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The Entrepreneurial Engagement of Italian University Students: Some Insights from a Population-Based Survey

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Title: The Entrepreneurial Engagement of Italian University Students: Some Insights from a Population-Based Survey
Language: English
Authors: Ferrante, Francesco (ORCID 0000-0002-4154-6451), Federici, Daniela, Parisi, Valentino
Source: Studies in Higher Education. 2019 44(11):1813-1836.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 24
Publication Date: 2019
Document Type: Journal Articles
Reports - Descriptive
Education Level: Higher Education
Postsecondary Education
Descriptors: Entrepreneurship, College Students, College Graduates, Employment Potential, Role, Alumni, Universities, Intention, Comparative Analysis, Foreign Countries, Innovation, Human Capital, Student Characteristics, Personal Autonomy, Occupational Mobility, Career Choice
Geographic Terms: Italy
DOI: 10.1080/03075079.2018.1458223
ISSN: 0307-5079
Abstract: Start-ups founded by university students and graduates play a substantial role in bringing new knowledge to the market and in employment creation, a role that appears to be even more important than that played by the typical technology transfer activities carried out by universities. We use a population-based approach to explore entrepreneurship among 61,115 graduate alumni of 64 Italian universities. In order to assess the potential supply of highly educated entrepreneurs, we develop a novel empirical approach to analyse engagement in entrepreneurship, based on the idea that entrepreneurship is a process that begins with intention and ends in action. We find that the share of intentional entrepreneurs, among recent cohorts of graduates in Italy, is large in comparison to the small share of actual entrepreneurs detected five years after graduation. We discuss which barriers may deter intentional entrepreneurs from being engaged in entrepreneurship and how universities can trigger the entrepreneurial process and close the gap between entrepreneurial intentions and action.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1233243
Database: ERIC
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  Value: <anid>AN0139429872;she01nov.19;2019Nov04.01:56;v2.2.500</anid> <title id="AN0139429872-1">The entrepreneurial engagement of Italian university students: some insights from a population-based survey </title> <p>Start-ups founded by university students and graduates play a substantial role in bringing new knowledge to the market and in employment creation, a role that appears to be even more important than that played by the typical technology transfer activities carried out by universities. We use a population-based approach to explore entrepreneurship among 61,115 graduate alumni of 64 Italian universities. In order to assess the potential supply of highly educated entrepreneurs, we develop a novel empirical approach to analyse engagement in entrepreneurship, based on the idea that entrepreneurship is a process that begins with intention and ends in action. We find that the share of intentional entrepreneurs, among recent cohorts of graduates in Italy, is large in comparison to the small share of actual entrepreneurs detected five years after graduation. We discuss which barriers may deter intentional entrepreneurs from being engaged in entrepreneurship and how universities can trigger the entrepreneurial process and close the gap between entrepreneurial intentions and action.</p> <p>Keywords: Entrepreneurship education; university; diffusion of innovation; students</p> <hd id="AN0139429872-2">1. Introduction</hd> <p>The motivation of this paper is threefold. First, a growing number of university students and graduates consider entrepreneurship to be a viable career option (Lindholm Dahlstrand and Berggren [<reflink idref="bib57" id="ref1">57</reflink>]). Second, robust empirical evidence suggests that education is an important component of entrepreneurial human capital and a positive determinant of entrepreneurial performance (Bates [<reflink idref="bib8" id="ref2">8</reflink>]; Otani [<reflink idref="bib69" id="ref3">69</reflink>]; Ferrante [<reflink idref="bib34" id="ref4">34</reflink>]; Van Der Sluis, Van Praag, and Vijverberg [<reflink idref="bib88" id="ref5">88</reflink>], [<reflink idref="bib89" id="ref6">89</reflink>]; Matlay [<reflink idref="bib61" id="ref7">61</reflink>]; Parker [<reflink idref="bib71" id="ref8">71</reflink>]). Future economic scenarios, shaped by rapid diffusion of technologies based on Artificial Intelligence (AI), will be characterized by more turbulent business environments and decision settings and, consequently, by an even more crucial role of entrepreneurial skills and knowledge, specifically provided through higher education.[<reflink idref="bib1" id="ref9">1</reflink>] The idea that the education of entrepreneurs is a predictor of firms' performance is corroborated by case studies in Italy[<reflink idref="bib2" id="ref10">2</reflink>] which show that entrepreneurs' education explains entrepreneurial and managerial styles, strategies and performance, in particular, the incentive to invest in R&D, to go abroad and, finally, firms' profitability (Bugamelli, Amatori, and Colli [<reflink idref="bib12" id="ref11">12</reflink>]; Bugamelli et al. [<reflink idref="bib13" id="ref12">13</reflink>]). Therefore, it is not surprising that scholars (Bugamelli et al. [<reflink idref="bib13" id="ref13">13</reflink>]; Federici and Ferrante [<reflink idref="bib32" id="ref14">32</reflink>]) attribute poor economic performance of the Italian economy in the past 15 years or so, partially to ineffective entrepreneurial styles and strategies determined by poor endowment of human capital. Third, the share of Italian entrepreneurs holding tertiary education is relatively quite small even among recent cohorts of graduates (Ferrante and Sabatini [<reflink idref="bib36" id="ref15">36</reflink>]; Federici and Ferrante [<reflink idref="bib32" id="ref16">32</reflink>]). Moreover, Italy records a comparatively low share of entrepreneurs with a university degree (Damiani and Ricci [<reflink idref="bib20" id="ref17">20</reflink>]; Federici and Ferrante [<reflink idref="bib32" id="ref18">32</reflink>]), even taking into account younger cohorts of entrepreneurs. Most worrying is that the level of education of entrepreneurs is below that of their employees (Ferrante and Sabatini [<reflink idref="bib36" id="ref19">36</reflink>]). In 2014, the share of new entrepreneurs surveyed by General Entrepreneurship Monitor[<reflink idref="bib3" id="ref20">3</reflink>] (GEM) who hold a tertiary degree was 21% (33% of survey sample had completed compulsory schooling; GEM [<reflink idref="bib44" id="ref21">44</reflink>]). By way of comparison, in 2010, 31% of German and 48% of UK new entrepreneurs surveyed by GEM had a tertiary degree against 19% in Italy (GEM [<reflink idref="bib43" id="ref22">43</reflink>]). This finding is supported by the '2016 AlmaLaurea survey on graduates' occupational status five years after graduation', which shows a very low share of graduates (1.3%) actively engaged in entrepreneurship.[<reflink idref="bib4" id="ref23">4</reflink>]</p> <p>In this paper, we use a population-based survey to explore entrepreneurship among 61,115 graduates, alumni of 64 Italian universities belonging to the AlmaLaurea[<reflink idref="bib5" id="ref24">5</reflink>] consortium, in the second half of 2014, at the time of completion of their academic experience. We developed a novel empirical approach to assess students' entrepreneurial engagement based on the notion that engagement is a process. We identified various levels of engagement in entrepreneurship, and we assessed significant factors that impacted more on the decision or intention to engage in entrepreneurship. In order to investigate the specific role that the university plays in entrepreneurial engagement, we focused on graduates whose engagement was post-university. In the spirit of the Theory of Planned Behaviour (TPB), we aimed to assess the potential supply of highly educated entrepreneurs, and thus we extended the analysis to entrepreneurial intentions.</p> <p>Briefly, this paper aims to investigate: (a) the key factors that influence the decisions of Italian university students to engage in entrepreneurship; (b) the potential supply of highly educated entrepreneurs in different fields of entrepreneurship; and (c) what universities can do to lower barriers to entrepreneurship and increase the expected value of this career option.</p> <p>The main management policy implication of our investigation was premised on the assumption that universities are capable of making interventions that reduce barriers to entrepreneurship among university students and can support students and graduates in the creation of new ventures. We posited that the main and most effective tool to lower these barriers and to trigger the entrepreneurial process is entrepreneurship education (Arranz et al. [<reflink idref="bib5" id="ref25">5</reflink>]). We envisaged that the benefits of providing entrepreneurial education to university students and graduates are not confined to its contribution to the creation of new ventures and innovation per se; they also derive from the cultivation of an entrepreneurial spirit that can foster university graduates' employability and their contribution to <emph>intrapreneurship</emph> and corporate innovation (European Commission [<reflink idref="bib28" id="ref26">28</reflink>]; Ferrante and Supino [<reflink idref="bib37" id="ref27">37</reflink>]).</p> <p>The viewpoint that measures to lower these barriers to entrepreneurship can improve job satisfaction and welfare appears to be confirmed by the AlmaLaurea surveys. They show that graduates who opted for entrepreneurship were much more satisfied with their jobs than colleagues who became employees: on a scale from 1 to 10, the job satisfaction of entrepreneurs is 8.4 compared with an average of 7.5 for employees (7.7 for other self-employed; AlmaLaurea [<reflink idref="bib3" id="ref28">3</reflink>]).</p> <p>It is noteworthy that our analysis is based on a unique population-based survey of university students at the time of graduation, run at the country level with a very high response rate (94%). Also for this reason, we believe that the relevance of the insights that we provide here on the contribution of Higher Education Institutions (HEIs) to entrepreneurship is not limited to the Italian case alone but could be extended to apply to other countries showing similar entrepreneurial engagement characteristics.</p> <p>This paper is organized into five sections. The first is an introduction that discusses the rationale of this survey. In the second section, we discuss the role of education as a source of entrepreneurial human capital and the theoretical framework of this paper. In the third section, we present the data and some preliminary descriptive evidence on the characterization of the different groups of graduates distinguished by the level of involvement in entrepreneurship. In the fourth section, we present a preferred analytical approach relative to the survey's purpose to evaluate the role played by various factors in fostering the intention to engage in entrepreneurship as a career option, and we discuss the main results. The final section of this work presents the main academic issues and higher education management implications.</p> <hd id="AN0139429872-3">2. Education as a source of entrepreneurial human capital</hd> <p>Entrepreneurship among students and graduates has captured the interest of many scholars (Dahlander and McFarland [<reflink idref="bib19" id="ref29">19</reflink>]; Perkmann et al. [<reflink idref="bib72" id="ref30">72</reflink>]; Arranz et al. [<reflink idref="bib5" id="ref31">5</reflink>]) in connection with the empirical evidence that start-ups founded by university students and graduates play a substantial role in bringing new knowledge to the market. This contribution appears, at least on quantitative grounds, to be even more important than that of the typical technology transfer initiatives carried out by universities, i.e. patenting and licensing activities, research contracts or spin-offs founded by academic staff (Roberts and Eesley [<reflink idref="bib74" id="ref32">74</reflink>]; Astebro, Bazzazian, and Braguinsky [<reflink idref="bib6" id="ref33">6</reflink>]; Roberts, Murray, and Kim [<reflink idref="bib75" id="ref34">75</reflink>]). Undeniably, entrepreneurship is one of the main drivers of innovation and sustainable growth (Iyigun and Owen [<reflink idref="bib46" id="ref35">46</reflink>]; Wennekers and Thurik [<reflink idref="bib92" id="ref36">92</reflink>]; Wennekers et al. [<reflink idref="bib93" id="ref37">93</reflink>]) and it is seen as a means to providing good opportunities for labour market entry, in particular, to those social groups that may encounter obstacles in finding good jobs as employees, e.g. women, young people and immigrants.</p> <p>Numerous theories and models from different fields of disciplines have been proposed to investigate an individual's decision to become an entrepreneur or entrepreneurial intentions and assess the characteristics of entrepreneurs. It has to be emphasized, however, that such theories need to be based on a reliable assessment of the drivers of the entrepreneurial process. The recognition, pursuit and development of opportunities constitute the core of the entrepreneur's task (Shane and Venkataraman [<reflink idref="bib84" id="ref38">84</reflink>]; Ardichvili, Cardozo, and Ray [<reflink idref="bib4" id="ref39">4</reflink>]). Once opportunities are discovered, the successful entrepreneur must select, organize and adopt solutions and strategies to develop those opportunities.</p> <p>The links between aspects of knowledge and the human capital of the entrepreneur in this opportunity discovery as well as exploitation process have been a popular area of entrepreneurship study (e.g. Shane [<reflink idref="bib81" id="ref40">81</reflink>]; Davidsson and Honig [<reflink idref="bib22" id="ref41">22</reflink>]; Dimov and Shepherd [<reflink idref="bib26" id="ref42">26</reflink>]; Ferrante [<reflink idref="bib34" id="ref43">34</reflink>]). Knowledge asymmetries and prior experience have been shown to play an important role in the opportunity recognition process (Shane [<reflink idref="bib82" id="ref44">82</reflink>]). Other scholars have focused on aspects of entrepreneurial cognition that should be coupled with knowledge in order for opportunities to be identified (Shane and Venkataraman [<reflink idref="bib84" id="ref45">84</reflink>]; Mitchell et al. [<reflink idref="bib64" id="ref46">64</reflink>]). More recently, the learning/entrepreneurship interface has been probed (Minniti and Bygrave [<reflink idref="bib63" id="ref47">63</reflink>]; Dimov [<reflink idref="bib25" id="ref48">25</reflink>]; Corbett [<reflink idref="bib14" id="ref49">14</reflink>], [<reflink idref="bib15" id="ref50">15</reflink>]). Prior knowledge is also strongly correlated with recurring or serial opportunity recognition and re-entry into entrepreneurship (Stam, Audretsch, and Meijaard [<reflink idref="bib87" id="ref51">87</reflink>]).