Navigating AI conformity: A design framework to assess fairness, explainability, and performance
Author
Abstract
Suggested Citation
DOI: 10.1007/s12525-025-00770-2
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
- Carolina Costabile & Jon Iden & Bendik Bygstad, 2022. "Building digital platform ecosystems through standardization: an institutional work approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1877-1889, December.
- Ole Hanseth & Bendik Bygstad, 2015. "Flexible generification: ICT standardization strategies and service innovation in health care," European Journal of Information Systems, Taylor & Francis Journals, vol. 24(6), pages 645-663, November.
- Abraham, Rene & Schneider, Johannes & vom Brocke, Jan, 2019. "Data governance: A conceptual framework, structured review, and research agenda," International Journal of Information Management, Elsevier, vol. 49(C), pages 424-438.
- K. Valerie Carl & Cristina Mihale-Wilson & Jan Zibuschka & Oliver Hinz, 2024. "A consumer perspective on Corporate Digital Responsibility: an empirical evaluation of consumer preferences," Journal of Business Economics, Springer, vol. 94(7), pages 979-1024, October.
- Magnani, Giovanna & Gioia, Denny, 2023. "Using the Gioia Methodology in international business and entrepreneurship research," International Business Review, Elsevier, vol. 32(2).
- repec:osf:socarx:pm3wy_v1 is not listed on IDEAS
- 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.
- Kira J.M. Matus & Michael Veale, 2022. "Certification systems for machine learning: Lessons from sustainability," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 177-196, January.
- Bill Kuechler & Vijay Vaishnavi, 2008. "On theory development in design science research: anatomy of a research project," European Journal of Information Systems, Taylor & Francis Journals, vol. 17(5), pages 489-504, October.
- Lei Wang & Ram Gopal & Ramesh Shankar & Joseph Pancras, 2022. "Forecasting venue popularity on location‐based services using interpretable machine learning," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 2773-2788, July.
- Kraus, Mathias & Feuerriegel, Stefan & Oztekin, Asil, 2020. "Deep learning in business analytics and operations research: Models, applications and managerial implications," European Journal of Operational Research, Elsevier, vol. 281(3), pages 628-641.
- Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
- Fahmida E. Moula & Chi Guotai & Mohammad Zoynul Abedin, 2017. "Credit default prediction modeling: an application of support vector machine," Risk Management, Palgrave Macmillan, vol. 19(2), pages 158-187, May.
- Moritz Zahn & Stefan Feuerriegel & Niklas Kuehl, 2022. "The Cost of Fairness in AI: Evidence from E-Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 335-348, June.
- Ron Iphofen & Mihalis Kritikos, 2021. "Regulating artificial intelligence and robotics: ethics by design in a digital society," Contemporary Social Science, Taylor & Francis Journals, vol. 16(2), pages 170-184, March.
- Robin Hirt & Niklas Kühl & Gerhard Satzger, 2019. "Cognitive computing for customer profiling: meta classification for gender prediction," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 93-106, March.
- Smith, James F, 1977. "The Equal Credit Opportunity Act of 1974: A Cost/Benefit Analysis," Journal of Finance, American Finance Association, vol. 32(2), pages 609-622, May.
- Nic Fleming, 2018. "How artificial intelligence is changing drug discovery," Nature, Nature, vol. 557(7707), pages 55-57, 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.- Maisa Cardoso Aniceto & Flavio Barboza & Herbert Kimura, 2020. "Machine learning predictivity applied to consumer creditworthiness," Future Business Journal, Springer, vol. 6(1), pages 1-14, December.
- Keding, Christoph & Meissner, Philip, 2021. "Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
- Vítor Ribeiro & João Barata & Paulo Rupino Cunha, 2024. "Modeling inter-organizational business process governance in the age of collaborative networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-27, December.
- Moritz Zahn & Stefan Feuerriegel & Niklas Kuehl, 2022. "The Cost of Fairness in AI: Evidence from E-Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 335-348, June.
- Philippe Jardin, 2025. "Designing Ensemble-Based Models Using Neural Networks and Temporal Financial Profiles to Forecast Firms’ Financial Failure," Computational Economics, Springer;Society for Computational Economics, vol. 65(1), pages 149-209, January.
- Lucian Belascu & Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu, 2021. "Performance Dissimilarities in European Union Manufacturing: The Effect of Ownership and Technological Intensity," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
- Stefan Feuerriegel & Mateusz Dolata & Gerhard Schwabe, 2020. "Fair AI," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 379-384, August.
- Yoganathan, Vignesh & Osburg, Victoria-Sophie, 2024. "The mind in the machine: Estimating mind perception's effect on user satisfaction with voice-based conversational agents," Journal of Business Research, Elsevier, vol. 175(C).
- Abedin, Mohammad Zoynul & Hajek, Petr & Sharif, Taimur & Satu, Md. Shahriare & Khan, Md. Imran, 2023. "Modelling bank customer behaviour using feature engineering and classification techniques," Research in International Business and Finance, Elsevier, vol. 65(C).
- Gahm, Christian & Uzunoglu, Aykut & Wahl, Stefan & Ganschinietz, Chantal & Tuma, Axel, 2022. "Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning," European Journal of Operational Research, Elsevier, vol. 296(3), pages 819-836.
- Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
- Tobias Götze & Marc Gürtler & Eileen Witowski, 2020. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 428-446, September.
- Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
- Roy Cerqueti & Francesca Pampurini & Annagiulia Pezzola & Anna Grazia Quaranta, 2022. "Dangerous liasons and hot customers for banks," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 65-89, July.
- Klockmann, Victor & von Schenk, Alicia & Villeval, Marie Claire, 2022.
"Artificial intelligence, ethics, and intergenerational responsibility,"
Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 284-317.
- Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021. "Artificial Intelligence, Ethics, and Intergenerational Responsibility," Working Papers halshs-03237437, HAL.
- Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021. "Artificial Intelligence, Ethics, and Intergenerational Responsibility," Working Papers 2110, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
- Klockmann, Victor & von Schenk, Alicia & Villeval, Marie-Claire, 2022. "Artificial intelligence, ethics, and intergenerational responsibility," SAFE Working Paper Series 335, Leibniz Institute for Financial Research SAFE.
- Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2022. "Artificial Intelligence, Ethics, and Intergenerational Responsibility," Post-Print hal-03778525, HAL.
- Sievert, Martin & Vogel, Dominik & Döring, Matthias, 2024. "Gendered Language in Job Advertisements Relates to Gender Sorting in Public Labor Markets: A Multi-Source Analysis," SocArXiv u6z5e, Center for Open Science.
- repec:iim:iimawp:14638 is not listed on IDEAS
- Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2019. "Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?," Working Papers 201980, University of Pretoria, Department of Economics.
- Bhattacharya, Sourabh & Govindan, Kannan & Ghosh Dastidar, Surajit & Sharma, Preeti, 2024. "Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
- Justyna Łapińska & Iwona Escher & Joanna Górka & Agata Sudolska & Paweł Brzustewicz, 2021. "Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland," Energies, MDPI, vol. 14(7), pages 1-20, April.
- Steven Heston & Nitish R. Sinha, 2016. "News versus Sentiment : Predicting Stock Returns from News Stories," Finance and Economics Discussion Series 2016-048, Board of Governors of the Federal Reserve System (U.S.).
More about this item
Keywords
Machine learning; Algorithmic fairness; Explainable AI; Certification; AI auditing; Impact assessment;All these keywords.
JEL classification:
- M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
- O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
Statistics
Access and download statisticsCorrections
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:35:y:2025:i:1:d:10.1007_s12525-025-00770-2. 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.