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The Nature of Theory in Information Systems1
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The aim of this research essay is to examine the structural nature of theory in Information Systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction, and generalization that underlie an understanding of theory. A taxonomy is proposed that classifies information systems theories with respect to the manner in which four central goals are addressed: analysis, explanation, prediction, and prescription. Five interrelated types of theory are distinguished: (1) theory for analyzing, (2) theory for explaining, (3) theory for predicting, (4) theory for explaining and predicting, and (5) theory for design and action. Examples illustrate the nature of each theory type. The applicability of the taxonomy is demonstrated by classifying a sample of journal articles. The paper contributes by showing that multiple views of theory exist and by exposing the assumptions underlying different viewpoints. In addition, it is suggested that the type of theory under development can influence the choice of an epistemological approach. Support is given for the legitimacy and value of each theory type. The building of integrated bodies of theory that encompass all theory types is advocated.
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“This perspective allows for shifting theory development from analysis towards explanation and, ideally, design and action (Gregor 2006).”
From How to measure the status quo bias? A review of current literature (2023) · cites this paper as Gregor 2006
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“The nature of the contribution this framework makes to IS research can be classified according to Gregor's (2006) taxonomy as theory for explanation and understanding (Type II).”
From An Explanatory Framework for Achieving Business Benefits from ERP Systems (2012) · cites this paper as Gregor's (2006)
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“In Gregor’s (2006) landmark typology of theories, our study contributes a Type II theory.”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Gregor (2006)
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Metadata
- Authors
- Gregor, S.
- Affiliations
- Australian National University (AU)
- Corresponding author
- Gregor, Shirley
- ORCID
- Gregor, Shirley
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2006-09-01
- Volume
- 30
- Issue
- 3
- Pages
- 611-642
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W2151020819
- Cited by
- 3,306
- References
- 106
- Citations by year
- 2026: 158 · 2025: 142 · 2024: 137 · 2023: 171 · 2022: 208 · 2021: 208 · 2020: 184 · 2019: 189 · 2018: 178 · 2017: 163 · 2016: 153 · 2015: 229 · 2014: 207 · 2013: 209 · 2012: 195
- FWCI
- 288.19
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- MIS Quarterly (publishedVersion)
- ANU Open Research (Australian National University) (submittedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Scientific Research and Philosophical Inquiry
- Keywords
- information systems theory, nature of theory, causality, explanation, prediction, generalization, epistemology
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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.
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