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Explainable AI: from black box to glass box

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Cited by:

  1. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
  2. Alex Mari & Andreina Mandelli & René Algesheimer, 2023. "Shopping with Voice Assistants: How Empathy Affects Individual and Family Decision-Making Outcomes," Working Papers 399, University of Zurich, Department of Business Administration (IBW).
  3. Shahriar Akter & Katina Michael & Muhammad Rajib Uddin & Grace McCarthy & Mahfuzur Rahman, 2022. "Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics," Annals of Operations Research, Springer, vol. 308(1), pages 7-39, January.
  4. Aitken, Mhairi & Ng, Magdalene & Horsfall, Dave & Coopamootoo, Kovila P.L. & van Moorsel, Aad & Elliott, Karen, 2021. "In pursuit of socially-minded data-intensive innovation in banking: A focus group study of public expectations of digital innovation in banking," Technology in Society, Elsevier, vol. 66(C).
  5. Grewal, Dhruv & Gauri, Dinesh K. & Roggeveen, Anne L. & Sethuraman, Raj, 2021. "Strategizing Retailing in the New Technology Era," Journal of Retailing, Elsevier, vol. 97(1), pages 6-12.
  6. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
  7. Henner Gimpel & Vanessa Graf-Seyfried & Robert Laubacher & Oliver Meindl, 2023. "Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing," Group Decision and Negotiation, Springer, vol. 32(1), pages 75-124, February.
  8. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
  9. Pascal Hamm & Michael Klesel & Patricia Coberger & H. Felix Wittmann, 2023. "Explanation matters: An experimental study on explainable AI," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
  10. Alantari, Huwail J. & Currim, Imran S. & Deng, Yiting & Singh, Sameer, 2022. "An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 1-19.
  11. Jie Tao & Lina Zhou & Kevin Hickey, 2023. "Making sense of the black‐boxes: Toward interpretable text classification using deep learning models," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(6), pages 685-700, June.
  12. Denis Dennehy & Anastasia Griva & Nancy Pouloudi & Yogesh K. Dwivedi & Matti Mäntymäki & Ilias O. Pappas, 2023. "Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI," Information Systems Frontiers, Springer, vol. 25(1), pages 1-7, February.
  13. Siala, Haytham & Wang, Yichuan, 2022. "SHIFTing artificial intelligence to be responsible in healthcare: A systematic review," Social Science & Medicine, Elsevier, vol. 296(C).
  14. Xiaohui Zhang & Qianzhou Du & Zhongju Zhang, 2022. "A theory‐driven machine learning system for financial disinformation detection," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3160-3179, August.
  15. Valeria D’Amato & Rita D’Ecclesia & Susanna Levantesi, 2022. "ESG score prediction through random forest algorithm," Computational Management Science, Springer, vol. 19(2), pages 347-373, June.
  16. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.
  17. Jana Gerlach & Paul Hoppe & Sarah Jagels & Luisa Licker & Michael H. Breitner, 2022. "Decision support for efficient XAI services - A morphological analysis, business model archetypes, and a decision tree," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2139-2158, December.
  18. Zhu, John Jianjun & Chang, Yung-Chun & Ku, Chih-Hao & Li, Stella Yiyan & Chen, Chi-Jen, 2021. "Online critical review classification in response strategy and service provider rating: Algorithms from heuristic processing, sentiment analysis to deep learning," Journal of Business Research, Elsevier, vol. 129(C), pages 860-877.
  19. Trocin, Cristina & Hovland, Ingrid Våge & Mikalef, Patrick & Dremel, Christian, 2021. "How Artificial Intelligence affords digital innovation: A cross-case analysis of Scandinavian companies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
  20. Dhruv Grewal & John Hulland & Praveen K. Kopalle & Elena Karahanna, 2020. "The future of technology and marketing: a multidisciplinary perspective," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 1-8, January.
  21. Söderlund, Magnus, 2023. "Service robot verbalization in service processes with moral implications and its impact on satisfaction," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
  22. Vinay Singh & Brijesh Nanavati & Arpan Kumar Kar & Agam Gupta, 2023. "How to Maximize Clicks for Display Advertisement in Digital Marketing? A Reinforcement Learning Approach," Information Systems Frontiers, Springer, vol. 25(4), pages 1621-1638, August.
  23. Ben Allen & Morgan Lane & Elizabeth Anderson Steeves & Hollie Raynor, 2022. "Using Explainable Artificial Intelligence to Discover Interactions in an Ecological Model for Obesity," IJERPH, MDPI, vol. 19(15), pages 1-13, August.
  24. Beeler, Lisa & Zablah, Alex R. & Rapp, Adam, 2022. "Ability is in the eye of the beholder: How context and individual factors shape consumer perceptions of digital assistant ability," Journal of Business Research, Elsevier, vol. 148(C), pages 33-46.
  25. Erik Hermann, 2022. "Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective," Journal of Business Ethics, Springer, vol. 179(1), pages 43-61, August.
  26. Manjunath Padigar & Ljubomir Pupovac & Ashish Sinha & Rajendra Srivastava, 2022. "The effect of marketing department power on investor responses to announcements of AI-embedded new product innovations," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1277-1298, November.
  27. 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.
