Developing an Artificial Intelligence Capability: A Theoretical Framework for Business Value
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Organisations often find it difficult to integrate AI within their business processes and systems, which often inhibits AI adoption.
“research has found that organisations often find it difficult to integrate AI within their business processes and systems, which often inhibits AI adoption (Davenport and Ronanki, 2018;Mikalef., et al., 2019).”
From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Mikalef., et al., 2019
Cites
Bharadwaj, A. S. (2000) · MIS Quarterly · doi:10.2307/3250983 · Cited by 5,042 · see citing works
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020) · Information & Management · doi:10.1016/j.im.2019.05.004 · Cited by 1,072 · see citing works
Self-citationMikalef, P., & Pateli, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.09.004 · Cited by 1,038 · see citing works
Self-citationClinical decision support in the era of artificial intelligence
Shortliffe, E. H., & Sepúlveda, M. J. (2018) · JAMA · doi:10.1001/jama.2018.17163 · Cited by 920 · see citing works
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019) · British Journal of Management · doi:10.1111/1467-8551.12343 · Cited by 835 · see citing works
Self-citationQuestions for artificial intelligence in health care
Maddox, T. M., Rumsfeld, J. S., & Payne, P. R. O. (2019) · JAMA · doi:10.1001/jama.2018.18932 · Cited by 385 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Mikalef, P., & Gupta, M. (2021) · Information & Management · doi:10.1016/j.im.2021.103434 · Cited by 1,700 · see citing works
Self-citationChowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
Responsible Artificial Intelligence Governance: A Review and Research Framework
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2024.101885 · Cited by 565 · see citing works
Self-citationChowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.01.069 · Cited by 531 · see citing works
Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes
Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2023) · Information Systems Frontiers · doi:10.1007/s10796-022-10251-y · Cited by 191 · see citing works
Self-citation
- Authors
- Mikalef, P., Fjørtoft, S. O., & Torvatn, H. Y.
- Affiliations
- Norwegian University of Science and Technology (NO)
- SINTEF Digital (NO)
- Corresponding author
- Mikalef, Patrick
- Venue
- Lecture Notes in Business Information Processing
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 409-416
- ISSN
- 1865-1348 (ISSN-L)
- 1865-1356
- OpenAlex
- W2995432247
- Cited by
- 72
- References
- 6
- Citations by year
- 2026: 8 · 2025: 19 · 2024: 13 · 2023: 12 · 2022: 10 · 2021: 8 · 2020: 2
- FWCI
- 1.87
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in business information processing (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Keywords
- AI capabilities, business value of AI, resource-based view, complementary resources, AI adoption barriers, theoretical framework
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review