Michael Gogas

Optimization of Decision-Making in Port Logistics Terminals: Using Analytic Hierarchy Process for the Case of Port of Thessaloniki

Abstract The management models pursued in logistics terminals determine their performance to a great extent. Terminals managed by public actors usually incorporate more social criteria into their decision-making processes. In addition, private management focuses on economic viability of the initiative. Decision-making is a complex process regardless the structure of management or the decision models useddue to the fact that a wide range of diverse criteria are embedded into this process. The objective of this paper it to determine a prioritization of a set of alternative options for investment projects which were suggested by port executives taking into account criteria and evaluation that have already validated by them. In order to perform the analysis a multi-criteria decision-making model was used: the Analytic Hierachy Process. The outcomes support a low-biased and efficient strategic planning through a balanced decision-making framework.

Assessing the Contribution of Urban Freight Terminals in Last Mile Operations

Abstract This paper introduces a multi-stakeholder multi-criteria evaluation framework, which can be used for the assessment of the last mile distribution performance of urban freight terminals. To this end, a comparative analysis is conducted addressing two Greek urban intermodal freight terminals located at the port of Thessaloniki (ThPA) and Kuehne+Nagel (K+N)’s premises. The assessment of the terminals’ performance relies on a tailored multi-criteria Key Performance Indicator (KPI)-based evaluation framework, whereas the selection and significance of the incorporated criteria and KPIs is predetermined by the relevant responsible stakeholders, who imposed their viewpoint through an analytic hierarchy process. Results showed that ThPA was ranked first according to its performance pertaining to the role of an intermodal interchange; still, K+N’s performance index was only 8.5% lower than ThPA’s, while in specific KPIs it seems that it performs in a better way.