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ET
61,6 Exploring entrepreneurial
orientation and intentions among
technical university students
718 Role of contextual antecedents
Received 28 November 2018
Revised 1 May 2019
Swagatika Sahoo and Rajeev Kumar Panda
Accepted 18 May 2019 School of Management, National Institute of Technology, Rourkela, India

Abstract
Purpose – The purpose of this paper is to empirically investigate the impact of the contextual antecedents on
the individual entrepreneurial orientation (IEO) of university graduates, which, in turn, affects their
entrepreneurial intentions (EIs).
Design/methodology/approach – Primary data were collected in the form of 510 valid responses from
engineering students across two technical universities in India, through a structured questionnaire consisting
of scales adapted from the extant literature, and the data were empirically validated in this study.
The reliability and validity measures of the constructs were validated through the confirmatory factor
analysis, and the proposed hypotheses were validated using structural equation modelling.
Findings – The results of this empirical analysis validate that the contextual antecedents have a significant
positive impact on students’ entrepreneurial orientation (EO), which, in turn, has a significant positive
influence on EIs.
Research limitations/implications – This analysis depicts the significance of EO as a perceptual driver at
the individual level and substantiates that the availability of resources such as startup capital, access to business
information, social networks and supportive university context significantly affects the decision-making process of
an individual to venture into an otherwise uncertain occupation of entrepreneurship.
Practical implications – The study has the likely potential to help university administrators and
policymakers to allocate resources, develop strategies and provide effective entrepreneurial learning in
entrepreneurship-oriented courses aimed at honing entrepreneurial skills and self-confidence of the university
students. This holistic model can be used as a tool for resource planning and prioritising in order to provide
the desired contextual support essential for fostering the IEO of the university students towards adopting
entrepreneurial career, thereby assisting them to achieve their career goals and the broader objective of
nation-building.
Originality/value – This study adopts an innovative approach to empirically validate the EO construct at
the individual level, which has been studied at the organisation ( firm) level till today. This research
explores the relevant contextual antecedents and analyses their impact on IEO as well as the explanatory
capacity of IEO to explain students’ EIs in the contextual backdrop of universities in a fast transitioning
economy like India.
Keywords Structural equation modelling, Developing countries, University students,
Entrepreneurial intentions, Contextual antecedents, Individual entrepreneurial orientation
Paper type Research paper

1. Introduction
Entrepreneurs and entrepreneurship are considered as crucial growth agents of a nation to
achieve economic, social, technological and organisational development (Ács et al., 2014;
Bosma et al., 2018). They serve as catalysts for economic development due to the wide array
of economic benefits provided by them in terms of introducing innovative products,
services, job creation, facilitating technology transfer from lab to land, increasing
competitiveness and enabling social empowerment (Ács et al., 2014; Bosma et al., 2018;
Education + Training Fayolle et al., 2016). Therefore, policymakers across the globe are emphasising on numerous
Vol. 61 No. 6, 2019
pp. 718-736
entrepreneurship support measures (Gürol and Atsan, 2006). In line with the proliferating
© Emerald Publishing Limited
0040-0912
emphasis on entrepreneurship development, there is a precipitous rise in policies and
DOI 10.1108/ET-11-2018-0247 government patronage to create entrepreneurial ecosystems for aspiring entrepreneurs in
India as well. However, these formulated policies cannot achieve their desired goal and Role of
global benchmark due to lack of understanding of the critical factors and appropriate contextual
directions for enactment. Therefore, it is imperative to understand the fundamental factors antecedents
in the specific context stimulating entrepreneurship development to achieve the desired
outcome of such ambitious plans.
It is evident from studies that the new-age entrepreneurs have access to formal university
education and training, compared to those self-employed individuals without university 719
education (Ferreira and Trusko, 2018; Franke and Lüthje, 2004; Koe, 2016). Moreover, the socio-
economic contributions of these enterprises/businesses (generating employment, economic
growth and social inclusion) setup by university graduates have been found to be significant
(Lüthje and Franke, 2003). These outcomes have driven the integration of entrepreneurship
education/training programmes to the university education system (Lindberg et al., 2017).
The most recent and eminent trend is that educational institutions in India and around the globe
have started playing a predominant role in strengthening entrepreneurial competencies through
mentorship and support to the aspiring entrepreneurs at the nascent stage of their startup
journey. Universities have shifted their focus from traditional to entrepreneurship-oriented
education, instilling confidence in the budding entrepreneurs to turn their entrepreneurial ideas
into reality (Fayolle, 2013; Lindberg et al., 2017).
Many studies (Canever et al., 2017; Engle et al., 2011; Karimi et al., 2016; Liñán and
Fayolle, 2015; Maresch et al., 2016; Schwarz et al., 2009; Trivedi, 2016) conducted on
university graduates across different country contexts have tried to explain entrepreneurial
intentions (EIs) through the impact of various distal antecedents (psycho-personal,
demographic and environmental). However, Díaz-Casero et al. (2012) argued that the distal
antecedents in the entrepreneurial context do not affect EIs directly, rather they affect the
perception of desirability and feasibility, thus steering the attitudinal orientation of an
individual towards adopting an entrepreneurial career. In order to validate the above
proposition, the relationship between the distal predictors and entrepreneurial orientation
(EO) as well as entrepreneurial intention being affected by EO as an antecedent must be
critically examined (Robinson et al., 1991; Shariff and Saud, 2009). As suggested by Taatila
and Down (2012), a practical understanding of the students’ EO is pivotal to assess their
drive and competencies essential for their success in an entrepreneurial career. Since
university ecosystem plays a significant role in building up the students’ entrepreneurial
skills and competencies (Farashah, 2013; Ferreira and Trusko, 2018), it is binding upon the
scholarly enquiry to assess the impact of the entrepreneurial context in shaping the
orientation and intentions of students in the university ecosystem (Ferreira and Trusko,
2018). Driven by the above motivation, this study attempts to explore and assess the impact
of the contextual antecedents, prevalent in a technical university setup, on individual
entrepreneurial orientation (IEO) of the students, thus fostering their EIs.

