Zhang, Zhenyu; Lin, Ken-yu; Lin, Jia-hua. (2022). 2safe: A Health Belief Model-integrated Framework For Participatory Ergonomics. Theoretical Issues In Ergonomics Science, 1 – 18.
View Publication
Abstract
Abstract Initiating ergonomics interventions in a business environment requires changes in the behaviour of relevant actors. When participating in an intervention, researchers need to collect and share information with practitioners to help them make better behaviour-related decisions. This paper describes the five-step 2SAFE (Surveillance, Screening, Assessment, Framing, and Evaluation) planning framework, which can be used to guide research-practice collaboration in participatory ergonomics programmes. This framework combines the understanding of work-related musculoskeletal disorders with the principles of the health belief model. This theoretical synthesis empowers the framework to address the following critical challenges: (1) how to make data collection processes attuned to the nature of ergonomic injuries; and (2) how to transform the data collected into immediately usable information for practitioners to change their behaviours. The framework is interdisciplinary and can facilitate transfer of knowledge between ergonomics and health behaviour science. The framework can enhance the ability of researchers to collaborate with practitioners and bring participatory ergonomics programmes closer to success. In the long term, we hope that this framework can lead to more high-quality interventions that are able to prevent work-related musculoskeletal disorders in various industrial settings. [ABSTRACT FROM AUTHOR]; Copyright of Theoretical Issues in Ergonomics Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Health Belief Model; Intervention Programme; Participatory Ergonomics; Planning Framework; Work-related Musculoskeletal Disorders
Migliaccio, Giovanni C.; Guindani, Michele; D’Incognito, Maria; Zhang, Linlin. (2013). Empirical Assessment of Spatial Prediction Methods for Location Cost-Adjustment Factors. Journal Of Construction Engineering & Management, 139(7), 858 – 869.
View Publication
Abstract
In the feasibility stage of a project, location cost-adjustment factors (LCAFs) are commonly used to perform quick order-of-magnitude estimates. Nowadays, numerous LCAF data sets are available in North America, but they do not include all locations. Hence, LCAFs for unsampled locations need to be inferred through spatial interpolation or prediction methods. Using a commonly used set of LCAFs, this paper aims to test the accuracy of various spatial prediction methods and spatial interpolation methods in estimating LCAF values for unsampled locations. Between the two regression-based prediction models selected for the study, geographically weighted regression analysis (GWR) resulted the most appropriate way to model the city cost index as a function of multiple covariates. As a direct consequence of its spatial nonstationarity, the influence of each single covariate differed from state to state. In addition, this paper includes a first attempt to determine if the observed variability in cost index values could be at least partially explained by independent socioeconomic variables. (C) 2013 American Society of Civil Engineers.
Keywords
Construction Industry; Interpolation; Regression Analysis; Socio-economic Effects; Spatial Prediction Methods; Location Cost-adjustment Factors; Empirical Assessment; Lcaf; Order-of-magnitude Estimates; North America; Unsampled Locations; Spatial Interpolation Methods; Geographically Weighted Regression Analysis; Gwr; Independent Socioeconomic Variables; Inflation; Indexes; Estimation; Geostatistics; Construction Costs; Planning; Budgeting
Kim, Jonghyeob; Lee, Hyun Woo; Bender, William; Hyun, Chang-taek. (2018). Model for Collecting Replacement Cycles of Building Components: Hybrid Approach of Indirect and Direct Estimations. Journal Of Computing In Civil Engineering, 32(6).
View Publication
Abstract
Building maintenance, repair, and replacement (MR&R) costs are estimated to be two to three times larger than initial construction costs. Thus, it is important to accurately estimate and manage MR&R costs in the planning phase and/or design phase of a construction project based on life cycle cost analysis (LCCA). However, the nature of LCCA requires making necessary assumptions for the prediction and analysis of MR&R costs, and the reliability of the assumptions greatly impacts LCCA results. In particular, determining reasonable replacement cycles is especially important given that each replacement typically involves a significant amount of capital. However, conventional approaches largely focus on either collecting component-specific replacement cases or surveying expert opinions, both of which reduce the usability and reliability of replacement cycle data at an early stage. To overcome these limitations, this study aims to develop a replacement cycle collection model that can expedite the data collection by combining indirect estimations with direct estimations. The development of the model involves collecting replacement cases, developing replacement cycle and index estimation methods, and developing an algorithm to implement the suggested model. As a validation, the applicability and effectiveness of the model were illustrated and tested by using simulated cases based on 21 real-world facilities. This study makes a theoretical contribution to the body of knowledge by developing a replacement cycle data collection model based on long-term and macro perspectives. The developed model will also be of value to practitioners when they try to improve the reliability of their LCCA.
Keywords
Buildings (structures); Life Cycle Costing; Maintenance Engineering; Structural Engineering; Building Components; Building Maintenance; Planning Phase; Design Phase; Construction Project; Life Cycle Cost Analysis; Replacement Cycle Data Collection Model; Construction Costs; Lcca; Maintenance Repair And Replacement Cost; Service Life Prediction; Repair; Replacement; Replacement Cycles; Replacement Index; Database; Indirect Estimations
Hall, Joshua C.; Lacombe, Donald J.; Neto, Amir; Young, James. (2022). Bayesian Estimation of the Hierarchical SLX Model with an Application to Housing Markets. Journal Of Economics & Finance, 46(2), 360 – 373.
View Publication
Abstract
Hierarchical or multilevel models have long been used in hedonic models to delineate housing submarket boundaries in order to improve model accuracy. School districts are one important delineator of housing submarkets in an MSA. Spatial hedonic models have been extensively employed to deal with unobserved spatial heterogeneity and spatial spillovers. In this paper, we develop the spatially lagged X (or SLX) hierarchical model to integrate these two approaches to better understanding local housing markets. We apply the SLX hierarchical model to housing and school district test score data from Cincinnati Ohio. Our results highlight the importance of accounting for spatial spillovers and the fact that houses are embedded in school districts which vary in quality. [ABSTRACT FROM AUTHOR]; Copyright of Journal of Economics & Finance is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Housing Market; Multilevel Models; Test Scoring; Cincinnati (ohio); Ohio; Bayesian Methods; Slx Model; Spatial Econometrics; Spatial Hierarchical Models
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…
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, 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…
Sustainable transportation, travel behavior, GIS, geospatial big data
Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems
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