conventional methods. This cost-time trade-off effect was confirmed by the ACT2 model, which determines the level of cost-time trade-off for different ACMs. This study will help state transportation agencies promote more effective application of ACMs by providing data-driven performance benchmarking results when evaluating competing acceleration strategies and techniques.
Keywords
Errors (statistics), Project management, Benefit cost ratios, Regression analysis, Construction costs, Infrastructure construction, Contracts and subcontracts, Construction methods