The Journal of Asian Finance, Economics and Business

Korea Distribution Science Association (한국유통과학회)
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Influence of Financial Literacy and Educational Skills on Entrepreneurial Intent: Empirical Evidence from Young Entrepreneurs of Pakistan

  • BILAL, Muhammad Ahmed (Balochistan University of Information Technology Engineering & Management Sciences) ;
  • KHAN, Hadi Hassan (Department of Management Sciences, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • IRFAN, Muhammad (Department of Management Sciences, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • Ul HAQ, S.M. Nabeel (Department of Economics, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • ALI, Manzoor (Department of Management Sciences, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • KAKAR, Ali (Department of Economics, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • AHMED, Wahab (Department of Management Sciences, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences) ;
  • RAUF, Abdul (Department of Management Sciences, Faculty of Management Sciences, Balochistan University of Information Technology Engineering & Management Sciences)
  • Received : 2020.10.01
  • Accepted : 2020.12.14
  • Published : 2021.01.30
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Abstract

This paper attempts to study the impact of Financial Literacy on Youth Entrepreneurial Intent in Pakistan. A closed-ended self-administered structured questionnaire covering financial literacy, computer knowledge, financial attitude, and financial knowledge with Entrepreneurial Intent was collected from young entrepreneurs. The research tried to investigate the education level with computer skill to inspect the effect of financial literateness on young generation Entrepreneurial Intent in the context of Pakistan. The research model was tested using PLS-SEM and authenticating a measurement model through the advanced methodology and their association with Entrepreneurial Intent. Results revealed that financial literacy and its two parts (financial attitude and financial knowledge) have a positive impact on Entrepreneurial Intent. The size of the joint impact of financial literacy and its components on Entrepreneurial Intent was assessed to be adequate. Entrepreneurial Intent is essential for creating new firms to maintain economic development. Furthermore, it is determined in this research that if youth has better financial knowledge and financial attitude, the probability of Entrepreneurial Intent increases. This suggests that if the youth in Pakistan desire to attain a higher limit of Entrepreneurial Intent, they must implement financial literacy models for enhancing and promoting their current Entrepreneurial Intent.

Keywords

1. Introduction

Akanbi (2016) stated that in recent years, entrepreneurship has gained much attention from academicians, economists, policymakers, investors, and governments. An individual’s pre-business stages are from the age group of 15-19 years with very limited experience, skills, and maturity level (Hongdiyanto et al., 2020). The potential entrepreneurs are people in the middle 20s with some experience, knowledge, and wealth. Khuong and An (2016) discussed that entrepreneurship activities and startups can be found in every corner of the world now. The business world has highly developed, and this has been considered as one of the major driving forces of the global economy.

Rugimbana and Oseifuah (2010) clarified that entrepreneurs are involved in the process of resource utilization, decision making, and other activities on daily basis, regardless of what age group they fall in. Entrepreneurs must be financially sound and literate, to function properly and effectively. Research studies show that poor financial knowledge and improper management limits their activities. Therefore, the entrepreneurial process needs them to be capable to fill the gaps and deficiencies in the market. According to Garba et al. (2014), entrepreneurship is just not a field in education but a necessity for the development of an economy. Existing meanings of entrepreneurship or descriptions of entrepreneurship study emphasize development (Gartner, 1988; Shane & Venkataraman, 2000).

Heuer and Liñán (2013) discussed that explaining an individual’s behavior is a very difficult task, and the importance of one’s cognition has also been recognized. It also helps to deliver an insight into the subject of entrepreneurship as well as provides a ground to prove positive results and strengthens a country’s economy. Ahmad and Seymour (2008) in their paper, stated that in modern times, policymakers are more interested to facilitate and encourage the growth of new enterprises and boost the economy through the growth of entrepreneurship because it is regarded as a driving force. Since business creation is not just about generating money and creating employment opportunities rather, it is about value creation, which eventually creates a good image of the company as well as about the country. Furthermore, they revealed that different countries focus on entrepreneurship according to their requirements. Some use it for creating employment opportunities in the country, especially when its youths are jobless, while others use it for solving environmental problems occurring in the country, making contributions to social inclusion.

Entrepreneurial activities in any form or any investment to the economy, motivate its people to come up and play their part in economic development. Remeikiene et al. (2013) aimed at the establishment of the impact of entrepreneurial education promoting entrepreneurship among young people. The results of the research confirmed that the main factors of entrepreneurial intention are personality traits (self-efficacy, risk-taking, need for achievement, proactiveness, attitude towards entrepreneurship, behavioral control, and internal locus of control), and they can be developed during the study process (Braunstein & Welch, 2002; Perry et al., 2008). Krueger et al. (2000) came up with a thought-provoking point in their paper that Intent always feels interesting to those who always are in search of new venture formations. Entrepreneurship is a way of thinking, a way of thinking that emphasizes opportunities over threats. The opportunity identification process is intentional, and, therefore, entrepreneurial intentions clearly merit our attention. Equally important, they offer a means to better explain and predict entrepreneurship. They may respond to the conditions around us, such as an intriguing market niche, by starting a new venture 

According to Hilgert et al. (2003), most professionals come to an agreement that self-beneficial financial performance seems directly associated with financial knowledge. For instance, Lusardi and Mitchell (2011) studied financial learning among the young generation of the United States of America and concluded that less than 33% of youth have a simple understanding of different financial terms. It is, thus, necessary to know whether financial understanding (one of the parts of financial literacy) has any link with Entrepreneurial Intent among youth. The motivation behind this study to study the impact of financial literacy on youth Entrepreneurial Intent in Pakistan. The core purpose of this research was to inspect the effect of financial literateness and its components on young generation Entrepreneurial Intent in the context of Pakistan

2. Literature Review

The theory of planned behavior is the general guidelines that explain the procedures of starting a new firm whereby it views behavioral aim as a direct cause of planned behavior (Ajzen, 1991; Ajzen & Fishbein, 1977). It relates mainly when the behavior is infrequent, difficult to detect, or includes changeable time intervals. According to Krueger Jr et al. (2000), Intentions are the single best predictor of any planned behavior, including entrepreneurship. Understanding the antecedents of intentions increases our understanding of the intended behavior. However, research addressing causes for students’ Entrepreneurial Intention is very limited (Lüthje & Franke, 2003; Hoda et al., 2020; Wang & Wong, 2004). Douglas and Fitzsimmons (2005) stated that an individual’s intention to behave entrepreneurially will have attitudinal and self-efficacy antecedents. Nascent entrepreneurs also have the choice to behave entrepreneurially in their own new business or to behave entrepreneurially in an existing business. When faced with choices, intentions are driven by attitudes towards elements of the outcomes associated with the choice items. They confirmed that an individual’s attitudes to autonomy, ownership, and risk defined the Entrepreneurship Intent.

