The added value of the European university campus: challenges for collecting management information

Universities are key agents in the knowledge-based economy and their campuses are increasingly seen as resources enabling regional innovation. Previous research outlining the university campus as a European asset (Den Heijer & Tzovlas, 2014) collected various indicators about universities’ goals, finances, users and spaces across 866 European universities. This research also found limitations for comparison (e.g. differences in university types, socio-economic contexts and data collection techniques). Both, the value of such management information and challenges to collect comparable data are addressed here. This paper aims to compare campus management information (CMI) in universities of technology located in Europe’s innovative regions. This scope allows comparing campus management in universities with a similar knowledge-base and located in similar socio-economic contexts. In order to do so, this research asks: What is the current state of the tech-campus in Europe’s most innovative regions?Four perspectives of campus management were used to develop a structured survey targeting 1) university country organisations and 2) university real estate management departments. The survey containing 19 indicators across the four perspectives was sent via email in spreadsheet format. The review of documents and statistical datasets generated by country organisations was also used as data source. Available data from country documents and statistics datasets focused on one or two types of indicators. From 62 universities contacted in 12 countries, 13 universities in 8 countries agreed to participate. The respondents provided most of the indicators and/or sent links to relevant documents to retrieve them. However, the overview of the current state of the tech-campus in Europe is limited to this relatively small sample of respondents. Although the added value of the campus for universities and Europe is relevant, collecting CMI to improve this practice is still a challenge for CREM researchers. First, the indicators in our framework integrate various perspectives and their collection may be challenged by the availability of CMI in different departments. Second, some universities may lack structural information databases and do not want to share incomplete data for comparison. Last, the benefits of collecting CMI may not (yet) seem to exceed the costs of investing time on it in absence of structured databases. These lessons can be used to improve further research.