The role of external factors versus managerial ability in determining seaports’ relative efficiency: An input-by-input analysis through a multi-step approach on a panel of Southern European ports (original) (raw)

Abstract

This article provides an analysis of the performance of a panel of Southern European ports. In contrast with previous research, a multi-step approach is followed. This methodology allows distinguishing between the role of both factors that are external and internal to the organisation of the port in determining the relative ranking of ports in terms of efficiency. Furthermore, it enables the identification of the impact on an input-by-input basis. Managerial capacities, port infrastructure endowment and services are tested together with port policies, macroeconomic conditions and other external factors to verify their individual impact. In the first stage, efficiency is measured via the traditional input-oriented Data Envelopment Analysis (DEA). In the second stage a stochastic frontier analysis in carried out through fixed-effect estimators in order to identify the determinants of input-specific efficiency differentials across ports. In general, governance-related factors and macroeconomic conditions predominate the managerial skills for the more flexible factors of production. The outcome of the DEA applied in the third stage shows that netting inputs of the impact of factors considered outside direct port managers’ control, relative to performances, change significantly. This is particularly true for multi-functional ports.

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Notes

  1. Recently, multi-step procedures have been used to estimate efficiency of a number of sectors, among others, the banking sector (Liu and Tone, 2008), education (Aubyn et al, 2009), local governments (Worthington and Dollery, 2002), public transport services and infrastructure provision and expenditure at local level (Buzzo Margari et al, 2007 and Bergantino and Porcelli, 2011), health service provision (Alfonso and Aubyn, 2006; Porcelli, 2009), and water and sewerage (Erbetta and Cave, 2007).
  2. For greater details on the reasons for not adopting the Tobit model given the fractional nature of the dependent variable, the reader is referred to the recent paper of Papke and Wooldridge (2008).
  3. The results of the random effect model are reported in Bergantino and Musso (2010) for a sample of Northern and Southern European ports. The outcome is in line with that of the present study.
  4. The method used to separate the composed error term into its components has been developed by Jondrow et al (1982).
  5. For instance, they refer to technological progress, which might induce dramatic changes in any pre-determined relationship between terminal facilities and the absolute number of workers, or to the differences in the use of labour in ports of different sizes, with different clients, or, and this is particularly relevant for this study, for different governance regimes. Some studies approximate labour input with port authorities employees (among these see Tongzon, 2001a, 2001b).
  6. The first three variables are measured at NUTS III level (provincial), whenever the data are available. For Cyprus and Malta we have used NUTS II level data.

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Acknowledgements

The authors thank Francesco Porcelli for very helpful comments and suggestions and the participants of the WCTR 2010 and SIE 2010. The usual disclaimer applies.

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Authors and Affiliations

  1. Department of Economics, Faculty of Economics, University of Bari, Via C. Rosalba, 53, Bari, 70124, Italy
    Angela Stefania Bergantino
  2. Department of Economics, Faculty of Economics, University of Genoa, Via Vivaldi 5, Genoa, 16124, Italy
    Enrico Musso

Authors

  1. Angela Stefania Bergantino
  2. Enrico Musso

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Bergantino, A., Musso, E. The role of external factors versus managerial ability in determining seaports’ relative efficiency: An input-by-input analysis through a multi-step approach on a panel of Southern European ports.Marit Econ Logist 13, 121–141 (2011). https://doi.org/10.1057/mel.2011.1

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