• Journal of Digital Convergence
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• v.19 no.12
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• pp.531-539
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• 2021

Given the rapid development of information and communication technology (ICT) and the deepening of the information gap phenomenon in the context of the COVID-19 pandemic, researchers and practitioners need to understand the changing perceptions of new phenomena such as COVID-19 information gap on the existing information-vulnerable population. In this study, an empirical analysis was performed with the digital information gap survey data in 2020 to understand the potential impact of COVID-19 on the information gap according to the information-vulnerable class. This study is to verify the effect of information gap, marginalized groups, gender, and major factors of information services (contents, social relations, life services, information production, networking, social participation, non-face-to-face services) on the change in perception of digital information technology after Corona. Hierarchical regression analysis was performed. As a result of the analysis, it was found that the higher the content, social relationship, life service, networking, and digital non-face-to-face service, the higher the change in perception of digital information technology after Corona. Therefore, in light of the evolving phenomenon of COVID-19, it is considered that the government needs to provide education and training to strengthen the capabilities of the information-vulnerable class in order to resolve the digital information gap.

• Land and Housing Review
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• v.12 no.2
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• pp.13-32
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• 2021

Rapid urbanization has resulted in the unprecedented growth of population in Metro Manila, the Philippines and has led to a 'dual' housing crisis - vacant/unoccupied socialized housing and a chronic housing shortage or delayed housing supply. By developing two GIS-based statistical models, this study is to examine socialized housing in comparison with private housing with respect to location patterns, integration, accessibility, social and economic aspects, and vulnerability to environmental hazards. Multiple regression analysis was integrated with the GIS to identify significant variables that influence the spatial distribution of socialized housing. The comparison between the two regression models has shown that socialized housing is located in areas with inappropriate land use and poor accessibility to transportation facilities and built urban resources. Moreover, both regression models have proven the statistical significance of the vulnerability of socialized housing to environmental hazards. The finding explains how the current housing policies do not address the country's housing crisis, especially for the marginalized and low-income households. Thus, the findings provide implications for urban planners and local decision-makers in reforming the current policy interventions.