  28. Jacob Dexe & Ulrik Franke & Kasia Söderlund & Niels Berkel & Rikke Hagensby Jensen & Nea Lepinkäinen & Juho Vaiste, 2022. "Explaining automated decision-making: a multinational study of the GDPR right to meaningful information," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 669-697, July.
  29. Elena Mazurova & Willem Standaert & Esko Penttinen & Felix Ter Chian Tan, 2022. "Paradoxical Tensions Related to AI-Powered Evaluation Systems in Competitive Sports," Information Systems Frontiers, Springer, vol. 24(3), pages 897-922, June.
  30. Satornino, Cinthia B. & Grewal, Dhruv & Guha, Abhijit & Schweiger, Elisa B. & Goodstein, Ronald C., 2023. "The perks and perils of artificial intelligence use in lateral exchange markets," Journal of Business Research, Elsevier, vol. 158(C).
  31. Linda Hagen & Kosuke Uetake & Nathan Yang & Bryan Bollinger & Allison J. B. Chaney & Daria Dzyabura & Jordan Etkin & Avi Goldfarb & Liu Liu & K. Sudhir & Yanwen Wang & James R. Wright & Ying Zhu, 2020. "How can machine learning aid behavioral marketing research?," Marketing Letters, Springer, vol. 31(4), pages 361-370, December.
  32. Janasz, Tomasz & Mortensen, Peter & Reisswig, Christian & Weller, Tobias & Herrmann, Maximilian & Crnoja, Ivona & Höhne, Johannes, 2021. "Advancements in ML-Enabled Intelligent Document Processing and How to Overcome Adoption Challenges in Enterprises," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 75(3), pages 340-358.
  33. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
  34. Benjamin M. Abdel-Karim & Nicolas Pfeuffer & Oliver Hinz, 2021. "Machine learning in information systems - a bibliographic review and open research issues," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 643-670, September.
  35. Florian Pethig & Julia Kroenung, 2023. "Biased Humans, (Un)Biased Algorithms?," Journal of Business Ethics, Springer, vol. 183(3), pages 637-652, March.
  36. Piotr Tomasz Makowski & Yuya Kajikawa, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Papers 2103.02395, arXiv.org.
  37. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
  38. van Giffen, Benjamin & Herhausen, Dennis & Fahse, Tobias, 2022. "Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods," Journal of Business Research, Elsevier, vol. 144(C), pages 93-106.
  39. Willem Standaert & Steve Muylle, 2022. "Framework for open insurance strategy: insights from a European study," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 643-668, July.
  40. Patrick Rehill & Nicholas Biddle, 2023. "Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability," Papers 2310.13240, arXiv.org, revised Mar 2024.
  41. Meike Schroeder & Sebastian Lodemann, 2021. "A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management," Logistics, MDPI, vol. 5(3), pages 1-17, September.
  42. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
  43. Aimé, Isabelle & Berger-Remy, Fabienne & Laporte, Marie-Eve, 2022. "The brand, the persona and the algorithm: How datafication is reconfiguring marketing work☆," Journal of Business Research, Elsevier, vol. 145(C), pages 814-827.
  44. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
  45. Xiumei Ma & Yongqiang Sun & Xitong Guo & Kee-hung Lai & Doug Vogel, 2022. "Understanding users’ negative responses to recommendation algorithms in short-video platforms: a perspective based on the Stressor-Strain-Outcome (SSO) framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 41-58, March.
  46. Araz Zirar, 2023. "Can artificial intelligence’s limitations drive innovative work behaviour?," Review of Managerial Science, Springer, vol. 17(6), pages 2005-2034, August.
  47. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
  48. Priporas, Constantinos Vasilios & Vellore Nagarajan, Durga & Kamenidou, Irene (Eirini), 2023. "A technology-people-integrated toolkit for retail care management during a crisis," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
  49. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
  50. Spiekermann, Sarah & Krasnova, Hanna & Hinz, Oliver & Baumann, Annika & Benlian, Alexander & Gimpel, Henner & Heimbach, Irina & Köster, Antonia & Maedche, Alexander & Niehaves, Björn & Risius, Marten , 2022. "Values and Ethics in Information Systems – A State-of-the-Art Analysis and Avenues for Future Research," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130842, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  51. Roman Lukyanenko & Wolfgang Maass & Veda C. Storey, 2022. "Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1993-2020, December.
  52. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl & Joshua Gawlitza, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Information Systems Research, INFORMS, vol. 32(3), pages 713-735, September.
  53. John-Mathews, Jean-Marie, 2022. "Some critical and ethical perspectives on the empirical turn of AI interpretability," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  54. Heiko A. von der Gracht, 2021. "Beware of Bureaucrats: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
  55. Kim, Doha & Song, Yeosol & Kim, Songyie & Lee, Sewang & Wu, Yanqin & Shin, Jungwoo & Lee, Daeho, 2023. "How should the results of artificial intelligence be explained to users? - Research on consumer preferences in user-centered explainable artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
  56. Abdallah Moubayed & Abdallah Shami & Anwer Al-Dulaimi, 2022. "On End-to-End Intelligent Automation of 6G Networks," Future Internet, MDPI, vol. 14(6), pages 1-28, May.
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