Akanbi (2016) further elaborated that Entrepreneurship is not just about finding and filling gaps in the market, rather it is a process of discovering the true entrepreneurial potential, evaluating the risks, and taking chances in creating future products. This discovery starts with the identification and recognition of the opportunities, where individuals translate Entrepreneurial Intentions into the creation of new enterprises. Entrepreneurship has become a need of time not only for survival but also for sustainability in such dynamic age as it brings competitiveness in economic activities globally and creates employment opportunities (Ismail et al., 2015; Polin et al., 2016).

Remund (2010) explained financial literacy as “Financial literacy is the level to which one knows important business and financial terms and has the capability and sureness to accomplish personal capitals over suitable, short- range decision-making and thorough, long-term financial scheduling, although aware of life actions and varying economic circumstances.” Financial Literacy is not just convenience or knowledge that everyone has, but an indispensable survival tool that individuals must have to survive in today‘s modern society (Jacob et al., 2000; Nguyen & Nguyen, 2020). According to Messy and Monticone (2016) regardless of its significance, several types of research in the world draw attention to the issue that financial illiteracy is still affecting a major part of the world’s people, thus this problem should be solved as a priority basis. Persons with more financial literacy, tend to make rare errors in financial choices and thus are in good financial positions (Meier & Sprenger, 2013).

Gerardi et al. (2010) investigated whether a particular aspect of borrowers’ financial literacy -their numerical ability - may have played a role. They measured several aspects of financial literacy and cognitive ability in a survey of subprime mortgage borrowers who took out mortgages in 2006 or 2007 and match these measures to objective data on mortgage characteristics and repayment performance. They found a large and statistically significant negative correlation between numerical ability and various measures of delinquency and default. Foreclosure starts are approximately two-thirds lower in the group with the highest measured level of numerical ability compared with the group with the lowest measured level. The result is robust to controlling for a broad set of sociodemographic variables and not driven by other aspects of cognitive ability or the characteristics of the mortgage contracts. Their results raised the possibility that limitations in certain aspects of financial literacy played an important role in the subprime mortgage crisis. Financial literacy has two parts as recommended by Huston (2010): Knowledge, that is the person’s familiarity and understanding of finance or financial learning, and its usage, i.e. the use of such information and knowledge in one’s financial management.

Von Gaudecker (2015) examined how financial literacy and advice of experts affect the decisions of households regarding portfolio diversification. Findings showed after running OLS regression that the households get better investment outcomes who uptake advice from experts than those who believe in their own decision making. Lusardi and Mitchell (2011) argued that while it is valuable to measure the financial literacy of individuals, in reality, it is difficult to discern the method of how people use financial knowledge and take judgments established on this information. The reason is that financial literacy covers several ideas, which include financial know-how and information, financial abilities, and financial competency, and it is difficult to get all this data in a realistic span of the period to research.

Another significant outcome is that students who take their under graduation level studies at colleges offering entrepreneurship training (in specific districts) probably grow a positive approach towards following an entrepreneurial profession (Walter & Dohse, 2009). Schooling and knowledge play an important role in detecting entrepreneurial chances (Davidsson & Honig, 2003; Shane & Venkataraman, 2000; Ucbasaran et al., 2008) and in magnificently taking advantage of them (Gimeno et al., 1997; Lofstrom et al., 2014; Robinson & Sexton, 1994).

As shown by the quick development in the number of entrepreneurship courses and programs at universities (Katz, 2007; Klandt, 2004; Vesper & Gartner, 1997), many strategy creators appear to share the trust that universities transfer vital entrepreneurial knowledge and thus investments in training and education deals may eventually result in further (fruitful) entrepreneurship. Researchers have intensively discussed whether entrepreneurship can be officially imparted and educated (Aronsson, 2004; Gendron, 2004; Gorman et al., 1997). Numerous analysts adopt that university education can handover at least some entrepreneurial knowledge (Henry et al., 2005).

2.1. Theoretical Framework and Hypotheses Development

2.1.1. Relationship of Computer Literacy and Entrepreneurial Intent

In recent decades, the research field of entrepreneurship phenomenon has significantly increased in both quantity and sophistication. Bui et al. (2020) evaluated the factors that affect the entrepreneurial intention of IT students in Vietnam. Results highlighted five independent variables affecting the dependent variable, the entrepreneurial intention, in descending order as following: entrepreneurial educational environment, personal characteristics, perception of feasibility, entrepreneurial supports, and financial accessibility. Besides, this research has proved that the variable attitudes towards entrepreneurship partially mediated among the interrelationship of the aforementioned variables. The use of information knowledge has a positive effect on financial development (Kopnina & Meijers. 2014; Yoon et al., 2018). Though less care has been given to the effect of ICT use on entrepreneurship, numerous studies have indirectly explored the ICT use by entrepreneurs and the relationship between public ICT plans and entrepreneurship (Hashim et al., 2011; Kemal, 2019; Ndubisi & Kahraman, 2005). The increasing need for automation is due to globalization. The more computer literate can help in searching new business ideas which will help in making his/her aim towards new startups. This contention can be affirmed by the structure of the paper of Rugimbana and Oseifuah (2010) which revealed that financial literacy among youth entrepreneurs appears to be above average and contributes meaningfully to their entrepreneurship skills. Education and training with an emphasis on financial literacy and entrepreneurial skills can have significant implications for the development and growth of youth entrepreneurs

2.1.2. Relationship of Financial Attitude and Entrepreneurial Intent

Veciana et al. (2005) concluded that there is a general agreement that attitudes towards the entrepreneur, entrepreneurial activity, and its social functions are determinant factors for university students to decide an entrepreneurial career. Their empirical study aimed at evaluating and comparing the attitudes of university students toward entrepreneurship and enterprise formation in Catalonia and Puerto Rico. Results revealed a positive entrepreneur’s image. The samples had a favorable perception of the desirability of new venture creation. So, based on these findings of the research, the third hypothesis has been proposed.

2.1.3. Relationship of Financial Knowledge and Entrepreneurial Intent

In a fast-moving environment, entities require to frequently detect new chances outside of current capabilities for their survival and success (Doz et al., 1989; McGrath et al., 1996). The findings of opportunities has been acknowledged as one of the most significant capabilities of prosperous entrepreneurs (Ardichvili et al., 2003) and therefore has become a vital component of the intellectual study of entrepreneurship and (Gaglio & Katz, 2001); Alvarez and Busenitz (2001) developed and applied the ideas of the resource-based theory to entrepreneurship. They extended the concepts of resources to include the various cognitive abilities possessed by the individual entrepreneur to create and combine new heterogeneous resources. The first goal of this analysis was to describe activities and skills that can be seen as resources. These include opportunity-seeking behavior, combining and organizing resources, assembling the resources into a firm, and creating heterogeneous outputs through the firm that are superior to the market. Entrepreneurial cognition facilitates competitive advantage through opportunity discovery and development of the firm through its early stages. There has been extensive attention on why, when, and how some persons are intelligent to identify opportunities, though others are not able to identify (Shane & Venkataraman, 2000).

