Very Final TP

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Research Proposal

Assessing the Entrepreneurial Intentions of Business Students in Pakistan

Name:

Shaffia Mansur(1125139)

Class:

MBA-DAY 36 credit hours

Semester: Fall

[2011]

Yours Signature

Due Date:

30/12/11

Submission Date:

30/12/11

Department of Management Science

SZABIST, Islamabad


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List of Acronyms

EI: Entrepreneurial Intentions

RP: Risk Perception

RTP: Risk Taking Propensity

SME: Small Medium Enterprises

M: Motivation

SE: Self Efficacy

ES: Entrepreneurial Support

I: Intentions


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Contents

1. ....................................................................................................................................... Introduction

7

1.1. Background of Study ................................................................................................................... 8

1.2. Problem Statement ....................................................................................................................... 9

1.3. Objectives of Study...................................................................................................................... 9

1.4. )Research Questions..................................................................................................................... 9

1.5. Delimitations of the study ............................................................................................................ 9

2. Literature Review ......................................................................................................................... 10

2.1)Entrepreneurial Intentions(I) ....................................................................................................... 10

2.1)Risk-taking propensity(RTP) ...................................................................................................... 10

2.1)Risk Perception(RP) ................................................................................................................... 11

2.1)Self Efficacy(SE)........................................................................................................................ 11

2.1)Motivation (M) ........................................................................................................................... 12

2.1)Entrepreneurial Support (ES)...................................................................................................... 13

3. Theoretical Framework................................................................................................................. 14

3.1) Variables and hypothesis ........................................................................................................... 14

3.1.1) Dependant variable: ................................................................................................................ 14

3.1.2) Independent variables: ............................................................................................................ 15

3.1.3) Control variables: ................................................................................................................... 17

4. Research Methodology ................................................................................................................. 19

4.1) Type of Study ............................................................................................................................ 19

4.2) Time Horizon ............................................................................................................................ 19


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4.3) Unit of Analysis......................................................................................................................... 19

4.4) Population and sample Frame .................................................................................................... 19

4.5) Instrument Selection .................................................................................................................. 19

4.6) Proposed Data Collection Procedures......................................................................................... 21

4.7) Proposed Data Analysis Techniques........................................................................................... 21

4.7.1) Descriptive statistics ............................................................................................................... 22

4.7.2) Reliability of data .................................................................................................................. 22

4.7.3) P-P Plots ................................................................................................................................ 22

4.7.4) Measures of association ......................................................................................................... 22

4.7.5) Regression analysis ................................................................................................................ 22

4.7.6) Independent sample T-test .......................................................... Error! Bookmark not defined.

4.7.7) One-way ANOVA and post hoc tuckey .................................................................................. 22

5. Results and Discussion.................................................................................................................. 22

5.1) Descriptive statistics for Demographics ..................................................................................... 23

5.2) Descriptive Statistics for Independent Variable and Dependant Variable ................................ .... 23

5.3) Estimated Distribution Parameters; ............................................................................................ 24

5.4) Reliability Analysis ................................................................................................................... 25

5.5) Inter-Item Correlation Matrix..................................................................................................... 25

5.6) ANOVA table............................................................................................................................ 25

5.7) Regression analysis and Co-efficient table ................................................................................. 26

5.8) Regression line to Dependant variable ....................................................................................... 26

5.9) One way ANOVA and post hoc tuckey ...................................................................................... 26

5.9.1) Education ............................................................................................................................... 26

5.9.2) Household income .................................................................................................................. 27


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5.9.3) Work experience..................................................................................................................... 27

5.9.4) Father employment ................................................................................................................. 27

5.9.5) Mothers employment .............................................................................................................. 28

5.9.6) Age group............................................................................................................................... 28

5.11) Hypothesis results.................................................................................................................... 28

6) Conclusion ................................................................................................................................... 28

6.1) Recommendations ..................................................................................................................... 29

6.1.1)Model for credit Provision to student: ...................................................................................... 29

Annexure A : List of Tables and Figures ........................................................................................... 35

Annexure B: Questionnaire.................................................................... Error! Bookmark not defined.

Annexure C : References ....................................................................... Error! Bookmark not defined.


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1. Introduction

There has been a growing debate about how economies can prosper and the role of young

minds to play in it. This study is taken to study the entrepreneurial profile of Pakistani Business

students as to what stops them or encourages them from starting new venture. We want to know

that are the students job inclined or self-employment inclined. It also wants to be established that

have the educational institutes crafted the pre-requisites of entrepreneurial traits in the business

students or not.

The SMEs are a very important source of income generation in country and if the nascent

entrepreneur wants to thrive in the market he starts of by establishing some sort of an SME. In

the Pakistani landscape SMEs constitute nearly 90% of all the enterprises in Pakistan and employ

80% of the non-agricultural labor force; and their share in the annual GDP is 40%,

approximately. The present economic situation shows unemployment even for the educated at

6% according to Pakistan Labor Force Survey 2011. (www.smeda.org.pk)

Pakistan, Total early-stage Entrepreneurial Activity rate is 9.0%. The male rate (14.38%) is

4.1 times the female rate (3.43%). In terms of motivation to start-up, 5.0% of the adult

population cites opportunity-driven factors, whilst 3.6% cite necessity-driven factors. The

predominant motive for pursuing entrepreneurial activity in the country is to increase income

(38.0%) and to a much lesser degree (2.4%) acquire independence. Of nascent entrepreneurs, 75

percent find it more difficult to start a business and 80 percent report more difficult (or about the

same) to grow it, with 56 percent pointing towards fewer business opportunities, compared to a

year ago. Fear of failure rate (27.7 %) prevented business start-ups. (GEM Pakistan 2010)

Therefore it can be seen that nascent entrepreneurial activity in Pakistan is very marginal

inspite of the growing importance associated to it.


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Wilson et al (2007) argued that entrepreneurship education can also increase students interest

in entrepreneurship as a career. Souitaris et al (2007) found that entrepreneurship programs

significantly raised students subjective norms and intentions toward entrepreneurship by

inspiring them to choose entrepreneurial careers.

1.1. Background of Study

Entrepreneurship has many fruits to be reaped in terms of multiplying employment

opportunities as well as revenues in the economy. The encouragement of entrepreneurship is

essential to stimulate growth in a growth-conscious world, (Baumol, 1968, p. 71). They

accelerate economic development through generating ideas and making them into profitable

ventures so that employment opportunities and competitiveness is increased (Reynolds, 1987;

Zahra, 1999).

Students from emerging economies are more likely to envisage future careers as entrepreneurs

and are more positive towards entrepreneurship than their industrialized European counterparts

(Davey et al, 2011; Nabi and Linan, 2011). Economic and institutional frameworks tend to be

unfavourable to entrepreneurial activity in the developing world (Nabi and Linan, 2011).

The policy implications of Global Entrepreneurship Monitor (GEM, 2001) indicated that

people with limited education are less likely to participate in entrepreneurial initiatives.

Henderson and Robertson (2000) also stated . . . the future working environment will depend

on the creativity and individuality of the young.


