IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/vyid10.1007_s10796-016-9686-2.html
   My bibliography  Save this article

Big data in the public sector: Uncertainties and readiness

Author

Listed:
  • Bram Klievink

    (Delft University of Technology)

  • Bart-Jan Romijn

    (Delft University of Technology)

  • Scott Cunningham

    (Delft University of Technology)

  • Hans Bruijn

    (Delft University of Technology)

Abstract

Big data is being implemented with success in the private sector and science. Yet the public sector seems to be falling behind, despite the potential value of big data for government. Government organizations do recognize the opportunities of big data but seem uncertain about whether they are ready for the introduction of big data, and if they are adequately equipped to use big data. This paper addresses those uncertainties. It presents an assessment framework for evaluating public organizations’ big data readiness. Doing so demystifies the concept of big data, as it is expressed in terms of specific and measureable organizational characteristics. The framework was tested by applying it to organizations in the Dutch public sector. The results suggest that organizations may be technically capable of using big data, but they will not significantly gain from these activities if the applications do not fit their organizations and main statutory tasks. The framework proved helpful in pointing out areas where public sector organizations could improve, providing guidance on how government can become more big data ready in the future.

Suggested Citation

  • Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 0. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
  • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-016-9686-2
    DOI: 10.1007/s10796-016-9686-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-016-9686-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10796-016-9686-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marijn Janssen & Haiko Voort & Anne Fleur Veenstra, 2015. "Failure of large transformation projects from the viewpoint of complex adaptive systems: Management principles for dealing with project dynamics," Information Systems Frontiers, Springer, vol. 17(1), pages 15-29, February.
    2. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    3. Kathleen M. Eisenhardt & Jeffrey A. Martin, 2000. "Dynamic capabilities: what are they?," Strategic Management Journal, Wiley Blackwell, vol. 21(10‐11), pages 1105-1121, October.
    4. Atreyi Kankanhalli & Jungpil Hahn & Sharon Tan & Gordon Gao, 2016. "Big data and analytics in healthcare: Introduction to the special section," Information Systems Frontiers, Springer, vol. 18(2), pages 233-235, April.
    5. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    6. Chittaranjan Hota & Shambhu Upadhyaya & Jamal Nazzal Al-Karaki, 2015. "Advances in secure knowledge management in the big data era," Information Systems Frontiers, Springer, vol. 17(5), pages 983-986, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 2017. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 19(2), pages 267-283, April.
    2. Keshav Singh Rawat & Sandeep Kumar Sood, 2021. "Emerging trends and global scope of big data analytics: a scientometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1371-1396, August.
    3. Marijn Janssen & David Konopnicki & Jane L. Snowdon & Adegboyega Ojo, 0. "Driving public sector innovation using big and open linked data (BOLD)," Information Systems Frontiers, Springer, vol. 0, pages 1-7.
    4. Palma Lampreia Dos Santos, Maria José, 2018. "Nowcasting and forecasting aquaponics by Google Trends in European countries," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 178-185.
    5. Qizhi Tao & Yizhe Dong & Ziming Lin, 0. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    6. Nam, Dalwoo & Lee, Junyeong & Lee, Heeseok, 2019. "Business analytics use in CRM: A nomological net from IT competence to CRM performance," International Journal of Information Management, Elsevier, vol. 45(C), pages 233-245.
    7. E. Raguseo & Pigni, F. & Claudio Vitari, 2021. "Streams of digital data and competitive advantage: The mediation effects of process efficiency and product effectiveness," Post-Print hal-03323663, HAL.
    8. Olivia Benfeldt & John Stouby Persson & Sabine Madsen, 2020. "Data Governance as a Collective Action Problem," Information Systems Frontiers, Springer, vol. 22(2), pages 299-313, April.
    9. E. Raguseo & Pigni, F. & Claudio Vitari, 2021. "Streams of digital data and competitive advantage: The mediation effects of process efficiency and product effectiveness," Grenoble Ecole de Management (Post-Print) hal-03323663, HAL.
    10. Olivia Benfeldt & John Stouby Persson & Sabine Madsen, 0. "Data Governance as a Collective Action Problem," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    11. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    12. Lawarée, Justin & Jacob, Steve & Ouimet, Mathieu, 2020. "A scoping review of knowledge syntheses in the field of evaluation across four decades of practice," Evaluation and Program Planning, Elsevier, vol. 79(C).
    13. Peter M. Bednar & Christine Welch, 2020. "Socio-Technical Perspectives on Smart Working: Creating Meaningful and Sustainable Systems," Information Systems Frontiers, Springer, vol. 22(2), pages 281-298, April.
