Open Government Data: The Key to Promoting Public Participation, and Fighting against Corruption
Keywords:
Open government data, Public participation, Corruption controlAbstract
Poor governance resulted from corruption is a chronic problem for the public sector. Although there is an effort to involve citizens to participate in dealing with the issue, they tend to avoid such participation since they do not have sufficient data or have to face data asymmetry that may debase their opinions or arguments. However, open government data (OGD) is now being widely implemented around the world. It is expected to produce a variety of positive impacts on society. This study aimed to investigate the effects of OGD on empowering public participation (PP) and enhancing corruption control (CC). Based on data analysis of 113 countries using Partial Least Squares-Structural Equation Modelling (PLS-SEM), this study found that OGD had a positive significant effect on PP. Besides, OGD could also significantly increase effective efforts to CC. Indeed, OGD has helped citizens to increasingly participate in CC. Given the importance of OGD, countries should be aware of the development of OGD and better capitalize on its benefits and values.
References
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Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(January), 277–319.
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Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2013). Generating value from open government data. International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design, 2, 1737–1756.
Kalampokis, E., Tambouris, E., & Tarabanis, K. (2011). A classification scheme for open government data: Towards linking decentralized data. International Journal of Web Engineering and Technology, 6(3), 266–285.
Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30(4), 508–513.
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Safarov, I., Meijer, A., & Grimmelikhuijsen, S. (2017). Utilization of open government data: A systematic literature review of types, conditions, effects and users. Information Polity, 22(1), 1–24.
Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115.
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Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. In Handbook of partial least squares (pp. 47-82): Springer.
Vrushi, J., & Hodess, R. (2017). Connecting the dots: Building the case for open data to fight corruption.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1–32.
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Zuiderwijk, A., & Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1), 17–29.
Zuiderwijk, A., Janssen, M., Choenni, S., Meijer, R., & Alibaks, R. S. (2012). Socio-technical impediments of open data. Electronic Journal of E-Government, 10(2), 156–172.
Awan, R. U., Akhtar, T., Rahim, S., Sher, F., & Cheema, A. R. (2018). Governance , corruption and economic growth :A panel data analysis of selected SAARC countries. Pakistan Economic and Social Review, 56(1), 1–20.
Bartenberger, M., & Grubmüller, V. (2014). The enabling effects of open government data on collaborative governance in smart city contexts. JeDEM - EJournal of EDemocracy and Open Government, 6(1), 36–48.
Bertot, J. C., Jaeger, P. T., & Grimes, J. M. (2010). Using ICTs to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies. Government Information Quarterly, 27(3), 264–271.
Bhayani, M. (2013). Challenges of corruption and good governance: A human rights perspective. International Proceedings of Economics Development and Research, 71(6), 21–27.
Bishop, P., & Davis, G. (2002). Mapping public participation in policy choices. Australian Journal of Public Administration, 61(1), 14–29.
Daniel, D., & Habsari, P. (2019). Informational asymmetry in public participation on environmental monitoring in Indonesian regulation: A preliminary discourse. Journal of Infrastructure Development, 2(1), 4–19.
Darusalam, D., Said, J., Omar, N., Janssen, M., & Sohag, K. (2019). The diffusion of ICT for corruption detection in open government data. Knowledge Engineering and Data Science (KEDS), 2(1), 10–18.
Davies, T. (2012). Ten building blocks of an open data initiative. Retrieved from open data impacts, research notes website: http://www.opendataimpacts.net/2012/08/ten-building-blocks-of-an-open-data-initiative/
Davies, T., & Perini, F. (2016). Researching the emerging impacts of open data: Revisiting the ODDC conceptual framework. Journal of Community Informatics, 12(2), 148–178.
DeLone, W.H., & Mclean, E.R. (1992). Information system success: The quest for the dependent variable. Information systems research, 3(1), 60–95.
DeLone, W., & McLean, E. (2003). The DeLone and McLean model of information systems success: A ten-year update. JMIS, 19(4), 9–31.
