Keywords

Entrepreneurship, Education, Students, University, Family.

Introduction

Lebanon has a reputation for having a dynamic entrepreneurial landscape and a solid base of SMEs contributing to its open economy (Stel & Naudé, 2012). Indeed, throughout the past two-to-three decades, Lebanon has developed its ecosystem for entrepreneurs and SMEs, starting by strengthening the enabling environment, moving to subsidized loans lead by the Banque du Liban, to the establishment of financial companies with a public concern that assists Small and Medium-sized Enterprises (SMEs) to access commercial bank funding such as Kafalat and IDAL (Saleh, 2014). In addition to the recent emergence of private sector support and Lebanese Central Bank’s new initiative, allowing banks to invest in startups, accelerators, and incubators, there has been a variety of initiatives supporting the early stage entrepreneurs (Schellen, 2018; Hendieh, 2016).

The factors that initiate the spirit of entrepreneurship and the degree to which this spirit exists or can be simulated, lie within individual members of societies. The key question in this paper is, what triggers the release of this invaluable enterprising spirit? This paper seeks to make a small contribution towards an explanation by focusing on university students. It is argued that there is a significant relationship between entrepreneurship and cultural specificity (Deakins & Freel, 2009; Schoof, 2006).

Literature Review

University students’ beliefs are expected to influence attitudes and behaviors and thus serve as a channel for a certain outcome (Ajzen, 1991). The desirability of a university student to indulge into an entrepreneurial activity can not in itself create a propensity to act unless it is accentuated with the perception of feasibility (Shapero, 1982). Both desirability and feasibility will integrate to drive a potential and an intention towards a new venture creation (Ahmed et al., 2012).

In examining how desirability is established, Shapero (1982) sheds light on the role of the family, peer groups, educational and professional contexts of potential entrepreneurs. He states that the mother or the father can play an influential role in bringing about an entrepreneurial spirit in the family. Collins et al. (1964) have suggested also in their empirical research that the family circumstances have an effect on the development of the venture idea for the entrepreneur. Mathews and Moser (1996) in their turn and through their empirical research were able to associate the family background with the entrepreneurial idea formulation. Kolvereid (1996) have carefully examined the role of the family background and have determined a positive relationship, however, the result was not statistically significant. In their exploratory analysis and investigations of university student’s beliefs and attitudes towards the entrepreneurial activity Veciana and Urbano (2005) have also hinted that the presence of entrepreneurs in the family or among relatives could foster the intention to create a new venture. On family background also, Scott and Twomey (1988) have stated that the preference of students to self-employment is higher among those whose parents own a small business.

According to the theory of planned behavior (Ajzen, 1991) the resources and opportunities that an individual can avail himself of, would affect his behavior and exuberate his intentions and actions towards entrepreneurship. In this context Shapero (1982) emphasized the factor of financial support and other supports also like consulting and training that if available would lift off the entrepreneurial potential and renders it more feasible to embark on a new venture. In addition, and according to Veciana (1999) the excessive regulation and lack of governmental support would hinder also the entrepreneurial process and new venture creation.

The entrepreneurial research has extensively examined also among other factors the relationship between gender and the entrepreneurial actions. With the steady increase in the number of female entrepreneurs, an increasing body of research has investigated the role of gender differences in entrepreneurial intentions (Haus et al., 2013). Although more women than ever are now choosing entrepreneurship as a career (Jalbert, 2000), numerous studies still demonstrate a higher entrepreneurial intention among men than among women (Gupta et al., 2009). Delmar and Davidsson (2000) and Mathews and Moser (1996) have established in their research on gender influence that males have a higher preference for entrepreneurial activity than females. This higher preference for self-employment by males was also tested by Kolvereid (1996) who concluded that male’s attitudes and intentions towards self-employment are significantly higher than females. Among the literature treating this relationship was also that of (Kourilsky & Walstad, 1998; Mesch & Czamanski, 1997; Kolvereid, 1996; Lerner & Hendeles, 1996; Mathews & Moser, 1996; Crant, 1996; De Wit & Van Winden, 1989) who have found that males have stronger tendency and preferences towards self-employment than women.

