The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Strategic decision speed and firm performance
Abstract
This 4‐year study examines the effect of strategic decision speed upon subsequent firm performance and identifies environmental and organizational characteristics that relate to decision speed. We draw upon strategic decision‐making theory and organization theory to propose that strategic decision speed mediates the relation between environmental and organizational characteristics and performance. Measures of business environment, organization structure, strategic decision speed, and firm performance (growth and profitability) were collected from 318 CEOs from 1996 to 2000. Structural equation modeling confirmed that fast strategic decision‐making predicts subsequent firm growth and profit and mediates the relation of dynamism, munificence, centralization, and formalization with firm performance. Copyright © 2003 John Wiley & Sons, Ltd.
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
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
Judgment under Uncertainty: Heuristics and Biases
(1982) · doi:10.1017/cbo9780511809477 · Cited by 8,240
The unbearable automaticity of being
Bargh, J. A., & Chartrand, T. L. (1999) · American Psychologist · doi:10.1037/0003-066x.54.7.462 · Cited by 3,699 · cited 1×
“Many decision researchers claim that this synoptic explanation is an incomplete description of real decision processes ( Bargh and Chartrand, 1999; Beach, 1993).”
BackgroundMeasuring the performance of emerging businesses: a validation study
Chandler, G. N., & Hanks, S. H. (1993) · Journal of Business Venturing · doi:10.1016/0883-9026(93)90021-v · Cited by 728 · cited 1×
“Self-reported objective measures were used rather than subjective measures (e.g., respondents’ reports about performance relative to competitors’), because objective measures are more fine-grained ( Chandler and Hanks, 1993 ).”
MethodImplementing computerized technology: An organizational analysis.
Klein, K. J., Conn, A. B., & Sorra, J. S. (2001) · Journal of Applied Psychology · doi:10.1037/0021-9010.86.5.811 · Cited by 615
Cited by
Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research
Fiss, P. C. (2011) · Academy of Management Journal · doi:10.5465/amj.2011.60263120 · Cited by 5,930
Managing Firm Resources in Dynamic Environments to Create Value: Looking Inside the Black Box
Sirmon, D. G., Hitt, M. A., & Ireland, R. D. (2007) · Academy of Management Review · doi:10.5465/amr.2007.23466005 · Cited by 3,701
Transparency and replicability in qualitative research: the case of interviews with elite informants
Aguinis, H., & Solarino, A. M. (2019) · Strategic Management Journal · doi:10.1002/smj.3015 · Cited by 791
Wilden, R., & Gudergan, S. P. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0380-y · Cited by 631
Tallon, P. P., Queiroz, M., Coltman, T., & Sharma, R. (2019) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2018.12.002 · Cited by 453
Tang, J., Tang, Z., Marino, L. D., Zhang, Y., & Li, Q. (2008) · Entrepreneurship Theory and Practice · doi:10.1111/j.1540-6520.2007.00223.x · Cited by 426
Perifanis, N.-A., & Kitsios, F. (2023) · Information · doi:10.3390/info14020085 · Cited by 407
Heuristics as adaptive decision strategies in management: HEURISTICS IN MANAGEMENT
Artinger, F., Petersen, M., Gigerenzer, G., & Weibler, J. (2015) · Journal of Organizational Behavior · doi:10.1002/job.1950 · Cited by 255
Terjesen, S., Patel, P. C., & Covin, J. G. (2011) · Journal of Operations Management · doi:10.1016/j.jom.2010.07.004 · Cited by 158
Metadata
- Authors
- Robert Baum, J., & Wally, S.
- Venue
- Strategic Management Journal
- Publisher
- Wiley
- Published
- 2003-08-11
- Volume
- 24
- Issue
- 11
- Pages
- 1107-1129
- ISSN
- 0143-2095 (ISSN-L)
- 1097-0266
- OpenAlex
- W2079517683
- Cited by
- 1,001
- References
- 7
- FWCI
- 28.61
- 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.