Analysing The Data Collection By Spss Software Commerce Essay

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In chapter four, we will examine and analysis the data collected by using the SPSS software. We will examine the independent variables such as social network, education, prior knowledge and experience, Government regulations, Opportunity identification and availability of resources as the involvement of undergraduates in entrepreneurship and e-entrepreneurship. A total of 250 respondents had answered the questionnaires and it will be the primary data of this research.

There are five sections in this chapter. We will do the descriptive analysis on the demographic or background of the respondents. Next, we will compute the reliability test of the variables and following with the Signification of the variables which will be tested under coefficient by using Multiple Regression analysis and Pearson Correlation analysis will be presented The last section will discuss the finding of the data analysis.

Result

Descriptive test, Mean, Reliability, Coefficient and Pearson Correlation analysis were conducted to determine the relationship between five independents variables with the dependent variable. The results computed will show the relationship between hypothesis and the involvement of the undergraduates in entrepreneurship and e-entrepreneurship.

Descriptive Analysis

The Descriptive Analysis is to calculate the frequencies, study the mean scores, and also the ranking results. In this section, descriptive analysis will conduct on the primary data which is the questionnaires collected by the respondents to give a brief overview. The analyses include gender, age, nationality, ethnicity, educational level; own a business and preferences to start up a business. Bar charts and pie charts are used to have a better and clearer understanding to the analysis.

4.2.1 Gender

Attributes

Demographic Distribution

Frequency

Percentage (%)

Gender:

Male

Female

Total

127

123

250

50.8

49.2

100.0

Table1: Distribution of Gender

Figure 3: Distribution of Gender

A total of 250 questionnaires are distributed to all the respondents in MMU Malacca campus. The frequency of the male take part in this survey is 127 people and female is 123 people. The percentage of male and female take part in this survey is 50.8% and 49.2%. The different among male and female in this survey is just 1.6% where male respondents are higher than female respondents for 4 people.

4.2.2 Age

Attributes

Demographic Distribution

Frequency

Percentage (%)

Age:

Below 20

20-22

23-25

26-27

61

78

110

1

24.4

31.2

44.0

0.4

Table 2: Distribution of Age

Figure 4: Distribution of the Age Group

According to the pie chart, the highest percentage of respondents that conduct this survey is from the range of 23-25 years old which 44 per cent are whereas the lowest percentage of respondents falls to the age group of 26 years old and above. There are 24% of respondents are from the age group of below 20 years old and 31% of respondents from the range of 20-22 years old. The reason why the lowest percentage of the age group of 26 years old and above is the respondents are undergraduates' students who currently study in MMU Malacca and normally undergraduates are between 18- 25 years old.

4.2.3 Nationality

Attributes

Demographic Distribution

Frequency

Percentage (%)

Nationality:

Malaysian

Non-Malaysian

225

25

90

10

Table 2: Distribution of Nationality

Figure 4: Distribution of the Nationality

The chart above shows the nationality of the respondents. There are 225 respondents are Malaysians and 25 respondents are non-Malaysians. The percentage of the Malaysians take part in this survey is 90% whereas non-Malaysians are 10%. The difference between these two groups is 80%. Non- Malaysians respondents are came from Indonesia, Iran, Brunei and other middle-east countries. All the non-Malaysians are the international students who are studying in MMU Malacca.

4.2.4 Ethnicity

Attributes

Demographic Distribution

Frequency

Percentage (%)

Ethnic Group:

Malay

Chinese

Indian

Others

63

110

52

25

25.2

44.0

20.8

10.0

Table 2: Distribution of Ethnicity

Figure 4: Distribution of the Ethnicity

The ratio composition is bias towards Chinese, with a percentage of 44%. Malay has 25% takes part in this survey and follow by Indian, with a percentage of 21%. The remaining 10% is the others races such as Indonesians, Iranian, and others.