The relationship between innovativeness and entrepreneurial activity has been broadly explored in different studies in the entrepreneurship literature. According to Thomas and Mueller (2000), the impetus to do something new is a major trait of the entrepreneur. Sweo (2003) likewise consider innovativeness as inherent in the entrepreneurial spirit. The search for new opportunities & new products and implementing own business idea, serve as well to drive individuals to impart motion towards entrepreneurial activity (Cromie, 2000).

As any business activity triggers a certain degree of risk, the factor of risk & its impact upon the intentions and behavior of potential entrepreneurs was also analyzed in the literature (Sánchez & Sahuquillo, 2012). The Major difference between an entrepreneur and an employed worker or a manager is that in the latter case the propensity to take risk is much lower than in the former. Sexton and Bowman (1985) found that entrepreneurs show much more tolerance for ambiguity than managers. The income stability factor and the family responsibility to earn constant amount of money propel individuals to avoid risk. The entrepreneur is not averse to taking risk; on the contrary he assumes financial risk as the stream of earnings is less secure as an entrepreneur than as an employee. He also misses career opportunities & undergoes family and emotional pressures (Erdem, 2001).

The effect of the educational background on entrepreneurial intentions and behavior has been under scrutiny by many research studies. To what degree the educational background impacts the intention of university students to start their own venture was debated by Ferrante and Sabatini (2007); they casted a strong light on the connection between educational background and the ability to perform and build intentional behavior. They construed that educational attainment should reveal the cognitive abilities possessed by individuals. Richardson (1993) in his research also showed that there is a strong link in the wiring between some academic majors like communication, human ecology and science in general and the growth and development of personal , social and quantitative skills of students. Ewert and Baker (2001) have stated also that the acquirement of different knowledge from different academic fields will facilitate the way towards entrepreneurship. In support of the impact of education on stimulating entrepreneurship, the Global Entrepreneurship Monitor (Kelley et al., 2011) through its efforts to 1enhance the understanding of the entrepreneurship phenomenon have pointed that individuals with limited education are less likely to embark into entrepreneurial initiatives. However, Garavan and O’Cinneide (1994) protracted further and indicated that entrepreneurship education and training play a major role in people’s inclination to start-up a business in the future.

The issue of dissatisfaction with present or previous job and the desire to earn more money and become richer was also the subject of research by many scholars. Hofstede et al. (2004) commented that individuals often expect material and non-material benefit from entrepreneurial activity. According to Huisman and De Ridder (1984), the findings inferred from a large sample of entrepreneurs in eleven different countries have spotted light and cited several inducements spurring individuals to become entrepreneurs. Among these motives are frustration with previous salaried jobs, unemployment and personal crisis. Van Uxem and Bais (1996) annotated that 50% of almost 2000 new entrepreneurs in Denmark considered that dissatisfaction with their previous jobs was among the motives to start their own business. Zgheib and Kowatly (2011) studied the expatriate Lebanese entrepreneurs and found that, they are perseverant, innovative, risk taking individuals who compete aggressively in the marketplace and are driven by a need for autonomy.

Among the critical factors that influence entrepreneurship is the availability of resources. It is construed that capital is considered as an indispensable element to start a business. The availability of capital facilitates the entrepreneurial process as it allows the entrepreneur to secure among others, the raw materials, a proper infrastructure and the provision of utilities. The literature has dealt extensively and broadly with this factor. The availability of capital has been positively related to new venture creation, to business growth and to the broadening of strategic options (Romanelli, 1987). According to Kristiansen and Indarti (2004) the availability of capital is considered as one of the common obstacles that hinder a potential entrepreneur to establish a new business. The access to finance is an important entry barrier for self-employment as investors show reluctance to invest in small and new firms due to the lack of track record, the high risk and the fixed cost elements of transactions (Cressy, 2006; Berger & Udell, 1998).

Objective

The objective of the article is to explore and analyze the factors that influence the behaviors and attitudes of university students toward entrepreneurship. Such attitudes and behaviors stem from internal and informal factors as well as environmental factors in a country (Ewert & Baker 2001; Veciana, 1999).