2. Literature review and hypotheses development

2.1 Individual entrepreneurial orientation and intentions – the relationship
Studies in the past (Karimi et al., 2016; Kautonen et al., 2015; Maresch et al., 2016) have
investigated that “Intent to act” is central to the creation of an enterprise, as this happens to
be the key driver of the entrepreneurial process (Zhao et al., 2010). In order to understand
this process, it is essential to understand and analyse EIs (Ozaralli and Rivenburgh, 2016).
According to researchers (Hisrich et al., 2013; Liñán and Fayolle, 2015), entrepreneurship is a
complex process involving entrepreneurial cognition and actions. Although psycho-
personal traits, demographic factors, environmental influence, family background,
education and training of an individual have significant impact on perceived ease or
difficulty of choosing an entrepreneurial career (Dinis et al., 2013; Iakovleva et al., 2011;
Lüthje and Franke, 2003; Trivedi, 2016), predicting the exact combination of characteristics
ET and context for new venture creation has been proven to be difficult due to the dynamism of
61,6 the entrepreneurial process.
It has been observed that not all individuals possessing some or other entrepreneurial
personality traits will necessarily intend to venture into the entrepreneurial journey (Bolton
and Lane, 2012). Although personality traits approach predicting propensity for
entrepreneurial activities has been extensively studied since the last three decades
720 (Dinis et al., 2013; Nabi and Liñán, 2013; Rauch and Frese, 2007; Zhao et al., 2010), it lacks the
explanatory power to predict entrepreneurial behaviour (Bolton and Lane, 2012; Lüthje and
Franke, 2003). To address this weak predicting capacity of the trait approach, modern
researchers have proposed entrepreneurial attitude orientation (EAO) approach for
predicting entrepreneurial intention, leading to subsequent behaviour, as it depicts the
positive or negative evaluation of the behaviour in question (Bolton, 2012; Bolton and Lane,
2012; Iglesias-Sánchez et al., 2016; Rauch et al., 2009).
The concept of EAO at the individual level was first introduced by Robinson et al. (1991).
They suggested a scale comprising of four subscales (achievement, self-esteem, personal
control and innovation) and 75 items to measure an individual’s EAO. However, at the firm
level, Miller (1983) for the first time introduced the concept of EO, characterised by
innovativeness, proactiveness and risk-taking affinity. Subsequently, these measures of EO
were augmented by Lumpkin and Dess (1996) by incorporating some additional measures
such as autonomy and competitive aggressiveness. Successive studies (Lumpkin and Dess,
1996; Rauch et al., 2009) have extensively studied the EO construct at the organisation level,
which has been the key to understand whether a firm assumes entrepreneurial activities or
not (Franco and Haase, 2013). Studies have also found EO to have a significant influence on
innovativeness, performance, growth and profitability in entrepreneurial firms (Franco and
Haase, 2013; Moreno and Casillas, 2008; Rauch et al., 2009). In the present scenarios, when
EO has been extensively studied at the firm level for explaining initiation and growth of
business firms, there has been a negligible research effort for assessing EO at the individual
level, in spite of the fact that the attitude measures are inherent in the original EO scale.
Bolton and Lane (2012) filled this void by proposing a reliable measure of IEO and
reiterated that EO as a construct should be studied at the individual level in diverse contextual
setup to validate the robustness of the IEO scale proposed by them. Subsequent studies that
examined IEO have found it to be a multi-dimensional construct similar to that of firm-level
EO, impacting business performance and success. For instance, Bolton (2012), in his study on
entrepreneurs of Western Kentucky, found a significant correlation of IEO with business
performance and success. In another study on Taiwanese franchisees, Chien (2014) discovered
IEO to be positively related to business performance. Extending upon the IEO scale proposed
by Bolton and Lane (2012), a recent scholastic work by Popov et al. (2019) validated the
psychometric properties of the IEO measures in a Serbian student sample.
Recent studies have considered IEO as an entrepreneurial competency that can be
learned through experiential learning. For example, Ibrahim and Lucky (2014) found a
significant relationship between IEO and entrepreneurial intention in Nigerian student
sample in a University of Malaysia. Similarly, the study by Ekpe and Mat (2012) found a
positive impact of IEO on EIs. Moreover, Robinson and Stubberud (2014) found the impact
of entrepreneurship education on IEO of students, which, in turn, affects their intentions to
adopt an entrepreneurial career. Likewise, Zhang and Bruning (2011) argued in favour of an
essential association between the EO and entrepreneurial intention of individuals, which
translates into their performance in business.
Although the above studies have certainly explored the dimensions of IEO to a greater
extent, most of them have used the dimensions of IEO for reliability, validity and
comparative analysis or have studied it as a construct in a linear relationship but never
explored its predicting capacity in a multilinear relationship.
 Hence, it is inevitable to assess the causal relationship between IEO and entrepreneurial Role of
intention at the individual level that would help us to understand the interdependency contextual
among the constructs that is essential to gauge students’ positive or negative inclination antecedents
towards adopting an entrepreneurial career.
Based on the presumption that an individual with a favourable appraisal of the
entrepreneurial career would have a positive intention for new venture creation, the
following hypothesis is proposed: 721
H1. Entrepreneurial orientation of an individual significantly influences his/her intention
to adopt an entrepreneurial career.

