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

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  • Jun Houng Kim

    (Center of Intelligent Society and Policy, Seoul National University, Seoul 08826, Korea)

  • Seok-Jin Eom

    (Graduate School of Public Administration, Seoul National University, Seoul 08826, Korea)

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.

Suggested Citation

  • Jun Houng Kim & Seok-Jin Eom, 2019. "The Managerial Dimension of Open Data Success: Focusing on the Open Data Initiatives in Korean Local Governments," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6758-:d:292058
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    References listed on IDEAS

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    1. Jovani Taveira de Souza & Antonio Carlos de Francisco & Cassiano Moro Piekarski & Guilherme Francisco do Prado, 2019. "Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018," Sustainability, MDPI, vol. 11(4), pages 1-14, February.
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    Cited by:

    1. JinHyo Joseph Yun & Xiaofei Zhao & KwangHo Jung & Tan Yigitcanlar, 2020. "The Culture for Open Innovation Dynamics," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    2. Seunghoo Jin & Kangwon Lee, 2021. "Factors Affecting Technology Transfer of Universities in the LINC (Leaders in Industry-University Cooperation) Program of Korea," Sustainability, MDPI, vol. 13(18), pages 1-15, September.

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