The notion of entrepreneurial potential among university students and their intent to start a new business was and still is an interesting subject for researchers, who continuously find a need to try to better comprehend the student’s entrepreneurial intentions and the factors affecting them. The main purpose of this article is to investigate both the factors and beliefs that would thrust university students to become entrepreneurs and the factors and beliefs that would curb them from delving into this new venture creation. The successful identification of these factors enhances university administration’s ability to introduce additional measures to augment students’ desirability and interest in an entrepreneurial business.

Methodology

Research Framework

A questionnaire was used to explore students’ entrepreneurial motivation after graduation. A sample of undergraduate and MBA students at the Arab Open University (AOU) Lebanon branch was chosen for this purpose. The primary assumption in this study centers on the notion that “university students constitute a significant portion of the pool of potential entrepreneurs in both developed and developing countries…” (Thomas & Mueller, 1998).

Questionnaire Design, Measurement and Sample Size

Building on several prior researches in the field of entrepreneurship, the survey questionnaire was formulated. We used as a basis for our questions the International Labour Organisation questionnaire (Maul, 2007), and other research questions related to students’ entrepreneurial attitudes from Harris and Gibson (2008), Venesaar et al. (2006), Veciana & Urbano (2005), Ramayah and Harun (2005), Robertson and Wilkinson (2005).

The survey was conducted personally by the authors during the month of May 2018, following a pre-testing round on 30 senior students and 4 lecturers in entrepreneurship. Changes were made to several questions, making them easier to understand. Following the approval of the University administration, the authors took 15 minutes from every tutorial to distribute the questionnaire and explain the questions one by one to students, in order to make sure that all questions are clearly understood and completed.

The questionnaire was subdivided into 3 parts, comprising 14 questions/items in total: (a) 6 questions covering the demographic/personal details; (b) 4 questions about training in entrepreneurship, motivation to start new business after graduation, potential barriers to the development of entrepreneurial activities, among others; and (c) 4 questions about family expectations after completion of degree and current education system, to name a few. In total we were able to collect 430 questionnaires, out of which 390 were actually used (about 90.7% response rate). A number of students were absent (e.g. work, sickness), and thus did not complete the survey.

The Dependent Variable (DV) “entrepreneurial motivation” was measured by the question “what is your plan after finishing your degree at AOU?” the students were instructed to choose between two alternatives: option 1 (to get a salaried job) or option 2 (to start your own venture). Since the DV is dichotomous, we measured it using nominal scale. We gave the DV the value of 1 if the respondent chose option 2 (to start your own venture), and the value of 0 if the respondent selected option 1 (to get a salaried job). The predictor (independent variable) “Age” was measured at the scale level. The following predictors were measured at the nominal level: “Gender” (1=male, 0=female); “Education” (1=undergraduate, 0=postgraduate); “FamExpecta”, “family expectations from you after completion of your degree”, (1=to get salaried job, 0=to start your own business); “TrainingImp”, “is training in entrepreneurship important to become an entrepreneur?”, (1=training is important, 0=training is not important). Finally, we measured the remaining two predictors “FamilSup”, “friends and relatives support”, and “GovSup2”, “government policies/support”, using ordinal level of measurement. The corresponding responses were collected on a 5-point Likert-type scale from not important to more important. To analyze the data, we used SPSS. The sample size in this research was 390 students, 53.1% of which were female and 46.9% were male. Table 1 depicts some information about the respondents.

Table 1: Information About Respondents
		Frequency	Percent (%)
Gender	Male	183	46.9
	Female	207	53.1
Education	Undergraduate	329	84.4
	Postgraduate	61	15.6
Job	Did not have/or had a job	87	22.3
	Have or had a job	303	77.7

The mean age for the respondents is 23.39 years for the males and 23.07 for the females. As for the educational backgrounds, 83.61% of men are pursuing an undergraduate degree and 16.39% a postgraduate degree; as for the females, 85.02% are pursuing an undergraduate degree and 14.98% a graduate degree. 84.15% of the men have a job while 15.85% are unemployed, while 71.98% of the women are employed and 28.08% don’t have a job. Concerning the working students, 48.7% of male have a managerial position and 51.3% a non-managerial position, as for the females 34.9% have a managerial position and 65.1% a non-managerial position. From the 207 female respondents 35.27% consider gender discrimination as an obstacle for females to own a new business while 64.73% do not. Both men and women consider that the training in entrepreneurship is essential to an individual to become an entrepreneur, 77.7% of man and 88.7% of women. Finally 69.40% of the male respondents’ families own a business and 30.6% don’t, while 58.94% of the female respondents’ families own a business and 30.6% don’t. 69.7% of the respondents think about starting their own business and 95.6 % of them think that they will encounter high risks in their entrepreneurial activities. The main motives to start their own business are: to earn more money (90.64%), to do something new (87.77%), self-realization (86.33%), to implement their own business ideas (60.94%), to be their own boss (89.20%) and to exploit a potential opportunity in the market (92.08%).

