The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Road to “Root Cause”: Shop-Floor Problem-Solving at Three Auto Assembly Plants
Abstract
This paper uses case studies of shop-floor problem-solving at three automotive assembly plants to examine organizational influences on process quality improvement. Three complex quality problems—water leaks, paint defects, and electrical defects—were chosen because they are universally found in assembly plants, have multiple sources, and can only be resolved with high levels of interaction and coordination among individuals in multiple departments or functional groups. The case studies focus particularly on the early stages of the problem-solving process—problem definition, problem analysis, and the generation of solutions—emphasizing how each plant tries to identify the “root cause” of defects. The paper then explores consistencies and contrasts within and across the three cases to analyze the factors underlying effective shop-floor problem-solving. Central to this analysis is the idea that successful process quality improvement depends heavily on how the organization influences the cognitive processes of its members. Problem-solving processes benefit from rich data that capture multiple perspectives on a problem, problem categories that are “fuzzy”, and organizational structures that facilitate the development of a common language for discussing problems. Also, when problems are framed as opportunities for learning, the combination of positive attributions that boost motivation and the suppression of threat effects can improve the effectiveness of improvement activities. Finally, when process standardization is understood as marking the beginning (and not the end) of further improvement efforts, the normal inertial tendencies of organizations with respect to adaptive learning can be partially overcome.
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.
Integrity signals
Registry
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.
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
Organizational Information Requirements, Media Richness and Structural Design
Daft, R. L., & Lengel, R. H. (1986) · Management Science · doi:10.1287/mnsc.32.5.554 · Cited by 9,868
Cited by
Psychological Safety and Learning Behavior in Work Teams
Edmondson, A. (1999) · Administrative Science Quarterly · doi:10.2307/2666999 · Cited by 12,026
Nembhard, I. M., & Edmondson, A. C. (2006) · Journal of Organizational Behavior · doi:10.1002/job.413 · Cited by 2,385
Lee, G. K., & Cole, R. E. (2003) · Organization Science · doi:10.1287/orsc.14.6.633.24866 · Cited by 713
de Treville, S., & Antonakis, J. (2006) · Journal of Operations Management · doi:10.1016/j.jom.2005.04.001 · Cited by 549
The Robot Revolution: Managerial and Employment Consequences for Firms
Dixon, J., Hong, B., & Wu, L. (2021) · Management Science · doi:10.1287/mnsc.2020.3812 · Cited by 463
Collective Learning in Global Diffusion: Spreading Quality Standards in a Developing Country Cluster
Perez-Aleman, P. (2011) · Organization Science · doi:10.1287/orsc.1090.0514 · Cited by 120
The Role of Ego Networks in Manufacturing Joint Venture Formations
Carnovale, S., & Yeniyurt, S. (2014) · Journal of Supply Chain Management · doi:10.1111/jscm.12015 · Cited by 70
Neirotti, P., Pesce, D., & Battaglia, D. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121088 · Cited by 39
Metadata
- Authors
- MacDuffie, J. P.
- Venue
- Management Science
- Published
- 1997-04
- Volume
- 43
- Issue
- 4
- Pages
- 479-502
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2034082940
- Cited by
- 307
- References
- 1
- FWCI
- 8.65
- 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.