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1.2. Problem Statement

Are the Pakistani business students having high entrepreneurial intentions or not

1.3. Objectives of Study

y To study the entrepreneurial profile of Pakistani business students.

y To know about the domains in which the academic Institutions need to improve

entrepreneurial intentions as regards the case of Pakistani business students according to their

entrepreneurship profile.

1.4. )Research Questions

y Do Pakistani business students have high entrepreneurial intentions?

y Are Pakistani business students motivated for venture creation?

y Is Risk a substantive barrier for Pakistani business students in having entrepreneurial

intentions?

y Do Pakistani business students have capability to combat risk?

y Are entrepreneurial support institutions and departments helpful in increasing

entrepreneurial intentions?

y Do Pakistani business students have the self autonomy required to carry out business.

y What role has demographics to play in entrepreneurial intentions?

1.5. Delimitations of the study

The sample is taken from Islamabad only to represent entire population due to the lack of

resources.


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2. Literature Review

2.1)Entrepreneurial Intentions(I)

Theory of Planned Behavior provides a general framework to analyse the entrepreneurial

intention of a person (Ajzen and Fishbein, 1980; Ajzen, 1987, 1991). According to Bird (1988),

intentionality can be defined as a state of mind directing a persons attention, experience and

action towards a specific goal or a path to achieve something. Therefore, entrepreneurial action

can be also classified as an intentional behavior (Bird, 1988; Shapero, 1982) or intention is a

predictor of planned entrepreneurial behavior (Krueger, 1993). Shapero (1982) indicated that the

entrepreneurial intention stems from the perception of feasibility and desirability of a person and

this path is affected by the cultural and social context.

2.1)Risk-taking propensity(RTP)

Following the lead of Atkinson, risk-taking propensity has been defined in the

entrepreneurship literature as the willingness to take moderate risks (Begley, 1995). Atkinson

(1957) argued that individuals who have higher achievement motivation should prefer activities

of intermediate risk because these types of activities will provide a challenge, yet appear to be

attainable. On the other hand, individuals who score high on the motive to avoid failure will

avoid intermediate risks. Instead, they will prefer easy and safe under- takings. Risk propensity is

a key construct used in Sitkin and Pablos model (1992) to characterize the current tendency of a

decision-maker to take or avoid risks. In contrast to previous definitions of this construct, risk

propensity is conceptualized as an individual trait that can be changed over time, rather than as a

stable and constant dispositional characteristic (Sitkin and Pablo, 1992).


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2.1)Risk Perception(RP)

Variation across people in their perceptions of risk and opportunity influence entrepreneurial

decisions (Shane & Venkataraman, 2000). People vary in how they view the risk of expending

resources before knowing the distribution of outcomes (Palich & Bagby, 1995). Similarly, the

probability of success at the entrepreneurial process is low, and those people who are willing to

proceed despite these odds might be more optimistic or higher in self-efficacy than people

deterred by these odds.

Opportunities are aspects of the environment that represent potentialities for profit making.

We follow Shane and Venkataraman (2000, p. 220) to define entrepreneurial opportunities as

situations in which new goods, services, raw materials, and organizing methods can be

introduced and sold at greater than the cost of their production. Since potentialities are not yet

actual, measuring them objectively and prospectively at the level of an individual entrepreneur

poses daunting challenges.

The impact of attitude towards self-employment might be linked to risk-taking propensity and

two contextual factors perceived barriers and perceived support ( Luthje and Franke 2003).

2.1)Self Efficacy(SE)

Self-efficacy is the belief in ones ability to muster and implement the necessary personal

resources, skills, and competencies to attain a certain level of achievement on a given task

(Bandura, 1997). In other words, self-efficacy can be seen as task-specific self-confidence. Self-

efficacy for a specific task has been shown to be a robust predictor of an individuals


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performance in that task and helps to explain why people of equal ability can perform differently.

An individual with high self-efficacy for a given task will exert more effort for a greater length

of time, persist through set backs, set and accept higher goals, and develop better plans and

strategies for the task. A person with high self-efficacy will also take negative feedback in a

more positive manner and use that feedback to improve their performance. These attributes of

self-efficacy may be important to the entrepreneurial process because these situations are often

ambiguous ones in which effort, persistence, and planning are important.

2.1)Motivation (M)

Researchers have shown that people are willing to look for opportunities for projects

depending on things such as the opportunity cost (Amit, Meuller, and Cockburn, 1995), stocks of

financial capital (Evans and Leighton, 1989), social relations of the investors (Aldrich and

Zimme, 1986 ), and professional experience (Carroll & Mosakowski, 1987; Cooper, Wu, and

Dunkleberg, 1989).

Motivation refers to the willingness to put forth effort both the effort of thinking and the effort

involved in bringing ones ideas into reality. The motivation can be extrinsic or intrinsic. The

process involves opportunity identification. These opportunities can be realized through

innovation and creativity. When entrepreneurs pursue opportunity, they must take action to make

it real. The four aspects of motivation that determine the realization of ideas and converting them

to efforts are: ambition, goals, energy and stamina, and persistence. Ambition influences the

degree to which entrepreneurs seek to create something great, important, and significant when


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they pursue opportunities. The nature of the entrepreneurial ambition may include making

money or the desire to create something new, from conception to actuality.

Ambition translates into setting high goals for oneself and others (see the earlier Goal setting

section). It is well known that high goals lead to better performance results than moderate or low

goals (Locke & Latham, 1990). To achieve high goals requires enormous energy and stamina.

When goal-directed energy is sustained over time, it is called persistence or tenacity.

2.1)Entrepreneurial Support (ES)

Many universities now are working in close consortium with corporate for the development of

small business development centers (Rich 2009).These centers have directors that advise

students and share their research costs for setting up a new venture. The student employees act as

research agents for companies giving themselves experience with gainful employment and

adding to university pool of funds. This could be included in the CSR and the research could also

help the companies stay in touch with recent research. Universities continue to look for private

sources of funding as public funds decline. Universities have become more entrepreneurial, as

shown in the research of Clark (1998) and Sporn (1999). Clark (1998) argues for a more diverse

funding base as one of his five elements of innovation. Sporn (1999) suggests that institutions

have more autonomy and are better able to adapt in changing environments by having a

discretional funding base.

Such activities are created out of necessity due to the restriction of public funding causing a

funding crisis leading to an increase in entrepreneurial activities (Yokoyama, 2006).


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Many individual entrepreneurs approach the Small Business Development Centre with an idea

and their consultants analyze whether the person has a decent business plan and generally do not

analyze the marketability of the venture.

3. Theoretical Framework

A common theoretical framework for explaining Pakistani business students entrepreneurial

intentions is identified as follows.

3.1) Variables and hypothesis

The following dependant and independent variables are identified in light of the literature

review.

3.1.1) Dependant variable:

Dependant variable is seen as the end product of the factors affecting entrepreneurial set-up.