Results

Since the dependent variable is dichotomous (0 or 1) (Table 2), we use a binary logistic regression. The outcome in SPSS for binary logistic regression presents the results in two steps or blocks. It starts with results for the model with no predictors (independent variables) included. We will often refer to this model as the baseline model. All the predictors are then entered in step 2 or Block 1. The model in Block 1 will be referred to as the full model.

Table 2: Dependent Variable Encoding
Original Value	Internal Value
Get Salaried Job	0
Start your own Venture	1

The Omnibus Tests of Model Coefficients (Table 3) reveals highly significant results (Chi²=101.888, df=7, p=0.000). The model Chi-square (101.888, p<0.05), which is the difference between -2 Log likelihood (-2LL) in Block 0 (524.127) and -2LL in Block 1 (422.240), shows a reduction of -2LL for Block 1 (Tables 4 and 5). This implies that the full model (with the predictors) has an improved fit compared to the baseline model. Nagelkerke R2 (0.311) revealed that the full model describes approximately 31% of the variation in the dependent variable (Table 6).

Table 3: Omnibus Tests Of Model Coefficients
		Chi-square	df	Sig.
Step 1	Step	101.888	7	0
	Block	101.888	7	0
	Model	101.888	7	0

Table 4: Block 0: Iteration Historya,B,C
Iteration		-2 Log likelihood	Coefficients
			Constant
Step 0	1	524.131	-0.41
	2	524.127	-0.416
	3	524.127	-0.416
a: Constant is included in the model.
b: Initial -2 Log Likelihood: 524.127.
c: Estimation terminated at iteration number d. because parameter estimates changed by less than 0.001.

Table 5: Block 1: Iteration Historya,B,C,D
Iteration		-2 Log likelihood	Coefficients
			Constant	Age	Gender	Education	TrainingImp	FamilSup	GovSup2	FamExpecta
Step 1	1	424.914	-0.903	0.047	0.408	0.088	0.209	0.196	-0.125	-1.81
	2	422.261	-1.325	0.059	0.552	0.103	0.302	0.277	-0.178	-2.044
	3	422.24	-1.367	0.06	0.567	0.104	0.314	0.287	-0.185	-2.064
	4	422.24	-1.367	0.06	0.567	0.104	0.314	0.287	-0.185	-2.064
a: Method: Enter.
b: Constant is included in the model.
c: Initial -2 Log Likelihood: 524.127.
d: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001.

Table 6: Model Summary
Step 1	-2 Log likelihood	Cox & Snell R2	Nagelkerke R2
	422.240a	0.23	0.311
a: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001.

The Hosmer and Lemeshow Test, an alternate to model Chi-square, also indicated that the full model has produced an improved fit as p=0.161 (p>0.05). Here, a non-significant result greater than 0.05 implies an improved prediction (Table 7). The Classification Table shows that our model is now correctly predicting the outcome at 74.4%, a rather significant improvement from 60.3% in Block 0 (Tables 8 A and Table B).

Table 7: Hosmer And Lemeshow Test
Step 1	Chi-square	df	Sig.
	11.792	8	0.161

Table 8A: Block 1: Classification Tablea
Observed			Predicted
			1:GSJ or 2:SOwnVent		Percentage Correct (%)
			Get Salaried Job	Start your own Venture
Step 1	1:GSJ or 2:SOwnVent	Get Salaried Job	197	38	83.8
		Start your own Venture	62	93	60
	Overall Percentage				74.4
a: The cut value is 0.500.

