본 연구실은 경제지리와 시공간 빅데이터 분석을 기반으로 도시 활력, 인간 이동성, 광역도시권 네트워크, 지역 산업생태계의 구조와 회복력을 연구하며, 와이파이·보행·휴대전화 데이터 등 다양한 도시 데이터를 활용해 스마트시티와 지역정책 수립에 기여하는 데이터 기반 도시·지역 분석을 수행하고 있다.
Urban Vitality Measurement Through Big Data and Internet of Things Technologies
Young-Long Kim
IF 2.8
ISPRS International Journal of Geo-Information
This paper examines the evolution of urban vitality measurement, emphasizing the transformative impact of big data and Internet of Things (IoT) technologies. Traditionally assessed through direct observations and surveys, urban vitality measurement has shifted with the advent of these technologies, enabling the collection of vast amounts of urban data. This approach offers a more dynamic and comprehensive picture of urban vitality, facilitated by advanced analytical tools such as machine learning and predictive analytics, which can interpret complex datasets to offer real-time insights and better decision-making for urban planning. However, this shift also raises significant methodological and ethical concerns, particularly regarding privacy, reliability, and accuracy. The paper discusses the theoretical underpinnings of urban vitality, current technological advancements, and the challenges and future directions in urban studies. It highlights the need for an interdisciplinary approach to fully harness the potential of emerging technologies in developing livable, sustainable, and responsive cities.
Do inter-firm networks sustain the resilience of regional industrial ecosystems? A network-based analysis of the South Korean automotive industry
Mikyoung Cho, Young-Long Kim
IF 2.4
Regional Studies Regional Science
Firms may grow and decline, and their impact on the regional economy can be attributed not only to each firm but also to their inter-firm networks in the region. Therefore, firms and their connectivity should be understood within the context of the regional industrial ecosystem. To empirically show the role of inter-firm networks for the sustainability of the regional industrial ecosystem, this study analyses the automotive industry in South Korea. The Automobile Parts Yearbook, the main data source for the study, provides the addresses of 892 firms and the connectivity between five major automakers and their subcontractors. A network-based approach is chosen to untangle the complex production network and compare the network structure by region. Specifically, the number of nodes, links and connections, as well as density and modularity measures, are analytically compared across six sub-regions in the country. There are more links within the groups than between the groups, which suggests preferential attachment in the network structure. Multiple centralised structures are observed to exist around the five major automakers in sub-regions in South Korea. The empirical results of the paper imply that firms with multiple trading networks in the regional industrial ecosystem tend to recover from an industrial crisis or employment shock crisis more successfully than companies with a single trading network. Overall, these findings highlight the importance of understanding the role of inter-firm networks in regional industrial ecosystems for promoting sustainability and resilience.
Inside out: human mobility big data show how COVID-19 changed the urban network structure in the Seoul Metropolitan Area
Young-Long Kim, Bogang Jun
IF 4.7
Cambridge Journal of Regions Economy and Society
Abstract The COVID-19 pandemic has fundamentally changed human mobility patterns in cities. Lockdowns, social distancing and flexible working hours have restructured pre-existing dynamics between two opposing forces in major cities: centripetal and centrifugal. To scrutinise the new dynamics, human mobility in the Seoul Metropolitan Area in early 2020 was investigated using big data collected from cell phone activity. By suggesting a network-based approach to untangle complex human mobility in the urban network, this research contributes to understanding how the COVID-19 shock impacted human mobility patterns in everyday life and how human behaviours adapted to the new normal.