Realizing entrepreneurial opportunities needs that people not only hold some type of previous information and knowledge, but they should also have the intellectual capabilities and skills that permit them to value and use that information (Corbett, 2007). The nature and origins of new ideas are examined, focusing particularly on how existing knowledge shapes those ideas and on cognitive processes by which people access and use their knowledge. The origin of an idea can be determined through a variety of processes accessing knowledge, such as conceptual combination, analogy, and problem formulation. This can also be applied to entrepreneurship. Careful application of a number of various basic processes can put knowledge to effective use and improve entrepreneurial creativity (Ward, 2004).

As per the arguments of Gaglio and Katz (2001), understanding the opportunity identification process is one of the main demands within the field of entrepreneurship. Scholars have asserted that opportunity identification may be linked to, amongst other causes, entrepreneurial attentiveness (Kirzner, 2009), previous information and knowledge (Shane & Venkataraman, 2000), social links (Singh et al., 1999), entrepreneurial thought (Baron, 1998), and possible financial returns (Schumpeter, 1942). While every area of these studies has made a role in our understanding of chance detection, previous information and knowledge and possible financial return have been essential to numerous current researches. For instance, social linkages are mainly essential for gaining access to and decreasing the costs of assets essential for entrepreneurial action (Cromie, 1994; Lin et al., 1981; Portes, 1998); they are a foundation of knowledge about new opportunities (enhance knowledge) and make the entrepreneurial act more financially pleasing (Birley, 1985; Burt, 1997; Johannisson & Huse, 2000).

Previous information and knowledge is an individual’s distinguishing knowledge about a specific topic and offers him or her the ability to identify certain opportunities (Shane & Venkataraman, 2000; Venkataraman, 2002). Financial literacy and financial education are phenomena that have been overly explored in the developed world, on the other end are scarcely examined in developing economies. Much need to be done in terms of research on the subject matter, there is a need to restructure the institutional frameworks to enhance initiatives and policies for upselling financial literacy educational outreach in developing countries. (Mabula & Ping, 2019).

2.1.4. Financial Literacy and Entrepreneurship

In general, it is recognized that most of the customers do not have the necessary financial knowledge essential for making vital economic judgments and choices in their greatest interest (Perry et al., 2008). Consumer financial literacy has become a growing concern to educators, community groups, businesses, government agencies, and policymakers. Correspondingly, there has been an increase in the number and types of financial education programs available to households. Many of these programs focus on providing information to consumers and operate under the implicit assumption that increases in information and knowledge will lead to changes in financial- management practices and behaviors. (Hilgert et al., 2003). It was discovered that there was a great relationship between financial literacy and successful entrepreneurship. Above all, with their small sample, they found that the financial literacy of the entrepreneurs was above average (Mabula & Ping, 2019). 

Financial literacy is explained by Noctor et al. (1992) as: “The capability to create knowledgeable decisions & choices about the use and management of capital”. The Financial Literacy and Education Commission (FLEC) of the US defines financial literacy as “the capability to take well- versed decisions and to take active arrangements concerning the present and upcoming usage and management of capital” (Maes & Basu, 2005). As per the definition of OECD, financial literateness is: “‘A combination of awareness, knowledge, skill, attitude, and behavior necessary to make sound financial decisions and ultimately achieve individual financial wellbeing”. Mandell and Klein (2009) examined the differential impact of high school students of a personal financial management course. The findings indicated that those who took the course were no more financially literate than those who had not. Besides, those who took the course did not evaluate themselves to be more savings-oriented and did not appear to have better financial behavior than those who had not taken the course. The study raises serious questions about the longer-term effectiveness of high school financial literacy courses. The above explanations proposed that monetary and financial information or abilities and fluctuations in financial performance are increased from financial literacy (Hilgert et al., 2003).

Financial knowledge has an impact on persons, families, financial organizations, and the wider economy as it is an essential part of our day-to-day lives and its absence has been mentioned by several analysts as a central cause for reducing saving amounts (Hilgert et al., 2003), rising customer obligation (Stango & Zinman, 2007), insufficient preparation for superannuation (Lusardi & Mitchell, 2007), the foundation for separation, psychological disease & the range of further hopeless practices (Kinnunen & Pulkkinen, 1998). Much research, which has been done mostly in advanced nations, has revealed that financial literacy is a vital element of comprehensive financial choice creating and may create crucial consequences for economic conduct. i.e. debt- taking problem is mostly with low financial literate people (Lusardi et al., 2011). Their participation in the share market is also very low (Van Rooij et al., 2007), and fewer chances to take low fee benefits of investment products (Hastings & Tejeda-Ashton, 2008). With no financial literacy, there is less chance that they gather capital and manage capital efficiently (Stango & Zinman, 2009) and may not make a strategy for superannuation (Lusardi, 2008).

H1 : There is a relationship between educational attainment level and entrepreneurial intent.

H2: There is a relationship between the level of computer literacy and entrepreneurial intent.

H3: There is an association between financial attitude and entrepreneurial intent.

H4: There is an association between financial knowledge and entrepreneurial intent.

3. Method

3.1. Measurement scale

The aim of the Theoretical model as adapted by

Rugimbana and Oseifuah (2010), is to examine and to have deep knowledge of financial literacy and youth Entrepreneurial Intent. The nature of this research was quantitative. According to Saunders and Lewis (2012), logical research is causal research that is used to test the relationship between factors. A single data collection technique was used followed by a parallel quantitative analysis process (Tabachnick et al., 2007). A closed-ended self-administered questionnaire (self-administered as the respondents fill it in themselves, without an interviewer) as a research tool was used. The questionnaire consists of questions to be answered by participants, with closely defined alternatives (Sekaran & Bougie, 2010). The aim was to get legal, consistent, neutral data from a representative sample of participants (McColl et al., 2001). Organized survey forms were used for data collection. The questionnaire was adapted from the study of Rugimbana and Oseifuah (2010).

The population in this study is youth; hence, the data was collected from youth from the age of 18 to 35. G Power, a software used to calculate power for a wide variety of statistical tests, was used to determine the sample size. The minimum sample size was 148 as determined from G power. A convenience sampling method (Non-Probability) was used. Saunders and Lewis (2012) trust data collection from population members who are appropriately accessible to contribute to the study.

3.2. Analytical tool

The data is analyzed through a smart-PLS and estimated by Partial Least Square (PLS). PLS was used to check the impact of independent variables (more than one) on the dependent variable (Hair et al., 2006; Rehman et al., 2020). Hair et al. (2017) defined Structural Equation Modeling (SEM) as “a multivariate statistical analysis technique that is used to analyze structural relationships”.

