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RUSSIAN LAW JOURNAL Volume XI (2023) Issue 6s
THE INFLUENCE OF SOCIAL NETWORK TIES TOWARDS SOCIAL ENTREPRENEURIAL INTENTION OF UNDERGRADUATE STUDENTS: THE
CASE OF SRI LANKA
MOHAMED WAHISH HASHIM1, ALI KHATIBI2, S.M. FERDOUS AZAM3
1University of Buraimi (Oman) Email address: mohamed.w@uob.edu.om 2Management Science University (Malaysia)
Email address: alik@msu.edu.my 3Management Science University (Malaysia) Email address: drferdous@msu. edu. my
Abstract: The purpose of this study is to complement the existing body of knowledge on social entrepreneurial intention by testing the Theory of Planned Beavior and Social Network Theory in the Sri Lankan Context among state undergraduate students. The Theory of Planned behavior (TPB) and Social Network Theory was tested in the context of state undergraduate students in Sri Lanka. Exogenous variables included Personal Attitude, Subjective Norm, Perceived Behavioral control, and social networks were studied. The instrument used in the study was developed using validated items from past literature. Data for this quantitative study were collected from undergraduate students from nine state universities in Sri Lanka. Structural equation modeling was used to see the insights from the valid data using IBM's SPSS 25 and AMOS 22. Results of the confirmatory factor analysis and subsequent evaluation of the structural model revealed a positive relationship exists between Social Entrepreneurial Intention and employment attitude, social entrepreneurial Intention and Perceived behavioral control and, Social Network Ties and perceived behavioral control . However, the results did not support the relationships between social entrepreneurial intention and subjective Norms. limited research has been carried out in the area of social entreprenurship in the Sri Lankan context. This research will shed light on the antecedent factors that affect social entrepreneurial intention and assist policymakers in developing appropriate strategies for promoting Social entrepreneurship among undergraduates and therby assisting in solving the unemployment problem faced by state undergraduate students.
Keywords - Social Entrepreneurship intention, Theory of Planned Behavior, Social Network Theory, Sri Lanka.
1 Introduction
In recent years, social entrepreneurship has grown in importance both as a research field and as a social phenomenon (Dacin et al., 2011 b, Yu et al., 2021). The interest in social entrepreneurship has not been limited to academic researchers, but business and government organizations have also turned their eyes toward this (Alderson, 2012). This is due to the commandeering of social reform in areas such as poverty elevation, social inclusion, and environmental threats (Seelos et al., 2011).
Unemployment among state university undergraduates has become a social problem since the1960s. Since then, It has evolved with more noticeable political implications as a socio-economic problem in itself, as seen by two left-wing insurrections in the south and north of the country (Samaranayake, 2016). Despite the prevailing unemployment situation of state university graduates in Sri Lanka (Singam, 2017), which is considered a major socio-politico-economic problem (Chandrasiri, 2008b), limited studies have examined social entrepreneurship as a career choice among State University graduates in Sri Lanka.
Unemployment has been identified as a motivational factor influencing individuals to start a business (Manimala et al., 2009). However, Despite the Government of Sri Lanka promoting entrepreneurship through various programs such as "Enterprise Sri Lankan" ('Enterprise Sri Lanka' Will
Foster Entrepreneurship, n.d.), there is little to show that these programs have reached the undergraduates of state universities and had an impact on the unemployment problem.
This document is formatted in accordance with the SJIS formatting guidelines by means of a Microsoft Word style sheet. SJIS authors are requested to use the template described in this document.
2 Literature Review
Social entrepreneurship is considered as a solution to the challenges of sustainable development and improving the living conditions of people in a socity (Amani & Link to external site, 2022). Social entrepreneurship is a by-product of established concepts such as social innovation and entrepreneurship. Therefore, the theoretical literature on social entrepreneurship lacks (Tiwari et al., 2017b). This is evident in the Sri Lankan Context, as there is a lack of literature on Social Entrepreneurship. Literature on Social entrepreneurial Intention is far lessor to find and more specifically regarding State University undergraduates. Therefore, exploring the antecedent factors that affect social entrepreneurial intentions among state undergraduate students is vital to understanding what motivates them to choose a career as a social entrepreneur. In addition, Social entrepreneurship scholars aim is to provide practitioners with knowledge which will successfully progress in creating and sustaining social business ventures (Ranville et al., 2022).
