Co-worker safety support has been given prominence in manufacturing and transportation field for its positive effect on individual workers’ safety; however, there is little evidence to show if such supporting role of co-workers is significant in improving project-level safety performance in construction workplace. This study adopts agent-based modeling (ABM) to understand the effectiveness of two distinct co-worker-safety-support actions on the safety performance of a construction project. Based on the risk theory, the ABM model simulates a construction site where worker agents reinforce steel bars with the likelihood of suffering crane-related incidents. The results indicate that both co-worker-support actions can significantly reduce the occurrence of nonfatal incidents but shows little influence in fatal incidents, and in reducing high-severity incidents, the action of warning peers to leave the hazardous area has the same effectiveness as reminding peers to wear Personal Protective Equipment. The present study provides a fresh insight into the safety-related role of co-workers: not only reveals how the local-level effects of co-workers’ safety assistance emerge the system-level consequences, but demonstrates the effectiveness of specific peer-support actions on three levels of construction safety performance, and thereby extends our existing body of knowledge on co-worker safety support in the construction field.
Risk and resilience assessments have been both widely, but separately, used as tools for guiding policymakers to formulate disaster-risk reduction policies. On one hand, risk assessment is utilized to estimate the risk associated with disasters in terms of operational metrics such as monetary or casualties' loss; on the other, most resilience analysis assesses and represent community resilience as an index, without a specific unit metric, to gauge levels of disparity in community's post-disaster recovery capability among the areas of interest. Although disaster-risk reduction policies should be best informed by both risk and resilience assessments, an informative integrated assessment approach accounting for both seems to be lacked in current research, insofar as the difficulty in properly integrating their distinct measurement metrics. This paper commences with a literature review of risk assessment and community resilience. It then proposes an integrated framework that can comprehensively assess both seismic risk and resilience, by taking into account the casualties and economic losses associated with earthquakes resulted from a risk assessment, and the infrastructure-system resilience and community socioeconomic-demographic resilience resulted from a resilience assessment. More specifically, an integrated tool, risk-based resilienceconcentration curve, is proposed for assessing the inequality of given types of risk in the community's infrastructure-system resilience, and socioeconomic-demographic resilience, respectively. A case study is presented using the data from a city in Israel: the first phase of the case study focused on the concentration of casualties' risk in community's infrastructure-system resilience, and the second on the concentration of economic risk in community's socioeconomicdemographic resilience. The results show that unevenly distributed risk and community resilience can cause inequality of risk in resilience capacity in certain administrative tracts of the city. Based on these findings, the paper recommends a range of risk-reduction strategies for different administrative tracts based on their risk-based resilience concentration curves.
Data-driven housing-market segmentation has been given increasing prominence for its 4 objectiveness in identifying submarkets based on the housing data's underlying structures. 5However, although popular in existing literature, current statistical-clustering methods, when 6 handling high-dimensionality housing dataset, has been found to tend to loss low-variance 7 information of the dataset and be deficient in deriving the globally optimal number of 8 submarkets. Accordingly, with the intention of achieving more rigorous housing-market 9 segmentation in the case of high-dimensionality housing dataset, a swarm-inspired projection (SIP) algorithm is introduced by this study. A case study is then conducted using housing dataset of Taipei city to evaluate the predictive accuracy of submarkets' housing prices obtained using hedonic price models, and which are based on the segmentations resulted from both the proposed SIP and a statistical-clustering method using the combination of principal component analysis (PCA) and K-means clustering. The results show that, as compared to the use of PCA and K-means, our proposed SIP algorithm can obtain more optimal number of submarkets for segmentation, and the resulted submarkets are more homogenous and distinctive. This finding highlights the advantages of our proposed SIP algorithm in housing segmentation, and thus it can better help inform the further studies of market segmentationrelated problems.
Senior housing with age-friendly design and elderly care services contributes to the health and well-being of older people. Previous research has evidenced that the immediate environment factors of senior housing, such as the design of housing features and facilities, have a direct bearing on the satisfaction and quality of life of older people. However, external environment factors, such as political, economic, and social ones that affect key stakeholders’ behaviors in senior housing development, are relatively under-researched. Accordingly, this study aimed to explore the external environmental factors influencing the development of senior housing. Taking Hong Kong as case study, this study first commenced with a systematic review to identify the factors in political, economic, and social domains from global evidence. Following this, we interviewed local experts from academia, industry, and government to solicit their opinions on the relative importance of these factors. We then determined the factor rankings using the analytical hierarchy process method. The results showed that local experts perceived economic factors as the most critical ones in influencing senior housing development in Hong Kong, including land costs, funding from financial institutions, and government incentives. If policymakers tend to promote senior housing in densely populated cities like Hong Kong, the policies should be attractive for housing developers, such as land premium concessions and innovative financial channels for supporting the long-term development of senior housing.
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