2.2 Contextual antecedents and individual entrepreneurial orientation

In the previous section, it is proposed that EO is a plausible predictor of entrepreneurial
intention because it distinguishes entrepreneurs from non-entrepreneurs (Rauch et al., 2009;
Taatila and Down, 2012). Since the past few decades, adopting a strong EO has been
considered extremely crucial for firms to determine their performance and success.
However, EO as an individual-level construct has grabbed the attention of scholars more
recently (Robinson and Stubberud, 2014). Amidst the growing volume of research on IEO,
practical studies aimed to explore the antecedents of EO in diverse entrepreneurial context
are lacking (Taatila and Down, 2012).
EO has been conceptualised as a dispositional construct by Covin and Lumpkin (2011),
but its presence alone does not guarantee entrepreneurial intention and behaviour. Hence,
they suggested exploring EO under the influence of different environmental and situational
variables that would yield useful insights on the initiation of the entrepreneurial process.
Even at the firm level, the presence of one or more dimensions of EO may define the
entrepreneurial attributes, but the future intentions and behaviour are always shaped by
contextual and situational antecedents (Urban and Verachia, 2019). According to Harris and
Gibson (2008), the facets of entrepreneurial competencies can be learnt. This concept is
further reinforced, as entrepreneurship education has been found to foster entrepreneurial
aptitude and orientation, thus promoting entrepreneurial intent and behaviour of university
students (Ferreira and Trusko, 2018). However, studies have found a significant difference
in the IEO of students belonging to different academic disciplines (Franco et al., 2010;
Tackey and Perryman, 1999). Similarly, students with prior entrepreneurial experience were
found to have higher IEO score than those without any entrepreneurial experience
(Harris and Gibson, 2008; Taatila and Down, 2012). Furthermore, the entrepreneurial
propensity of students also differs across student samples of different countries and
entrepreneurial contexts. For example, Levenburg and Schwarz (2008), in their study, found
that Indian students have a higher entrepreneurial propensity than the US students. In
another study, on Turkish university students, Gürol and Atsan (2006) found that very less
percentage of students (18 per cent) showed entrepreneurial propensity. Thus, an
individual’s EO, which is considered as an entrepreneurial competency (Koe, 2016), is
significantly influenced by learning from educational systems, socialisation and the
university context (Farashah, 2013; Ferreira and Trusko, 2018; Lüthje and Franke, 2003).
Ozaralli and Rivenburgh (2016) advocated that an individual’s entrepreneurial intention
can be shaped by his/her perception of support and barriers to start the new venture,
cultural values and the contextual environment. Thus, assessing the key determinants in the
entrepreneurial context that affects the IEO of university students and fosters their EIs is
fundamental to understand the inception of the entrepreneurial process. The results can
provide valuable insights on an individual’s perception of his/her surrounding context,
which influences his/her cognitive and affective process to become an entrepreneur
(Canever et al., 2017; Díaz-Casero et al., 2012; Ferreira and Trusko, 2018).
ET Although personal and contextual antecedents affecting the entrepreneurial intent of an
61,6 individual had been a key issue of research for quite a long time, there is a conspicuous lack
of studies that have considered the impact of perceptual drivers like attitudes or orientation
on EIs. Only a few studies have investigated the influence of perceptual drivers like
attitudes and orientation on students’ intentions towards being entrepreneurs (Díaz-Casero
et al., 2012; Farashah, 2013; Ferreira and Trusko, 2018; Franke and Lüthje, 2004). Moreover,
722 the results are somewhat inconsistent because it is not known in most contexts whether
these contextual antecedents drive the students’ intentions towards starting a new business
or not (Canever et al., 2017; Fini et al., 2012; Popov et al., 2019; Schwarz et al., 2009).
Although scholars have acknowledged that the IEO of students is significantly affected
by educational background (Franco et al., 2010), experiential entrepreneurship education
(Lindberg et al., 2017), university environment (Farashah, 2013; Ferreira and Trusko, 2018),
entrepreneurial context (Gürol and Atsan, 2006; Popov et al., 2019), cultural differences
(Levenburg and Schwarz, 2008) and situational antecedents (Covin and Lumpkin, 2011),
there is a negligible attempt to empirically gauge their impact on IEO, which is central to
understand the decision-making process of an individual.
In order to bridge this gap, the present study empirically probes and validates the impact
of contextual antecedents acknowledged by previous studies across multi-country contexts
(Engle et al., 2011; Ozaralli and Rivenburgh, 2016; Trivedi, 2016; Turker and Selcuk, 2009),
on the entrepreneurial proclivity of university graduates. However, as suggested by
entrepreneurial learning theories (Krueger, 2017), these contextual factors do not affect
students’ cognition directly, rather they shape their perception towards the favourable or
unfavourable evaluation of the entrepreneurial career (Trivedi, 2016). This study adopts a
novel attempt to investigate and validate IEO as the perceptual driver of entrepreneurial
intent, which is influenced by the contextual antecedents of these young aspiring
entrepreneurs. The relevance of the contextual factors under study is discussed in the
following section.
2.2.1 Access to financing. According to the past research evidence (Covin and Lumpkin,
2011; Zou et al., 2009), the availability of financial resources or startup capital acts as a
significant antecedent to entrepreneurial proclivity at the firm level, which also acts as a
strong stimulus at individual level, as pointed out by vaious studies (Covin and Lumpkin,
2011; Indarti et al., 2010; Sandhu et al., 2011). Therefore, Cetindamar et al. (2012) emphasised
that accessible financial capital boosts the confidence of the entrepreneurs to start, manage
and succeed in their entrepreneurial pursuit. This perceived linkage between financial
capital and entrepreneurial propensity has convinced researchers to accept it as one of the