EntrepreneurialIntentions

Motivation

Risk Perception

EntrepreneurialSupport

Risk TakingPropensity

SelfEfficacy


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3.1.1.1) Entrepreneurial intentions

The dependant variable identified is entrepreneurial intentions and it is affected by five other

independent variables namely: risk taking propensity; risk perception; self-efficacy; motivation

and entrepreneurial support.

3.1.2) Independent variables:

Independent variables are identified from literature and have a direct affect on dependant

variable.

3.1.2.1) Risk taking propensity

Risk taking propensity was seen to be affected by the following domains: Locus of control;

Peer Behavior; Goals; Initiative and Skill of idea realization. The following hypothesis were

identified:

y Ho1 the risk taking propensity of Pakistani business students is positively co-related to

entrepreneurial intentions

y Ho2 the risk taking propensity of Pakistani business students is significant in determining

entrepreneurial intentions of Pakistani business students.

3.1.2.2) Risk perception

Risk perception was defined by student view regarding opportunities and losses in market.

The following hypothesis were identified:

y

Ho3 the risk perception of Pakistani business students is negatively co-related to

entrepreneurial intentions.

y Ho4 the risk perception of Pakistani business students is significant in determining



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3.1.2.3) Self-efficacy

Self efficacy was identified by belief of competence, resourcefulness, confidence, EQ and

persistence. The following hypothesis were identified:

y Ho5 the self efficacy of Pakistani business students is positively co-related to


y Ho6 the self efficacy of Pakistani business students is significant in determining


3.1.2.4) Motivation

It was probed that are the students motivated by entrepreneurial benefits or not. The factors

that were included are: career choice; money; recognition; autonomy and innovation. The

following hypothesis were identified:

y Ho7 the motivation of Pakistani business students is positively co-related to


y Ho8 the motivation of Pakistani business students is significant in determining


3.1.2.5) Entrepreneurial support

In order to check the entrepreneurial supports effectiveness the facilities offered by a

business institute like business centre, entrepreneurial trainings, trade and VC fairs, provision of

loans etc. was checked in case of students.

y Ho9 the entrepreneurial support offered to Pakistani business students is positively co-

related to entrepreneurial intentions.


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y Ho10 the entrepreneurial support offered to Pakistani students is significant in

determining entrepreneurial intentions.

3.1.3) Control variables:

The control variables in this case were the demographics of the sample. This included the

following variables:

3.1.3.1) Gender

The first variable checked was gender.

3.1.3.2) Work experience

The previous work experience of students in jobs and internships was gauged and checked for

connection with dependant variable. The following hypothesis was deduced:

y Ho12 People in higher experience bracket have more entrepreneurial intentions.

3.1.3.3) Age group

The age group of sample was assessed in respect to the effect on dependant variable. The

following hypothesis was deduced:

y Ho11 People in higher age bracket have more entrepreneurial intentions.

3.1.3.4) Education

The affect of the samples education level was gauged in accordance to having affect on

dependant variable. The following hypothesis was deduced:

y Ho13 People in higher education bracket have more entrepreneurial intentions.


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3.1.3.5) Fathers employment

The effect of employment back ground was checked on the students entrepreneurial

intentions. The fathers employment hypothesis is the following:

y Ho14 People whose fathers are self employed have more entrepreneurial intentions.

3.1.3.6) Mothers employment

The effect of employment back ground was also checked for mother. The following

hypothesis was deduced:

y Ho15 People whose mothers are self employed have more entrepreneurial intentions.

3.1.3.7) House hold income

The effect of house-hold income on the students entrepreneurial efforts was checked and the

following hypothesis was deduced:

y Ho16 People in higher house hold income bracket have more entrepreneurial intentions.


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4. Research Methodology

4.1) Type of Study

It is a descriptive type of study in which already established hypothesis in internationally

literature are checked in the case of Pakistan Business Students in accordance to their

entrepreneurial profile.

4.2) Time Horizon

It is a cross-sectional study for the present time period.

4.3) Unit of Analysis

The unit of analysis in the study is the entrepreneurial intentions as affected by independent

variables. The element of analysis is the Business student in Pakistani Universities.

4.4) Population and sample Frame

All Pakistani business students are the population frame for this quantitative analysis.

4.5) sampling technique used:

convenience sampling was practiced for data collection as the researchers are present in the

sample. The sample of study is drawn randomly from business students enrolled in the

universities of Islamabad namely: IIUI; FAST; SZABIST; NUST; Bahria and Iqra.

4.5) Instrument Selection

For the purpose of data collection we used the tool of questionnaire.

Entrepreneurial Intentions, Entrepreneurial Support and Demographic Variables are adapted

from:


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Linan,F., Rodriguez-Cohard, J.C. & Rueda-Cantache, J.M.(2005)

independent variables of motivation, risk perception, risk taking propensity and self efficacy

are adapted from questionnaires of:

Iakovleva, T., Kolvereid, L., Stephan, U., (2011) also used by: Barbosa, S., Kickul, J., and

Liao-Troth, M. (2007); Rybowiak, V., Garts, H. and Frese, M. (1999); Linan, F., Chen, l. (2006)

in their studies.

Questionnaire has two parts. First part measures dependant variable, entrepreneurial

intentions (I) and independent variables, risk taking propensity(RTP) ; risk perception (RP);

motivation (M); entrepreneurial support (ES) and self efficacy (SE). The next part denotes

demographic traits of the students. All variables have five items. Entrepreneurial intentions part

asks about how keen and ready the students are to step into the business world soon enough and

whether they would prioritize it as a career or not (Ajzen and Fishbein, 1980; Ajzen, 1987,

1991).

Next, the risk taking propensity (RTP) of students is gauged. Important factors determining

higher were higher age, higher education, fathers background of self employment. The items

check student response rate, initiative and EQ. After that RP is rated with regards to view of

student to opportunities and barriers in the external environment and how that moulds his

business ventures success. The next variable SE gauges students self belief and confidence of

traits and skill necessary to start and run the business. M follows to know about what motivates


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students for business set-up. ES reveals about the students knowledge and effectiveness of help

offered by government and their own academic institute.

In addition, the demographic information is related to first of all to gender because growing

attention is being paid to what works in the case women entrepreneurs because they too form a

significant part of the population. Parents employment background, education, age and

household income are also checked to know about any implications.

The questionnaires were mainly hand-filled but electronic means of collection e.g. email and

website links were also helpful.

4.6) Proposed Data Collection Procedures

At first literature review was established from desk research by having a thorough read of

many digital libraries namely Jstor and Emerald. From the literature review, it can be seen that

theoretical and empirical research in the academic literature has associated EI with the respective

independent variables and control variables. Interviews and discussions were held with students

and academicians regarding their views on the entrepreneurial problem of business graduates in

Pakistan. On the basis of that questionnaire was obtained from associated authors and adapted

according to Pakistani landscape. Its validity was checked with pilot testing. Next, the

questionnaire was floated in through email and link to many people. When responses stopped

increasing electronically, hand-filled questionnaires were also added to data set.

4.7) Proposed Data Analysis Techniques

SPSS technique is used for all quantitative data analysis.