</p> <p>Accordingly, we argue that <emph>entrepreneurial human capital consists of those cognitive abilities and non-cognitive traits</emph>[<reflink idref="bib6" id="ref52">6</reflink>]<emph>required to generate social value, within a given economic environment, through the discovery and successful exploitation of market opportunities</emph>.</p> <p>The distinction between tacit knowledge acquired through experience and codified knowledge acquired through education, as sources of entrepreneurial talent, has been addressed specifically by De Bruin and Ferrante ([<reflink idref="bib23" id="ref53">23</reflink>]) and Schultz ([<reflink idref="bib79" id="ref54">79</reflink>]) in relation to the intensification of the process of technical change.</p> <p>Why is this distinction important here? Codified knowledge is systematic and formal. It is describable and transformable into standardized processes; hence, it is not primarily personal and individual but may be used and distributed through time and space through education and training. By contrast, tacit knowledge is an individual asset based on personal experience and interaction, and it reflects the potential and capabilities of human capital in an economic area (Federici, Ferrante, and Vistocco [<reflink idref="bib33" id="ref55">33</reflink>]).</p> <p>Globalization II and the waves of technological and financial innovations that took place in the last thirty years or so have shaped a more complex world for entrepreneurs and employees alike. Today, the capability to understand social systems and those cultural trends from which entrepreneurial opportunities emanate relies more than in the past on people's endowment of skills and knowledge, which can be acquired mainly through higher education. This is particularly so for the ability to draw information for commercial purposes from the large mass of data generated within the Web. Michelacci and Schivardi ([<reflink idref="bib62" id="ref56">62</reflink>]) provide strong support to the view that the technological and institutional changes experienced since the 1990s have made higher education an important driver of human capital development. They argue that: (a) entrepreneurs reap higher benefits on investment made in higher education in the USA; (b) the education premium has increased since the 1990s; (c) entrepreneurs benefited from the premium more than employees; and (d) post-graduates received the highest share of the premium, in particular, as entrepreneurs.</p> <p>Formal training and education enhance entrepreneurial skills in many ways. It mostly fosters those planning and coordination abilities, such as managerial skills, which are needed to develop market opportunities once they are discovered. By so doing, education training can help to compress the uncertainty surrounding a given business venture and, more generally, environmental uncertainty.</p> <p>Families are a major source of tacit knowledge that generates the sort of cognitive and non-cognitive abilities required to discover and exploit entrepreneurial opportunities. Individuals whose parents are entrepreneurs are arguably more familiar with entrepreneurial decision-making, and in particular, with the process of taking risky decisions. They are constantly exposed to the manner in which the information necessary to take decisions is selected and processed. Hence, they develop more confidence about the effective outcomes of their decisions and actions. Of course, this may result in overconfidence and excessive optimism in entry decisions (Fraser and Greene [<reflink idref="bib41" id="ref57">41</reflink>]). The empirical evidence on the effects of family background on occupational choices is quite clear. It shows that belonging to a family of entrepreneurs enhances entrepreneurial engagement but that entrepreneurial performance depends on whether these entrepreneurs acquired entrepreneurial human capital by actively taking part in managing the family business (Fairlie and Robb [<reflink idref="bib31" id="ref58">31</reflink>]): so, nurture rather than nature seems to matter more for entrepreneurial human capital.</p> <p>In theoretical and empirical models, entrepreneurial talent has in most cases been modelled as depending on a generic 'human capital' variable, including highly assorted concepts like on-the-job knowledge and accumulated experience, educational qualification, family background, optimism, risk aversion, Big Five and the extent of social networks. Besides some notable exceptions, the multidimensional nature of entrepreneurial talent (Lazear [<reflink idref="bib56" id="ref59">56</reflink>]) has generally been undervalued, and the distinction between tacit and codified sources of cognitive abilities has been unduly stressed.</p> <p>The theoretical roots of the available models are grounded in different disciplinary approaches providing different perspectives. Given the space available and the aim of this paper, any attempt to summarize the relevant multidisciplinary theoretical contributions in this field would be inevitably incomplete. From an empirical point of view, the differences among approaches are not substantial in terms of the identification of the main drivers of entrepreneurship, and, in particular, the positive role of education.</p> <p>We can distinguish two main topics afforded by the empirical analysis on entrepreneurship: the decision to become entrepreneurs, seen as a career option and assessed mainly through a microeconomic-grounded approach, and entrepreneurial intentions, assessed mainly through psychology-grounded approaches adopted within business-oriented studies. In this paper, building on the standard microeconomic approach to occupational choices, we propose a novel empirical approach aiming to assess the drivers of the degree of engagement in the entrepreneurial process.</p> <p>Two papers are worth mentioning, as they have laid down specifically the microeconomic theoretical foundations of the choice for becoming an entrepreneur. In his seminal paper, Lucas ([<reflink idref="bib59" id="ref60">59</reflink>]) provides microeconomic foundations to the occupational choice and traces the roots of this decision to personal characteristics of individuals, i.e. their productivity in running a firm or <emph>managerial talent</emph>, which varies from one individual to another. In the labour market, the talent level required to become an entrepreneur determines the distinction between wage-earners and entrepreneurs who hire them. Kihlstrom and Laffont's ([<reflink idref="bib51" id="ref61">51</reflink>]) model is based on the same idea and on the substitution of the managerial talent with an individual's propensity to face entrepreneurial risks, i.e. risk taking required to become entrepreneurs determines the distinction between wage-earners and the entrepreneurs who hire them.</p> <p>Looking at empirical evidence grounded on the microeconomic approach, Parker ([<reflink idref="bib70" id="ref62">70</reflink>]) summarizes a great number of studies in which age, labour market experience, marital status, having self-employed parents and earnings differential have the most robust positive association with the probability of being or becoming an entrepreneur. The general result emerging from the empirical evidence on the characteristics of self-employment in different countries (e.g. Blanchflower and Oswald [<reflink idref="bib10" id="ref63">10</reflink>]; Cowling [<reflink idref="bib17" id="ref64">17</reflink>]) and new entrepreneurship (GEM [<reflink idref="bib44" id="ref65">44</reflink>]) is that technological and institutional country-specific factors shape the nature of entrepreneurial talent and the explicit role of human capital and education. These elements are the drivers of occupational choices insofar as they influence the risk-adjusted returns to education in different occupations[<reflink idref="bib7" id="ref66">7</reflink>] (Kanbur [<reflink idref="bib47" id="ref67">47</reflink>]). Moreover, the enhancement of managerial ability helps to reduce subjective uncertainty about one's entrepreneurial talent (Van Praag and Cramer [<reflink idref="bib90" id="ref68">90</reflink>]). Regarding education in entrepreneurship, a meta-analysis by Van Der Sluis, Van Praag, and Vijverberg ([<reflink idref="bib88" id="ref69">88</reflink>]) offers support for the context-dependent nature of entrepreneurial talent. The authors show that (a) entrepreneurial selection is not significantly affected by education; (b) performance, i.e. returns to education for entrepreneurs, varies substantially across countries; and (c) returns to education for entrepreneurs may or may not be higher than returns to education for employees.</p> <p>This corroborates other studies showing that more educated entrepreneurs perform better (e.g. Bates [<reflink idref="bib8" id="ref70">8</reflink>]), which would suggest that education improves entrepreneurial human capital, i.e. the skills and knowledge required to discover and exploit market opportunities, independently of its specific content. Less clear is the evidence on the effects of education on the decision to become entrepreneurs (Parker [<reflink idref="bib70" id="ref71">70</reflink>]) and on entrepreneurial intentions (Bae et al. [<reflink idref="bib7" id="ref72">7</reflink>]). At this point, it makes sense to distinguish education according to its content.</p> <p>A growing number of entrepreneurship literature focuses on the entrepreneurial orientation of university students (Zhao, Seibert, and Hills [<reflink idref="bib96" id="ref73">96</reflink>]; Fini et al. [<reflink idref="bib38" id="ref74">38</reflink>]). In this context, 'Psychologists have proven that intentions are the best predictors of any planned behaviour particularly when the behaviour is rare, hard to observe, or involves unpredictable time lags' (Krueger, Reilly, and Carsrud [<reflink idref="bib53" id="ref75">53</reflink>], 413). Indeed, TPB has been the most influential approach to the design of the empirical analysis of entrepreneurial intentions (Ajzen [<reflink idref="bib1" id="ref76">1</reflink>], [<reflink idref="bib2" id="ref77">2</reflink>]) and to test, specifically, the role of entrepreneurship education (Bae et al. [<reflink idref="bib7" id="ref78">7</reflink>]).</p> <p>Self-efficacy is the main factor behind students' entrepreneurial intentions, which can be related to the role of human capital and higher education in entrepreneurship. With respect to the use of objective measures of people's human capital, such as educational attainment, one derives the advantage of measuring perceived entrepreneurial skills, mediated by personality traits, demographics and role models, such as overconfidence and gender that are responsible for shaping intentions and the actual occupational choices.[<reflink idref="bib8" id="ref79">8</reflink>] According to the TPB, intentions are good predictors of actual behaviours and the evidence based on the theory shows that the degree of correlation between intentions and decision to become entrepreneurs is quite large (Sheeran [<reflink idref="bib85" id="ref80">85</reflink>]).</p> <hd id="AN0139429872-4">3. The survey</hd> <p>The survey design and the interpretation of data are based on the assumption that the decision to be engaged in entrepreneurship belongs to the realm of <emph>occupational choices and intentions</emph>, i.e. we follow a microeconomic-grounded approach: individuals compare the pecuniary and non-pecuniary expected benefits of different occupational options and choose or express their intentions accordingly. The latter benefits are affected by environmental and subjective factors and they are assessed by individuals idiosyncratically, i.e. according to their knowledge, skills, personality traits and beliefs (Ajzen [<reflink idref="bib1" id="ref81">1</reflink>]; Shane [<reflink idref="bib81" id="ref82">81</reflink>]; Shane, Locke, and Collins [<reflink idref="bib83" id="ref83">83</reflink>]). It is evident that the main difference between the occupational choices of the population at large, on one hand, and students and graduates, on the other, is that (a) the environment in which the latter are embedded also includes the university and (b) university students and graduates accumulate more codified human capital than other individuals. Of course, the actual entrepreneurial orientation of their human capital is determined by the overall educational investments and life experiences of the students. For instance, they may have attended a vocational upper secondary school rather than a lyceum, they may have taken a university course in management or marketing, or they may have participated in meetings organized by the Career Office or by the Technology Transfer Office.</p> <p>Psychological and cultural traits are an important part of the story. They may not only affect the decision to be engaged in entrepreneurship but also the difference between remaining intentional rather than becoming an active entrepreneur. For instance, individuals holding different degrees of confidence or trust in others may attach different values to the same business opportunity and, therefore, show a different attitude towards being engaged in the actual setting up of a firm. Role models related to gender or social factors can seemingly determine idiosyncratic outcomes. For example, in socially fragmented societies, groups may have different perceptions of entrepreneurship, presumably due to differences in accessibility to relevant social networks. Therefore, in addition to gender, the social background of university students is a factor to consider.</p> <p>The purpose of this survey is to investigate entrepreneurship (Reynolds and White [<reflink idref="bib73" id="ref84">73</reflink>]) among university students by looking at the various steps of the <emph>entrepreneurial process</emph> as defined by GEM ([<reflink idref="bib44" id="ref85">44</reflink>]), i.e. the process that extends from the recognition of opportunities to the actual setting up of a firm to develop them. Since we are mainly interested in assessing the actual entrepreneurial engagement of university students as well as the <emph>supply of highly educated entrepreneurs</emph>, we included in the research model entrepreneurial intentions and outcome that characterize <emph>entrepreneurship</emph> among university students.</p> <p>Whilst using these two approaches, this survey aims to first detect the characteristics of nascent entrepreneurs at various stages of the entrepreneurial process and second, to investigate the actual behaviours of nascent entrepreneurs in the <emph>process of emergence</emph> (Gartner and Carter [<reflink idref="bib42" id="ref86">42</reflink>]; Davidsson [<reflink idref="bib21" id="ref87">21</reflink>]) through repeated observation of individual respondents. Since at this stage of the project panel data were not yet available,[<reflink idref="bib9" id="ref88">9</reflink>] we followed the first approach.</p> <p>Table 1 shows the descriptive statistics of 61,115 respondents including undergraduates (bachelor degree, 3 years) and graduates (master degree: <emph>laurea magistrale</emph>, <emph>two years after the BA</emph>, and <emph>laurea a ciclo unico</emph>, <emph>five years degree</emph>). Students who completed the 'Student Entrepreneurship Survey' graduated between September and December 2014.