4. Data Analysis

4.1. Descriptive

The questionnaire consists of questions on Qualification, Computer literacy, Age, Occupation, and Gender. A major portion of the respondents had a bachelor’s degree (48.3%), 32.5% had a Master’s/MS degree and 19.2% had Intermediate or less education. Overall, respondents had graduation or higher qualification i.e. 80.8%. Of the computer Knowledge, 68.4% of respondents had good computer literacy and 31.6% had no or little computer literacy. 224 males and 99 females were among the respondents. 222 students, 86 employed, and 15 unemployed respondents filled the questionnaires with 71.5% between the age of 18-25 and 28.5% between the age of 26-35. Data is presented in Table 1.

Table 1: Descriptive Statistics

4.2. Measurement Model Analysis (Stage-1)

The relationship between dependent and independent variables is shown by the measurement model (Hair et al., 2017). In this research, the data that was gathered through the survey was broken down using SEM. Generally operated software for Partial Least Square-SEM (Smart PLS form 3.02.7) was being used for the analysis of quantitative data. In this study, the measurement model is analyzed into 2 diverse phases.

In the first phase, the dimensions of Entrepreneurial Intent and Financial Literacy are measured for reliability and validity using the criteria suggested by Hair et al. (2017). In the second phase, the bootstrapping technique is used to assess the structural model to get the ‘t-statistics’ and ‘p’ values. The t-statistic is the ratio of the departure of the estimated value of a parameter from its hypothesized value to its standard error. The T-statistic is used in a T-test to determine if we should support or reject the null hypothesis. The p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct. A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis. Hence, the assessment of the measurement model was very important, which gives a comprehensive summary of the constructs.

4.2.1. Reliability

Cronbach’s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. As shown in Table 2, Cronbach’s coefficient Alpha values demonstrate good consistency. Hence, is reliable. The lowest Cronbach’s coefficient Alpha value is 0.730 while the highest value is 0.901 indicating that the questionnaires have reliable & constant outcomes. Cronbach’s coefficient Alpha accepts that all the indicators are similarly consistent. Composite reliability or construct reliability is a measure of internal consistency in scale items, similar to Cronbach’s alpha. Table 2 shows that the composite reliability (CR) values are within the acceptable range of 0.863 to 0.935. Thus, it is observed from the results that the instrument used in this research is reliable.

4.2.2. Convergent Validity

Convergent validity refers to how closely the new scale is related to other variables and other measures of the same construct. While the construct must correlate with related variables, it should not correlate with dissimilar, unrelated ones. Therefore, the variance or convergence should be high for the indicators of a construct. The average variance extracted (AVE) is a measure of the amount of variance that is captured by a construct in relation to the amount of variance due to measurement error. To establish convergent validity, the outer/ factor loadings of the indicator, composite reliability (CR), and the average variance extracted (AVE) have to be considered. For the outer loadings of a construct to be high, it should be above 0.708 (ideally), which represents that the factor extracts sufficient variance from that variable (Hair et al., 2017). As shown in Table 2, the constructs have factor loadings greater than the threshold value of 0.708. This shows that the indicators for the constructs in this research had much in common.

As shown in Table 2, the AVE values for the construct are more than 0.5 indicating that the construct explains the greater part of the difference of its indicators. Hence, from the outcomes of factor loadings and the AVE, it is resolved that there are no convergent validity issues for the constructs (Table 2).

4.2.3. Discriminant Validity

Table 3 offered the outcomes for the Fornell and Larcker (1981) criterion. Discriminant Validity determines whether the constructs in the model are highly correlated among them or not. It compares the square root of AVE of a particular construct with the correlation between that construct with other constructs. The value of the square root of AVE should be higher than the correlation. The outcomes show that the square root of the AVE of the constructs is higher than the association (correlation) between the constructs. From these outcomes, it can be recognized that the discriminant validity problem does not exist in current research.

Table 2: Reliability and Convergent Validity 

Note: CA= Cronbach’s Alpha, CR= Composite Reliability, AVE= Average Variance Extracted. The two exogenous constructs education level and computer knowledge are not reported due to a single item.

4.2.4. HTMT Criteria for Discriminant Validity Assessment

Henseler et al. (2015) have given one more technique for discriminant validity to assess discriminant validity: Heterotrait –Monotrait Ratio of correlations. According to this technique, the value of HTMT < 0.9 shows that the two constructs are differently distinct from each other. Table 3 presents the values, which are less than the threshold of 0.9; hence, the discriminant validity has been established between two constructs

4.3. Assessment of the Structural Model (Stage-2)

The relationships between the examined constructs are displayed by the structural model. Figure 1 depicts the structural model highlighting the association between financial literacy, computer knowledge, and education level, and Entrepreneurial Intent. While Figure 1 also shows the structural model showing the relationships between the dimensions of financial literacy and Entrepreneurial Intent. Moreover, the model was evaluated to decide if the independent variables had been an effect on the dependent variable. In the current research, financial literacy and its two parts (financial attitude and financial knowledge) were assumed to have a positive impact on Entrepreneurial Intent. Figure 1 shows a beta value of 0.179 for financial attitude and 0.122 for financial knowledge, 0.119 for computer knowledge, and 0.559 for education level Table 5.

Table 3: Discriminant Validity (Fornell and Larcker (1981) Criterion & HTMT-Ratio) Table 4: Collinearity Diagnostic

Note: Table represents VIF (Variance Inflation Factor) results, recommended threshold < 03 (Joe F Hair Jr et al., 2020).

4.3.1. Collinearity Assessment

Furthermore, it is suggested that the collinearity measurement (Variance Inflation Factor) must be examined for the construct (Hair et al., 2020). Multicollinearity is a problem because it undermines the statistical significance of an independent variable. It reduces the precision of the estimate coefficients, which weakens the statistical power of the model. Multicollinearity was measured by variance inflation factors (VIF) and tolerance. VIF and tolerance are both widely used measures of the degree of multi-collinearity of the ith independent variable with the other independent variables in a regression model. The recommended VIF is 5, and the values of VIF that exceed 5 are regarded as indicating multicollinearity (Hair et al., 2006). The results of the VIF are exhibited in Table 4, and it shows the most extreme VIF value for the manifest variable was 1.095, which was well under the suggested value, hence it indicates that there are no multicollinearity issues (Figure 1).

Figure 1: Structural Model

4.3.2. Path Coefficient

The path coefficient tells the significance of hypothesized relations among the constructs. In this model, four latent variables are tested for path coefficient, hypothesized in development section 2.2. The results for the path coefficient for each hypothesis are shown in Table 5. It is found that Financial attitude (β 0.179; p< 0.001), financial knowledge (β 0.122; p< 0.005), computer knowledge (β 0.119; p< 0.000), and education level (β 0.559; p< 0.000) all had a positive significant effect on Entrepreneurial Intent (P-value is below the 0.05). Thus, it is confirmed that all the hypotheses are supported, as shown in Table 5.

