Research Design and Methodology
This study uses survey-based cross-sectional data
collected from Public sector, a centrally funded
university in Multan. The convenience sampling
method was used for collecting the data. This
method has been widely used in many EI studies and
has produced reliable and valid results (Anwar et al.,
2020a; Anwar and Saleem, 2019b; Bazan et al.,
2019; Hassan et al., 2020; Roy et al., 2017). In April
2022, a survey was conducted online with the help
of Google Forms: a number of 250 students
receiving entrepreneurship education at different
sectors were contacted. Of these, 204 students
responded and completed the survey, giving a
response rate of 81.6%. During the data screening
process, no single response were discarded due to
the non-suitability of the data; hence the final
sample comprised of 204 responses (117 males and
85 females and 2 other).
Samples
Students studying business and management
courses were selected for the study. These included
Bachelor of Commerce (Hons), Master of
Commerce,
MBA
in
Human
Resource
Management, Finance and Control, Insurance and
Risk Management, and Hospitality. Topics studied
included business and organizational management,
accounting,
financial
management,
entrepreneurship and business management, etc. and the
courses were delivered by classroom teaching, case
studies, presentations, dissertations at postgraduate
level, and/or internships in industry.
Questionnaire development
A conceptual model, including entrepreneurship
education, IEO and entrepreneurial motivations and
ecosystem, was hypothesized to predict students’
EI. Moreover, the researchers also investigated
whether entrepreneurial motivations mediated the
relationships between entrepreneurship education,
IEO and EI. Entrepreneurial ecosystem positively
influence EI. A questionnaire was developed, with
validated scales borrowed and contextualized from
earlier published studies. The EI questionnaire
from Liñán and Chen (2009) was used to measure
entrepreneurship education and EI. The scale for
IEO was borrowed from Bolton and Lane (2012),
while Solesvik (2013) was consulted for
entrepreneurial motivations. The instrument to
measure entrepreneurial ecosystem factors is taken
from GEM National Experts Survey (NES). In total,
20 items were included in the questionnaire (see
Appendix 1), excluding items that were used to
ascertain the demographic profile (age, gender and
father’s occupation).
Data screening
During the data screening process, no
questionnaires with missing responses were
found. However, 17 questionnaires were found
to have been completed without proper
engagement (i.e. the same option had been
chosen throughout the questionnaire) and thus
were removed from the dataset. Furthermore,
outliers were identified in the dataset using
Cook’s distance method (Stevens, 2012) and
seven response s were found showing Cook’s
statistics above 1 (threshold); thus, they were
also excluded from the dataset. Thus a final
dataset of 204 responses was obtained for
further statistical analysis, which is considered
to be large enough to represent a population
above 2000 (Krejcie and Morgan, 1970) – the
target population for this study is about 1500
undergraduate and postgraduate students
receiving entrepreneurship education at
Bahauddin Zakariya University. The study also
fulfills the requirement of a minimum of 10
responses for each observed item used. Since the
questionnaire included 20 items, the
requirement of a sample of 200 or more
responses is also fulfilled for applying PLS and
SEM techniques. Another requirement for PLS
and SEM using AMOS is the normality of the
data, so, to check that this requirement was
fulfilled, skewness for each observed and latent
variable was computed. The statistics for
skewness ranged from 1 to 1 for each observed
and latent variable, thus confirming the
normality of the data (Kline, 1998).
Common method bias
The remedial suggestions of Podsakoff and
Organ (1986) regarding common method bias
were also kept in mind while developing the
research instrument to ensure that the results
were not affected. The language of the
questionnaire items was kept as simple as
possible, double-barreled questions were
avoided, and variables were also described
before their measurement items to create
psychological separation in the respondents’
minds (Podsakoff and Organ, 1986). The
authors also applied Harman’s single factor test
to statistically testify whether the variance
explained by all 20 observed items under one
single factor was below 50% (see Table 1). The
explained variance was 42.524%, well below
the threshold limit and hence con- firming that
the study was not affected by common method
biases (Podsakoff and Organ, 1986).
Demographic profile
Out of a total of 204 usable responses, 83.82% and 11.27 of students, respectively, belonged to the 15–24 and
25–34 age groups. With regard to gender, 57.35% were male and 41.66 % were female. As noted above, the
sample included both under- graduate and postgraduate students: 49.20% of the students were undergraduates
and 31.60% postgraduates. Moreover, to gather information about their entrepreneurial back- ground,
respondents were also asked about their father’s occupation: only 108 (33.40%) students reported that their
fathers were self-employed or engaged in entrepreneurial activities. Finally, before measuring ‘entrepreneurial
intention’ students’ entrepreneurial inclination was also measured by asking ‘Have you ever seriously
considered becoming an entrepreneur?’ (Yes inclined, No not inclined): and 168 (52%) expressed an inclination
toward entrepreneurship Later, in the study, CFA was applied to ensure model fitness and the convergent and
divergent validity of the data, while for testing the hypotheses (Anderson and Gerbing, 1988), SEM was used.
Table 2. Demographic profile of the sample (N ¼ 204).
Variable name
Age
Category
15–24
25–34
35 and above
Gender
Male
Female
Educational level Undergraduate
Postgraduate
Father’s
Self-employed/
occupation
entrepreneur
Other
Entrepreneurial Yes
inclination
No
Frequency
Percentage (%)
172
23
08
204
119
221
102
108
83.2
11.7
215
168
155
66.6
52.0
48.0
63.2
36.8
68.4
31.6
33.4