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Prior education and entrepreneurial intentions: the differential impact of a wide range of fields of study

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Abstract

Studies on entrepreneurial intentions often neglect the heterogeneity of individuals’ education background. This paper develops an integrated intention-based framework and analyzes the impact of fields of study on entrepreneurial intentions. Based on a sample of 2423 final-year students, enrolled in 32 fields of study, and resorting to logistic estimations, we find that, beside the attitude towards starting a business, fields of study, considered at a highly detailed level, are relevant (direct and indirect) predictors of entrepreneurial intention. We unambiguously show that there is a huge hidden potential for new venture creation in fields of study related to creative and leisure activities (e.g., Arts and humanities, or, more specifically, Literature and linguistics, History and archaeology, Audio-visual techniques and media production, Sports, and Architecture and town planning), Law, and Health (most notably, Pharmacy and Veterinary). Significant differences in the level of intention between students of different fields of study indicate that universities should more extensively focus entrepreneurship education on students in other subject area than business or engineering/technology sciences.

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Notes

  1. A table with the list of these studies which explicitly identifies the educational background (i.e., course/major/field of study) of the students surveyed can be available on request from the authors.

  2. To categorize the different education programs, we use the detailed educational field classification, ISCED 2013 (UNESCO 2014).

  3. Personality factors, namely age, gender and academic performance, are included in the model as control variables in line with the extant literature in the area (see Walter and Heinrichs 2015).

  4. Although the data are rather old, they are still a valid basis for deriving current conclusions, seeing as entrepreneurial values and intentions have not changed much since 2007, neither in the education system nor in the start-up behavior. Even though the Bologna Process was formally implemented in Portugal in 2006 (by Decree-Law no 74/2006), according to Leite and Ramos (2014: 81), “…the implementation of the new teaching/learning framework represents a challenge not fully overcome within HEI”. Moreover, a recent study by Barros (2015) shows that the financial crises did not have a major impact on students’ values and attitudes towards entrepreneurship: no significant statistical differences were found between the students of the 2012 cohort and students of the 2006 cohort in terms of achievement, risk, authority or autonomy.

  5. Nonresponse bias might occur when (Yu and Cooper 1983: 36) “a researcher (1) fails to obtain information from a sizable portion of the sample members and (2) the missing members' responses affect conclusions about the variables of interest. Sample members may become nonrespondents because they refuse to respond, lack the ability to respond, or are inaccessible to the researcher.”

  6. From the total responses gathered (2430), 7 responses were discarded as no valid information on the field of study was provided by the respondents.

  7. The school of Economics, namely the economics and management courses (representing 20 % in the sample versus 13 % in the population), was overrepresented in the sample, whereas the two schools of medicine, and the corresponding medicine courses, were underrepresented (4 % in the sample versus 10 % in the population). All the remaining schools and courses presented similar weights in the sample and in the population.

  8. Data analysis is available from the authors upon request.

  9. Internal reliability or consistency refers to the overall degree to which the items that make up a scale are intercorrelated, whereas homogeneity and unidimensionality indicate whether the scale items assess a single underlying factor or construct (Clark and Watson 1995). Internal consistency is a necessary but not sufficient condition for homogeneity or unidimensionality. In other words, a scale cannot be homogeneous unless all of its items are interrelated, but a scale can contain many interrelated items and still not be unidimensional. Because theory-driven assessment seeks to measure a single construct systematically, the ultimate goal to pursue is that of homogeneity or unidimensionality rather than internal consistency per se.

  10. All models included the control variables (age, gender and academic performance) as well as the variables prior entrepreneurial exposure (PEE) and learning orientation (LO) which proxied the construct ‘Other entrepreneurial knowledge/human capital’. We also estimated specifications that include the mediating effects of these latter variables via perceived individual control and perceived power but the estimates fail to be statistical significant and the signal and significance levels did not changed for the other estimates.

  11. This evidence is presented in Table 2, in the Appendix and corresponds to Model I considering broad FS (estimated model in Table 3, in the Appendix). For the remaining baseline models, correlation matrixes are available upon request from the authors.

  12. Conventional estimation techniques (e.g., multiple regression analysis), in the context of a discrete dependent variable, are not a valid option. First, the assumptions needed for hypothesis testing in conventional regression analysis are necessarily violated—it is unreasonable to assume, for instance, that the distribution of errors is normal. Second, in multiple regression analysis, predicted values cannot be interpreted as probabilities—they are not constrained to fall in the interval between 0 and 1.

  13. If we considered broad FS (Table 3 in the Appendix), only ‘Arts and humanities’ emerges as significantly (p value <0.001) and directly related to entrepreneurial intentions. ‘Business, administration and law’, ‘Services (Sports)’ and ‘Education’ are positively and significantly associated with entrepreneurial intentions at the 0.05 significance level.

  14. We also estimated the indirect impact of PEE and LO via PiC and PP (results not shown but available upon request from the authors) but again results failed to emerge as statistically significant.

  15. Between 2003 and 2007, Portugal presented one of the highest firm mortality rates (13 %) among the European countries—only the rate for Lithuania (17.1 %) was higher (Source: Eurostat).

  16. See Table 5 in Appendix for the concrete figures.

  17. We are indebted to one of the referees for this important insight.

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  1. CEF.UP, Faculdade de Economia Porto, INESC Tec, Universidade do Porto, R. Dr. Roberto Frias, 4200-464, Porto, Portugal

    Aurora A. C. Teixeira & Rosa Portela Forte

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Teixeira, A.A.C., Forte, R.P. Prior education and entrepreneurial intentions: the differential impact of a wide range of fields of study. Rev Manag Sci 11, 353–394 (2017). https://doi.org/10.1007/s11846-015-0188-2

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