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Theorizing routines with computational sequence analysis : a critical realism framework

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Zhang, Zhewei, Lee, Habin, Yoo, Youngjin and Choi, Youngseok (2022) Theorizing routines with computational sequence analysis : a critical realism framework. Journal of the Association for Information Systems, 23 (2). pp. 589-630. doi:10.17705/1jais.00734 ISSN 1536-9323.

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Official URL: https://doi.org/10.17705/1jais.00734

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Abstract

We develop a methodological framework to develop process theories on routines by leveraging large volumes of digital trace data following critical realism principles. Our framework begins with collecting and preprocessing digital trace data, corresponding to the empirically observed experience of critical realism. In the second and third steps of the framework, we identify a finite set of similar repetitive patterns (routines) through computational analysis. We accomplish this by combining frequent subsequence mining and clustering analysis to transform empirical observation into a set of routines that correspond to actual happening in critical realism. Then, we employ a retroduction approach to identify generative mechanisms of the routines. In the final step, we validate the generative mechanisms by evaluating proposed processual explanations and/or eliminating alternatives. We provide an illustrative example of developing a process theory in relation to the collaboration pattern in Wikipedia.

Item Type: Journal Article
Subjects: B Philosophy. Psychology. Religion > B Philosophy (General)
H Social Sciences > H Social Sciences (General)
T Technology > T Technology (General)
Divisions: Faculty of Social Sciences > Warwick Business School > Information Systems & Management
Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Process philosophy, Process mining , Management Science, Critical realism , Social sciences -- Methodology
Journal or Publication Title: Journal of the Association for Information Systems
Publisher: Association of Information Systems
ISSN: 1536-9323
Official Date: 3 March 2022
Dates:
DateEvent
3 March 2022Published
3 June 2021Accepted
Volume: 23
Number: 2
Page Range: pp. 589-630
DOI: 10.17705/1jais.00734
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 17 June 2021
Date of first compliant Open Access: 18 June 2021
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