Towards nurturing the entrepreneurial intentions of neglected female business students of Pakistan through proactive personality, self-efficacy and university support factors

2.1 Entrepreneurship in Pakistan

Entrepreneurship had been an essential topic for research since 200 years (Bull and Willard, 1993). As Wennekers and Thurik (1999) stated that entrepreneurship has expanded its attention globally in the past decade. However, in many countries the need for entrepreneurship, its driving forces and economic support remained inactive. The entrepreneurship is the procedure of creating new venture, and entrepreneurial intention takes an important part in this process (Saeed et al., 2015).

In the developing countries, there is need of entrepreneurship as the unemployment level is higher (Rana, 2011). It is a way to overcome the unemployment in the country. Pakistan suffers from unemployment and the numbers of unemployed graduates’ increases as there are more unemployed educated people as compared to uneducated (Iftikhar, 2016). The overall unemployment rate of Pakistan after the global financial crisis is 5.90 per cent. Moreover, according to The World Bank (2013)’s report, young female unemployment rate in Pakistan was 11.90. Global Entrepreneurship Monitor (GEM) (2010) Report also highlighted the significance of entrepreneurship and found that Pakistan has the lower rate of entrepreneurial activities as compared to other countries. On the other hand, one of the key components for creating awareness about entrepreneurship is to provide entrepreneurship education to students, definitely through the business schools (GEM, 2012).

In this context of Pakistan where there is patriarchal society, and thus, there is fewer number of female entrepreneur, Azam Roomi and Harrison (2010) conclude that in the context of Pakistan, barriers perceived by the women entrepreneurs can be lessened by providing women-only training and education programs that allow them in developing skills and capabilities. For improving the quality of women’ life, female entrepreneurship has been assumed as a substantial factor (Anwar and Rashid, 2012). Moreover, from the feminist point of management sciences, the female entrepreneurship particularly of business students is too important particularly for the suppressed women of developing countries.

Prior literature shows that fewer research studies have been carried out specifically on the female students regarding entrepreneurship. Some problems faced by the female in becoming an entrepreneur include the financing difficulty in getting financial resources for starting a new business in Pakistan (Tanveer et al., 2013). Afza et al. (2010) stated that in Pakistan the socio-economic growth is adverse because of its uncertain environmental condition that has also affected women entrepreneur in Pakistan. Batool and Ullah (2017) stated that the constraints faced by females in Pakistan are lack of family support, finances, insufficient education. Education plays an important role in entrepreneurial activities but not only education is necessary, but the support from the university is also important for nurturing the business. Mehtap et al. (2017) also argued that providing practical education on entrepreneurship and necessary skills to the female students help them in their future entrepreneurial activities.

2.2 Entrepreneurial intention and its predictors

In prior studies, researchers defied entrepreneurial intention in broader as well as in narrow terms. Given the scholarly importance of entrepreneurial intentions, many researchers have discussed deeply on factors which influences an individual's entrepreneurial intentions and try to understand it by using a wide range of theoretical approaches (Peng et al., 2013). As Sesen (2013) stated that for entrepreneurial intentions, in majority of studies three basic approaches are followed: Shapero’s model of the entrepreneurial event (SEE); Ajzen’s theory of planned behavior (TPB); and Luthje and Franke’s model (LFM).

The first approach is entrepreneurial event model (SEE), given by Shapero (1982), states that entrepreneurial intention depends on perceived desirability, propensity to act and perceived feasibility (Shapero, 1982). Second, Ajzen (1991) gave the Theory of Planned Behavior. The model of theory contains planned behavior which is the outcome of intention supported by subjective norms as well as environment and perceived behavior control (Ajzen, 1991). This shows that the perceptions that the behaviors are personally controllable (Krueger et al., 2000).

Finally, Luthje and Franke model include both personality trait and contextual factors in examining the attitude regarding entrepreneurial intentions. This model is the relevant and prime focus of this study. It provides a sound framework to access the antecedent of entrepreneurial intention (Mustafa et al., 2016). LFM model is used by the various scholar to examine the demographic, personal and entrepreneurial antecedent of Entrepreneurial intention (Kristiansen and Indarti, 2004; Sesen, 2013; Schwarz et al., 2009 and Mustafa et al., 2016). In emerging and developed economies, LFM model has proven to be a strong predictor of entrepreneurial intention.