most critical antecedents in fostering entrepreneurial activities. These startup capitals can
be obtained from multiple sources such as personal resources, seed funding, venture capital
funding and bank loans, etc. (Farooq, 2018; Kristiansen and Indarti, 2004). Although, access
to financing or availability of capital can undoubtedly foster one’s favourable inclination
towards entrepreneurship (Farooq et al., 2018; Indarti et al., 2010; Pruett et al., 2009; Sandhu
et al., 2011), a recent study by Pruett (2012) in the USA obtained a non-significant
relationship between the two. Since these results are somehow inconsistent, the following
hypothesis is proposed to investigate the above relationship:
H2. Access to financing positively affects the entrepreneurial orientation of individuals
to adopt an entrepreneurial career.
2.2.2 Access to business information. The aspiring entrepreneur actively engages in
gathering information, because it is indispensable for initiation, growth and success of the
nascent entrepreneurial ventures (Kristiansen and Indarti, 2004; Zhao et al., 2011).
Accessibility and use of business information about prospective customers, the market,
technological solutions, sources of human and financial capital, business competitors and
government regulations before starting a business is crucial for sustainable growth and Role of
achieving competitive advantage (Indarti et al., 2010; Kristiansen, 2002; Kristiansen and contextual
Indarti, 2004). Hence, the decision to start a business is made through a cognitive process antecedents
affecting the perception of feasibility, which is mitigated through accessible and accurate
information about the proposed business and its surrounding context (Altinay et al., 2016;
Franke and Lüthje, 2004; Indarti et al., 2010). A study by Keh et al. (2007) on SMEs found EO
to have a significant impact on firm’s performance and validated that the information 723
pertaining to the business context can significantly affect the marketing-mix decisions that
implicate the firm’s performance. Similarly, IEO being an individual’s perspective involving
strategic decision-making process to adopt an entrepreneurial career may be affected by
information acquisition and utilisation.
The accessibility of business information, therefore, may favourably influence the EO of
the nascent entrepreneurs, leading to the following hypothesis:
H3. Access to business information positively affects the entrepreneurial orientation of
individuals to adopt an entrepreneurial career.
2.2.3 Social networks. Entrepreneurs develop and utilise their social networks in terms of
personal and professional networking (Kristiansen and Indarti, 2004), which plays a critical
role in the acquisition of necessary resources such as financing, human resource and
logistics, expertise and encouragement essential for survival and growth of nascent
entrepreneurial venture (Farooq et al., 2018; Indarti et al., 2010; Sandhu et al., 2011; Shiri
et al., 2012). Past literature concurrently agrees that social network size or numbers and tie
strength of an individual have a significant impact on the entrepreneurial intention,
behaviour and success (Farooq, 2018; Indarti et al., 2010; Quan, 2012; Sandhu et al., 2011).
Moreover, studies have empirically validated that a strong social network can ensure
regular inflow of resources for initiation of the venture (Farooq, 2018; Sequeira et al., 2007;
Shiri et al., 2012) and encouragement, which mitigates their risk perception (Kristiansen and
Indarti, 2004), thereby affecting their decision to choose an entrepreneurial career. In a
recent study by Shiri et al. (2012) on agriculture university students, the social support
received from family, friends, university, etc., has a significant positive effect on their
perceived desirability towards entrepreneurship instead of their intention directly. Schwarz
et al. (2009), as well as Fayolle et al. (2010), have therefore emphasised to investigate the
entrepreneurial process as a socially embedded process wherein the social networks of an
individual should be included to analyse the EO of individuals at the verge of making their
career decisions.
Thus, personal and professional social networks can be presumed to have a significant
positive impact on the individual’s perceived desirability towards an entrepreneurial career,
leading to our fourth hypothesis:
H4. Social networks of individuals have a positive effect on their entrepreneurial
orientation to adopt an entrepreneurial career.
2.2.4 University support. According to past research evidence (Engle et al., 2011; Nabi and
Liñán, 2013; Trivedi, 2016), university students’ decision to adopt entrepreneurship is
significantly affected by the perceived support or barriers prevalent in the university’s
context. Often, the education imparted (Franco et al., 2010; Farashah, 2013; Lindberg
et al., 2017; Robinson and Stubberud, 2014) and a favourable university environment
(Farsi et al., 2014) serve as the key drivers in nurturing the entrepreneurial competencies of the
students, thereby steering their EIs (Fayolle and Liñan, 2014; Ferreira and Trusko, 2018;
Saeed et al., 2015). On the contrary, a hostile entrepreneurial environment, e.g. lack of technical
skills and restrictive university context, is counterintuitive to the entrepreneurial spirit of
students. This is because it oppresses their EIs, irrespective of the students’ favourable
ET orientation towards an entrepreneurial career (Díaz-Casero et al., 2012). According to Iglesias-
61,6 Sánchez et al. (2016), the university plays a prominent role in developing students’ perception,
competency, confidence and conviction by providing cross-curricular courses augmented with
specific training on venture creation and creating a culture of entrepreneurship. Some scholars
(Farsi et al., 2014; Fayolle and Liñan, 2014) found a significant relationship between university
support and EO, whereas some scholars (Gurel et al., 2010; Schwarz et al., 2009) could not find
724 any significant relationship between the above two. Such conflicting results imply that a
supportive university context, though essential, may not be the sufficient condition to impact
students’ perception or orientation (Kraaijenbrink et al., 2009). Thus, to gauge the impact of
university support on students’ EO, the following hypothesis is proposed:
H5. Supportive university environment positively affects the entrepreneurial orientation
of students to adopt an entrepreneurial career.

