Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 523

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Assessing the impact of common method variance on higher order multidimensional constructs.

Open access
Johnson, Russell E., Rosen, Christopher C., Djurdjevic, Emilija·2011·Journal of Applied Psychology

Abstract

Researchers are often concerned with common method variance (CMV) in cases where it is believed to bias relationships of predictors with criteria. However, CMV may also bias relationships within sets of predictors; this is cause for concern, given the rising popularity of higher order multidimensional constructs. The authors examined the extent to which CMV inflates interrelationships among indicators of higher order constructs and the relationships of those constructs with criteria. To do so, they examined core self-evaluation, a higher order construct comprising self-esteem, generalized self-efficacy, emotional stability, and locus of control. Across 2 studies, the authors systematically applied statistical (Study 1) and procedural (Study 2) CMV remedies to core self-evaluation data collected from multiple samples. Results revealed that the nature of the higher order construct and its relationship with job satisfaction were altered when the CMV remedies were applied. Implications of these findings for higher order constructs are discussed.

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 · 10.1037/a0021504

Cites

15 of 15 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 15 references

Cited by

See all 523

Metadata

Authors
Johnson, R. E., Rosen, C. C., & Djurdjevic, E.
Venue
Journal of Applied Psychology
Published
2011-07
Volume
96
Issue
4
Pages
744-761
ISSN
  • 0021-9010 (ISSN-L)
  • 1939-1854
OpenAlex
W1974076590
Cited by
523
References
15
FWCI
16.13
Type
journal article
Language
en
Open access
green

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: Assessing the impact of common method variance on higher order multidimensional constructs. https://app.cochat.ai/papers/10.1037/a0021504
The paper
Johnson, R. E., Rosen, C. C., & Djurdjevic, E. (2011). Assessing the impact of common method variance on higher order multidimensional constructs. Journal of Applied Psychology. https://doi.org/10.1037/a0021504

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.