Jeong-Il Park

Jeong-Il Park

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2016 in Renewable Energy
Verified
Journal Article
Closed access
TKTaeyun Kim
Taeyun Kim
JPJeong-Il Park
Jeong-Il Park
JMJunho Maeng
Junho Maeng

1 February 2022 in Journal of Cleaner Production
Verified
Journal Article
Open access
JPJeong-Il Park
Jeong-Il Park
Jin-Oh KimJin-Oh Kim
Jin-Oh Kim



1 September 2017 in Journal of Urban Technology
Verified
Journal Article
Closed access
JPJeong-Il Park
Jeong-Il Park
NLNancey Green Leigh
Nancey Green Leigh
Using longitudinal data from the National Establishment Time-Series dataset, this paper presents research on intra-metropolitan spatial patterns of manufacturing employment created by foreign direct investment (FDI) in the Atlanta, Georgia metropolitan area. A panel regression analysis reveals that the loss of urban industrial land in the central metro area is associated with the suburbanization of FDI manufacturing jobs over time. Based on the key findings of the analyses, the paper discusses the policy implications of job losses in urban manufacturing and some strategies for attracting and retaining these jobs.

30 April 2019 in Sustainability
Verified
Journal Article
Open access
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JPJeong-Il Park
Jeong-Il Park
Previous studies on housing vacancy mostly focused on variables representing regional characteristics while overlooking the characteristics of individual houses. This is due to the limitations of available data. Using the house-level Housing Vacancy Database, this study aims to identify the spatial clustering pattern of vacant houses by examining single-family houses in Daegu, South Korea, and analyze the factors affecting housing vacancy. The Housing Vacancy Database built in this study provides accurate location information of vacant houses, making it possible to analyze the clustering pattern of vacant houses in a more detailed spatial unit. Furthermore, the Housing Vacancy Database considered various physical and neighborhood factors at the house level. The result of hot spot analysis showed that vacant houses were spatially concentrated in the city center. As a result of analyzing the factors affecting housing vacancy at the house level and neighborhood level using a multilevel model, it was found that the physical environment characteristics of individual houses were key factors affecting housing vacancy. Additionally, the probability of housing vacancy tended to increase when the land prices were higher, the houses were located in redevelopment zones, and there were more neighboring vacant houses nearby. Meanwhile, population decline and the ratio of old houses were the only significant variables at the neighborhood level. Thus, this study addresses that policies are needed to improve housing and physical environment characteristics that contribute to housing vacancy.