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4.7.1) Descriptive statistics

Descriptive statistics are used to define mean, standard deviations, range, skewness and

kurtosis of demographics, independent variables and dependant variables.

4.7.2) Reliability of data

Reliability of data is checked the value of cronbachs alpha in scale.

4.7.3) P-P Plots

P-P Plots are obtained to check normality of data. Normal probability histogram is used to

check normality of overall data to dependant variable. A regression line is obtained. P-P Plots of

independent variables to dependant variable are also obtained to check nature of data.

4.7.4) Measures of association

Inter item co-relations are found through Pearsons co-relation to test the hypothesis.

4.7.5) Regression analysis

Through regression analysis regression equation is formulated. The beta co-efficient is

obtained and its significance level is tested in the F-test. The beta co-efficient explains nature and

magnitude of relationship. R square tells goodness of data. It is helpful in predicting how much

change independent variable are causing in dependant variable.

4.7.6) One-way ANOVA and post hoc tuckey

This is used for other variables in grouped data of demographics. The effect of different

demographic groups with respect to dependant variables is checked.

5. Results and Discussion

After employing the above mentioned techniques, the following results were obtained.


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entrepreneurial support. It means students realize that by enhancing it entrepreneurial intentions

would be directly affected.

For variable I, Statistic 2, dominates the data set with 41% presence. This means majority of

people have negative intentions for entrepreneurship. Cumulative RTP at statistic 3 is 80%. This

means majority of people dont have the potential to face the unexpected situations of business.

For variable RP, majority of the sample is towards the extreme agreement to risks associated

with starting and running business. For variable M, Majority of people are not strongly

motivated. The cumulative frequency till 3 is 74%. The variable SE, has mixed responses. It is

equally towards both ends. In variable ES, most people are in disagreement to the entrepreneurial

supports effectiveness and presence. If it exists universities need to create better awareness of it

and also improve facilities and aid offered.

5.3) Estimated Distribution Parameters;

Normality of data was checked in P-P Plots of variables. The variable I graph shows good

normality having higher incidence at statistic 2. In RTP, Graph shows good normality. Higher

incidence is towards lesser statistics. In RP, The graph is more right skewed. Higher incidence is

towards greater statistic. In ES, graph is defined for below 3 statistics. For SE, the data is quite

normal with slight right skew. For M, the data is quite normal with slight left skew.


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5.4) Reliability Analysis

Cronbachs Alpha is well within the acceptable range of to 0.60. This is calculated for the

mean values of dependant and independent variables. This is telling that data is reliable.

Therefore analysis could be easily conducted.

5.5) Inter-Item Correlation Matrix

As can be seen in table 11, the co-relation between RTP and I is very strong. It is above 0.7

and below 1. The co-relation of RP with all variables is negative. SE and I have positive

moderate to weak relationship of 0.5. M has a very strong positive relationship with I, above 0.7.

ES has a very strong positive co-relation with I. RP and RTP have a very strong negative co-

relation. M has an extremely strong positive co-relation with RTP. SE has positive moderate

relationship with RTP. ES has a strong positive co-relation with RTP. RP has a moderate

negative relationship with SE and it has a strong negative relationship with M. ES and RP have

a strong negative relationship. SE has a moderate relationship with M and ES. M has a strong

relationship with ES.

5.6) ANOVA table

As can be seen in table 13, for each model (independent variable), regression is much higher

than residual. This means most of the information is on the normal curve or line than away from

it.


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5.7) Regression analysis and Co-efficient table

As can be seen in table 15, T value is above 2 and significant for all independent variables

except motivation.

Standardized regression equation with standardized co-efficient and alpha is following:

I = 0.395 RTP - 0.413 RP + 0.148 SE - 0.195M + 0.236 ES + 0.583

Unstandardized regression equation with unstandardized co-efficients and alpha is following:

I = 0.443RTP - 0.536RP + 0.307SE - 0. 204M + 0.565ES + 0.557

RTP increases I by around 40%; RP decreases I by around 41%; SE increases I by around

15%; M decreases I by around 20%; ES decreases I by around 24% and other wise Pakistani

business students have around 60% entrepreneurial intentions.

5.8) Regression line to Dependant variable

As suggested in graph 13, histogram of dependant variable I, is slightly left skew.

5.9) One way ANOVA and post hoc tuckey

It is used for one way control group variables.

5.9.1) Education

As shown in table 16 alpha is significant at around 0.7. Around 67% sample is of masters

education and they are above the neutral to agreement side in respect to variables chosen. F value


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is significant and above 33. The group 3-4 Years of BBA have 0.25564 more I than 1-2 Years of

BBA. MBA/MSC/M.phill have 1.59937 more I than 3-4 Years of BBA and 1.85501 more I than

1-2 Years of BBA. This shows MBA/MSC/M.phill have highest I than 3-4 Years of BBA

follows and 1-2 Years of BBA in the end.

5.9.2) Household income

Table 20 shows 70% of the sample is Rs. 0-60,000 income group. F is significant at 30.2 and

alpha is significant at 0.117. The income group having highest entrepreneurial intentions is the

one above Rs. 100,000. It is 1.41 more than the second income group and 2.06 more than first

income group. The middle income group is 0.64 more entrepreneurially inclined than first

income group.

5.9.3) Work experience

As shown in table 25 half of sample is having 0-0.5 Years work experience and 29 % people

are having 0.5-1.0 Years experience. F is significant at 90. The group1.0-2.0 Years work

experience are having most entrepreneurial incline of 2.84, more than the first bracket, 1.53

more than the second bracket and 0.15 more than fourth bracket. The group above 2.0 Years

work experience are having 2.7 more I than first group, 1.4 more than second group.

5.9.4) Father employment

F is significant at above 41. The group Father Self Employed are having 1.89 more I than

second group and 2.6 more I than third group. Father Employed group is having 0.74 more I

than third group. 24% sample was first group and 69% was second group.


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5.9.5) Mothers employment

As can be seen in table 31 for mothers occupation, first group has 6%, second group 11% and

third group 83% composition in sample.. Mother Unemployed group is having 1.9 more I than

first group and 1.8 more I than second group. Data is significant at F equal to 19.

5.9.6) Age group

As can be seen in table 34, 55% of sample is in 25-30 Years age group and 27% is in the 20-

25 Years age group. Second group is having 0.5 more I than first group. Third group is having

2.17 more I than first group and 1.7 more I than second group. F is significant at 61.

5.11) Hypothesis results

In light of the above analysis hypothesis for demographic variables from H11 to H16 are all

proven. The independent variables have high co-relation with dependant variable at above 0.8

and only 0.5 in case of SE. Table 11 proves that H1, H3, H7, H9 are rightly proven. Only H5 and

H6 is not proven as regression co-efficient is small. Regression equation proves all hypotheses of

H2, H4, H8 and H10.

6) Conclusion

Pakistani business students have somewhat neutral entrepreneurial intentions and rank high on

risk perception. Students are not strongly motivated for venture creation and have moderate risk

taking propensity. Their self-efficacy is not high and the effectiveness of institutions for the aid

of student entrepreneurs is not satisfactory in propelling student entrepreneurial intentions.