According to Alvord et al., (2004), there are Three main approaches to social entrepreneurship: the first combines profitmaking while having a social impact; the second approach is where the social entrepreneur is an innovator with a social impact; and the third approach is where the entrepreneur produces small social changes in the short-term that echo through established existing structures to act as a catalyst to initiate changes in the longer-term.
The antecedent factors that affect social entrepreneurial Intention have been studied in different contexts. However, these factors have not been extensively studied among state university undergraduates in the Asian region (Tiwari et al., 2017a). The environmental and start-up factors influencing the social entrepreneurship process in Asia differ significantly from the aspects covered by existing research studies (Tiwari et al., 2017a). In addition, authors such as Linan et al., (2015), have emphasized the lack of empirical research in the areas of Social entrepreneurial Intention in general.
Social network ties are considered an input factor in entrepreneurial Intention (De Ruysscher et al., 2017), and they help design products and services with social value (Sridharan & Viswanathan,
2008). Dacin et al. (2011), propose that empirical studies are scarce in social entrepreneurship and social network ties
Academics recognize that the social enterprise creation and development process is unknown, describing it as an unclear field of research and recognizing the need for academic input (Hechavarri'a et al. 2012; Bechir, 2021). Therefore, the knowledge gained from the study will shed light on the impact of different factors that will affect Social entrepreneurial Intention. The extensive literature highlighted that the lack of literature on social entrepreneurial Intention in Sri Lanka could hinder future research. Therefore, the knowledge gained through this research can assist in furthering the research activity in this area.
3 Theoretical Framework
3.1 Social Network Theory
Social Network Theory is a theory that discusses the relationships and connections in a social structure (Kadushin, 2004). A social network is a set of actors or nodes connected by social relationships or ties.
To develop a comprehensive understanding of entrepreneurship, it is vital to appreciate the Network in which the entrepreneur operates ( Birley, 1985). It has been pointed out that social networks that entrepreneurs build are important or essential for entrepreneurial success (Egbert,
2009); it also influences the firm's innovation and economic performance (Ahuja, 2000). The entrepreneur will use their social Network at the initial stages of the venture when the foundation
of the firm is established and subsequently develop marking networks with the aim of increasing sales (Lechnerand Dowling, 2003) and will also assist in identifying potential customers and suppliers (Adler and Kwon, 2002). The decision by the entrepreneur to get involved in an organizational or individual network will affect the organizational outcomes (Qian & Kemelgor, 2013), therefore to benefit from the advantages of these networks, entrepreneurs have been known to invest time and resources in developing social relationships (Nasser Al Muniri et al., 2019).
Identifying market opportunities and developing a business idea is essential to becoming an entrepreneur. In the early stages of venture creation, an entrepreneur consistently uses the social, professional, and personal networks that have been created to gather information and ideas and to identify and exploit market opportunities (e.g., Ozgen and Baron, 2007; Fang et al., 2015; Lechner et al.,2006). Start-up ventures finding low-cost financial capital is important because the cash flow is limited in the initial stages. Social networks can assist the obtaining low-cost financial capital (Uzzi, 1999) to entrepreneurs, enabling them to exploit opportunities that present to them.
There has recently been a surge in interest in the association between various entrepreneurial outcomes and networks (Hoang and Antoncic, 2003). Many research studies have investigated the relationship between entrepreneurs' social networks and organizational performance. Several studies have found a positive relationship between a social network and organizational performance, while others have failed to do so. This makes us believe that entrepreneurs' use of available social networks varies (Hoang and Antoncic, 2003). Other studies it has shown that an organization benefits from increased performance with the increasing number of ties with suitable partners (Hallen and Eisenhardt, 2012).
