Review: The Resource-Based View and Information Systems Research: Review, Extension, and Suggestions For Future Research1
Abstract
Information systems researchers have a long tradition of drawing on theories from disciplines such as economics, computer science, psychology, and general management and using them in their own research. Because of this, the information systems field has become a rich tapestry of theoretical and conceptual foundations. As new theories are brought into the field, particularly theories that have become dominant in other areas, there may be a benefit in pausing to assess their use and contribution in an IS context. The purpose of this paper is to explore and critically evaluate use of the resource-based view of the firm (RBV) by IS researchers. The paper provides a brief review of resource-based theory and then suggests extensions to make the RBV more useful for empirical IS research. First, a typology of key IS resources is presented, and these are then described using six traditional resource attributes. Second, we emphasize the particular importance of looking at both resource complementarity and moderating factors when studying IS resource effects on firm performance. Finally, we discuss three considerations that IS researchers need to address when using the RBV empirically. Eight sets of propositions are advanced to help guide future research.
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Digital technologies correspond to IT-related resources that support core organizational activities such as computer-supported collaborative work, supply chain management, and human resource management.
“Digital technologies correspond to IT-related resources that support core organizational activities such as computer-supported collaborative work, supply chain management, and human resource management [25,113].”
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Managing on the computer at a Korean insurance company
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Digital Business Strategy: Toward a Next Generation of Insights
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37:2.3 · Cited by 4,392 · see citing works
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Synthesizing information systems knowledge: A typology of literature reviews
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A Guide to Conducting a Systematic Literature Review of Information Systems Research
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Toward the development of a big data analytics capability
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A Guide to Conducting a Standalone Systematic Literature Review
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Big data analytics capabilities: A systematic literature review and research agenda
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Factors influencing big data decision-making quality
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Big data analytics capabilities and knowledge management: Impact on firm performance
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Assessing business value of big data analytics in European firms
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An integrated big data analytics-enabled transformation model: application to health care
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CRM to Social CRM: The Integration of New Technologies into Customer Relationship Management
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Innovating with enterprise systems and digital platforms: A contingent resource-based theory view
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The Business Value of IT: A Synthesis and Framework of Archival Research
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Building data management capabilities to address data protection regulations: Learnings from EU-GDPR
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- Authors
- Wade, M., & Hulland, J.
- Affiliations
- York University (CA)
- University of Pittsburgh (US)
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2004-03-01
- Volume
- 28
- Issue
- 1
- Pages
- 107-142
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1485916023
- Cited by
- 2,822
- References
- 142
- Citations by year
- 2026: 130 · 2025: 99 · 2024: 116 · 2023: 111 · 2022: 121 · 2021: 112 · 2020: 133 · 2019: 153 · 2018: 134 · 2017: 132 · 2016: 130 · 2015: 181 · 2014: 171 · 2013: 188 · 2012: 189
- FWCI
- 235.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- MIS Quarterly (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Keywords
- resource-based view, information systems resources, resource complementarity, moderators, firm performance, resource attributes
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 ›
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