2.3 Research model

Based on the theory and proposed hypothesis, the research model presents the contextual
antecedents affecting the EO of individuals, which, in turn, affects their entrepreneurial
intention. The hypothesised model includes contextual antecedents such as access to
financing (FIN), access to business information (INF), social networks (SNT), university
support (UNS), as well as IEO and entrepreneurial intention (EI) as dependent variables.
Figure 1 shows the research model with arrows representing the hypotheses.

3. Methodology
3.1 Sample and data collection
Purposive sampling technique was used for this study with an objective to select a sample
that can yield the most comprehensive understanding of the object of study. This sampling
method was deployed to collect responses from the final-year engineering students across
two Centrally Funded Technical Institutes (CFTIs) in India during the academic year
2016–2017. The rationale for selecting engineering students is that we are trying to assess

ACCESS TO
FINANCING

H2

ACCESS TO BUSINESS
INFORMATION

H3
INDIVIDUAL H1 ENTREPRENEURIAL
ENTREPRENEURIAL INTENTIONS
ORIENTATION
H4
SOCIAL
NETWORKS

H5

Figure 1.
Proposed UNIVERSITY
research model SUPPORT
the behavioural intention behind technology-based startup creation due to the significant Role of
contribution made by them towards economic development (Sánchez and Sahuquillo, 2012). contextual
A volume of past research, such as Koe (2016), Turker and Selcuk (2009) and Urbano et al. antecedents
(2010), argued in favour of studying university students having formal university education,
thus making them the most potential individuals to become entrepreneurs due to their
involvement in the career choice decision-making process. Therefore, investigating their
predisposition towards choosing an entrepreneurial career instead of salaried employment 725
would enable us to understand the correlation among the chosen constructs more elaborately.
A structured survey questionnaire was developed for collecting responses to measure
the correlation among the independent and dependent variables of the proposed model.
The questions in this section were formulated as sentences to capture the responses on a
five-point Likert-scale, ranging from 1, indicating “completely disagree”, to 5, indicating
“completely agree”. The questionnaires were distributed to 900 undergraduate engineering
final-year students of two CFTIs during the academic year 2016‒17 (National Institute of
Technology Rourkela and Indian Institute of Technology Kharagpur). The responses were
screened to eliminate missing data and skewed responses, finally yielding 510 responses
found to be useful for further analysis.

4. Data analysis and results

4.1 Descriptive analysis
The descriptive statistics denoting the mean, standard deviation and correlation coefficients
of the constructs are given in Table I. The results confirm that the inter-construct
correlations are significant and positive.

4.2 Analytical approach

The proposed hypothesised model, as shown in Figure 1, proposed that the factors affecting
IEO and intentions (EI) of an individual in the entrepreneurial environment are as follows:
access to financing (FIN), access to information (INF), social networks (SNT) and university
support (UNS). These contextual factors are assumed to steer the orientation of an individual
towards entrepreneurship, which, in turn, impacts the EIs. A two-step analytical approach
was applied for analysing the reliability and validity of constructs, followed by assessment
and validation of the proposed hypotheses through structural equation modelling (SEM)
using SPSS (24.0) and AMOS (24.0) software. In the first step, assessment of the measurement
model was conducted to ascertain the validity and robustness of constructs depicted by the
goodness-of-fit (GFI) indices for the constructs under investigation, followed by the second
step in which SEM was conducted for empirical analysis of the hypothesised relationship
between the constructs of the path model by path estimates.
4.2.1 Construct reliability and validity. According to Hair et al. (2011), “The first step is to
examine the measures’ reliability and validity according to certain criteria associated with

