Construction Management Archives - Page 6 of 21

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

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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.

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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).

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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

The Impact of Empowering Front-Line Managers on Planning Reliability and Project Schedule Performance

Kim, Yong-Woo, and Rhee, Byong-Duk. (2020). The Impact of Empowering Front-Line Managers on Planning Reliability and Project Schedule Performance. Journal of Management in Engineering, 36(3).

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Abstract

This study applies empowerment theory to production planning at the level of frontline managers in a construction project. Using structural equation modeling, we investigate how empowering frontline managers impacts their planning performance. In contrast to prior studies, we find that although psychological empowerment of frontline managers has no direct effect on their production planning reliability or scheduling performance, it has an indirect effect on planning reliability and scheduling performance, as long as the organization supports the empowerment structurally during production planning. This implies that a project manager should provide frontline managers at the operational level with proper formal and informal authority over workflow development, shielding, and resource allocation when planning production in order to enhance job performance through psychological empowerment. This study contributes to the body of knowledge on construction management by exploring the impact of psychological and structural empowerment of frontline managers on their performance of production planning reliability and scheduling performance.

Keywords

Organizations, Managers, Structural models, Scheduling, Structural reliability, Construction management, Human and behavioral factors, Resource allocation

College of Built Environments Announces 2023 Inspire Fund Awards

In 2021, the College of Built Environments launched the CBE Inspire Fund to “inspire” CBE research activities that are often underfunded, but for which a relatively small amount of support can be transformative. The Inspire Fund aims to support research where arts and humanities disciplines are centered, and community partners are engaged in substantive ways. Inspire Fund is also meant to support ‘seed’ projects, where a small investment in early research efforts may serve as a powerful lever for future…

Coastal Adaptations with the Shoalwater Bay Tribe: Centering Place and Community to Address Climate Change and Social Justice

The proposed community-based participatory action research project is a collaborative research, planning and design initiative that will enable a UW research team to work with the Shoalwater Bay Indian Tribe to explore sustainable and culturally relevant strategies for an upland expansion in response to climate change-driven sea level rise and other threats to their coastal ecosystems and community. The situation is urgent as the reservation is located in the most rapidly eroding stretch of Pacific coastline in the US, on near-sea-level land vulnerable also to catastrophic tsunamis. The project will advance the Tribe’s master plan and collaboratively develop a model of climate adaptive, culture-affirming and change-mitigating environmental strategies for creating new infrastructure, housing and open spaces in newly acquired higher elevation land adjacent to the reservation. Design and planning strategies will draw on culturally-based place meanings and attachments to support a sense of continuity, ease the transition, and create new possibilities for re-grounding. Sustainable strategies generated by the project will draw on both traditional ecological knowledge and scientific modeling of environmental change. The project will involve the following methods and activities:

The creation of a Tribal scientific and policy Advisory Board with representatives from the Tribal Council, elder, youth, state and county agencies, and indigenous architects and planners;
Student-led collaborative team-building and research activities that will also engage Tribal youth;
Systematic review of the Tribe’s and neighboring county plans;
Interviews, focus groups and community workshops to identify priority actions, needs and strategies;
Adaptation of existing research on sustainable master planning, design and carbon storing construction materials; and
The development of culturally meaningful and sustainable building prototypes.

Deliverables include a report of findings summarizing community assets and values, and priorities for the upland expansion vetted by Tribal leaders, documentation and evaluation of the UW-community partnership and engagement process, digitized web- based geo-narratives and story maps and technical recommendations for culturally-informed schematic designs, sustainable construction methods and low-embodied carbon storing materials. The project process and outcomes will have broad applicability for other vulnerable coastal communities and can be used to support their climate adaptation efforts as well.

Research Team
Principal Investigator: Daniel Abramson, College of Built Environments, Urban Design and Planning, University of Washington
Community Lead: Jamie Judkins, Shoalwater Bay Indian Tribe

University of Washington Partners:
Rob Corser, Associate Professor, Department of Architecture
Julie Kriegh, Affiliate Lecturer, Departments of Construction Management and Architecture and Principal, Kriegh Architecture Studios | Design + Research
Jackson Blalock, Community Engagement Specialist, Washington Sea Grant
Lynne Manzo, Professor, Department of Landscape Architecture
Kristiina Vogt, Professor, School of Environmental and Forest Sciences

Community Partners:
Daniel Glenn, AIA, NCARB, Principal, 7 Directions Architects/Planners
John David “J.D.” Tovey III, Confederated Tribes of the Umatilla Indian Reservation
Timothy Archer Lehman, Design and Planning Consultant and Lecturer

Clean Energy Justice: Different Adoption Characteristics of Underserved Communities in Rooftop Solar and Electric Vehicle Chargers in Seattle

Min, Yohan, Lee, Hyun Woo, & Hurvitz, Philip M. (2023). Clean Energy Justice: Different Adoption Characteristics of Underserved Communities in Rooftop Solar and Electric Vehicle Chargers in Seattle. Energy Research & Social Science, 96.