4.2.5 Educational Level

Attributes

Demographic Distribution

Frequency

Percentage (%)

Educational Level:

Foundation/Diploma

Degree

Master

PhD

52

182

13

3

20.8

72.8

5.2

1.2

Table 2: Distribution of Educational level

Figure 4: Distribution of the Educational level

It is observed that among 250 respondents, 52 respondents or 20.8% is currently taking their foundation studies and Diploma certificate in MMU Malacca. 13 respondents or 5.2% is taking the Master certificate. Degree undergraduates achieve the highest percentage which is 72.8%, because most of the undergraduates are came from Degree studies. 3 respondents are from PhD and the percentage is 1.2% among others educational level.

4.2.6 You have your own business

Have own business

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

18

7.2

7.2

7.2

No

232

92.8

92.8

100.0

Total

250

100.0

100.0

Table 2: Distribution of respondents who have their own business

Figure 4: Distribution of the respondents who have their own business

Base on the research finding, among the 250 respondents, there is 93% of respondents are not having their own business. The remaining 7% or 18 respondents are having their own business. There is a big percentage of the undergraduates respondents are not having their own business, the reason of undergraduates not having own business maybe because they are busy focusing on their study and they still have not enough experience to start up a business.

4.2.7 Preferences on business style

Preferences

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Brick and mortal

121

48.4

48.4

48.4

click and mortal

129

51.6

51.6

100.0

Total

250

100.0

100.0

Table 2: Distribution of respondents who have their own business

Figure 4: Distribution of the respondents who have their own business

Base on the observation of the chart, 121 respondents are choosing brick and mortal as their preferences on business start up whereas 129 students are choosing click and mortal as their preferences on business start up. The difference between two choices is 3.2% only. The result from the histogram above shows that more respondents prefer click and mortal or e-entrepreneurship than the brick and mortal. The traditional entrepreneurship or brick and mortal are still popular among the undergraduates because they want to have a physically company and business.

Validity Test

Validity test was conducted in this research to establish the goodness of measure. My supervisor, Mdm. Rahayu is evaluated the validity of the questionnaires. Pilot study was conducted in the earlier stage of the data collecting. A set of 15 questionnaires was first distributed to the respondents to run the pilot testing. The purpose of doing pilot testing is to check the relevance of the variables and the validity of the questionnaire.

Reliability Analysis

Reliability refers to the instrument's ability to provide consistent results in repeated uses. A reliability analysis is to check the dimension of success factors generate through factor analysis. It is a measurement that shows the extent of the research and data is without bias. The purpose to conduct reliability analysis is to ensure the variables measure the exact value and error free. Cronbach's alpha reliability coefficients or interitem consistency reliability are used to test the stability and consistency of the responded items. Cronbach's alpha verifies the internal consistency or average correlation of items in the survey instrument to calculate its reliability.

A rule of thumb suggests that the acceptance Gronbach alpha value should exceed 0.7 (Hair et al., 1998) or the minimum should greater than 0.6 to ensure it is reliable (Nunally 1967). All the factors exhibit a Cronbach's alpha coefficient indicating that the questionnaire (n=250) has attained rather high level of reliability for the involvement of undergraduates in entrepreneurship and e-entrepreneurship. Using the reliability analysis, all of the independent and dependent variables will be tested to measure whether it is reliable or vice versa.

Variable

N

Cronbach's Alpha

Education, Prior Knowledge and Experience

5

0.835

Government Regulations & Incentives

5

0.888

Social Network

5

0.768

Availability of Resources

5

0.752

Opportunity Identification

5

0.809

Involvement in entrepreneurship & e-entrepreneurship

3

0.861

Table 4.10 Reliability Analysis

The Cronbach's alpha values should meet the minimum requirement value that is 0.70. The benchmark or the acceptance of the Gronbach's alpha value should exceed 0.70. The results of the reliability test in the table above overall show that there is a high reliability for each variable in this survey. The alpha's values from this analysis are all above 0.75 which achieve the minimum requirement value of 0.70. According to the analysis, Government regulations and incentives achieve the highest alpha's value of 0.888, the second highest alpha's value follow by the involvement in entrepreneurship and entrepreneurship score 0.861. Education, prior knowledge and experience have an alpha of 0.835, Opportunity identification has an alpha of 0.809 and Social network has an alpha of 0.768. The lowest alpha's value is the availability of resources that is 0.752. The reliability test on all the variables are reliable and enable to continue further analysis.