Students with higher education, experience, age and household income have higher


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entrepreneurial intentions. The background of students parents employment also has a

significant affect in case of father.

6.1) Recommendations

To improve the motivations of students so that entrepreneurial intentions can be increased

educational institutes need to conduct campaigns increasing awareness of the benefits of

entrepreneurship in general and specific to the case of the business student. Factors that diminish

the effect of risk perception or apprehensions to starting venture creation should be lessened by

factors like creativity, innovation and operational efficiencies. Risk taking propensity of students

should be increased by making them participate in simulation programs related to

entrepreneurship and have course of class related to experiencing the risks and mitigating them.

Self-efficacy can be increased through encouragement, guidance and mentorship. More

entrepreneurial exposure should be created to enhance motivation, increase inspiration, develop

networking and reduce risk perception.

6.1.1)Model for credit Provision to student:

Institutes can improve their offerings of the business centre by getting research sponsors for

market research of product launch. They can increase experience of students through more

guided internships etc. Also, since dearth of funds accounts for major reason to discouragement

of entrepreneurial intentions universities can create a banking institution of their own or in

association with some banking institution to launch the credit provision service.

6.1.1.1) Features:

Its funds will be availed from the services of students gathered in internships, research work,

voluntary work at university for co-coordinating events etc. furthermore, a certain percentage of

students funds will start collecting from first semester of BBA to be claimed by MBA education


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completion. This amount will be compounded interest by the end of the tenure of education. The

pool of funds of all students will provide for competent and hopeful students entrepreneurial

aspirations. There is risk mitigation through this channel as the academia are personally aware of

student traits that play an important role in venture creation and success. Also, they can guide in

the ideas launch as they are the experts. After some time the amount taken could be returned

when profitable. So that other students can use the amount. This way many students will practice

entrepreneurial work and risk to student groups will be mitigated. Also, they can form networks

which will be very helpful.


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Annexure: A Reffrences

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Wilson, F., J. Kickul, and D. Marlino. 2007. Gender, entrepreneurial self-efficacy, and

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Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and performance. Englewood

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Sitkin, S. and Pablo, A. (1992), Reconceptualizing the determinants of risk behaviour,

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Atkinson, J. W. (1957). Motives in fantasy, action, and society. Princeton, NJ: Van Nostrand.

Bird, B. (1988), Implementing entrepreneurial ideas: the case for intention, The Academy

of Management Review, Vol. 13 No. 3, pp. 442-53.

Shapero, A. (1982), Social Dimensions of Entrepreneurship, Prentice-Hall, Englewood Cliffs.

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Krueger, N.J. and Carsrud, A. (1993), Entrepreneurial intentions: applying the theory of

planned behaviour, Entrepreneurship and Regional Development, Vol. 5, pp. 315-30.

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personality and social psychology, in Berkowitz, L. (Ed.), Advances in Experimental Social

Psychology, Vol. 20, Academic Press, New York, NY, pp. 1-56.

Ajzen, I. (1991), The theory of planned behavior, Organizational Behavior and Human

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Prentice-Hall, Englewood Cliffs, NJ.

Sporn, B. (1999), Adaptive University Structures: An Analysis of Adaptation to

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Clark, B. (1998), Creating Entrepreneurial Universities: Organizational Pathways of

Transformation, International Association of Universities Press and Pergamon, Oxford.

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entrepreneurial intentions level, 45th Congress of the European Regional Science Association,

Amsterdam, 23-27 August

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Annexure B : List of Tables and Figures

Graph: 1, Descriptive Statistics; Histogram of E I

Graph: 2, Descriptive Statistics; Histogram of RTP

Graph: 3, Descriptive Statistics; Histogram of RP

Graph: 4,Descriptive Statistics; Histogram of ES

Graph:5, Descriptive Statistics; Histogram of SE

Graph: 6, Descriptive Statistics; Histogram of M

Graph:7, Probability Plot for Intentions (I)

Graph:8,Probability Plot for RTP

Graph: 9, Probability plot for RP

Graph:10, Probability plot for SE

Graph:11,Probability plot for M

Graph:12, Probability Plot ES

Graph 13, Histogram of dependant variable I with frequency

Graph:14, Normal P-P Plot of regression standardized residual

Graph:15, Partial regression plot of dependant variable I with RTP

Graph:16, Partial regression plot of dependant variable I with RP

Graph:17,Partial regression plot of dependant variable I with SE

Graph:18, Partial regression plot of dependant variable I with M

Graph: 19, Partial regression plot of dependant variable I with ES

Table.1 Descriptive statistics for Demographics

Table.2 Descriptive Statistics for Independent Variable and Dependant Variable

Table: 3 Frequency Table for Intentions ( I)


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Table 28 fathers employment anova

Table 29 fathers employment Post hoc tockey

Table 30 mothers employment descriptives

Table 31 mothers employment ANOVA

Table 32 mothers employment post hoc tuckey

Table 33 age group descriptives

Table 34 age group Anova

Table 35 age group post hoc tuckey

Table 36 gender descriptives

Table 37 gender independent sample test


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Graphs

Histograms with normality curve of dependant and independent variable.

Graph: 1 Descriptive Statistics; Histogram of E I

Graph shows good normality, with higher incidence at 2.


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Graph: 2, RTP

Graph shows good normality. Higher incidence is towards lesser statistic.


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Graph: 3, RP

The graph is more right skewed. Higher incidence is towards greater statistic.


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Graph: 4 Entrepreneurial support (ES)

Graph is defined for below 3 statistics.


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Graph: 5

Self Efficacy (SE)

The data is quite normal with slight right skew.


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Graph: 6, Motivation

The data is quite normal with slight left skew.


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Graph:7, P-P Plot of Intentions (I)


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Graph:8 , Probability Plot for RTP


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Graph: 9, Probability plot for RP


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Graph:10, Probability plot for SE


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Graph:11, Probability plot for M


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Graph:12, Probability Plot ES


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Graph 13, Histogram of dependant variable I with frequency:


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Graph:14, Normal P-P Plot of regression standardized residual


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Graph:15, Partial regression plot of dependant variable I with RTP


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Graph:16, Partial regression plot of dependant variable I with RP


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Graph:17, Partial regression plot of dependant variable I with SE


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Graph:18, Partial regression plot of dependant variable I with M


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Graph: 19, Partial regression plot of dependant variable I with ES


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Table:1 Descriptive statistics for Demographic

Minimum Maximum Mean Std.

