Cited by 7,502Business Strategies and Management ResearchQualitative Research Methods and ApplicationsBusiness and Management Studies

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Strategies for Theorizing from Process Data

Langley, Ann·1999·The Academy of Management Review

DOI 10.5465/amr.1999.2553248

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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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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)
DOI: 10.5465/amr.1999.2553248
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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Strategies for Theorizing from Process Data

Abstract

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