- Title: Necessity and Possibilities of a Data-driven Regional Research Methodology for Exploring Mega Asia: Implications from KCI Indexed Regional Study Articles with Quantitative Research Methods
- Author: Jungwon Huh, Seonyoung Park, Hyo Jin Jang, Woo Jin Shim
- Journal: Asia Review 11(2)
- Publication Date: August, 2021
- Abstract
The purpose of this paper is to explore a new data-driven research method for a comparative area study. The paper examines the data and analysis methods utilized by previous area studies with a quantitative method and proposes innovative research methods to explore the discourse of Mega Asia and comparative area studies. The authors searched research articles that compared countries and regions from KCI indexed journals and collected bibliographic data such as titles, keywords, abstracts, areas of interest, and main topics. Since 2000, the publication of regional study journals has significantly increased, and most newly published journals focus on Asia. Mainly, newly published Asia study journals specialized on East Asia and Southeast Asia regions, reflecting the growing interest in South Korea due to geographical proximity. More studies investigated countries than regions, and the most popular regions of interest among study subjects are Asia and Europe. Most of the studies relied on macro data from international organizations or country-level statistics produced by the governments. Few studies utilized spatial data with no scale dependency. Spatial data allow them to extract the information regardless of interstate boundaries. The findings reaffirm the need for an alternative blended database with geographical coordinates and a data-driven approach with a data science perspective to analyze regional dynamics.
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