Table 8B: Block 0: Classification Tablea,B
Observed			Predicted
			1:GSJ or 2:SOwnVent		Percentage Correct (%)
			Get Salaried Job	Start your own Venture
Step 0	1:GSJ or 2:SOwnVent	Get Salaried Job	235	0	100
		Start your own Venture	155	0	0
	Overall Percentage				60.3
a: Constant is included in the model.
b: The cut value is 0.500.

The Variables in the Equation Block 1 table allows for the detection of the significant effects, or lack thereof, of each predictor on the dependent variable (Table 9). Four predictors-Age, Gender, FamilSup, and FamExpecta–are significant at p<0.05. The estimated coefficients (β) in a binary logistic regression permit for declarations pertaining to the significance as well as corresponding sign of an effect. The coefficient (β) of Age (Wald=4.482, p=0.034) is positive and statistically significant (p=0.034), implying that this predictor has a positive effect on the dependent variable. Odds ratio value (Exp(B)) for Age is 1.062 (>1.000)–noting that if Exp(B) is greater than 1.000, as is the case here, indicating that when the predictor is raised by one unit the odds of the dependent variable occurring is increased. Next, Gender is also positive and statistically significant (Wald=5.606, B=0.567, p=0.018), with Exp(B)=1.763 (>1.000). Similarly, FamSup is positive and statistically significant (Wald=6.238, B=0.287, p=0.013), with Exp(B)=1.064 (>1.000). However, the FamExpecta’s effect is negative (B=-2.064), yet it is statistically significant (Wald=67.531, p=0.000), with Exp(B)=0.127 (<1.000). This implies that when the predictor FamExpecta is raised by one unit the odds of the dependent variable occurring decreases. The Wald criterion allows for the classification of the (significant) by order of importance; the greater this value, the more significant the variable. Hence, FamExpecta (Wald=67.531) is the largest single determinant of the outcome (dependent) variable.

Table 9: Variables In The Equation (Block 1)
		B	S.E.	Wald	df	Sig.	Exp(B)	95% CI. for EXP(B)
								Lower	Upper
Step 1a	Age	0.06	0.028	4.482	1	0.034	1.062	1.004	1.123
	Gender	0.567	0.239	5.606	1	0.018	1.763	1.103	2.818
	Education	0.104	0.387	0.073	1	0.788	1.110	0.520	2.367
	TrainingImp	0.314	0.396	0.627	1	0.428	1.369	0.63	2.976
	FamilSup	0.287	0.115	6.238	1	0.013	1.332	1.064	1.669
	GovSup2	-0.185	0.123	2.242	1	0.134	0.831	0.653	1.059
	FamExpecta	-2.064	0.251	67.531	1	0.000	0.127	0.078	0.208
	Constant	-1.367	1.055	1.679	1	0.195	0.255
a: Variable(s) entered on step 1: Age, Gender, Education, TrainingImp, FamilSup, GovSup2, FamExpecta.

Finally, the data shows that education, training and government support have a statistically non-significant effects at p>0.05 (p=0.788, 0.428 and 0.134 respectively).

Discussion

An enormous number of research studies have investigated the effect of gender, family background and ethnicity on entrepreneurship propensity of university students attending or not attending an entrepreneur program (Camacho-Miñano & Del Campo, 2017; Kusmintarti et al., 2017; Bizri et al., 2014; Venesaar et al., 2006; Veciana & Urbano, 2005; Ramayah & Harun, 2005; Robertson & Wilkinson, 2005; Wang & Wong, 2004). The question of whether entrepreneurs “are born or made” was the central interest of few research papers (Henderson & Robertson, 2000). In this article we studied the effect of family, gender, university and personality traits on the entrepreneurship propensity of the Arab Open University in Lebanon.

Would the age, gender or educational program/track have impact on entrepreneurship tendency? If a student is currently employed or have an entrepreneur in his close circle, would it affect his career prospect? Will the current status of the Lebanese economy have an effect on the perception of students about entrepreneurship?

In this exploratory study, the results obtained are encouraging. Concerning the significance of the results, it seems that the family expectation is the main factor that will affect the careers of students, but surprisingly the family expectation has a negative relationship with the entrepreneurial motivation; one explanation may be to avoid the pressure witch contradicts the existing literature (Saleh, 2014; Aziz et al., 2012; Fahed-Sreih & Pistrui, 2012) . Our tests show that the age, gender and family support will also have a significant positive influence which supports the findings of (Jaggi, 2015; Fatoki, 2014; Zgheib, 2006) and contradicts the finding of Hussain et al. (2018). While surprisingly, the education, the training and the government support don’t seem to have a significant effect (Ojiaku et al., 2018; Demiral, 2016; Ahmad & Xavier, 2012; Sánchez & Sahuquillo, 2012; Stel, 2012).

