Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 279

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Turning around Troubled Software Projects: An Exploratory Study of the Deescalation of Commitment to Failing Courses of Action

Keil, Mark, Robey, Daniel·1999·Journal of Management Information Systems

Abstract

:Project failure in the information systems field is a costly problem and troubled projects are not uncommon. In many cases, whether a troubled project ultimately succeeds or fails depends on the effectiveness of managerial actions taken to turn around or redirect such projects. Before such actions can be taken, however, management must recognize problems and prepare to take appropriate corrective measures. While prior research has identified many factors that contribute to the escalation of commitment to failing courses of action, there has been little research on the factors contributing to the deescalation of commitment. Through deescalation, troubled projects may be successfully turned around or sensibly abandoned. This study seeks to clarify the factors that contribute to software project deescalation and to establish practical guidelines for identifying and managing troubled projects. Through interviews with forty-two IS auditors, we gathered both quantitative and qualitative data about the deescalation of commitment to troubled software projects. The interviews sought judgments about the importance of twelve specific factors derived from a review of the literature on deescalation. Interviews also generated qualitative data about specific actors and actions taken to tum troubled projects around.The results indicate that the escalation and deescalation phases of projects manifest different portraits. While there were no factors that always turned projects around, many actors triggered deescalation, and many specific actions accounted for deescalation. In the majority of cases, deescalation was triggered by actors such as senior managers, internal auditors, or external consultants. Deescalation was achieved both by managing existing resources better and by changing the level of resources comrmtted to the project. We summarize the implications of these findings in a process model ofproject deescalation.

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 · 10.1080/07421222.1999.11518222

Cites

1 of 1 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 1 references

Cited by

Metadata

Authors
Keil, M., & Robey, D.
Venue
Journal of Management Information Systems
Published
1999-03
Volume
15
Issue
4
Pages
63-87
ISSN
  • 0742-1222 (ISSN-L)
  • 1557-928X
OpenAlex
W80414419
Cited by
279
References
1
FWCI
21.86
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.