Table 5: Structural model Summary 

Note: The β= path coefficients of partial least square results. STDEV= standard error for specific coefficients. T= t-statistics and decision rules are for alternative hypotheses developed in chapter two.

Table 6: f -Square (Effect Size), R-Square, & Predictive relevance

4.3.3. Assessment of R²

Another step of assessment in the structural model analysis is R², it is also called the coefficient of determination (Hair et al., 2020). The coefficient of determination is the proportion of the variance in the dependent variable that is predictable from the independent variable(s) (analyze how differences in one variable can be explained by a difference in a second variable) From Table 6, we see that 44% of the change in Entrepreneurial Intent (R² 0.44) was explained by financial literacy and its dimensions. Therefore, we can determine that the strength of the relationship between variables is significant.

4.3.4. Assessment of Effect Size ( f ²)

Effect size is a statistical concept that measures the strength of the relationship between two variables on a numeric scale. The effect size (f²) of the coefficient of determination (R²) was vital since it regulates the strength of the change described by the independent variables. The f ² (effect size) of 0.02 is considered as minor, 0.15 as mediocre & 0.35 as high (Cohen et al., 2013). Therefore, as per Cohen’s criteria, the impact of financial attitude (f ² 0.054) on Entrepreneurial Intent was mediocre, while the impact of financial knowledge (f ² 0.025) on Entrepreneurial Intent was minor. The highest effect size was from education level on Entrepreneurial Intent (f ² 0.521) as shown in Table 6.

4.3.5. Assessment of the Predictive Relevance (Q²)

The final stage of structural model analysis is predictive relevance. It is donated by Q². The blindfolding technique has been used to analyze the predictive relevance of the independent variables over the dependent variable (Hair et al., 2017, 2020). It is recommended by Hair et al. (2020) that the value of Q² (Stone Geisser) should be observed after the R² assessment as a measurement of predictive accuracy. In the structural model, a Q² value larger than zero for a certain construct indicates the PLS path model has predictive relevance for that construct. Table 6 shows 0.287 for Q² which is greater than zero. This value is significant, and it shows that financial attitude, financial knowledge, computer knowledge, and education level predicts Entrepreneurial Intent.

5. Discussion and Conclusion

The core purpose of this research was to inspect the effect of financial literateness and its components on young generation Entrepreneurial Intent in the context of Pakistan. Generally, the research added and contributed to current works by suggesting & authenticating a measurement model and the association with Entrepreneurial Intent. The hypothetically resulting research model was verified using PLS-SEM.

Moreover, the research has given the experimental confirmation that financial literacy has a positive impact on Entrepreneurial Intent. Likewise, the research provides truthful and accurate evidence that two dimensions (financial attitude and financial knowledge) of financial literacy has a major positive effect on Entrepreneurial Intent. The size of the joint impact of financial literacy and its components on Entrepreneurial Intent was detected to be adequate (Khuong & An, 2016; Mabula & Ping, 2019; Rugimbana & Oseifuah, 2010).

Entrepreneurial Intent, particularly in developing countries like Pakistan, is very essential for creating new firms to maintain economic development. The main objective of the research was to find the influence of financial learning and its dimensions on Entrepreneurial Intent to discover their fundamental interrelationships. As per the earlier studies and the experimental proof of the current research, this has been confirmed that financial literacy can provide a lot of benefits to a country like Pakistan for the i) Creation of new firms and ii) it positively affect Entrepreneurial Intent (McMillan & Woodruff, 2002; Tanveer et al., 2011).

Furthermore, it is determined in this research that if youth has better financial knowledge and financial attitude, the probability of Entrepreneurial Intent may increase. This will increase the number of new firms and help in the reduction of unemployment which is one of the major issues in Pakistan (Abid et al., 2015). Youth will become job creators instead of job seekers. In the situation of Pakistan, we determine that financial literacy models influence Entrepreneurial Intent positively (Mubarka et al., 2012). However, to date, there is no agreement presently on a single financial literacy model that is accepted internationally. Hence, it is arguable. Finally, the results of this study add to the understanding of in what way societies can make use of financial literacy in enhancing the probabilities of creating new firms by increasing Entrepreneurial Intent among youth (Faizunnisa & Ikram, 2004; Kasim et al., 2014; Lerner, et al., 2009).