[<reflink idref="bib10" id="ref89">10</reflink>]</p> <p>Table 1. Summary statistics of the variables used in the empirical analysis (whole sample, year 2015).</p> <p> <ephtml> <table><tbody><tr><td><italic>Gender</italic></td><td /><td /><td><italic>Cultural motivations to enrol</italic></td><td /><td /></tr><tr><td>Female</td><td char=".">25,880</td><td char=".">40.0</td><td>Yes</td><td char=".">60,779</td><td char=".">93.9</td></tr><tr><td>Male</td><td char=".">38,830</td><td char=".">60.0</td><td>No</td><td char=".">3931</td><td char=".">6.1</td></tr><tr><td><italic>Area of birth</italic></td><td /><td /><td><italic>Professional motivations to enrol</italic></td><td /><td /></tr><tr><td>North</td><td char=".">16,448</td><td char=".">25.4</td><td>Yes</td><td char=".">53,523</td><td char=".">82.7</td></tr><tr><td>Centre</td><td char=".">20,364</td><td char=".">31.5</td><td>No</td><td char=".">11,187</td><td char=".">17.3</td></tr><tr><td>South</td><td char=".">25,165</td><td char=".">38.9</td><td><italic>Past work experience</italic></td><td /><td /></tr><tr><td>Abroad</td><td char=".">2733</td><td char=".">4.2</td><td>Yes</td><td char=".">36,815</td><td char=".">56.9</td></tr><tr><td><italic>Area of study</italic></td><td /><td /><td>No</td><td char=".">25,341</td><td char=".">39.2</td></tr><tr><td>North</td><td char=".">17,610</td><td char=".">27.2</td><td>Not applicable</td><td char=".">2554</td><td char=".">3.9</td></tr><tr><td>Centre</td><td char=".">28,413</td><td char=".">43.9</td><td><italic>Current work experience</italic></td><td /><td /></tr><tr><td>South</td><td char=".">18,687</td><td char=".">28.9</td><td>Yes</td><td char=".">48,226</td><td char=".">74.5</td></tr><tr><td><italic>High school diploma</italic></td><td /><td /><td>No</td><td char=".">14,052</td><td char=".">21.7</td></tr><tr><td>Lyceum</td><td char=".">47,939</td><td char=".">74.1</td><td>Not applicable</td><td char=".">2432</td><td char=".">3.8</td></tr><tr><td>Technical</td><td char=".">13,984</td><td char=".">21.6</td><td><italic>Trust in others</italic></td><td /><td /></tr><tr><td>Vocational</td><td char=".">1379</td><td char=".">2.1</td><td>Yes</td><td char=".">25,285</td><td char=".">39.1</td></tr><tr><td>Abroad</td><td char=".">1408</td><td char=".">2.2</td><td>No</td><td char=".">39,425</td><td char=".">60.9</td></tr><tr><td><italic>Degree level</italic></td><td /><td /><td>Average score</td><td>3.9</td><td /></tr><tr><td>3 years (B.A.)</td><td char=".">40,448</td><td char=".">62.5</td><td /><td /><td /></tr><tr><td>3 + 2 years</td><td char=".">2546</td><td char=".">3.9</td><td><italic>Father entrepreneur</italic></td><td /><td /></tr><tr><td>5 years</td><td char=".">21,716</td><td char=".">33.6</td><td>Yes</td><td char=".">11,285</td><td char=".">17.4</td></tr><tr><td><italic>Field of study</italic></td><td /><td /><td>No</td><td char=".">53,425</td><td char=".">82.6</td></tr><tr><td>Agriculture and vet.</td><td char=".">2050</td><td char=".">3.2</td><td><italic>Mother entrepreneur</italic></td><td /><td /></tr><tr><td>Architecture</td><td char=".">2244</td><td char=".">3.5</td><td>Yes</td><td char=".">3599</td><td char=".">5.6</td></tr><tr><td>Chemistry</td><td char=".">3327</td><td char=".">5.1</td><td>No</td><td char=".">61,111</td><td char=".">94.4</td></tr><tr><td>Economics and statistics</td><td char=".">12,613</td><td char=".">19.5</td><td><italic>Father qualifications</italic></td><td /><td /></tr><tr><td>Physical education</td><td char=".">8136</td><td char=".">12.6</td><td>No qualifications</td><td char=".">553</td><td char=".">0.9</td></tr><tr><td>Biology</td><td char=".">2472</td><td char=".">3.8</td><td>Primary school</td><td char=".">3603</td><td char=".">5.6</td></tr><tr><td>Law</td><td char=".">1662</td><td char=".">2.6</td><td>Middle school</td><td char=".">17,288</td><td char=".">26.7</td></tr><tr><td>Engineering</td><td char=".">9104</td><td char=".">14.1</td><td>High school</td><td char=".">26,910</td><td char=".">41.6</td></tr><tr><td>Teaching</td><td char=".">5434</td><td char=".">8.4</td><td>University</td><td char=".">12,891</td><td char=".">19.9</td></tr><tr><td>Humanities</td><td char=".">3257</td><td char=".">5.0</td><td>Not applicable</td><td char=".">3465</td><td char=".">5.4</td></tr><tr><td>Languages</td><td char=".">4401</td><td char=".">6.8</td><td><italic>Mother qualifications</italic></td><td /><td /></tr><tr><td>Medicine</td><td char=".">3159</td><td char=".">4.9</td><td>No qualifications</td><td char=".">513</td><td char=".">0.8</td></tr><tr><td>Political sciences</td><td char=".">2687</td><td char=".">4.2</td><td>Primary school</td><td char=".">3483</td><td char=".">5.4</td></tr><tr><td>Psychology</td><td char=".">2750</td><td char=".">4.3</td><td>Middle school</td><td char=".">16,110</td><td char=".">24.9</td></tr><tr><td>Science</td><td char=".">1385</td><td char=".">2.1</td><td>High school</td><td char=".">29,229</td><td char=".">45.2</td></tr><tr><td>Not applicable</td><td char=".">29</td><td char=".">0.0</td><td>University</td><td char=".">11,742</td><td char=".">18.1</td></tr><tr><td><italic>Erasmus</italic></td><td /><td /><td>Not applicable</td><td char=".">3633</td><td char=".">5.6</td></tr><tr><td>Yes</td><td char=".">170</td><td char=".">0.3</td><td><italic>Job security important</italic></td><td /><td /></tr><tr><td>No</td><td char=".">62,379</td><td char=".">96.4</td><td>Yes</td><td char=".">60,259</td><td char=".">93.1</td></tr><tr><td>Not applicable</td><td char=".">2161</td><td char=".">3.3</td><td>No</td><td char=".">4451</td><td char=".">6.9</td></tr><tr><td><italic>Internship</italic></td><td /><td /><td>Average score</td><td>4.5</td><td /></tr><tr><td>Yes</td><td char=".">36,855</td><td char=".">57.0</td><td><italic>Autonomy important</italic></td><td /><td /></tr><tr><td>No</td><td char=".">25,694</td><td char=".">39.7</td><td>Yes</td><td char=".">56,859</td><td char=".">87.9</td></tr><tr><td>Not applicable</td><td char=".">2161</td><td char=".">3.3</td><td>No</td><td char=".">7851</td><td char=".">12.1</td></tr><tr><td><italic>ICT skills</italic></td><td /><td /><td>Average score</td><td>4.2</td><td /></tr><tr><td>Yes</td><td char=".">60,976</td><td char=".">94.2</td><td><italic>Attitudinal factors</italic></td><td /><td /></tr><tr><td>No</td><td char=".">3734</td><td char=".">5.8</td><td>Yes</td><td char=".">57,547</td><td char=".">88.9</td></tr><tr><td><italic>Social class</italic></td><td /><td /><td>No</td><td char=".">7163</td><td char=".">11.1</td></tr><tr><td>Bourgeoisie</td><td char=".">13,660</td><td char=".">21.1</td><td>Total</td><td char=".">64,710</td><td char=".">100.0</td></tr><tr><td>Middle class</td><td char=".">17,361</td><td char=".">26.8</td><td /><td /><td /></tr><tr><td>Petite bourgeoisie</td><td char=".">13,310</td><td char=".">20.6</td><td /><td /><td /></tr><tr><td>Working class</td><td char=".">16,743</td><td char=".">25.9</td><td /><td /><td /></tr><tr><td>Not applicable</td><td char=".">3636</td><td char=".">5.6</td><td /><td /><td /></tr><tr><td>Total</td><td char=".">64,710</td><td char=".">100.0</td><td /><td /><td /></tr><tr><td><italic>Students' performance indicators (mean values)</italic></td><td /><td /><td /><td /><td /></tr><tr><td>High school diploma mark</td><td>82.0/100</td><td /><td /><td /><td /></tr><tr><td>Exams average mark</td><td>26.3/30</td><td /><td /><td /><td /></tr><tr><td>Degree grade</td><td>103/110</td><td /><td /><td /><td /></tr><tr><td>Age at graduation</td><td>25.8</td><td /><td /><td /><td /></tr></tbody></table> </ephtml> </p> <p>We distinguished between graduates who started their business respectively before and after enrolment at university and we considered various levels of early-stage engagement in the <emph>entrepreneurial process</emph>.</p> <p>These ranged from 'pure' entrepreneurial intentions, to which the potential supply of entrepreneurs should be related, to 'actual' setting up of a business[<reflink idref="bib11" id="ref90">11</reflink>]. The various measures of entrepreneurial intention that we adopted differed from those used by GEM, in that they consider whether individual respondents had or had not already identified and exploited an enterprise opportunity. In our investigation, we did not set a time limit for establishing an active firm (the GEM project sets it at 3.5 years).</p> <p>The data show that 1100 respondents (1.7%) were entrepreneurs who had started a new venture during their university study; 564 (0.9%) were entrepreneurs who had started their business before enrolling at university; 2232 (3.4%) were nascent entrepreneurs (i.e. students who were currently engaged in some sort of entrepreneurial activity); and 57,219 (93.7%) were non-entrepreneurs (i.e. students who were not engaged in any entrepreneurial activity).[<reflink idref="bib12" id="ref91">12</reflink>] Among the latter, there were also <emph>intentional entrepreneurs</emph>. For further investigation and measurement of entrepreneurial intentions, we devised and employed different indicators as explained in the following statements of intention (scale 1–7; for which 1 is the lowest intention and 7 the highest; see Table 2):</p> <p></p> <ulist> <item> 'I thought I would start a business based on an idea I had'</item> <p></p> <item> 'I will do whatever it takes to become an entrepreneur'</item> <p></p> <item> 'My professional objective is to become an entrepreneur'</item> <p></p> <item> 'I will do whatever it takes to start and manage a firm'</item> <p></p> <item> 'I seriously intend to start a firm in the future'</item> </ulist> <p>Empirical estimates show a high positive correlation between intention statement answers. Thus, we selected statement (b) and we considered two measures: (a) a continuous one based on the scores assigned by all respondents within the entire scale; and (b) a binary one based on those respondents who indicated a score larger than 4 (5 > 7). Due to technical limitations, we do not provide a detailed description of the survey, which can be found in Fini et al. ([<reflink idref="bib39" id="ref92">39</reflink>]).</p> <p>Table 2. The share of students by degree of engagement in the entrepreneurial process.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Group</td><td>Definition</td><td>(%)</td></tr></thead><tbody><tr><td><italic>G1</italic></td><td>Students who started a business after enrolment at university</td><td char=".">1.7</td></tr><tr><td><italic>G2</italic></td><td>Students who had taken concrete actions to start a business</td><td char=".">3.4</td></tr><tr><td><italic>G3</italic></td><td>Students who gave a score > 4 to statement (b)</td><td char=".">33.1</td></tr><tr><td><italic>G4</italic></td><td>Students at different stages of the entrepreneurial process (non-entrepreneurs = 1; intentional entrepreneurs (sentence (a) > 4) = 2; students who had taken concrete actions to become entrepreneurs = 3; students who started a business after enrolment = 4)</td><td /></tr><tr><td><italic>G5</italic></td><td>Students at different stages of the entrepreneurial process including intentional entrepreneurs (G1 + G2 + G3 = 1)</td><td char=".">38.2</td></tr></tbody></table> </ephtml> </p> <p>We start by distinguishing the various groups of individuals in terms of their engagement in entrepreneurship, and we provide some descriptive analysis of the characteristics of the different groups (see Table 2). The first group (G1) includes all those graduates who started a business while at the university.[<reflink idref="bib13" id="ref93">13</reflink>] The second group (G2) included all those students who had taken concrete actions to start a business while at the university. Group (G3) included students who expressed <emph>entrepreneurial intentions</emph> according to the answer provided to statement (b).</p> <p>Finally, we aggregated the previous groups in order to obtain a group including all those individuals who were engaged in the entrepreneurial process at different stages. Then, we computed a measure of the degree of entrepreneurial engagement by assigning a score of 4 if the student belonged to group G1, a score of 3 if the student belonged to G2, a score of 2 if he/she belonged to G3[<reflink idref="bib14" id="ref94">14</reflink>] and, finally, a score of 1 in all the other cases. Finally, G5 includes all the students engaged <emph>to any degree</emph> in the entrepreneurial process (we use the answer to statement (b) to assess entrepreneurial intentions).</p> <p>The share of students engaged in entrepreneurship by level of engagement, gender, field of study, upper secondary educational background (general vs. vocational), social class and region of birth/study is shown in Tables 3 and 4. Table 5 displays the incidence of entrepreneurship among foreign students by level of engagement.</p> <p>Table 3. Distribution of students by level of engagement in entrepreneurship (%).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Non-entrepreneurs (a)</td><td>Intentional entrepreneurs (b)</td><td>Nascent entrepreneurs (took concrete actions to start a business, (c))</td><td>Actual entrepreneurs (d)</td><td>(e) = ((b) + (c) + (d)</td><td>(f) = (b)/((c) + (d))</td><td>Tot.</td></tr></thead><tbody><tr><td><italic>Gender</italic></td></tr><tr><td>Male</td><td char=".">53.6</td><td char=".">38.7</td><td char=".">5.1</td><td char=".">2.6</td><td char=".">46.4</td><td char=".">5.1</td><td char=".">40.0</td></tr><tr><td>Female</td><td char=".">68.4</td><td char=".">28.1</td><td char=".">2.4</td><td char=".">1.1</td><td char=".">31.6</td><td char=".">8.1</td><td char=".">60.0</td></tr><tr><td><italic>Field of study</italic></td></tr><tr><td>Agriculture and vet.</td><td char=".">65.8</td><td char=".">29.2</td><td char=".">3.3</td><td char=".">1.7</td><td char=".">34.2</td><td char=".">5.8</td><td char=".">3.2</td></tr><tr><td>Architecture</td><td char=".">63.7</td><td char=".">31.9</td><td char=".">2.9</td><td char=".">1.4</td><td char=".">36.3</td><td char=".">7.3</td><td char=".">3.5</td></tr><tr><td>Chemistry</td><td char=".">65.5</td><td char=".">31.0</td><td char=".">2.6</td><td char=".">0.9</td><td char=".">34.5</td><td char=".">9.0</td><td char=".">5.1</td></tr><tr><td>Economics, business and statistics</td><td char="."