Young Entrepreneurs in Hungary Kornélia Lazányi, PhD habil Young Entrepreneurs in Hungary Kornélia Lazányi, PhD habil. Óbuda University, Keleti Faculty of Business and Management

The importance of entrepreneurship   Number (%) People employed (%) Value added (%) EU Hungary Micro 92.2 94.8 29.6 36.5 21.2 18.2 Small 6.5 4.4 20.6 19.3 18.5 15.9 Medium 1.1 0.7 17.2 16.9 18.4 19.5 Big 0.2 0.1 32.6 27.1 41.9 46.2

1. Research on entrepreneurial competencies PEC test (McClelland, 1987) 70 statements - 13 factors (five point Likert scale) first quartile of 2014 - two separate samples students from tertiary education (Óbuda University, Széchényi István University and Szent István University), N=470 successful entrepreneurs, N=35 average age: 22.69 (Std. Dev.: 3.279); 37.00 (Std. Dev.: 8.228). average work experience in months 9.496 (Std. Dev.:13.411); 194.686 (Std. Dev.: 99.184)

Research questions Do entrepreneurs perform better, than students; and if yes, in which personal entrepreneurial competencies? Does the gender, age or the work experience significantly influence the levels of distinct competencies?

Significant differences within the entrepreneurs’ sample Age Gender Level of education Duration of longest job Persistence 0.355* (0.037) Information seeking   0.352* (0.038) 0.337* (0.048) Concern for high quality work 0.362* (0.032) 0.574** (0.000) Self-confidence 0.378* (0.025) Assertiveness 0.394* (0.019)

Significant differences within the students’ sample Age Gender Work experiene Taking initiative 0.097*(0.036) 0.119**(0.010) Sees and acts on opportunities   0.124**(0.007) Information seeking 0.103*(0.026) Concern for high quality work 0.098*(0.034) Commitment to the work contract 0.146**(0.002) Systematic planning 0.117*(0.011) Problem Solving 0.114*(0.013) Self-confidence 0.106*(0.021) Persuasion 0.111*(0.016) Use of influence strategies 0.105*(0.023)

Summary - conclusions Entrepreneurs performed way better in entrepreneurial competencies than students did. There are significant differences even within the group of entrepreneurs. With age, and work experience, students hopefully mature to a level, where they can become the successful entrepreneurs of the future.

2. Research on entrepreneurship Demographic variables (age, gender) and Neptun code (unique student identification code) Hungarian adopted version of the SEM (Self-Employment Model - Entrepreneur Aptitude Quiz) rate 25 statements, with the help of a 5-point Likert Scale 180 full- and part time bachelor students of Óbuda University's Kelety Faculty of Business and Management Each of them attended the elective course of "Establishing a business venture" in 2012 or 2013 Establishing a business venture – students supposedly pick the cours because they are interested Elméletileg azért veszi fel, mer érdekli

Participants of the research 179 questionnaires were applicable for further analysis Representative on the population taking the elective course „Establishing a business venture” Not representative (<30%) of the total population 68 male and 111 female students average age 22.9106 (Std.: 2.216) female (22.32); male (23.87) 60.5% part time students The research can be regarded representative, since almost all students, who attended the Establishing a business venture course filled out the questionnaire, however not each KGK student did attend the selected course, accordingly the research is not representative regarding the whole population of BSc level KGK students (representation ratio 30%) Not each and every student is as good in entrepreneurial skills as it is shown in our research, but those attending the course are well represented Reprezentatív, mert mert 99%-os a kitöltöttség, de nem reprezentatív, mert az össz KGK hallgatóknak csak 30%-a töltötte ki. Tehát nem állítható, hogy minden KGK hallgató ilyen jó, de a vállalkozás iránt érdeklődök ilyenek. STD= Standart deviation, azaz szórás.

