This paper examines how knowledge transfer (KT) indicators affect analyses on efficiency in the Higher Education sector, taking into account the characteristics of the Higher Education Institutions (HEIs). After revising the concept of third mission as a field for data development and its importance in assessing university performance, we applied various Data Envelopment Analysis (DEA) models with different specifications to 47 Spanish public universities to test whether KT indicators are relevant when evaluating the performance of HEIs in terms of their efficiency and, if so, which indicators are most suitable. Our results suggest that the effect of including KT indicators in the efficiency analyses varies from university to university according to their characteristics. The subject mix taught at the university, the focus according to each mission's relative importance within the total range of activities carried out in each university (mission mix) and the mix of their third mission activities affect the increase of the universities' efficiency scores when KT is taken into account in the analysis. This means that these factors affect the universities' position for the different efficiency scores.

multidimensional scalingapplied to data on the universe of HEIs in the United Kingdom, we show that HEIs with different institutional resources and undertaking different sets of activities prioritise their engagement with different stakeholder groups. We also confirm the complex associations between HEIs' institutional resources, activity profiles and stakeholder prioritisation strategies, which lock HEIs into configurations that are difficult to change.

Purpose The purpose of this study is to analyse how different patterns of production factors consumption of Spanish universities lead to specific technology transfer (TT) profiles (outcomes). Design/methodology/approach Adopting a resource-based view perspective (RBV), qualitative comparative analysis (QCA) is used to analyse the relationship between different combinations of resources – human resources, financial resources and support services – and various portfolios of TT outcomes – intellectual or industrial property agreements, spin-offs and TT income. Findings Results indicate that there is no unique formula of resource consumption that leads to a specific portfolio of TT outcomes. These results seem to reflect the characteristics and competencies added by universities, along with the characteristics of their socioeconomic context. From a RVB perspective, this indicates that the considered resources are substitutable. Practical implications The effectiveness of university policies is expected to vary by university, for example depending on the type of resources that is most relevant in the university’s production process. To develop competitive advantages Spanish public universities must resort to internal intangible resources or specific and inimitable combinations of the available resources. Social implications Since Spanish universities are heterogeneous and display different TT portfolios they address the needs of different users. Originality/value Previous studies have failed to acknowledge the heterogeneity among universities. To perform the analysis QCA is used, an innovative methodology in the higher education sector that enables us to purposefully acknowledge institutional diversity (in both resources and results). This allows us to indirectly take into account the capabilities of universities using a more holistic approach to evaluate their competitiveness.

Universities are organizational structures with individual activity mixes or strategies that lead to different performance levels by mission. Evaluation techniques based on performance indicators or rankings risk rewarding just a specific type of university and undermining university diversification: they usually introduce homogenising pressures and risk displacing university objectivesneglecting their socioeconomic contribution and focusing on succeeding on the evaluation system. In this study, we propose an alternative evaluation method that overcomes these limitations. We produce a multidimensional descriptive classification of universities into typologies, while analysing the relation between their institutional factors (characteristics) and their (technical) efficiency performance from a descriptive perspective. To do so we apply a bootstrap DEA-MDS analysis to data on the Spanish university system, and unlike previous studies, we include data on an important dimension of the third mission of universities (specifically knowledge transfer) in their characterisation. We identify six types of (homogeneous) universities. Results indicate that to be fairly efficient, universities may focus on teaching, knowledge transfer or overall efficiency, but always have to fairly perform in research. Additionally, results confirm the relevance of the third mission as a source of institutional diversity in Higher Education. This approach could be used to address an alternative evaluation methodology for HEIs with formative purposes, evaluating universities according to their unique characteristics for the improvement of HE systems.

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