Interesting results emerge from our tests, and we have learned four lessons. The first is that, as in previous research, the family support will affect the strategic choices (Saleh, 2014). Second students still perceive that there is gender discrimination (Syam et al., 2018). Third older male students will be more interested than females in starting their own business (Israr & Saleem, 2018). Fourth, despite the efforts spent by the government to encourage entrepreneurship, this support has no significant relation with students’ motivation. The government should provide better support and find new means in order to encourage the entrepreneurs who are considered as the backbone for the Lebanese economy (Hejase et al., 2014; Fahed-Sreih & Pistrui, 2012; Mezher et al., 2008).

Conclusion and Limitation

The purpose of this research was to survey student attitudes toward the entrepreneurial behavior and the importance of university education to their future entrepreneurial career. Our results proved that the university students who answered the questionnaire survey are interested in starting their own venture. This research suggests that 35% of the female respondents felt that gender discrimination is an obstacle for starting their own businesses. The results indicate that surprisingly the motivation is not significantly related to the university entrepreneurial education, trainings or government support, although 77.7% and 88.7% of the students considered that respectively education and trainings in entrepreneurship are essential (Bagheri et al., 2013), but these two factors lose their significance when tested with other factors. In general, age, gender, family support and family expectation were significantly related to their perceptions about entrepreneurship. Older, male students that are supported by their families have strong positive attitudes toward starting their own business. However, when their families’ expectations are high their motivation will decrease and vice versa.

In conclusion, the results indicate that the students’ motivations towards entrepreneurial activities are high; 69.7% of the students have a firm intention or are seriously thinking about starting their own business noting that 95.6 % of them think that they will encounter high risks in their entrepreneurial activities. When asked to discuss the reason behind such motivation, 90.64% said that they would like to earn more money, followed by: to do something new (87.77%), self-realization (86.33%), to implement their own business ideas (60.94%), to be their own boss (89.20%) and to exploit a potential opportunity in the market (92.08%).

There are several limitations in the study. The greatest challenge we see is in the data collection process since we only collected data from one university in Lebanon and we limited our sample to graduate students who will enter the labor market within one year. As we have four faculties, the educational background of the sample was also limited. Unfortunately, the existing political intervention and corruption in all sectors and industries in Lebanon can reduce the effect of the selected factors on the entrepreneurship tendency. The number of respondent in our sample was reduced from 430 to 390 during the coding. Finally, the findings are valid within the context/characteristics of the sample and the study region, i.e. the Arab Open University, Lebanon Branch; consequently, we cannot extrapolate the findings to other universities.

Recommendations

Important implications for universities and public policy makers arise from this study. First, our model can be used to predict the Lebanese universities students’ entrepreneurial intentions. Second, the educational background wouldn’t impact the entrepreneurial intentions as long as the students have entrepreneurial intentions. Third, the education system should focus and pay a specific attention to entrepreneurial skills and it should motivate and inspire students’ interest in entrepreneurship (Syam et al., 2018). Fourth and most important, the government should increase the efforts spent and search for other appealing means to better support the entrepreneurs and to motivate the citizens into taking an entrepreneurial venture (Fahed-Sreih & Pistrui, 2012).

Our study could be used as basis for future research as:

1. An empirical study using a larger number of variables. The number of variables in the literature is quite important. Moreover, empirical studies using other factors or combinations of factors rather than those we used are recommended (Behavioral intention, the social aspects...).

2. In-depth case studies/qualitative studies are another important angle for future research.

3. Repeat the same study but using a larger sample of universities.

4. Empirical or qualitative studies using the same factors in other universities in other countries.

5. Empirical and qualitative studies using the same factors, in high schools.

6. Finally, the same limitation found by Wu and Wu in 2008, there is no standardization of educational background in previous literature, it is important to redefine/standardize the variables that compose the educational background.

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