Measuring the performance has become an important issue also in the cultural sector. In the recent literature, in order to evaluate the performance of museums, Data Envelopment Analysis (DEA) models have been proposed; these models allow to take into account the multidimensional nature of the museum performance. In this paper we exploit the capability of DEA to assess the performance by integrating the DEA approach with the Balanced Scorecard (BSC) tool; this is the first study that proposes a joint application of DEA and BSC to museums. To this aim we propose a new two-stage DEA-BSC approach. In the first stage we set a Balanced Scorecard scheme devised for museums, then we define a proper DEA model for each BSC perspective and compute the DEA efficiency score for every perspective. In the second stage we define a further DEA model which combines the efficiency scores of the various BSC perspectives into an overall performance indicator. In order to prevent the computation of the efficiency score to be almost exclusively determined by one output while disregarding the others, we set proportional restrictions on the virtual outputs. Finally, the DEA-BSC joint approach is applied to the municipal museums of Venice, carrying out a detailed empirical analysis.

How well is the museum performing? A joint use of DEA and BSC to measure the performance of museums

BASSO, Antonella;CASARIN, Francesco;FUNARI, Stefania
2018-01-01

Abstract

Measuring the performance has become an important issue also in the cultural sector. In the recent literature, in order to evaluate the performance of museums, Data Envelopment Analysis (DEA) models have been proposed; these models allow to take into account the multidimensional nature of the museum performance. In this paper we exploit the capability of DEA to assess the performance by integrating the DEA approach with the Balanced Scorecard (BSC) tool; this is the first study that proposes a joint application of DEA and BSC to museums. To this aim we propose a new two-stage DEA-BSC approach. In the first stage we set a Balanced Scorecard scheme devised for museums, then we define a proper DEA model for each BSC perspective and compute the DEA efficiency score for every perspective. In the second stage we define a further DEA model which combines the efficiency scores of the various BSC perspectives into an overall performance indicator. In order to prevent the computation of the efficiency score to be almost exclusively determined by one output while disregarding the others, we set proportional restrictions on the virtual outputs. Finally, the DEA-BSC joint approach is applied to the municipal museums of Venice, carrying out a detailed empirical analysis.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3691804
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