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Nel corso degli ultimi 20 anni la gestione logistica delle imprese ha subito profondi cambiamenti. Il passaggio attraverso differenti modelli di produzione delinea un cammino evolutivo le cui tappe sono scandite dall'avvicendarsi nella posizione di leadership di distinte funzioni operative. Mentre gli anni '70 hanno rappresentato l'era del primato del marketing e della comunicazione d'impresa, con gli anni '80 la qualità e la ricerca della produttività sono tornati ad essere gli elementi principali sui quali le imprese hanno cercato di costruire il proprio vantaggio competitivo. In questo ambito, la funzione logistica è destinata ad assumere un ruolo guida nei processi di riorganizzazione delle imprese.

The paper investigates the importance of banks’ business classification in shaping the risk profile of financial institutions on a global scale. We employ a rare-event logit model based on a state-of-the-art list of major global distress events from the global financial crisis. When clustering banks by their business strategies using a community detection approach, we show that (i) capital enhanced resilience only for traditional banks that were on average less capitalized than other banks; (ii) boosting ROE, usually associated with riskier exposures, improved resilience for stable funded and asset diversified banks; (iii) conversely, higher levels of ROA exacerbated banks’ vulnerability when associated with concentrated (not-diversified) investment structures; (iv) size in terms of total assets contributed to instability only for wholesale-funded institutions due to their high levels of unstable funding. Liquidity, on the contrary, reduced the institution likelihood of being in distress, regardless of its business classification. Although our findings refer to the recent financial crisis, they provide evidence that a tailored risk monitoring based on a proper peer group identification can facilitate banks’ distresses prediction.

This paper introduces a new empirical procedure for the estimation of hospitals' technical efficiency in presence of spatial heterogeneity. We propose a methodology that allows treating spatial heterogeneity independently of a predetermined reference to administrative borders. We define geographical spatial regimes, characterised by spatial proximity and homogeneity of relevant demand characteristics, within which to assess the efficiency of hospitals. The methodology has then been tested on a large sample of Italian hospitals, for which their production efficiency has been assessed within homogeneous demand areas.