The moderating role of entrepreneurship education in shaping entrepreneurial intentions

We assumed positivist research philosophy and quantitative approach to obtain evidence to affirm the theoretical assertions. We collected quantitative data through a self-administered survey. The target population is students at various higher education institutions of Sultanate of Oman, offering entrepreneurship course which is a mandatory course for all disciplines at undergraduate level. The study includes only Higher Education institutions working in Oman; therefore, we assume that courses and their contents would be at par with each other. The Sultanate of Oman has an active regulatory body, namely Oman Academic Accreditation Authority, to ensure that all higher education institutions weather public or private, and comply the standards set by this authority. Therefore, we can expect that the entrepreneurship courses offered at undergraduate level in higher education institutions across the country are homogenous with respect to contents and delivery. In this survey, a questionnaire comprising 33 questions was floated among the sampled units of the population. The unit of study of this research is an individual student in the higher education institutes of the Sultanate of Oman. The sultanate encourages higher education institutions to offer entrepreneurship courses to the students in various disciplines especially the business schools. We approached the higher education institutions, which are offering entrepreneurship courses, through personal contacts. The respondents were randomly selected using convenient sampling method. The randomly collected data were divided into two subgroups based on the course completion.

Informed consent was obtained from all the participants prior to the survey, and the confidentiality and anonymity of the responses were ensured. For data collection, we used the Entrepreneurial Intentions Questionnaire (EIQ) designed by Liñán and Chen (2009) with additional demographic questions (age, gender, course, father occupation, etc.). A question was also added in the questionnaire to ask if the participant has studied the entrepreneurship courses or otherwise. The sample was divided into two subgroups based on the entrepreneurship education: the treatment group who had completed entrepreneurship courses and control group who had not completed entrepreneurship courses. The two groups were chosen to compare the results in terms of student attitude toward entrepreneurship, subjective norms and self-efficacy which might change because of entrepreneurship education. More than 500 questionnaires were distributed in person to the students at various higher education institutions offering entrepreneurship courses in the Sultanate of Oman. Convenience sampling approach was used to obtain the responses from the subjects. Total of 204 completed questionnaires was collected back in person out of which 192 questionnaires were usable. Overall, the response rate was 41.4%. Around 36% of the respondents were female and 64% were male. The average age of the respondents was 23 years. With regard to the entrepreneurship course, 55% of students in our sample have completed while 45% have not yet studied the course.

The Entrepreneurial Intentions Questionnaire (EIQ), designed by Liñán and Chen (2009) is used to collect the data from the two groups of students, i.e., who have completed the course of entrepreneurship and students who have not yet completed entrepreneurship course. The EIQ was developed to measure entrepreneurship intentions (EI) and other variables such as attitude toward entrepreneurship (ATE), subjective norm (SN), and perceived behavioral control/self-efficacy (SE). Another variable, i.e., students’ demographic factors (DF) is included in the same questionnaire. Reliability and validity of the questionnaire were already verified by Liñán and Chen (2009) to ensure that each pool of questions is related to the same subject and each subject corresponds to the required measure. However, we also performed the reliability and validity tests with collected data.

The questionnaire used in the research is divided into five sections. Section A identifies the profile/personal information of the respondents developed from various resources and own thought as well. Sections B, C, D and E comprehend questions related to attitude, subjective norms, self-efficacy and entrepreneurship intentions, respectively, taken the different constructs of the entrepreneurial intention model. These items are summarized in Table 1.

At the first place, we checked the measurement quality of our constructs through various reliability and validity tests. At the first place, reliability of the construct was checked by performing the most commonly used tests of instrument reliability, namely Cronbach’s Alpha and composite reliability. We used alternate test of reliability to ensure that our constructs are free from measurement bias. For testing the validity of instrument, we used combined loading and cross-loading method. We used average variance extracted (AVE) for convergent validity and square roots of AVE for discriminant validity. We checked the possibility of collinearity by variance inflation factor (VIF).

As shown in Table 2, the calculated values of Cronbach’s alpha for all four constructs are greater than the frequently used threshold value of 0.70 following Vaske et al. (2017). Similarly, the composite reliability coefficients of all four latent variables exceed the threshold value of 0.70 (Peterson and Kim 2013). Thus, all four latent variables qualify both tests of reliability. We can say that the latent variables have good internal consistency and indicators are a reliable measurement of the construct. For discriminate validity, we used square roots of AVE; the results indicate that the items have good discriminant validity as the square roots of AVE is greater than the respective coefficients of correlation with other variables (Johnston et al. 2014). The correlation coefficient values are also lower than the suggested 0.71 standard (Cooke et al. 2016). The VIF values of our constructs remained less than 5, which indicates that there is no issue of collinearity.