Deviation

Skewness Kurtosis

Gender 1.00 2.00 1.3200 .46883 .784 -1.415

Work Experience 1.00 4.00 1.8200 1.00885 1.034 -.084

Fathers Employment 1.00 3.00 1.8300 .53286 -.148 .177

Mothers

Employment1.00 3.00 2.7700 .54781 -2.338 4.413

Age Group 1.00 3.00 2.3700 .77401 -.754 -.923

Household Income 1.00 3.00 1.4800 .78470 1.219 -.243

Education 1.00 3.00 2.5300 .73106 -1.214 -.031

Std. Error of Skewness is 0.241 andStd. Error of Kurtosis is 0..478

Table.2 Descriptive Statistics for Independent Variable and Dependant Variable

I RTP RP SE M ES

Mean 2.7200 2.7000 4.0100 3.1380 2.7200 1.8820

Std. Error of Mean .12719 .11326 .09795 .06115 .12151 .05319

Median 2.0000 3.0000 4.0000 3.0000 3.0000 1.8000

Std. Deviation 1.27192 1.13262 .97954 .61147 1.21506 .53189

Skewness .575 .319 -.612 .287 .212 .536

Std. Error of Skewness .241 .241 .241 .241 .241 .241

Kurtosis -.762 -.350 -.701 -.305 -.818 -.678

Std. Error of Kurtosis .478 .478 .478 .478 .478 .478

Minimum 1.00 1.00 2.00 1.80 1.00 1.20

Maximum 5.00 5.00 5.00 4.60 5.00 2.80


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Frequency Tables

Table: 3 Intentions ( I) Frequency Tables

Frequency Percent Valid Percent Cumulative Percent

Valid

1.00 14 14.0 14.0 14.0

2.00 41 41.0 41.0 55.0

3.00 19 19.0 19.0 74.0

4.00 11 11.0 11.0 85.0

5.00 15 15.0 15.0 100.0

Total 100 100.0 100.0

Table: 4 Risk Taking Propensity (RTP)


Valid

1.00 16 16.0 16.0 16.0

2.00 26 26.0 26.0 42.0

3.00 39 39.0 39.0 81.0

4.00 10 10.0 10.0 91.0

5.00 9 9.0 9.0 100.0

Total 100 100.0 100.0

Table: 5 Risk Perception (RP)


Valid

2.00 9 9.0 9.0 9.0

3.00 20 20.0 20.0 29.0

4.00 32 32.0 32.0 61.0

5.00 39 39.0 39.0 100.0

Total 100 100.0 100.0


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Table: 6 Motivation (M)


Valid

1.00 19 19.0 19.0 19.0

2.00 25 25.0 25.0 44.0

3.00 30 30.0 30.0 74.0

4.00 17 17.0 17.0 91.0

5.00 9 9.0 9.0 100.0

Total 100 100.0 100.0

Table: 7 Self Efficacy (SE)


Valid

1.80 2 2.0 2.0 2.0

2.00 1 1.0 1.0 3.0

2.20 4 4.0 4.0 7.0

2.40 5 5.0 5.0 12.0

2.60 14 14.0 14.0 26.0

2.80 9 9.0 9.0 35.0

3.00 17 17.0 17.0 52.0

3.20 15 15.0 15.0 67.0

3.40 8 8.0 8.0 75.0

3.60 5 5.0 5.0 80.0

3.80 5 5.0 5.0 85.0

4.00 7 7.0 7.0 92.0

4.20 4 4.0 4.0 96.0

4.40 3 3.0 3.0 99.0

4.60 1 1.0 1.0 100.0

Total 100 100.0 100.0


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Table: 8 Entrepreneurial Support (ES)


Valid

1.20 21 21.0 21.0 21.0

1.60 15 15.0 15.0 36.0

1.80 28 28.0 28.0 64.02.00 11 11.0 11.0 75.0

2.20 5 5.0 5.0 80.0

2.60 2 2.0 2.0 82.0

2.80 18 18.0 18.0 100.0

Total 100 100.0 100.0

Estimated Distribution Parameters; Normality of Data P-P Plot

Independent Variable and Dependant Variable

Table: 9

I RTP RP SE M ES

Location 2.7200 2.7000 4.0100 3.1380 2.7200 1.8820

Scale 1.27192 1.13262 .97954 .61147 1.21506 .53189

Table:10Reliability Statistics

Cronbach's Alpha Standardized N of Items

.557 .583 6


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Table :11 Inter-Item Correlation Matrix

Inter-Item Correlation Matrix

I RTP RP SE MRTP .839

RP -.849 -.890

SE .500 .408 -.410

M .805 .944 -.923 .387

ES .832 .846 -.862 .410 .799

Table: 12 Inter-Item Covariance MatrixInter-Item Covariance Matrix

I RTP RP SE M ES

I 1.618

RTP 1.208 1.283

RP -1.058 -.987 .959

SE .389 .282 -.246 .374

M 1.244 1.299 -1.098 .288 1.476

ES .563 .510 -.449 .133 .516 .283


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Table: 13 ANOVA table

Model Sum of Squares df Mean Square F Sig.

1

Regression 112.631 1 112.631 232.235 .000b

Residual 47.529 98 .485

Total 160.160 99

2

Regression 120.781 2 60.391 148.757 .000c

Residual 39.379 97 .406

Total 160.160 99

3

Regression 124.283 3 41.428 110.854 .000d

Residual 35.877 96 .374

Total 160.160 99

4

Regression 125.592 4 31.398 86.290 .000e

Residual 34.568 95 .364

Total 160.160 99

5

Regression 127.384 5 25.477 73.065 .000f

Residual 32.776 94 .349

Total 160.160 99

a. Dependent Variable: I

b. Predictors: (Constant), RTP

c. Predictors: (Constant), RTP, RP

d. Predictors: (Constant), RTP, RP, SE

e. Predictors: (Constant), RTP, RP, SE, M

f. Predictors: (Constant), RTP, RP, SE, M, ES


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Table:15

Co-efficient table

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig. 95.0% Confidence Interval

for B

B Std. Error Beta Lower Bound Upper Bound

1(Constant) .177 .181 .981 .329 -.181 .536

RTP .942 .062 .839 15.239 .000 .819 1.064

2

(Constant) 4.080 .887 4.602 .000 2.320 5.839

RTP .449 .124 .399 3.625 .000 .203 .694

RP -.641 .143 -.494 -4.481 .000 -.925 -.357

3

(Constant) 2.921 .931 3.138 .002 1.073 4.769

RTP .411 .119 .366 3.447 .001 .174 .648

RP -.592 .138 -.456 -4.287 .000 -.867 -.318

SE .339 .111 .163 3.061 .003 .119 .559

4

(Constant) 3.998 1.080 3.702 .000 1.854 6.141

RTP .631 .165 .562 3.822 .000 .303 .958

RP -.764 .164 -.589 -4.668 .000 -1.089 -.439

SE .325 .110 .156 2.968 .004 .108 .543

M -.344 .181 -.329 -1.897 .061 -.704 .016

5

(Constant) 2.200 1.322 1.664 .099 -.425 4.824

RTP .443 .181 .395 2.444 .016 .083 .804

RP -.536 .189 -.413 -2.834 .006 -.912 -.160

SE .307 .108 .148 2.857 .005 .094 .521

M -.204 .188 -.195 -1.084 .281 -.577 .170

ES .565 .249 .236 2.266 .026 .070 1.060

a. Dependent Variable: I


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Table 16 one way ANOVA Education

Descriptives Education

I

N Mean Std.

Deviation

Std.

