مقاله انگلیسی رایگان در مورد آموزش کارآفرینی و فعالیت های کسب و کار تاسیس شده – الزویر 2024

Abstract

his paper introduces a conceptual model with perceived opportunity and perceived capability as mediators in the process by which entrepreneurship education helps improve the established business activities. Specifically, we hypothesize that the prevalence of entrepreneurship education relates positively with the rate of established business activity, and that perceived opportunity and capability mediate this relationship. We find support for all our hypotheses using Poisson regression with the Global Entrepreneurship Monitor data collected from 826 participants across 107 countries during the 2001–2018 period. Our findings confirm that entrepreneurship education has a significant positive impact on the performance of established businesses by helping the entrepreneurs improve their perceived capabilities and opportunities. These findings extend the current research on the impact of entrepreneurship education on entrepreneurial activities at different stages of development for entrepreneurial businesses.

Introduction

Entrepreneurship education (EE) can contribute to economic growth by improving entrepreneurial activities (EA), as reflected by growing research on the link between EE and EA (e.g., Abodohoui & Su, 2020; Abreu, Demirel, Grinevich, & Karataş-Özkan, 2016; Audretsch, 2014; Cohen, Hsu, & Shinnar, 2021). Based on two alternative EE models—experiential model and contingency model (Honig, 2004), EE may influence EA by making entrepreneurial learning process experiential (Politis, 2005) and engaging individuals in key learning behaviors, such as exploratory and exploitative learning (Nogueira, 2019; Wang & Chugh, 2014) to acquire entrepreneurial knowledge. This knowledge is needed to effectively cope with the liabilities of newness and recognize and act on entrepreneurial opportunities (Hahn, Minola, Bosio, & Cassia, 2020; Karlsson & Moberg, 2013; Politis, 2005). In addition, EE can impact EA (e.g., new business creation) by strengthening entrepreneurial self-efficacy (McGee, Peterson, Mueller, & Sequeira, 2009; Zhao, Seibert, & Hills, 2005) and competencies (Klarin, Inkizhinov, Nazarov, & Gorenskaia, 2021; Santos, Neumeyer, & Morris, 2019; Vidal, Pittz, Hertz, & White, 2021).

Some empirical studies also confirm the relationships between EE and EA (Souitaris, Zerbinati, & Al-Laham, 2007). Walter and Block (2016) show the strong link between entrepreneurship education and entrepreneurial activity (i.e., start a new business), with the sample of 11,230 individuals in 32 countries. Using data of 75 countries, Berrill, O’Hagan-Luff, and van Stel (2020) find that entrepreneurship education can reinforce the total early-stage entrepreneurial activities (either nascent or new entrepreneurial activities). Bergmann, Hundt, and Sternberg (2016) empirically find that entrepreneurship education has a positive effect on new business creations at the regional level with the 2011 Global University Entrepreneurial Spirit Students’ Survey data and multi-level analysis techniques. Shirokova, Osiyevskyy, Morris, and Bogatyreva (2017) also adopt the same dataset to test the effect of EE on student entrepreneurs from 26 countries, and the results indicate that entrepreneurial curricula have positive effect on causation and effectuation approaches in nascent entrepreneurship activities. By utilizing the data about Stanford alumni, Eesley and Lee (2021) find that entrepreneurship education programs may not improve new business creation but can help the individuals understand themselves well becoming entrepreneurs. Rahman, Hasibuan, Syah, Sagala, and Prayogo (2022) also examine how entrepreneurship education in universities can teach and introduce business students to entrepreneurial thinking, which includes intrapreneurial spirits (Delić & Alibegović, 2016). This improves individuals’ readiness to become entrepreneurs or persist in a professional environment.

Data analysis and results

Table 1 reports mean, standard deviation, and correlations of the variables. Before we conduct the regression analysis, we standardize the variables to reduce the dimensional issue. To test multicollinearity, we compute the variance inflation factor (VIF) for the variables included in each regression equation. The results indicate that the maximum VIF value is 3.98 among all the equations. Following the suggestions from De Clercq, Lim, and Oh (2014), Dheer (2017), and Hechavarría and Ingram (2019), we also calculate the mean VIF value for each equation, and the maximum value is 2.18. All the VIF values are below the threshold of 10.0 (Hair, Tatham, Anderson, & Black, 2006; Wooldridge, 2013), which indicates that there is no multicollinearity in our sample. In Table 1, the correlation results show that there are significant positive correlations between perceived opportunity and established business activity (r = 0.260, p < 0.001), between perceived capability and established business activity (r = 0.393, p < 0.001), and between entrepreneurship education and perceived opportunity (r = 0.136, p < 0.001). The results provide initial evidence for the analysis on the effect of entrepreneurship education on established business activity.