Analysing the lobby‐effect of port competitiveness’ determinants: a stochastic frontier approach

Building upon a formerly performed study on port competitiveness, this article discusses the use of a stochastic frontier model as an interesting novel use to test, identify and correct respondents’ bias by applying it to competitiveness analysis based on perceptions of senior executives. Measuring the importance of competition determinants of seaports, conventionally analyzed using a SWOT‐analysis based on (transport) infrastructure as a prime requirement for port activity growth, is an important issue to port management. However, it seems that the ‘institutional’ environment of a seaport is also critical in obtaining a competitive advantage. In Haezendonck et al. (2000 and 2001) those port specific advantages and disadvantages were identified using factor analysis and L1‐regression on the perceptions of 75 respondents, all senior executives and experts, through a survey. As regards the results of this study, critiques were formulated on the use of perceptions, often biased due to the political lobbying potential of the results. Since respondents often see independent studies as an opportunity to obtain more or early government subsidies, attract new investment projects or at least highlight the attention on their specific problems and demands, they were prone to underestimating the positive impact of the key success factors of the studied seaport compared to its main rivals, in this case major seaports in the so‐called Hamburg–Le Havre competitive range. The purpose of this article is to test the assumption that respondents significantly underestimate the positive impact of port specific advantages and to see which of the respondent subgroups within the 75 respondents sample are more responsible than others for this underestimation. In addition, we argue and demonstrate that the use of a stochastic frontier method is appropriate for this matter. Each of 25 considered competition determinants of the original study is decomposed into a noise and ‘efficiency’ term, based on the Bayesian stochastic frontier model (BSFM). In this article, we find evidence that BSFM could be used to test the ‘lobby‐effect’ or underestimation of the real effect of determinants, that terminal operators as a subgroup of respondents, are more likely to underestimate the key success factors than the subgroup of port experts and that those determinants that are directly related to government action show more underestimation than competitiveness determinants that result from private investments.