According to Greve and Salaff (2003), whether an entrepreneur expands or shrinks, his Network will be part of his business decision, which means that it is a conscious choice that is made while considering the pros and cons associated with that decision. The development of these networks will depend on the phase of entrepreneurship he may be in (Greve and Salaff , 2003). These networks will change and evolve based on the individual entrepreneur's needs (Burt,1992).
Start-up firms and their custodians, on behalf of their organizations, establish professional and personal networks and maintain relationships to build their reputation and gain access to resources and vital information (Konrad, 2013 & Florin et al.,2003). Even after the initial stages of creating a venture, entrepreneurs continue to depend on social networks to access resources such as information, advice, technology, and referrals (Batjargal and Liu, 2004). According to Nahapiet and Ghoshal (1998), the larger the Network s it is more likely the organization will have greater access to resources than a smaller network, which encourages the entrepreneur to enlarge their Network (Greve and Salaff , 2003).
Development of a business venture is a social process in which the entrepreneurs and its social. Being part of a social network brings many advantages, if not a necessary asset for an entrepreneur (Masurel et al., 2002); on the other hand, it brings limitations regarding influence, information, and solidarity (Adler and Kwon, 2002). If social networks get too large, the entrepreneur may be less benefited by the resources that the Network gives access to (Lechner et al., 2006) and may hurt an organization's overall performance (Qian & Kemelgor, 2013). It has been argued by Egbert (2009) that successful entrepreneurs may impair their overall performance through social networks.
Networks play an impotent role in the venture's success (Aldrich and Ruef, 2006). It is widely believed that networks are vital in the entrepreneurial process since they provide a framework to organize resources according to the market opportunities that present themself (Powell et al.,1996). The factors that affect the entrepreneurial process can be considered as the network structure made up of the relationship patterns and the network content and the network content or, in other words, the access it provides to the resources (Slotte-Kock and Coviello,2010); they will affect the daily operations of the start-up and eventually the venture success. During the early stages of the entrepreneurial process, much time is spent maintaining network relationships using external social ties (Greve and Salaff, 2003). Knowledge transfer, trust, and relationship diversity are believed to be key ingredients or elements of a well-functioning network within a social network (Thorgren et al., 2009).
Entrepreneurial literature states that personal characteristics are essential in building social networks and capital. The extent of an entrepreneur's social Network and success is related to the entrepreneur's personal characteristics (Anderson, 2008). According to Burt et al, (1998), Characteristics such as personality traits and cognition have been found to influence how individuals construct social networks in an organizational context. Another study found that political skills are essential to success in high-risk, uncertain environments (Fang et al., 2015). This would mean that individual differences will determine the extent to which people will utilize their social capital (Emirbayer and Goodwin, 1994).
3.2 Theory of Planned Behavior
The rational for using the Theory of Planned Behavior (TPB) is that the intentions of an individual can affect the behavior. However, as there are many factors that affect the intention of an individual, the explanatory power of the model may be reduced (Ming et al., 2020). In addition, The TPB assumes that humans are rational and places little concern to social factors (Sajeewanie et al., 2019)
Personal attitude
The TPB is one of the most widely used theories in the area of entrepreneurial intention reserach(Amofah & Saladrigues, 2020). According to Beck & Ajzen, (1991), the Theory of planned behavior provides a framework for understanding, and studying believes and attitudes. Luksi et al., (2016) define attitudes are a positive or negative disposition towards people, objects, events, or organizations.
The TPB can help understand human social behavior Beck & Ajzen, (1991 );,this Theory is an important social cognitive model that attempts to explain differences in consumer behavior. The feedback loop in the TPB model is hidden, which forms from prior behavior to present cognitions (Ajzen, 2015). This Theory suggests three factors that affect behavior: subjective norms, attitudes, and behavioral controls (Ajzen, 1991). (Ajzen, (2001), has defined attitudes as positive or negative feelings towards a behavior, while Luksi et al., (2016) define attitudes as a positive or negative disposition towards people, objects, events, or organizations. A person's positive attitude toward a behavior will influence whether that behavior will be pursued in addition to other factors (Obschonka et al., 2015).