> 70.1</td><td char=".">27.2</td><td char=".">1.9</td><td char=".">0.8</td><td char=".">29.9</td><td char=".">10.2</td><td char=".">19.5</td></tr><tr><td>Physical education</td><td char=".">57.2</td><td char=".">37.3</td><td char=".">3.7</td><td char=".">1.8</td><td char=".">42.8</td><td char=".">6.7</td><td char=".">12.6</td></tr><tr><td>Biology</td><td char=".">49.5</td><td char=".">43.7</td><td char=".">4.3</td><td char=".">2.5</td><td char=".">50.5</td><td char=".">6.4</td><td char=".">3.8</td></tr><tr><td>Law</td><td char=".">48.5</td><td char=".">43.8</td><td char=".">5.2</td><td char=".">2.5</td><td char=".">51.5</td><td char=".">5.7</td><td char=".">2.6</td></tr><tr><td>Engineering</td><td char=".">55.2</td><td char=".">36.7</td><td char=".">5.4</td><td char=".">2.7</td><td char=".">44.8</td><td char=".">4.5</td><td char=".">14.1</td></tr><tr><td>Teaching</td><td char=".">62.4</td><td char=".">31.0</td><td char=".">4.5</td><td char=".">2.1</td><td char=".">37.6</td><td char=".">4.7</td><td char=".">8.4</td></tr><tr><td>Humanities</td><td char=".">63.6</td><td char=".">30.2</td><td char=".">3.3</td><td char=".">2.9</td><td char=".">36.4</td><td char=".">4.8</td><td char=".">5.0</td></tr><tr><td>Languages</td><td char=".">65.0</td><td char=".">29.9</td><td char=".">3.4</td><td char=".">1.7</td><td char=".">35.0</td><td char=".">5.9</td><td char=".">6.8</td></tr><tr><td>Medicine</td><td char=".">72.1</td><td char=".">24.9</td><td char=".">2.0</td><td char=".">1.0</td><td char=".">27.9</td><td char=".">8.3</td><td char=".">4.9</td></tr><tr><td>Political sciences</td><td char=".">64.8</td><td char=".">31.0</td><td char=".">2.9</td><td char=".">1.3</td><td char=".">35.2</td><td char=".">7.4</td><td char=".">4.2</td></tr><tr><td>Psychology</td><td char=".">66.6</td><td char=".">28.7</td><td char=".">3.3</td><td char=".">1.3</td><td char=".">33.4</td><td char=".">6.1</td><td char=".">4.2</td></tr><tr><td>Science</td><td char=".">53.3</td><td char=".">41.5</td><td char=".">3.7</td><td char=".">1.5</td><td char=".">46.7</td><td char=".">8.0</td><td char=".">2.1</td></tr><tr><td><italic>HS diploma</italic></td></tr><tr><td>Lyceum (general)</td><td char=".">63.6</td><td char=".">31.8</td><td char=".">3.1</td><td char=".">1.6</td><td char=".">36.4</td><td char=".">6.9</td><td char=".">75.4</td></tr><tr><td>Other (vocational)</td><td char=".">59.0</td><td char=".">34.2</td><td char=".">4.7</td><td char=".">2.1</td><td char=".">41.0</td><td char=".">5.0</td><td char=".">24.6</td></tr><tr><td><italic>Social class</italic></td></tr><tr><td>Bourgeoisie</td><td char=".">58.0</td><td char=".">35.3</td><td char=".">4.2</td><td char=".">2.5</td><td char=".">42.0</td><td char=".">5.3</td><td char=".">21.1</td></tr><tr><td>Middle class</td><td char=".">63.8</td><td char=".">31.7</td><td char=".">3.3</td><td char=".">1.2</td><td char=".">36.2</td><td char=".">7.1</td><td char=".">26.8</td></tr><tr><td>Petite bourgeoisie</td><td char=".">58.4</td><td char=".">35.4</td><td char=".">4.0</td><td char=".">2.2</td><td char=".">41.6</td><td char=".">5.7</td><td char=".">20.6</td></tr><tr><td>Working class</td><td char=".">66.5</td><td char=".">29.7</td><td char=".">2.8</td><td char=".">0.9</td><td char=".">33.5</td><td char=".">7.9</td><td char=".">25.9</td></tr><tr><td>Total</td><td char=".">61.7</td><td char=".">33.1</td><td char=".">3.4</td><td char=".">1.7</td><td char=".">38.3</td><td char=".">6.4</td><td char=".">100.0</td></tr></tbody></table> </ephtml> </p> <p>Table 4. Students' involvement in entrepreneurial activities by region of birth and place of study (% shares; N = North, C = Centre, S = South, A = Abroad; NN = resident in the North and enrolled in the North).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Non-entrepreneurs (a)</td><td>Intentional entrepreneurs (b)</td><td>Nascent entrepreneurs (took concrete actions to start a business, (c))</td><td>Actual entrepreneurs (d)</td><td>(e) = ((b) + (c) + (d)</td><td>(f) = (b)/((c) + (d)</td><td>Total</td></tr></thead><tbody><tr><td>NN</td><td char=".">66.8</td><td char=".">29.0</td><td char=".">2.9</td><td char=".">1.2</td><td char=".">33.2</td><td char=".">7.0</td><td char=".">22.3</td></tr><tr><td>NC</td><td char=".">64.9</td><td char=".">29.9</td><td char=".">3.3</td><td char=".">1.9</td><td char=".">35.1</td><td char=".">5.7</td><td char=".">2.7</td></tr><tr><td>NS</td><td char=".">63.3</td><td char=".">32.0</td><td char=".">2.7</td><td char=".">2.0</td><td char=".">36.7</td><td char=".">6.8</td><td char=".">0.4</td></tr><tr><td>CC</td><td char=".">63.6</td><td char=".">31.6</td><td char=".">3.1</td><td char=".">1.7</td><td char=".">36.4</td><td char=".">6.6</td><td char=".">30.1</td></tr><tr><td>CN</td><td char=".">64.0</td><td char=".">31.8</td><td char=".">3.3</td><td char=".">0.9</td><td char=".">36.0</td><td char=".">7.6</td><td char=".">1.0</td></tr><tr><td>CS</td><td char=".">58.5</td><td char=".">34.3</td><td char=".">4.2</td><td char=".">3.0</td><td char=".">41.5</td><td char=".">4.8</td><td char=".">0.4</td></tr><tr><td>SS</td><td char=".">59.0</td><td char=".">34.9</td><td char=".">3.9</td><td char=".">2.1</td><td char=".">41.0</td><td char=".">5.8</td><td char=".">27.6</td></tr><tr><td>SC</td><td char=".">60.1</td><td char=".">35.1</td><td char=".">3.5</td><td char=".">1.3</td><td char=".">39.9</td><td char=".">7.3</td><td char=".">8.8</td></tr><tr><td>SN</td><td char=".">60.1</td><td char=".">34.8</td><td char=".">4.1</td><td char=".">1.1</td><td char=".">39.9</td><td char=".">6.8</td><td char=".">2.4</td></tr><tr><td>AN</td><td char=".">57.6</td><td char=".">35.0</td><td char=".">5.3</td><td char=".">2.1</td><td char=".">42.4</td><td char=".">4.7</td><td char=".">1.5</td></tr><tr><td>AC</td><td char=".">59.5</td><td char=".">32.6</td><td char=".">5.1</td><td char=".">2.9</td><td char=".">40.5</td><td char=".">4.1</td><td char=".">2.2</td></tr><tr><td>AS</td><td char=".">63.4</td><td char=".">29.0</td><td char=".">5.0</td><td char=".">2.5</td><td char=".">36.6</td><td char=".">3.8</td><td char=".">0.5</td></tr><tr><td>Total</td><td char=".">61.7</td><td char=".">33.1</td><td char=".">3.4</td><td char=".">1.7</td><td char=".">38.2</td><td char=".">6.4</td><td char=".">100.0</td></tr></tbody></table> </ephtml> </p> <p>Table 5. The share of foreign students by entrepreneurial group (%).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Share</td></tr></thead><tbody><tr><td>Intentional</td><td char=".">4.7</td></tr><tr><td>Nascent entrepreneurs (took concrete actions to start a business)</td><td char=".">7.8</td></tr><tr><td>Actual entrepreneurs (after enrolment)</td><td char=".">6.4</td></tr><tr><td>Total</td><td char=".">4.2</td></tr></tbody></table> </ephtml> </p> <p>It is noteworthy that as far as entrepreneurial intentions are concerned, the gender gap appears to be much smaller than in the case of the actual engagement in entrepreneurship or in the case of nascent entrepreneurship (the male/female ratio is 1:4 in the first case and 2:1 and 2:4 in the other two cases[<reflink idref="bib15" id="ref95">15</reflink>]).</p> <p>However, indications show that there might be barriers specific to gender which deter female intentional entrepreneurs from being more engaged in entrepreneurship. Preliminary evidence on the presence of factors specific to the fields of study and to the social background of the students, that may deter intentional entrepreneurs from being more active, is also provided by column (f) showing the ratio between the share of intentional and active entrepreneurs. Surprisingly, the groups <emph>Economics and Statistics</emph> followed by <emph>Medicine and Science</emph> show the highest ratios, whereas the groups <emph>Engineering and Teaching</emph> display the lowest. This preliminary evidence seems to confirm that the sort of entrepreneurial skills and attitudes required to start a business are not necessarily provided by economic disciplines as they are currently taught, and it may suggest, conversely, that the latter studies may deter entrepreneurship by manifesting an idea of the complexity of doing business.</p> <p>The social class also seems to exert an impact on the gap between intentions and actions: students whose parents belong to the working class appear the most affected. In addition to barriers affecting all students alike, credit rationing and limited access to appropriate social networks are candidate explanations for this larger gap.</p> <p>Not surprisingly, university students holding a vocational educational background show a smaller gap with respect to those who attended a Lyceum.</p> <p>The geographical distribution by entrepreneurial group shown in Table 4 suggests that there may be territorial factors playing a role and motivating the interplay between students' mobility flows, occupational choices and entrepreneurial intentions. Leaving aside foreign students, the propensity to be engaged in various degree in entrepreneurship activities shows a territorial gradient, with students coming from the Southern and the Central regions being more active.</p> <p>Not surprisingly, foreign students are overrepresented at all levels of entrepreneurial engagement (Table 5). In particular, the share engaged in starting new ventures (7.8%) and in active entrepreneurship (6.4%) is relatively high. This confirms the findings of previous studies on entrepreneurship among immigrants (Schuetze and Antecol [<reflink idref="bib78" id="ref96">78</reflink>]; Fairlie and Lofstrom [<reflink idref="bib30" id="ref97">30</reflink>]).</p> <hd id="AN0139429872-5">4. Empirical strategy and results</hd> <p>Indeed, population surveys based on large populations and providing significant results are not superior to well-designed sample surveys. Self-selection problems may strongly affect the former unless response rates are sufficiently high. On the other hand, sample surveys might be based on incorrect sampling and may not provide enough information on subgroups (Mutz [<reflink idref="bib65" id="ref98">65</reflink>]; Sincero [<reflink idref="bib86" id="ref99">86</reflink>]).</p> <p>The population survey on which we relied on is characterized by very high response rates (92%). Moreover, the source of a large part of the information, concerning mainly students' academic career and educational background, is administrative.</p> <p>The aim of our study was to investigate factors that influence the degree of students' engagement in entrepreneurship and, in particular, the role of universities. The idea is that entrepreneurship is a process and that students' engagement in entrepreneurship can be decomposed into its main stages: mere entrepreneurial intentions, concrete actions to set up a new firm and the actual setting up of a firm. In addition, we found it expedient to run a separate analysis of the entrepreneurial intentions in order to detect differences in factors influencing them.</p> <p>In pursuance of this paper's objective as stated in Section 2, we selected the following factors that we expected to influence entrepreneurial engagement: age, upper secondary educational background, i.e. general vs. vocational and diploma grade; level of university course (graduate, undergraduate); field of study; curricular experiences: work experience during university (actual or past), participation in internships or international student exchange programmes (Erasmus); students' university performance: performance, average mark and graduation grade; activities delivered by universities that can be related to the acquisition of entrepreneurial skills and attitudes: having attended university curricular or non-curricular courses on entrepreneurship; other university stimuli to engage in entrepreneurship; an overall indicator of ICT skills including a wide set of digital skills; parents' education and social background, the latter related mainly to their occupation. As regards geographic factors, given the large existing territorial differences and students' mobility, we constructed 12 dummies as shown in Table 4 to account for the role of occupational and entrepreneurial opportunities in both region of birth and region of study. We also included university-fixed effects.</p> <p>One of the problems associated with this approach is that there may be unobservable characteristics explaining the propensity to engage in entrepreneurship that also correlated with the observable ones (Davidsson [<reflink idref="bib21" id="ref100">21</reflink>]). This is particularly true for those unobservable factors affecting self-efficacy. For this reason, we included various controls for unobservable personality traits, attitudes and beliefs, a choice that is also in line with the TPB approach: trust in others; motivations to enrol at university (cultural vs. career motivations); the importance of job security and autonomy in job search. Furthermore, we asked respondents to rank the degree of agreement to the following sentence statements (1–7, with 7 high and 1 low):</p> <p></p> <ulist> <item> Since 'it will be what it will be' I attach little importance to what I do</item> <p></p> <item> I am an impulsive person</item> <p></p> <item> What is important in life is enjoying yourself</item> <p></p> <item> Taking risks allows you to avoid boredom</item> <p></p> <item> My life is controlled by forces that I cannot influence</item> <p></p> <item> There is no point in being worried about the future because we cannot do anything about it</item> <p></p> <item> When I want to do something, I start by identifying my targets and the specific actions I need to take to achieve them</item> <p></p> <item> Tomorrow's commitments and duties are more important than today's pleasures</item> <p></p> <item> I accomplish my projects on time and I prefer to progress constantly</item> </ulist> <p>We were quite confident that the rich set of variables that we include in the estimations allowed us to control for the main unobservable traits that may affect the perceived value of entrepreneurship as a career option. However, we were aware that we could not <emph>overstate</emph> our results as the outcome of causality rather than just correlation.</p> <p>The standard approach to the analysis of the decision to become an entrepreneur, which we adopted here, is based on a probit estimator and, in the case of the degree of engagement in entrepreneurship,[<reflink idref="bib16" id="ref101">16</reflink>] on an ordinal probit (Parker [<reflink idref="bib71" id="ref102">71</reflink>]; Fox [<reflink idref="bib40" id="ref103">40</reflink>]). Our specific focus was on how different sources of entrepreneurial human capital, and in particular those sources that can be related to the university experience, are associated with the entrepreneurial engagement of university students. As a general case, we expected that the degree of association between the former and the latter sources is stronger for intentions than for actual engagement. Our ex ante expectations are summarized in Table 6.</p> <p>Table 6. Expected statistical association.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Factor</td><td>Intentions</td><td>Degree of engagement</td></tr></thead><tbody><tr><td>Gender (female)</td><td>(−)</td><td>(−)</td></tr><tr><td>Family background (father entrepreneur)</td><td>(?)</td><td>(+)</td></tr><tr><td>Age</td><td>(?)</td><td>(+)</td></tr><tr><td>Vocational-oriented upper secondary educational background</td><td>(+)</td><td>(+)</td></tr><tr><td>ICT skills</td><td>(?, +)</td><td>(+)</td></tr><tr><td>Work experience (past or current)</td><td>(?, +)</td><td>(+)</td></tr><tr><td>Internship experience</td><td>(?, +)</td><td>(+)</td></tr><tr><td>BP competition</td><td>(?, +)</td><td>(+)</td></tr><tr><td>Personality trait: trust in others</td><td>(+)</td><td>(+)</td></tr><tr><td>Personality trait: job security important</td><td>(−)</td><td>(−)</td></tr><tr><td>Personality trait: autonomy important</td><td>(+)</td><td>(+)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0139429872-6">4.1. Probit and ordered probit models</hd> <p>The first research question of this paper is to examine the key factors of engagement in the entrepreneurial process. In this case, we estimate a probit equation where the response</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>y</mi><mi>i</mi></msub></math> </ephtml> is binary, taking value one if it turns out they are engaged and zero otherwise. The variable</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>y</mi><mi>i</mi></msub></math> </ephtml> is a realization of a random variable</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mi>i</mi></msub></math> </ephtml> that can take the values one and zero with probabilities</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>π</mi><mi>i</mi></msub></math> </ephtml> and</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>1</mn><mo>−</mo><msub><mi>π</mi><mi>i</mi></msub></math> </ephtml> , respectively. The expected value and variance of</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mi>i</mi></msub></math> </ephtml> is</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>E</mi><mo>(</mo><mi>Y</mi><mo>)</mo><mo>=</mo><msub><mi>μ</mi><mi>i</mi></msub><mo>=</mo><msub><mi>π</mi><mi>i</mi></msub></math> </ephtml> , and</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mtext>Var(</mtext><msub><mi>Y</mi><mi>i</mi></msub><mo>)</mo><mo>=</mo><msubsup><mi>σ</mi><mi>i</mi><mn>2</mn></msubsup><mo>=</mo><msub><mi>π</mi><mi>i</mi></msub><mo>(</mo><mn>1</mn><mo>−</mo><msub><mi>π</mi><mi>i</mi></msub><mo>)</mo></math> </ephtml> .