Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 204

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Causal inferences between participation in decision making, task attributes, work effort, rewards, job satisfaction and commitment

Scott‐Ladd, Brenda, Travaglione, Anthony, Marshall, Verena·2006·Leadership & Organization Development Journal

Abstract

Purpose: Regulatory frameworks in Australia encourage employee participation in decision making (PDM) on the basis that participation benefits work effort, job satisfaction and commitment. Although the literature supports this premise, there is little evidence that patterns of causal inference in the relationship are clearly understood. This study aims to examine for structural and causal inference between PDM and the work environment over time. Design/methodology/approach: Structural equation modeling was used to examine longitudinal, matched sample data for causal inferences. Findings: The paper finds that participation in decision making appears to promote job satisfaction and commitment, whereas task variety and work effort foster participation. Research limitations/implications: The use of quantitative, self report data, small samples and cross industry data as well as possible overlap between commitment foci may limit the transferability of the findings. It is also important to note causality is merely inferred. Practical implications: Although participation in decision making positively influences work effort, autonomy and commitment, practitioners need to be mindful of keeping a balance between employee and employer needs. Job satisfaction and commitment are at risk in the long term if participation is viewed merely as a survival strategy for coping with work effort and task variety. Originality/value: The paper examines inferred causality within a participative decision‐making framework and addresses the previously neglected need for multi‐site and longitudinal studies.

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 · 10.1108/01437730610677990

Cites

3 of 3 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

Cited by

See all 204

Metadata

Authors
Scott‐Ladd, B., Travaglione, A., & Marshall, V.
Venue
Leadership & Organization Development Journal
Publisher
Emerald
Published
2006-07-01
Volume
27
Issue
5
Pages
399-414
ISSN
0143-7739 (ISSN-L)
OpenAlex
W2039424655
Cited by
204
References
3
FWCI
7.05
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

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.