Government data openness and knowledge management: configurational patterns for national competitiveness
| DOI | https://doi.org/10.1108/IMDS-03-2022-0188 |
| Published date | 03 October 2022 |
| Date | 03 October 2022 |
| Pages | 2710-2736 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Juyeon Ham,Yunmo Koo,Jae Nam Lee |
Government data openness
and knowledge management:
configurational patterns for
national competitiveness
Juyeon Ham
School of Management and Economics, Beijing Institute of Technology,
Beijing, China
Yunmo Koo
Busan Development Institute, Busan, South Korea, and
Jae Nam Lee
Department of MIS, Korea University Business School, Seoul, South Korea
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 configur ational patterns constit uted by government data open ness 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.
Keywords Open data, Knowledge management, Open innovation, National competitiveness, Fuzzy-set
qualitative comparative analysis (fsQCA)
Paper type Research paper
1. Introduction
In almost every field, expectations for the potential value of data and the importance of
innovation using data are growing. Improved data use can affect countries’political,
economic, and social development (Janssen et al., 2012). It can increase productivity, create
new jobs, and develop new products and services (Janssen et al., 2012;Magalhaes and Roseira,
2020). It can also provide enhanced policies and public services, such as prompt response to
the COVID-19 pandemic (Awotunde et al., 2021) or protecting people safe from crime
(Bulgakova et al., 2019). Therefore, the ability to use data well determines the competitiveness
of individuals, firms, and countries (Magalhaes and Roseira, 2020).
Recognizing the value of data, countries in the world have established related policies
(Janssen et al., 2012;Zuiderwijk et al., 2012). Governments have been implementing open
IMDS
122,12
2710
This work was supported by the Korea University Business School and the National Research
Foundation of Korea Grant funded by the Korean Government (NRF- 2014S1A5A2A03064953), the
Korea University Business School Research Grant and the Beijing Institute of Technology Research
Fund Program for Young Scholars.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 31 March 2022
Revised 27 August 2022
Accepted 11 September 2022
Industrial Management & Data
Systems
Vol. 122 No. 12, 2022
pp. 2710-2736
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-03-2022-0188
policies on government data as entities that generate substantial data. Since the UK and the
US first implemented the policy in 2009, many countries have joined the policy to increase
transparency and participation, create data-driven innovations, and further improve national
competitiveness (Wang and Shepherd, 2020;Zuiderwijk et al., 2015).
However, the question of whether such open data is properly recognized and used in
practice can be considered separate from the issue of how much data has been opened. Many
countries show significant gaps in data provision and use (Ham et al., 2019). It means that
while expectations for open data are high, its potential has not yet been fully realized (Ruijer
et al., 2020;Safarov et al., 2017;Worthy, 2015). Simply posting substantial data in an open data
portal cannot guarantee the use of data. Data that users do not utilize cannot show its value.
Thus, for the true success of the open data policy, the focus should be on data utilization (Ham
et al., 2019).
According to previous studies on open data, a sufficient knowledge base and its
appropriate management are important to effectively derive the potential value from open
data (Keralis, 2017;Mohamed et al., 2020). The Organization for Economic Cooperation and
Development (OECD) has also emphasized the role of knowledge-based capital (KBC), [1] a
group of intangible knowledge-related assets or resources that enables a firm or country to
create new value and innovations (Schiuma and Lerro, 2008) as new growth engines in the
data economy era (OECD, 2013). To realize the potential value of open data for national
competitiveness, open data should be associated with appropriate knowledge management
based on sufficient knowledge flows.
One issue is that open data policies, strategies, and capabilities of each country differ in
terms of type, scope, and depth (Amankwah-Amoah, 2015;Nugroho et al., 2015;Zuiderwijk
and Janssen, 2014), which can ultimately affect a country’s competitive advantage. For
example, during the global pandemic, governments of each country tried to reduce national
confusion by providing real-time data and information related to the pandemic, while also
improving trust and potential competitiveness of the country. The level of KBC seems also
distinct across countries. For example, South Korea focuses on the creation of new
knowledge, whereas Switzerland pays attention to the diffusion of knowledge (Dutta et al.,
2015). Based on the strategic focus and intention, each country must set the specific type and
scope of data provision and usage (Ham et al., 2019). However, although there are differences
in open data strategies and KBCs by country, and national performance may be different as a
result, extant research on these aspects is still lacking.
Another issue is that a country can implement multiple and equally viable means to
effectively align open data with knowledge management, which lead to high national
performance such as competitiveness. A high level of national competitiveness can be
achieved by various ways (Porter, 1990). That is, therecan be various configurations for open
data and knowledge management strategies, and these various configurations can expect
achieve the same high national performance.However, previous studies lack consideration of
the possibility of these various configurations. To enhance and deepen the understanding
about how to utilizethe resources in each country for achieving high national competitiveness,
a new approach is needed to explore the situation froma holistic perspective.
To fill in these knowledge gaps, this study aims to investigate how various combinations
of government data openness and knowledge management can contribute to national
competitiveness. Based on the premise of equifinality, [2] we empirically examine how data
openness and knowledge management combine into multiple and viable configurations in the
government context. In keeping with this research goal, we use fuzzy-set qualitative
comparative analysis (fsQCA), a set-theoretic configuration method for effectively handling
the statistical intransigence of interdependency between data openness and knowledge
management. fsQCA is applied to a sample of 76 countries collected from the ODB, Global
Innovation Index (GII), and Global Competitiveness Report (GCR). With the findings, this
Government
data openness
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