Transportation Research Part E: Logistics and Transportation Review
Airport quality and productivity changes: A Malmquist index decomposition assessment
Introduction
While there is growing interest in the measurement of airport productivity world-wide (Oum et al., 2006), the literature appears to offer few studies dealing with the relationship between the level of service quality and some measure(s) of airport performance. Indeed, airports are business units engaged in the provision of a service. Clearly, then, customers’ evaluation of a facility’s quality of service is of fundamental importance to airport managers and related administration (Correia et al., 2008a, Correia et al., 2008b).
Although airports generally benefit from a monopolistic position, it is important to understand that travelers’ perceptions of airport service can be an initial indictor of the related city’s ‘quality’ or attractiveness; and/or a parting impression for those who are leaving the area. That is to say, airports can be viewed as urban facilities essential to the city in which they are located (Caves and Gosling, 1999). Moreover, when the quality indicators involve factors having a direct bearing on airlines’ operative costs, they can become important elements in a given airline’s choice of hub (Adler and Berechman, 2001, Adler and Golany, 2001).
As noted, the role of service quality within an airport setting has been a focus of recent research. However, such efforts have been more concerned with the measurement of quality, and less so with its connection to the efficiency or productivity of facility operations. In the current paper, following the approach proposed by Fare et al. (1995) regarding the use of non-parametric Data Envelopment Analysis (DEA), we incorporate the quality aspect of services in the measurement of total factor productivity.
To the best of our knowledge, we thus offer the first attempt to fill this gap in the literature of performance measurement within the airport industry. As discussed below in some detail, our research suggests that the key factors explaining the deterioration of Italian airport productivity, in particular, are inadequate levels of technology improvement andquality of service.
The paper is structured as follows: The next section offers a brief review of the literature on airport productivity and quality analysis. In Section 3, the data set, as well the variables employed in the analysis, are presented. Section 4 discusses key issues in the measurement of quality, and presents the proposed Malmquist decomposition that incorporates a quality change component. Section 5 reviews the study’s results, while Section 6 presents the conclusion(s) and some discussion of our findings.
Section snippets
Review of the literature
In recent years, the analysis of service quality within airports has become a mandatory element in the management of their operations. Evidence of this point is provided by the Airport Service Quality Awards (ASQ), which have been given by the Airport Council International (ACI) since 2010. The awards recognize those airports that have achieved the highest ratings of passenger satisfaction as measured by ASQ surveys.
This growing interest in quality has lead the empirical literature to focus on
Inputs and outputs
In the present study, we measure the global productivity of airports by employing both physical and monetary variables (Barros and Dieke, 2008, Gitto and Mancuso, 2012a, Pacheco and Fernandes, 2003, Oum et al., 2003, Sarkis and Talluri, 2004). Data have been collected from three sources: Airport annual statistics (ENAC, 2007–2009a, ENAC, 2007–2009b), Assaeroporti,1 and TELEMACO (Camere di Commercio,
Methodology
In this section, we first present the Malmquist index, which includes a quality component, and then discuss the measures of quality that can be obtained from the available data set.
Airport quality index
From Section 4.2, the first step of our analysis considers the relationship between ocl and the four quality indicators. Due to the panel nature of our data, we estimate the Eq. (5) by employing pooled-OLS method. The results of this analysis are given in Table 2.
Note that the only regression coefficient that is significant at the 5% level, is that for the intercept. The regression analysis thus suggests that the overall perception of comfort level, ocl, is not statistically dependent on the
Conclusions and discussion
The current paper has applied a modified Malmquist index, based on classic DEA models and methodologies, that allows to incorporate quality aspect on productivity measurement of 20 Italian airport management companies over the period 2006–2008. The advantage of the proposed approach stems directly from its underlying DEA technique, which is based on identifying the best performers in a prescribed set of units. The main contribution of the paper to the literature is that airports’ quality
Acknowledgments
The authors would like to thank Barnett Parker and the participants at GAB Final Workshop, June 2012, Berlin, Wayne Talley and two anonymous referees for their helpful comments. The usual disclaimer applies.
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