Mean

Variables:

Mean

Standard Deviation

Education, prior experience and knowledge

3.93

0.584

Government Regulations and Incentives

4.03

0.652

Social Network

4.04

0.457

Availability of resources

3.97

0.422

Opportunity identification

4.00

0.508

Involvement in entrepreneurship and e-entrepreneurship

3.83

0.713

Table 4.10 Mean Analysis

The table above shows the analysis of mean and standard deviation of all variables. Social network scores the highest mean among the variables that is 4.04, whereas the lowest mean among the variables is involvement in entrepreneurship and e-entrepreneurship has 3.83. The variable of availability of resources is the highest standard deviation which is 0.422 and in the opposite, the lowest standard deviation score is involvement of entrepreneurship and e-entrepreneurship which is 0.713.

Correlation

Pearson correlation is suitable for interval and ration scaled variables Spearman Rank or the Kendall's Tau coefficients are appropriate when variables are measures on interval scale. The correlation test was used to test the hypothesis whether there are any relationship between the independent variable and dependent variable. Pearson correlation also observes the dependent variable affects the independent variables in their relationship.

Correlation test will be conducted in this survey to determine the relationship between the five independent variables include social network, availability of resources, opportunity identification, government regulations and incentives and education, prior knowledge and experience with the dependent variable which is the involvement of the entrepreneurship and e-entrepreneurship.

Education, prior experience and knowledge correlation test

Correlations

Education, prior experience and knowledge Mean

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Education, prior knowledge and experience

Pearson Correlation

1

.463(**)

Sig. (2-tailed)

.000

N

250

250

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Pearson Correlation

.463(**)

1

Sig. (2-tailed)

.000

N

250

250

**. Correlation is significant at the 0.01 level (2-tailed).

The correlation test conducted on the responses from the respondents answers. From the Pearson Correlation analysis above, the result of p-value is 0.00 which is lower than 0.05 and r-value is 0.463. The result shows that the independent variable of education, prior experience and knowledge has a significant correlation with the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

These outcomes are consistent with previous study of Reynold et al. (1999) has concluded that the investment of the country on their tertiary education is positively impact on the rate of new business is formed. The knowledge is also playing an important role in cultivating the Entrepreneurship and E-entrepreneurship. Braunerhjelm & Lundblad (2007) pointed that knowledge is an externally factors for entrepreneurship.

Government Regulations and Incentives correlation test

Correlations

Government regulations and incentives

Mean

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Government regulations and incentives

Pearson Correlation

1

.666(**)

Sig. (2-tailed)

.000

N

250

250

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Pearson Correlation

.666(**)

1

Sig. (2-tailed)

.000

N

250

250

**. Correlation is significant at the 0.01 level (2-tailed).

The result of the correlation is positive and the independent variable is significant. The p-value is 0.000 which is lower than 0.05 and the correlation is 0.666. The result shows a positive relationship between the Government regulations and incentives with the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

The government regulations and incentives are essential fact for entrepreneurs to consider before they decide to venture into business. The government influence entrepreneurship directly by develop supporting policies and indirectly by build up the restriction and legislation (Storey, et al. 1999),

Social network correlation test

Correlations

Social network Mean

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Social network

Pearson Correlation

1

.283(**)

Sig. (2-tailed)

.000

N

250

250

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Pearson Correlation

.283(**)

1

Sig. (2-tailed)

.000

N

250

250

**. Correlation is significant at the 0.01 level (2-tailed).

The result of the table above shows that the social network has a positive relationship with the involvement of undergraduates in entrepreneurship and e-entrepreneurship. The correlation test of social network is significant because the p-value is 0.000 and has a positive correlation of Pearson Correlation, r-value is 0.283.

