Analysis of Barriers on Student Spin-Offs Intention.
Student spin-off (SSO) has captured the attention of researchers and policymakers in the last few years due to its vast contributions to self-employment generation, job opportunities, innovation and contribution to local economic growth (Corsi and Prencipe, 2016; Leire et al., 2016; Manbachi et al., 2018). Bailetti (2011) added the importance of SSOs for several reasons such as: (i) SSOs offer a concrete proof the university is relevant, up-to-date, and competitive; (ii) SSOs substantially contribute to the development of local region where the university is located; (iii) SSOs assist to commercialize undeveloped knowledge within the university; (iv) SSOs facilitate universities accomplish their core missions (research, teaching, and community development); and (v) The return on government investment particularly in university research and development can be increased with the establishment of SSOs. Krisztian (2007) has defined SSO as a company that founded by a student who started the company while still affiliated with the university.
The study of SSO can be easily found in developed countries than developing countries (Hayter et al., 2016). For instance, the development of entrepreneurship in both theory and activity is becoming more important particularly to university students in Malaysia. To support the growth need of spin-offs formation, Malaysian government and universities have facilitated various programs and initiatives for university students to become entrepreneurs. For instance, in April 2015, the Malaysian Ministry of Higher Education (MoHE) launched the Malaysia Education Blueprint 2015-2025 (Higher Education). The Blueprint outlined 10 Shifts that will encourage the continuation of excellence in the higher education system. Shift-1 indicated that Malaysian higher educational institutions (HEIs) should produce holistic, entrepreneurial, and balanced graduates in the future. Despite these, the percentage of graduates becoming entrepreneurs are less than 7 percent in 2016 (Malaysia Ministry of Higher Education, 2017).
Many previous scholars have empirically postulated the drivers and barriers of entrepreneurial intention (e.g. Chuah et al., 2016; Al Mamun et al., 2017). Several past studies (Keat and Ahmad, 2012; Mohamad, 2015; Thavaraj and Varghese, 2015; Chuah et al., 2016; Zahari and Azizan, 2018) claimed that the awareness level pertaining to perception of barriers to become student entrepreneur is still very low. Due to this, this study aimed to examine the effect of perception of barriers on student spin-offs intention. Also, the current paper targets to investigate the differences between perception of barriers and demographic variables. The identification of perception of barriers among founders of SSO can provide adequate understanding about negative determinants of student spin-offs intention and can help universities and policymakers to nurture more SSO establish at Malaysian universities.
To study the effects of perception of barriers on student-spin-offs intention, the current paper refers to the Theory of Planned Behavior (TPB) which was developed by Ajzen (1988). Even though the various models are used to explain entrepreneurship intention, the TPB is considered one of the best primary theory-driven models for describing entrepreneurial intention (Ajzen, 1991). This theory has widely adopted among entrepreneurship scholars like Karimi et al., (2015), Ali, Ajmal and Iqbal (2016), Al Mamun et al., (2017) and Arranz, Arroyabe and Fdez. de Arroyabe, (2018) to determine the effects of barriers on entrepreneurial intention. It is very important to examine the barriers that negatively influence student-spin-offs intention because universities and policymakers can implement the right strategies to mitigate these. Hence, the percentage of graduates becoming entrepreneurs can be increased in the future.
Moy et al., (2001) advocated such barriers like high labour costs, high interest rates, strict government regulations, lack of managerial experience, lack of technical knowledge and excessive risk are faced by university students when starting and sustaining new ventures. Apart from that, Pruett et al., (2009) and Giacomin et al., (2011) grouped the perceptions of barriers in the forms of lack of support structures, knowledge, operating risks, start-up risks and lack of social support are well associated with student entrepreneurs. Moreover, previous scholars (Iakovleva et al. 2014; Mohamad 2015; Ali et al., 2016) classified the barriers under three headings: (i) student attributes (e.g. fear of failure, lack of skills and lack of self-efficacy); (ii) university policies and services (e.g. lack of capital 'seed capital', lack of support, and lack of entrepreneurship education) and (iii) environmental factors (e.g. economic, political climate, tax law, and regional barriers or scale of competition). More importantly previous works of (Che Ku Yusof et al., 2014; Karimi et al., 2015; Ali et al., 2016; Chuah et al., 2016; Pruett and Sesen, 2017; Arranz et al., 2018) have found perception of barriers has a negative influence on student spin-offs intention. These considerations led to the following hypothesis:
H1: There will be a significant negative relationship between perception of barriers and student spin-offs intention.
