Smart city initiatives have the potential to address many contemporary urban challenges, utilizing information and technology. Increasingly, smart cities are considered as social innovation processes to achieve sustainable and inclusive urban development, being influenced by broader socio-economic and institutional contexts of cities. This paper explores ‘smart city transitions’ across varied urban contexts, in particular, how smart city transitions are enacted and how they contribute to inclusive urban transformation and public value. Using a multiple case studies approach, the research investigated infrastructure planning practices in Amsterdam in the Netherlands, Seoul in Korea, Portland in the U.S. and Ho Chi Minh City (HCMC) in Vietnam, cities that were known for strong efforts to establish integrated platforms to enhance societal benefits. Our analysis showed that each city has addressed its goals around sustainability, equity and affordability by reinforcing the engagement of multiple actors with the support of integrated platforms that facilitate open and multi-directional information flow in a transparent manner. In Amsterdam, innovative solutions for sustainable use of resources have been invented and distributed through multi-level social networks, contributing to the transformation into a circular economy. In Seoul and HCMC, the city's persistent efforts to utilize an open and integrated platform resulted in proactive engagement and collaboration of public and private actors in improving quality, equity and efficiency of transit services. Portland has tackled inequitable access and mistrust issues by setting principles for data governance and facilitating equity in the adoption of innovative technologies. Our research revealed that four cities established different forms of integrated platforms such as a centrally-controlled platform and a community-centred platform in order to address specific socio-economic issues within an institutional setting of each city. We concluded that building an integrated platform is not easy, but it is a critical prerequisite for the process of sustainable transformation to truly achieve smart cities across the globe.

COVID-19 is unique in that it is spread through everyday contact with other people. Therefore, social protective measures, beyond medical protective measures, such as social distancing, lockdowns, border closures, and human tracing are initiated to control the spread of COVID-19. Such responses have produced secondary issues such as drastic changes in people’s way of life and work, housing instability, economic shock, and privacy issues. This paper examines the four domains of urban and regional issues related to the secondary impact of COVID-19, including (1) social distancing, urban structure, community, and density; (2) housing affordability; (3) lockdowns, border closures, reshoring, and regional economic recovery; and (4) smart city technology, contact tracing, and privacy. The following six recommendations have been proposed. First, institutional and cultural factors are more important than urban features, such as population density. To handle infectious diseases such as COVID-19, it is important to build systems, technology, infrastructure, and urban structures that can strengthen resilience instead of implementing a directionless policy of dispersion. Second, it is necessary to improve accessibility to essential services at the community level, including medical facilities and food supply. Third, continuous effort should be made to boost housing affordability, as it is directly related to people’s basic life. Fourth, measures are needed to protect those people who are socioeconomically disadvantaged. There is also the need to restore global trade and economic relations. Fifth, since data technology-based COVID-19 control raises the human tracing and privacy issue, we must ensure the principles of privacy management, such as transparency and voluntary consent, are being met. Finally, since COVID-19 is spread through people, individuals may become anxious and fearful of others without grounds; this may increase prejudice and hatred, including xenophobia. Significant social effort is needed to overcome such ill-defined anxiety and fear and maintain a healthy civil society.

(2020). Smart city technologies for pandemic control without lockdown. International Journal of Urban Sciences. Ahead of Print.

Previous empirical researches on elderly housing preference show controversial findings; for example, Sun (2004) found women like silver town more than men do, but Park (2005) found the opposite. This controversial outcome is an example of Simpson's Paradox, so we need to group old people into subgroups. We hypothesize that elderly peoples' personal inclination affects housing preference. This research investigates the linkage between elderly peoples' personal inclination and their preference for silver town. To overcome the complexity of housing choice, we used a Structural Equation Model (SEM). We surveyed 350 prospective elderly people, whose ages' ranged from 45 to 65. 293 surveys were returned with proper answers. We extracted six latent criteria, which affect elderly peoples' housing choice, using factor analysis. The criteria include location, capital gain, monthly fee, amenity, convenience, and security. This research finds that old people who are concerned with proximity to city, low monthly fee, and high security tend to prefer silver towns to other housing options. This research confirms that location is the most important factor of silver towns.

As the region with the fastest and highest level of economic growth in China, the instability of the Pearl River Delta Economic Region's (PRDER) housing prices has always been a social focus. In order to make housing price stabilization policies effective, more research is required about China's housing market mechanism and the influential factors of housing prices. China used to be a socialist economy since 1949. Deng Xiaoping began China's economic reform and introduced market principles in 1978. Since then China's housing had undergone transition from socialist system to market economy. After 1998, China had housing market economy. This paper aims to understand the housing price behaviour of newly transformed housing market economy of China by analysing the influential factors of China's housing prices compared to that of conventional market economy. This study established a fixed-effect model of panel data and conducts empirical analysis on the influential factors of housing prices in nine cities in the PRDER by adopting the least squares dummy variable method. Because access to China's housing markets data is extremely limited, collecting reliable and consistent housing market data at city level was the biggest challenge in this research. We successfully compiled local housing market data at city level including housing sales price index of the nine cities, number of resident (registered and non-registered-but-long-stay residents), GDP per capita, residential sales area, annual investment on housing development land purchasing cost, and so forth. The analysis confirms that China's housing market follows a market mechanism. Demand is the major driver of housing prices, housing supply tends to lower the housing prices, and land cost is positively correlated with housing prices. Since cities grow with continuing urbanization and industrialization, housing supply policy seems required to effectively stabilize the housing price.