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Abstract
Purpose: The purpose of this chapter is to verify the degree of formalization and measurement of the third mission in the planning documents of European higher education institutions (HEIs). We will adopt the perspective of intellectual capital (IC) (Bezhani J Intellect Capital 11(2):179–207, 2010; Ramírez ad Gordillo J Intellect Capital 15(1):173–188, 2014) because the third mission dimensions (technology transfer innovation, continuing education, public engagement) are strictly related to the external dimensions of IC components (human capital, organizational capital, and social capital).
Design/methodology/approach: A content analysis on the planning documents of a sample of 25 European HEIs in Italy, the United Kingdom (UK), France is carried out based on a validated third mission dictionary (Göransson et al. Sci Public Policy 36(2):157–164, 2009; Loi and Di Guardo Sci Public Policy 42(6):855–870, 2015; Marhl and Pausits Eval Higher Educ 5(1):43–64, 2011; Secundo et al. Technol Forecast Soc Change 123:229–239, 2017).
Findings: Our findings confirm that despite the relevance of third mission activities for economic and social development, the lack of a comprehensive definition and measurement framework for the third mission leads to a low formalization of the third mission in university disclosure. As a consequence, the external dimension of IC is formalized and disclosed in a limited manner. Specifically, although third mission has evolved from a productive concept focused on the economic exploitation of research to a universalistic concept that also includes the social impact of university activities, the formalization of third mission is mainly related to the productive conception.
Originality/value: This chapter attempts to link the third mission and IC. As knowledge-based institutions (Sánchez and Elena J Intellect Capital 7(4):529–548, 2006), HEIs pay high attention to IC, whose external dimension can be considered strictly related to third mission. This perspective highlights the relevance of third mission within HEIs’ activities.
Implications: This chapter highlights the best-in-class experiences and provides suggestions for universities that are later adopters of third mission measures; it can further suggest the determinants for enhancing third mission disclosure to policy makers and public managers.
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The Observatory of the European HEI was established within the PRIME funded by the European Commission for the creation of management tools for research activity governance and to create a framework useful for comparing universities.
AVA requires universities to compile two Annual Self-evaluation Forms (SUA) focused, respectively, on the evaluation of teaching programs (SUA-DID, in force by 2012) and on the evaluation of departmental research and third mission activities (SUA-RES-TM, in force by 2014) (Anvur, 2015; Lumino et al., 2017).
Times Higher Education World University Ranking is the only table ranking university performance; it judges research-intensive universities across all core missions: teaching, research, knowledge transfer, and international outlook (third mission).
The European Tertiary Education Register (ETER) is a database that collects data about European universities’ characteristics, providing data at the level of individual universities.
The extraction of the documents took place in January 2018. We downloaded the most recent documents available at the date of extraction, as the documents are dated between 2009 and 2018. In the absence of a strategic plan, the integrated plan of universities has been considered in the automated content analysis.
WordStat calculates the expression frequencies for each of the retrieved documents. We restrict the number of included expressions to a maximum of 1000 items based on the computed TFxIDF index, which is the “term frequency weighted by inverse document frequency”; and it is based on “the assumption that the more often a term occurs in a document, the more it is representative of its content yet, the more documents in which the term occurs, the less discriminating it is” (Provalis Research, 2015, p. 37). Expressions have a minimum of 2 and a maximum of 5 words.