Gu, Naeun. (2020). Korean Apartment Complexes and Social Relationships of the Residents. Housing Studies, 35(8), 1362 – 1389.
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Abstract
Korean apartment housing, where more than half of the population lives, has drawn attention with its spatial, historical, and cultural uniqueness. Among many questions on Korean apartments, this article explains how the socio-spatial characteristics of apartment housing have impacts on the social relationships among the residents. This article first analyses the historical, socio-cultural, and spatial characteristics of Korean apartments, and then synthesizes up-to-date empirical study results to examine how the diverse characteristics can be associated with the residents' social relations. The empirical evidence clarifies the effects of Korean apartments' characteristics on residents' social relations-the exclusive complex design, spatial configurations, shared spaces including community facilities, heights of the units, public/private housing types, social homogeneity, and community programs are all associated with social relations of the residents. Key methodological problems in current studies as well as implications for future apartment planning are highlighted.
Keywords
Housing; Homogeneity; Shared Space (traffic Engineering); Empirical Research; Sociocultural Theory; High-rise High-density; Korean Apartments; Residents; Social Relationships; Socio-spatial Characteristics; Built Environment; South-korea; Neighborhood; Community; Health; City; Place; Density; Seoul; Configuration Management; Apartments; Uniqueness; Social Relations; Empirical Analysis; Characteristics
Lee, Yong-Cheol; Shariatfar, Moeid; Rashidi, Abbas; Lee, Hyun Woo. (2020). Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents. Automation In Construction, 113.
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Abstract
As the construction industry experiences a high rate of casualties and significant economic loss associated with accidents, safety has always been a primary concern. In response, several studies have attempted to develop new approaches and state-of-the-art technology for conducting autonomous safety surveillance of construction work zones such as vision-based monitoring. The current and proposed methods including human inspection, however, are limited to consistent and real-time monitoring and rapid event recognition of construction safety issues. In addition, the health and safety risks inherent in construction projects make it challenging for construction workers to be aware of possible safety risks and hazards according to daily planned work activities. To address the urgent demand of the industry to improve worker safety, this study involves the development of an audio-based event detection system to provide daily safety issues to laborers and through the rapid identification of construction accidents. As an evidence-driven approach, the proposed framework incorporates the occupational injury and illness manual data, consisting of historical construction accident data classified by types of sources and events, into an audio-based safety event detection framework. This evidence-driven framework integrated with a daily project schedule can automatically provide construction workers with prenotifications regarding safety hazards at a pertinent work zone as well as consistently contribute to enhanced construction safety monitoring by audio-based event detection. By using a machine learning algorithm, the framework can clearly categorize the narrowed-down sound training data according to a daily project schedule and dynamically restrict sound classification types in advance. The proposed framework is expected to contribute to an emerging knowledge base for integrating an automated safety surveillance system into occupational accident data, significantly improving the accuracy of audio-based event detection.
Keywords
Construction Projects; Occupational Hazards; Construction Workers; Construction; System Safety; Video Surveillance; Work-related Injuries; Audio-based Accident Recognition; Autonomous Safety Surveillance; Construction Safety; Evidence-driven Sound Event Detection; Accident Prevention; Accidents; Audio Acoustics; Classification (of Information); Construction Industry; Health Hazards; Health Risks; Knowledge Based Systems; Learning Algorithms; Losses; Machine Learning; Monitoring; Motion Compensation; Occupational Diseases; Steel Beams And Girders; Audio-based; Construction Accidents; Construction Work Zones; Historical Construction; Sound Event Detection; State-of-the-art Technology; Vision Based Monitoring; Algorithm; System
Shang, Luming; Lee, Hyun Woo; Dermisi, Sofia; Choe, Youngjun. (2020). Impact of Energy Benchmarking and Disclosure Policy on Office Buildings. Journal Of Cleaner Production, 250.
