Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Drivers of Dissatisfaction with an Open Government Data Portal: A Critical Incident Technique Approach

  • Conference paper
  • First Online:
Electronic Government (EGOV 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14130))

Included in the following conference series:

  • 674 Accesses

Abstract

Open government data (OGD) has emerged as a crucial aspect of digital transformation strategies, prompting many governments to establish national OGD portals to facilitate access to large amounts of public sector datasets. However, despite the OGD portals’ goal of serving as intermediaries between OGD producers and OGD users, they have faced numerous criticisms for their low use and failure to adequately meet users’ needs. The lack of consensus within the OGD community on the sources of dissatisfaction with the OGD portals and their negative impact on their use warrants a detailed examination of users’ dissatisfying experiences. Taking a user-centred perspective, I adopt a critical incident technique (CIT) approach to identify the drivers and sources of dissatisfaction with a national OGD portal. Based on my analysis, a descriptive model is proposed to help to comprehend the interrelations between three sources of dissatisfaction with the OGD portal and ten respective drivers: OGD production (i.e., development of high-quality datasets, completeness of the metadata), OGD distribution (i.e., accessibility of the datasets, organisation of the datasets, centralisation of the datasets, search engine, interface, visualisation), and OGD use (i.e., skills and knowledge, and added value).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Jetzek, T., Avital, M., Bjorn-Andersen, N.: The sustainable value of open government data. J. Assoc. Inf. Syst. 20(6), 702–734 (2019)

    Google Scholar 

  2. Nikiforova, A., McBride, K.: Open government data portal usability: a user-centred usability analysis of 41 open government data portals. Telematics Inform. 58(101539), 1–13 (2021)

    Google Scholar 

  3. Zhao, Y.P., Fan, B.: Exploring open government data capacity of government agency: based on the resource-based theory. Gov. Inf. Q. 35(1), 1–12 (2018)

    MathSciNet  Google Scholar 

  4. Máchová, R., Hub, M., Lněnička, M.: Usability evaluation of open data portals: evaluating data discoverability, accessibility, and reusability from a stakeholders’ perspective. Aslib J. Inf. Manag. 70(3), 252–268 (2018)

    Google Scholar 

  5. Janssen, M., Charalabidis, Y., Zuiderwijk, A.: Benefits, adoption barriers and myths of open data and open government. Inf. Syst. Manag. 29(4), 258–268 (2012)

    Google Scholar 

  6. Nikiforova, A., Lněnička, M.: A multi-perspective knowledge-driven approach for analysis of the demand side of the open government data portal. Gov. Inf. Q. 38(4), 1–19 (2021)

    Google Scholar 

  7. Martin, C.: Barriers to the open government data agenda: taking a multi-level perspective. Policy Internet 6(3), 217–239 (2014)

    Google Scholar 

  8. Gascó-Hernández, M., Martin, E.G., Reggi, L., Pyo, S., Luna-Reyes, L.F.: Promoting the use of open government data: cases of training and engagement. Gov. Inf. Q. 35(2), 233–242 (2018)

    Google Scholar 

  9. Ruijer, E., Grimmelikhuijsen, S., Meijer, A.: Open data for democracy: developing a theoretical framework for open data use. Gov. Inf. Q. 34(1), 45–52 (2017)

    Google Scholar 

  10. Quarati, A.: Open government data: usage trends and metadata quality. J. Inf. Sci. 49, 1–24 (2021)

    Google Scholar 

  11. Hughes, D.L., Rana, N.P., Simintiras, A.C.: The changing landscape of IS project failure: an examination of the key factors. J. Enterp. Inf. Manag. 30(1), 142–165 (2017)

    Google Scholar 

  12. Osagie, E., Waqar, M., Adebayo, S., Stasiewicz, A., Porwol, L., Ojo, A.: Usability evaluation of an open data platform. In: International Conference on Digital Government Research, pp. 495–504. ACM (2017)

    Google Scholar 

  13. OECD, GovLab: Open Data in Action - Initiatives During the Initial Stage of the COVID-19 Pandemic (2021)

    Google Scholar 

  14. Office fédéral de la statistique: Besoins et Attentes dans l’Utilisation et la Mise à Disposition de Données Publiques Ouvertes en Suisse - Résultats de l'Enquête Open Government Data 2022. In: Département fédéral de l’intérieur (ed.), pp. 1–25, Neuchâtel (2022)

    Google Scholar 

  15. Lassinantti, J., Ståhlbröst, A., Runardotter, M.: Relevant social groups for open data use and engagement. Gov. Inf. Q. 36(1), 98–111 (2019)

    Google Scholar 

  16. Susha, I., Grönlund, Å., Janssen, M.: Driving factors of service innovation using open government data: an exploratory study of entrepreneurs in two countries. Inf. Polity 20(1), 19–34 (2015)

    Google Scholar 

  17. Bhattacherjee, A.: Understanding information systems continuance: an expectation-confirmation model. MIS Q. 25(3), 351–370 (2001)

    Google Scholar 

  18. Schwarz, C.: Understanding the Role of Expectation Disconfirmation Theory on IT Outsourcing Success, Louisiana (2011)