The study of perception of barriers is not only limited to examine the negative relationship with student spin-offs intention but also has extended to measure the different between perception of barriers and demographics. Several past studies have measured the differences between construct and individual item of perception of barriers with demographic characteristics such gender (e.g. Pruett et al., 2009; Roudaki, 2010; Giacomin et al., 2011; Shinar, Giacomin and Janssen, 2012; Keat and Ahmad, 2012; Amentie and Negash, 2014; Pruett and Sesen, 2017), age (e.g. Pruett et al., 2009; Giacomin et al., 2011; Samuel, Ernest and Awuah, 2013; Pruett and Sesen, 2017), ethnicity (e.g. Pruett et al., 2009; Giacomin et al., 2011; Shinar et al., 2012; Pruett and Sesen, 2017), level of study (e.g. Pruett et al., 2009; Giacomin et al., 2011; Pruett and Sesen, 2017), year of study (e.g. Saleh, 2014) and type of university (e.g. Saleh, 2014). Of these, the majority of above studies have found significant difference between groups of gender, age, ethnicity, level of study, year of study and type of university with perception of barriers. Therefore, the following hypotheses are proposed:
H2: There is a significant different between perception of barriers in gender of SSO founders.
H3: There is a significant different between perception of barriers in age of SSO founders.
H4: There is a significant different between perception of barriers in ethnicity of SSO founders.
H5: There is a significant different between perception of barriers in level of study of SSO founders.
H6: There is a significant different between perception of barriers in year of study of SSO founders.
H7: There is a significant different between perception of barriers in types of university of SSO founders.
The respondents in this current study are the founders of SSO from Malaysian public HEIs. Due to personal data protection policy, only founders of SSO from eleven Malaysian public HEIs were involved in this study. The online survey questions were emailed to 750 founders of SSO and the study was able to collect 369 completed questionnaires. The cluster sampling approach was used to capture the respondents. The questionnaire used in this study was consisted of two sections. Section one is related to factors that influence student spin-offs intention and nine questions were used in Section two to explain the characteristic of respondents. Table 2 shows the detail items used in this study. In brief, eight items for perception of barriers were adapted from Pruett et al., (2009) and six items for student spin-offs intention were from Linan and Chen (2009). In addition, the first section of the questionnaire applied a 5-point Likert scale, which ranging from 1 (strongly disagree) to 5 (strongly agree). To increase the face validity of the questionnaires, the current study has complied with several procedures namely experts' opinion session, pre-tested approaches and pilot study. The feedback received from these procedures was used to refine the questionnaire. With the majority of respondents are non-English native speakers, the questionnaire was translated into local language. The data was analysed using IBM Statistical Package for Social Science (SPSS) Statistics for Windows, Version 24.0. Descriptive analysis, reliability test, regression analysis, independent-samples t-test and analysis of variance (ANOVA) are among the analyses used for this study.
Table 1 summarizes the profile of respondents. There are nine characteristics of respondents as shown in Table 1.
Table 2 posits the mean values score for perception of barriers and student spin-offs intention according to factor and individual items. Results for mean value scores for student spin-offs intention construct and individual items are greater than both perception of barriers and its individual items. Based on the mean value scores, lack of initial capital is claimed as a major barrier to establish SSO. The findings are in line with past works of Staniewski and Awruk (2015), Ali et al., (2016), Enninful, Boakye-Amponsah and Nduro (2016) and Arranz et al., (2018) who identified lack of capital as the main hurdle for entrepreneurial intentions. Then it was followed by 'having to work too many hours' and 'lack of knowledge of the business world and market' respectively. Furthermore, the results of Cronbach's Alpha are reported at .840 (perception of barriers) and .948 (student spin-offs intention) indicates a very good internal consistency (Pavot et al., 1991).
