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Drivers and Barriers for Open Government Data Adoption: An Isomorphic Neo-Institutional Perspective

  • Henry N. RoaEmail author
  • Edison Loza-Aguirre
  • Pamela Flores
Conference paper
  • 81 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1129)

Abstract

By making government data available to all, Open Government Data (OGD) initiatives promote transparency, accountability and value creation. However, these initiatives face several problems affecting their implementation throughout its adoption process. This study focuses on the forces driving or hindering the adoption of OGD in a developing country at its early stages. In depth, through the analysis of qualitative data, which was collected from seven governmental institutions, we highlight that OGD adoption is mainly hindered by the lack of a comprehensive legal framework. On the other hand, the adoption of OGD is mainly driven by the participation of the governmental practitioners on professional networks and by the transmission of success stories from other countries with similar characteristics to the country studied in this research.

Keywords

Open government data Neo-Institutional theory Isomorphic pressures Adoption Information systems 

Notes

Acknowledgment

This research was supported by the Pontificia Universidad Católica del Ecuador through the grant research project O13050. In addition, we acknowledge and thank the Anonymous Reviewers for their valuable recommendations, which contributed to improving the quality of this paper.

References

  1. 1.
    Sadiq, S., Indulska, M.: Open data: quality over quantity. Int. J. Inf. Manage. 37(3), 150–154 (2017)CrossRefGoogle Scholar
  2. 2.
    Bertot, J., Gorham, U., Jaeger, P., Sarin, L., Choi, H.: Big data, open government and e-government: Issues, policies and recommendations. Inf. Polity 19(1–2), 5–16 (2014)CrossRefGoogle Scholar
  3. 3.
    Allen, K.B.: Access to government information. Gov. Inf. Q. 9(1), 67–80 (1992)CrossRefGoogle Scholar
  4. 4.
    Kassen, M.: A promising phenomenon of open data: a case study of the Chicago open data project. Gov. Inf. Q. 30(4), 508–513 (2013)CrossRefGoogle Scholar
  5. 5.
    Dawes, S.S.: Stewardship and usefulness: policy principles for information-based transparency. Gov. Inf. Q. 27(4), 377–383 (2010)CrossRefGoogle Scholar
  6. 6.
    Roa, H.N., Loza-Aguirre, E., Flores, P.: A survey on the problems affecting the development of open government data initiatives. In: Proceedings of the Sixth International Conference on eDemocracy & eGovernment (ICEDEG), Quito, Ecuador (2019)Google Scholar
  7. 7.
    Conradie, P., Choenni, S.: On the barriers for local government releasing open data. Gov. Inf. Q. 31(S. 1), S10–S17 (2014)CrossRefGoogle Scholar
  8. 8.
    Janssen, M., Charalabidis, Y., Zuiderwijk, A.: Benefits, adoption barriers and myths of open data and open government. Inf. Syst. Manage. 29(4), 258–268 (2012)CrossRefGoogle Scholar
  9. 9.
    Lesca, N., Caron-Fasan, M.-L., Loza-Aguire, E., Chalus-Sauvannet, M.C.: Drivers and barriers to pre-adoption of strategic scanning information systems in the context of sustainable supply chain. Systèmes d’Information et Manage. 20(3), 9–46 (2015)CrossRefGoogle Scholar
  10. 10.
    Krishnamurthy, R., Awazu, Y.: Liberating data for public value: the case of data. Gov. Int. J. Inf. Manage. 36(4), 668–672 (2016)CrossRefGoogle Scholar
  11. 11.
    Styrin, E., Luna-Reyes, L.F., Harrison, T.M.: Open data ecosystems: an international comparison. Transform. Gov. People, Process Policy 11(1), 132–156 (2017)Google Scholar
  12. 12.
    Nam, T.: Challenges and concerns of open government: a case of government 3.0 in Korea. Soc. Sci. Comput. Rev. 33(5), 556–570 (2015)CrossRefGoogle Scholar
  13. 13.
    Yang, T.-M., Lo, J., Shiang, J.: To open or not to open? Determinants of open government data. J. Inf. Sci. 41(5), 596–612 (2015)CrossRefGoogle Scholar
  14. 14.
    Verra, L.G., Karoui, M., Dudezert, A.: Adoption symbolique d’un Réseau Social pour entreprise: Le cas de Bouygues Construction. In: 17ème colloque de l’AIM, Bordeaux, France (2012)Google Scholar
  15. 15.