    14. Sarah Giest & Annemarie Samuels, 2020. "‘For good measure’: data gaps in a big data world," Policy Sciences, Springer;Society of Policy Sciences, vol. 53(3), pages 559-569, September.
    15. Peter M. Bednar & Christine Welch, 0. "Socio-Technical Perspectives on Smart Working: Creating Meaningful and Sustainable Systems," Information Systems Frontiers, Springer, vol. 0, pages 1-18.
    16. Sarah Giest, 2017. "Big data for policymaking: fad or fasttrack?," Policy Sciences, Springer;Society of Policy Sciences, vol. 50(3), pages 367-382, September.
    17. Liliane Manny & Mert Duygan & Manuel Fischer & Jörg Rieckermann, 2021. "Barriers to the digital transformation of infrastructure sectors," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(4), pages 943-983, December.
    18. Marijn Janssen & David Konopnicki & Jane L. Snowdon & Adegboyega Ojo, 2017. "Driving public sector innovation using big and open linked data (BOLD)," Information Systems Frontiers, Springer, vol. 19(2), pages 189-195, April.
    19. Elvin Shava & Shikha Vyas-Doorgapersad, 2022. "Fostering digital innovations to accelerate service delivery in South African Local Government," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(2), pages 83-91, March.
    20. Roel Heijlen & Joep Crompvoets & Geert Bouckaert & Maxim Chantillon, 2018. "Evolving Government Information Processes for Service Delivery: Identifying Types & Impact," Administrative Sciences, MDPI, vol. 8(2), pages 1-14, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 2017. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 19(2), pages 267-283, April.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. Claudio Vitari & Elisabetta Raguseo, 2016. "Big data value and financial performance: an empirical investigation [Digital data, dynamic capability and financial performance: an empirical investigation in the era of Big Data]," Post-Print halshs-01923271, HAL.
    4. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    5. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Post-Print hal-03032504, HAL.
    6. Mónica Santana & Mirta Díaz-Fernández, 2023. "Competencies for the artificial intelligence age: visualisation of the state of the art and future perspectives," Review of Managerial Science, Springer, vol. 17(6), pages 1971-2004, August.
    7. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Gupta, Shivam & Sivarajah, Uthayasankar & Bag, Surajit, 2023. "Assessing the impact of big data analytics on decision-making processes, forecasting, and performance of a firm," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    8. Qizhi Tao & Yizhe Dong & Ziming Lin, 0. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    9. Yogesh K. Dwivedi & Marijn Janssen & Emma L. Slade & Nripendra P. Rana & Vishanth Weerakkody & Jeremy Millard & Jan Hidders & Dhoya Snijders, 0. "Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    10. Yan Mandy Dang & Yulei Gavin Zhang & James Morgan, 2017. "Integrating switching costs to information systems adoption: An empirical study on learning management systems," Information Systems Frontiers, Springer, vol. 19(3), pages 625-644, June.
    11. Zeng, Huixiang & Ran, Hangxin & Zhou, Qiong & Jin, Youliang & Cheng, Xu, 2022. "The financial effect of firm digitalization: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    12. Raguseo, Elisabetta & Vitari, Claudio & Pigni, Federico, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," International Journal of Production Economics, Elsevier, vol. 229(C).
    13. Yan Mandy Dang & Yulei Gavin Zhang & James Morgan, 0. "Integrating switching costs to information systems adoption: An empirical study on learning management systems," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    14. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    15. Giorgi Shuradze & Yevgen Bogodistov & Heinz-Theo Wagner, 2018. "The Role Of Marketing-Enabled Data Analytics Capability And Organisational Agility For Innovation: Empirical Evidence From German Firms," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-32, May.
    16. Claudio Vitari & Elisabetta Raguseo, 2016. "Big data value and financial performance: an empirical investigation [Digital data, dynamic capability and financial performance: an empirical investigation in the era of Big Data]," Grenoble Ecole de Management (Post-Print) halshs-01923271, HAL.
    17. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    18. Yogesh K. Dwivedi & Marijn Janssen & Emma L. Slade & Nripendra P. Rana & Vishanth Weerakkody & Jeremy Millard & Jan Hidders & Dhoya Snijders, 2017. "Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling," Information Systems Frontiers, Springer, vol. 19(2), pages 197-212, April.
    19. Caesarius, Leon Michael & Hohenthal, Jukka, 2018. "Searching for big data," Scandinavian Journal of Management, Elsevier, vol. 34(2), pages 129-140.
    20. Elisabetta Raguseo & Claudio Vitari & Federico Pigni, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," Grenoble Ecole de Management (Post-Print) hal-03032504, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-016-9686-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.