Berke, Ethan M.; Vernez-Moudon, Anne. (2014). Built Environment Change: A Framework to Support Health-Enhancing Behaviour through Environmental Policy and Health Research. Journal Of Epidemiology And Community Health, 68(6), 586 – 590.
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Abstract
As research examining the effect of the built environment on health accelerates, it is critical for health and planning researchers to conduct studies and make recommendations in the context of a robust theoretical framework. We propose a framework for built environment change (BEC) related to improving health. BEC consists of elements of the built environment, how people are exposed to and interact with them perceptually and functionally, and how this exposure may affect health-related behaviours. Integrated into this framework are the legal and regulatory mechanisms and instruments that are commonly used to effect change in the built environment. This framework would be applicable to medical research as well as to issues of policy and community planning.
Keywords
Geographic Information-systems; Physical-activity; Obesity; Place; Associations; Walkability; Risk; Care
Hurvitz, Philip M.; Moudon, Anne V.; Kang, Bumjoon; Fesinmeyer, Megan D.; Saelens, Brian E. (2014). How Far from Home? The Locations of Physical Activity in an Urban US Setting. Preventive Medicine, 69, 181 – 186.
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Abstract
Little is known about where physical activity (PA) occurs, or whether different demographic groups accumulate PA in different locations. Method. Objective data on PA and location from 611 adults over 7 days were collected in King County, WA in 2008-2009. The relative amounts of time spent in sedentary-to-low and moderate-to-vigorous PA (MVPA) were quantified at three locations: home (1666 m). Differences in MVPA by demographics and location were examined. The percent of daily time in MVPA was estimated using a mixed model adjusted for location, sex, age, race/ethnicity, employment, education, BMI, and income. Results. Most MVPA time occurred in nonhome locations, and disproportionately near home; this location was associated with 16.46% greater time in MVPA, compared to at-home activity (p< 0.001), whereas more time spent at away locations was associated with 3.74% greater time in MVPA (p< 0.001). Location was found to be a predictor of MVPA independent of demographic factors. Conclusion. A large proportion of MVPA time is spent at near locations, corresponding to the home neighborhood studied in previous PA research. Away locations also host time spent in MVPA and should be the focus of future research. (C) 2014 Elsevier Inc All rights reserved.
Keywords
Accelerometer Data; Built Environment; United-states; Neighborhood Walkability; Exercise Intensity; Time Use; Land-use; Walking; Health; Behavior; Physical Activity; Objective Measurement; Gps; Accelerometry; Gis
Zhang, Su; Migliaccio, Giovanni C.; Zandbergen, Paul A.; Guindani, Michele. (2014). Empirical Assessment of Geographically Based Surface Interpolation Methods for Adjusting Construction Cost Estimates by Project Location. Journal Of Construction Engineering And Management, 140(6).
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Keywords
Construction; Interpolation; Project Management; Geographically Based Surface Interpolation Methods; Construction Cost Estimates; Project Location; Construction Projects; Proximity-based Interpolation; Location Factor; Proximity-based Method; Global Spatial Autocorrelation; Cost Index Databases; Cost Estimators; Spatial Interpolation Techniques; Conditional Nearest Neighbor; Cnn; Inverse Distance Weighted; Idw Methods; Spatial Prediction Models; Distance Weighted Interpolation; Spatial Interpolation; Kriging Method; Precipitation; Temperature
Kim, Sang-chul; Kim, Yong-woo; Park, Kun Soo; Yoo, Choong-yuel. (2015). Impact of Measuring Operational-Level Planning Reliability on Management-Level Project Performance. Journal Of Management In Engineering, 31(5).
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Abstract
The earned value management system (EVMS) and the last planner system (LPS) have been widely used as effective performance measurement tools for construction managers and production units at construction projects. While the EVMS measures project-level costs and scheduling performances, the LPS measures the percent plan complete (PPC), which indicates the level of planning reliability. This paper investigates the relationship between planning reliability at the operational level and project performance at the management level (i.e., the success or failure of a project). Analyzing the empirical data of 23 residential projects of a large construction company, the authors find that, while the production plan in the weekly schedule is correlated rigidly with the daily plan in successful projects, such a rigid correlation is not observed in unsuccessful projects. To understand this finding, the authors further conducted interviews with project stakeholders. Taken together, this study suggests that an emphasis on LPS indices causes subcontractors to engage in myopic behaviors such as modifying operational-level indices. Consequently, management-level production plan rigidity is at risk. The findings in this paper offer valuable insights and help project stakeholders understand the attributes of operational-level and management-level indices and their relationships. (C) 2014 American Society of Civil Engineers.