The result can conclude that the social network is significant and have a positive relation with the dependent variable. The social network is basically closely tied with the family and friends. A successful entrepreneur normally has the support from their family and friends (Granovetter, 1973). Social network will help you to know more friends and it may be useful in your future time. If he or she has a rich social network, it is an advantage for an individual to attract financial capital, recruit skilled labor, access to tacit knowledge and greater success in overcoming the obstacles if he or she has a rich social network.

Availability of Resources correlation test

Correlations

Availability of resources

Mean

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Availability of resources

Pearson Correlation

1

.579(**)

Sig. (2-tailed)

.000

N

250

250

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Pearson Correlation

.579(**)

1

Sig. (2-tailed)

.000

N

250

250

**. Correlation is significant at the 0.01 level (2-tailed).

The result for this variable is significant at (p-value = 0.000) levels (2-tailed) and availability of resources is having a significant effect on the involvement of undergraduates in entrepreneurship and e-entrepreneurship. The result shows that availability of resources has positive correlation which is 0.579.

The financial capital is essential for the start up cost while the human resource is vital in carrying out the business activities, both are the resources need to start up a business. The resources are needed and utilized to create products and services, which can make the customers and the market feel satisfaction. Enterprising people have certain personal traits, motivations, creativity and ideas as the opportunities for them to obtain resources needed to exploit in their business (Thompson, 1999).

Opportunity identification correlation test

Correlations

Opportunity identification Mean

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Opportunity identification

Pearson Correlation

1

.396(**)

Sig. (2-tailed)

.000

N

250

250

Involvement of undergraduates in entrepreneurship and e-entrepreneurship

Pearson Correlation

.396(**)

1

Sig. (2-tailed)

.000

N

250

250

**. Correlation is significant at the 0.01 level (2-tailed).

The last variable in the correlation test is opportunity identification. The Pearson Correlation analysis shows that the r-value is 0.396 and the p-value is 0.00. Given that the p-value is lower than 0.05, so it can conclude that the opportunity identification has a significant correlation with the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

The outcomes can support to the previous study of Stevenson et al. (1985), he said that it is important for a successful entrepreneur to have the ability to identify and selecting the right opportunities for a new business. ). Kirzner (1973) also discussed in the opportunity development is a continuous and proactive process which is necessary to form a business.

Regression analysis

In this section, regression analysis will be conducted to address the results for the hypothesis which were early presented. Multiple Regression analysis is an expansion of Bivariate Regression Analysis in that more than one independent variable is used in the regression equation. Regression analysis is used when independent variables are correlated with one another and with the dependent variable which is the involvement of undergraduates in entrepreneurship and e-entrepreneurship. The independent variables in this test are social network, availability of resources, opportunity identification, education, prior experience and knowledge and government regulations and incentives.

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.967(a)

.935

.934

.187

Table 2: Model Summary

a. Predictors: (Constant), Education, prior knowledge and experience, social network, government regulations and incentives, availability of resources, opportunity identification.

Base on the table above, the result of the multiple regression analysis indicate that the coefficient of determination (R square) is 0.967, also is 96.7 percent of the variation in the involvement of the undergraduates in entrepreneurship and e-entrepreneurship was explained by the independent variables (education, prior knowledge and experience, government regulations and incentives, social network, availability of resources and opportunity identification). From the table, the adjusted R square is 93.4 percent and the multiple linear regression tests shows 96.7 percent. Meanwhile, the standard error of estimate is 0.187.