Correlations
Constructs Mean SD EI IEO FIN INF SNT UNS

EI 4.023 0.729 1.000

IEO 3.930 0.898 0.422*** 1.000
FIN 3.515 0.994 0.380*** 0.528*** 1.000
INF 3.493 0.999 0.386*** 0.522*** 0.444*** 1.000 Table I.
SNT 3.659 1.056 0.386*** 0.451*** 0.367*** 0.462*** 1.000 Means, standard
UNS 3.654 0.939 0.421*** 0.559*** 0.573*** 0.538*** 0.411*** 1.000 deviations and
Note: ***Denotes significance level at po 0.001 correlation coefficients
ET formative and reflective measurement model specification”. To assess the construct
61,6 validity, the study adopted face validity, convergent validity and discriminant validity.
Face validity refers to the process in which the measurement instrument measures the
variables or constructs that it is supposed to measure, which is established by taking
scales from the existing studies and adapting to the present context. The measures of the
dependent variable, EIs, were developed by adopting a six-item scale taken from Liñan
726 and Chen’s (2009) work. The measures for the contextual antecedents such as access to
financing and access to business information, each with four items, were adapted from the
scales used by Kristiansen and Indarti (2004). The four-item scale for social networks
construct was adapted from Sequeira et al. (2007), and for assessing the impact of the
University support, a four-item scale used by Schwarz et al. (2009) was adopted. Although
scales adapted from Rauch et al. (2009) have been extensively used for measuring the EO
at the firm level in multiple studies, there is a paucity of research for mapping IEO. Thus, a
recent IEO scale suggested by Bolton and Lane (2012), comprising of ten items, was
adapted for this study with some modification, reducing the number of items to 8, on the
basis of the feedback from focussed group discussions. Thus, the final test instrument
comprising of 30 items deployed to measure the six constructs in the hypothesised model
was examined for robustness through exploratory factor analysis, followed by
confirmatory factor analysis (CFA) (Hair et al., 2010; Ho, 2013). To observe the total
variance explained by each factor, only those with eigenvalues greater than 1 and factor
loadings more than 0.5 were retained, which validates this measurement instrument
comprising of 23 items (Hair et al., 2010; Ho, 2013).
The result of scale reliability for the instrument comprising of 23 items depicted by
Cronbach’s α is 0.932, and the Cronbach’s α value for the individual constructs (ranged
between 0.841 and 0.894.) is shown in Table II, which is found to be acceptable and
validates that the measurement instrument is consistent (Nunnally and Bernstein, 1994).
According to the two-step analytical approach suggested by Hair et al. (2010), CFA was
deployed in the first step to probe the reliability, validity and GFI statistics of the measures,
followed by testing of hypotheses through SEM in the second step. The three indicators of
convergent validity are standardised estimates ( factor loadings), average variance
extracted (AVE) and composite reliability (CR). Table II represents the results pertaining to
the measurement model.
Hair et al. (2010) suggested that a construct should have standardised estimates of 0.5 or
higher and must be statistically significant; adequate convergence is confirmed when AVE
is 0.5 or higher, and reliability of the scale is validated when CR is 0.7 or higher. The results
of standardised estimates, AVE and CR, being within the specified thresholds confirm the
convergent validity. As mentioned under the diagonal values of Table III, the square root of
the AVE values for all the constructs is greater than the corresponding inter-construct
correlations, which supports the discriminant validity of the constructs (Hair et al., 2010).
Further, the inter-construct correlations among the six constructs are moderate to low, thus
refuting any multicollinearity concerns.
The GFI statistics of the fully constrained model with six constructs, as presented in
Table II, indicate adequate model fit ( χ2 ¼ 468.08; df ¼ 214; p o0.001; χ2/df ¼ 2.187;
GFI ¼ 0.927; comparative fit index (CFI) ¼ 0.965; normed fit index ¼ 0.937; Tucker‒Lewis
coefficient index (TLI) ¼ 0.958; relative fit index (RFI) ¼ 0.926; root mean square error of
approximation ¼ 0.048) and the score of χ2/df ¼ 2.187 (i.e. o3) is acceptable (Hair et al.,
2010). Thus, the measurement model represents decent construct validity and apposite
psychometric properties.
4.2.2 Testing of hypotheses. The theoretical model assumes that the contextual factors
influence an individual’s EO, thus steering his/her EIs. Structural equation modelling is a
Constructs Measurement items Standardised estimates AVE CR p-value
Role of
contextual
Access to financing FIN1 0.848 0.685 0.867 0.000 antecedents
FIN2 0.784 0.000
FIN3 0.748 0.000
Access to business INF1 0.818 0.639 0.841 0.000
information INF2 0.777 0.000
INF3 0.733 0.000 727
Social networks SNT1 0.864 0.684 0.866 0.000
SNT2 0.834 0.000
SNT3 0.762 0.000
University support UNS1 0.771 0.613 0.862 0.000
UNS2 0.751 0.000
UNS3 0.762 0.000
UNS4 0.732 0.000
Individual entrepreneurial orientation IEO1 0.766 0.623 0.892 0.000
IEO2 0.794 0.000
IEO3 0.762 0.000
IEO4 0.760 0.000
IEO5 0.749 0.000
Entrepreneurial intentions EI1 0.829 0.628 0.894 0.000
EI2 0.814 0.000
EI3 0.785 0.000
EI4 0.826 0.000
EI5 0.719 0.000
Notes: AVE, average variance extracted; CR, composite reliability of the construct (1 o CMIN/df range o3, Table II.
po 0.05; GFI, NFI, RFI, IFI, TLI, CFI W 0.9 or close to 1 indicates a good fit; RMSEA o0.05 indicates a close Measurement
fit (Hair et al., 2010)) model results

Constructs EI IEO FIN INF SNT UNS

EI (0.792)
IEO 0.459 (0.789)
FIN 0.424 0.600 (0.828)
INF 0.433 0.596 0.521 (0.799)
SNT 0.432 0.505 0.414 0.530 (0.827)
UNS 0.456 0.633 0.683 0.612 0.488 (0.783) Table III.
Note: The values in the diagonal represent the squared root estimate of AVE Discriminant validity

systematic approach that offers a simultaneous assessment of an entire model with all the
interrelationships, which enables validation of the consistency of the model along with the
data by removing measurement errors (Byrne, 2009).
After obtaining a satisfactory measurement model, the second step in SEM analysis
was undertaken for evaluation of the structural model. The GFI statistics indicated that
the structural model (Figure 2) demonstrated adequate fit to the data ( χ2 ¼ 511.84;
df ¼ 218; p o 0.001; χ2/df ¼ 2.348; GFI ¼ 0.921; CFI ¼ 0.959; TLI ¼ 0.953; RFI ¼ 0.921;
RMSEA ¼ 0.051).
As per the path coefficients denoted in Figure 2 and β estimates and critical ratio (CR or
t-value) values mentioned in Table IV, the proposed hypotheses have been empirically
validated. According to the results, IEO was found to have a strong positive impact on EI
(H1: β ¼ 0.491), thus supporting the first hypothesis. The rest four hypotheses depicting the
influence of the contextual antecedents under study (UNS, FIN, INF and SNT) on IEO were
ET
ACCESS TO
61,6 FINANCING

0.248

ACCESS TO BUSINESS
728 INFORMATION

0.238
INDIVIDUAL 0.491 ENTREPRENEURIAL
ENTREPRENEURIAL INTENTIONS
ORIENTATION
0.169
SOCIAL R 2 = 0.24
2
NETWORKS R = 0.54

Figure 2.
Structural equation 0.247
model with
standardized UNIVERSITY
coefficients SUPPORT

