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Strategies for Theorizing from Process Data
Abstract
In this article I describe and compare a number of alternative generic strategies for the analysis of process data, looking at the consequences of these strategies for emerging theories. I evaluate the strengths and weaknesses of the strategies in terms of their capacity to generate theory that is accurate, parsimonious, general, and useful and suggest that method and theory are inextricably intertwined, that multiple strategies are often advisable, and that no analysis strategy will produce theory without an uncodifiable creative leap, however small. Finally, I argue that there is room in the organizational research literature for more openness within the academic community toward a variety of forms of coupling between theory and data.
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Metadata
- Authors
- Langley, A.
- Affiliations
- Université du Québec à Montréal (CA)
- Corresponding author
- Langley, Ann
- ORCID
- Langley, Ann
- Venue
- The Academy of Management Review
- Publisher
- Academy of Management
- Published
- 1999-10
- Volume
- 24
- Issue
- 4
- Pages
- 691
- ISSN
- 0363-7425 (ISSN-L)
- OpenAlex
- W2115497642
- Semantic Scholar
- 419fd94ab6cccf99829edebee437ef9755829fba
- Cited by
- 7,008
- References
- 106
- Citations by year
- 2026: 578 · 2025: 535 · 2024: 482 · 2023: 445 · 2022: 507 · 2021: 504 · 2020: 450 · 2019: 398 · 2018: 374 · 2017: 329 · 2016: 267 · 2015: 289 · 2014: 283 · 2013: 261 · 2012: 231
- FWCI
- 28.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academy of Management Review (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Business, Management and Accounting › Business and International Management › Business and Management Studies
- Keywords
- process data, theorizing, theory generation, parsimony, generalizability, organizational analysis
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