3.1 Perceived university support and entrepreneurial intentions

Carsrud et al. (1986) underlined the need to study the environmental impact on the individual in becoming entrepreneurs. A university environment plays an important role in student's entrepreneurial intentions. Similarly, Lüthje and Franke (2004) illustrated that the students’ perception of their university environment affects entrepreneurial intentions; and it significantly affects entrepreneurial intentions. Mustafa et al. (2016) also illustrated that a supportive university environment could differ in its composition and quality of support services offered to the students. Nowadays, there is a growing interest in entrepreneurship and new firm startup, but a few number of research studies have been carried out that finds entrepreneurial education and support factors together (Walter et al., 2006).

Entrepreneurial education programs influence an individual’s entrepreneurial intention as Kolvereid and Moen (1997) found that entrepreneurial education programs positively influenced Entrepreneurial intention of students. Many universities across the world still are working on converting the ideas of students into the practical concept (Saeed et al., 2015). Nasiru et al. (2015) also illustrated the importance of perceived university for entrepreneurial intentions. Kraaijenbrink et al. (2010) suggested that it is crucial to measure the extent to which university support influences students. Similarly, Saeed et al. (2015) also illustrated that student's perception of the university support could be measured by the support that they receive. In spite of such issues, this study focuses on the three types of support that universities can offer female students to nurture their interest in entrepreneurship as a career, that is, perceived educational support (PES), perceived concept development support (PCDS) and perceived business development support (PBDS). The relations of these types with the entrepreneurial intentions are explained as follows.

3.2 Perceived educational support

Perceived educational support refers to as a student’s perception about the education support provided by the university. Lüthje and Franke (2004) also recognized that a student’s perception of his/her university environment could significantly impact their Entrepreneurial intention. According to Henderson and Robertson (2000), entrepreneurial education and entrepreneurial support that is provided by the universities are actual ways of getting knowledge about entrepreneurship and influences the students to pursue the career as an entrepreneur (Souitaris et al., 2007). The students are provided with the necessary knowledge, skill, internship which help them in enhancing their entrepreneurial intention (Saeed et al., 2015). Díaz-Casero et al. (2017) investigate the relationship between university support and entrepreneurial intention and found that in environmental factors, university support has a substantial impact on the entrepreneurial intentions. Therefore, by above discussion, the following hypothesis is proposed:

3.3 Perceived concept development support

Perceived concept development support refers to as a students’ perception about the support provided by the university in term of “motivation, awareness, and business ideas in the early stages of the entrepreneurial process” (Saeed et al., 2015). The provision of support provided by the universities to the students regarding the business ideas development, the knowledge required for new business startup and introducing with entrepreneurial role models (Mustafa et al.. 2016). This type of support motivates female students to pursue their career in the field of entrepreneurship through pushing their ideas into reality. Many universities across the world are now focusing on the making and converting student’s ideas into the concept. Recent findings by Mustafa et al. (2016) and Saeed et al. (2015) showed that student's perception of concept development support positively influences entrepreneurial intention of students. Hence by above discussion the following hypothesis is elicited.

3.4 Perceived business development support

Perceived business development support refers to as a students’ perception about university support in term of developing their enterprise once they have graduated (Mustafa et al., 2016). It is the support by the university in startup venture of the students by providing the financial resources. Díaz-Casero et al. (2017) investigated the link between university support and entrepreneurial intention and found that in environmental factors, university support has a significant impact on entrepreneurial intentions. Hence, based on the above reasoning the following hypothesis is proposed:

3.5 Entrepreneurial self efficacy

Self-efficacy refers to as an individual's self-assurance and capability to achieve a certain behavior (Karimi et al., 2011). Entrepreneurial Self-efficacy is used to highlight career choice intentions. Self-efficacy plays a significant role and similarly, in many other studies entrepreneurial self-efficacy is assumed as an important factor which has a significant impact on entrepreneurial intentions (Zhao et al., 2005; Krueger and Carsrud, 2000). Peng et al. (2013) illustrated that entrepreneurial self-efficacy has a considerable impact on entrepreneurial intention. There is the optimistic connection between entrepreneurial self-efficacy and entrepreneurial intention among college women (Austin and Nauta, 2016).