Keywords
Construction Industry; Costing; Production Planning; Project Management; Reliability; Scheduling; Subcontracting; Construction Projects; Production Units; Myopic Behaviors; Project Stakeholders; Subcontractors; Production Plan; Percent Plan Completion; Scheduling Performances; Project-level Costs; Performance Measurement Tools; Construction Managers; Last Planner System; Earned Value Management System; Management-level Project Performance; Evms; Operational-level Planning Reliability; Balanced Scorecard; Lean Construction; Contractors; Indexes; Design; Model; Earned Value; Lean; Construction; Schedule Performance Index; Cost Performance Index; Percent-plan-completion; Empirical Analysis
Choi, Kunhee; Lee, Hyun Woo. (2016). Deconstructing the Construction Industry: A Spatiotemporal Clustering Approach to Profitability Modeling. Journal Of Construction Engineering And Management, 142(10).
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Abstract
In spite of the strong influence of the construction industry on the national health of the United States' economy, very little research has specifically aimed at evaluating the key performance parameters and trends (KPPT) of the industry. Due to this knowledge gap, concerns have been constantly raised over lack of accurate measures of KPPT. To circumvent these challenges, this study investigates and models the macroeconomic KPPT of the industry through spatiotemporal clustering modeling. This study specifically aims to analyze the industry in 14 of its subsectors and subsequently, by 51 geographic spatial areas at a 15-year temporal scale. KPPT and their interdependence were firstly examined by utilizing the interpolated comprehensive U.S. economic census data. A hierarchical spatiotemporal clustering analysis was then performed to create predictive models that can reliably determine firm's profitability as a function of the key parameters. Lastly, the robustness of the predictive models was tested by a cross-validation technique called the predicted error sum of square. This study yields a notable conclusion that three key performance parameterslabor productivity, gross margin, and labor wageshave steadily improved over the study period from 1992 to 2007. This study also reveals that labor productivity is the most critical factor; the states and subsectors with the highest productivity are the most profitable. This study should be of value to decision-makers when plotting a roadmap for future growth and rendering a strategic business decisions.
Keywords
Construction Industry; Decision Making; Knowledge Management; Labour Resources; Macroeconomics; Organisational Aspects; Productivity; Profitability; Salaries; Statistical Analysis; Strategic Planning; Hierarchical Spatiotemporal Clustering Approach; National Health; Macroeconomic Kppt; Knowledge Gap; Spatiotemporal Clustering Modeling; Interpolated Comprehensive U.s. Economic Census Data; Parameters-labor Productivity; Gross Margin; Labor Wages; Strategic Business Decisions; Deconstructing; Key Performance Parameters And Trends; Firms Profitability; Error Sum Of Square; Labor Productivity; Projects; Firms; Performance; Performance Measurement; Cluster Analysis; Economic Census; Project Planning And Design
Hwang, Liang-dar; Hurvitz, Philip M.; Duncan, Glen E. (2016). Cross Sectional Association between Spatially Measured Walking Bouts and Neighborhood Walkability. International Journal Of Environmental Research And Public Health, 13(4).
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Abstract
Walking is the most popular choice of aerobic physical activity to improve health among U.S. adults. Physical characteristics of the home neighborhood can facilitate or hinder walking. The purpose of this study was to quantify neighborhood walking, using objective methods and to examine the association between counts of walking bouts in the home neighborhood and neighborhood walkability. This was a cross-sectional study of 106 adults who wore accelerometers and GPS devices for two weeks. Walking was quantified within 1, 2, and 3 km Euclidean (straight-line) and network buffers around the geocoded home location. Walkability was estimated using a commercially available index. Walking bout counts increased with buffer size and were associated with walkability, regardless of buffer type or size (p < 0.001). Quantification of walking bouts within (and outside) of pre-defined neighborhood buffers of different sizes and types allowed for the specification of walking locations to better describe and elucidate walking behaviors. These data support the concept that neighborhood characteristics can influence walking among adults.
Keywords
Physical-activity; Accelerometer Data; United-states; Urban Form; Land-use; Validation; Health; Transportation; Environments; Intensity; Geographic Information Systems; Residence Characteristics; Twins; Walking
Pan, Haixiao; Li, Jing; Chen, Peng. (2016). Study on the Ownership of Motorized and Non-Motorized Vehicles in Suburban Metro Station Areas: A Structural Equation Approach. Urban Rail Transit, 2(2), 47 – 58.
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Abstract
As Chinese megacities are experiencing a large-scale motorization and suburbanization, an ever greater number of households are relocated to suburban towns. The increasing average travel distance surely encourages car growth. China is now the world's largest car consumer, resulting in a series of unforeseen environmental and public health issues. On the other hand, scooters, electric bikes, and motorcycles become attractive options to substitute non-motorized bicycles. The ongoing demographic changes should also be taken in account. China has a rapidly aging population and a higher birth rate following reforms to the one-child policy allowing couples to have a second child. These changes will lead to a dramatic alteration of the household composition in the near future. Under above emerging contexts, this study aims to understand what implies the ownership of motorized and non-motorized vehicles in suburban metro station areas by means of a structural equation model. The data employed in this study are based on a household survey collected from three neighborhoods in Shanghai suburban metro station areas in 2010. The major findings include: (1) Income is a decisive element in car ownership. Specifically, high-income households have higher propensity to own a car, while middle and poor income families tend to own scooters, electric bikes, motorcycles, or bicycles. (2) Workplace built environment features or mode preferences are not essential to understanding vehicle ownership in Chinese context. (3) Stem families are more likely to own cars; the presence of a child or a senior family member increases the probability of owning a car by enlarging the household. (4) The results estimated for core family and DINK (couple with no child) family are highly consistent, and these families are less likely to own cars. Therefore, transport policies may focus more on households. Providing safe, pleasant, and efficient pedestrian and bicycle paths for children and seniors may decrease the attractiveness of owning cars.