Error

95% Confidence Interval for

Mean

Minimum Maximum

Lower Bound Upper Bound

1-2 Years of BBA 14 1.4286 .51355 .13725 1.1321 1.7251 1.00 2.00

3-4 Years of BBA 19 1.6842 .47757 .10956 1.4540 1.9144 1.00 2.00

MBA/MSC/M.phill 67 3.2836 1.15215 .14076 3.0026 3.5646 2.00 5.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00

Table 17: ANOVA Education

I

Sum of Squares df Mean Square F Sig.

Between Groups 65.014 2 32.507 33.141 .000

Within Groups 95.146 97 .981

Total 160.160 99

Table 18: Post hoc tuckey tests Education

Multiple Comparisons

Dependent Variable: I

Tukey HSD

(I) Education (J) Education Mean

Difference (I-J)

Std. Error Sig. 95% Confidence Interval


1-2 Years of BBA3-4 Years of BBA -.25564 .34884 .745 -1.0860 .5747

MBA/MSC/M.phill -1.85501*

.29104 .000 -2.5477 -1.1623

3-4 Years of BBA1-2 Years of BBA .25564 .34884 .745 -.5747 1.0860

MBA/MSC/M.phill -1.59937*

.25742 .000 -2.2121 -.9867

MBA/MSC/M.phill1-2 Years of BBA 1.85501

*.29104 .000 1.1623 2.5477

3-4 Years of BBA 1.59937*

.25742 .000 .9867 2.2121

*. The mean difference is significant at the 0.05 level.


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Table 19 Homogenous subsets Education

I

Tukey HSD

Education N Subset for alpha = 0.05

1 2

1-2 Years of BBA 14 1.4286

3-4 Years of BBA 19 1.6842

MBA/MSC/M.phill 67 3.2836

Sig. .674 1.000

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 21.585.

b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not

guaranteed.

Table 20 Descriptive household income with I

Descriptives

I

N Mean Std.

Deviation

Std. Error 95% Confidence Interval for Mean Minimum Maximum


Rs. 0-

60,000

70 2.2714 .89962 .10753 2.0569 2.4859 1.00 4.00

Rs. 60,000

to 100,00012 2.9167 1.16450 .33616 2.1768 3.6566 2.00 5.00

Above

Rs.100,00018 4.3333 1.28338 .30250 3.6951 4.9715 2.00 5.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00


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Table 21: ANOVA household income

ANOVA

I


Between Groups 61.400 2 30.700 30.153 .000

Within Groups 98.760 97 1.018

Total 160.160 99

Table 22: Post hoc tuckey tests household income



Tukey HSD

(I) Household Income (J) Household Income Mean

Difference (I-

J)



Rs. 0-60,000

Rs. 60,000 to 100,000 -.64524 .31526 .107 -1.3956 .1052

Above Rs.100,000 -2.06190*

.26666 .000 -2.6966 -1.4272

Rs. 60,000 to

100,000

Rs. 0-60,000 .64524 .31526 .107 -.1052 1.3956

Above Rs.100,000 -1.41667*

.37604 .001 -2.3117 -.5216

Above Rs.100,000Rs. 0-60,000 2.06190

*.26666 .000 1.4272 2.6966

Rs. 60,000 to 100,000 1.41667*

.37604 .001 .5216 2.3117



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Table 23 Homogenous Subsets Household Income Tukey HSD with I

I

Tukey HSD

Household Income N Subset for alpha = 0.05

1 2

Rs. 0-60,000 70 2.2714

Rs. 60,000 to 100,000 12 2.9167

Above Rs.100,000 18

Sig. .117 1.000

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 19.585.

b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not

guaranteed.

Table 24 Work Experience Descrptives

Descriptives

I

N Mean Std.

Deviation

Std.

Error


Mean

Minimum Maximum


0-0.5 Years 50 1.7600 .51745 .07318 1.6129 1.9071 1.00 3.00

0.5-1.0 Years 29 3.0690 .65088 .12087 2.8214 3.3165 2.00 4.00

1.0-2.0 Years 10 4.6000 .51640 .16330 4.2306 4.9694 4.00 5.00

Above 2.0

Years11 4.4545 1.21356 .36590 3.6393 5.2698 2.00 5.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00

Table 25 Work Experience Anova

ANOVA

I

Sum of Squares df Mean Square F Sig.Between Groups 118.051 3 39.350 89.710 .000


Total 160.160 99


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Table 26 Post Hoc Tuckey



Tukey HSD(I) Work Experience (J) Work Experience Mean

Difference (I-J)



0-0.5 Years

0.5-1.0 Years -1.30897*

.15459 .000 -1.7132 -.9048

1.0-2.0 Years -2.84000*

.22943 .000 -3.4399 -2.2401

Above 2.0 Years -2.69455*

.22057 .000 -3.2712 -2.1179

0.5-1.0 Years

0-0.5 Years 1.30897*

.15459 .000 .9048 1.7132

1.0-2.0 Years -1.53103*

.24288 .000 -2.1661 -.8960

Above 2.0 Years -1.38558*

.23452 .000 -1.9988 -.7724

1.0-2.0 Years

0-0.5 Years 2.84000*

.22943 .000 2.2401 3.4399

0.5-1.0 Years 1.53103*

.24288 .000 .8960 2.1661

Above 2.0 Years .14545 .28938 .958 -.6112 .9021

Above 2.0 Years

0-0.5 Years 2.69455*

.22057 .000 2.1179 3.2712

0.5-1.0 Years 1.38558*

.23452 .000 .7724 1.9988

1.0-2.0 Years -.14545 .28938 .958 -.9021 .6112


Table 27 Fathers Employment Descrptives

Descriptives

I

N Mean Std.

Deviation

Std.

Error


Mean

Minimum Maximum

Lower

Bound

Upper

Bound

Father Self

Employed24 4.2083 1.21509 .24803 3.6952 4.7214 2.00 5.00

Father Employed 69 2.3188 .86590 .10424 2.1108 2.5269 1.00 4.00

Father

Unemployed7 1.5714 .53452 .20203 1.0771 2.0658 1.00 2.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00


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Table 28 Fathers Employment Anova

ANOVA

I


Between Groups 73.502 2 36.751 41.137 .000


Total 160.160 99

Table 29 Fathers Employment Post Hoc Tuckey



Tukey HSD

(I) Fathers

Employment

(J) Fathers

Employment

Mean

Difference (I-

J)



Father Self EmployedFather Employed 1.88949

*.22399 .000 1.3563 2.4226

Father Unemployed 2.63690*

.40602 .000 1.6705 3.6033

Father EmployedFather Self Employed -1.88949

*.22399 .000 -2.4226 -1.3563

Father Unemployed .74741 .37493 .119 -.1450 1.6398

Father UnemployedFather Self Employed -2.63690

*.40602 .000 -3.6033 -1.6705

Father Employed -.74741 .37493 .119 -1.6398 .1450


Table 30 Mothers Employment Descriptives

Descriptives

I

N Mean Std.

Deviation

Std.

