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This paper discusses the effectiveness of a consortium-based student mobility programme by investigating the impact of the Asian International Mobility for Students (AIMS) Programme. AIMS is a regional multilateral large-scale student mobility programme based on a consortium of 10 member countries and 87 member universities with the Southeast Asian Ministers of Education Organization Regional Centre for Higher Education and Development (SEAMEO RIHED) as a facilitator. Over 6,000 students have participated in a semester-long intra-regional student exchange under AIMS since 2010.

The study employed questionnaire surveys and semi-structured interviews to investigate the impact of AIMS and its advantages as a consortium-based student mobility programme.

It was found that AIMS significantly impacted member universities by accelerating their internationalisation processes through increasing the number of inbound and outbound students and courses offered in English and so on. AIMS has promoted harmonisation among the members by developing common procedures and guidelines, providing platforms for mutual sharing of experiences and good practices and capacity building of international relations offices. AIMS has also had a significant impact on students by enhancing their regional identity and knowledge about the region of Asia, contributing to their development as future regional and global citizens. As advantages of AIMS, member universities efficiently built a foundation for international collaboration with common procedures and guidelines and shared their experiences through such venues as Annual Review Meetings. Students also feel supported by having clear guidance and find programmes prepared by host universities and SEAMEO RIHED useful.

This study is unique in that it empirically studies the impact of one of Asia’s largest student mobility programmes for the first time by analysing large-scale qualitative and quantitative data.

A deteriorating security situation and an increased need for defence equipment calls for new forms of collaboration between Armed Forces and the defence industry. This paper aims to investigate the ways in which the accelerating demand for increased security of supply of equipment and supplies to the Armed Forces requires adaptability in the procurement process that is governed by laws on public procurement (PP).

This paper is based on a review of current literature as well as empirical data obtained through interviews with representatives from the Swedish Defence Materiel Administration and the Swedish defence industry.

Collaboration with the globalized defence industry requires new approaches, where the PP rules make procurement of a safe supply of defence equipment difficult.

The study's empirical data and findings are based on the Swedish context. In order to draw more general conclusions in a defence context, the study should be expanded to cover more nations.

The findings will enable the defence industry and the procurement authorizations to better understand the requirements of Armed Forces, and how to cooperate under applicable legal and regulatory requirements.

The paper extends the extant body of academic knowledge of the security of supply into the defence sector. It serves as a first step towards articulating a call for new approaches to collaboration in defence supply chains.

The present paper assesses the decision problem of selecting Unmanned Aerial Vehicle Systems (SARP) by the hybrid MPSI-SPOTIS approach for deployment in border control and transborder illicit combat.

By the hybrid MCDA MPSI-SPOTIS approach, and from the database available in Gettinger (2019), models were filtered by Endurance, Range, Maximum Take-Off Weight (MTOW), and Payload, fitting within the classification of Categories EB 0 and 2. Category EB 1 was not considered in this study due to the limited number of models in the data source.

The use of the Multi-Criteria Decision Analysis (MCDA) tool MPSI-SPOTIS allowed the determination of weights by stochastic criteria, applied in a ranking method resistant to reverse ordering. The application of the method identified the Raybird-3 (Cat EB 0) and Searcher (Mk3) (Cat EB 2) models as the best alternatives. From a proposed clustering, other selection possibilities with close performance in the evaluation were presented. The cost criterion was not taken into consideration due to the absence of information in the data source employed. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.

The cost criterion was not taken into consideration due to the absence of information in the data source used. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.

This paper aims to propose a technology selection method applied to complex defense acquisitions when multiple factors influence the decision makers and it is hard to obtain a major optimum solution in multitask and multi-mission platform.

Going beyond the usual approach of measuring port performance – focusing on the efficiency of port operations – this paper aims to look into shipping lines and other port users’ perceptions on port performance.

The paper develops a framework measuring the perceptions of port users (i.e. shipping companies, shippers, etc.) on port performance. A typology of elements that shape port users’ perceptions has been developed with an eye on capturing the peculiarities of different port markets. Based on this typology, a tool to assess users’ perspectives, and subsequently evaluate, any given port has been developed. The tool provides port authorities the flexibility they need for customized approaches. The developed evaluation mechanism has been tested on a group of European seaports, and the results are presented by this study.