    Baskerville, R., Pries-Heje, J.: A multiple theory analysis of a diffusion of information technology case. Inf. Syst. J. 11(3), 181–212 (2001)CrossRefGoogle Scholar
  16. 16.
    Rogers, E.M.: Diffusion of Innovations. The Free Press, New York (1983)Google Scholar
  17. 17.
    Hameed, M.A., Counsell, S., Swift, S.: A conceptual model for the process of IT innovation adoption in organisations. J. Eng. Technol. Manage. 29(3), 358–390 (2012)CrossRefGoogle Scholar
  18. 18.
    Klonglan, G.E., Coward Jr., E.W.: The concept of symbolic adoption: a suggested interpretation. Rural Sociol. 35(1), 77–83 (1970)Google Scholar
  19. 19.
    Kwon, T.H., Zmud, R.W.: Unifying the Fragmented models of information systems implementation. In: Boland, R.J., Hirschheim, R.A. (eds.) Critical Issues in Information Systems Research, pp. 227–251. Wiley, Chichester (1987)Google Scholar
  20. 20.
    Cooper, R.B., Zmud, R.W.: Information technology implementation research: a technological diffusion approach. Manage. Sci. 36(2), 123–139 (1990)CrossRefGoogle Scholar
  21. 21.
    Rai, A., Brown, P., Tang, X.: Organisational assimilation of electronic procurement innovations. J. Manage. Inf. Syst. 26(1), 257–296 (2009)CrossRefGoogle Scholar
  22. 22.
    Swanson, E., Ramiller, N.C.: Innovating mindfully with information technology. MIS Q. 28(4), 553–583 (2004)CrossRefGoogle Scholar
  23. 23.
    Zhu, K., Kraemer, K.L., Xu, S.: The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Manage. Sci. 52(10), 1557–1576 (2006)CrossRefGoogle Scholar
  24. 24.
    Ngwenyama, O., Nielsen, P.A.: Using organizational influence processes to overcome IS implementation barriers: lessons from a longitudinal case study of SPI implementation. Eur. J. Inf. Syst. 23(2), 205–222 (2014)CrossRefGoogle Scholar
  25. 25.
    Fui-Hoon Nah, F., Tan, X., The, S.H.: An empirical investigation of end-users’ acceptance of enterprise systems. Inf. Resour. Manage, J. 17(3), 32–53 (2004)CrossRefGoogle Scholar
  26. 26.
    Grover, V., Goslar, M.D.: The initiation, adoption, and implementation of telecommunications technologies in U.S. organisations. J. Manage. Inf. Syst. 10(1), 141–163 (1983)CrossRefGoogle Scholar
  27. 27.
    Karahanna, E., Straub, D.W., Chervany, N.L.: Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q. 23(2), 183–213 (1999)CrossRefGoogle Scholar
  28. 28.
    Hofer, A.R., Hofer, C., Eroglu, C., Waller, M.A.: An institutional theoretic perspective on forces driving adoption of lean production globally: China vis-à-vis the USA. Int. J. Logist. Manage. 22(2), 148–178 (2011)CrossRefGoogle Scholar
  29. 29.
    Di Maggio, P.J., Powell, W.W.: The iron cage revisited: institutional isomorphism and collective rationality in organizational fields. Am. Sociol. Rev. 48(2), 147–160 (1983)CrossRefGoogle Scholar
  30. 30.
    Abdennadher, S., Cheffi, W.: L’adoption du vote par internet aux assemblées générales des actionnaires de sociétés cotées en France: une perspective institutionnaliste. Systèmes d’Information et Manage. 16(2), 35–71 (2011)CrossRefGoogle Scholar
  31. 31.
    Mizruchi, M.S., Fein, L.C.: The social construction of organizational knowledge: a study of the uses of coercive, mimetic, and normative isomorphism. Adm. Sci. Q. 44(4), 653–683 (1999)CrossRefGoogle Scholar
  32. 32.
    Scott, W.R.: Institutions and Organizations: Foundations for Organizational Science. Sage Publications, California (1995)Google Scholar
  33. 33.
    Slack, T., Hinings, B.: Institutional Pressures and Isomorphic Change: An Empirical test. Organ. Stud. 15(6), 803–827 (1994)CrossRefGoogle Scholar
  34. 34.
    Fusch, P.I., Ness, L.R.: Are we there yet? data saturation in qualitative research. Qual. Rep. 20(9), 1408–1416 (2015)Google Scholar
  35. 35.
    Saldaña, J.: The Coding Manual for Qualitative Researchers. Sage Publications, London (2009)Google Scholar
  36. 36.
    Bardin, L.: L’analyse de contenu. Presses Universitaires de France, Paris (2007)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Henry N. Roa
    • 1
    Email author
  • Edison Loza-Aguirre
    • 2
  • Pamela Flores
    • 2
  1. 1.Facultad de IngenieríaPontificia Universidad Católica del EcuadorQuitoEcuador
  2. 2.Facultad de Ingeniería en SistemasEscuela Politécnica NacionalQuitoEcuador

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