</p> <p>For the case of the degree of involvement in entrepreneurship and to assess intentionality with the continuous measure, we employ the standard ordered probit model. Formally, we let ordered categorical outcome</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi></math> </ephtml> be coded, without loss of generality, in a rank preserving manner, i.e.</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>∈</mo><mo>(</mo><mn>1</mn><mo>,</mo><mn>2</mn><mo>,</mo><mo>...</mo><mi>J</mi><mo>)</mo><mo>,</mo></math> </ephtml> where <emph>J</emph> denotes the total number of distinct categories.</p> <p>In standard ordered response models, the cumulative probabilities of discrete outcomes are related to a single index of explanatory variables in the following way:</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mo movablelimits="false">Pr</mo><mo>[</mo><mi>y</mi><mo>≤</mo><mi>j</mi><mo fence="false">|</mo><mi>x</mi><mo>]</mo><mo>=</mo><mi>F</mi><mo>(</mo><msub><mi>k</mi><mi>j</mi></msub><mo>−</mo><msup><mrow><mi>x</mi></mrow><mrow><mi mathvariant="normal">′</mi></mrow></msup><mtext fontfamily="times">β</mtext><mo>)</mo><mspace width="thinmathspace" /><mo>,</mo><mspace width="thickmathspace" /><mi>j</mi><mo>=</mo><mn>1</mn><mo>,</mo><mo>...</mo><mi>J</mi><mo>,</mo></math> </ephtml> </p> <p>where</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>k</mi><mi>j</mi></msub></math> </ephtml> and</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mtext fontfamily="times">β</mtext><mrow><mo>(</mo><mi>k</mi><mi>x</mi><mn>1</mn><mo>)</mo></mrow></msub></math> </ephtml> denote unknown model parameters, and <emph>F</emph> can be any monotonic increasing function mapping the real line onto the unit interval. Although no further restrictions are imposed <emph>a priori</emph> on the transformation <emph>F</emph>, it is standard practice to replace <emph>F</emph> with a distribution function, the most commonly used ones being the standard normal which yields the ordered probit, and the logistic distribution associated with the ordered logit model.</p> <p>In order to ensure well-defined probabilities, it is required that</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>k</mi><mi>j</mi></msub><mo>></mo><msub><mi>k</mi><mrow><mspace width="thinmathspace" /><mi>j</mi><mo>−</mo><mn>1</mn><mo>,</mo></mrow></msub><mi mathvariant="normal">∀</mi><mi>j</mi><mo>,</mo></math> </ephtml> and it is understood that</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>k</mi><mi>j</mi></msub><mo>=</mo><mi mathvariant="normal">∞</mi></math> </ephtml> such that</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>F</mi><mo>(</mo><mi mathvariant="normal">∞</mi><mo>)</mo><mo>=</mo><mn>1</mn></math> </ephtml> as well</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>k</mi><mn>0</mn></msub><mo>=</mo><mo>−</mo><mi mathvariant="normal">∞</mi></math> </ephtml> and</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>F</mi><mo>(</mo><mspace width="negativethinmathspace" /><mo>−</mo><mspace width="negativethinmathspace" /><mi mathvariant="normal">∞</mi><mo>)</mo><mo>=</mo><mn>0</mn></math> </ephtml> .</p> <p>An underlying continuous but latent process usually motivates response models</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>∗</mo><mspace width="thickmathspace" /></math> </ephtml> together with a response mechanism of the form:</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>=</mo><mi>j</mi><mspace width="thickmathspace" /><mtext>if and only if </mtext><mspace width="thickmathspace" /><msub><mi>k</mi><mrow><mspace width="thinmathspace" /><mi>j</mi><mo>−</mo><mn>1</mn></mrow></msub><mo>≤</mo><mi>y</mi><mo>∗</mo><mo>=</mo><msup><mrow><mi>x</mi></mrow><mrow><mi mathvariant="normal">′</mi></mrow></msup><mtext fontfamily="times">β</mtext><mo>+</mo><mi>μ</mi><mo><</mo><msub><mi>k</mi><mi>j</mi></msub><mo>,</mo><mspace width="thickmathspace" /><mspace width="thickmathspace" /><mi>j</mi><mo>=</mo><mn>1</mn><mo>,</mo><mo>...</mo><mi>J</mi><mo>,</mo></math> </ephtml> </p> <p>where</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>k</mi><mn>0</mn></msub><mo>,</mo><mo>...</mo><msub><mi>k</mi><mi>j</mi></msub></math> </ephtml> are introduced as threshold parameters, discretizing the real line, represented by</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>∗</mo></math> </ephtml> into <emph>J</emph> categories. In our case,</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>∗</mo></math> </ephtml> can be thought of as an unobserved willingness to <emph>be</emph>(<emph>come</emph>) an entrepreneur. The latent variable</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>∗</mo></math> </ephtml> is related linearly to observable and unobservable factors and the latter have a fully specified distribution function</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>F</mi><mo>(</mo><mi>μ</mi><mo>)</mo></math> </ephtml> with zero mean and constant variance.</p> <p>Differently from this latent variable, we observe the variable</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mi>i</mi></msub></math> </ephtml> (the engagement level to which individual <emph>i</emph> belongs) with outcomes</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>y</mi><mi>i</mi></msub></math> </ephtml> where</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>y</mi><mi>i</mi></msub><mo>=</mo><mn>1</mn><mo>,</mo><mn>2</mn><mo>,</mo><mo>...</mo><mo>.</mo><mi>J</mi></math> </ephtml> and <emph>J</emph> is the number of engagement levels.</p> <p>The focus in the analysis of ordered data should be put on the conditional cell probabilities: that is, for</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>j</mi><mo>=</mo><mn>2</mn><mo>,</mo><mo>...</mo><mi>J</mi><mo>−</mo><mn>1</mn></math> </ephtml> , each probability of belonging to engagement level <emph>j</emph> for individual <emph>I</emph> is given by:</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mo movablelimits="false">Pr</mo><mo>[</mo><mi>y</mi><mo>=</mo><mi>j</mi><mo fence="false">|</mo><mi>x</mi><mo>]</mo><mo>=</mo><mi>F</mi><mo>(</mo><msub><mi>k</mi><mi>j</mi></msub><mo>+</mo><msup><mrow><mi>x</mi></mrow><mrow><mi mathvariant="normal">′</mi></mrow></msup><mtext fontfamily="times">β</mtext><mo>)</mo><mo>−</mo><mi>F</mi><mo>(</mo><msub><mi>k</mi><mrow><mspace width="thinmathspace" /><mi>j</mi><mo>−</mo><mn>1</mn></mrow></msub><mo>+</mo><msup><mrow><mi>x</mi></mrow><mrow><mi mathvariant="normal">′</mi></mrow></msup><mtext fontfamily="times">β</mtext><mo>)</mo><mo>.</mo></math> </ephtml> </p> <hd id="AN0139429872-7">4.2. Results</hd> <p>We estimated three models based on G3, G4 and G5. Furthermore, for robustness check, we estimated the entrepreneurial intentions through an ordered probit model by using the score assigned to sentence (b). We obtained quite robust and common evidence (Table 7) on the role of several explanatory factors within the realm of statistical association – which are in line with the expectations and the results obtained in the literature (Delmar and Davidsson [<reflink idref="bib24" id="ref104">24</reflink>]; Davidsson and Honig [<reflink idref="bib22" id="ref105">22</reflink>]; Wagner [<reflink idref="bib91" id="ref106">91</reflink>]; Fairlie and Robb [<reflink idref="bib31" id="ref107">31</reflink>]). In the discussion, we stressed the different roles played by the explanatory variables, if any, in the four models. Gender (female, −), father and mother's occupations (entrepreneur, +), past and current work experience[<reflink idref="bib17" id="ref108">17</reflink>] (+), internship (+) are all significant. The possession of ICT skills, having done an internship and having taken part in a business plan competition also show a positive sign.</p> <p>Table 7. Estimates: entrepreneurial intentions and engagement (robust standard errors).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Entrepreneurial intentions</td><td>Entrepreneurial engagement</td></tr><tr><td /><td>Probit</td><td>Ordered probit</td><td>Probit</td><td>Ordered probit</td></tr></thead><tbody><tr><td>Gender (male)</td><td char=".">−0.18127***</td><td char=".">−0.31402***</td><td char=".">−0.34683***</td><td char=".">−0.33603***</td></tr><tr><td char=".">(0.01479)</td><td char=".">(0.01003)</td><td char=".">(0.01235)</td><td char=".">(0.01158)</td></tr><tr><td>HS diploma grade</td><td char=".">−0.00680***</td><td char=".">−0.00345***</td><td char=".">−0.00327***</td><td char=".">−0.00284***</td></tr><tr><td char=".">(0.00065)</td><td char=".">(0.00044)</td><td char=".">(0.00054)</td><td char=".">(0.00051)</td></tr><tr><td>HS diploma: general education</td><td char=".">−0.04977***</td><td char=".">−0.03362***</td><td char=".">−0.03571**</td><td char=".">−0.03600***</td></tr><tr><td char=".">(0.01659)</td><td char=".">(0.01135)</td><td char=".">(0.01402)</td><td char=".">(0.01307)</td></tr><tr><td>University average mark</td><td char=".">−0.02694**</td><td char=".">−0.00187</td><td char=".">−0.00894</td><td char=".">−0.01567*</td></tr><tr><td char=".">(0.01104)</td><td char=".">(0.00739)</td><td char=".">(0.00916)</td><td char=".">(0.00864)</td></tr><tr><td>Graduation grade</td><td char=".">−0.00539**</td><td char=".">−0.00268</td><td char=".">−0.00219</td><td char=".">−0.00157</td></tr><tr><td char=".">(0.00265)</td><td char=".">(0.00179)</td><td char=".">(0.00221)</td><td char=".">(0.00208)</td></tr><tr><td>Age at graduation</td><td char=".">−0.00781***</td><td char=".">0.00222*</td><td char=".">0.00621***</td><td char=".">0.00931***</td></tr><tr><td char=".">(0.00180)</td><td char=".">(0.00132)</td><td char=".">(0.00140)</td><td char=".">(0.00136)</td></tr><tr><td><italic>Field of study (Agriculture and veterinary default)</italic></td></tr><tr><td>Architecture</td><td char=".">0.28365***</td><td char=".">0.18049***</td><td char=".">0.11976***</td><td char=".">0.09243**</td></tr><tr><td char=".">(0.05498)</td><td char=".">(0.03566)</td><td char=".">(0.04494)</td><td char=".">(0.04219)</td></tr><tr><td>Chemistry</td><td char=".">0.15015***</td><td char=".">0.13423***</td><td char=".">0.09593**</td><td char=".">0.06524*</td></tr><tr><td char=".">(0.04963)</td><td char=".">(0.03159)</td><td char=".">(0.03951)</td><td char=".">(0.03730)</td></tr><tr><td>Economics, business and statistics</td><td char=".">0.00884</td><td char=".">−0.02009</td><td char=".">−0.00979</td><td char=".">−0.02808</td></tr><tr><td char=".">(0.04490)</td><td char=".">(0.02833)</td><td char=".">(0.03519)</td><td char=".">(0.03341)</td></tr><tr><td>Physical education</td><td char=".">0.32718***</td><td char=".">0.20831***</td><td char=".">0.14392***</td><td char=".">0.11333***</td></tr><tr><td char=".">(0.04380)</td><td char=".">(0.02765)</td><td char=".">(0.03499)</td><td char=".">(0.03301)</td></tr><tr><td>Biology</td><td char=".">0.42353***</td><td char=".">0.40757***</td><td char=".">0.40899***</td><td char=".">0.33967***</td></tr><tr><td char=".">(0.05273)</td><td char=".">(0.03445)</td><td char=".">(0.04374)</td><td char=".">(0.04003)</td></tr><tr><td>Law</td><td char=".">0.51292***</td><td char=".">0.49080***</td><td char=".">0.46541***</td><td char=".">0.40233***</td></tr><tr><td char=".">(0.05456)</td><td char=".">(0.03717)</td><td char=".">(0.04602)</td><td char=".">(0.04164)</td></tr><tr><td>Engineering</td><td char=".">0.45071***</td><td char=".">0.22377***</td><td char=".">0.21112***</td><td char=".">0.19839***</td></tr><tr><td char=".">(0.04286)</td><td char=".">(0.02740)</td><td char=".">(0.03438)</td><td char=".">(0.03266)</td></tr><tr><td>Teaching</td><td char=".">0.16931***</td><td char=".">0.12578***</td><td char=".">0.14196***</td><td char=".">0.13799***</td></tr><tr><td char=".">(0.04655)</td><td char=".">(0.02975)</td><td char=".">(0.03684)</td><td char=".">(0.03519)</td></tr><tr><td>Humanities</td><td char=".">0.12270**</td><td char=".">0.09981***</td><td char=".">0.07072*</td><td char=".">0.06496*</td></tr><tr><td char=".">(0.05095)</td><td char=".">(0.03314)</td><td char=".">(0.04064)</td><td char=".">(0.03924)</td></tr><tr><td>Languages</td><td char=".">0.05631</td><td char=".">0.15304***</td><td char=".">0.17531***</td><td char=".">0.16608***</td></tr><tr><td char=".">(0.05005)</td><td char=".">(0.03125)</td><td char=".">(0.03837)</td><td char=".">(0.03659)</td></tr><tr><td>Medicine</td><td char=".">0.04872</td><td char=".">0.00276</td><td char=".">0.00836</td><td char=".">−0.00342</td></tr><tr><td char=".">(0.05345)</td><td char=".">(0.03306)</td><td char=".">(0.04157)</td><td char=".">(0.03988)</td></tr><tr><td>Political sciences</td><td char=".">0.04488</td><td char=".">0.17554***</td><td char=".">0.21479***</td><td char=".">0.16870***</td></tr><tr><td char=".">(0.05491)</td><td char=".">(0.03510)</td><td char=".">(0.04253)</td><td char=".">(0.04052)</td></tr><tr><td>Psychology</td><td char=".">−0.00750</td><td char=".">0.10832***</td><td char=".">0.09720**</td><td char=".">0.08153**</td></tr><tr><td char=".">(0.05437)</td><td char=".">(0.03387)</td><td char=".">(0.04195)</td><td char=".">(0.04000)</td></tr><tr><td>Science</td><td char=".">0.22607***</td><td char=".">0.24518***</td><td char=".">0.22189***</td><td char=".">0.13929***</td></tr><tr><td char=".">(0.06194)</td><td char=".">(0.04054)</td><td char=".">(0.05122)</td><td char=".">(0.04644)</td></tr><tr><td>Erasmus (yes)</td><td char=".">0.09598</td><td char=".">0.11908</td><td char=".">0.15013</td><td char=".">0.12449</td></tr><tr><td char=".">(0.11764)</td><td char=".">(0.08275)</td><td char=".">(0.10310)</td><td char=".">(0.08907)</td></tr><tr><td>Internship (yes)</td><td char=".">0.05573***</td><td char=".">0.07199***</td><td char=".">0.06616***</td><td char=".">0.06482***</td></tr><tr><td char=".">(0.01509)</td><td char=".">(0.01000)</td><td char=".">(0.01251)</td><td char=".">(0.01170)</td></tr><tr><td>Participation in business plan competition</td><td char=".">0.33593***</td><td char=".">0.53521***</td><td char=".">0.73077***</td><td char=".">0.92619***</td></tr><tr><td char=".">(0.05139)</td><td char=".">(0.03948)</td><td char=".">(0.05199)</td><td char=".">(0.04401)</td></tr><tr><td>ICT skills (yes)</td><td char=".">0.06991**</td><td char=".">0.17513***</td><td char=".">0.16952***</td><td char=".">0.15918***</td></tr><tr><td char=".">(0.03173)</td><td char=".">(0.02064)</td><td char=".">(0.02495)</td><td char=".">(0.02464)</td></tr><tr><td><italic>Social class (petite bourgeoisie default)</italic></td></tr><tr><td>Middle class</td><td char=".">−0.03617</td><td char=".">−0.03708**</td><td