Dr. Maayan Nakash

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Dr. Maayan Nakash

Articles & Books

Publications Articles in Scientific Journals

  1. Cai, F., Bolisani, E., Nakash, M., & Kassaneh, T. C. (2026). AI-driven knowledge management for sustainable businesses: a comprehensive analysis. VINE Journal of Information and Knowledge Management Systems, , Vol. ahead-of-print No. ahead-of-print, 1-23. https://doi.org/10.1108/VJIKMS-09-2025-0444.
  2. Nakash, M., & Bolisani, E. (2026). The Road to Integration: Mapping Barriers and Challenges in AI Implementation Processes within KMSs. Business Process Management Journal, 32(8), 52-75. https://doi.org/10.1108/BPMJ-12-2025-2008.
  3. Nakash, M. (2026). Beyond Certification: Practitioner Narratives on the ISO 30401 Knowledge Management Standard Adoption Gap in Israel. VINE Journal of Information and Knowledge Management Systems. https://doi.org/10.1108/VJIKMS-06-2025-0261. 
  4. Nakash, M. (2026). The Hidden Layers of Knowledge Management Processes: A Multidimensional Framework for Organizational KM Excellence. Journal of Knowledge Management, 30(11), 189-213. https://doi.org/10.1108/JKM-08-2025-1169.
    *JKM is recognized as the highest-ranked (Tier A+) journal in the international Knowledge Management (KM) community.
  5. Nakash, M. (2026). Work from Home: Balancing Flexibility, Productivity Concerns, and the Transition to Output Measurement. Work & Stress: An International Journal of Work, Health & Organisations. http://dx.doi.org/10.1080/02678373.2026.2633715.
  6. Yavetz, G., & Nakash, M. (2026). Adopting GenAI Applications in the Workplace: Managerial Implications and Insights from ICT Professionals. EuroMed Journal of Business, 1-19. https://doi.org/10.1108/EMJB-08-2024-0217.
  7. Nakash, M., & Peretz, O. (2025). Decoding the AI Job Market: Mapping Skills and Classifying Careers through Online Job Ads. Employee Relations: The International Journal, Special Issue: The Use of Social Media in Talent Acquisition and Talent Management, 1-18. https://doi.org/10.1108/ER-07-2025-0566.
  8. Ziv, L., & Nakash, M. (2025). Behind the Algorithm: International Insights into Data-Driven AI Model Development. Machine Learning and Knowledge Extraction. 7(4), 122, https://doi.org/10.3390/make7040122.
  9. Nakash, M., & Bolisani, E. (2025). The Transformative Impact of AI on Knowledge Management Processes. Business Process Management Journal, 31(8), 124-147. https://doi.org/10.1108/BPMJ-11-2024-1137.
  10. Nakash, M. (2025). From knowledge stock to innovation flow: strategies for organizational learning and renewal. VINE: The Journal of Information and Knowledge Management Systems, 56(1), 122-138, https://doi.org/10.1108/VJIKMS-02-2024-0062.
  11. Nakash, M. (2024). “A Profession that is a Story”: Blurred Professional Identity of CKO's. Knowledge Management Research & Practice, 24(13), 235-245. https://doi.org/10.1080/14778238.2024.2431114.
  12. Nakash, M., & Bolisani, E. (2024). Making Knowledge Management Transparent: A New Perspective on KM Processes Integration in the Organizational Framework. Business Process Management Journal, 31(8), 49-66. https://doi.org/10.1108/BPMJ-07-2024-0566.
  13. Nakash, M. (2024). Toward effective KMS measurement: Usage statistics vs. perceived value. Knowledge and Process Management, 31(4), 338-344. https://doi.org/10.1002/kpm.1789.
  14. Nakash, M., & Bouhnik, D. (2023). The effects of COVID-19 on information management in remote and hybrid work environments. Journal of the Association for Information Science and Technology, 74(9), 1067-1080. https://doi.org/10.1002/asi.24803.
    *This article has ranked within the top 10% of most-viewed papers published by JASIST in 2023.
  15. Nakash, M., & Bouhnik, D. (2023). Motivations for the initiation of knowledge management activities in times of routine and emergency. Aslib Journal of Information Management, 76(4), 553-569‏, https://doi.org/10.1108/AJIM-10-2022-0458.
  16. Nakash, M., & Bouhnik, D. (2023). The Influence of COVID-19 on Employees' Use of Organizational Information Systems. Interdisciplinary Journal of Information, Knowledge, and Management, 18, 353-368, https://doi.org/10.28945/5164.
  17. Nakash, M., & Bouhnik, D. (2022). “A system that will do magic”; organizational perspective on the technological layer in knowledge management. Aslib Journal of Information Management, 74(6), 1089-1102, https://doi.org/10.1108/AJIM-11-2021-0341.
  18. Nakash, M., Bouhnik, D., & Baruchson-Arbib, S. (2022). Challenges and methods for evaluating the effectiveness of knowledge management in organizations: KM professionals’ perceptions. Knowledge Management Research & Practice, 22(3), 247-255. https://doi.org/10.1080/14778238.2022.2141147.
  19. Nakash, M., Baruchson-Arbib, S., & Bouhnik, D. (2021). A holistic model of the role, development, and future of knowledge management: Proposal for exploratory research. Knowledge and Process Management, 29(1), 23-30. https://doi.org/10.1002/kpm.1694.
  20. Nakash, M., & Bouhnik, D. (2021). Challenges of justification of investment in organizational knowledge management. Knowledge Management Research & Practice. 21(4), 703-713. https://doi.org/10.1080/14778238.2021.1999184.
  21. Nakash, M., & Bouhnik, D. (2021). Can return on investment in knowledge management initiatives in organizations be measured?. Aslib Journal of Information Management, 74(3), 417-431, https://doi.org/10.1108/AJIM-09-2021-0268.
  22. Nakash, M., & Bouhnik, D. (2021). Should knowledge management in organizations be rebranded?. VINE: The Journal of Information and Knowledge Management Systems, 54(2), 242-255, https://doi.org/10.1108/VJIKMS-09-2021-0193.
  23. Nakash, M., & Bouhnik, D. (2020). Risks in the absence of optimal knowledge management in knowledge-intensive organizations. VINE: The Journal of Information and Knowledge Management Systems, 52(1), 87-101, https://doi.org/10.1108/VJIKMS-05-2020-0081.
  24. Nakash, M., & Bouhnik, D. (2020). “Knowledge Management is not dead. It has changed its appearance. And it will continue to change”. Knowledge and Process Management, 28(1), 29-39, https://doi.org/10.1002/kpm.1655.