Subjective norms
Subjective norms, the third independent factor in the TPB theory, is the individuals' perceptions of social pressures exerted to or against the behavior (St-Pierre et al., 2017). Luksi et al., (2016) explain that social pressure is exerted by people perceived as important to the individual in his environment to inspire that individual to complete or not to complete that behavior.
Perceived behavioral control
Ajzen, (2011), emphasizes that the Intention to complete a behavior depends on the adequate control you have over that behavior and the ease or difficulty in completing the behavior, which is reflected in the model in terms of perceptions of behavioral controls. Luksi et al., (2016) suggest that behavioral controls are the extent to which the individual has or has no control over external and internal factors that relate to the behavior. This concept has been further defined by Voegel & Pearson (2016) as "an individual's perception of how easy or difficult the act will be to perform." Cheng, Chu, & Ma (2016), further elaborates on the concept by stating that behavioral control is whether the individuals perceive self-efficacy and possess the resources needed to carry out the behavior.
4 Hypothesis
In a study conducted by Alam et al., (2019), where a survey was conducted among 448 senior-level engineering students in Pakistan, found that there was a significant and positive relationship between entrepreneurial Intention and personal attitude. According to Akinwale et al., (2019), an empirical
study conducted among 743 students from private and public universities in Saudi Arabia revealed that the student's attitude toward entrepreneurial Intention directly influences their attitude toward behavior has a direct and indirect influence. This study's results confirm and challenge the Theory of Planned Behavior, which asserts that intentions are a precursor to behavior (Esposito et al., 2016). In a study conducted in 2018 among 183 sports science students in Spain, it was found that personal attitude played an important role in determining entrepreneurial Intention (Gonzalez-Serrano et al., 2018a)
Hypothesis 1 (H1) -There is a positive relationship between State University Undergraduate students' social entrepreneurial Intention and Personal attitude.
As per a study conducted by Bazan et al., (2019), at Memorial University, Canada, 479 undergraduate students releveled that a significate relationship existed between Subjective Norm and Attitude and Perceived Behavioral Control. According to Zhang & Cain (2017), a study conducted among 306 dental students found that the attitude perceived behavioral control and Subjective norm positively related to entrepreneurial Intention. The findings of this study confirm the Theory of Planned Behavior.
Hypothesis 2 (H2) -There is a positive relationship between State University Undergraduate students' social entrepreneurial Intention and subjective Norms.
Nguyen, (2018), through his qualitative study, validated the notion that has been presented through various quantitative studies that perceived behavioral control influenced EI. An empirical study conducted by Cubillas et al., (2018) among informal entrepreneurs in Peru, found that Perceived Behavioral Control was not significant in influencing entrepreneurial Intention, while other factors of the TPB were found to be significant, with attitude being the most significant. In contrast to some of the studies conducted, scholars such as Akinwale et al., (2019), have not considered the perceived behavioral control variable as part of determining the entrepreneurial Intention as part of the Theory of Planned Behavior.
Hypothesis 3 (H3) -There is a positive relationship between State University Undergraduate students' social entrepreneurial Intention and Perceived behavioral control.
A study conducted by Farooq et al., (2018), to investigate the relationship between perceived social support from one's social Network and entrepreneurial Intention among fresh graduates found that social support from one's social Network positively influences entrepreneurial Intention, which was fully mediated by perceived behavioral control. Similarly, a study done among university students in Spain found that Network ties significantly influenced social entrepreneurial Intention, which was mediated by perceived behavioral control (Perez-Maci'as et al., 2019).
Hypothesis 4 (H4) - There is a positive relationship between social network ties and Perceived behavioral control.
5 Methodology
Research is categorized as qualitative or quantitative in nature. Qualitative research focuses on experiences and human perceptions, while quantitative research employs the use of numbers (Polit & Beck, 2012). The study aims to determine the relationships between the different variables; therefore, a quantitative method will be adopted.
A cross-sectional or social survey design was used in this research project because the research questions aim to answer the patterns between many different variables, such as the relationships among the social entrepreneurial intention and antecedent factors.