3.6 Mediating role of entrepreneurial self-efficacy between proactive personality and entrepreneurial intentions

Brandstätter (2011) illustrated that proactive personality and self-efficacy helps in predicting entrepreneurial intentions. Prabhu et al. (2012) concluded that individual with proactive personality and entrepreneurial self-efficacy predicts the environmental situation and are more confident in taking the initiative to start their own business. Moreover, this study found that entrepreneurial self-efficacy partially mediates the relationship between proactive personality and entrepreneurial intention. Similarly, Zhao et al. (2015) also investigated the mediating role of entrepreneurial self-efficacy in nurturing the entrepreneurial intention of students in becoming entrepreneurs. Wang et al. (2016) examined the mediating effect between the personality trait and entrepreneurial intention and recommended using proactive personality and entrepreneurial self-efficacy for mediation. Zhao et al. (2005) also recommend for studying the mediation role of self-efficacy between proactive personality and entrepreneurial intention. Zhao et al. (2005) examined the mediating role of entrepreneurial intention in becoming entrepreneurs and results find that entrepreneurial self-efficacy plays a mediating role in many personality traits and entrepreneurial intention. Thus, the proposed hypothesis is:

4.1 Sample and data collection

The unit of analysis in the present study is the female business student enrolled in the last years of study in business schools of universities of Islamabad, the capital of Pakistan. Business students were taken for the study because of the reason that they are assumed to pursue their career as entrepreneurs in the future. The data was collected through personal physical survey questionnaires.

The sample size was determined by using Krejcie and Morgan (1970) formula, which yield the sample size of 306 female students from the total population of 1,485 students. The questionnaire was personally administrated for data collection. The process of questionnaire distribution and collection was carried out for three months. A total of 306 questionnaires were received and used for the analysis.

Of the 306 sample size, 211 were from the female students from public sector universities (69 per cent) and 95 were from private sector universities (31 per cent). The average age of the respondent was 23.5 years. As the data was collected through personal physical survey questionnaires, therefore, there was no involvement of late respondents. Consequently, no additional analysis concerning the late respondents was needed.

4.2 Measurement scales/instruments

A questionnaire using a five-point Likert scale was used to collect the data for each construct of the research model. Proactive personality trait was measured by using the adopted scale of Bateman and Crant (1993) with 12 items. Perceived university support was measured by adopting the scale of Saeed et al. (2015) which contains 13 items (the number of items for perceived educational support is six; four number of items have been used for perceived concept development support; and three number of item for business development support). Entrepreneurial self-efficacy was measured by using four items adopted from Zhao et al. (2005). The final construct is an entrepreneurial intention which was measured by six items adopted from Liñan and Chen (2009).

To assess the common method variance bias, the Harman factor’s approach was used. It was found that common method variance bias does not exist as the value of the technique was less than 50 per cent.

4.3 Data analysis

To analyze the data, PLS-SEM was used in SmartPLS 3 Version 2.6 (Ringle et al., 2015, 2018). Hair et al. (2014) stated that PLS replace the stepwise regression with multiple regressions, and it allows the user to run the entire model with some advanced techniques for validity and mediation. But more specifically, the choice of the PLS-SEM over the CB-SEM was by the lower sample size and exploratory nature power issue.

5.1 Measurement model evaluation

A part of the measurement model, the study following the guiding articles (Ringle et al., 2015, 2018; Wong, 2013) assesses the four components: outer loadings, indicator reliability, construct reliability, convergent validity and discriminant validity. Latent variable’s reliability was accessed through outer loadings, indicator reliability and composite reliability (Fornell and Larker, 1981; Hair et al., 2014). The outer loading of indicators should be 0.7 or higher (Hair et al., 2014; Wong, 2013). So all those items were included in the model which had the value equals to 0.7 or above.

Similarly, the acceptable value for indicator reliability is 0.4 or higher (Hulland, 1999). As Table I shows the values of indicator reliability, which were greater than the threshold level of 0.4. For estimating internal consistency reliability, composite reliability of threshold value 0.7 or higher is preferable (Wong, 2013). The composite reliability for all the variables ranged between 0.83 and 0.89 indicates that the reliability of constructs is good enough.

For measuring the convergent validity, Average Variance Extracted (AVE) was used. All constructs demonstrated good convergent validity as the values of AVE for each construct ranges from 0.51 to 0.66 that is larger than the threshold value of 0.50 (Fornell and Larcker, 1981). Discriminant validity was evaluated using the Fornell–Larcker criterion and for that Wong (2013) suggested that the square root of average variance extracted from each latent variable should be greater than the correlations among the latent variables. Similarly, Hair et al. (2014) also suggested that off-diagonal values in latent variable correlation should be less than the diagonal ones. As shown in Table II Ismail, the square root of AVE appears in the diagonal cells and correlations appear below it, and the diagonal values (in bold) are higher than off-diagonal values.

