This section addresses findings of the study, their interpretations and results extracted from the study. It covers all the objectives set in the study and all the questions that made researchers investigate and conduct this study.

Table 4.1: Demographical Features of respondents


F %

Gender Male 71 56.8 125 100

Female 53 42.4 Age less than 20 1 .8 125 100

21-23 28 22.4 23-25 64 51.2 26 and above 31 24.8 Degree Bachelors 65 52.8 125 100

Masters 59 47.2 Semester 8th (Bachelors) 95 75 125 100

4th (Masters) 30 25 Specialization EE (Electrical Engineering) 43 34.4 125 100

ME (Mechanical Engineering) 44 34.6 CE (Chemical Engineering) 39 31.2 Entrepreneur in Family Yes 26 20.8 125 100

No 99 79.2 Personal Entrepreneurial Experience Yes 4 3.2 125 100

No 121 96.8 Entrepreneurial Course Yes 0 0 125 100

No 125 100 Table 4.1 represents the data on the entrepreneurial intentions of the technical graduates from electrical, chemical and mechanical engineering of Lahore.

According to the data in the table 4.1, 56.8% of the respondents were male and 42.4% are female. When I distributed the population by age, then majority of the respondents were in between 20-26 and above years in which 23-25 represent the majority of the students and represent 51.2%. The majority of the respondents are part of bachelors programs 52.8% and 47.2% were belongs to masters programs. If we distribute the students according to the semester than 75% belongs to bachelors program 8th semester and 25% belongs to Masters and 4th semester. The respondents from the Electrical engineering are 34.4%, 34.6% belongs to mechanical engineering and 31.2% belongs to chemical engineering. Only 20.8% students claim that they have entrepreneurs in family whereas 79.2% said no to this requirement. Only 3.2% students have personal entrepreneurial experience and the left have no entrepreneurial experience yet. The response to the question about entrepreneurial course is negative from all students.

Table 4.2 : Descriptive Statistics

Descriptive Statistics

N Mean Std. Deviation

Behavioral Factors 125 3.5947 .26550

Structural and Financial Factors 125 2.8160 .79954

Economic Factors 125 2.3093 .98572

Cultural Factors 125 3.1080 1.47982

Entrepreneurial Intentions 125 3.1580 1.55073

Self Efficacy 125 3.3467 2.11119

Locus of Control 125 4.0112 2.64859

Risk Taking 125 3.0740 3.12557

Valid N (listwise) 125 Descriptive statistics are given in the table 4.2; it consists of the mean and standard deviation of all the factors that affect the entrepreneurial intentions of the students. The instrument used for the data collection comprises five point likert scale from strongly disagree to strongly agreed. The mean score of behavioral factors is 3.5947 and mean score of locus of control is 4.0112 that are near to agree. Structural and financial factors and cultural factors are near to neutral as their mean score are 2.8160 and 3.1080. The economic factors have the mean score is 2.3093 that is near to disagree. Entrepreneurial intentions, Self efficacy and risk taking are also neutral 3.1580, 3.3467, 3.0740.

In crux we can say that most of the respondents are neutral to factors such as entrepreneurial intentions, self efficacy, risk taking, cultural factors and structural and financial factors.

Table 4.3: Linear regression test

Variables R R SquareB P

Behavioral Factors 0.126 0.016 0.126 0.162

Structural and Financial factors 0.417 0.174 0.417 0.061

Economic Factors 0.946 0.895 0.946 0.017

Cultural Factors 0.544 0.295 0.544 0.000

Independent variables = behavioral factors, structural and financial factors, economic factors,

Cultural factors

Dependant variable = Entrepreneurial intentions

The table 4.3 indicates those factors which helps the students to show their entrepreneurial intentions. There is a highly significant relationship between behavioral factors entrepreneurial intentions (r= 0.126, p< 0.01) the relationship is strong and it has positive impact on the entrepreneurial intentions. This finding verifies our hypothesis H1 that “Behavioral factors positively influence the entrepreneurial intentions”.

Table 4.3 also indicates that there is a negative relationship between structural and financial factors and entrepreneurial intentions where (r= 0.417, p>0.01) here the relationship is moderately weak and has negative impact on the intentions. This verifies our hypothesis H4 that “structural support meaningfully influences entrepreneurial preference of students.”

Table 4.3 showed that there is a positive and significance relationship between recognition and motivation of employees that is (r= 0.429, p<0.01) the results shows moderately significant but positive relationship which certify our hypothesis H2 that “recognition is a good motivator for the employees”.

Table 4.3 also showed that there is a positive and highly significant relationship between compensation and motivation of employees that is (r= 0.617, p<0.01). This result showed strong, significant and positive relationship which certify our hypothesis H1 that “Appropriate compensation plans motivate employees” .