Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 374

The DOI matches its Crossref record.

Complexities and Controversies in Linking HRM with Organizational Outcomes

Truss, Catherine·2001·Journal of Management Studies

Abstract

Our understanding of the way in which human resource management (HRM) is linked to organizational performance is still limited, despite recent advances that use a quantitative approach to argue for a strong positive relationship between ‘High Performance Work Practices’ and firm financial performance. These studies are limited by their reliance on a single informant in each organization, and their emphasis on financial performance at the expense of a broader range of outcome variables. This paper contributes to the debate by analysing in detail the human resource policies and practices of one case‐study organization over a two‐year time period, using a variety of methodologies and drawing on a broad range of informants across the organization. Instead of devising a list of ‘best practice’ HRM from the literature and testing its impact on performance, we instead invert the question and take a firm that is financially successful and ask what HR policies and practices it uses. We also examine the way in which these policies are enacted. This methodology enables us to show that even successful organizations do not always implement ‘best practice’ HRM, and that there is frequently a discrepancy between intention and practice. Outcomes at the individual and organizational levels are complex and often contradictory; we question the extent to which is it possible or meaningful to attempt to measure the interrelationship between HRM, at the level of the formal system, and organizational performance, without taking into consideration the role played by the informal organization in the process and implementation of HR policies.

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 · 10.1111/1467-6486.00275

Cites

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

Cited by

Metadata

Authors
Truss, C.
Venue
Journal of Management Studies
Publisher
Wiley
Published
2001-12
Volume
38
Issue
8
Pages
1121-1149
ISSN
  • 0022-2380 (ISSN-L)
  • 1467-6486
OpenAlex
W2042681103
Cited by
374
References
0
FWCI
19.41
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.