Table 3 summarizes the result of regression analysis of perception of barriers on student spin-offs intention. As shown in Table 3, the variance inflation factors (VIF) for the independent variable was highly satisfactory at 1.000. Findings show that the adjusted [R.sup.2] was at -.001 percent indicates a negative role of perception of barriers as a predictor for student spin-offs intention. Subsequently, there is a negative relationship between perception of barriers with F (1, 367) = .544, p > .05 on student spin-offs intention. Thus, Hypothesis 1 is supported.
In order to determine whether significant differences existed between the mean scores assigned to the items by male and female respondents, this current study has conducted an independent-samples t-test on the mean scores of perception of barriers (individual and factor item). Findings shown in Table 4 stated that there were no significant differences in scores for both factor and individual items of perception of barriers. For example, there was no significant different in scores for perception of barriers construct in males (M = 3.65, SD = .696) and females (M = 3.65, SD = .715); t (367) = .036, p = .971 (two-tailed).
Note: (N) Male = 151; (N) Female = 218; (*) The negative t-values mean that female has higher mean scores than male for perception of barriers construct and individual items. The criteria were based on a 5-point scale, ranging from 1= strongly disagree to 5 = strongly agree.
Table 5 displayed the mean differences between perception of barriers in age, ethnicity, level of study, year of study and types of university. To measure the mean differences of those characteristics, series of one-way between-groups analysis of variance (ANOVA) were conducted. The results indicate that there are no significant difference between perception of barriers (factor and individual item) with groups of age and level of study. With regards to four groups of ethnicity (Malay, Chinese, Indian and others), only PB1 (about entrepreneurial competence) has shown a significant different. However, the effect size is considered small because the eta squared was recorded at .031 (Cohen, 1988). Moreover, only PB3 (strong competition) and PB8 (having to work too many hours) postulated significant difference with the three types of public university in Malaysia. Despite reaching statistical significance, the actual differences in mean scores between the groups were small, where the eta squared were at .031 and .038 respectively. Finally, groups of year of study have shown significance differences with perception of barriers construct and four individual items namely PB1, PB4, PB6 and PB7. However, the effect sizes are considered small because the eta squared was recorded at .038, .025, .032, .050 and .041 respectively (Cohen, 1988). In brief, there is a significant different between construct of perception of barriers with year of study, thus Hypothesis 6 is supported. In contrast, Hypotheses H2, H3, H4, H5 and H7 are not supported because the findings unable to record any significance difference between gender, age, ethnicity, level of study and type of university with perception of barriers.
Discussion and Conclusion
Findings illustrated in Table 3 indicate a negative relationship between perception of barriers and student spin-offs intention. Hence, Hypothesis 1 is supported. The results are consistent with past studies of Pruett et al., (2009), Giacomin et al., (2011), Che Ku Yusof et al., (2014), Yusoff, Zainol and Ibrahim (2015), Pruett and Sesen (2017) and Arranz et al., (2018). For example, Pruett et al., (2009) revealed that perception of barriers negatively influenced entrepreneurial intentions. They surveyed 1058 students from three universities in the US, China and Spain. Similarly, Che Ku Yusof et al., (2014) identified four key barriers to entrepreneurial intentions among 294 business students in a public university in Malaysia. Among the barriers were: (1) capital and culture; (2) skills and education; (3) inclination factors such as fear of failure and operating risks and (4) networking. Moreover, Yusoff et al., (2015) have added eight barriers that demotivated entrepreneurship activities in Malaysian public HEIs such as students' soft skills, financing, commitment, coordination among support agencies, bureaucracy, manager support, staff and student mentality and pedagogy.
Furthermore, the findings displayed in Table 4 show that there is no significant different between groups of gender (male and female SSO founders) with perception of barriers, therefore, Hypothesis 2 is not supported. The results are in line with past works of Olofunso (2010) and Staniewski and Awruk (2015). Staniewski and Awruk (2015) explained no significant different between groups of gender among 255 students at one university in Poland with perception of barriers. Tests of ANOVA as depicted in Table 5 posit that there are no significant difference between age, ethnicity, level of study and type of university with perception of barriers. Thus, Hypotheses 3, 4, 5 and 7 were not supported. The results are similar to past studies of Olofunso (2010) and Staniewski and Awruk (2015). For instance, a study by Olufunso (2010) recorded that those demographic profiles unable to have significant difference in relation to the perception of barriers among 701 students at one university in South Africa. In addition, a group of year of study is able to show a significant different with perception of barriers (see Table 5), therefore Hypothesis 6 is supported. The results are consistent with past study of Saleh (2014) who conducted a study among university students in Iran.
To conclude, the findings revealed a negative relationship between perception of barriers on student spin-offs intention. In addition, the current study unable to record significance difference between characteristics of demographic except for year of study with perception of barriers. It is critical to examine the barriers that negatively influence student-spin-offs intention because universities and policymakers can establish the appropriate strategies to soften the stated barriers. With this, the percentage of graduates becoming entrepreneurs can be increased in the future and may lead to generate self-employment society among university students in Malaysian public higher educational institutions. The current study is conducted with few limitations. Firstly, the scope of study is focused in Malaysian public higher educational institutions; therefore replication of a similar study can be extended to Malaysian private HEIs. Secondly, the current study only concentrated with items of perception of barriers, future studies can introduce more items to perception of barriers. Finally, the future studies should engage with qualitative approach to in depth study the perception of barriers.
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Abdul Rahman Zahari (*)
College of Business Management and Accounting, Universiti Tenaga Nasional, Malaysia
Puteri Fadzline Muhamad Tamyez
Faculty of Industrial Management, Universiti Malaysia Pahang, Malaysia
Noor Azlinna Azizan
College of Business Administration, Prince Sultan University, Saudi Arabia
College of Business Management and Accounting, Universiti Tenaga Nasional, Malaysia
(*) Corresponding Author
Table 1: Profile of Respondents Measure Item Frequency (N=369) Percent Gender Male 151 40.9 Female 218 59.1 Age 20 years old and below 24 6.5 21 to 25 years old 320 86.7 26 to 30 years old 21 5.7 31 years old and above 4 1.1 Ethnicity Malay 316 85.6 Indian 18 4.9 Chinese 24 6.5 Others 11 3.0 Religion Islam 327 88.6 Buddhism 19 5.1 Christianity 10 2.7 Hinduism 13 3.6 Place of origin Rural area 174 47.2 Urban area 195 52.8 Level of study Postgraduate 51 13.8 Undergraduate 315 85.4 Others (Diploma) 3 .8 Year of study Year 1 27 7.3 Year 2 117 31.7 Year 3 116 31.4 Year 4 109 29.6 Type of public university Research universities 99 26.8 Focus universities 234 63.4 Comprehensive universities 36 9.8 Nature of business Product oriented 169 45.8 Service oriented 200 54.2 Table 2: Descriptive Analysis and Reliability Test Factors/Individual Items MV Perception of barriers (PB) [I was worried/afraid of....] 3.65 PB1 About entrepreneurial competence. 3.52 PB2 Lack of knowledge of the business world and market. 3.69 PB3 Strong competition. 3.49 PB4 Lack of initial capital. 