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
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
- (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.
- (2020) Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities. European Journal of Information Systems.
- (2020) Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management.
- (2020) Big data and business analytics: A research agenda for realizing business value. Information & Management.
- (2020) IT architecture flexibility and IT governance decentralisation as drivers of IT-enabled dynamic capabilities and competitive performance: The moderating effect of the external environment. European Journal of Information Systems.
- (2020) Seeking Information on Social Commerce: An Examination of the Impact of User- and Marketer-generated Content Through an Eye-tracking Study. Information Systems Frontiers.
- (2020) Building dynamic capabilities by leveraging big data analytics: The role of organizational inertia. Information & Management.
- (2020) Identifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approach. International Journal of Information Management. vol. 53.
- (2020) How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data. Lecture Notes in Computer Science (LNCS). vol. 12067.
- (2020) Information and communication technologies (ICT)-enabled severe moral communities and how the (Covid19) pandemic might bring new ones. International Journal of Information Management.
- (2019) Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda. European Journal of Operational Research. vol. 281 (3).
- (2019) Technology-Enhanced Organizational Learning: A Systematic Literature Review. Lecture Notes in Computer Science (LNCS). vol. 11701 LNCS.
- (2019) The relations between IT work distribution, project benefits management and organizational performance. NOKOBIT - Norsk konferanse for organisasjoners bruk av informasjonsteknologi. vol. 27 (1).
- (2019) Exploring the Relationship Between Data Science and Circular Economy: An Enhanced CRISP-DM Process Model. Lecture Notes in Computer Science (LNCS). vol. 11701 LNCS.
- (2019) Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment. British Journal of Management. vol. 30 (2).
- (2019) Big data analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research. vol. 98.
- (2019) Artificial Intelligence in the Public Sector: A Study of Challenges and Opportunities for Norwegian Municipalities. Lecture Notes in Computer Science (LNCS). vol. 11701 LNCS.
- (2019) Developing an artificial intelligence capability: A theoretical framework for business value. Lecture Notes in Business Information Processing. vol. 373 LNBIP.
- (2019) Investigating the data science skill gap: An empirical analysis. IEEE Global Engineering Education Conference, EDUCON. vol. April-2019.