char=".">−0.03319*</td><td char=".">−0.03413*</td></tr><tr><td char=".">(0.02420)</td><td char=".">(0.01621)</td><td char=".">(0.01997)</td><td char=".">(0.01882)</td></tr><tr><td>Petite bourgeoisie</td><td char=".">0.09996***</td><td char=".">0.05976***</td><td char=".">0.08563***</td><td char=".">0.08138***</td></tr><tr><td char=".">(0.02392)</td><td char=".">(0.01645)</td><td char=".">(0.02014)</td><td char=".">(0.01892)</td></tr><tr><td>Working class</td><td char=".">−0.09537***</td><td char=".">−0.10921***</td><td char=".">−0.09971***</td><td char=".">−0.10053***</td></tr><tr><td char=".">(0.02641)</td><td char=".">(0.01768)</td><td char=".">(0.02179)</td><td char=".">(0.02048)</td></tr><tr><td>Cultural motivations to enrol</td><td char=".">−0.02287</td><td char=".">−0.02447</td><td char=".">−0.06426*</td><td char=".">−0.08102**</td></tr><tr><td char=".">(0.04086)</td><td char=".">(0.02904)</td><td char=".">(0.03393)</td><td char=".">(0.03239)</td></tr><tr><td>Professional motivations to enrol</td><td char=".">0.07644***</td><td char=".">0.01193</td><td char=".">−0.02405</td><td char=".">−0.03714**</td></tr><tr><td char=".">(0.02118)</td><td char=".">(0.01368)</td><td char=".">(0.01654)</td><td char=".">(0.01579)</td></tr><tr><td>Past work experience</td><td char=".">0.06220***</td><td char=".">0.17487***</td><td char=".">0.18474***</td><td char=".">0.19680***</td></tr><tr><td char=".">(0.01505)</td><td char=".">(0.00985)</td><td char=".">(0.01245)</td><td char=".">(0.01152)</td></tr><tr><td>Current work experience</td><td char=".">0.09535***</td><td char=".">0.07339***</td><td char=".">0.09428***</td><td char=".">0.15639***</td></tr><tr><td char=".">(0.01727)</td><td char=".">(0.01191)</td><td char=".">(0.01454)</td><td char=".">(0.01380)</td></tr><tr><td>Trust in others</td><td char=".">0.03938***</td><td char=".">0.10644***</td><td char=".">0.09641***</td><td char=".">0.07205***</td></tr><tr><td char=".">(0.01365)</td><td char=".">(0.00919)</td><td char=".">(0.01134)</td><td char=".">(0.01054)</td></tr><tr><td>Father entrepreneur</td><td char=".">0.15047***</td><td char=".">0.08609***</td><td char=".">0.10417***</td><td char=".">0.12272***</td></tr><tr><td char=".">(0.02117)</td><td char=".">(0.01473)</td><td char=".">(0.01803)</td><td char=".">(0.01692)</td></tr><tr><td>Mother entrepreneur</td><td char=".">0.13656***</td><td char=".">0.08509***</td><td char=".">0.08510***</td><td char=".">0.08199***</td></tr><tr><td char=".">(0.02832)</td><td char=".">(0.02003)</td><td char=".">(0.02451)</td><td char=".">(0.02286)</td></tr><tr><td>Father educational attainment</td><td char=".">−0.01672*</td><td char=".">0.02540***</td><td char=".">0.02498***</td><td char=".">0.02450***</td></tr><tr><td char=".">(0.00890)</td><td char=".">(0.00603)</td><td char=".">(0.00745)</td><td char=".">(0.00701)</td></tr><tr><td>Mother educational attainment</td><td char=".">−0.02650***</td><td char=".">−0.00653</td><td char=".">0.00667</td><td char=".">0.00989</td></tr><tr><td char=".">(0.00827)</td><td char=".">(0.00572)</td><td char=".">(0.00693)</td><td char=".">(0.00647)</td></tr><tr><td>Degree level 1 (3 + 2 years default = BA, 3 years)</td><td char=".">−0.06080</td><td char=".">−0.06273**</td><td char=".">−0.02132</td><td char=".">−0.02403</td></tr><tr><td char=".">(0.04075)</td><td char=".">(0.02746)</td><td char=".">(0.03271)</td><td char=".">(0.03013)</td></tr><tr><td>Degree level 2 (5 years default = BA, 3 years)</td><td char=".">0.02593</td><td char=".">−0.03643***</td><td char=".">0.00250</td><td char=".">0.02636*</td></tr><tr><td char=".">(0.01840)</td><td char=".">(0.01233)</td><td char=".">(0.01495)</td><td char=".">(0.01416)</td></tr><tr><td>Job security important</td><td char=".">−0.09416***</td><td char=".">−0.14702***</td><td char=".">−0.12417***</td><td char=".">−0.14775***</td></tr><tr><td char=".">(0.02775)</td><td char=".">(0.01998)</td><td char=".">(0.02282)</td><td char=".">(0.02142)</td></tr><tr><td>Autonomy important</td><td char=".">0.30595***</td><td char=".">0.28707***</td><td char=".">0.31782***</td><td char=".">0.29631***</td></tr><tr><td char=".">(0.02336)</td><td char=".">(0.01383)</td><td char=".">(0.01806)</td><td char=".">(0.01770)</td></tr><tr><td>University controls</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Control for attitudinal factors (see i–vii)</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Dummy for the region of birth</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Obs.</td><td char=".">59.553</td><td char=".">59.553</td><td char=".">59,553</td><td char=".">59,553</td></tr><tr><td>Wald chi<sup>2</sup></td><td char=".">7722.83</td><td char=".">8557.63</td><td char=".">6737.90</td><td char=".">7392.35</td></tr><tr><td>Prob. > chi<sup>2</sup></td><td char=".">0.0000</td><td char=".">0.0000</td><td char=".">0.0000</td><td char=".">0.0000</td></tr><tr><td>Pseudo <italic>R</italic><sup>2</sup></td><td char=".">0.1688</td><td char=".">0.0388</td><td char=".">0.0935</td><td char=".">0.0796</td></tr></tbody></table> </ephtml> </p> <p>***= sig. 1%; **= sig. 5%; *= sig. 10%, Robust standard errors.</p> <p>Most of the controls for attitudinal factors are also significant and show the expected sign in accordance with underpinnings of TPB.</p> <p>Individuals for whom autonomy is important are keener to start a business, whereas the opposite holds for individuals looking for security in life. Students who are more willing to engage in entrepreneurship do not appear to be the best performers at school and university (lower high school diploma grade as well as average university grade). One may wonder if schools and universities' assessment systems are appropriate to reveal entrepreneurial skills. The latter evidence is also consistent with the result that enrolment in courses such Economics and Statistics is not statistically significant (see below).</p> <p>In socially stratified societies, entrepreneurship can be seen as a means of social mobility and Italy cannot be considered today a socially mobile economy (OECD [<reflink idref="bib68" id="ref109">68</reflink>]). Assuming that one can rank different social classes in descending order (bourgeoisie, petite bourgeoisie, middle class, working class), the social background has <emph>non-linear</emph> effects on the degree of engagement and entrepreneurial intentions. Coming from the <emph>petite bourgeoisie</emph> class seems highly favourable to entrepreneurship than from the bourgeoisie class (default, 99%), whereas coming from the middle and the working classes has a negative effect (default, 99%). This outcome could be attributed to the joint effects of the presence of social barriers in specific occupations, characterized by high intergenerational persistence in Italy (i.e. lawyer), the importance of social networks in entrepreneurship and families' role in shaping occupational expectations. It seems entrepreneurship is a better career option and avenue for social mobility for individuals with a <emph>petite bourgeoisie</emph> background.</p> <p>Also, the field of study effect shows consistent results across the four models and unexpected outcomes in the order of students' disciplines: Law, Engineering, Physical Education and Science students being more favourably inclined to entrepreneurial engagement. A striking exception is Economics and Statistics students who seem to be less willing to be engaged. We suggested two interpretations for this puzzling phenomenon or result: (a) students of Economics and Statistics, particularly those in Italy[<reflink idref="bib18" id="ref110">18</reflink>] acquire, during their university studies, better skills for analysing and solving difficulties pertaining to enterprise start-up and operation. Inadvertently, the skills and knowledge lead them to develop psychological barriers to starting their own businesses. Consequent to this outcome, we suggest that entrepreneurship education and transferrable technical skills need to be jointly provided to enable the cultivation of a positive entrepreneurial attitude.</p> <p>The distinction between general and vocational secondary education seems to matter: students with a general education, i.e. lyceum diploma, appear to be less willing to be engaged at any stage of the process.</p> <p>Students' <emph>trust in others</emph> has a positive and significant effect in the three models. This result is in line with the literature on the positive role of trust in entrepreneurship (Ferrante and Ruiu [<reflink idref="bib35" id="ref111">35</reflink>]).</p> <p>Dummies for geographical mobility (Table 8) confirm that the North of the country is the most favourable area to start a business, in particular for students coming from the South or abroad.</p> <p>Table 8. Estimates: geographical mobility and occupational opportunity (robust standard errors).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Entrepreneurial intentions</td><td>Entrepreneurial engagement</td></tr><tr><td /><td>Probit</td><td>Ordered probit</td><td>Probit</td><td>Ordered probit</td></tr></thead><tbody><tr><td>NN</td><td char=".">0.48318</td><td char=".">0.60332***</td><td char=".">0.67786**</td><td char=".">0.69137***</td></tr><tr><td char=".">(0.30406)</td><td char=".">(0.20213)</td><td char=".">(0.26442)</td><td char=".">(0.23566)</td></tr><tr><td>NC</td><td char=".">0.11108</td><td char=".">0.08305</td><td char=".">0.09894</td><td char=".">0.20242</td></tr><tr><td char=".">(0.22002)</td><td char=".">(0.15939)</td><td char=".">(0.19364)</td><td char=".">(0.17790)</td></tr><tr><td>NS</td><td char=".">−0.00713</td><td char=".">0.15985</td><td char=".">0.10076</td><td char=".">0.10441</td></tr><tr><td char=".">(0.14484)</td><td char=".">(0.10711)</td><td char=".">(0.12706)</td><td char=".">(0.11927)</td></tr><tr><td>CC</td><td char=".">0.05379</td><td char=".">0.06881</td><td char=".">0.10509</td><td char=".">0.20009</td></tr><tr><td char=".">(0.21603)</td><td char=".">(0.15698)</td><td char=".">(0.19067)</td><td char=".">(0.17494)</td></tr><tr><td>CN</td><td char=".">0.47256</td><td char=".">0.69723***</td><td char=".">0.73078***</td><td char=".">0.72834***</td></tr><tr><td char=".">(0.31212)</td><td char=".">(0.20705)</td><td char=".">(0.27010)</td><td char=".">(0.24118)</td></tr><tr><td>CS</td><td char=".">−0.16233</td><td char=".">0.21978**</td><td char=".">0.10531</td><td char=".">0.10709</td></tr><tr><td char=".">(0.14867)</td><td char=".">(0.10777)</td><td char=".">(0.12964)</td><td char=".">(0.11915)</td></tr><tr><td>SS</td><td char=".">−0.09555</td><td char=".">0.19626**</td><td char=".">0.15688*</td><td /></tr><tr><td char=".">(0.10599)</td><td char=".">(0.08129)</td><td char=".">(0.09511)</td><td char=".">(0.08948)</td></tr><tr><td>SC</td><td char=".">0.19094</td><td char=".">0.18484</td><td char=".">0.22485</td><td char=".">0.30120*</td></tr><tr><td char=".">(0.21646)</td><td char=".">(0.15726)</td><td char=".">(0.19111)</td><td char=".">(0.17532)</td></tr><tr><td>SN</td><td char=".">0.61148**</td><td char=".">0.75776***</td><td char=".">0.84014***</td><td char=".">0.83408***</td></tr><tr><td char=".">(0.30723)</td><td char=".">(0.20423)</td><td char=".">(0.26693)</td><td char=".">(0.23785)</td></tr><tr><td>AN</td><td char=".">0.83145***</td><td char=".">0.72727***</td><td char=".">0.83763***</td><td char=".">0.85997***</td></tr><tr><td char=".">(0.31312)</td><td char=".">(0.21011)</td><td char=".">(0.27293)</td><td char=".">(0.24376)</td></tr><tr><td>AC</td><td char=".">0.13403</td><td char=".">0.15857</td><td char=".">0.23858</td><td char=".">0.32620*</td></tr><tr><td char=".">(0.22322)</td><td char=".">(0.16250)</td><td char=".">(0.19669)</td><td char=".">(0.18077)</td></tr><tr><td>AS (default)</td><td /><td /><td /><td /></tr></tbody></table> </ephtml> </p> <p>***= sig. 1%; **= sig. 5%; *= sig. 10%, Robust standard errors.</p> <p>This is not surprising and suggests that since the Northern part of the country provides better employment and <emph>self-employment</emph> opportunities to young people, the net effect on occupational choice is favourable to entrepreneurship as a career option.</p> <p>To obtain further insights, we computed the marginal probability effects for the ordinal probit model looking at the degree of entrepreneurial engagement (see Appendix). They provide information on those factors playing a major role in the transition from <emph>intention to action</emph>. First, as one may expect, most of the impact is absorbed by the transition from being non-entrepreneurs to being an intentional entrepreneur. Second, the transition from being an intentional to being an active entrepreneur is much more affected by the different mediating factors than the transition from being a nascent to being an active one. The systematic non-linear pattern in transition probabilities is shown in Figure 1, where at zero we measure, on the vertical axis, the impact on the transition probability from the category of non-entrepreneurs to the category of intentional entrepreneurs. Table 8 shows the impact on the transition probabilities of a selection of factors providing information about activities universities can perform to promote the transition from entrepreneurial intention to entrepreneurial action. The organization of business plan competitions appears to be quite effective as it increases the probability of passing from the group of intentional to the group of actual entrepreneurs by almost 7%. The overall impact of the factors selected on the transition probability is 11.5%.</p> <p>PHOTO (COLOR): Figure 1. Degree of entrepreneurial engagement – pattern of transition probabilities.</p> <p>Transition probabilities also provide information on those personal traits that should be cultivated through entrepreneurial education, at any age, to close the gap between intention and action (trust in others (+), search for autonomy (+) and job security (−)) (Table 9).</p> <p>Table 9. Impact of a selection of mediating factors on transition probabilities.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>⇒Intentional (%)</td><td>⇒Nascent (%)</td><td>⇒Active (%)</td><td>From intentional to active (%)</td></tr></thead><tbody><tr><td>Participation in business plan competitions</td><td char=".">28.0</td><td char=".">4.9</td><td char=".">2.3</td><td char=".">7.1</td></tr><tr><td>Past work experience</td><td char=".">5.9</td><td char=".">1.0</td><td char=".">0.5</td><td char=".">1.5</td></tr><tr><td>ICT skills</td><td char=".">4.8</td><td char=".">0.8</td><td char=".">0.4</td><td char=".">1.2</td></tr><tr><td>Current work experience</td><td char=".">4.7</td><td char=".">0.8</td><td char=".">0.4</td><td char=".">1.2</td></tr><tr><td>Internship</td><td char=".">2.0</td><td char=".">0.3</td><td char=".">0.2</td><td char=".">0.5</td></tr></tbody></table> </ephtml> </p> <hd id="AN0139429872-8">5. Discussion and conclusions</hd> <p>The waves of technological, organizational and financial innovations that started about 40 years ago with the ICT revolution brought about an acceleration in the pace of economic and social change (Nordhaus [<reflink idref="bib67" id="ref112">67</reflink>]) that has entailed a compression of the knowledge life cycle. Consequently, the value of tacit knowledge acquired through experience has decreased with respect to the value of codified knowledge acquired through formal education (Schultz [<reflink idref="bib79" id="ref113">79</reflink>]; De Bruin and Ferrante [<reflink idref="bib23" id="ref114">23</reflink>]). The resulting change in human capital required in entrepreneurship resulting from a more intense process of 'creative destruction' can be described as (a) an increase in the minimum amount of codified knowledge necessary to generate a unit of entrepreneurial human capital, and (b) a reduction in the degree of substitutability between codified and tacit knowledge (Ferrante [<reflink idref="bib34" id="ref115">34</reflink>]).