The Managerial Dimension of Open Data Success: Focusing on the Open Data Initiatives in Korean Local Governments

Abstract

Open government data (open data) initiatives have been at the forefront of the strategy to make more transparent, responsive, and accountable government, and thereby lead to open innovation across the public and private sector. Governments around the world often understand that open data is disclosing their data to the public as much as possible and that open data success is the result of a data and technology-related endeavor rather than the result of organizational, institutional, and environmental attributes. According to the resource-based theory, however, managerial capability to mobilize tangible and intangible resources and deploy them in adequate places or processes under the leadership of capable leaders during the information technology (IT) project is a core factor leading to organizational performance such as open data success. In this vein, this study aims to analyze managerial factors as drivers and challenges of open data success from the resource-based theory. Findings illustrate that managerial factors are the driving forces that often boost or hinder open data success when institutional, socio-economic, and demographic factors are controlled. Discussion illustrates theoretical and practical implications for the managerial factors as drivers and challenges of open data success in terms of the comparison between technological determinism and the socio-technical perspective.

The Culture for Open Innovation Dynamics

“…The 18th paper is about bridging the gap in the technology commercialization process by using a three-stage technology-product-market model, which is related to entrepreneurship leading culture for open innovation dynamics, in addition to marketing innovation and users' continuous intentions [134][135][136].…”

Modeling of Open Government Data for Public Sector Organizations Using the Potential Theories and Determinants—A Systematic Review

“…The third most utilized theory was DOI theory whereby it was employed by the four researchers [7,9,20,58]. The fourth theory, which was employed mostly, was resource-based theory and it was employed three times [6,11,37]. The remaining twenty-six (30) theories were employed only once whereas some of them were used combinedly.…”

“…Fourth, an SLR, a meta-analysis, and accordingly, the weight analysis may have a novel contribution and could bring in-depth insights to the OGD adoption studies from the perspective of public sector organizations which should then be rigorously tested in future. Fifth, there are several control variables introduced in earlier research, like institutional status of the chief information officer (CIO), institutionalization of informatization, financial size, financial independence, aging population, population density [37], department type [20], as well as moderating variables like power distance, uncertainty avoidance [11] are introduced. Further research should be carried out, including these control and moderating variables.…”

Factors Affecting Technology Transfer of Universities in the LINC (Leaders in Industry-University Cooperation) Program of Korea

“…As a result of the analysis, it was shown that the competency factors (individuals), cooperative factors, and policy factors had a significant effect on comprehensive performance. At the corporate level, the competency factors of individuals, cooperative factors, policy factors, and external environmental factors all had a significant effect [19]. Based on the data from the LINC project by the Ministry of Education in 2012, Kim Han-ki analyzed each influence factor by classifying the results of industry-academic cooperation as subordinate variables, such as objective performance and subjective performance [20].…”