References

  1. Abid, T., Altaf, M., Yousaf, U., & Bagram, M. (2012). Entrepreneur as an authentic leader: A study of small and medium-sized enterprises in Pakistan. Management Science Letters, 2(7), 2355-2360. https://10.5267/j.msl.2012.08.007
  2. Ahmad, N., & Seymour, R. G. (2008). Defining entrepreneurial activity: Definitions supporting frameworks for data collection. OECD Statistics Working Papers 2008/1. OECD Publishing. http://doi.org/10.1787/2431646867632
  3. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
  4. Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research Psychological Bulletin, 84(5), 888. https://doi.org/10.1037/0033-2909.84.5.888
  5. Akanbi, S. T. (2016). Contributions of perfectionism and social support to the prediction of work-family conflict among women academics in Oyo State, Nigeria. Gender & Behaviour, 14(1), 7182-7196.
  6. Alvarez, S. A., & Busenitz, L. W. (2001). The entrepreneurship of resource-based theory. Journal of Management, 27(6), 755-775. https://doi.org/10.1177/014920630102700609
  7. Ardichvili, A., Cardozo, R., & Ray, S. (2003). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18(1), 105-123. https://doi.org/10.1016/S0883-9026(01)00068-4
  8. Aronsson, M. (2004). Education matters-but does entrepreneurship education? An interview with David Birch. Academy of Management Learning & Education, 3(3), 289-292. https://doi.org/10.5465/amle.2004.14242224
  9. Baron, R. A. (1998). Cognitive mechanisms in entrepreneurship: Why and when entrepreneurs think differently than other people. Journal of Business Venturing, 13(4), 275-294. https://doi.org/10.1016/S0883-9026(97)00031-1
  10. Birley, S. (1985). The role of networks in the entrepreneurial process. Journal of Business Venturing, 1(1), 107-117. https://doi.org/10.1016/0883-9026(85)90010-2
  11. Braunstein, S., & Welch, C. (2002). Financial literacy: An overview of the practice, research, and policy. Federal Reserve Bulletin., 88, 445. https://www.federalreserve.gov/pubs/Bulletin/2002/1102lead.pdf
  12. Bui, N. V., Nguyen, N. D. P., Dao, D. H., & Tran, N. Q. (2020). A model of factors affecting entrepreneurial intention among information technology students in Vietnam. The Journal of Asian Finance, Economics, and Business, 7(8), 461-472. https://doi.org/10.13106/jafeb.2020.vol7.no8.461
  13. Burt, R. S. (1997). The contingent value of social capital. Administrative Science Quarterly, 42(2), 339-365. https://doi.org/10.2307/2393923
  14. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. London, UK: Routledge.
  15. Corbett, A. C. (2007). Learning asymmetries and the discovery of entrepreneurial opportunities. Journal of Business Venturing, 22(1), 97-118. https://doi.org/10.1016/j.jbusvent.2005.10.001
  16. Cromie, S. (1994). Entrepreneurship: The role of the individual in small business development. Irish. Business and Administrative Research, 15, 62.
  17. Davidsson, P., & Honig, B. (2003). The role of social and human capital among nascent entrepreneurs. Journal of Business Venturing, 18(3), 301-331. https://doi.org/10.1016/S0883-9026(02)00097-6
  18. Douglas, E., & Fitzsimmons, J. (2005). Entrepreneurial intentions towards individual vs corporate entrepreneurship. In: P. Hutchinson (Ed.), Small enterprise research: The Journal of SEAANZ (pp. 1-22). SEAANZ, New South Wales, Australia: Armidale,
  19. Doz, Y., Hamel, G., & Prahalad, C. (1989). Collaborate with your competitors and win. Harvard Business Review, 67(1), 133-139. https://hbr.org/1989/01/collaborate-with-your-competitors-and-win
  20. Faizunnisa, A., & Ikram, A. (2004). Determinants of youth development in Pakistan. Lahore Journal of Economics, Department of Economics, 9(2), 119-133. https://ideas.repec.org/a/lje/journl/v9y2004i2p119-133.html https://doi.org/10.35536/lje.2004.v9.i2.a7
  21. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Los Angeles, CA: Sage Publications
  22. Gaglio, C. M., & Katz, J. A. (2001). The psychological basis of opportunity identification: Entrepreneurial alertness. Small Business Economics, 16(2), 95-111. https://10.1023/a:1011132102464
  23. Garba, A. S., Kabir, S., & Nalado, A. M. (2014). An assessment of students' entrepreneurial intentions in the tertiary institution: A case of Kano State Polytechnic, Nigeria. International Journal of Asian Social science, 4(3), 434-443. http://www.aessweb.com/pdf-files/ijass-2014-4(3)-434-443.pdf
  24. Gartner, W. B. (1988). "Who is an entrepreneur?" iI the wrong question. American Journal of Small Business, 12(4), 11-32. https://doi.org/10.1177/104225878801200401
  25. Gaudecker, V. H. M. (2015). How does household portfolio diversification vary with financial literacy and financial advice? The Journal of Finance, 489-507. https://doi.org/10.1111/jofi.12231
  26. Gendron, B. (2004). Why emotional capital matter in education and labor? Toward optimal exploitation of human capital and knowledge management. In: Les Cahiers de la Maison des Sciences Economiques, Serie Rouge, N° 113, (p. 35) Paris: Universite Pantheon-Sorbonne. http://econpapers.repec.org/paper/msewpsorb/r04113.htm
  27. Gerardi, K., Goette, L., & Meier, S. (2010). Financial literacy and subprime mortgage delinquency: Evidence from a survey matched to administrative data. Working Paper 2010. Federal Reserve of Atlanta. https://www.frbatlanta.org/-/media/documents/research/publications/wp/2010/wp1010.pdf
  28. Gimeno, J., Folta, T. B., Cooper, A. C., & Woo, C. Y. (1997). Survival of the fittest? Entrepreneurial human capital and the persistence of underperforming firms. Administrative Science Quarterly, 750-783. https://doi.org/10.2307/2393656
  29. Gorman, G., Hanlon, D., & King, W. (1997). Some research perspectives on entrepreneurship education, enterprise education, and education for small business management: A ten-year literature review. International Small Business Journal, 15(3), 56-77. https://doi.org/10.1177/0266242697153004
  30. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice-Hall.
  31. Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110. https://doi.org/10.1016/j.jbusres.2019.11.069
  32. Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Los Angels, CA: Sage Publications.
  33. Hashim, R., Rufai, S. A., & Nor, M. R. M. (2011). Traditional Islamic education in Asia and Africa: A comparative study of Malaysia's Pondok, Indonesia's Pesantren, and Nigeria's traditional Madrasah. World Journal of Islamic History and Civilization, 1(2), 94-107. http://irep.iium.edu.my/24129/1/Traditional_Islamic_Education_in_Asia_and_Africa.pdf
  34. Hastings, J. S., & Tejeda-Ashton, L. (2008). Financial literacy, information, and demand elasticity: Survey and experimental evidence from Mexico. NBER Working Paper No 14538. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w14538
  35. Henry, C., Hill, F., & Leitch, C. (2005). Entrepreneurship education and training: can entrepreneurship be taught? Education+ Training, 47(2), 98-111. https://doi.org/10.1108/00400910510586524
  36. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
