European Business & Management

Special Issue

Artificial Intelligence and Employee Adaptive Learning

  • Submission Deadline: 1 June 2024
  • Status: Open for Submission
  • Lead Guest Editor: Nicoleta ISAC
About This Special Issue
Artificial Intelligence (AI) is rapidly transforming industries and businesses, revolutionizing the way daily tasks are performed. However, the adoption of AI may have unintended consequences on employee behavior, leading to burnout and decreased motivation for on-the-job learning. To address this issue, adaptive learning (AL) has emerged as a digitally-led learning approach that identifies skill gaps and has the potential to transform how employees learn, retain, and apply new knowledge. To provide employees with an effective learning experience, organizations must offer flexible learning options that allow them to learn according to their preferences and needs, rather than forcing them to learn according to the organization's strategy. This requires organizations to redefine their learning methodologies and align them with employee development goals. Consequently, organizations are seeking to optimize their training programs and help their staff acquire new skills more efficiently. Training courses can be personalized to meet each employee's unique skills, goals, and abilities, thereby promoting job success.

Potential topics include but are not limited to the following:

  1. 1. The impact of adaptive learning on employee performance
  2. 2. The role of leadership in promoting adaptive learning
  3. 3. The impact of adaptive learning on employee well-being
  4. 4. The role of AI in personalized learning
  5. 5. The impact of adaptive learning on employee engagement and motivation
This special issue welcomes original research articles, reviews, and case studies that address the topics of interest listed above. The research methods may include quantitative, qualitative, or mixed-methods approaches.
Lead Guest Editor
  • Nicoleta ISAC

    Business Administration/Business Administration and Management Sciences, Istanbul Sabahattin Zaim University, Istanbul, Turkey

Guest Editors
  • Cosmin Dobrin

    Department of Management, Academy of Economic Studies, Bucharest, Romania

  • Weian Wang

    Department of Computer and Information Sciences, Hartwick College, Oneonta, United States

  • Waqar Badshah

    Management Information System, Istanbul University, Istanbul, Turkey

  • Amalia Dutu

    Business Administration/Faculty of Economics and Law, University of Pitesti, Pitesti, Romania

  • Asad ul Islam Khan

    Economics/Humanity and Social Sciences, IBN Haldun University, Istanbul, Turkey

  • Irina Daniela L. Cismasu

    Economic-financial analysis and evaluation, Bucharest University of Economic Studies, Bucharest, Romania

  • Rasim Ozcan

    Management Information System, Istanbul University, Istanbul, Turkey

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