This thesis investigates the administrative performance of Italian universities, with a specific focus on the cost efficiency and customer satisfaction of administrative support services. Driven by the rising requirements for accountability, transparency, and cost control in higher education, the research aims to classify universities based on their administrative performance and identify the structural and contextual determinants underlying such profiles. In data gathered from the "Good Practice project" and external sources, between 2014–2023, customer satisfaction scores and unit cost measures are combined across 5 key service areas (administration, didactic support, infrastructure, research support, and library systems). The methodological approach combines Latent Profile Analysis (LPA) to uncover distinct university typologies, multinomial logistic regression to explain profile membership through institutional characteristics (such as size and region), and ANOVA tests to assess the relationship between profiles and graduate employability outcomes. Three main university profiles are identified in the findings: high efficiency and effectiveness, low effectiveness with average efficiency, and average effectiveness with low efficiency. Over time, a rising trend is noted with more universities adopting the high-performance pattern. When it comes to year-to-year LPA , I can highlight notable fluctuations in institutional classifications, reflecting the dynamic nature of administrative practices. These results are highly useful for university governance, suggesting targeted interventions to enhance administrative efficacy and stakeholder satisfaction and maintain the connection between administrative performance and graduate employability.
Questa tesi analizza la performance amministrativa delle università italiane, con un focus specifico sull’efficienza dei costi e sulla soddisfazione degli utenti dei servizi amministrativi di supporto. Spinta dalle crescenti esigenze di accountability, trasparenza e controllo dei costi nell’istruzione superiore, la ricerca mira a classificare le università in base alla loro performance amministrativa e a identificare i determinanti strutturali e contestuali che sottendono tali profili. Nei dati raccolti dal “Good Practice project” e da fonti esterne, tra il 2014 e il 2023, sono stati combinati gli indicatori di soddisfazione degli utenti e le misure di costo unitario in cinque principali aree di servizio (amministrazione, supporto didattico, infrastrutture, supporto alla ricerca e sistemi bibliotecari). L’approccio metodologico combina l’Analisi dei Profili Latenti (LPA) per individuare tipologie distintive di università, la regressione logistica multinomiale per spiegare l’appartenenza ai profili sulla base delle caratteristiche istituzionali (come dimensione e regione) e i test ANOVA per valutare la relazione tra i profili e gli esiti occupazionali dei laureati. Dai risultati emergono tre principali profili universitari: alta efficienza ed efficacia, bassa efficacia con efficienza media, ed efficacia media con bassa efficienza. Nel tempo si osserva una tendenza positiva, con un numero crescente di università che adotta il modello ad alte prestazioni. L’analisi anno per anno evidenzia notevoli fluttuazioni nella classificazione delle istituzioni, riflettendo la natura dinamica delle pratiche amministrative. Questi risultati sono estremamente utili per la governance universitaria, suggerendo interventi mirati per migliorare l’efficacia amministrativa, la soddisfazione degli stakeholder e mantenere il legame tra performance amministrativa e occupabilità dei laureati.
Analysing the performance of italian universities: the role of technical and administrative services
KARIMOVA, NERMIN
2024/2025
Abstract
This thesis investigates the administrative performance of Italian universities, with a specific focus on the cost efficiency and customer satisfaction of administrative support services. Driven by the rising requirements for accountability, transparency, and cost control in higher education, the research aims to classify universities based on their administrative performance and identify the structural and contextual determinants underlying such profiles. In data gathered from the "Good Practice project" and external sources, between 2014–2023, customer satisfaction scores and unit cost measures are combined across 5 key service areas (administration, didactic support, infrastructure, research support, and library systems). The methodological approach combines Latent Profile Analysis (LPA) to uncover distinct university typologies, multinomial logistic regression to explain profile membership through institutional characteristics (such as size and region), and ANOVA tests to assess the relationship between profiles and graduate employability outcomes. Three main university profiles are identified in the findings: high efficiency and effectiveness, low effectiveness with average efficiency, and average effectiveness with low efficiency. Over time, a rising trend is noted with more universities adopting the high-performance pattern. When it comes to year-to-year LPA , I can highlight notable fluctuations in institutional classifications, reflecting the dynamic nature of administrative practices. These results are highly useful for university governance, suggesting targeted interventions to enhance administrative efficacy and stakeholder satisfaction and maintain the connection between administrative performance and graduate employability.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/239847