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.
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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.
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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).
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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.
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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
Won, Jongsung; Lee, Ghang; Dossick, Carrie; Messner, John. (2013). Where to Focus for Successful Adoption of Building Information Modeling within Organization. Journal Of Construction Engineering And Management, 139(11).
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Abstract
Suggestions abound for successful adoption of building information modeling (BIM); however, a company with limited resources cannot adopt them all. The factors that have top management priority for successful accomplishment of a task are termed critical success factors (CSFs). This paper aims to derive the CSFs for four questions commonly asked by companies in the first wave of BIM adoption: (1)What are the CSFs for adopting BIM in a company? (2)What are the CSFs for selecting projects to deploy BIM? (3)What are the CSFs for selecting BIM services? (4)What are the CSFs for selecting company-appropriate BIM software applications? A list of consideration factors was collected for each question, based on a literature review, and then refined through face-to-face interviews based on experiences of BIM experts. An international survey was conducted with leading BIM experts. From the 206 distributed surveys, 52 responses from four continents were collected. This study used quantitative data analysis to derive a manageable number (4-10) of CSFs for each category from dozens of anecdotal consideration factors. The derived CSFs are expected to be used as efficient metrics for evaluating and managing the level of BIM adoption and as a basis for developing BIM evaluation models in the future.
Keywords
Architectural Cad; Building Information Modeling; Bim; Critical Success Factors; Csf; Management; Building Information Models; Organizations; Computer Software; Building Information Modeling (bim); Critical Success Factor (csf); Organizational Strategy; Bim Software Application; Bim Service; Bim-assisted Project; Information Technologies
Liang, Huakang; Lin, Ken-yu; Zhang, Shoujian. (2018). Understanding The Social Contagion Effect Of Safety Violations Within A Construction Crew: A Hybrid Approach Using System Dynamics And Agent-based Modeling. International Journal Of Environmental Research And Public Health, 15(12).
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Abstract
Previous research has recognized the importance of eliminating safety violations in the context of a social group. However, the social contagion effect of safety violations within a construction crew has not been sufficiently understood. To address this deficiency, this research aims to develop a hybrid simulation approach to look into the cognitive, social, and organizational aspects that can determine the social contagion effect of safety violations within a construction crew. The hybrid approach integrates System Dynamics (SD) and Agent-based Modeling (ABM) to better represent the real world. Our findings show that different interventions should be employed for different work environments. Specifically, social interactions play a critical role at the modest hazard levels because workers in this situation may encounter more ambiguity or uncertainty. Interventions related to decreasing the contagion probability and the safety-productivity tradeoff should be given priority. For the low hazard situation, highly intensive management strategies are required before the occurrence of injuries or accidents. In contrast, for the high hazard situation, highly intensive proactive safety strategies should be supplemented by other interventions (e.g., a high safety goal) to further control safety violations. Therefore, this research provides a practical framework to examine how specific accident prevention measures, which interact with workers or environmental characteristics (i.e., the hazard level), can influence the social contagion effect of safety violations.
Keywords
Risk-taking; Coworker Support; Employee Safety; Job Demands; Work Groups; Behavior; Climate; Impact; Performance; Simulation; Social Contagion Effect; Routine Safety Violations; Situational Safety Violations; System Dynamics; Agent-based Simulation; Research; Violations; Modelling; Accident Prevention; Social Factors; Safety; Organizational Aspects; Occupational Safety; Construction; Influence; Construction Accidents & Safety; Workers; Safety Management; Information Processing; Construction Industry; Hybrid Systems; Social Interactions; Cognitive Ability; Human Error; Accident Investigations
Rhew, Isaac C.; Hurvitz, Philip M.; Lyles-riebli, Rose; Lee, Christine M. (2022). Geographic Ecological Momentary Assessment Methods to Examine Spatio-temporal Exposures Associated with Marijuana Use Among Young Adults: A Pilot Study. Spatial And Spatio-temporal Epidemiology, 41.
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Abstract
Background: This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users. Method: Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time. Results: Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1). Conclusions: GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.
Keywords
Geographic Ecological Momentary Assessment; Spatio-temporal Factors; Marijuana; Young Adults; Geographic Information System; Poverty; Substance Use; Alcohol; Tracking
Hong, Jinhyun; Shen, Qing; Zhang, Lei. (2014). How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales. Transportation, 41(3), 419 – 440.
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Abstract
Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor-if any-influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.
Keywords
Land-use; Urban Form; Multilevel Models; Physical-activity; Neighborhood; Choice; Impact; Specification; Accessibility; Causation; Built Environment; Travel Behavior; Self-selection; Spatial Autocorrelation; Bayesian Hierarchical Model
Liang, Huakang; Lin, Ken-yu; Zhang, Shoujian; Su, Yikun. (2018). The Impact Of Coworkers’ Safety Violations On An Individual Worker: A Social Contagion Effect Within The Construction Crew. International Journal Of Environmental Research And Public Health, 15(4).
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Abstract
This research developed and tested a model of the social contagion effect of coworkers' safety violations on individual workers within construction crews. Both situational and routine safety violations were considered in this model. Empirical data were collected from 345 construction workers in China using a detailed questionnaire. The results showed that both types of safety violations made by coworkers were significantly related to individuals' perceived social support and production pressure. Individuals' attitudinal ambivalence toward safety compliance mediated the relationships between perceived social support and production pressure and both types of individuals' safety violations. However, safety motivation only mediated the effects of perceived social support and production pressure on individuals' situational safety violations. Further, this research supported the differences between situational and routine safety violations. Specifically, we found that individuals were more likely to imitate coworkers' routine safety violations than their situational safety violations. Coworkers' situational safety violations had an indirect effect on individuals' situational safety violations mainly through perceived social support and safety motivation. By contrast, coworkers' routine safety violations had an indirect effect on individuals' routine safety violations mainly through perceived production pressure and attitudinal ambivalence. Finally, the theoretical and practical implications, research limitations, and future directions were discussed.
Keywords
Health-care Settings; Job Demands; Attitudinal Ambivalence; Industry Development; Workplace Safety; Behavior; Climate; Model; Risk; Employee; Social Contagion; Situational Safety Violations; Routine Safety Violations; Social Learning; Social Information Processing
Kim, Taehoon; Kim, Yong-woo; Lee, Dongmin; Kim, Minju. (2022). Reinforcement Learning Approach To Scheduling Of Precast Concrete Production. Journal Of Cleaner Production, 336.
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Abstract
The production scheduling of precast concrete (PC) is essential for successfully completing PC construction projects. The dispatching rules, widely used in practice, have the limitation that the best rule differs according to the shop conditions. In addition, mathematical programming and the metaheuristic approach, which would improve performance, entail more computational time with increasing problem size, let alone its models being revised as the problem size changes. This study proposes a PC production scheduling model based on a reinforcement learning approach, which has the advantages of a general capacity to solve various problem conditions with fast computation time and good performance in real-time. The experimental study shows that the proposed model outperformed other methods by 4-12% of the total tardiness and showed an average winning rate of 77.0%. The proposed model could contribute to the successful completion of off-site construction projects by supporting the stable progress of PC construction.
Keywords
Precast Concrete; Reinforcement Learning; Deep Q -network; Production Scheduling; Minimize; Model