Human-artificial intelligence interactions: Redefining knowledge creation and sharing for sustainable human resource management

Grant no.: 2024/55/D/HS4/02631

Funding agency: NATIONAL SCIENCE CENTRE

Funding scheme: Sonata 20

Funding period: September 2024-2027

Budget: 544 120 PLN

Title in Polish: Interakcje człowieka ze sztuczną inteligencją: Redefinicja tworzenia i udostępniania wiedzy na rzecz zrównoważonego zarządzania zasobami ludzkimi

Research team:

Principal Investigator (Kierownik):

• Asha Thomas

Investigators (Wykonawcy):

• Pratik Mullick

Collaborators (Współpracownicy):

 – Ph.D. / M.Sc. / B.Sc. student

Aims and scope:

This study investigates how organizations can effectively adopt artificial intelligence (AI) while aligning these advancements with sustainable and human-centric practices. The primary aim is to understand, develop, and redefine the mechanisms through which Sustainable Human Resource Management (Sus-HRM) enables the realignment of human–AI collaboration .The research is structured to achieve the following objectives:

1. To understand the drivers and barriers influencing knowledge creation and sharing.
2. To investigate the manifestation and impact of counterproductive knowledge-sharing behaviors on HRM practices.
3. To redefine Sustainable HRM

Methodology of this project

This study employs a mixed-methods approach, beginning with a systematic literature . The review will identify critical research gaps using Scopus, Web of Science, ProQuest, and other databases.Following the review, qualitative research will focus on inductive theorizing through in-depth interviews conducted within knowledge-intensive organizations. Semi-structured interviews will involve participants from five countries: India, Italy, Poland, the United Kingdom, and Malaysia.The study's quantitative phase will develop and test both measurement and structural models. Advanced analytical approaches, including Structural Equation Modeling (SEM) using SPSS, AMOS, and SmartPLS, will examine complex relationships. Complementary techniques such as Necessary Condition Analysis (NCA), Finite Mixture Modeling (FIMIX-PLS), and Multi-Group Analysis (MGA) will address the multifaceted nature of human-AI collaboration. Moderators and mediators identified through the literature and qualitative findings will be proposed and tested to understand their influence on key constructs.

Tasks:

Systematic Review / Conceptual paper Qualitative Research Empirical Research

Expected impact:

The project is designed and planned to deliver:

1. A validated framework for understanding and redefining Sustainable
2. Understanding drivers of knowledge creation and knowledge sharing.
3. Strategies to overcome barriers to knowledge sharing and address counterproductive behaviors.
4. Actionable recommendations for HR practitioners and policymakers to develop adaptive, ethical, and sustainable HRM systems.

Publications:

Peer-reviewed articles in JCR-listed journals

2024 (0+), 2023 (1)

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Peer-reviewed articles in non JCR-listed journals

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Book chapters

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Conference papers/posters

• (0+), 2023 (1)

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Forthcoming publications, submitted papers and work in progress 

Critically Advancing HRM Theory: AI, Sustainability, Common Good