The sampling unit of this research is undergraduate students from business and non-business faculties/ specializations currently studying at state universities in Sri Lanka. The study population will be undergraduate students presently studying at Sri Lankan universities. The sampling unit will be chosen from 9 universities out of the 16 state universities covering all parts of the county. These universities will include Colombo University, the University of Peradeniya, the University of Ruhuna, the University of Jaffna, Wayamba University, Sabaragamuwa University, University of Moratuwa, University of Sri Jayewardenepura and Eastern University.
Awad et al., (2016), propose that many challenges in conducting research within education systems often lead researchers to adopt a non-probability sampling. In this research, the researcher will find it extremely difficult to access a sampling frame or a list of undergraduate students from state universities. This information is not made available to non-university staff due to privacy and security reasons. Therefore, the research will adopt non-probability sampling, specifically quota sampling.
The sample size will be determined using Krejcie and Morgan (1970), table. The total undergraduate student population in 16 universities in 2021 was 144,040, per the University Grants Commission, Sri Lanka. Accordingly, the sample size will be 384. However, 504 respondents was interviewed as part of the research.
5.1 Instrument Development
A researcher attempts to achieve three conflicting goals when conducting a survey, obtaining the right information, minimizing the cost associated with gathering the information, and speed of data collection (Vriens et al., 2001). Ambrose & Anstey (2010), states that the principles and foundation concepts of questionnaire design are limited, meaning there is no exact science in developing a questionnaire. However, based on the available literature, the questionnaire design was carried out as much as possible scientifically.
This research has used existing instruments to measure social entrepreneurial Intention, self-efficacy, and social network ties. The researcher developed his instrument to measure the construct of "prior experience of social problems" as there was no instrument readily available to the researcher.
The Theory of planned behavior was used to identify entrepreneurial Intention using the research instrument developed and validated by Kolvereid, (1996). The social network instrument was adopted from Chimucheka et al., (2019).
5.2 Data Analysis
Data collected were analyzed using IBM's SPSS and AMOS. Respondents' profile was analyzed using descriptive statistics. Confirmatory factor analysis (CFA) and SEM were used to evaluate the measurement and proposed research models.
A pilot study was conducted as an essential part of a research project. The pilot study was conducted among 127 undergraduate students from seven universities. The internal reliability test in the pilot study, for each subscale, were: Reasons for becoming a Social Entrepreneur of 19 items (a = .938), Employment attitude of 4 items ( a = .795), Subjective Norm of 6 items ( a = .897), Perceived Behavioral Controls of 6 items ( a = . 0.758), and Social Network Ties of 14 items (a = .938). In addition, exploratory factor analysis was carried out to determine the validity of the measurement instrument. A principal component analysis with a direct oblimin rotation of 71 of the 86 items from the social entrepreneurship questionnaire was conducted on data gathered from 127 participants. An examination of the Kaiser-Meyer Olkin measure suggested that the sample was factorable (KMO =.808), and the Bartlett's test of Sphercity was significant (p<.001).
6 Respondents Profile
Descriptive statistics were obtained to see the respondents' demographic details. The majority of the 504 respondents were females, accounting for 73% or 368 individuals, while males, or 27% or 136 individuals. The respondents in the survey were from two age categories, 21-30 and 31-35 years. The majority of the 428 respondents were from the 21 -30 age category, which accounted for 84.5%, while the second largest category was the 15-20 age category, which accounted for 14.5%. Undergraduate students who participated in the survey were from five years of study. The number of students from years 1, 2, 3, 4, and 5 was 36 (7.1%), 55 (10.9%), 118 (23.4%), 262 (52%), and 33 (6.5%), respectively.
Variable Frequency (%)
Gender
Male 136 27
Female 368 73
Age
15-20 years 73 14.5
21-30 years 428 84.5
31-35 years 3 .6
Over 35 years 0 0
Year of Study
Year 1 36 7.1
Year 2 55 10.9
Year 3 118 23.4
Year 4 262 52
Year 5 33 6.5
Table 1. Demographic of Respondents
7 Structural Equation Modeling Analysis
Structural Equation Modeling was used to test the study's hypothesis following the two-stage approach proposed by Anderson & Gerbing, (1988). The first stage is the development of the measurement model, which will take the form of individual and overall measurements. The confirmatory Factor Analysis (CFA) method will be used to develop the measurement model. The second stage will involve the development of the structural model to assess the relationships between the independent, dependent, and mediating constructs.
