The DOI matches its Crossref record; 44 of the 46 references it cites were found in a registry or an index.
The motivation to become an entrepreneur
Open accessAbstract
Purpose Since the 1950s, organizational psychology research investigating work‐related motivation has progressed from static content models to dynamic process models. Entrepreneurship research has evolved along a similar trajectory, adapting organizational psychology findings to better understand the motivation to become an entrepreneur. This paper reviews motivation research from both fields, explores some of the commonalities among current theories, and presents a new model of entrepreneurial motivation. Design/methodology/approach In an exploratory study, the ability of tolerance for risk, perceived feasibility, and perceived net desirability to predict intentions for self‐employment is examined in a sample of 114 undergraduate business students at Florida Gulf Coast University. Findings Results indicated that tolerance for risk, perceived feasibility and net desirability significantly predicted self‐employment intentions, with an adjusted R 2 of 0.528. Research limitations/implications Because the sample consisted entirely of undergraduate business students, findings may not be generalizable to non‐student populations. This research did not examine the role of negative motivations, or “push” factors. The cross‐sectional rather than longitudinal design of the study raises the usual caveats regarding lack of causal evidence. Finally, a limitation of any survey research is the inability to ask follow‐up questions and explore in more depth the reasoning behind any finding. Future research including qualitative interviews and/or focus group sessions could therefore provide rich explanatory information that could add value to the survey data. Practical implications As a result of this research, educators, government officials, and others interested in stimulating entrepreneurial motivation should consider how their words and actions affect potential entrepreneurs’ perceptions of entrepreneurial feasibility and net desirability. Originality/value Although the model is original and unique, it is based on established theories and models. It provides a well‐supported explanation of the motivation to become an entrepreneur that will be useful to potential entrepreneurs and those who encourage and guide them.
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“Entrepreneurial self-efficacy has thus indeed been consistently shown to be a positive influence on an individual's intentions to become involved in entrepreneurship (e.g., Chen etal., 1998; Segal etal., 2005; Zhao etal., 2005; Cassar and Friedman, 2009).”
From Impact of Entrepreneurship Training on Entrepreneurial Efficacy and Alertness among Adolescent Youth (2018) · cites this paper as Segal et al., 2005
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Metadata
- Authors
- Segal, G., Borgia, D., & Schoenfeld, J.
- Affiliations
- Florida Gulf Coast University (US)
- Venue
- International Journal of Entrepreneurial Behavior & Research
- Publisher
- Emerald
- Published
- 2005-02-01
- Volume
- 11
- Issue
- 1
- Pages
- 42-57
- ISSN
- 1355-2554 (ISSN-L)
- OpenAlex
- W2032673140
- Cited by
- 1,026
- References
- 46
- Citations by year
- 2026: 20 · 2025: 30 · 2024: 58 · 2023: 73 · 2022: 78 · 2021: 94 · 2020: 81 · 2019: 86 · 2018: 61 · 2017: 71 · 2016: 51 · 2015: 62 · 2014: 53 · 2013: 48 · 2012: 40
- FWCI
- 20.38
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- International Journal of Entrepreneurial Behaviour & Research (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Entrepreneurship Studies and Influences
- Social Sciences › Sociology and Political Science › Migration, Ethnicity, and Economy
- Social Sciences › Education › Vocational and Entrepreneurial Education
- Keywords
- entrepreneurial motivation, self-employment intention, risk tolerance, perceived feasibility, undergraduate business students, push and pull factors
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 ›
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