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Government data openness and knowledge management: configurational patterns for national competitiveness

Authors
Ham, JuyeonKoo, YunmoLee, Jae Nam
Issue Date
2022
Publisher
EMERALD GROUP PUBLISHING LTD
Keywords
Open data; Knowledge management; Open innovation; National competitiveness; Fuzzy-set qualitative comparative analysis (fsQCA)
Citation
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
Indexed
SCIE
SCOPUS
Journal Title
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/147112
DOI
10.1108/IMDS-03-2022-0188
ISSN
0263-5577
Abstract
Purpose In the data economy era, despite the tremendous effort of governments to actively provide and use open data, its effect on national performance such as competitiveness differs widely from country to country. A sufficient knowledge base and its appropriate management are important to effectively derive the potential value from open data. A country can implement multiple and equally viable means to effectively align open data with knowledge management, which lead to high national performance. However, previous studies lack consideration of the possibility of these various configurations. To fill the research gap, this study aims to investigate the configurational patterns constituted by government data openness and knowledge management for national competitiveness. Design/methodology/approach From the open innovation perspective, this study collected data from the global reports of 76 countries and examined them through fuzzy-set qualitative comparative analysis (fsQCA). Findings Four configurational patterns are identified, namely, coupled (outbound-focused)-, coupled (inbound-focused)-, inbound-focused-, and outbound-focused national competitiveness. Originality/value This study provides a foundation that enables researchers to build a holistic and balanced perspective that can manage open government data and develop knowledge management capability.
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