Editing Scientific Book

  1. Bolisani, E., Nakash, M., Bratianu, C., & Bejinaru, R. (2026). Managing Human and Artificial Knowledge: New Horizons in AI-Supported Knowledge Management. Cham: Springer Nature Switzerland AG, pp.1-267. Book series: "Knowledge Management and Organizational Learning", a peer‑reviewed papers collection. This international collaborative project brings together contributors from 16 universities across Europe, North America, South America, and the Middle East. It is led by four research universities – University of Padova (Italy), Bar-Ilan University (Israel), Bucharest University of Economic Studies (Romania), and University of Suceava (Romania) – and follows a rigorous peer-review process. https://link.springer.com/book/9783032147202. DOI: https://doi.org/10.1007/978-3-032-14721-9

Peer-Reviewed Chapters in Scholarly Books

  1. Nakash, M. (2027). Artificial Knowledge Risk Management: Cultivating Organizational Wisdom to Sustain Trustworthy Knowledge Ecosystems. In: Bratianu, C., Kaiser, A., & Peschl, M. (eds) Spiritual Knowledge Management: Integrating Human Values, Wisdom, and Meaning in Knowledge Management. Springer, Cham, pp. TBD.
  2. Nakash, M. (2027). Not by Money Alone: Shifting from ROI to VOI in Measuring Knowledge Management Performance. In: Busu, M. (eds) Driving Competitive Advantage through AI and Digital Ecosystems. ICBE 2026 - the 20th International Conference on Business Excellence. Springer Proceedings in Business and Economics. Springer, Cham, pp. TBD.
  3. Te’eni, D., Nakash, M., & Drori, I. (2026). Designing Human Oversight in Autonomous Scientific Discovery. In Stephanidis, C. et al. (eds.) The HCI International 2026 Posters Book; the Communications in Computer and Information Science series, Springer Nature Switzerland AG, CCIS 3052, Chapter 45, p. 1-9, https://doi.org/10.1007/978-3-032-30836-8_45
  4. Nakash, M., & Bolisani, E. (2026). Do Organizations Struggle to Implement AI in Knowledge Management Systems? Initial Empirical Insights. In Schiuma, G., & Lerro, A. (Eds.), IFKAD25 Knowledge Insights: Exploring knowledge futures; AI, Technology, and the New Business Paradigm. The Forum on Knowledge Asset Dynamics (pp. TBD). Springer Nature Switzerland AG. Chapter 20, https://doi.org/10.1007/978-3-032-23684-5_20, https://link.springer.com/book/9783032236838
  5. Peretz, O., & Nakash, M. (2026). The Artificial Intelligence Talent Puzzle: How Company Size Shapes Hiring Patterns in AI. In: Busu, M. (eds) Leading Change in Disruptive Times. ICBE 2025 - the 19th International Conference on Business Excellence. Springer Proceedings in Business and Economics. Springer, Cham, pp. 442-453. https://doi.org/10.1007/978-3-032-19276-9_30.
  6. Nakash, M., & Bolisani, E. (2026). AI and the Changing Landscape of Knowledge: Rethinking KM Core Concepts and Models. In Bolisani, E., Nakash, M., Bratianu, C., & Bejinaru, R. (Eds.), Managing Human and Artificial Knowledge: New Horizons in AI-Supported Knowledge Management. Vol. 17, Chapter 3. Book series:  Knowledge Management and Organizational Learning (pp. 33-55). Cham: Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-032-14721-9_3
  7. Bolisani, E., Nakash, M., Bratianu, C., & Bejinaru, R. (2026). Introduction: Reframing Knowledge Management in the Age of Artificial Intelligence. In Bolisani, E., Nakash, M., Bratianu, C., & Bejinaru, R. (Eds.), Managing Human and Artificial Knowledge: New Horizons in AI-Supported Knowledge Management. Vol. 17, Chapter 1. Book series:  Knowledge Management and Organizational Learning (pp. 1-10). Cham: Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-032-14721-9_1
  8. Nakash, M. (2025). Redefining Workforce Dynamics: The Rise of Generation Z. In Tomé, E. (Ed.), Critical Aspects in Advanced Human Resource Management (pp. 187-218). IGI Global Scientific Publishing. Chapter 8, DOI: 10.4018/979-8-3693-6279-2.
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