EZATECH: Design and development of Artificial Intelligence technologies for knowledge management throughout the life cycle of workers in organizations
Submitted: 2024-05-17
|Accepted: 2024-10-23
|Published: 2025-01-21
Copyright (c) 2025 Maria Ruiz, Juan Ignacio Igartua, Jabier Retegi, Aitor Uriondo, Jose Antonio Sudupe, Izaskun Heriz, Estibaliz Garate
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Downloads
Keywords:
Knowledge Management, Education, Industry, Artificial Intelligence
Supporting agencies:
Basque Government
Abstract:
This research presents the results of a project called “EZATECH: Design and development of Artificial Intelligence technologies for knowledge management through the life cycle of workers in organizations”, funded by the Basque Government (BG) (Economic Development, Sustainability and Environment Department). The project started in April 2021 and was completed in December 2023. The aim of the study was to develop an architecture to organize and structure knowledge from educational and industrial companies based on the professional profiles that composed the company and the key competencies necessary for the achievement of their organizational objectives. This objective responds to the challenges derived from the existence of a multitude of approaches that have “significantly hindered” the practical development of Knowledge Management in the business environment: The majority of practical application cases published to date refer to large companies or service companies. Machine Learning, Learning Analytics and People Analytics are the techniques used for the development of the EZATECH architecture, which is a software system to unable Knowledge Management in Educational and Industrial sectors.
References:
Aljapurkar, A. V., Purandare, S. P., & Ingawale, S. D. (2022). Metamorphose recruitment process through artificial intelligence. In Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments. https://doi.org/10.4018/978-1-6684-4950-9.ch013
Ashwini, N., & Patil, A. (2018). A Study on Artificial Intelligence its Opportunities and Challenges in Human Resource Management. International Journal of Arts, Science and Humanities, 6(1), 36-39
Bauer, T. N., Bodner, T., Erdogan, B., Truxillo, D. M., & Tucker, J. S. (2007). Newcomer adjustment dur-ing organizational socialization: A meta-analytic review of antecedents, outcomes, and methods. Journal of Applied Psychology, 92(3), 707-721. https://doi.org/10.1037/0021-9010.92.3.707
Beesley, L. G. A., & Cooper, C. (2008). Defining knowledge management (KM) activities: Towards consensus. Journal of Knowledge Management. https://doi.org/10.1108/13673270810875859
Cabrera, E. F., & Cabrera, A. (2005). Fostering knowledge sharing through people management practices. International Journal of Human Resource Management, 16(5), 720-735. https://doi.org/10.1080/09585190500083020
Cattermole, G. (2019). Developing the employee lifecycle to keep top talent. Strategic HR Review, 18(6). https://doi.org/10.1108/SHR-05-2019-0042
Chaithanapat, P., Punnakitikashem, P., Khin Khin Oo, N. C., & Rakthin, S. (2022a). Relationships among knowledgeoriented leadership, customer knowledge management, innovation quality and firm performance in SMEs. Journal of Innovation and Knowledge, 7(1). https://doi.org/10.1016/j.jik.2022.100162
Chaithanapat, P., Punnakitikashem, P., Khin Khin Oo, N. C., & Rakthin, S. (2022b). Relationships among knowledgeoriented leadership, customer knowledge management, innovation quality and firm performance in SMEs. Journal of Innovation and Knowledge, 7(1). https://doi.org/10.1016/j.jik.2022.100162
Davenport, T., & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Ubiquity (Vol. 1).