7.1 Confirmatory Factor Analysis Measurement model
As part of the confirmatory factor analysis, factor loadings were assessed for each item. No items were removed due to low factor loadings (< 0.5). The model fit measures were used to assess the model's overall goodness of fit (CMIN/df, GFI, CFI, TLI, SRMR, and RMSEA), and all values were within their respective common acceptance levels ((Bagozzi & Yi, 1988; Bentler, 1990; Hair et al., 2010; Hu & Bentler, 1998; Schumacker & Lomax, 2004). The initial individual measurement model yielded good fit ( table 2) for the data: CMIN/df = 1.533, GFI = .925 , CFI = .961, TLI = .957, SRMR =.0417 , and RMSEA = .033.
Figure 1. Measurement Model
Fit Indices Recommended Vales Source Obtained Values
P Insignificant (Bagozzi & Yi, 1988) .000
CMIN (chi- <5 (Schumacker & 1.533
square/ df) Lomax, 2004)
GFI >.90 (Hair et al., 2010) .925
CFI >.90 (Bentler, 1990) .961
TLI >.90 (Bentler, 1990) .957
SRMR <.08 (Hu & Bentler, 1998) .0417
RMSEA <.08 (Hu & Bentler, 1998) .033
Table 2. Fit Indices for Reasons for Prior Experience of Social Problems
Structural Model and Hypothesis Testing
A structural equation model generated through AMOS was used to test the hypothesis in this research project. A good fit model is accepted if the values of CMIN/df, the Goodness of Fit Indices (GFI) (Hair et al., 2010), Tucker Lewis Index (TLI); Confirmatory Fit Indices (CFI) (Bentler, 1990) is >0.90 (Hair et al., 2010). In addition, an adequate fit model was accepted if the computed values of the Standardized Root Mean Square Residuals (SRMR) < 0.08 (Hu & Bentler, 1998), and the Root Mean
Square of Error Approximation (RMSEA) is between 0.05 and 0.08 (Hair et al., 2010). The fit indices of the model fell within acceptable range: CMIN/df = 1.676, GFI = .918, CFI = .950, TLI = .945, SRMR =.0662, and RMSEA = .037.
The squared multiple correlation was 0.288 for Social entrepreneurial Intention; this shows that 28.8% variance in Social entrepreneurial Intention accounted by employment attitude, Subjective Norm, and Perceived behavioral control. While the squared multiple correlation was 0.047 for Perceived Behavioral Control, this shows a 4.7% variance in Perceived Behavioral Control accounted by Social Network Ties.
The study assessed the Social Entrepreneurial Intention Among Students in Sri Lanka Higher Education. The impact of Personal Attitude on Social Entrepreneurial Intention was positive and significant (b =.041, t =4.145, p<.001), supporting H1. The impact of Subjective Norms on Social Entrepreneurial Intention was positive and insignificant (b =0.52, t =1.689, p=0.091), hence not supporting H2. The impact of Perceived Behavioral Control on Social Entrepreneurial Intention was positive and significant (b =.069, t =8.467, p<.001), supporting H3. The impact of Social Network Ties on Perceived Behavioral control was positive and insignificant (b =-.039, t =-3.870, p<.001), supporting H4.
Figure 2. Structural model Model
The model fit indices and hypothesis results are presented in table 3.
Hypothesized Standardized t value P value Decision
relationship Estimates
Employment 0.041 4.145 <.001 Supporting H1
Attitude — Social
Entrepreneurial
Intention
Subjective Norms 0.52 1.689 p=0.091 Not supporting
— Social H2
Entrepreneurial
Intention
Perceived 0.069 8.467 <.001 Supporting H3
Behavioral Control
- Social
Entrepreneurial Intention
Social Network Ties — Perceived Behavioral Control 0.039 3.870 <.001 supporting H4
R- Square
Social Entrepreneurial Intention 0.288
Perceived Behavioral Control 0.047
Model Fit
CMIN/df = 1.676, GFI = .918, CFI = .950, TLI = .945, SRMR =.0662, and RMSEA = .037.