Hypotheses Relationship β estimate SE CR (t-value) p-value Results

H1 IEO → EI 0.491 0.040 10.157 *** Accepted

H2 FIN → IEO 0.248 0.058 4.313 *** Accepted
H3 INF → IEO 0.238 0.053 4.227 *** Accepted
H4 SNT → IEO 0.169 0.039 3.545 *** Accepted
Table IV. H5 UNS → IEO 0.247 0.069 3.872 *** Accepted
Inferences drawn Notes: n ¼ 510. R2 (entrepreneurial orientations) ¼ 0.54; R2 (entrepreneurial intentions) ¼ 0.24. ***Denotes
on hypotheses significance level at p o0.001

found to be highly significant and positive. Whereas three of these antecedents, UNS
(H2: β ¼ 0.247), FIN (H3: β ¼ 0.248) and INF (H4: β ¼ 0.238), were seen having a stronger
influence on IEO, one of the factors, SNT (H5: β ¼ 0.169), seemed to have a comparatively
weaker impact on IEO.
The structural model evaluation is not complete without assessing the explanatory
capacity of the model denoted by R2-statistic, which depicts the percentage of the total
variance of each endogenous construct explained by its predictors. The model explains
54 per cent of the variance in the latent construct IEO on the basis of the four contextual
antecedents, whereas 24 per cent of the variance in EIs is explained by the contextual
antecedents and IEO. The result converges with previous studies using linear models, which
explained less than 40 per cent of the variance (Liñan and Chen, 2009; Schlaegel and Koenig,
2014). As discussed in the earlier sections, the intent to choose an entrepreneurial career is
an outcome of the interplay among various factors (personality, environmental context as
well as demographics). Hence, the low explanatory power of the model can be attributed to
non-inclusion of other factors in the entrepreneurial context of the students such as their
personality, attitudes, gender, family background, role models or cultural factors.

5. Discussion
EO has been referred to as the “strategy making processes that provides organisations with
a basis for entrepreneurial decisions and actions” (Rauch et al., 2009). A considerable volume
of entrepreneurial research has examined the concept of EO in fostering EIs (Kantur, 2016), Role of
performance (Franco and Haase, 2013; Rauch et al., 2009) and success (Frese et al., 2002) at contextual
the firm level, and it has been extensively studied both theoretically and empirically antecedents
(Bolton and Lane, 2012). However, at individual level, very few studies focussing on IEO
(e.g. Bolton and Lane, 2012; Ekpe and Mat, 2012; Ibrahim and Lucky, 2014; Koe, 2016;
Robinson and Stubberud, 2014) have probed and validated the impact of EO on EIs,
business performance (Chien, 2014) and success (Bolton, 2012) in the entrepreneurial career 729
of individuals. Most of the above scholastic works have assessed the reliability and validity
measures of the IEO construct and its dimensions at the individual level and tested their
explanatory capacity in linear relationships, neglecting the other antecedents affecting the
dimensions of IEO. Therefore, scholars (Bolton and Lane, 2012; Popov et al., 2019) have
urged for further research to examine the relationship between IEO and intentions in
presence of other antecedents across varied contextual settings.
Drawing upon the suggestion of scholars (Bolton, 2012; Bolton and Lane, 2012; Robinson
and Stubberud, 2014; Popov et al., 2019), this study adopts an unconventional approach to
introduce and validate IEO in a comprehensive model to examine the relationship between
IEO and EIs under the influence of other contextual antecedents in a university setup.
In order to understand the decision-making process of the budding entrepreneurs, this
study incorporated four contextual factors from the entrepreneurial environment into a
conceptual framework and explored whether these antecedents have any impact on the IEO
and EIs of technical university students.
Previous researchers (Farooq et al., 2018; Kristiansen and Indarti, 2004; Pruett et al., 2009;
Sandhu et al., 2011) have stressed on the accessibility of resources, such as financial capital,
information about the business environment, human and social capital significantly
affecting the EIs of aspiring entrepreneurs. However, they evaluated the direct impact of the
availability of resources on EIs, neglecting the role of perceptual drivers. According to the
results of this study, access to financing has emerged as the strongest factor affecting IEO.
The findings also validate that the availability or lack of financial resources affects the
perception of support or barriers of the students, thus influencing their innovativeness,
proactiveness and risk perceptions and steering their orientation towards entrepreneurial
behaviour, similar to the findings of Eggers et al. (2013), a study which was done on SME’s
growth. In other words, inaccessibility of entrepreneurial resources may lead to anxiety,
a lower expectation of success and a diminished affinity towards risk, thus curbing the EO
and behavioural intentions at the individual level (Cetindamar et al., 2012; Farooq et al.,
2018). Contrary to the findings of previous research works (Farooq et al., 2018; Sandhu et al.,
2011), social networks, even though with a significant positive impact, seemed to have the
weakest impact on IEO in comparison to access to financing and business information,
which can be attributed to the independent decision-making mindset of the aspiring
entrepreneurs. These results imply that adopting an entrepreneurial career, being a
consciously planned process, is not likely to be affected by the opinions of others to a greater
extent, which furthers the claims of past researchers (Fini et al., 2012; Iglesias-Sánchez et al.,
2016; Nabi and Liñán, 2013).
Extending upon the scholastic invitation of researchers (Bolton and Lane, 2012; Ferreira
and Trusko, 2018; Popov et al., 2019), this study was carried out on university students to
analyse the role of the entrepreneurial context in affecting their IEO. Many studies in the
past (Franke and Lüthje, 2004; Iglesias-Sánchez et al., 2016; Turker and Selcuk, 2009)
investigated career choice intentions of university students being at the decisive point of
choosing their careers. Some of these studies (Autio et al., 2001; Turker and Selcuk, 2009)
argued in favour of direct influence of distal antecedents on intentions, neglecting the
cognitive process, whereas the recent scholastic works (Iglesias-Sánchez et al., 2016; Nabi
and Liñán, 2013; Robinson and Stubberud, 2014) advocated in favour of perceptual drivers.
ET Therefore, cognitive models with attitude or orientation as perceptual drivers have been
61,6 reinforced in the recent works (Engle et al., 2011; Nabi and Liñán, 2013; Ozaralli and
Rivenburgh, 2016; Robinson and Stubberud, 2014; Shiri et al., 2012) due to their greater
predictive capacity in explaining the complex cognitive process of developing intentions
and subsequent behaviour. Some studies conducted on university students’ EIs
(Canever et al., 2017; Gurel et al., 2010; Ismail et al., 2009; Schwarz et al., 2009) could not
730 find a significant relationship between university support and EIs. The findings of this
study, contrary to those of the above studies, conclude that a supportive university
environment is inevitable for the aspiring entrepreneurs to nurture their entrepreneurial
competencies and boost their confidence. University support has emerged as the second
strongest antecedent affecting the EO of students, thereby fostering their intentions to
choose an entrepreneurial career. Hence, the results of this empirical analysis validate that
universities play a decisive role by providing students with necessary education, training
and venture creation support (Ferreira and Trusko, 2018; Iglesias-Sánchez et al., 2016;
Trivedi, 2016), thus nurturing their entrepreneurial skills and affecting their strategic
decision-making process to adopt an entrepreneurial career.