5.2 Research structural model for hypotheses testing

The study adhering to the instructions of Ringle et al. (2018) maintains that the PLS-SEM does not require assessing the goodness-of-fit measures like that of CB-SEM. It places the minimal requirement on these statistics and normality of data. Therefore, to test the fit of the model R² has been used. The value of regression is 0.479 (Figure 1) that is quite adequate. Figure 1 and Table III present the results. The value of R² was 0.479 which means that 47.9 per cent of the variance in entrepreneurial intention can be explained by other variables (Figure 2).

The results revealed that all other direct hypotheses for the entrepreneurial intention of female business students (PP (β = 0.460, p < 0.01), PES (β = 0.135, p < 0.05), PCDS (β = 0.145, p < 0.01), ESE (β = 0.191, p < 0.01) have been accepted. However, H4 on PBDS to entrepreneurial intention is significant, but negative predictor (β= -0.154, p < 0.01). Thus, H4 is not supported and accepted.

5.3 Mediation analysis

The mediation analysis of the research model was carried out through the method defined by Hair et al. (2014) by using SmartPLS. The first step was to evaluate the significance of direct path relation (PP to EI) by checking significance (t- statistics significance in bootstrap). If it is significant, then check the significance of indirect effect (ESE to EI). If this relationship is also significant, then the mediation exists. The results indicated that both the direct and indirect effects are significant because both the values of t-statistics (7.837 and 2.705) are greater than the threshold value 1.96. Hence, the mediation exists, and entrepreneurial self-efficacy mediates the relationship between proactive personality and entrepreneurial intention. The strength of mediation was found out through variance accounted for (VAF) (Hair et al., 2014). Variance accounted for (VAF) is calculated through the following formula

Total effect = indirect effect + direct effect;

Indirect effect: PP → ESE = 11.36, ESE → EI = 2.705;

Direct effect: PP → EI = 7.837;

VAF > 80 per cent = full mediation;

VAF 20 − 80 per cent = partial mediation; and

VAF < 20 per cent = no mediation.

The value of VAF for the mediation of entrepreneurial self-efficacy equals to 80 per cent that explains that entrepreneurial self-efficacy partially mediates the relationship between proactive personality and EI.

7.1 Theoretical contribution

The study makes following contributions to the literature. First, by collecting data from Pakistan, the study explores the feminist point of view of developing countries like Pakistan in management literature. Second, this study also adds our understanding about the drivers/factors of entrepreneurial intentions of female students especially in the context of emerging economy. Third, to the best of authors' knowledge, this is the first study that tested the university support factors and individual personality factors (proactive personality and entrepreneurial self-efficacy) as predictors of the intention of the business students empirically. Fourth, the study tests the mediating role of entrepreneurial self-efficacy between proactive personality and entrepreneurial intention of the female students. Finally, this study affirms that Luthje and Franke model works as a relatively useful tool for measuring entrepreneurial intentions and furthers it for the entrepreneurial self-efficacy and proactive personality, while given that this model has been used for the relationship of individual personality factors.

7.2 Practical implications

From the findings of the study, the implications for academic institutions and public policy arise. Academic institutions should regularly assess the type of support that they provide to female students. The study findings show entrepreneurial education and concept development support are perceived to be good in enhancing entrepreneurial intentions of female students but lacking in their business development support role. Thus Pakistani academic institutions can pay attention in reinforcing their traditional teaching roles.

About designing entrepreneurship programs and courses, the policymakers and academic institutions can shift their focus from theoretical concept to the practical concepts. The attitudes and skills can be developed by the business simulation experiences. As in developed countries, the liaison between academia and industry is high. Therefore, the students can get the experience. However, in Pakistan, less effort has been put so the universities should focus for greater liaison. The most of the business schools here in Pakistan focus too much on the publications in JCR journals, while ignoring professional and entrepreneurial development. Moreover, academic institutions should craft the entrepreneurial ecosystem into the universities. Also, it is suggested that universities teachers should receive training on how the teach and how to change “the heart and mind” of the students for inspiring them in the process of entrepreneurship. Finally, to raise proactive personality of female students, the academic institutions should provide training and skill to them.