</p> <p>It appears higher education has become an important ingredient of entrepreneurial human capital. A case in point is the increase of high education premium in the US where entrepreneurs dominate in uptake of education premium compared to employees (Michelacci and Schivardi [<reflink idref="bib62" id="ref116">62</reflink>]). Although the actual relevance of education in entrepreneurship may vary from country to country, one should expect that, at least among the advanced countries, the above trend is a common one.</p> <p>The Italian scenario in relation to this finding is worrying. The share of Italian entrepreneurs with tertiary educations is relatively low, and this is also the case of the younger generation of entrepreneurs. The AlmaLaurea surveys on new cohorts of university graduates, including the survey presented here, confirm this 'not-so-good' picture.</p> <p>In this paper, we developed a novel empirical approach, based on the idea that entrepreneurship is a process, to assess the entrepreneurial engagement of Italian university students and barriers deterring entrepreneurial engagement. We are aware that our findings should be validated by means of panel data analysis. Besides, they provide interesting preliminary insights into factors affecting entrepreneurial engagement.</p> <p>The good news provided by our analysis is that there is a large potential supply of entrepreneurs in Italy with tertiary education, consisting of those students who can be considered <emph>intentional entrepreneurs</emph> (33%). The share of intentional entrepreneurs is substantial in study fields such as Law (48.5%), and also in STEM curricula like Biology (43.7%) and Science (41.5%). Surprisingly, the share is relatively small in Economics, Business and Statistics, an outcome that is confirmed by our regressions which shows that being enrolled in these courses does not have a significant impact either on the entrepreneurial intentions or on the degree of entrepreneurial engagement.</p> <p>According to the TPB, intentions are good predictors of actual behaviours and the evidence based on the theory shows that the degree of correlation between intentions and decision to become entrepreneurs is quite large (Sheeran [<reflink idref="bib85" id="ref117">85</reflink>]). Unfortunately, the very small share of graduates, monitored by AlmaLaurea five years after graduation, who declare to be entrepreneurs (1.3%), would suggest that, in Italy, there are abnormal barriers deterring a significant share of these intentional entrepreneurs from becoming actual entrepreneurs.</p> <p>This evidence evocates an initial educational management implication which may suggest that the first step to take here is to improve the entrepreneurial awareness and alertness of Italian graduates. This may seem to confirm that entrepreneurial education does necessarily not coincide with business education[<reflink idref="bib19" id="ref118">19</reflink>] (Bae et al. [<reflink idref="bib7" id="ref119">7</reflink>]).</p> <p>Table 3 shows that factors determining barriers to entrepreneurship may differ among gender, the field of study, etc. Some groups show good intentions for engagement but have relatively low propensity to be actively engaged in entrepreneurship that could benefit them more. For example, women appear to suffer relatively more from these barriers and are the group to target most (Kauffman Foundation [<reflink idref="bib50" id="ref120">50</reflink>]). But there is something universities can do independently from the nature of the existing barriers. Curricular and extra-curricular courses of entrepreneurial education (Katz [<reflink idref="bib48" id="ref121">48</reflink>]; Kuratko [<reflink idref="bib55" id="ref122">55</reflink>]; Nabi and Holden [<reflink idref="bib66" id="ref123">66</reflink>]; European Commission [<reflink idref="bib28" id="ref124">28</reflink>]; Kauffman Foundation [<reflink idref="bib49" id="ref125">49</reflink>]; Ferrante and Supino [<reflink idref="bib37" id="ref126">37</reflink>]), based on the concepts of interdisciplinary contamination and lateral thinking, appear to be effective tools with which to provide the appropriate entrepreneurial skills and attitudes and to lower the psychological and cultural barriers, often related to role models, which may limit access to entrepreneurship.</p> <p>The AlmaLaurea surveys on graduates' occupational status show that those graduates who have embraced entrepreneurship as a career choice are more satisfied with their jobs than other colleagues are. On the other hand, they declare that the skills acquired at the university are not as effective as declared by their colleagues doing other jobs. Surprisingly, graduates who opted for entrepreneurship and hold a degree in economics are also not very satisfied with their skills.</p> <p>The scopes for the provision of entrepreneurship education by HEIs are several and they are not confined to the aim to generate new ventures (Kuratko [<reflink idref="bib55" id="ref127">55</reflink>]). The positive role of education in entrepreneurship can be assessed through different approaches. First, according to human capital theory, education can cultivate those cognitive and non-cognitive skills needed to perform entrepreneurial and managerial tasks (Becker [<reflink idref="bib9" id="ref128">9</reflink>]; Cunha and Heckman [<reflink idref="bib18" id="ref129">18</reflink>]; Corduras Martinez et al. [<reflink idref="bib16" id="ref130">16</reflink>]). Education can also enhance students' attitudes and intentions, as well as the founding of a new firm (Liñán [<reflink idref="bib58" id="ref131">58</reflink>]). Martin, McNally, and Kay ([<reflink idref="bib60" id="ref132">60</reflink>]) offer empirical support to these conclusions. Second, according to TPB, entrepreneurship education can enhance self-efficacy and, thereby, entrepreneurial intentions (Zhao, Seibert, and Hills [<reflink idref="bib96" id="ref133">96</reflink>]; Wilson, Kickul, and Marlino [<reflink idref="bib94" id="ref134">94</reflink>]; Bae et al. [<reflink idref="bib7" id="ref135">7</reflink>]).</p> <p>More generally, entrepreneurial education can cultivate students' propensity to act in an entrepreneurial way; and, although university graduates do not start their own businesses, their employability is positively affected by this attitude (European Commission [<reflink idref="bib27" id="ref136">27</reflink>], [<reflink idref="bib29" id="ref137">29</reflink>]), mainly due to its impact on more effective job search strategies.</p> <p>Another benefit of entrepreneurial education is that it develops <emph>intrapreneurship</emph>, an attitude that is very much appreciated by employers. Indeed, most graduates find jobs as employees, and their endowment with an entrepreneurial spirit can contribute substantially to fostering the innovation and competitiveness of the organizations for which they work.</p> <p>The need for university action stems also from the recognition that, according to our survey, only a small percentage of student entrepreneurs have attended an entrepreneurship course or participated in a business competition, and that they have indicated the importance of these instruments. Among those who had no chance to benefit from these opportunities, about 80% would have liked to do so.</p> <p>We showed that a vocational-oriented upper secondary school education is favourable to entrepreneurship: internships during the university experience, which show a significant positive sign in all our estimations, could be a means to cultivate in university students, in particular in those holding a general background, those vocational skills that they did not have a chance to acquire in their studies.</p> <p>According to our estimations, other tools to cultivate an entrepreneurial attitude among university students are ICT skills. Indeed, the Fourth Industrial Revolution, i.e. Industry 4.0, is generating entrepreneurial opportunities whose recognition and exploitation will require stronger ICT skills than in the past and the development of technologies based on AI will reinforce this trend.</p> <p>In conclusion, there are many things that HEIs can and should do, in particular in Italy, to trigger the entrepreneurial process among university students and graduates and to close the gap between entrepreneurial intentions and action.</p> <hd id="AN0139429872-9">Acknowledgements</hd> <p>We would like to acknowledge valuable comments by two anonymous referees. The usual disclaimer applies.</p> <hd id="AN0139429872-10">Disclosure statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0139429872-11">ORCID</hd> <p> <emph>Francesco Ferrante</emph> <ulink href="http://orcid.org/0000-0002-4154-6451">http://orcid.org/0000-0002-4154-6451</ulink> </p> <hd id="AN0139429872-12">Appendix. Marginal probability effects</hd> <p>Additional information can be gained by computing the marginal probability effects, i.e. the shift of the predicted discrete ordered outcome distribution as one or more of the regressors change. These partial effects give the impacts on the specific probabilities per unit change in the variables. In general, the magnitude of these probability changes depends on the specific values of the</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>i</mi><mrow><mi>t</mi><mi>h</mi></mrow></msub></math> </ephtml> observation's covariates.</p> <p>Table 10 is based on the ordinal probit model and reports the change in the respective probabilities of being engaged in different stages of the entrepreneurial process due to a change in the regressors. We interpret the signs of the partial effects as follows: where we consider a variable with a positive coefficient (like trust, ICT, etc.), increases in that variable will increase the probability of engagement at that level and decrease the probability in the lowest level. These are reversed for a variable with a negative coefficient. For instance, the change in the probability of non-entrepreneurs passing from the group of non-intentional to the group of intentional entrepreneurs for those who attended a business plan competition is about 20%.</p> <p>Table 10. Marginal effects (coefficients are reported only if significant at least at 10%).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Entrepreneurial engagement (ordered probit)</td></tr><tr><td>Intentional entrepreneurs</td><td>Nascent entrepreneurs</td><td>Active entrepreneurs</td></tr></thead><tbody><tr><td>Gender (male)</td><td>−0.10147***</td><td char=".">−0.01770***</td><td char=".">−0.00822***</td></tr><tr><td>(0.00356)</td><td char=".">(0.00070)</td><td char=".">(0.00038)</td></tr><tr><td>HS diploma grade</td><td>−0.00086***</td><td char=".">−0.00015***</td><td char=".">−0.00007***</td></tr><tr><td>(0.00015)</td><td char=".">(0.00003)</td><td char=".">(0.00001)</td></tr><tr><td>HS diploma</td><td>−0.01086***</td><td char=".">−0.00192***</td><td char=".">−0.00090***</td></tr><tr><td>(0.00394)</td><td char=".">(0.00071)</td><td char=".">(0.00034)</td></tr><tr><td>University average mark</td><td>−0.00473*</td><td char=".">−0.00083*</td><td char=".">−0.00038*</td></tr><tr><td>(0.00261)</td><td char=".">(0.00046)</td><td char=".">(0.00021)</td></tr><tr><td>Graduation grade</td><td /><td /><td /></tr><tr><td>Age at graduation</td><td>0.00281***</td><td char=".">0.00049***</td><td char=".">0.00023***</td></tr><tr><td>(0.00041)</td><td char=".">(0.00007)</td><td char=".">(0.00003)</td></tr><tr><td><italic>Field of study</italic></td></tr><tr><td>Architecture</td><td>0.02791**</td><td char=".">0.00443**</td><td char=".">0.00196**</td></tr><tr><td>(0.01273)</td><td char=".">(0.00203)</td><td char=".">(0.00091)</td></tr><tr><td>Chemistry</td><td>0.01970*</td><td char=".">0.00306*</td><td char=".">0.00134*</td></tr><tr><td>(0.01125)</td><td char=".">(0.00173)</td><td char=".">(0.00075)</td></tr><tr><td>Economics and statistics</td><td /><td /><td /></tr><tr><td>Physical education</td><td>0.03423***</td><td char=".">0.00552***</td><td char=".">0.00247***</td></tr><tr><td>(0.00995)</td><td char=".">(0.00154)</td><td char=".">(0.00068)</td></tr><tr><td>Biology</td><td>0.10093***</td><td char=".">0.01980***</td><td char=".">0.00984***</td></tr><tr><td>(0.01176)</td><td char=".">(0.00238)</td><td char=".">(0.00127)</td></tr><tr><td>Law</td><td>0.11834***</td><td char=".">0.02457***</td><td char=".">0.01261***</td></tr><tr><td>(0.01200)</td><td char=".">(0.00270)</td><td char=".">(0.00153)</td></tr><tr><td>Engineering</td><td>0.05977***</td><td char=".">0.01036***</td><td char=".">0.00481***</td></tr><tr><td>(0.00982)</td><td char=".">(0.00158)</td><td char=".">(0.00072)</td></tr><tr><td>Teaching</td><td>0.04166***</td><td char=".">0.00686***</td><td char=".">0.00310***</td></tr><tr><td>(0.01060)</td><td char=".">(0.00169)</td><td char=".">(0.00076)</td></tr><tr><td>Humanities</td><td>0.01961*</td><td char=".">0.00304*</td><td char=".">0.00133*</td></tr><tr><td>(0.01184)</td><td char=".">(0.00183)</td><td char=".">(0.00080)</td></tr><tr><td>Languages</td><td>0.05011***</td><td char=".">0.00845***</td><td char=".">0.00387***</td></tr><tr><td>(0.01101)</td><td char=".">(0.00182)</td><td char=".">(0.00084)</td></tr><tr><td>Medicine</td><td /><td /><td /></tr><tr><td>Political sciences</td><td>0.05089***</td><td char=".">0.00860***</td><td char=".">0.00394***</td></tr><tr><td>(0.01218)</td><td char=".">(0.00207)</td><td char=".">(0.00097)</td></tr><tr><td>Psychology</td><td>0.02462**</td><td char=".">0.00387**</td><td char=".">0.00171**</td></tr><tr><td>(0.01207)</td><td char=".">(0.00189)</td><td char=".">(0.00084)</td></tr><tr><td>Science</td><td>0.04205***</td><td char=".">0.00693***</td><td char=".">0.00314***</td></tr><tr><td>(0.01399)</td><td char=".">(0.00238)</td><td char=".">(0.00110)</td></tr><tr><td>Erasmus (yes)</td><td /><td /><td /></tr><tr><td>Internship (yes)</td><td>0.01957***</td><td char=".">0.00341***</td><td char=".">0.00159***</td></tr><tr><td>(0.00354)</td><td char=".">(0.00062)</td><td char=".">(0.00029)</td></tr><tr><td>Participation in business plan competition</td><td>0.27969***</td><td char=".">0.04878***</td><td char=".">0.02267***</td></tr><tr><td>(0.01345)</td><td char=".">(0.00257)</td><td char=".">(0.00123)</td></tr><tr><td>ICT skills (yes)</td><td>0.04807***</td><td char=".">0.00838***</td><td char=".">0.00390***</td></tr><tr><td>(0.00745)</td><td char=".">(0.00131)</td><td char=".">(0.00061)</td></tr><tr><td><italic>Social class (petite bourgeoisie default)</italic></td></tr><tr><td>Middle class</td><td>−0.01030*</td><td char=".">−0.00181*</td><td char=".">−0.00084*</td></tr><tr><td>(0.00568)</td><td char=".">(0.00100)</td><td char=".">(0.00047)</td></tr><tr><td>Petite bourgeoisie</td><td>0.02439***</td><td char=".">0.00470***</td><td char=".">0.00230***</td></tr><tr><td>(0.00568)</td><td char=".">(0.00108)</td><td char=".">(0.00053)</td></tr><tr><td>Working