The nature of an entrepreneurial university is such that there is an expectation of external engagement with industry, the commercialisation of research and the development of entrepreneurially minded graduates. The organisational culture at department and institutional level should reflect this conception. Therefore, the entrepreneurial orientation of the university becomes a key indicator of the entrepreneurial university (Guerrero, 2014). Todorovic et al. (2011) describe development of a scale, ENTRE-U, that measures the entrepreneurial orientation (EO) of university departments. EO is the “inclination of top management to take calculated risks, to be
innovative, and to demonstrate proactiveness” (Morris et al., 1987, p 41). The research provides support for the assertion that what it means to be “entrepreneurial’’ likely varies between industries and universities, and develops a new scale, ENTRE-U, that successfully predicts spinout and patenting activity in university departments. The exploratory factor analysis suggests that university entrepreneurial orientation consists of four
dimensions- Research Mobilization, Unconventionality, Industry Collaboration and University Policies.
Research Mobilization refers to an emerging paradigm for the research process in which researchers engage external stakeholders at all stages of the research process, especially in making sure that research outcomes are communicated to multiple audiences in ways that are easily understood, so the results are more readily transferred and applied by stakeholders.
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Unconventionality also focuses on research, especially looking for new opportunities and making sure research is useful and benefits stakeholders. However, the items also suggest doing things that are unconventional,
and/or innovative. The items do not directly refer to sources of risk (or what is at risk, for example, reputation, resources, or career advancement).
Industry collaboration refers to the department, faculty, and student engagement with the related industry.
University policies relate to the general culture of the university, especially being “responsive to new ideas and innovative approaches’’, having a
“bottom-up’’ approach to policy development, and good fit between university policies and department objectives.
The results point to the importance of an entrepreneurial orientation as a partial explanation for the heterogeneity between departments, even within the same university, in commercialization outcomes.
Kiani Mavi (2014) provides a comprehensive criteria set for evaluation of entrepreneurial universities. The environmental and internal factors of entrepreneurial universities as developed by Guerrero and Urbano (2010) were used as the measurement criteria. The author then applied fuzzy analytic hierarchy process (FAHP) for prioritizing critical factors and fuzzy technique for order preferences by similarity to ideal solution (FTOPSIS) for ranking alternative universities with regard to their entrepreneurialism.
An interesting collaboration which further underlines the importance of research on the entrepreneurial university is the HEInnovate collaboration
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between the EU and the OECD. They have developed a self-assessment tool for HEIs to consider the entrepreneurial nature of their higher education environment covering the below eight areas for assessment:
• Leadership and Governance
• Organisational Capacity: Funding, People and Incentives • Entrepreneurial Teaching and Learning
• Preparing and Supporting Entrepreneurs • Digital Transformation and Capability • Knowledge Exchange and Collaboration • The Internationalised Institution
• Measuring Impact
Mahdavi, Mazdeh et al. (2013) feel little research has focused on evaluation frameworks for measuring universities’ entrepreneurial intensity and propose an evaluation framework for determining the performance of entrepreneurship development initiatives in universities. The measure Entrepreneurial Intensity (EI) was introduced by Morris and Sexton (1996) and considers varying levels of entrepreneurship.
Figure 2.20: Categorisation of evaluation criteria of Entrepreneurial Intensity (EI) (Mahdavi Mazdeh et al., 2013)
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The authors use a hybrid multimethod methodology consisting of Delphi, Analytic Network Process (ANP), and the VIKOR method developed to evaluate the EI performance of (Iranian) universities and to provide some directions to improvements. The goal of this research is to facilitate universities in bridging the gap between actual and desired EI performance. The Delphi method is used to localize and reduce the number of criteria extracted from a deep literature review. After that, a group approach to ANP was utilized as an evaluation method to derive the weights of each criterion. Next, the evaluation data were gathered through a questionnaire, and, finally, the compromise ranking of universities was calculated using the VIKOR Method. Finally, weight-variance analysis (WVA) is used to suggest improvement actions.
Cullen et al. (2009) present a framework to measure the success and impact of knowledge transfer activities in UK universities (Figure 2.21). In this model, knowledge transfer activities are effectively in the middle of this
innovation system, with research, from which knowledge originates, at one end, and economic activity and impact at the other.
