IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v5y2020i2p35-d341931.html
   My bibliography  Save this article

Data Quality as a Critical Success Factor for User Acceptance of Research Information Systems

Author

Listed:
  • Otmane Azeroual

    (German Center for Higher Education Research and Science Studies (DZHW), Schützenstraße 6A, 10117 Berlin, Germany
    Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
    University of Applied Sciences HTW Berlin, Wilhelminenhofstraße 75 A, 12459 Berlin, Germany)

  • Gunter Saake

    (Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany)

  • Mohammad Abuosba

    (University of Applied Sciences HTW Berlin, Wilhelminenhofstraße 75 A, 12459 Berlin, Germany)

  • Joachim Schöpfel

    (GERiiCO-Labor, University of Lille, 59650 Villeneuve-d’Ascq, France)

Abstract

In our present paper, the influence of data quality on the success of the user acceptance of research information systems (RIS) is investigated and determined. Until today, only a little research has been done on this topic and no studies have been carried out. So far, just the importance of data quality in RIS, the investigation of its dimensions and techniques for measuring, improving, and increasing data quality in RIS (such as data profiling, data cleansing, data wrangling, and text data mining) has been focused. With this work, we try to derive an answer to the question of the impact of data quality on the success of RIS user acceptance. An acceptance of RIS users is achieved when the research institutions decide to replace the RIS and replace it with a new one. The result is a statement about the extent to which data quality influences the success of users’ acceptance of RIS.

Suggested Citation

  • Otmane Azeroual & Gunter Saake & Mohammad Abuosba & Joachim Schöpfel, 2020. "Data Quality as a Critical Success Factor for User Acceptance of Research Information Systems," Data, MDPI, vol. 5(2), pages 1-13, April.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:2:p:35-:d:341931
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/5/2/35/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/5/2/35/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Azeroual, Otmane & Saake, Gunter & Schallehn, Eike, 2018. "Analyzing data quality issues in research information systems via data profiling," International Journal of Information Management, Elsevier, vol. 41(C), pages 50-56.
    2. Otmane Azeroual & Gunter Saake & Jürgen Wastl, 2018. "Data measurement in research information systems: metrics for the evaluation of data quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1271-1290, June.
    3. Otmane Azeroual & Joachim Schöpfel, 2019. "Quality Issues of CRIS Data: An Exploratory Investigation with Universities from Twelve Countries," Publications, MDPI, vol. 7(1), pages 1-18, February.
    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. Joachim Schöpfel & Stéphane Chaudiron & Bernard Jacquemin & Eric Kergosien & Hélène Prost & Florence Thiault, 2023. "The Transformation of the Green Road to Open Access," Publications, MDPI, vol. 11(2), pages 1-12, 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. Otmane Azeroual & Joachim Schöpfel & Dragan Ivanovic, 2020. "Influence of Information Quality via Implemented German RCD Standard in Research Information Systems," Data, MDPI, vol. 5(2), pages 1-10, March.
    2. Joachim Schöpfel & Stéphane Chaudiron & Bernard Jacquemin & Eric Kergosien & Hélène Prost & Florence Thiault, 2023. "The Transformation of the Green Road to Open Access," Publications, MDPI, vol. 11(2), pages 1-12, May.
    3. Otmane Azeroual, 2020. "Data Wrangling in Database Systems: Purging of Dirty Data," Data, MDPI, vol. 5(2), pages 1-9, June.
    4. Janne Pölönen & Otto Auranen, 2022. "Research performance and scholarly communication profile of competitive research funding: the case of Academy of Finland," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7415-7433, December.
    5. Otmane Azeroual & Joachim Schöpfel, 2019. "Quality Issues of CRIS Data: An Exploratory Investigation with Universities from Twelve Countries," Publications, MDPI, vol. 7(1), pages 1-18, February.
    6. Han Meng & Xiaoyu Qi & Gang Mei, 2024. "A Deep Learning Approach for Stochastic Structural Plane Generation Based on Denoising Diffusion Probabilistic Models," Mathematics, MDPI, vol. 12(13), pages 1-22, June.
    7. Yrjö Lappalainen & Matti Lassila & Tanja Heikkilä & Jani Nieminen & Tapani Lehtilä, 2023. "Migrating 120,000 Legacy Publications from Several Systems into a Current Research Information System Using Advanced Data Wrangling Techniques," Publications, MDPI, vol. 11(4), pages 1-16, November.
    8. Sandra Rousseau & Ronald Rousseau, 2021. "Bibliometric Techniques And Their Use In Business And Economics Research," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1428-1451, December.

    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:gam:jdataj:v:5:y:2020:i:2:p:35-:d:341931. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.