Dei, D. G. J., & van der Walt, T. B. (2020). Knowledge management practices in universities: The role of communities of practice. Social Sciences and Humanities Open, 2(1). https://doi.org/10.1016/j.ssaho.2020.100025
DeLong, D. W. (2007). Lost Knowledge: Confronting the Threat of an Aging Workforce. In Lost Knowledge: Confronting the Threat of an Aging Workforce. https://doi.org/10.1093/acprof:oso/9780195170979.001.0001
DeLong, D. W. (2009). Reducing risk: Building the business case for investing in knowledge retention. International Journal of Human Resources Development and Management, 9(2-3), 294-299. https://doi.org/10.1504/IJHRDM.2009.023457
Ferreira, L. S., & Nobre, F. S. (2022). Agile project management under the perspective of dynamic capa-bilities | Gestão ágil de projetos sob a perspectiva das capacidades dinâmicas. Gestao e Producao, 29. https://doi.org/10.1590/1806-9649-2022v29e3122
Gladka, O., Fedorova, V., & Dohadailo, Y. (2022). DEVELOPMENT OF CONCEPTUAL BASES OF THE EMPLOYEE LIFE CYCLE WITHIN AN ORGANIZATION. Business: Theory and Practice, 23(1). https://doi.org/10.3846/btp.2022.13510
Gloet, M., & Berrell, M. (2003). The dual paradigm nature of knowledge management: Implications for achieving quality outcomes in human resource management. Journal of Knowledge Management. https://doi.org/10.1108/13673270310463635
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185-214. https://doi.org/10.1080/07421222.2001.11045669
Ibrahim, F., & Reid, V. (2009). What is the value of knowledge management practices? Electronic Journal of Knowledge Management.
Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1). https://doi.org/10.1016/j.bushor.2022.03.002
Kammeyer-Mueller, J. D., Wanberg, C. R., Glomb, T. M., & Ahlburg, D. (2005). The role of temporal shifts in turnover processes: It's about time. Journal of Applied Psychology, 90(4), 644-658. https://doi.org/10.1037/0021-9010.90.4.644
Kazemi, M., & Zafar Allahyari, M. (2010). Defining a knowledge management conceptual model by using MADM. Journal of Knowledge Management. https://doi.org/10.1108/13673271011084916
Kianto, A., Shujahat, M., Hussain, S., Nawaz, F., & Ali, M. (2019). The impact of knowledge manage-ment on knowledge worker productivity. Baltic Journal of Management, 14(2). https://doi.org/10.1108/BJM-12-2017-0404
Lin, H.-F. (2007). Knowledge sharing and firm innovation capability: An empirical study. International Journal of Manpower, 28(3-4), 315-332. https://doi.org/10.1108/01437720710755272
Mäki, Eerikki; Järvenpää, Eila & Hämäläinen, L. (2001). Managing knowledge processes in knowledge intensive work. In Second european conference on knowledge management (Bled, 8-9 de noviembre de 2001). SL.: Academic Conferences Limited
Massingham, P. R. (2018). Measuring the impact of knowledge loss: a longitudinal study. Journal of Knowledge Management, 22(4), 721-758. https://doi.org/10.1108/JKM-08-2016-0338
Nonaka, I., & Takeuchi, H. (1995). Knowledge-Creating Company. Knowledge-Creating Company. https://doi.org/10.1093/oso/9780195092691.003.0004
Raudeliūnienė, J., Davidavičienė, V., & Jakubavičius, A. (2018). Knowledge management process model. Entrepreneurship and Sustainability Issues, 5(3). https://doi.org/10.9770/jesi.2018.5.3(10)
Slotte, V., Tynjälä, P., & Hytönen, T. (2004). How do hrd practitioners describe learning at work? Human Resource Development International, 7(4), 481-499. https://doi.org/10.1080/1367886042000245978
Sundaresan, S., & Zhang, Z. (2022). AI-enabled knowledge sharing and learning: redesigning roles and processes. International Journal of Organizational Analysis, 30(4). https://doi.org/10.1108/IJOA-12-2020-2558
Supriya P Inamdar, Dr. S. A. (2020). A strategic approach to HR Analytics: a framework for employee life cycle model. AIMA Journal OfManagement & Research, 14(1/4).
Taherdoost, H., & Madanchian, M. (2023). Artificial Intelligence and Knowledge Management: Impacts, Benefits, and Implementation. Computers. https://doi.org/10.3390/computers12040072