  37. Heuer, A., & Linan, F. (2013). Testing alternative measures of subjective norms in entrepreneurial intention models. International Journal of Entrepreneurship and Small Business, 19(1), 35-50. https://doi.org/10.1504/IJESB.2013.054310
  38. Hilgert, M. A., Hogarth, J. M., & Beverly, S. G. (2003). Household financial management: The connection between knowledge and behavior. Federal Reserve Bulletin, 89, 309. https://www.federalreserve.gov/pubs/bulletin/2003/0703lead.pdf
  39. Hoda, N., Ahmad, N., Ahmad, M., Kinsara, A., Mushtaq, A. T., Hakeem, M., & Al-Hakami, M. (2020). Validating the entrepreneurial intention model on university students in Saudi Arabia. The Journal of Asian Finance, Economics, and Business, 7(11), 469-477. https://doi.org/10.13106/jafeb.2020.vol7.no11.469
  40. Hongdiyanto, C., Teofilus, T., Sutrisno, T. F. C. W., & Dewanti, P. S. P. (2020). The effect of entrepreneurial learning on the entrepreneurial intention of Indonesian Women. The Journal of Asian Finance, Economics, and Business, 7(9), 573-582. https://doi.org/10.13106/jafeb.2020.vol7.no9.573
  41. Huston, S. J. (2010). Measuring financial literacy. Journal of Consumer Affairs, 44(2), 296-316. https://doi.org/10.1111/j.1745-6606.2010.01170.x
  42. Ismail, S., Romle, A. R., & Azmar, N. A. (2015). The impact of organizational culture on job satisfaction in higher education institutions. International Journal of Administration and Governance, 1(4), 14-19. http://www.iwnest.com/AACE/
  43. Jacob, K., Hudson, S., & Bush, M. (2000). Tools for survival: An analysis of financial literacy programs. Chicago, IL: Woodstock Institute.
  44. Johannisson, B., & Huse, M. (2000). Recruiting outside board members in the small family business: An ideological challenge. Entrepreneurship & Regional Development, 12(4), 353-378. https://doi.org/10.1080/08985620050177958
  45. Kasim, R. S. R., Zulkharnain, A., Hashim, Z., Ibrahim, W. N. W., & Yusof, S. E. (2014). Regenerating youth development through entrepreneurship. Procedia-Social and Behavioral Sciences, 129, 322-327. https://doi.org/10.1016/j.sbspro.2014.03.683
  46. Katz, J. A. (2007). Education and training in entrepreneurship, the organizational frontiers. In: J. R. Baum, M. Frese, & R. A. Baron (Eds.), The psychology of entrepreneurship (pp. 209-235). Mahwah, NJ: Lawrence Erlbaum Associates Publishers.
  47. Kemal, A. A. (2019). ICTs and entrepreneurial development: A critical review through the livelihood lens. Paper presented at 24th UK Academy for Information Systems International Conference, 9th - 10th April 2019. At: St Catherine's College, University of Oxford. https://aisel.aisnet.org/ukais2019/3/
  48. Khuong, M. N., & An, N. H. (2016). The factors affecting entrepreneurial intention of the students of Vietnam national university: A mediation analysis of perception toward entrepreneurship. Journal of Economics, Business, and Management, 4(2), 104-111. https://doi.org/10.7763/JOEBM.2016.V4.375
  49. Kinnunen, U., & Pulkkinen, L. (1998). Linking economic stress to marital quality among Finnish marital couples: Mediator effects. Journal of Family Issues, 19(6), 705-724. https://doi.org/10.1177/019251398019006003
  50. Kirzner, I. M. (2009). The alert and creative entrepreneur: A clarification. Small Business Economics, 32(2), 145-152. https://10.1007/s11187-008-9153-7
  51. Klandt, H. (2004). Entrepreneurship education and research in German-speaking Europe. Academy of Management Learning & Education, 3(3), 293-301. :https://doi.org/10.5465/amle.2004.14242226
  52. Kopnina, H., & Meijers, F. (2014). Education for sustainable development (ESD). International Journal of Sustainability in Higher Education, 15(2), 188-207. https://doi.org/10.1108/IJSHE-07-2012-0059
  53. Krueger Jr, N. F., Reilly, M. D., & Carsrud, A. L. (2000). Competing models of entrepreneurial intentions. Journal of Business Venturing, 15(5-6), 411-432. https://doi.org/10.1016/S0883-9026(98)00033-0
  54. Lerner, J. V., Phelps, E., Forman, Y., & Bowers, E. P. (2009). Positive youth development. Hoboken, NJ: John Wiley & Sons Inc.
  55. Lin, N., Ensel, W. M., & Vaughn, J. C. (1981). Social resources and strength of ties: Structural factors in occupational status attainment. American Sociological Review, 393-405. https://doi.org/10.2307/2095260
  56. Lofstrom, M., Bates, T., & Parker, S. C. (2014). Why are some people more likely to become small-businesses owners than others: Entrepreneurship entry and industry-specific barriers. Journal of Business Venturing, 29(2), 232-251. https://doi.org/10.1016/j.jbusvent.2013.01.004
  57. Lusardi, A. (2008). Financial literacy: An essential tool for informed consumer choice?. NBER Working Papers 14084. National Bureau of Economic Research, Inc.. https://www.nber.org/papers/w14084
  58. Lusardi, A., & Mitchell, O. S. (2007). Baby boomer retirement security: The roles of planning, financial literacy, and housing wealth. Journal of Monetary Economics, 54(1), 205-224. https://doi.org/10.1016/j.jmoneco.2006.12.001
  59. Lusardi, A., & Mitchell, O. S. (2011). Financial literacy around the world: an overview. Journal of Pension Economics & Finance, 10(4), 497-508. https://doi.org/10.1017/S1474747211000448
  60. Lusardi, A., Schneider, D. J., & Tufano, P. (2011). Financially fragile households: Evidence and implications. NBER Working Paper 17072. National Bureau of Economic Research, Inc.. https://www.nber.org/papers/w17072. https://doi/org/10.3386/w17072
  61. Luthje, C., & Franke, N. (2003). The 'making-of an entrepreneur: testing a model of entrepreneurial intent among engineering students at MIT. R&D Management, 33(2), 135-147. https://doi.org/10.1111/1467-9310.00288
  62. Mabula, J. B., & Ping, H. D. (2019). Financial literacy position in developing economies: A review of studies and open issues. Paper presented at the 2nd International Conference on Social Science, Public Health, and Education (SSPHE 2018).
  63. Maes, J., & Basu, M. (2005). Building economic self-reliance: Trickle Up's microenterprise seed capital for the extreme poor in rural India. Journal of Microfinance/ESR Review, 7(2), 6. https://scholarsarchive.byu.edu/esr/vol7/iss2/6
  64. Mandell, L., & Klein, L. S. (2009). The impact of financial literacy education on subsequent financial behavior. Journal of Financial Counseling and Planning, 20(1), 15-22.
  65. McColl, E., Jacoby, A., Thomas, L., Soutter, J., Bamford, C., Steen, N., Bond, J. (2001). Design and use of questionnaires: A review of best practice applicable to surveys of health service staff and patients. Health Technology Assessment, 5(31), 1-256. https://doi.org/10.3310/hta5310
  66. McGrath, R. G., Tsai, M.H., Venkataraman, S., & MacMillan, I. C. (1996). Innovation, competitive advantage, and rent: A model and test. Management Science, 42(3), 389-403. https://doi.org/10.1287/mnsc.42.3.389
  67. McMillan, J., & Woodruff, C. (2002). The central role of entrepreneurs in transition economies. Journal of Economic Perspectives, 16(3), 153-170. https://10.1257/089533002760278767
  68. Meier, S., & Sprenger, C. D. (2013). Discounting financial literacy: Time preferences and participation in financial education programs. Journal of Economic Behavior & Organization, 95, 159-174. https://doi.org/10.1016/j.jebo.2012.02.024