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Figure 2.21: Knowledge Transfer within the Innovation Ecosystem (Cullen et al., 2009)
Cullen et al. (2009) adapted a social impact model to clarify what is meant by impact in the context of knowledge transfer, and how to measure it. This knowledge transfer impact model is from the perspective of the universities, given that they are responsible for performing the actual knowledge transfer (Figure 2.22). This shows that impact can be split between gross impact and net impact. Both originally result from an input, which, in this case, is a particular knowledge transfer activity of a university, (e.g. consulting or licensing). Following analysis of the available UK data and both frameworks, Cullen et al. (2009) have come up with a set of measures of both the quantity and quality of the knowledge transfer mechanisms.
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Figure 2.22: Model of Impact in the Knowledge Transfer Ecosystem (Cullen et al., 2009)
Typically, the efforts to empirically measure the economic impact of entrepreneurial universities have focused on the measurement of inputs and outputs (such as university earnings from tech transfer) within a managed economy. Few studies have even linked entrepreneurial university activities to GDP. To date there is only one exploratory study completed which
proposes methods to measure the economic impact of entrepreneurial universities third mission activities. Guerrero, Cunningham & Urbano (2014) found a positive economic impact from the teaching, research and
entrepreneurial activities of UK universities through the use of structural equation modeling to test data from 2005-2007 collected from 147 universities which demonstrated entrepreneurial characteristics.
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2.11.5 Summary analysis of models and research gap
The models presented capture the state of the art and the
understanding of the entrepreneurial university paradigm. The modelling of the entrepreneurial university has been extensive and present an excellent framework and basis for this research. In summary, the models of the entrepreneurial university call for effective governance, the creation of physical infrastructure to support entrepreneurial activity and diversification of the funding base, the development of an entrepreneurial culture across the university, and the development of organisational units which work outside traditional university departments supportive of third mission activities including knowledge transfer and the management of intellectual property, engagement with external partners including industry and alumni and the broader entrepreneurial ecosystem. However, two gaps in the research were noted which informed and framed this research study. Firstly, as has been noted by other contributors (Klofsten et al. ,2019), while these models outline the factors and indeed the determinants in the development of
entrepreneurial universities, comment on leadership and strategic issues, as universities undertake this evolution and become more entrepreneurial, is quite limited. Secondly, the literature on the entrepreneurial university presents models and frameworks which are theoretical or quantitative in nature. A research gap exists in terms of looking at the entrepreneurial university qualitatively and understanding the evolution of entrepreneurial university from the perspective of those people tasked with managing this evolution from traditional universities to entrepreneurial universities.
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The principal theories employed – the resource based view, triple helix of innovation theory, institutional economics and the endogenous growth theory, all recognize the importance of the development of
entrepreneurial capital as a contributor to the university finance/health. The RBV, being internally focused, has been used in the models presented to identify the key internal resources of entrepreneurial universities. However, this researcher concurs with Spender (1994) and indeed Penrose (1959) that the RBV is a static theory. The RBV is a useful theoretical framework for the identification of the key resources within entrepreneurial universities but it does not consider the strategy required to manage the interaction between these resources to maximise their utility in achieving the university mission and strategic goals. This coordination of resources is referred to by Alchian and Demsetz (1972) as 'team production' who also argue that the outcome of the dynamic interaction of resources is not simply a sum of the individual outputs of each individual resource. This is reflected in the static nature of the entrepreneurial university models in the literature. Indeed, one could argue that the focus of the RBV is on the acquisition of VRIN resources rather than on their application in pursuit of the execution of a strategy. Further, the RBV does not afford the ability to develop a hierarchy of importance of the resources identified within the models developed for the entrepreneurial university.
The models presented to date offer an ‘outside in’ perspective on the development of the entrepreneurial university. To date, while semi
structured interviews have been used, there has been no phenomenological study of the lived experience within entrepreneurial universities from a
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strategic management perspective. It is hoped that this research, through capturing the lived experience of senior leaders of universities, will contribute to the field by offering an alternate ‘inside out’ perspective. Further, it is hoped that the theoretical lens of dynamic capabilities theory will offer useful insights into the coordination of resources within the entrepreneurial
university.