Hypothesises H0: Those signing up for the course of "Establishing a business venture" have an interest in, if not an explicit intention of starting their own business. H1: Older respondents do not score higher than younger respondents on the entrepreneurial aptitude test. H2: There is a structural difference between the younger and older respondents' entrepreneurial aptitudes. H3: Male respondents do not score higher than female respondents on the entrepreneurial aptitude test. H4: There is a structural difference between the male and female respondents' entrepreneurial aptitudes.

average score 77.073 (Std.: 9.450) out of 100 Although the choice the students make by electing the Establishing a business venture course is based on their interest if not intent in starting their own business, as it can be seen on this graph as well, almost half of the students did not have the sufficient level of skills (that should be above 75 point according to relevant international literature). This means either they do not have relevant sense of selfworth and are not aware of their lack of skills, or they did not select the course Establishing a business venture because they really did have interest in the topic or intention of starting a business venture. Either the first, or the second argument is true, both hold information if we consider those aplying for Msc at KGK. We want to have those, who are really interested in becoming an entrepreneur and have the necessarry skills to do so as well, so we want to be able to fail the 50% percent of student lacking either skills or motivation Bár elméletileg azért veszi fel a vállalkozásalapítás kurzust, mert érdekli és esetleg vállalkozó lenne, gyakorlatilag, mint az az ábrán is látszik, közel fele nem lenne sikeres vállalkozó, mert nincs meg hozzá a megfelelő kompetenciája. A megfelelő a szakirodalom, illetve az eredeti angol kérdőív kidolgozói szerint 75 pont felett van. Tehát vagy nincs releváns önismeretük (sense of selfworth), vagy nem azért vették fel a kurzust, mert tényleg vállalkozók akarnak lenni (intention to become entrepreneur). Márpedig mindkettő infó, ha ugyanezt az MSC jelentkezésre fordítjuk le – a célunk a jó képességű, tényleg vállalkozni kívánó emberek kiválasztása, tehát az, hogy azt az 50%-ot, aki nem veszi komolyan, vagy nem képes rá, azt már eleve kiejtsük. average score 77.073 (Std.: 9.450) out of 100 male average (78.706); female average (76.072)

Results H1: Older respondents do not score higher than younger respondents on the entrepreneurial aptitude test. - VERIFIED H3: Male respondents do not score higher than female respondents on the entrepreneurial aptitude test. – VERIFIED Statistical tools applied (SPSS): bivariate correlations, independent samples’ F test, t-test for equality of means, Verified – the corresponding statistical data support the statement there being no significant/relevant difference between younger/older or male/female students SPSS_ No significant correlation between the gender or age and enterpreneurial aptitude. That means that both H1 and H3 were verified. Bivariate correlations: no signifigant correlation on total score, but if we divide the enterpreniureal aptitude on the basis of the statements, we will see structurale differenties. It was actually the H2 and H4. Verified – azaz a vonatkozó statisztikai vizsgálatok megerősítették, hogy tényleg nincs szignifikáns/releváns különbség a fiatalok/idősek, nők/férfiak vállalkozói készség átlagpontjai közt

Difference of means (Equal variances assumed) Cut point at age 21 22 23 I do not like to be told what to do. -1.210** -0.663** -1.513** I don’t get tired easily when I am interested in a project. 0.670** 0.631** 1.576** I am flexible. 0.479** 0.323* 1.079** Others have called me stubborn. 0.680* 0.629** I am determined. 0.336* 0.574** I would like to set my own hours and working conditions -0.814** -0.572* I prefer my own way of doing things. -0.438** -0.488* I will take a chance when I think an idea has promise. 0.568** Once I set a goal, I see it through. 0.339* I enjoy continually learning new things. -0.352* I often trust my instincts. -0.473** I am self-confident. 0.732* I view mistakes as learning opportunities. -0.763** According to H2 There is a structural difference between the younger and older respondents' entrepreneurial aptitudes. - correlation tests verified the hypothesis, however the notion being young/old posed a bit of a difficulty when analysing the data. Depending on where we placed the cutpoint in between age groups different skills came up with significant differences in the t-test. The table shows all correlations with medium or high signficance and not all the 25 skills measured in the questionnaire The table displays the difference between average values (that should be considerd high or low compared to them being scaled on a 5 point likert scale - 1 point means 20% difference Negative values mean that the average of older students’ has been lower than that of younger students’, while positive values state that in the given skill older students have been better than youngers For excample: with the cutpoint at age 21, the value -1,210 means, thet the students older than 21 scored 1,2 points (25%) lower in average than the students older than 21 It can be seen that the first 3 skills had significantly different averages independent from the cutpoint (so the relation between age and the skills in the first 3 rows can be regarded transitive, meaning the older the better/worse in the given skill), however there have been various other skills that were only visible (or significant) with specific age cutpoints. In general, research data suggest that older students have a more thorough knowledge of the world of work, on the other hand younger students tend to rebel more A kettes hipotézis szerint strukturális eltérés van az idősebb és fiatalabb válaszadók közt – a korrelációs elemzések ezt némely kérdés/skill esetében igazolták is, a kérdés csak az volt, hogy az hogy ki az idősebb/fiatalabb. A csillagokat azok kapták, ahol van statisztikai összefüggés, de ez nem mind a 25 kérdésre igaz . Attól függően, hogy hány éves kor alatt/fölött tekintettük a hallgatókat fiatalnak/idősnek, eltérő kérdések adtak szignifikánsan releváns eredményt a t próbán. A táblázat a csoportátlagok eltérését mutatja, és az értékek az 5-ös Likert-skálás értékekre vonatkoznak. Tehát az 1 pontnyi eltérés pl 20%-os eltérés. A negatív azt jelenti, hogy az idősebbek értéke kevesebb volt, mint a fiataloké, a pozitív meg azt, h az idősebbek átlagértéke volt a magasabb az adott értékkel. Pl: Ha 21-nél néztem meg a kérdéseket, akkor a -1,210 azt jelenti, hogy a 21-nél idősebbek alacsonyabb átlagpontot értek el 1,2-vel, mint a fiatalabbak. Látszik, hogy az első három kérdés, az minden esetben ott volt, bárhol húztunk is korhatárt, - az első három sor olyan kérdéseket takar, amiből tranzitív relációt mutat, ami azt jelenti, hogy minél öregebbek, annál jobbak/rosszabbak az adott képességben - és voltak persze olyanok is, amik csak bizonyos korhatárokkal jelentek meg (alsóbb sorok) Összességében az idősebbek jobban tudják, mit jelent a munka világa, a fiatalabbak inkább lázadnak. Significant correlations are flagged by * and highly significant ones with**.