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Abstract
Building energy benchmarking policies require owners to publicly disclose their building's energy performance. In the US, the adoption of such policies is contributing to an increased awareness among tenants and buyers and is expected to motivate the owners of less efficient buildings to invest in energy efficiency improvements. However, there is a lack of studies specifically aimed at investigating the impact of such policies on office buildings among major cities through quantitative analyses. In response, this study evaluated the effectiveness of the benchmarking policy on energy efficiency improvements decision-making and on real estate performances, by applying two interrupted time series analyses to office buildings in downtown Chicago. The initial results indicate a lack of statistically strong evidence that the policy affected the annual vacancy trend of the energy efficient buildings (represented by ENERGY STAR labeled buildings). However, the use of interrupted time series in a more in-depth analysis shows that the policy is associated with a 6.7% decrease in vacancy among energy efficient buildings. The study proposed a method to quantitatively evaluate the impact of energy policies on the real estate performance of office buildings, and the result confirms the positive impact of energy-efficient retrofits on the real estate performance. The study findings support the reasoning behind the owners' decision in implementing energy efficiency improvements in their office buildings to remain competitive in the market. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords
Office Buildings; Building Failures; Time Series Analysis; Real Property; Energy Consumption; Metropolis; Building Performance; Chicago (ill.); Building Energy Benchmarking And Disclosure Policies; Building Energy Efficiency; Time Series Modeling; Energy Star (program); Building Management Systems; Buildings (structures); Decision Making; Energy Conservation; Maintenance Engineering; Time Series; Disclosure Policy; Energy Benchmarking Policies; Building; Benchmarking Policy; Energy Efficiency Improvements Decision-making; Estate Performance; Energy Efficient Buildings; Energy Star; Energy Policies; Energy-efficient Retrofits; Interrupted Time-series; Regression; Behavior; Designs; Building Energy Benchmarking And; Disclosure Policies; Buildings; Cities; Energy Efficiency; Energy Policy; Markets; Quantitative Analysis; United States
Chen, Chen; Lindell, Michael K.; Wang, Haizhong. (2021). Tsunami Preparedness and Resilience in the Cascadia Subduction Zone: A Multistage Model of Expected Evacuation Decisions and Mode Choice. International Journal Of Disaster Risk Reduction, 59.
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Abstract
Physical scientists have estimated that the Cascadia Subduction Zone (CSZ) has as much as a 25% chance to produce a M9.0 earthquake and tsunami in the next 50 years, but few studies have used survey data to assess household risk perceptions, emergency preparedness, and evacuation intentions. To understand these phenomena, this study conducted a mail-based household questionnaire using the Protective Action Decision Model (PADM) as a guide to collect 483 responses from two coastal communities in the CSZ: Crescent City, CA and Coos Bay, OR. We applied multistage regression models to assess the effects of critical PADM variables. The results showed that three psychological variables (risk perception, perceived hazard knowledge, and evacuation mode efficacy) were associated with some demographic variables and experience variables. Evacuation intention and evacuation mode choice are associated with those psychological variables but not with demographic variables. Contrary to previous studies, location and experience had no direct impact on evacuation intention or mode choice. We also analyzed expected evacuation mode compliance and the potential of using micro-mobility during tsunami response. This study provides empirical evidence of tsunami preparedness and intentions to support interdisciplinary evacuation modeling, tsunami hazard education, community disaster preparedness, and resilience plans.
Keywords
False Discovery Rate; American-samoa; Earthquake; Washington; Behavior; Oregon; Wellington; Responses; Disaster; Tsunami Evacuation; Cascadia Subduction Zone; Risk Perception
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
Zou, Tianqi; Aemmer, Zack; Mackenzie, Don; Laberteaux, Ken. (2022). A Framework for Estimating Commute Accessibility and Adoption of Ridehailing Services Under Functional Improvements from Vehicle Automation. Journal Of Transport Geography, 102.
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Abstract
This paper develops an analytical framework to estimate commute accessibility and adoption of various ridehailing service concepts across the US by synthesizing individual commute trips using national Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data. Focusing on potential improvements in cost and time that could be enabled by vehicle automation, we use this modeling framework to simulate a lower-price autonomous service (e.g., 50% or 75% lower) with variable wait times and implementation levels (solo, pooled, and first/last mile transit connections services, alone or in combination) to determine how they might affect adoption rates. These results are compared across metrics of accessibility and trip density, as well as socioeconomic factors such as household income. We find - unsurprisingly - that major cities (e.g. New York, Los Angeles, and Chicago) support the highest adoption rates for ridehailing services. Decreases in price tend to increase market share and accessibility. The effect of a decrease in price is more drastic for lower income groups. The proposed method for synthesizing trips using the LODES contributes to current travel demand forecasting methods and the proposed analytic framework can be flexibly implemented with any other mode choice model, extended to non-commute trips, or applied to different levels of geographic aggregation.
Keywords
Choice Of Transportation; Demand Forecasting; Poor People; Adoption; Price Cutting; Metropolis; Employment Statistics; Los Angeles (calif.); New York (state); Chicago (ill.); Accessibility; Autonomous Vehicles; New Mobility Services; Ridehailing; Travel Demand; Preferences
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Minimization of Socioeconomic Disruption for Displaced Populations Following Disasters. Disasters, 34(3), 865 – 883.
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Abstract
In the aftermath of catastrophic natural disasters such as hurricanes, tsunamis and earthquakes, emergency management agencies come under intense pressure to provide temporary housing to address the large-scale displacement of the vulnerable population. Temporary housing is essential to enable displaced families to reestablish their normal daily activities until permanent housing solutions can be provided. Temporary housing decisions, however, have often been criticized for their failure to fulfil the socioeconomic needs of the displaced families within acceptable budgets. This paper presents the development of (1) socioeconomic disruption metrics that are capable of quantifying the socioeconomic impacts of temporary housing decisions on displaced populations; and (2) a robust multi-objective optimization model for temporary housing that is capable of simultaneously minimizing socioeconomic disruptions and public expenditures in an effective and efficient manner. A large-scale application example is optimized to illustrate the use of the model and demonstrate its capabilities ingenerating optimal plans for realistic temporary housing problems.