ANOVA (b)

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

68.975

5

13.795

58.517

.000(a)

Residual

57.521

244

.236

Total

126.496

249

Table 2: ANOVA Table

Predictors: (Constant), Education, prior knowledge and experience, government regulations and incentives, social network, availability of resources, opportunity identification

Dependent variable: Involvement of undergraduates in entrepreneurship and e-entrepreneurship

The ANOVA test shows the test between independent variables with the dependent variable. From the table above, the p-value is 0.000 means the independent variables can significantly affect to the involvement of undergraduates in entrepreneurship and e-entrepreneurship

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

-.400

.362

-1.104

.271

2

Education, prior knowledge and experience

.072

.088

.059

.938

.349

3

Government regulations and incentives

.579

.061

.529

9.409

.000

4

Social network

-.137

.078

-.088

-1.761

.079

5

Availability of resources

.584

.089

.346

6.550

.000

6

Opportunity identification

-.037

.083

-.026

-.444

.658

Table 2: Regression table

Dependent Variable: Involvement of undergraduates in entrepreneurship and e-entrepreneurship

From the table above, we can see the availability of resources achieve the highest value in Beta level among all the variables with (and the significant level of 0.000. So, we can conclude that the Hypothesis 4 is accepted and the availability of resources has a significant relationship in involvement of undergraduates in entrepreneurship and e-entrepreneurship. Next, we also observed that the government regulations and incentives are also at the significant level of 0.000, so we also can conclude that the Hypothesis 2 is accepted. However, the other three hypotheses which are the social network, opportunity identification and education, prior knowledge and experience had to reject because their significant level is more than 0.05.

As a conclusion, even though all the independent variables are significant in Pearson Correlation analysis, but there is only availability of resources and government regulations and incentives are accepted in this Regression analysis and they are the determinants of the involvement of undergraduates in entrepreneurship and e-entrepreneurship. Others independent variables such as social network, opportunity identification and education, prior knowledge and experience are not significant in this regression analysis.

4.6 Discussion of study

Hypotheses

Results

H1:

Education, Prior knowledge and experience have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H2:

Government regulations and incentives have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H3:

Social network has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H4:

Availability of resources has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H5:

Opportunity identification has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

Table 2: Summary of correlation analysis

The table above shows that all hypotheses are found significant between the independent variables and the dependent variable. All hypotheses are accepted as all their correlation analyses are significant at 0.000 which is less than 0.05. From the Pearson correlation analysis, even though all the independent variables are having significant relationship to the dependent variable, we can observe that the most important determinant that influences the involvement of undergraduates in entrepreneurship and e-entrepreneurship is the government regulations and incentives. The least influence among the variables is the social network.

Hypotheses

Results

H1:

Education, Prior knowledge and experience have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Not Accepted

H2:

Government regulations and incentives have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H3:

Social network has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Not Accepted

H4:

Availability of resources has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Accepted

H5:

Opportunity identification has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Not Accepted

Table 2: Summary of Regression analysis

The above table is the summary of the regression analysis on all variables. We can see the hypothesis 2 and hypothesis 4 are having a significant relationship on the involvement of undergraduates in entrepreneurship and e-entrepreneurship as their significant value is 0.000 which is lower than 0.05. Other hypotheses are not accepted because the variables are not having significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

The first hypothesis of Education, Prior knowledge and experience has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship is not accepted. There are quite a number of successful entrepreneurs are not completed their secondary or tertiary education before they venture their business. There are arguments about "is the college necessary for entrepreneurs?", while it's a fact that a college degree does not guarantee success and do not guarantee you to be a successful entrepreneur. There are many entrepreneurs without a college or university degree certification but they are very successful and achieve what they want in their business.

The examples of entrepreneurs who succeeded without a college degree are: Charles Culpeper, owner and CEO of Coca-Cola, he dropped out of high school; Dustin Moskovitz, co-founder of Facebook, dropped out of Harvard; Tan Sri Lim Goh Tong who is the founder of Genting Group is also not graduated from tertiary education. Those entrepreneurs also do not have the prior knowledge and experience before they start up their business because their business is the pioneer in the related field of market. Entrepreneurship is emphasis creativity, innovative and dare to face the challenge.

The second hypothesis is accepted and government regulations and incentives are significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship. The establishment of restriction and legislation by the government can influence the level of involving to entrepreneurship (De Koning and Snijders, 1992). The Malaysian government has established all kinds of incentives to the company. There is financial assistance such as low interest loans for young entrepreneurs, guarantee scheme, tax incentives, advisory services and many other incentives (SMEINFO, 2009), due to all the incentives given by the government, young undergraduates will take consideration to involve in entrepreneurship and e-entrepreneurship.