  69. Messy, F. A., & Monticone, C. (2016). Financial education policies in Asia and the Pacific. OECD Working Paper No 40. OECD Working Papers on Finance, Insurance, and Private Pension https://doi.org/10.1787/20797117
  70. Mubarka, K., Yousaf, U., & Altaf, M. (2012). Entrepreneurial attributes among postgraduate students of a Pakistani university. Journal of Women's Entrepreneurship and Education, (3-4), 86-101.
  71. Ndubisi, N. O., & Kahraman, C. (2005). Malaysian women entrepreneurs: understanding ICT usage behaviors and drivers. Journal of Enterprise Information Management, 18(6), 721-739. https://doi.org/10.1108/17410390510628418
  72. Nguyen, T. A. N., & Nguyen, K. M. (2020). Role of financial literacy and peer effect in the promotion of financial market participation: Empirical evidence in Vietnam. The Journal of Asian Finance, Economics, and Business, 7(6), 1-8. https://doi/org/10.13106/jafeb.2020.vol7.no6.001
  73. Noctor, M., Stoney, S., & Stradling, R. (1992). Financial literacy: A discussion of concepts and competencies of financial literacy and opportunities for its introduction to young people's learning (Working Paper). National Foundation for Educational Research.
  74. Perry, S. J., Penney, L. M., & Witt, L. (2008). Coping with the constraints of self-employment: A person-situation model of entrepreneurial burnout. Academy of Management, 1-9. https://doi.org/10.5465/ambpp.2008.33636328
  75. Polin, B. A., Ehrman, C. M., & Kay, A. (2016). Understanding parental and gender impact on entrepreneurial intentions. Journal of Small Business & Entrepreneurship, 28(4), 267-283. https://doi.org/10.1080/08276331.2016.1203689
  76. Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of Sociology, 24(1), 1-24. https://doi.org/10.1146/annurev.soc.24.1.1
  77. Rehman, K., Khan, H. H., Sarwar, B., Muhammad, N., Ahmed, W., & Rehman, Z. U. (2020). A multi-group analysis of risk management practices of public and private commercial banks. The Journal of Asian Finance, Economics, and Business, 7(11), 893-904. https://doi.org/10.13106/jafeb.2020.vol7.no11.893
  78. Remeikiene, R., Dumciuviene, D., & Startiene, G. (2013). Explaining entrepreneurial intention of university students: The role of entrepreneurial education. Paper presented at the Active Citizenship by Knowledge Management & Innovation: Proceedings of the Management, Knowledge and Learning International Conference 2013.
  79. Remund, D. L. (2010). Financial literacy explicated: The case for a clearer definition in an increasingly complex economy. Journal of Consumer Affairs, 44(2), 276-295. https://doi.org/10.1111/j.1745-6606.2010.01169.x
  80. Robinson, P. B., & Sexton, E. A. (1994). The effect of education and experience on self-employment success. Journal of Business Venturing, 9(2), 141-156. https://doi.org/10.1016/0883-9026(94)90006-X
  81. Rugimbana, R., & Oseifuah, E. K. (2010). Financial literacy and youth entrepreneurship in South Africa. African Journal of Economic and Management Studies, 1(2), 164-182. https://doi.org/10.1108/20400701011073473
  82. Saunders, M. N., & Lewis, P. (2012). Researching business & management: An essential guide to planning your project. London, UK: Pearson.
  83. Schumpeter, J. A. (1942). Capitalism, socialism, and democracy. New York, NY: Harper & Row
  84. Sekaran, U., & Bougie, R. (2010). Theoretical framework and hypothesis development. In: U. Sekaran & R. Bougie, Research methods for business: A skill-building approach (7th ed., pp. 71-94). Hoboken, NJ: JohnWiley & Sons Inc. Publishing
  85. Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217-226. https://doi.org/10.5465/amr.2000.2791611
  86. Singh, R. P., Hills, G. E., Lumpkin, G., & Hybels, R. C. (1999). The entrepreneurial opportunity recognition process: Examining the role of self-perceived alertness and social networks. Academy of Management, 1(1), 1-7. https://doi.org/10.5465/apbpp.1999.27600505
  87. Stango, V., & Zinman, J. (2007). Fuzzy math and household finance: Theory and evidence. The Review of Financial Studies, 24(2), 506-534. https://doi.org/10.1.1.468.2272 https://doi.org/10.1.1.468.2272
  88. Stango, V., & Zinman, J. (2009). What do consumers pay on their checking and credit card accounts? Explicit, implicit, and avoidable costs. American Economic Review, 99(2), 424-429. https://doi.org/10.1257/aer.99.2.424
  89. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics. Boston, MA: Pearson
  90. Tanveer, M. A., Gillani, U. A., Rizvi, S., Latif, M., Maqbool, H., & Rizwan, M. (2011). Barriers for business students in becoming an entrepreneur in Pakistan. IOSR Journal of Business and Management, 74-82.
  91. Ucbasaran, D., & Westhead, P., Wright, M. (2008). Opportunity identification and pursuit: does an entrepreneur's human capital matter? Small Business Economics, 30(2), 153-173. https://doi.org/10.1007/s11187-006-9020-3
  92. Van Rooij, E., Sutherland, L. B., Qi, X., Richardson, J. A., Hill, J., & Olson, E. N. (2007). Control of stress-dependent cardiac growth and gene expression by a microRNA. Science, 316(5824), 575-579. https://10.1126/science.1139089
  93. Veciana, J. M., Aponte, M., & Urbano, D. (2005). University students' attitudes towards entrepreneurship: A two countries comparison. The International Entrepreneurship and Management Journal, 1(2), 165-182. https://doi.org/10.1007/s11365-005-1127-5
  94. Venkataraman, S. (2002). Stakeholder value equilibration and the entrepreneurial process. The Ruffin Series of the Society for Business Ethics, 3, 45-57. doi:https://doi.org/10.5840/ruffinx2002313
  95. Vesper, K. H., & Gartner, W. B. (1997). Measuring progress in entrepreneurship education. Journal of Business Venturing, 12(5), 403-421. https://doi.org/10.1016/S0883-9026(97)00009-8
  96. Walter, S. G., & Dohse, D. (2009). The interplay between entrepreneurship education and regional knowledge potential in forming entrepreneurial intentions (Working Paper No. 1549). Dusternbrooker Weg, Germany: Kiel Institute of World Economy. https://www.files.ethz.ch/isn/106013/kwp_1549.pdf.
  97. Wang, C. K., & Wong, P. K. (2004). The entrepreneurial interest of university students in Singapore. Technovation, 24(2), 163-172. https://doi.org/10.1016/S0166-4972(02)00016-0
  98. Ward, T. B. (2004). Cognition, creativity, and entrepreneurship. Journal of Business Venturing, 19(2), 173-188. https://doi.org/10.1016/S0883-9026(03)00005-3
  99. Yoon, S. A., Goh, S. E., & Park, M. (2018). Teaching and learning about complex systems in K-12 science education: A review of empirical studies 1995-2015. Review of Educational Research, 88(2), 285-325. https://doi.org/10.3102/0034654317746090
  100. Yousaf, U., Shamim, A., Siddiqui, H., & Raina, M. (2015). Studying the influence of entrepreneurial attributes, subjective norms, and perceived desirability on entrepreneurial intentions. Journal of Entrepreneurship In Emerging Economies. https://doi.org/10.1108/JEEE-03-2014-0005

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