Keywords
Suburban Metro Station Areas; Ownership Of Motorized And Non-motorized Vehicles; Built Environment; Mode Preferences; Family Composition; Structural Equation Model
Anderson, Anne; Dossick, Carrie Sturts; Iorio, Josh; Taylor, John E. (2017). The Impact of Avatars, Social Norms and Copresence on the Collaboration Effectiveness of AEC Virtual Teams. Journal Of Information Technology In Construction, 22, 287 – 304.
Abstract
A growing number of architecture, engineering, and construction (AEC) firms are outsourcing complex design and construction work to international vendors. Due to the significant geographic distances that can separate project team members in global design networks, much of this work is executed in virtual teams, defined as teams composed of geographically separated members who collaborate to accomplish organizational tasks mediated by technology. The challenges of working in geographically distributed networks have prompted the development of alternative, virtual workspaces. Questions remain on how these virtual workspaces support or hinder collaborative work. People are social beings that rely on body language and other non-verbal cues to communicate. What happens to team formation and collaborative effectiveness when non-verbal cues are mediated through avatar actions? In this paper, qualitative ethnographic data collected over four years from studies conducted in a 3D virtual world are used to examine collaboration effectiveness of global virtual engineering project teams. We found that avatar movement and position was effective at communicating nonverbal information, even when done so unintentionally. Avatar actions that map to established social norms in the physical world results in more efficient communication. Collaboration was also enhanced when gesture bubbles were used for backchannel communication and when text chat was used to avoid interrupting voice communication. We found collaboration was hindered when the learning curve was too steep for participants to adapt to tool use or avatar actions in the environment. These findings have important implications for the future of collaboration in virtual environments, particularly in the AEC industry where 3D models can be imported into the virtual environment and explored synchronously by a project team.
Keywords
Architectural Design; Human Resource Management; International Trade; Bim Coordination; Collaboration Technology; Distributed Teams; Social Norm; Virtual Worlds; Communication; Design; Technology; Dimensions; Teamwork; Behavior; Collaboration Technologies; Social Norms
James, Peter; Hart, Jaime E.; Hipp, J. Aaron; Mitchell, Jonathan A.; Kerr, Jacqueline; Hurvitz, Philip M.; Glanz, Karen; Laden, Francine. (2017). GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity. Cancer Epidemiology Biomarkers & Prevention, 26(4), 525 – 532.
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Abstract
Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity. Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minutelevel epochs. GPS records were linked to 250mresolution satellitebased vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations fromlinearity using splines. Results: Among 360 adult women (mean age of 55.3 +/- 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged. Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability. Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. (C) 2017 AACR.
Keywords
Built Environments; Health Research; Breast-cancer; Obesity; Neighborhood; Validation; Validity; Walking; Risk; Energetics
Zhang, Su; Bogus, Susan M.; Lippitt, Christopher D.; Migliaccio, Giovanni C. (2017). Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery. Journal Of Construction Engineering And Management, 143(1).
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Abstract
A fundamental process in construction cost estimation is the appropriate adjustment of costs to reflect project location. Unfortunately, location adjustment factors are not available for all locations. To overcome this lack of data, cost estimators in the United States often use adjustment factors from adjacent locations, referred to as the nearest neighbor (NN) method. However, these adjacent locations may not have similar economic conditions, which limit the accuracy of the NN method. This research proposes a new method of using nighttime light satellite imagery (NLSI) to estimate location adjustment factors where they do not exist. The NLSI method for estimating location adjustment factors was evaluated against an established cost index database, and results show that NLSI can be used to effectively estimate location adjustment factors. When compared with NN and other alternative proximity-based location adjustment methods, the proposed NLSI method leads to a 25-40% reduction of the median absolute error. This work contributes to the body of knowledge by introducing a more accurate method for estimating location adjustment factors which can improve cost estimates for construction projects where location adjustment factors do not currently exist. (C) 2016 American Society of Civil Engineers.
Keywords
Construction Industry; Costing; Industrial Economics; Project Management; Remote Sensing; Location-adjustment Factors; Nighttime Light Satellite Imagery; Construction Cost Estimation; Project Location; United States; Economic Conditions; Nlsi Method; Cost Index Database; Median Absolute Error Reduction; Construction Projects; Nearest Neighbor Method; Urbanization Dynamics; Proxy; Construction Costs; Estimation; Construction Management; Pricing; Cost And Schedule