Pub Date : 2023-12-25DOI: 10.1108/mbe-09-2023-0140
Isabella Nocella, R. Linzalone, S. Ammirato, A. M. Felicetti
Purpose Large scale research infrastructures (LSRIs) are rising in the competitive and globalized research environment, since they offer to external researchers-users, inputs and services for cutting-edge, large scale researches. Such researches would not be possible with usual infrastructures and budgets of single universities and research institutions. However, despite the strategic relevance acknowledged to LSRI by the nascent literature and by national policymakers, there is a lack of understanding of configurations and key performances of a LSRI. This paper aims to bridge this gap by identifying key morphologies of LSRIs and analysing their performances. Design/methodology/approach The research is carried out adopting a mixed research methodology, merging a literature review with a survey conducted on a sample of 11 LSRIs; they provided the data set for the parametrization of a morphological matrix. Findings The research led to the identification of seven LSRIs morphologies, with different performance linked to their structure. Originality/value To the best of the authors’ knowledge, this paper originally proposes the data set needed to develop a morphological analysis of LSRIs.
{"title":"A critical analysis of large scale research infrastructures’ performances","authors":"Isabella Nocella, R. Linzalone, S. Ammirato, A. M. Felicetti","doi":"10.1108/mbe-09-2023-0140","DOIUrl":"https://doi.org/10.1108/mbe-09-2023-0140","url":null,"abstract":"\u0000Purpose\u0000Large scale research infrastructures (LSRIs) are rising in the competitive and globalized research environment, since they offer to external researchers-users, inputs and services for cutting-edge, large scale researches. Such researches would not be possible with usual infrastructures and budgets of single universities and research institutions. However, despite the strategic relevance acknowledged to LSRI by the nascent literature and by national policymakers, there is a lack of understanding of configurations and key performances of a LSRI. This paper aims to bridge this gap by identifying key morphologies of LSRIs and analysing their performances.\u0000\u0000\u0000Design/methodology/approach\u0000The research is carried out adopting a mixed research methodology, merging a literature review with a survey conducted on a sample of 11 LSRIs; they provided the data set for the parametrization of a morphological matrix.\u0000\u0000\u0000Findings\u0000The research led to the identification of seven LSRIs morphologies, with different performance linked to their structure.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, this paper originally proposes the data set needed to develop a morphological analysis of LSRIs.\u0000","PeriodicalId":18468,"journal":{"name":"Measuring Business Excellence","volume":"51 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138943691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}