Social network is not significant in the relationship to the dependent variable. Erich et al. (2009) discussed that it is a complex process for students make a decision on their future occupational. There are many literatures on entrepreneurial intent concentrate on personal related perspective but less discussed for the external circumstances that might influence students' career choice to start up a business, including the social network factor. Social network factor often neglected by the researchers to identify the student's intention to start up so do the student themselves, maybe they think that the social network is less important and not that related to their business start up.

The availability of resources is significant impact to the involvement of undergraduates in entrepreneurship and e-entrepreneurship as the hypothesis 4 is accepted in the regression analysis. The resources are needed and utilized to create products and services, which can make the customers and the markets, feel satisfaction (Gibb, 1998). Rinalia (2009) discussed young adults become early adopters and adapters of the technologies, skills valued for innovation economic growth is because they are given early access to information and communication technologies (ICT). The availability of resources in ICT is motivated to link the use of the technologies to development goals including to involve in e-entrepreneurship.

The last hypothesis is not accepted in the regression analysis. It is important for a successful entrepreneur to have the ability to identify and selecting the right opportunities for new business (Stevenson et al., 1985), but opportunity identification is also the hardest or most difficult part for entrepreneurs. The respondent may feel that the other factors are more important than the opportunity identification.

CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Introduction

The primary objective of this study is to find out the determinants of the factors that motivate the undergraduates involve in entrepreneurship and e-entrepreneurship. Previous chapters had discussed the findings from the data collection. This chapter will present the recommendation, limitation, suggestions for future studies and conclusion.

Chapter five begins with the explanation about the summary of whole study to verify whether the objectives are achieved. Second part is the recommendations about the survey in order to foster more young entrepreneurs. Next section will be the limitation part and also the suggestion for the future studies. The last part of chapter five is the conclusion of this study.

Section 5.3

Recommendation

Section 5.2

Summary of the study

Section 5.1

Introduction

Section 5.6

Conclusion

Section 5.5

Suggestion for future research

Section 5.4

Limitation of the study

5.2 Summary of the study

In this summary part, researcher will present the summary for the whole report from chapter 1 to chapter 5. In the earlier chapter one, this research explained the entrepreneurship among the undergraduates and also the e-entrepreneurship. The problem statement had been defined and set the two objectives. The first objective is to identify the preferences of the undergraduates toward entrepreneurship and e-entrepreneurship. The second objective and also the main objective is to determine the determinants of undergraduates involving in entrepreneurship and e-entrepreneurship. The last part in chapter one is to explain the significant, the scope and the organization of the study.

Chapter two is all about the literature review of the study. The research had to read as many journals or articles which were related to this study. The literature review is discussing about the variables that determine the involvement of the undergraduates in entrepreneurship and e-entrepreneurship. There are five independent variables being found from the literature review, which are the education, prior knowledge and experience, government regulations and incentives, social network, availability of resources and opportunity identification.

In chapter three, the research methodology was being discussed. All the variables were designed into the research framework. The next part was developed the hypothesis of the study. There were five hypotheses being developed:

Hypotheses:

H1:

Education, Prior knowledge and experience have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

H2:

Government regulations and incentives have a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

H3:

Social network has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

H4:

Availability of resources has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

H5:

Opportunity identification has a significant impact on the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

Chapter four is about the analysis of the data collected by using the SPSS software. We will examine the independent variables such as social network, education, prior knowledge and experience, Government regulations, Opportunity identification and availability of resources as the involvement of undergraduates in entrepreneurship and e-entrepreneurship. A total of 250 respondents had answered the questionnaires and it will be the primary data of this research.

The last part of this study is the conclusion and recommendation part. In this chapter, the research will summarize all the output from this study and give recommendations. The limitation of the study and suggestions for future research were also been discussed.

