The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
A Resource‐Based View of Strategic IT Alignment: How Knowledge Sharing Creates Competitive Advantage
Open accessAbstract
A critical decision problem for top management, and the focus of this study, is whether the CEO (chief executive officer) and CIO (chief information officer) should commit their time to formal planning with the expectation of producing an information technology (IT)‐based competitive advantage. Using the perspective of the resource‐based view, a model is presented that examines how strategic IT alignment can produce enhanced organizational strategies that yield competitive advantage. One hundred sixty‐one CIOs provided data using a postal survey. Results supported seven of the eight hypotheses. They showed that information intensity is an important antecedent to strategic IT alignment, that strategic IT alignment is best explained by multiple constructs which operationalize both process and content measures, and that alignment between the IT plan and the business plan is significantly related to the use of IT for competitive advantage. Study results raise questions about the effect of CEO participation, which appears to be the weak link in the process, and also about the perception of the CIO on the importance of CEO involvement. The paper contributes to our understanding of how knowledge sharing in the alignment process contributes to the creation of superior organizational strategies, provides a framework of the alignment‐performance relationship, and furnishes several new constructs.
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Cited by
Tallon, P. P., & Pinsonneault, A. (2011) · MIS Quarterly · doi:10.2307/23044052 · Cited by 1,187
BHATT, G. D., & GROVER, V. (2005) · Journal of Management Information Systems · doi:10.1080/07421222.2005.11045844 · Cited by 1,117
Can big data and predictive analytics improve social and environmental sustainability?
Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Luo, Z., Wamba, S. F., & Roubaud, D. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2017.06.020 · Cited by 860
Kearns, G. S., & Sabherwal, R. (2006) · Journal of Management Information Systems · doi:10.2753/mis0742-1222230306 · Cited by 573
Self-citationWu, S. P.-J., Straub, D. W., & Liang, T.-P. (2015) · MIS Quarterly · doi:10.25300/misq/2015/39.2.10 · Cited by 566
Metadata
- Authors
- Kearns, G. S., & Lederer, A. L.
- Venue
- Decision Sciences
- Publisher
- Wiley
- Published
- 2003-02
- Volume
- 34
- Issue
- 1
- Pages
- 1-29
- ISSN
- 0011-7315 (ISSN-L)
- 1540-5915
- OpenAlex
- W2060383494
- Cited by
- 680
- References
- 13
- FWCI
- 18.80
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.