    Google Scholar 

  19. Schwarz, C., Schwarz, A., Black, W.C.: Examining the impact of multicollinearity in discovering higher-order factor models. Commun. Assoc. Inf. Syst. 34(1), 1191–1208 (2014)

    Google Scholar 

  20. Brown, S.A., Venkatesh, V., Goyal, S.: Expectation confirmation in information systems research: a test of six competing models. MIS Q. 38(3), 729–756 (2014)

    Google Scholar 

  21. Premkumar, G., Bhattacherjee, A.: Explaining information technology usage: a test of competing models. Omega 36(1), 64–75 (2008)

    Google Scholar 

  22. Oliver, R.L.: A cognitive model of the antecedents and consequences of satisfaction decisions. J. Mark. Res. 17(4), 460–469 (1980)

    Google Scholar 

  23. Lankton, N.K., McKnight, H.D.: Examining two expectation disconfirmation theory models: assimilation and asymmetry effects. J. Assoc. Inf. Syst. 13(2), 88–115 (2012)

    Google Scholar 

  24. Oliver, R.L.: Satisfaction: A Behavioral Perspective on the Consumer (2014)

    Google Scholar 

  25. Wang, H.-J., Jin, L.: Adoption of open government data among government agencies. Gov. Inf. Q. 33(1), 80–88 (2016)

    MathSciNet  Google Scholar 

  26. Kaasenbrood, M., Zuiderwijk, A., Janssen, M., de Jong, M., Bharosa, N.: Exploring the factors influencing the adoption of open government data by private organisations. Int. J. Public Adm. Digit. Age 2(2), 75–92 (2015)

    Google Scholar 

  27. Jetzek, T., Avital, M., Bjorn-Andersen, N.: Data-driven innovation through open government data. J. Theor. Appl. Electron. Commer. Res. 9(2), 100–120 (2014)

    Google Scholar 

  28. Bhattacherjee, A., Lin, C.-P.: A unified model of it continuance: three complementary perspectives and crossover effects. Eur. J. Inf. Syst. 24(4), 364–373 (2015)

    Google Scholar 

  29. McBride, K., Aavik, G., Toots, M., Kalvet, T., Krimmer, R.: How does open government data driven co-creation occur? six factors and a ‘perfect storm’; insights from Chicagos’ food inspection forecasting model. Gov. Inf. Q. 36(1), 88–97 (2019)

    Google Scholar 

  30. D'Emidio, T., Wagner, J.: Understanding the Customer Experience with Government. McKinsey & Company (2018)

    Google Scholar 

  31. Flanagan, J.: The critical incident technique. Psychol. Bull. 51(4), 327–358 (1954)

    Google Scholar 

  32. Holloway, B.-B., Beatty, S.E.: Satisfiers and dissatisfiers in the online environment: a critical incident assessment. J. Serv. Res. 10(4), 347–364 (2008)

    Google Scholar 

  33. Gremler, D.D.: The critical incident technique in service research. J. Serv. Res. 7(1), 65–89 (2004)

    Google Scholar 

  34. FitzGerlad, K., Seale, N.S., Kerins, C.A., McElvaney, R.: The critical incident technique: a useful tool for conducting qualitative research. J. Dent. Educ. 72(3), 299–304 (2008)

    Google Scholar 

  35. CKAN Homepage. https://ckan.org/. Accessed 16 Mar 2023

  36. Creswell, J.W., Poth, C.N.: Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Sage Publications Inc., Thousand Oaks (2016)

    Google Scholar 

  37. Hsieh, H.F., Shannon, S.E.: Three approaches to qualitative content analysis. Qual. Health Res. 15(9), 1277–1288 (2005)

    Google Scholar 

  38. Urquhart, C., et al.: Critical incident technique and explicitation interviewing in studies of information behavior. Libr. Inf. Sci. Res. 25(1), 63–88 (2003)

    Google Scholar 

  39. Hock, S.H., Malcus, L., Hasher, L.: Frequency discrimination: assessing global-level and element-level units in memory. J. Exp. Psychol. 12(2), 232–240 (1986)

    Google Scholar 

  40. Woodley-Zanthos, P., Ellis, N.R.: Memory of frequency of occurrence: intelligence level and retrieval cues. Intelligence 13(1), 53–61 (1989)

    Google Scholar 

  41. Islam, A.K.M.N.: Sources of satisfaction and dissatisfaction with a learning management system in post adoption stage: a critical incident technique approach. Comput. Hum. Behav. 30, 249–261 (2014)

    Google Scholar 

  42. Chan, J.K., Baum, T.: Determination of satisfiers and dissatisfiers using Herzberg’s motivator and hygiene factor theory: an exploratory study. Tour. Cult. Commun. 7(2), 117–131 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alizée Francey .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Francey, A. (2023). Drivers of Dissatisfaction with an Open Government Data Portal: A Critical Incident Technique Approach. In: Lindgren, I., et al. Electronic Government. EGOV 2023. Lecture Notes in Computer Science, vol 14130. Springer, Cham. https://doi.org/10.1007/978-3-031-41138-0_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-41138-0_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41137-3

  • Online ISBN: 978-3-031-41138-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics