IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v33y2023i1d10.1007_s12525-023-00644-5.html
   My bibliography  Save this article

Explainable artificial intelligence in information systems: A review of the status quo and future research directions

Author

Listed:
  • Julia Brasse

    (University of Ulm)

  • Hanna Rebecca Broder

    (University of Ulm)

  • Maximilian Förster

    (University of Ulm)

  • Mathias Klier

    (University of Ulm)

  • Irina Sigler

    (University of Ulm)

Abstract

The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented.

Suggested Citation

  • Julia Brasse & Hanna Rebecca Broder & Maximilian Förster & Mathias Klier & Irina Sigler, 2023. "Explainable artificial intelligence in information systems: A review of the status quo and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-30, December.
    • Handle: RePEc:spr:elmark:v:33:y:2023:i:1:d:10.1007_s12525-023-00644-5
    DOI: 10.1007/s12525-023-00644-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-023-00644-5
    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/s12525-023-00644-5?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. Jannis Beese & M. Kazem Haki & Stephan Aier & Robert Winter, 2019. "Simulation-Based Research in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 503-521, August.
    2. Ingrid Bauer & Liudmila Zavolokina & Gerhard Schwabe, 2020. "Is there a market for trusted car data?," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(2), pages 211-225, June.
    3. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    4. Martin Adam & Michael Wessel & Alexander Benlian, 2021. "AI-based chatbots in customer service and their effects on user compliance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 427-445, June.
    5. John Venable & Jan Pries-Heje & Richard Baskerville, 2016. "FEDS: a Framework for Evaluation in Design Science Research," European Journal of Information Systems, Taylor & Francis Journals, vol. 25(1), pages 77-89, January.
    6. Nelson Granados & Alok Gupta & Robert J. Kauffman, 2010. "Research Commentary---Information Transparency in Business-to-Consumer Markets: Concepts, Framework, and Research Agenda," Information Systems Research, INFORMS, vol. 21(2), pages 207-226, June.
    7. Christian Meske & Babak Abedin & Mathias Klier & Fethi Rabhi, 2022. "Explainable and responsible artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2103-2106, December.
    8. Martens, David & Baesens, Bart & Van Gestel, Tony & Vanthienen, Jan, 2007. "Comprehensible credit scoring models using rule extraction from support vector machines," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1466-1476, December.
    9. Venkata Marella & Bikesh Upreti & Jani Merikivi & Virpi Kristiina Tuunainen, 2020. "Understanding the creation of trust in cryptocurrencies: the case of Bitcoin," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(2), pages 259-271, June.
    10. Kevin Bauer & Oliver Hinz & Wil Aalst & Christof Weinhardt, 2021. "Expl(AI)n It to Me – Explainable AI and Information Systems Research," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(2), pages 79-82, April.
    11. Frantz Rowe, 2014. "What literature review is not: diversity, boundaries and recommendations," European Journal of Information Systems, Taylor & Francis Journals, vol. 23(3), pages 241-255, May.
    12. Florian Probst & Laura Grosswiele & Regina Pfleger, 2013. "Who will lead and who will follow: Identifying Influential Users in Online Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 179-193, June.
    13. Zhang, Chanyuan (Abigail) & Cho, Soohyun & Vasarhelyi, Miklos, 2022. "Explainable Artificial Intelligence (XAI) in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
    14. Bastos, João A. & Matos, Sara M., 2022. "Explainable models of credit losses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 386-394.
    15. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    Full references (including those not matched with items on IDEAS)

    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. Raffaele Fabio Ciriello & Alexandra Cecilie Gjøl Torbensen & Magnus Rotvit Perlt Hansen & Christoph Müller-Bloch, 2023. "Blockchain-based digital rights management systems: Design principles for the music industry," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
    2. Milad Mirbabaie & Felix Brünker & Nicholas R. J. Möllmann Frick & Stefan Stieglitz, 2022. "The rise of artificial intelligence – understanding the AI identity threat at the workplace," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 73-99, March.
    3. René Riedl, 2022. "Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2021-2051, December.
    4. Rainer Alt, 2021. "Electronic Markets on digital platforms and AI," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 233-241, June.
    5. Rainer Alt, 2022. "Electronic Markets on AI and standardization," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1795-1805, December.
    6. Roger W.H. Bons & Johan Versendaal & Liudmila Zavolokina & Weidong Larry Shi, 2020. "Potential and limits of Blockchain technology for networked businesses," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(2), pages 189-194, June.
    7. Albanese, Massimo, 2023. "Reviewing literature through multidimensional representations," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    8. Niklas Kühl & Max Schemmer & Marc Goutier & Gerhard Satzger, 2022. "Artificial intelligence and machine learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2235-2244, December.
    9. Nora Nahr & Marikka Heikkilä, 2022. "Uncovering the identity of Electronic Markets research through text mining techniques," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1257-1277, September.
    10. Aliya Tastemirova & Johannes Schneider & Leona Chandra Kruse & Simon Heinzle & Jan vom Brocke, 2022. "Microexpressions in digital humans: perceived affect, sincerity, and trustworthiness," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1603-1620, September.
    11. Ferdinand Thies & Sören Wallbach & Michael Wessel & Markus Besler & Alexander Benlian, 2022. "Initial coin offerings and the cryptocurrency hype - the moderating role of exogenous and endogenous signals," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1691-1705, September.
    12. Berahmand, Kamal & Bouyer, Asgarali & Samadi, Negin, 2018. "A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 41-54.
    13. Ting Li & Robert J. Kauffman & Eric van Heck & Peter Vervest & Benedict G. C. Dellaert, 2014. "Consumer Informedness and Firm Information Strategy," Information Systems Research, INFORMS, vol. 25(2), pages 345-363, June.
    14. Li, Yibei & Wang, Ximei & Djehiche, Boualem & Hu, Xiaoming, 2020. "Credit scoring by incorporating dynamic networked information," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1103-1112.
    15. Loterman, Gert & Brown, Iain & Martens, David & Mues, Christophe & Baesens, Bart, 2012. "Benchmarking regression algorithms for loss given default modeling," International Journal of Forecasting, Elsevier, vol. 28(1), pages 161-170.
    16. Yuxuan Li & Xin Miao & Dequan Zheng & Yanhong Tang, 2019. "Corporate Public Transparency on Financial Performance: The Moderating Role of Political Embeddedness," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    17. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    18. Jadbabaie, Ali & Kakhbod, Ali, 2019. "Optimal contracting in networks," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1094-1153.
    19. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring," European Journal of Operational Research, Elsevier, vol. 195(3), pages 942-959, June.
    20. Talan, Amogh & Rao, Amar & Sharma, Gagan Deep & Apostu, Simona-Andreea & Abbas, Shujaat, 2023. "Transition towards clean energy consumption in G7: Can financial sector, ICT and democracy help?," Resources Policy, Elsevier, vol. 82(C).

    More about this item

    Keywords

    Explainable artificial intelligence; Explainable machine learning; Comprehensible artificial intelligence; Comprehensible machine learning; Literature review;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

    Statistics

    Access and download statistics

    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:elmark:v:33:y:2023:i:1:d:10.1007_s12525-023-00644-5. 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.