5.3 Recommendations

The findings of the study hold significant practical recommendations for the university, as well as the government. All the variables examined in the study are significant to affect the involvement of undergraduates in entrepreneurship and e-entrepreneurship. Thus, this study can provide extra information to the government to satisfy the quench of the young entrepreneurs. The study can help the government to look into what are the determinants to determine undergraduates involve in entrepreneurship and e-entrepreneurship. The government should refer to the findings of this study to foster more and more young entrepreneurs to boost up the economic growth. Several determinants are well presented in this study.

The most reliable or significant variable in this study is the government regulations and incentives. The policies of the government to help youngsters to build up their own business are relatively important to determine the involvement of undergraduates in entrepreneurship and e-entrepreneurship. For instances, government incentives encourage the youngster to start up business and will help to increase the number of young entrepreneurs. Government should provide more incentives to help the young entrepreneurs such as providing financial assistance such as low interest loans for young entrepreneurs, guarantee scheme, tax incentives, advisory services and many other incentives.

In promoting entrepreneurship and e-entrepreneurship, the availability of resources is also important. The undergraduates will consider starting up their business if the resources are availability. The resources need to start up a business include capital, machine, human resources support, ICT, technology and others. The availability of resources is relatively important because without the resources, people are unable to continue their business set up. Government can help to promote e-entrepreneurship by providing high speed broadband, involve the youngster in the multimedia corridor and also giving advisory for those who want to start up their business.

5.4 Limitation of study

Limitation of research refers to the difficulties encountered when we are conducting this research. The limitation can be the internally difficulties and externally difficulties. There is no perfection in any study or research so do in this research. There are some new insights and views are observed base on the results analysis. This study has several limitations.

The first limitation is time consuming, the sample size of my study is facing a quite large (n=250) amount of respondent so I need much time in data collection process. Second, the limitation of the study is lack of generalization because the sample study is only randomly choose in MMU Malacca state instead the study is based on the involvement of all undergraduates in Malaysia. The lack of generalization may caused the result cannot be presented well in analysis part.

Third, the difficulties occurred on some of the respondents are not filling up the questionnaires seriously, but they are just simply fill in the answer. The data may be not reliable and it can cause bias in the response of the survey if the respondents do not answer properly. The fourth limitation is the objective of this study is the determinants to the involvement of undergraduates in entrepreneurship and e-entrepreneurship, the determinants will be change from time to time or will become less important according to time. Thus, future research is required to do on this topic so that it can comply with the changes in the determinants of the undergraduates.

Lastly, the utilization of the statistical tool is needed to enhance the reliability of this study. Researches with less knowledge on Statistical Program for Social Science (SPSS) cannot conduct this study well. So researchers should utilize the SPSS properly to analysis the data and interpret it.

5.5 Suggestion for future research

This research analyzes the preference of undergraduate and the determinants to the involvement of undergraduates in entrepreneurship and e-entrepreneurship. From the previous part, we can see that there are a few limitations in this study so the future research should need to address the measurement issue on the preferences of undergraduates in entrepreneurship and also to closely investigate the various determinants that influence the involvement of undergraduates in entrepreneurship and e-entrepreneurship.

There is still quite a lot of work needs to be done to identify the preferences of the undergraduates toward entrepreneurship and e-entrepreneurship. The sample size of 250 respondents are not enough to identify and analysis to determine the preferences of undergraduates toward entrepreneurship and e-entrepreneurship. Future researchers should improve their study by extending the sample size and should select the sample at least from the other local and private university (IPTA and IPTS) to carry out the study as different respondents from different universities may have different preferences toward entrepreneurship and e-entrepreneurship.

5.6 Conclusion

The study provides critical preliminary information on the preferences and the involvement of undergraduates toward entrepreneurship and e-entrepreneurship. The study is important to nurture more young entrepreneurs in Malaysia in order to achieve the nation's interest in developing a successful knowledge-based economy. There is a need to identify the determinants to determine undergraduates to the involvement in entrepreneurship and e-entrepreneurship. Government and the education institutions should look into the determinants and proceed to foster more young entrepreneurs in Malaysia.

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