Table 3. Standardized Regression Weights for the Proposed Model
8 Results and Discussion
Hypothesis 1 (H1) -There is a positive relationship between State University Undergraduate students' Social Entrepreneurial Intention and Personal attitude. In a study conducted by Alam et al., (2019), a survey was conducted among 448 senior-level engineering students in Pakistan. The research findings supported this hypothesis confirming the findings of the previous studies. Simialer findings was reported by Shazra Ibrahim et al. (2021), where they found that travel intentions significantly affected the destination image in accordance with the TPB.
Hypothesis 2 (H2) -There is a positive relationship between State University Undergraduate students' social entrepreneurial Intention and subjective Norms. A study revealed that the relationship between entrepreneurial intentions and subjective norms was different in Sri Lanka among state university undergraduates and that this hypothesis was not supported. The findings of this research are further supported by a study that revealed a weak relationship between subjective norms and entrepreneurial Intention conducted by Sousa et al., (2018), by collecting data from 280 undergraduate law students at the University of Porto in the year 2014. Another study that supports this notion was conducted by Gonzalez-Serrano et al., (2018), who looked at 183 sport science students from a Spanish University and found that Subjective Norms were not a significant determinant of entrepreneurial Intention.
Hypothesis 3 (H3) -There is a positive relationship between State University Undergraduate students' social entrepreneurial Intention and Perceived behavioral control. Ajzen (1991), has proposed that perceived behavioral controls are one of the factors that influence entrepreneurial Intention. Jeon, (2018), in a study using Global Entrepreneurship Monitor (GEM) data, tested the influence of perceived behavioral control on entrepreneurial Intention; the result indicated that perceived behavioral control strongly influences entrepreneurial Intention. This study confirmed these findings as the research study findings supported this hypothesis.
9 Contribution of the study
Graduate unemployment has been a pressing issue in Sri Lanka over the past few decades, with no viable solution that the responsible authorities have offered (Chandrasiri, 2008). Social entrepreneurship can be proposed as a viable career option to address the unemployment issue. Therefore, developing a deep understanding of social entrepreneurship is vital in being considered as a solution to the unemployment problem. However, social entrepreneurship is in a primitive stage, as stated by Singh, (2019). The findings of this research can address the lack of understanding of the antecedent factors that affect social entrepreneurial Intention.
10 Limitations of the study and future direction
There has been a lack of previous research studies in the context of social entrepreneurship in Sri Lanka and other south Asian counties like India and Pakistan. These prior studies provide the empirical
foundations for the research question the research is investigating and help in comparing the research findings.
Due to time and resource limitations, this study was limited to five state universities in Sri Lanka. It would have been helpful if all fifteen state universities located in all parts of the county were covered.
The study adopted a non-probability sampling due to the researcher being unable to obtain the sampling frame due to the university privacy policy. Adopting a non-probability sampling can be considered a limitation due to the researcher not knowing how well the sample will represent the population and the lower generalization of research findings compared to probability sampling.
Another limitation of this study was the study population considered was Undergraduate students presently studying at state universities in Sri Lanka and did not consider undergraduate students studying at private higher educational institutions.
Some suggestions for future research will include the following:
Conducting a comprehensive study that includes all 15 state universities in Sri Lanka. This will give a comprehensive picture of the social entrepreneurial intentions among undergraduate students. In addition, a study where the state universities are clustered by region whereby geographical regional differences in social entrepreneurial intentions could be identified if they existed.
A study can be conducted to include private higher educational institutions in Sri Lanka. This will give a comprehensive understanding of the social entrepreneurial intentions among all undergraduate students. In addition, this study could also explore the differences between state and private higher educational institutions' undergraduate students' entrepreneurial intentions.
A similar study can be conducted utilizing probability sampling, which can confirm the findings of this research and or reveal new findings which can help further the knowledge in this area of study.
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