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Abstract

Concerns over global climate change have led to energy transition to clean energy systems with the development of various clean energy policies. However, social equity issues have emerged in association with the rapid transition of energy systems related to distributed energy resources (DERs), evidenced by disparities in clean energy access. While most existing studies have focused on several variables impacting the adoption of DERs, there is a dearth of studies concerning distributional and recognition justice specifically aimed at investigating: (1) which DER adoption variable is the most important among several variables identified in the literature; and (2) how adoption patterns vary by technologies and communities. The objective of the present study is to answer the two questions by examining the geographic distribution of rooftop solar and electric vehicle (EV) chargers and the related community attributes. Also, the study involves identifying latent variables by addressing inter-correlations among several adoption determinants. The results show that rooftop solar and EV charger adoptions in Seattle present disparities associated with geographic locations and community attributes. In particular, housing variables are the main indicators for rooftop solar adoption and even stronger in communities with low adoption rates. EV charger adoptions are strongly associated with economic variables. Furthermore, spatial inequality of rooftop solar adoption is higher than that of EV charger adoption. The study suggests housing-related support may increase the adoption of both technologies, particularly in communities with low adoption rates. Considering that the installations of rooftop solar and EV chargers were concentrated in particular communities, the study results imply that policies aimed at increasing the adoption of DERs should be tailored to local community characteristics.

Characterization of Vulnerable Communities in Terms of the Benefits and Burdens of the Energy Transition in Pacific Northwest Cities

Min, Yohan; Lee, Hyun Woo. (2023). Characterization of Vulnerable Communities in Terms of the Benefits and Burdens of the Energy Transition in Pacific Northwest Cities. Journal of Cleaner Production.

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Abstract

Energy transition to renewable sources has occurred along with the development of various clean energy policies aimed at decarbonization and electrification. However, the transition can inadvertently lead to social inequity resulting in increasing burdens on vulnerable communities. Although many studies have tried to define and identify vulnerable communities, there has been no study specifically aimed at characterizing vulnerable communities in terms of the benefits and burdens of such energy transition. In response, the objective of this study is to characterize vulnerable communities by examining rooftop solar adoption and energy expenditure using spatial and mixed-effect models. Rooftop solar adoption operationalizes energy resilience and benefits, and energy expenditure operationalizes energy dependence and burdens of the transition. The study also investigates the link between rooftop solar adoption and energy expenditure by considering city-level variability in three Pacific Northwest cities. The results show that Bellevue has 50.4% less rooftop solar adoption than Portland, while Portland has 16.1% or $223 more energy expenditure than Seattle. On average, an increase in annual energy expenditure of $431 is associated with 29% increase in rooftop solar adoption, specifically Bellevue, Seattle, and Portland by 21.4%, 39.1%, and 26.2%, respectively, but not vice versa. Furthermore, the group of communities more vulnerable in housing attributes has 15.2% less rooftop solar adoption than the group of more vulnerable communities in socioeconomic attributes. In addition, the city centers, commercial areas, or mid-rise and high-rise zones are found to have lower rooftop solar adoption and energy expenditure than other areas. The results suggest that policymakers should consider between-city variability when identifying vulnerable communities. Policies should also be tailored to local communities based on their attributes as communities with similar attributes tend to cluster together. Furthermore, policymakers should focus more on housing and built environment attributes to promote resilient communities.

Use of Predictive Models for Labor-Productivity Loss in Settling Disputes

Ottesen, Jeffrey L., & Migliaccio, Giovanni (2023). Use of Predictive Models for Labor-Productivity Loss in Settling Disputes. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, 15(1).

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Abstract

Given inherent difficulties in construction, optimizing labor efficiencies is paramount to project success. Research described in this article conducted demonstrates that an analysis of planned activities in a critical path methodology (CPM) schedule may be used to forecast future productivity inefficiencies. Specifically, this study relies on the concept of CPM schedule’s density, which is defined as the number of overlapping like-trade activities on any given workday. This metric is directly related to the required labor resources required to complete that work within the activities’ planned durations. Schedule density increases where more planned activities overlap with each other; for instance, occurrence of such increases is common when the schedule is accelerated. Regression models were derived using metrics drawn from CPM schedule updates’ activities and durations and compared to actual labor productivity experienced. Strong correlation findings support development of predictive models that quantify potential labor inefficiencies before they occur. However, the question remains as to the strength and applicability of predictive models in formal litigation. This paper presents findings of this research and discusses how such findings may be used to facilitate settlement in dispute resolution procedures.