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Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers

Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.

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Abstract

This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.

Keywords

Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis

Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers

Cheng, Tao; Migliaccio, Giovanni C.; Teizer, Jochen; Gatti, Umberto C. (2013). Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers. Journal Of Computing In Civil Engineering, 27(3), 320 – 335.

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Abstract

Previous research and applications in construction resource optimization have focused on tracking the location of material and equipment. There is a lack of studies on remote monitoring for improving safety and health of the construction workforce. This paper presents a new approach for monitoring ergonomically safe and unsafe behavior of construction workers. The study relies on a methodology that utilizes fusion of data from continuous remote monitoring of construction workers' location and physiological status. To monitor construction workers activities, the authors deployed nonintrusive real-time worker location sensing (RTLS) and physiological status monitoring (PSM) technology. This paper presents the background and need for a data fusion approach, the framework, the test bed environment, and results to some case studies that were used to automatically identify unhealthy work behavior. Results of this study suggest a new approach for automating remote monitoring of construction workers safety performance by fusing data on their location and physical strain. DOI: 10.1061/(ASCE)CP.1943-5487.0000222. (C) 2013 American Society of Civil Engineers.

Keywords

Civil Engineering Computing; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Personnel; Sensor Fusion; Psm Technology; Rtls Technology; Construction Workforce Health; Construction Workforce Safety; Equipment Location; Material Location; Construction Resource Optimization; Construction Worker; Ergonomics Analysis; Physiological Status Monitoring; Realtime Location Sensing; Data Fusion; Exposure; Tracking; Demands; Sensors; System; Construction Worker Behavior; Remote Location Sensing; Work Sampling; Workforce Safety And Health

GPS or Travel Diary: Comparing Spatial and Temporal Characteristics of Visits to Fast Food Restaurants and Supermarkets

Scully, Jason Y.; Moudon, Anne Vernez; Hurvitz, Philip M.; Aggarwal, Anju; Drewnowski, Adam. (2017). GPS or Travel Diary: Comparing Spatial and Temporal Characteristics of Visits to Fast Food Restaurants and Supermarkets. Plos One, 12(4).

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Abstract

To assess differences between GPS and self-reported measures of location, we examined visits to fast food restaurants and supermarkets using a spatiotemporal framework. Data came from 446 participants who responded to a survey, filled out travel diaries of places visited, and wore a GPS receiver for seven consecutive days. Provided by Public Health Seattle King County, addresses from food permit data were matched to King County tax assessor parcels in a GIS. A three-step process was used to verify travel-diary reported visits using GPS records: (1) GPS records were temporally matched if their timestamps were within the time window created by the arrival and departure times reported in the travel diary; (2) the temporally matched GPS records were then spatially matched if they were located in a food establishment parcel of the same type reported in the diary; (3) the travel diary visit was then GPS-sensed if the name of food establishment in the parcel matched the one reported in the travel diary. To account for errors in reporting arrival and departure times, GPS records were temporally matched to three time windows: the exact time, +/-10 minutes, and +/-30 minutes. One third of the participants reported 273 visits to fast food restaurants; 88% reported 1,102 visits to supermarkets. Of these, 77.3 percent of the fast food and 78.6 percent supermarket visits were GPS-sensed using the +/-10-minute time window. At this time window, the mean travel-diary reported fast food visit duration was 14.5 minutes (SD 20.2), 1.7 minutes longer than the GPS-sensed visit. For supermarkets, the reported visit duration was 23.7 minutes (SD 18.9), 3.4 minutes longer than the GPS-sensed visit. Travel diaries provide reasonably accurate information on the locations and brand names of fast food restaurants and supermarkets participants report visiting.

Keywords

Global Positioning System; Fast Food Restaurants; Self-evaluation; Public Health; Supermarkets; Geoinformatics; Comparative Studies; Biology And Life Sciences; Computer And Information Sciences; Diet; Earth Sciences; Eating; Engineering And Technology; Food; Food Consumption; Geographic Information Systems; Geography; Medicine And Health Sciences; Nutrition; Physiological Processes; Physiology; Public And Occupational Health; Research And Analysis Methods; Research Article; Research Design; Survey Research; Surveys; Transportation; Global Positioning Systems; Environment; Neighborhood; Exposure; Health; Consumption; Tracking; Adults; Associations; Dietary

Measuring the Urban Forms of Shanghai’s City Center and Its New Districts: A Neighborhood-Level Comparative Analysis

Lin, Lin; Chen, Xueming (Jimmy); Moudon, Anne Vernez. (2021). Measuring the Urban Forms of Shanghai’s City Center and Its New Districts: A Neighborhood-Level Comparative Analysis. Sustainability, 13(15).

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Abstract

Rapid urban expansion has radically transformed the city centers and the new districts of Chinese cities. Both areas have undergone unique redevelopment and development over the past decades, generating unique urban forms worthy of study. To date, few studies have investigated development patterns and land use intensities at the neighborhood level. The present study aims to fill the gap and compare the densities of different types of developments and the spatial compositions of different commercial uses at the neighborhood level. We captured the attributes of their built environment that support instrumental activities of daily living of 710 neighborhoods centered on the public elementary schools of the entire Shanghai municipality using application programming interfaces provided in Baidu Map services. The 200 m neighborhood provided the best fit to capture the variations of the built environment. Overall, city center neighborhoods had significantly higher residential densities and housed more daily routine destinations than their counterparts in the new districts. Unexpectedly, however, the total length of streets was considerably smaller in city-center neighborhoods, likely reflecting the prominence of the wide multilane vehicular roads surrounding large center city redevelopment projects. The findings point to convergence between the city center's urban forms and that of the new districts.

Keywords

Quantifying Spatiotemporal Patterns; Fast-food Restaurants; Instrumental Activities; Physical-activity; Chinese Cities; Land; Schools; Redevelopment; Expansion; Transformation; Built Environment; Planning; Neighborhood; Urban Form; Shanghai

College of Built Environments’ unique Inspire Fund aims to foster research momentum in underfunded pursuits college-wide. And it’s working.

Launching the Inspire Fund: An early step for CBE’s Office of Research “For a small college, CBE has a broad range of research paradigms, from history and arts, to social science and engineering.” — Carrie Sturts Dossick, Associate Dean of Research Upon taking on the role of Associate Dean of Research, Carrie Sturts Dossick, professor in the Department of Construction Management, undertook listening sessions to learn about the research needs of faculty, staff and students across the College of Built…

Bo Jung

I am interested in developing analysis methods and metrics for accurate daylight analysis. More concretely, I would like to work on developing color accurate sky models through analyzing HDR photographs, and to integrate it to annual daylight simulation method. Additionally, I am also interested in integration of daylight simulation in environmental design.

Julie Kriegh and collaborators launch studio booklet based on their work with Google

Julie Kriegh, researcher with the Carbon Leadership Forum and other CBE research centers, and owner of Kriegh Architecture Studios, collaborated with other CBE faculty and external partners to lead a UW CBE studio course in collaboration with Google that developed and delivered a design proposal for a sustainable data center. CBE collaborators included Hyun Woo “Chris” Lee, P.D. Koon Professorship in Construction Management; Jan Whittington, Associate Professor of the Department of Urban Design and Planning, and Director of the Urban…

Tianqi Zou

Sustainable transportation, travel behavior, GIS, geospatial big data

Michael Tobey

Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems

Mingming Cai

Emerging transportation technologies, shared mobility and land use, interaction between human mobility based on shared vehicles and urban land uses. Spatio-temporal analysis and big data. Smart visualization methods