The DOI matches its Crossref record; 193 of the 193 references it cites were found in a registry or an index.
Experimental designs in management and leadership research: Strengths, limitations, and recommendations for improving publishability
Abstract
Abstract Despite the renewed interest in the use of experimental designs in the fields of leadership and management over the past few decades, these designs are still relatively underutilized. Although there are several potential reasons for this, chief among them is misunderstanding the value of these designs. The purpose of this article is to review the role of laboratory, field, and quasi-experimental designs in management and leadership research. We first discuss the primary goals of experimental studies. Next, we examine the characteristics of experimental designs and how to distinguish laboratory, field, and quasi-experiments from one another and from non-experimental studies. Following these discussions, we provide examples of each type of experimental design and discuss their relative strengths and limitations. Finally, we discuss steps that researchers can take to increase the probability of having articles reporting experiments accepted by leadership and management journals.
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Metadata
- Authors
- Podsakoff, P. M., & Podsakoff, N. P.
- Venue
- The Leadership Quarterly
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 30
- Issue
- 1
- Pages
- 11-33
- ISSN
- 1048-9843 (ISSN-L)
- OpenAlex
- W2901476464
- Cited by
- 312
- References
- 193
- FWCI
- 14.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- Podsakoff, P. M., & Podsakoff, N. P. (2019). Experimental designs in management and leadership research: Strengths, limitations, and recommendations for improving publishability. The Leadership Quarterly. https://doi.org/10.1016/j.leaqua.2018.11.002
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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.