Measurement, modelling and analysis of container port performance

Abstract

This thesis aims to develop a new framework of container port/terminal performance measurement, modelling and analysis. There is a need for a new performance measurement framework not only to meet the need of port stakeholders, but also to develop diagnostic tools capable of supporting decision-making in complex port/terminal operations in an uncertain environment. This study follows the related questions of ‘what to measure’, ‘how to measure’ and ‘how to control and improve’ container port performance. In this regard, this study proposes the development of a systematic approach to address the multi-stakeholder dimension in port performance measurement. This was achieved by integrating a multi-stakeholder dimension in a port performance measurement framework which takes into account the corresponding port performance indicators (PPIs). To this end, this study identified six dimensions of crucial interests in major (container) ports investigating stakeholders’ goals and objectives, and discussed them with port stakeholders. The six dimensions defined in this study cover the range of port activities to cope with new evolutionary changes, to measure and communicate their impacts on society, economy and environment and to be consistent with their goals. Then, through a literature review and an analysis of industrial practices the associated PPIs were selected. The semi-structured interviews were applied to assess the suitability of the potential indicators and to test the feasibility of the selected indicators. The multi-stakeholder dimension involves both quantitative and qualitative PPIs in order to reflect complexity of port/terminal business environments. This study develops two hybrid port performance measurement models: PPIs independency model and PPIs interdependency model. In the first port performance measurement model, a hybrid approach of the Analytic Hierarchy Process (AHP) and Fuzzy Logic based Evidential Reasoning (FER) for solving multiple criteria decision making (MCDM) problems is applied to address the challenges in port performance measurement. AHP is applied for a part of the FER to evaluate the relative importance of the selected PPIs. FER is applied for dealing with uncertainties presented in the evaluations of the selected PPIs as well as aggregation of the evaluations of PPIs and their importance. An analysis of 12 container terminals in South Korea is conducted to validate the proposed method. The second approach, a new conceptual PPI interdependency model, is developed using a hybrid approach of a Fuzzy Logic based Evidential Reasoning (FER), a Decision Making Trial and Evaluation Laboratory (DEMATEL) and an Analytic Network Process (ANP). These methods are combined to deal with the inherent data uncertainties and the interdependencies among the port performance indicators (PPIs). Its novelty lies in its capability of dealing with interdependency among the performance measures as well as accommodating both qualitative and quantitative evaluations on the measures simultaneously. An analysis of 4 major container ports in South Korea is conducted to demonstrate the feasibility of the proposed method. The empirical investigations are conducted by taking the perspectives from different port stakeholders. For instance, the quantitative data (i.e. cargo and vessel operations and financial data) are collected directly from terminal operating companies and information systems/databases managed by port authorities, government and credit rating agencies. The qualitative PPIs are collected using questionnaires from three groups of terminal operators, users (i.e. shipping lines, shippers, logistics service providers and freight forwarders) and administrators (i.e. port authority and government) to assess their own associated PPIs to measure each container port/terminal performance. The empirical results indicate that the hybrid approach attempting to use quantitative modelling for dealing with the uncertainties and interdependency problems can be successfully fulfilled. The framework and its supporting method suggest an effective performance measurement tool and offer a diagnostic instrument to ports/terminals to satisfy the port stakeholders in a flexible manner. Finally, this thesis proposes a decision making framework for prioritising and selecting port performance improvement strategies. It can be achieved by the concepts of benchmarking-best practices using the analytic hierarchy process (AHP) incorporating a fuzzy order preference by similarity to ideal solution (FTOPSIS) method. Based on the results obtained from the two performance approaches, the leading performer (i.e. Busan New Port) and the poor performer (i.e. Busan North Port) are analysed as real cases to demonstrate the feasibility of the proposed methodology. The results yielded by the framework present the ranking of strategy options in terms of their preference to different terminal operating companies (TOCs), which enables decision makers to find optimal solutions to improving performance under their own dynamic business environments.