Desta, Y. (2006). Designing anti-corruption strategies for developing countries: A country study of Eritrea. Journal of Developing Societies, 22(4), 421–449.
Economist Intelligence Unit. (2017). Democracy index 2016: Revenge of the deplorables. Retrieved from https://eiuperspectives.economist.com/sites/default%0A/files/The EIU%27s 2016 Democracy Index_0.pdf%0A
Evans, A. M., & Campos, A. (2013). Open government initiatives: Challenges of citizen participation. Journal of Policy Analysis and Management, 32(1), 172–185.
Faisal, F., & Jafri, A. R. (2017). Corruption as a source of failure of good governance and management in Pakistan: Proposed remedial measures. Jpuhs, 30(1), 57–75.
Florez, J., & Tonn, J. (2019). Accountability and anti-corruption. In T. Davies, S. Walker, M. Rubnistein, & F. Perini (Eds.), The state of open data: Histories and horizons (pp. 17–34). Cape Town and Ottawa: African Minds and International Development Research Centre.
Gigler, B., Custer, S., & Rahemtulla, H. (2011). Realizing the vision of open government data: Opportunities, challenges, and pitfalls. Open Development Technology Alliance and World Bank, (December), 13–35. Retrieved from https://www.academia.edu/35025372/Realizing_the_Vision_of_Open_Government_Data_Opportunities_Challenges_and_Pitfalls
Goodrich, S. (2015). How open data can help tackle corruption: Policy paper. Retrieved from https://www.transparency.org.uk/wp-content/plugins/%0Adownload-attachments/includes/download.php?id=1505%0A
Gujarati, D. N. (2003). Basic econometrics. New York: McGraw-Hill.
Guriev, S. (2004). Red tape and corruption. Journal of Development Economics, 73(2), 489–504.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. United States: CENGAGE.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: SAGE Publications Ltd.
Halonen, A. (2012). Being open about data: Analysis of the UK open data policies and applicability of open data. Retrieved from http://assets.finnishinstitute.studiocoucou.com/media/W1siZiIsIjIwMTMvMDEvMzEvMTNfMDNfMTNfNjM1X2JlaW5nXzIwb3Blbl8yMGFib3V0XzIwZGF0YS5wZGYiXV0/being open about data.pdf?sha=9b1040ca
Hartog, M., Mulder, B., Spée, B., Visser, E., & Gribnau, A. (2014). Open data within governmental organisations: Effects, benefits and challenges of the implementation process. JeDEM - EJournal of EDemocracy and Open Government, 6(1), 49–61.
Hays, R. A., & Kogl, A. M. (2007). Neighborhood attachment, social capital building, and political participation: A case study of low-and moderate-income residents of Waterloo, Iowa. Journal of Urban Affairs, 29(2), 181–205.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(January), 277–319.
Hulstijn, J., Darusalam, D., & Janssen, M. (2018). Open data for accountability in the fight against corruption. In M. Baldoni, C. Baroglio, & R. Micalizio (Eds.), Computational accountability and responsibility in multiagent systems (CARe-MAS 2017) (Vol. 2051, pp. 52–66).
Iglesias, D. (2017). Open data and the fight against corruption in Brazil (Vol. 1). https://doi.org/10.36574/jpp.v1i3.23
Ionescu, L. (2013). Perceptions of corruption in emerging economies. Economics, Management and Financial Markets, 8(1), 365–395.
Izdebski, K. (2015). Transparency and open data principles: Why they are important and how they increase public participation and tackle corruption. In U. S. Department of State. Retrieved from https://transparencee.org/wpcontent/uploads/2015/12/open-data-principles-by-krzysztof-izdebski.pdf
Janssen, K. (2012). Open government data and the right to information: Opportunities and obstacles. The Journal of Community Informatics, 8(2).
Janssen, M., & Zuiderwijk, A. (2012). Open data and transformational government. Conference Transforming Government Workshop. United Kingdom: Brunel University.
Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2013). Generating value from open government data. International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design, 2, 1737–1756.