3.93 PB5 Irregular income. 3.51 PB6 Business failure. 3.46 PB7 High operating expenses. 3.67 PB8 Having to work too many hours. 3.92 SSO intention (SI) 4.18 SI1 I am ready to do anything to be an entrepreneur. 4.02 SI2 My professional goal is to become an entrepreneur. 4.04 SI3 I will make every effort to start and run my own business. 4.18 SI4 I am determined to create a business in the future. 4.29 SI5 I have seriously thought about starting a business. 4.24 SI6 I have a firm intention to start a business some day. 4.29 Factors/Individual Items SD Perception of barriers (PB) [I was worried/afraid of....] .706 PB1 About entrepreneurial competence. .939 PB2 Lack of knowledge of the business world and market. .961 PB3 Strong competition. 1.113 PB4 Lack of initial capital. 1.029 PB5 Irregular income. 1.096 PB6 Business failure. 1.151 PB7 High operating expenses. 1.012 PB8 Having to work too many hours. .894 SSO intention (SI) .801 SI1 I am ready to do anything to be an entrepreneur. .885 SI2 My professional goal is to become an entrepreneur. .984 SI3 I will make every effort to start and run my own business. .853 SI4 I am determined to create a business in the future. .863 SI5 I have seriously thought about starting a business. .900 SI6 I have a firm intention to start a business some day. .905 Factors/Individual Items CA Perception of barriers (PB) [I was worried/afraid of....] .840 PB1 About entrepreneurial competence. PB2 Lack of knowledge of the business world and market. PB3 Strong competition. PB4 Lack of initial capital. PB5 Irregular income. PB6 Business failure. PB7 High operating expenses. PB8 Having to work too many hours. SSO intention (SI) .948 SI1 I am ready to do anything to be an entrepreneur. SI2 My professional goal is to become an entrepreneur. SI3 I will make every effort to start and run my own business. SI4 I am determined to create a business in the future. SI5 I have seriously thought about starting a business. SI6 I have a firm intention to start a business some day. Note: MV = Mean value; SD = Standard deviation; CA = Cronbach's Alpha Table 3: The Relationship of Perception of Barriers on SI Variables Beta Sig. Tolerance VIF (constant) .000 Perception of barriers -.038 1.000 1.000 Variables Adjusted [R.sup.2] F Statistics (constant) Perception of barriers -.001 .544 Table 4: Mean Differences between Perception of Barriers in Gender Factor/ Individual Items Male Female t-value 2-tail sig Perception of barriers (PB) 3.65 3.65 .036 .971 PB1 About entrepreneurial competence. 3.50 3.53 -.243 .808 PB2 Lack of knowledge of the 3.67 3.70 -.279 .781 business world and market. PB3 Strong competition. 3.50 3.49 .089 .930 PB4 Lack of initial capital. 4.01 3.88 1.157 .248 PB5 Irregular income. 3.47 3.54 -.612 .541 PB6 Business failure. 3.42 3.50 -.641 .522 PB7 High operating expenses. 3.71 3.65 .534 .594 PB8 Having to work too many hours. 3.93 3.90 .318 .751 Table 5: Mean Differences between Perception of Barriers in Age, Ethnicity, Level of Study, Year of Study and Types of University Factor/ Age Ethnicity Level of study Year of study Individual Items Sig. ES Sig. ES Sig. ES Sig. ES PB .501 - .705 - .622 - .003 .038 (*) PB1 .468 - .009 .031 (*) .121 - .026 .025 (*) PB2 .799 - .313 - .678 - .189 - PB3 .323 - .215 - .884 - .135 - PB4 .799 - .235 - .119 - .008 .032 (*) PB5 .683 - .292 - .717 - .432 - PB6 .724 - .362 - .957 - .000 .050 (*) PB7 .801 - .541 - .472 - .002 .041 (*) PB8 .225 - .926 - .795 - .560 - Factor/ Types of Individual university Items Sig. ES PB .360 - PB1 .099 - PB2 .699 - PB3 .003 .031 (*) PB4 .997 - PB5 .792 - PB6 .233 - PB7 .689 - PB8 .001 .038 (*) Note: PB = Perception of barriers; ES = Eta squared; (*) = Small effect size
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|Author:||Zahari, Abdul Rahman; Tamyez, Puteri Fadzline Muhamad; Azizan, Noor Azlinna; Esa, Elinda|
|Publication:||Global Business and Management Research: An International Journal|
|Date:||Apr 1, 2018|
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