Table 2 indicates that the estimated values of AVEs are greater than the normally adopted standard of 0.50. Table 3 depicts the results of combined loading and cross-loadings. The individual items’ loadings have greater values for their respective constructs than other constructs. It can be concluded that all items have valid convergent validity to their respective constructs. The statistics suggest good reliability and validity of the measurement instrument. It is inferred based on the empirical results that our model is free from potential measurement bias.

After having information about the psychometric properties of the instrument, we proceed to estimate the modeled equation. To capture the moderating role of entrepreneurship education, we used the standard approach previously used by Sharma et al. (2009), then Chin et al. (2012), and most recently Elbaz et al. (2018). To capture the moderating role of entrepreneurship education, we estimated three equations as a standard procedure. The first model using the complete data set. The second model was estimated using the data of the treatment group and the third model was estimated with the data of the control group. The difference in path coefficients, effect size and coefficients of determination was observed to find out the moderating role of entrepreneurship education. Figure 2 graphically depicts the path coefficients (βs) and statistical significance (P values) of the individual predictors as well as the coefficient of determination (R²) values of all three variants of the model. The parameter coefficients of the first equation (A) were calculated by overall data including treatment group as well as the control group. The estimated parameters in case of second equation (B) were based on data of the treatment group only and the third equation (C) was estimated for parameters of the control group. The results indicate that the path coefficients of attitude toward entrepreneurship (ETE, β = 0.24), subjective norms (SNR, β = 0.27) and self-efficacy (SEF β = 0.36) are significant predictors at 99% confidence level. The results favor the acceptance of suggested null hypotheses namely H1, H2 and H3. These findings are consistent with the predictions of Planned Behavior Theory. The coefficient of determination value (R² = 0.53) suggests that variation in intentions toward entrepreneurship is 53% explained collectively by the three independent variables. The results indicate that self-efficacy has more contribution to intentions toward entrepreneurship with the highest path coefficient than subjective norms and attitude toward entrepreneurship, respectively. To capture the mediating role of entrepreneurship education, the equation was separately estimated for treatment group (who completed entrepreneurship courses) and control group (who did not study entrepreneurship courses). The statistics in case of treatment group (B) indicate that the parameter coefficients (ATE) β = 0.33, (SNR) β = 0.26 and (SEF) β = 0.33 are significant at 99% confidence level and coefficient of determination is R² = 0.62. In case of the control group, the results indicate that the parameter coefficient of (ATE) β = 0.19 is significant at 95% confidence level and parameter coefficients of (SNR) β = 0.35 and (SEF) β = 0.29 are significant at 99% confidence level. The R² value is 0.48 which is lowest in all three cases.

The comparative results of the three estimated equations are reproduced in Table 4. It is found that entrepreneurship education moderates the relationship between attitude toward entrepreneurship and entrepreneurial intentions, as indicated by the path coefficient value. In case of treatment group, the path coefficient ATE → ITE is β = 0.331 significant at 99% confidence level. However, in case of control group, the value of path coefficient is β = 0.191 at 95% confidence level. The individual effect size in case of treatment group also favors the acceptance of H4 null hypothesis. The path coefficient SNR → ITE, in case of treatment group, is β = 0.257 significant at 99% confidence level whereas in case of control group, β = 0.346 significant at 99% confidence level. The findings favor the acceptance of H5 null hypothesis. This result also signifies the moderating role of entrepreneurship education on the relationship between subjective norms and entrepreneurial intentions. It can be observed that education reduces the impact of subjective norms on entrepreneurial intentions. It indicates that student’s intentions toward entrepreneurship are less influenced by their environment if imparted entrepreneurship education. The path coefficient SNR → ITE in case of treatment group is β = 0.330 significant at 99% confidence level and in case of control group is β = 0.287 significant at 99% confidence level. Similarly, the individual effect size is 0.212 in treatment group and in case of control group, it is 0.173. These results indicate that entrepreneurship education affects the relationship between self-efficacy and entrepreneurial intentions positively. Based on the results, the H6 null hypothesis is also accepted.