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Machine learning for enterprises: Applications, algorithm selection, and challenges

Citations

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Cited by:

  1. Pedro Guerra & Mauro Castelli, 2021. "Machine Learning Applied to Banking Supervision a Literature Review," Risks, MDPI, vol. 9(7), pages 1-24, July.
  2. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
  3. Mohamed Ismail & Noha A. Mostafa & Ahmed El-assal, 2022. "Quality monitoring in multistage manufacturing systems by using machine learning techniques," Journal of Intelligent Manufacturing, Springer, vol. 33(8), pages 2471-2486, December.
  4. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
  5. Berk Kaan Kuguoglu & Haiko van der Voort & Marijn Janssen, 2021. "The Giant Leap for Smart Cities: Scaling Up Smart City Artificial Intelligence of Things (AIoT) Initiatives," Sustainability, MDPI, vol. 13(21), pages 1-16, November.
  6. Bavaresco, Rodrigo Simon & Nesi, Luan Carlos & Victória Barbosa, Jorge Luis & Antunes, Rodolfo Stoffel & da Rosa Righi, Rodrigo & da Costa, Cristiano André & Vanzin, Mariangela & Dornelles, Daniel & J, 2023. "Machine learning-based automation of accounting services: An exploratory case study," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
  7. Canhoto, Ana Isabel & Clear, Fintan, 2020. "Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential," Business Horizons, Elsevier, vol. 63(2), pages 183-193.
  8. Jake B. Telkamp & Marc H. Anderson, 2022. "The Implications of Diverse Human Moral Foundations for Assessing the Ethicality of Artificial Intelligence," Journal of Business Ethics, Springer, vol. 178(4), pages 961-976, July.
  9. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
  10. Watson, Graeme J. & Desouza, Kevin C. & Ribiere, Vincent M. & Lindič, Jaka, 2021. "Will AI ever sit at the C-suite table? The future of senior leadership," Business Horizons, Elsevier, vol. 64(4), pages 465-474.
  11. Anderson, Brian S., 2022. "What executives get wrong about statistics: Moving from statistical significance to effect sizes and practical impact," Business Horizons, Elsevier, vol. 65(3), pages 379-388.
  12. Ionut Anica-Popa & Liana Anica-Popa & Cristina Radulescu & Marinela Vrincianu, 2021. "The Integration of Artificial Intelligence in Retail: Benefits, Challenges and a Dedicated Conceptual Framework," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 120-120, February.
  13. Neubert, Mitchell J. & Montañez, George D., 2020. "Virtue as a framework for the design and use of artificial intelligence," Business Horizons, Elsevier, vol. 63(2), pages 195-204.
  14. Bag, Surajit & Pretorius, Jan Ham Christiaan & Gupta, Shivam & Dwivedi, Yogesh K., 2021. "Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  15. Gianluca Gabrielli & Alice Medioli & Paolo Andrei, 2022. "Accounting and Big Data: Trends, opportunities and direction for practitioners and researchers," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2022(2), pages 89-112.
  16. Cong Cheng & Mengxin Zhang, 2023. "Conceptualizing Corporate Digital Responsibility: A Digital Technology Development Perspective," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
  17. Alisha Lakra & Shubhkirti Gupta & Ravi Ranjan & Sushanta Tripathy & Deepak Singhal, 2022. "The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach," Logistics, MDPI, vol. 6(4), pages 1-15, October.
  18. Jan Niederreiter, 2023. "Broadening Economics in the Era of Artificial Intelligence and Experimental Evidence," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 265-294, March.
  19. Alina Köchling & Marius Claus Wehner, 2020. "Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 795-848, November.
  20. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  21. Kamoonpuri, Sana Zehra & Sengar, Anita, 2023. "Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
  22. Ming‐Lang Tseng & Hien Minh Ha & Thi Phuong Thuy Tran & Tat‐Dat Bui & Chih‐Cheng Chen & Chun‐Wei Lin, 2022. "Building a data‐driven circular supply chain hierarchical structure: Resource recovery implementation drives circular business strategy," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2082-2106, July.
  23. Yakubu, Hanan & Kwong, C.K., 2021. "Forecasting the importance of product attributes using online customer reviews and Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
  24. Black, J. Stewart & van Esch, Patrick, 2020. "AI-enabled recruiting: What is it and how should a manager use it?," Business Horizons, Elsevier, vol. 63(2), pages 215-226.
  25. Pedro Guerra & Mauro Castelli & Nadine Côrte-Real, 2022. "Approaching European Supervisory Risk Assessment with SupTech: A Proposal of an Early Warning System," Risks, MDPI, vol. 10(4), pages 1-23, March.
  26. Ding Jian-lan & Shi Bing, 2021. "Analysis and Modeling of Enterprise Competitive Intelligence Based on Social Media User Comments," Entrepreneurship Research Journal, De Gruyter, vol. 11(2), pages 47-69, April.
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