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Cited by 533

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Frameworks for developing impactful systematic literature reviews and theory building: What, Why and How?

Open access
Paul, Justin, Khatri, Puja, Kaur Duggal, Harshleen·2024·Journal of Decision Systems

Abstract

With the increased momentum of knowledge generation in the field of research, systematic reviews are essential to epitomise the state of extant literature and for theory building. In this article, we discuss the advantages of synthesising and reporting findings using a more impactful type of systematic review, the framework-based review. Additionally, we list and summarise some of the popularly used frameworks, TCCM (theories-contexts-characteristics-methods; Paul & Rosado-Serrano, 2019), ADO (antecedents-decisions-outcomes; Paul & Benito, 2018), 5W+ H (who, when, where, what, why, how; Callahan, Citation2014) and IMO (input-mediators-outcomes; Ilgen et al., Citation2005). We also provide methodological guidelines for conducting such a review.

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Metadata

Authors
Paul, J., Khatri, P., & Kaur Duggal, H.
Venue
Journal of Decision Systems
Published
2023-04-04
Volume
33
Issue
4
Pages
537-550
ISSN
  • 1246-0125 (ISSN-L)
  • 2116-7052
OpenAlex
W4362623641
Cited by
533
References
54
FWCI
40.85
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Frameworks for developing impactful systematic literature reviews and theory building: What, Why and How? https://app.cochat.ai/papers/10.1080/12460125.2023.2197700
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Paul, J., Khatri, P., & Kaur Duggal, H. (2024). Frameworks for developing impactful systematic literature reviews and theory building: What, Why and How? Journal of Decision Systems. https://doi.org/10.1080/12460125.2023.2197700

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.