The framework and its pilot application unveil the key parameters that port users take into consideration when evaluating the effectiveness component of port performance. Moreover, the importance and evaluation ratings of specific performance parameters allow for a GAP analysis of the collected data.

The paper advances scholarly and practical discussion on how of port users’ perceptions can be a valuable tool for port performance measurement.

The proposed tool can be a valuable add-on for port authorities to evaluate their performance from the port users’ point of view and take the necessary actions to improve it. Also, the tool can be used for the evaluation of a new process, infrastructure. The evaluation of port users’ perception of port performance can and must be part of a European ports observatory, as it is a set of indicators that clearly reflects the satisfaction of port users by engaging their view on port performance issues, instead of relying almost exclusively on port-generated data.

The paper develops a framework for measuring port user’s perception on port performance, which is flexible and can be applied in any port.

The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process.

A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights.

The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector.

The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry.

The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.

The maritime industry is the transport mode that contributes most to air pollution. The International Maritime Organization (IMO) identified the reduction of air pollution by ships as a crucial issue. Since 1 January 2020, ships have had to adopt strategies and new technologies to eliminate air pollution. However, ship compliance with nitrate oxide (NOx) emission restrictions is more challenging. This paper aims to identify ship owners' challenges in investing in new technologies.

This paper applied a hybrid methodology combining a survey, a balanced scorecard and fuzzy analytic hierarchy process (F-AHP) to identify and evaluate constraints and weights in investment decision-making for NOx technologies. A survey was carried out to validate constraints.

A survey was carried out, representing 5.1% of Greek-owned ships by deadweight capacity. The findings provide a weighted list of seven crucial technical and economic constraints faced by ship operators. The constraints vary from ship retrofit expenditure to crew training and waste management. Additionally, NOx emission technologies were compared. It was found that liquefied natural gas is the preferred investment option for the survey participants compared with selective catalytic reduction, exhaust gas recirculation and batteries.

Several studies have dealt with the individual technical feasibility of NOx reduction technologies. However, apart from technical feasibility for a shipowner, the selection of a NOx technology has several managerial and safety risks. Therefore, the originality of this paper is to reveal those constraints that have a higher weight on ship owners. With this cost-benefit approach, investment challenges for ship operators are revealed. Policymakers can benefit from the results of the employed methodology.

Defence supply chains (SCs) aim at operational outcomes, and armed forces depend on them to provide availability and preparedness in peace and sustainability in war. Previous research has focussed on strategies for SCs aiming at financial outcomes. This raises the question of how suitable commercial supply chain strategies (SCSs) are for supply chain design (SCD) in defence. The purpose of this paper is to explain the constructs of SCSs that satisfy military operational requirements and to propose SCSs that are appropriate in defence.

This paper reports on a Delphi study with 20 experts from Swedish defence authorities. Through three Delphi rounds, two workshops and a validation round, these experts contributed to the reported findings.

The findings demonstrate that commercial SC constructs are acceptable and applicable in defence but not sufficient. An additional strategy is required to satisfy requirements on availability, preparedness and sustainability. The paper shows that different requirements in peace and war make it challenging to design suitable defence SCs and proposes eight SCSs that satisfy these requirements.

The results emanate from the Swedish defence context and further research is required for generalisation.

This paper extends theory by investigating SCs aiming at operational outcomes. For managers in companies and defence authorities, it explicates how the unique issues in defence must influence SCD to satisfy operational requirements.

The volumes of international containerized trade substantially increased over the past years. In the meantime, marine container terminal (MCT) operators are facing congestion issues at their terminals because of the increasing number of large-size vessels, the lack of innovative technologies and advanced handling equipment and the inability of proper scheduling of the available resources. This study aims to propose a novel memetic algorithm with a deterministic parameter control to facilitate the berth scheduling at MCTs and minimize the total vessel service cost.

A local search heuristic, which is based on the first-come-first-served policy, is applied at the chromosomes and population initialization stage within the developed memetic algorithm (MA). The deterministic parameter control strategy is implemented for a custom mutation operator, which alters the mutation rate values based on the piecewise function throughout the evolution of the algorithm. Performance of the proposed MA is compared with that of the alternative solution algorithms widely used in the berth scheduling literature, including a MA that does not apply the deterministic parameter control strategy, typical evolutionary algorithm, simulated annealing and variable neighborhood search.