Kalampokis, E., Tambouris, E., & Tarabanis, K. (2011). A classification scheme for open government data: Towards linking decentralized data. International Journal of Web Engineering and Technology, 6(3), 266–285.
Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30(4), 508–513.
Kim, S., Kim, H. J., & Lee, H. (2009). An institutional analysis of an e-government system for anti-corruption: The case of OPEN. Government Information Quarterly, 26(1), 42–50.
Kumar, R. (2004). Corruption and human rights: Promoting transparency in governance and the fundamental right to corruption-free service in India. Columbia Journal of Asian Law, 17(1), 31–72.
Lee, J. N., Ham, J., & Choi, B. (2016). Effect of government data openness on a knowledge-based economy. Procedia Computer Science, 91(Itqm), 158–167.
Lynch, J. G., Jr., Chen, Q., & Zhao, X. (2010). Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197–206. doi:10.1086/651257
Mellouli, S., Luna-Reyes, L. F., & Zhang, J. (2014). Smart government, citizen participation and open data. Information Polity, 19(1–2), 1–4.
Odongo, A. O., & Rono, G. C. (2016). Open government data as a right for effective citizen participation. ACM International Conference Proceeding Series, 01-03-Marc, 365–366.
OECD. (2018). Open government data report: Enhancing policy maturity for sustainable impact. https:// doi.org./10.1787/9789264305847-en
Park, C. H., & Kim, K. (2019). E-government as an anti-corruption tool: Panel data analysis across countries. International Review of Administrative Sciences, 1–36.
Park, S., Lee, H., & Chae, S. W. (2017). Rethinking balanced scorecard (BSC) measures: Formative versus reflective measurement models. International Journal of Productivity and Performance Management, 66(1), 92–110.
Peled, A. (2013). Re-designing open data 2.0. JeDEM - EJournal of EDemocracy and Open Government, 5(2), 187–199.
Rajshree, N., & Srivastava, B. (2012). Open government data for tackling corruption – A perspective case study : NREGA in India. 2012 AAAI Workshop - Semantic Cities, 21–24.
Renata, M. (2017). Measuring the effects of open data on the level of corruption. In Proceedings of the 21st International Conference Current Trends in Public Sector Research (pp. 58–65).
Safarov, I., Meijer, A., & Grimmelikhuijsen, S. (2017). Utilization of open government data: A systematic literature review of types, conditions, effects and users. Information Polity, 22(1), 1–24.
Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115.
Steele, J. L., Murnane, R. J., & Willett, J. B. (2010). Low-performing schools attract and keep academically talented teachers ? Evidence. Journal of Policy Analysis and Management, 29(3), 451–478.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159–205.
Transparency International. (2016). Corruption perception index 2016. Retrieved from https://www.transparency.org/news/feature/corruption_perceptions_index_2016
Tshepo, M. (2015). The Nexus between corruption and governance since the dispensation of democracy in South Africa: A time series analysis. Retrieved from http://2015.essa.org.za/fullpaper/essa_2854.pdf
United Nations. (2016). E-government survey 2016. Retrieved from http://workspace.unpan.org/sites/Internet/Documents/UNPAN96407.pdf
United Nations Development Programme. (1997). Corruption and good governance. New York.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5–40.
Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. In Handbook of partial least squares (pp. 47-82): Springer.
Vrushi, J., & Hodess, R. (2017). Connecting the dots: Building the case for open data to fight corruption.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1–32.
World Bank. (2018). Engaging citizens for better development results: An independent evaluation. Retrieved from https://ieg.worldbankgroup.org/evaluations/engaging%0A-citizens-better-development-results%0A
World Wide Web Foundation. (2016). Open data barometer global report. Retrieved from http://www.opendatabarometer.org
Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny : Myths and truths about mediation analysis. The Journal of Consumer Research, 37(2), 197–206.
Zuiderwijk, A., & Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1), 17–29.
Zuiderwijk, A., Janssen, M., Choenni, S., Meijer, R., & Alibaks, R. S. (2012). Socio-technical impediments of open data. Electronic Journal of E-Government, 10(2), 156–172.
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