6. Conclusion
This study explores the role of contextual antecedents and IEO in predicting university
students’ EIs. The results empirically validate that access to resources and entrepreneurial
support favourably drive the entrepreneurial proclivity of university students. Access to
startup capital, support from social networks, availability of relevant business information,
and supportive university context have the ability to influence the “strategic decision-
making processes” of the students and motivate them to venture into an otherwise uncertain
occupation of entrepreneurship.
Recently, the scholars exploring the IEO dimensions (e.g. Bolton and Lane, 2012;
Farashah, 2013; Fayolle et al., 2010; Ferreira and Trusko, 2018; Koe, 2016; Taatila and Down,
2012) invited further exploratory research to be carried out in a university context to assess
the EO of the university students. Extending upon their research implication, the present
analysis empirically investigates university students’ orientation towards the
entrepreneurial career. Majority of the contemporary studies (Lindberg et al., 2017; Popov
et al., 2019; Taatila and Down, 2012) assessing IEO have reiterated that further research is
inevitable in diverse cultural and contextual settings to measure the explanatory capacity of
the IEO construct. The empirical evidence provided by this study supports the proposition
of Popov et al. (2019), and establishes that the correlation among the contextual factors and
IEO in a diverse contextual backdrop of the Indian universities shall lead to a better
understanding of students’ EIs, explained by their IEO.
Moreover, the universities would have this “Individual entrepreneurial orientation”
mapping tool at their disposal to reallocate their resources, update their curricula, and
structure their education and training programmes more effectively to motivate the
students and provide them with required entrepreneurial skills and resources to adopt an
entrepreneurial career (Bolton and Lane, 2012; Iglesias-Sánchez et al., 2016; Lindberg et al.,
2017). As suggested by Taatila and Down (2012), quantifying the differential IEO levels in
students would enable the university administrators to create a more enriching learning
environment by devising customised course modules for different student groups and
improving their selection procedure on the basis of their IEO score. The course pedagogy
designed for student groups with lower IEO score should focus on motivating students
towards entrepreneurship by reinforcing entrepreneurial capabilities such as risk-taking,
innovativeness and proactiveness (Lindberg et al., 2017; Taatila and Down, 2012). On the
contrary, students with higher IEO score should be trained on actual entrepreneurial skills
like product/service development, market research, practical problem solving and venture
management skills. The significant positive relationship between contextual antecedents Role of
and IEO implies that the universities might seek to transform into “entrepreneurial contextual
ecosystems” by the integration of the academia with other institutions, industries, venture antecedents
capitalists and businesses to provide training, resources, business information and support
to foster students’ entrepreneurial skills and capabilities for motivating them towards
adopting an entrepreneurial career (Farooq, 2018; Iglesias-Sánchez et al., 2016). The findings
of this study have a likely potential to assist university administrators and policymakers to 731
allocate their resources, develop strategies and effective policies, which may provide the
essential contextual pillars nurturing the entrepreneurial spirit of students. The findings of
this study validate the proposition of previous studies that the availability of financial
capital, social and business resources (Farooq et al., 2018; Sandhu et al., 2011) as well as a
supportive university context (Ferreira and Trusko, 2018; Iglesias-Sánchez et al., 2016;
Trivedi, 2016) will stimulate the entrepreneurial activity by university graduates, thus
accelerating the economic growth of the country (Ács et al., 2014; Bosma et al., 2018).
Although the present study provides several important findings, some possible
limitations are as follows: first, the measurement of IEO only included and validated three
dimensions (risk-taking, innovativeness and proactiveness), thus leaving scope for future
studies to incorporate broader dimensions to develop a more evolved measurement tool.
Second, the study analysed the impact of only a few contextual factors, on IEO. Future
studies may incorporate other factors such as personality, demographics or other contextual
factors to develop a more comprehensive understanding of their impact on IEO, leading to
the development of EIs. Third, the study being cross-sectional cannot depict the direction of
causality of the contextual antecedents in predicting IEO, which, in turn, affects the
performance and success of the individual entrepreneurs in their entrepreneurial journey.
Although studies in the past validated IEO to be strongly associated with performance at
the firm level (Franco and Haase, 2013; Rauch et al., 2009), the strength of the relationship
between IEO and entrepreneurial performance at the individual level is yet to be explored
and empirically validated. Longitudinal studies are essential to precisely map the effect of
IEO on the performance and success of the nascent entrepreneurs over time. This study,
being carried out on students of Indian universities, may be generalisable to such university
contexts across other developing countries. Given the significant difference in the political,
socio-economic and cultural contexts among these countries, the framework can be probed
across these diverse contexts of developing nations for generalisations. However,
researchers (Iakovleva et al., 2011; Trivedi, 2016) emphasised that there is a significant
difference in the environmental context of developing and developed nations, which is also
reflected in differential intentions towards an entrepreneurial career and the key
antecedents between developing and developed nations. Hence, this empirically validated
model can be used for comparative analysis between developing and developed country
contexts to assess the impact of the diverse range of antecedents and explanatory power of
IEO construct in predicting EIs.

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Further reading
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Corresponding author
Swagatika Sahoo can be contacted at: asr.swagatika@gmail.com

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