Examining the impact of artificial intelligence capability on dynamic capabilities, organizational creativity and organization performance in public organizations
Purpose This study aims to evaluate an artificial intelligence (AI) capability scale using resource-based theory and tests its impact on dynamic capabilities and organizational creativity to influence the performance of public organizations. Design/methodology/approach The study used qualitative and quantitative methods to develop and validate an AI capability scale using an integrative psychometric approach. An initial set of 26 items was selected from the literature for qualitative analysis. Self-reported data from 344 public managers in United Arab Emirates public organizations were used for scale refinement and validation. Hypotheses were tested against theoretically related constructs for nomological validation. Findings A 23-item AI capability scale was developed. Nomological testing confirmed that AI capability positively and significantly enhances dynamic capabilities, which in turn boosts organizational creativity and improves organizational performance. Originality/value Previous information system literature has not sufficiently addressed the importance of organizational-level complementary resources in developing distinctive capabilities within public organizations. Grounded in resource-based theory and recent AI research, this study provides a framework for public sector organizations to assess their AI capabilities. The findings empirically support the proposed theoretical framework, showing that AI capability increases dynamic capabilities, organizational creativity and performance.
Authors
- Abdul Hafaz Ngah (ORCID: https://orcid.org/0000-0002-9928-1708)
- Syed Zamberi Ahmad (ORCID: https://orcid.org/0000-0003-2785-2185)
- Khalizani Khalid (ORCID: https://orcid.org/0000-0002-8485-1616)
- Hamad Mohamed Almheiri
Institutions
- Abu Dhabi University (AE)
- University of Dubai (AE)
- Universiti Malaysia Terengganu (MY)
- Canadian University of Dubai (AE)
Publication Details
- Journal
- Journal of Systems and Information Technology
- Published
- 2024-12-28
- DOI
- https://doi.org/10.1108/jsit-10-2022-0239
- Citations
- 11
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 5.81