class</td><td>−0.03037***</td><td char=".">−0.00505***</td><td char=".">−0.00229***</td></tr><tr><td>(0.00618)</td><td char=".">(0.00105)</td><td char=".">(0.00049)</td></tr><tr><td>Cultural motivations to enrol</td><td>−0.02447**</td><td char=".">−0.00427**</td><td char=".">−0.00198**</td></tr><tr><td>(0.00978)</td><td char=".">(0.00171)</td><td char=".">(0.00080)</td></tr><tr><td>Professional motivations to enrol</td><td>−0.01121**</td><td char=".">−0.00196**</td><td char=".">−0.00091**</td></tr><tr><td>(0.00477)</td><td char=".">(0.00083)</td><td char=".">(0.00039)</td></tr><tr><td>Past work experience</td><td>0.05943***</td><td char=".">0.01036***</td><td char=".">0.00482***</td></tr><tr><td>(0.00349)</td><td char=".">(0.00064)</td><td char=".">(0.00032)</td></tr><tr><td>Current work experience</td><td>0.04723***</td><td char=".">0.00824***</td><td char=".">0.00383***</td></tr><tr><td>(0.00417)</td><td char=".">(0.00075)</td><td char=".">(0.00037)</td></tr><tr><td>Trust in others</td><td>0.02176***</td><td char=".">0.00379***</td><td char=".">0.00176***</td></tr><tr><td>(0.00319)</td><td char=".">(0.00056)</td><td char=".">(0.00026)</td></tr><tr><td>Father entrepreneur</td><td>0.03706***</td><td char=".">0.00646***</td><td char=".">0.00300***</td></tr><tr><td>(0.00511)</td><td char=".">(0.00090)</td><td char=".">(0.00043)</td></tr><tr><td>Mother entrepreneur</td><td>0.02476***</td><td char=".">0.00432***</td><td char=".">0.00201***</td></tr><tr><td>(0.00691)</td><td char=".">(0.00121)</td><td char=".">(0.00056)</td></tr><tr><td>Father educational attainment</td><td>0.00740***</td><td char=".">0.00129***</td><td char=".">0.00060***</td></tr><tr><td>(0.00212)</td><td char=".">(0.00037)</td><td char=".">(0.00017)</td></tr><tr><td>Mother educational attainment</td><td /><td /><td /></tr><tr><td>Degree level 1 (3 + 2 years default = BA, 3 years)</td><td /><td /><td /></tr><tr><td>Degree level 2 (5 years default = BA, 3 years)</td><td>0.00796*</td><td char=".">0.00140*</td><td char=".">0.00065*</td></tr><tr><td>(0.00427)</td><td char=".">(0.00076)</td><td char=".">(0.00036)</td></tr><tr><td>Job security important</td><td>−0.04462***</td><td char=".">−0.00778***</td><td char=".">−0.00362***</td></tr><tr><td>(0.00647)</td><td char=".">(0.00114)</td><td char=".">(0.00053)</td></tr><tr><td>Autonomy important</td><td>0.08948***</td><td char=".">0.01561***</td><td char=".">0.00725***</td></tr><tr><td>(0.00539)</td><td char=".">(0.00097)</td><td char=".">(0.00048)</td></tr></tbody></table> </ephtml> </p> <p>***= sig. 1%; **= sig. 5%; *= sig. 10%, Robust standard errors.</p> <ref id="AN0139429872-13"> <title> Notes </title> <blist> <bibl id="bib1" idref="ref9" type="bt">1</bibl> <bibtext> The waves of technological, organizational and financial innovations that started 40 years or so ago with the ICT revolution brought about an acceleration in the pace of economic and social change that has implied a compression of the knowledge life cycle. Analysis of technological revolutions and of the diffusion pattern of the major technological breakthroughs seems to show that the typical technology life cycle has shrunk; i.e. the process of 'creative destruction' (Schumpeter [80]) has become more intense, thus leading to also shrink the life cycle of industries and firms (Bloom et al.[11]; Nordhaus [67]).</bibtext> </blist> <blist> <bibl id="bib2" idref="ref10" type="bt">2</bibl> <bibtext> Schivardi and Torrini ([76]) show that the propensity of Italian firms to hire graduates is three times greater for entrepreneurs with a university diploma than for other entrepreneurs. Bugamelli et al. ([13]) argue that the adoption by firms of more efficient organizational settings and human resources strategies (e.g. decentralized organizational settings, incentive-based wage schemes, etc.) is positively affected by entrepreneurs' education.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref20" type="bt">3</bibl> <bibtext> The total entrepreneurial activity index computed by GEM is given by the percentage of the working age population starting an entrepreneurial activity and those running a new business which is less than 3 and a half years old.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref23" type="bt">4</bibl> <bibtext> A share, which varies greatly according to the field of study, with a minimum of 0.3% for medicine and a maximum of 4.4% for agricultural studies. Indeed, the comparatively low general educational attainment of entrepreneurs in Italy has much to do with the low level of educational attainment of the Italian population as a whole: in 2015, the share of the population with at most compulsory education was 51% against a share of 13% with a university degree (ISTAT [45]). The long recession may have affected the relative value of occupational options (e.g. being an employee rather than a self-employed worker) in particular in Italy, which has suffered from high unemployment rates (in 2015, 12.1% for the 15–64 age bracket), especially among young people (18–29, 29.6%) even if they hold a university diploma (25–34, 16.2%). Indeed, although the outside option of becoming an entrepreneur has been negatively affected by the recession, entrepreneurial opportunities have also been negatively affected by the bad macroeconomic climate.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref24" type="bt">5</bibl> <bibtext> AlmaLaurea is an inter-university consortium set up in Italy in 1994. Today, it involves 73 universities and approximately 91% of Italian graduates. The Consortium is supported by the universities taking part in it, by the Italian Ministry of Education, University and Research and by all companies and institutions using the databank and the services offered by AlmaLaurea. AlmaLaurea engages in three core activities<emph>: Graduates' profile</emph>: an annual survey and report on the internal efficiency of the higher education system; <emph>Graduates' employment conditions</emph>: an annual survey and report on the external efficiency of the higher education system; <emph>Online graduates' databank</emph>: a tool intended to improve the match between the supply and demand of graduates and their transnational mobility. The members of the AlmaLaurea consortium numbered 64 at the time of the survey (2014) and 72 in 2015 (see the Appendix for the list of universities included in the sample).</bibtext> </blist> <blist> <bibl id="bib6" idref="ref33" type="bt">6</bibl> <bibtext> The empirical evidence on the effects of cognitive and non-cognitive abilities on an individual's life is impressive. In particular, a remarkably long list of characteristics and socio-economic outcomes of an individual are correlated with the standard measurement tests of cognitive abilities (Kuncel, Hezzlet, and Ones [54]; Schmidt [77]). Such abilities include analytical style, memory, reaction time, reading, creativity (craftwork, musical ability), health and fitness, interests (breadth and depth of interest, sports participation), morality? (delinquency, lie scores, racial prejudice, values), occupational status and income, perceptual (ability to perceive brief stimuli, field-independence, myopia), personality (achievement motivation, altruism, dogmatism) and practical skills (practical knowledge, social skills). Indeed, they are all characteristics that may be expected to affect the intrinsic and extrinsic reward of different occupational choices and, therefore, the incentive to make them. Psychology and neuroscience furnish strong evidence that most cognitive and non-cognitive skills are acquired up to a person's twenties, an age bracket below which the prefrontal cortex is still malleable (Cunha and Heckman [18]).</bibtext> </blist> <blist> <bibl id="bib7" idref="ref66" type="bt">7</bibl> <bibtext> For instance, an enforced entry regulation can reduce entry and income risk and thus create rents for incumbents in some occupations (thereby increasing returns to education); conversely, entry regulations that are not enforced owing to bribery may simply affect the type of entrepreneurial selection, with zero or even positive effects on entry (Klapper, Laeven, and Rajan [52]).</bibtext> </blist> <blist> <bibl id="bib8" idref="ref2" type="bt">8</bibl> <bibtext> 'Entrepreneurship researchers largely ignore the concept of self-efficacy despite its importance and proven robustness at predicting both general and specific behaviours. For instance, role models affect entrepreneurial intentions only if they affect self-efficacy. In addition, self-efficacy has been associated with opportunity recognition and risk-taking' (Krueger, Reilly, and Carsrud [53], 418).</bibtext> </blist> <blist> <bibl id="bib9" idref="ref88" type="bt">9</bibl> <bibtext> Students will be followed after graduation through a survey on their occupational status (1, 3 and 5 years after graduation).</bibtext> </blist> <blist> <bibtext> We verified that there were no observable differences among graduates at different times of the year which might affect our estimation results.</bibtext> </blist> <blist> <bibtext> However, we were not interested in assessing the process and the causes of discontinuation.</bibtext> </blist> <blist> <bibtext> The population size was 64,710, and the response rate was 94%. The survey includes administrative data, available for the population at large, and the responses to the questionnaire.</bibtext> </blist> <blist> <bibtext> We were less interested in the group of students who had started a business before enrolling at university because it was reasonable to expect that their choices were independent of their subsequent academic experience unless we made the strong assumption that their decision to start the business was linked to their decision to enrol at university in the future.</bibtext> </blist> <blist> <bibtext> We selected just one of the sentences contained in the survey providing proxies to detect entrepreneurial intentions because of the very high correlation among them (82–84%).</bibtext> </blist> <blist> <bibtext> See also column (e).</bibtext> </blist> <blist> <bibtext> Unfortunately, the questions on whether students had attended courses on entrepreneurship or if they had received stimuli from the university were put only to those students who had started a business or who had taken concrete actions to do so. 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  Label: Title
  Group: Ti
  Data: The Entrepreneurial Engagement of Italian University Students: Some Insights from a Population-Based Survey
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ferrante%2C+Francesco%22">Ferrante, Francesco</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-4154-6451">0000-0002-4154-6451</externalLink>)<br /><searchLink fieldCode="AR" term="%22Federici%2C+Daniela%22">Federici, Daniela</searchLink><br /><searchLink fieldCode="AR" term="%22Parisi%2C+Valentino%22">Parisi, Valentino</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Studies+in+Higher+Education%22"><i>Studies in Higher Education</i></searchLink>. 2019 44(11):1813-1836.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 24
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2019
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Descriptive
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Entrepreneurship%22">Entrepreneurship</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22College+Graduates%22">College Graduates</searchLink><br /><searchLink fieldCode="DE" term="%22Employment+Potential%22">Employment Potential</searchLink><br /><searchLink fieldCode="DE" term="%22Role%22">Role</searchLink><br /><searchLink fieldCode="DE" term="%22Alumni%22">Alumni</searchLink><br /><searchLink fieldCode="DE" term="%22Universities%22">Universities</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+Analysis%22">Comparative Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Innovation%22">Innovation</searchLink><br /><searchLink fieldCode="DE" term="%22Human+Capital%22">Human Capital</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Personal+Autonomy%22">Personal Autonomy</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+Mobility%22">Occupational Mobility</searchLink><br /><searchLink fieldCode="DE" term="%22Career+Choice%22">Career Choice</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Italy%22">Italy</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/03075079.2018.1458223
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0307-5079
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Start-ups founded by university students and graduates play a substantial role in bringing new knowledge to the market and in employment creation, a role that appears to be even more important than that played by the typical technology transfer activities carried out by universities. We use a population-based approach to explore entrepreneurship among 61,115 graduate alumni of 64 Italian universities. In order to assess the potential supply of highly educated entrepreneurs, we develop a novel empirical approach to analyse engagement in entrepreneurship, based on the idea that entrepreneurship is a process that begins with intention and ends in action. We find that the share of intentional entrepreneurs, among recent cohorts of graduates in Italy, is large in comparison to the small share of actual entrepreneurs detected five years after graduation. We discuss which barriers may deter intentional entrepreneurs from being engaged in entrepreneurship and how universities can trigger the entrepreneurial process and close the gap between entrepreneurial intentions and action.
– Name: AbstractInfo
  Label: Abstractor
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  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2019
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1233243
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/03075079.2018.1458223
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 1813
    Subjects:
      – SubjectFull: Entrepreneurship
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: College Graduates
        Type: general
      – SubjectFull: Employment Potential
        Type: general
      – SubjectFull: Role
        Type: general
      – SubjectFull: Alumni
        Type: general
      – SubjectFull: Universities
        Type: general
      – SubjectFull: Intention
        Type: general
      – SubjectFull: Comparative Analysis
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Innovation
        Type: general
      – SubjectFull: Human Capital
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Personal Autonomy
        Type: general
      – SubjectFull: Occupational Mobility
        Type: general
      – SubjectFull: Career Choice
        Type: general
      – SubjectFull: Italy
        Type: general
    Titles:
      – TitleFull: The Entrepreneurial Engagement of Italian University Students: Some Insights from a Population-Based Survey
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ferrante, Francesco
      – PersonEntity:
          Name:
            NameFull: Federici, Daniela
      – PersonEntity:
          Name:
            NameFull: Parisi, Valentino
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 0307-5079
          Numbering:
            – Type: volume
              Value: 44
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Studies in Higher Education
              Type: main
ResultId 1