Results demonstrate that the developed MA with a deterministic parameter control can obtain superior berth schedules in terms of the total vessel service cost within a reasonable computational time. Furthermore, greater cost savings are observed for the cases with high demand and low berthing capacity at the terminal. A comprehensive analysis of the convergence patterns indicates that introduction of the custom mutation operator with a deterministic control for the mutation rate value would provide more efficient exploration and exploitation of the search space.

This study does not account for uncertainty in vessel arrivals. Furthermore, potential changes in the vessel handling times owing to terminal disruptions are not captured.

The developed solution algorithm can serve as an efficient planning tool for MCT operators and assist with efficient berth scheduling for both discrete and continuous berthing layout cases.

The majority of studies on berth scheduling rely on the stochastic search algorithms without considering the specific problem properties and applying the guided search heuristics. Unlike canonical evolutionary algorithms, the developed algorithm uses a local search heuristic for the chromosomes and population initialization and adjusts the mutation rate values based on a deterministic parameter control strategy for more efficient exploration and exploitation of the search space.

This paper aims to study the function of standardisation in intermodal transport. It identifies where standardisation helps to improve intermodal transport, who is active in intermodal transport standardisation, what types of standards are needed and what the decision-making process and implementation of standards should be like to positively influence the performance of intermodal transportation.

An empirical study is designed to carry out this research project. The empirical study starts with a review of the organisations that are responsible for standardisation and intermodal transport, together with the standards that they have developed, and are developing, so far. It continues with analysing the topics where standardisation helps to improve the performance of intermodal transport. The analysis is based on 12 interviews, followed by desk research, to validate the respondents’ statements.

The results show that intermodal transportation should be distinguished in continental and maritime transport, which require different standards. In maritime transport, the hardware aspects of the system are highly standardised. However, further standardisation of information exchange offers potential to improve the quality of transport. For continental transport, challenges appear in the heterogeneity of infrastructure and loading units used in Europe. For both systems, openness and consensus are main requirements for the development of successful standards.

Standards facilitate interoperability, quality and safety of intermodal transportation, which leads to better performance. This has drawn little attention in the literature. This study addresses this gap and focuses on Europe.

Marine transportation has been faced with an increasing demand for containerized cargo during the past decade. Marine container terminals (MCTs), as the facilities for connecting seaborne and inland transportation, are expected to handle the increasing amount of containers, delivered by vessels. Berth scheduling plays an important role for the total throughput of MCTs as well as the overall effectiveness of the MCT operations. This study aims to propose a novel island-based metaheuristic algorithm to solve the berth scheduling problem and minimize the total cost of serving the arriving vessels at the MCT.

A universal island-based metaheuristic algorithm (UIMA) was proposed in this study, aiming to solve the spatially constrained berth scheduling problem. The UIMA population was divided into four sub-populations (i.e. islands). Unlike the canonical island-based algorithms that execute the same metaheuristic on each island, four different population-based metaheuristics are adopted within the developed algorithm to search the islands, including the following: evolutionary algorithm (EA), particle swarm optimization (PSO), estimation of distribution algorithm (EDA) and differential evolution (DE). The adopted population-based metaheuristic algorithms rely on different operators, which facilitate the search process for superior solutions on the UIMA islands.

The conducted numerical experiments demonstrated that the developed UIMA algorithm returned near-optimal solutions for the small-size problem instances. As for the large-size problem instances, UIMA was found to be superior to the EA, PSO, EDA and DE algorithms, which were executed in isolation, in terms of the obtained objective function values at termination. Furthermore, the developed UIMA algorithm outperformed various single-solution-based metaheuristic algorithms (including variable neighborhood search, tabu search and simulated annealing) in terms of the solution quality. The maximum UIMA computational time did not exceed 306 s.

Some of the previous berth scheduling studies modeled uncertain vessel arrival times and/or handling times, while this study assumed the vessel arrival and handling times to be deterministic.

The developed UIMA algorithm can be used by the MCT operators as an efficient decision support tool and assist with a cost-effective design of berth schedules within an acceptable computational time.

A novel island-based metaheuristic algorithm is designed to solve the spatially constrained berth scheduling problem. The proposed island-based algorithm adopts several types of metaheuristic algorithms to cover different areas of the search space. The considered metaheuristic algorithms rely on different operators. Such feature is expected to facilitate the search process for superior solutions.