Bakgrunn og aktiviteter
Patrick Mikalef is an Associate Professor in Data Science and Information Systems at the Department of Computer Science. In the past, he has been a Marie Skłodowska-Curie post-doctoral research fellow working on the research project "Competitive Advantage for the Data-driven Enterprise" (CADENT). He received his B.Sc. in Informatics from the Ionian University, his M.Sc. in Business Informatics for Utrecht University, and his Ph.D. in IT Strategy from the Ionian University. His research interests focus the on strategic use of information systems and IT-business value in turbulent environments. He has published work in international conferences and peer-reviewed journals including the Journal of Business Research, British Journal of Management, Information and Management, Industrial Management & Data Systems, and Information Systems and e-Business Management.
Vitenskapelig, faglig og kunstnerisk arbeid
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- (2022) Assessing the Implementation of AI Integrated CRM System for B2C Relationship Management: Integrating Contingency Theory and Dynamic Capability View Theory. Information Systems Frontiers.
- (2022) Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes. Information Systems Frontiers.
- (2022) Dynamic Capabilities in Information Systems Research: A Critical Review, Synthesis of Current Knowledge, and Recommendations for Future Research. Journal of the AIS.
- (2021) Digital working during the COVID-19 pandemic: how task–technology fit improves work performance and lessens feelings of loneliness. Information Technology and People.
- (2021) Assessing Organizational Users’ Intentions and Behavior to AI Integrated CRM Systems: a Meta-UTAUT Approach. Information Systems Frontiers.
- (2021) Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management. vol. 60.
- (2021) Artificial Intelligence and Business Value: a Literature Review. Information Systems Frontiers.
- (2021) Systematic literature review of E-learning capabilities to enhance organizational learning. Information Systems Frontiers.
- (2021) Toward the understanding of national culture in the success of non‐pharmaceutical technological interventions in mitigating COVID-19 pandemic. Annals of Operations Research.
- (2021) The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance. International Journal of Production Economics. vol. 239.
- (2021) Towards a business analytics capability for the circular economy. Technological Forecasting and Social Change. vol. 171.
- (2021) Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach. Industrial Marketing Management. vol. 98.
- (2021) Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management. vol. 58 (3).
- (2021) Enabling AI capabilities in government agencies: A study of determinants for European municipalities. Government Information Quarterly: an international journal of information technology management, policies, and practices.
- (2021) Truth or Dare? – How can we Influence the Adoption of Artificial Intelligence in Municipalities?. Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS).
- (2021) How Artificial Intelligence affords digital innovation: A cross-case analysis of Scandinavian companies. Technological Forecasting and Social Change. vol. 173.
- (2021) Responsible AI for Digital Health: a Synthesis and a Research Agenda. Information Systems Frontiers.
- (2021) Artificial Intelligence in Information Systems: State of the Art and Research Roadmap. Communications of the Association for Information Systems.
- (2020) The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies. Journal of Business Research.
- (2020) The role of information governance in big data analytics driven innovation. Information & Management. vol. 57 (7).