Keywords
Natural Disasters; Hurricanes; Disaster Relief; Temporary Housing; Tsunamis; Multi-objective Optimization; Post-disaster Recovery; Social Welfare; Socioeconomic Disruption
Kim, Yong-Woo; Han, Seungheon; Shin, Sungwon; Choi, Kunhee. (2011). A Case Study of Activity-Based Costing in Allocating Rebar Fabrication Costs to Projects. Construction Management And Economics, 29(5), 449 – 461.
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Abstract
How to improve cost allocation for reinforced steel bar (rebar) is an ongoing topic of debate among construction manufacturers and contractors. Traditionally, many fabrication shops have used a single overhead-cost pool accounting system. However, a new costing method, activity-based costing (ABC), may provide more advantages than the traditional system. In this case study, a single overhead-cost pool system is compared with the ABC method to demonstrate how ABC improves cost allocation and provides other benefits. The case study findings indicate that ABC provides such benefits as (1) accurate manufacturing costs; (2) cost information on processes; and (3) information on cost drivers. This paper also bridges the construction and cost accounting literature. Our study contributes to the construction management literature by offering a different cost allocation method to refine fabrication costs assigned to projects. The findings are expected to serve as a reference for industry professionals who recognize the shortcomings of a traditional single overheadcost pool system and are in need of a more accurate costing system. © 2011 Taylor & Francis.
Keywords
Bridges; Costs; Fabrication; Lakes; Project Management; Rebar; Accounting System; Activity Based Costing; Construction Management; Fabrication Shops; Industry Professionals; Manufacturing Cost; Overhead Costs; Traditional Systems
Maliszewski, Paul J.; Larson, Elisabeth K.; Perrings, Charles. (2012). Environmental Determinants of Unscheduled Residential Outages in the Electrical Power Distribution of Phoenix, Arizona. Reliability Engineering & System Safety, 99, 161 – 171.
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Abstract
The sustainability of power infrastructures depends on their reliability. One test of the reliability of an infrastructure is its ability to function reliably in extreme environmental conditions. Effective planning for reliable electrical systems requires knowledge of unscheduled outage sources, including environmental and social factors. Despite many studies on the vulnerability of infrastructure systems, the effect of interacting environmental and infrastructural conditions on the reliability of urban residential power distribution remains an understudied problem. We model electric interruptions using outage data between the years of 2002 and 2005 across Phoenix, Arizona. Consistent with perceptions of increased exposure, overhead power lines positively correlate with unscheduled outages indicating underground cables are more resistant to failure. In the presence of overhead lines, the interaction between birds and vegetation as well as proximity to nearest desert areas and lakes are positive driving factors explaining much of the variation in unscheduled outages. Closeness to the nearest arterial road and the interaction between housing square footage and temperature are also significantly positive. A spatial error model was found to provide the best fit to the data. Resultant findings are useful for understanding and improving electrical infrastructure reliability. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords
Determinants (mathematics); Electric Power Distribution; Reliability In Engineering; Social Factors; Temperature Effect; Phoenix (ariz.); Arizona; Distribution; Electricity; Interruption; Outage; Reliability; System Reliability Assessment; Maintenance; Overhead; Model; Interruptions; Regression; Flashover; Failures; Performance; Hurricanes
El-Anwar, Omar. (2013). Maximising the Net Social Benefit of the Construction of Post-Disaster Alternative Housing Projects. Disasters, 37(3), 489 – 515.
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Abstract
The widespread destruction that follows large-scale natural disasters, such as Hurricane Katrina in August 2005, challenges the efficacy of traditional temporary housing methods in providing adequate solutions to housing needs. Recognising these housing challenges, the Congress of the United States allocated, in 2006, USD 400 million to the Department of Homeland Security to support Alternative Housing Pilot Programs, which are intended to explore the possibilities of providing permanent and affordable housing to displaced families instead of traditional temporary housing. This paper presents a new methodology and optimisation model to identify the optimal configurations of post-shelter housing arrangements to maximise the overall net socioeconomic benefit. The model is capable of quantifying and optimising the impacts of substituting temporary housing with alternative housing on the social and economic welfare of displaced families as well as the required additional costs of doing so. An application example is presented to illustrate the use of the model and its capabilities.
Keywords
Public Housing; Temporary Housing; Hurricane Katrina, 2005; Natural Disasters; Socioeconomic Factors; Mathematical Models; Mathematical Optimization; United States; Alternative Housing Pilot Programs; Optimisation; Socioeconomic Benefit; Disasters