Difference of means (Equal variances assumed) I view problems as obstacles to overcome. 0.660** I prefer thinking out of the box and being innovative. 0.611** I don’t get tired easily when I am interested in a project. 0.521** I will take a chance when I think an idea has promise. 0.512** I am self-confident. 0.435* I would like to set my own hours and working conditions 0.432* I am a risk-taker. 0.373* I am inventive. 0.370* I would like to have control over my earning and growth potential. 0.296* I view mistakes as learning opportunities. -0.324* I work well by myself. -0.715* According to H4 there is a structural difference between the male and female respondents' entrepreneurial aptitudes - correlation tests verified the hypothesis. The relation was also tested with a t-test - the table shows all correlations with medium or high signficance The table here also displays the difference between average values (that should be considerd high or low compared to them being scaled on a 5 point likert scale - 1 point means 20% difference Negative values mean that the average of female students’ has been lower than that of male students’, while positive values state that in the given skill, females have been better than males According to the data female students have been better in numerous skills (first 9 lines) however there were skills (last 2 lines) were males were better off A négyes hipotézis szerint strukturális eltérés van a férfiak és a nők közt – a korrelációs elemzések ezt némely kérdés/skill esetében igazolták is. Csináltam rá t-próbát is. A táblázat a szignfikáns eredményeket jelöli A táblázat itt is a csoportátlagok eltérését mutatja, és az értékek az 5-ös Likert-skálás értékekre vonatkoznak. Tehát az 1 pontnyi eltérés pl 20%-os eltérés. A negatív azt jelenti, hogy a nők értéke kevesebb volt, mint a férfiaké, a pozitív meg azt, h a nők átlagértéke volt a magasabb az adott értékkel. Látszik, hogy sok mindenben a nők szignifikánsan jobbak (első 9 skill), de van amiben a férfiak (utolsó 2 sor) Significant correlations are flagged by * and highly significant ones with**.

Summary Not everyone, who intends to start a business has the necessary level of skills (55% are over the 75% limit), accordingly strict selection is necessary. Neither older students, nor male students are better than younger or female students respectively. There is a structural difference within the skill set based on their gender and age. So, that can be a basis for differentiation in their masters level education. Since male and female students as well as younger and older ones are lacking in different skills, they neccessitate different education. This differentiation could be a basis of a new structure of elective courses in the MSc programme. Tehát akár különböző tárgyakat is lehetne kínálni, más típusú fejlesztést igényelnek a nők mint a férfiak, illetve az öregebbek, mint a fiatalabbak. Erre kellene alapozni az elective course kínálatot.

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