Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 294

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Challenges in Conducting Empirical Work Using Structuration Theory: Learning from IT Research

Pozzebon, Marlei, Pinsonneault, Alain·2005·Organization Studies

Abstract

Giddens’s structuration theory is increasingly used as an alternative approach to studying numerous organizational phenomena. However, the applicability of Giddens’s concepts is not without difficulties because of two main challenges. First, structuration theory is complex, involving concepts and general propositions that operate at a high level of abstraction. Second, structuration theory is not easily coupled to any specific research method or methodological approach, and it is difficult to apply empirically. Arguing that structuration theory is a valuable framework for a rich understanding of management, organization and related subjects of inquiry, this paper aims to improve the application of structuration theory in empirical work by drawing on the experience in information technology (IT) research. It identifies patterns of use of Giddens’s theory in publications in the domain of IT, and then describes how IT researchers have attempted to address its major empirical challenges. The paper presents a repertoire of research strategies that might guide students of organization in dealing with three elements that are central to structuration theory: duality of structure, time/space and actors’ knowledgeability.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/0170840605054621

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 7 references

Metadata

Authors
Pozzebon, M., & Pinsonneault, A.
Venue
Organization Studies
Published
2005-09
Volume
26
Issue
9
Pages
1353-1376
ISSN
  • 0170-8406 (ISSN-L)
  • 1741-3044
OpenAlex
W2059706776
Cited by
294
References
7
FWCI
36.31
Type
journal article
Language
en
Open access
closed

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Challenges in Conducting Empirical Work Using Structuration Theory: Learning from IT Research. https://app.cochat.ai/papers/10.1177/0170840605054621
The paper
Pozzebon, M., & Pinsonneault, A. (2005). Challenges in Conducting Empirical Work Using Structuration Theory: Learning from IT Research. Organization Studies. https://doi.org/10.1177/0170840605054621

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.