Error


Mean

Minimum Maximum

Lower

Bound

Upper

Bound

Mother SelfEmployed

6 1.1667 .40825 .16667 .7382 1.5951 1.00 2.00

Mother Employed 11 1.2727 .46710 .14084 .9589 1.5865 1.00 2.00

Mother

Unemployed83 3.0241 1.16845 .12825 2.7690 3.2792 1.00 5.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00


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Table 31 Mothers Employment ANOVA

ANOVA

I


Between Groups 45.193 2 22.597 19.065 .000Within Groups 114.967 97 1.185

Total 160.160 99

Table 32 Mothers Employment Post Hoc Tuckey



Tukey HSD

(I) Mothers

Employment

(J) Mothers

Employment

Mean

Difference (I-

J)



Mother Self EmployedMother Employed -.10606 .55253 .980 -1.4212 1.2091

Mother Unemployed -1.85743*

.46024 .000 -2.9529 -.7620

Mother EmployedMother Self Employed .10606 .55253 .980 -1.2091 1.4212

Mother Unemployed -1.75137*

.34932 .000 -2.5828 -.9199

Mother UnemployedMother Self Employed 1.85743

*.46024 .000 .7620 2.9529

Mother Employed 1.75137*

.34932 .000 .9199 2.5828


Table 33 Age Group Descriptives

Descriptives

I

N Mean Std.

Deviation

Std. Error 95% Confidence Interval for

Mean

Minimum Maximum


18-20 Years 18 1.3889 .50163 .11824 1.1394 1.6383 1.00 2.00

20-25 Years 27 1.8889 .32026 .06163 1.7622 2.0156 1.00 2.00

25-30 Years 55 3.5636 1.08463 .14625 3.2704 3.8569 2.00 5.00

Total 100 2.7200 1.27192 .12719 2.4676 2.9724 1.00 5.00


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Table 34 Age Group Anova

ANOVA

I


Between Groups 89.688 2 44.844 61.725 .000Within Groups 70.472 97 .727

Total 160.160 99

Table 35 Age Group Post Hoc Tuckey



Tukey HSD

(I) Age Group (J) Age Group Mean Difference

(I-J)



18-20 Years20-25 Years -.50000 .25936 .136 -1.1173 .1173

25-30 Years -2.17475*

.23145 .000 -2.7257 -1.6238

20-25 Years18-20 Years .50000 .25936 .136 -.1173 1.1173

25-30 Years -1.67475*

.20029 .000 -2.1515 -1.1980

25-30 Years18-20 Years 2.17475

*.23145 .000 1.6238 2.7257

20-25 Years 1.67475*

.20029 .000 1.1980 2.1515


Table 36 Gender Descriptives

Group Statistics

Gender N Mean Std. Deviation Std. Error Mean

IMale 68 3.2647 1.15407 .13995

Female 32 1.5625 .50402 .08910


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Table 37Gender Independent Sample Test

Independent Samples Test

Levene's Test for

Equality of

Variances

t-test for Equality of Means

F Sig. t df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence

Interval of the

Difference

Lower Upper

I

Equal variances

assumed26.688 .000 7.977 98 .000 1.70221 .21340 1.27872 2.12569

Equal variances

not assumed10.260 97.648 .000 1.70221 .16591 1.37296 2.03146


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Annexure: C Questionnaire

Strongly Disagree: SD=1 Disagree: D=2 Agree Some What: ASW=3 Agree: A=4 Strongly Agree: SA=5

Indicate your level of agreement with the following statements from 1 (total disagreement) to 5 (total agreement)

A. Intentions 1 2 3 4 5

A1 Im prepared to do anything to be an entrepreneur

A2 My professional objective is becoming anentrepreneur

A3 I will make every effort to start and manage my ownfirm

A4 I have very seriously thought to initiate a business

A5 Ive got the firm resolve to Initiate a company oneday

B. Risk Taking Propensity

B1 Whenever something goes wrong, I search for asolution aptly

B2 I take initiative instantly even when others dont

B3 I use opportunities quickly in order to achieve mygoals

B4 generally I do more than I am asked to do

B5 I am mainly good at realizing ideas

C. Risk Perception

C1 I view the possibility of starting a business as apotential loss due to environmental factors

C2 I dont view the possibility of starting a business asa potential opportunity due to my own creativity

C3 If I dont initiate my own business, I wont bemissing a great opportunity unexplored

C4 There is great uncertainty for me when predictinghow well a new venture will do


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C5 The overall risk level of a new venture is highbecause lack of risk mitigating resources

D. Self Efficacy

D1 I can always handle to solve difficult problems if I tryhard enough

D2 If someone opposes me, I can find the means andways to get my way

D3 I am confident that I can resolve efficientlyunexpected events

D4 I am resourceful enough and know how to handleunforeseen situations

D5 Thanks to my coping abilities, I can remain calmwhen facing difficulties

E. Motivation

E1 Investing in my own small or medium-sizedenterprise and its management is a desirable careerchoice for me

E2 I want to start my own business, because I want tobe free and independent

E3 I want to start my own business, because I have goodideas and want to realize them.

E4 I want to start my own business to be better offfinancially.

E5 I want to start my own business, because I want to besuccessful.

F. Business Support

F1 The university crested access to specific trainingsand forums for young entrepreneurs

F2 The university created access to loans in speciallyfavorable terms to young entrepreneurs

F3 The university created access to facility of technicalaid to start the business

F4 The university created access to Business centrestailored to needs of graduate entrepreneurs


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F5 The university created access to Exposure toConsulting services and trade fairs

G1-Gender:

Male

Female

G2-Work Experience:

0-0.5 Years

0.5-1.0 Years

1.0-2.0 Years

Above 2.0 Years

G3&G4-Parents Employment:

G3-Father SelfEmployed

FatherEmployed

Father Unemployed

G4-Mother SelfEmployed

MotherEmployed

Mother Unemployed

G5-Age Group:

18-20 Years

20-25 Years

25-30 Years

G6-Household Income:

Rs. 0-60,000

Rs. 60,000 to 100,000

MorethanRs. 100,000

G7-Education:

1-2 YearsofBBA

3-4 YearsofBBA

MBA/MSC/M.phill/PHD


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References:

Entrepreneurial Intentions, Entrepreneurial Supportand Demographic Variablesareadapted

from:

Linan,F., Rodriguez-Cohard, J.C. & Rueda-Cantache, J.M.(2005) Factorsaffecting

entrepreneurialintentionslevel, 45th CongressoftheEuropeanRegional Science Association,

Amsterdam, 23-27 August

Motivation, Risk Perception, Risk Taking Propensity, SelfEfficacyareadaptedfrom

questionnaireof:

Iakovleva, T., Kolvereid, L., Stephan, U., (2011) Entrepreneurialintentionsindevelopingand

developedcountries, JournalofEducation& Training, Vol. 53 No. 5, pp. 353-370

Alsousedinthefollowingstudies:

Barbosa, S., Kickul, J., and Liao-Troth, M. (2007)

Rybowiak, V., Garts, H. and Frese, M. (1999)

Linan, F., Chen, l. (2006)

Documents

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