Most of the busiest airports worldwide experience serious congestion and delay problems which call for some immediate capacity and demand management action. Solutions aiming to manage congestion through better slot scheduling have lately received a great deal of consideration due to their potential for delivering quick and substantial capacity utilisation improvements. A slot scheduling approach brings promises to cope better with congestion problems in the short to medium run and in a more sustainable way based on existing resources. This paper aims to provide a critical review of current research in declared capacity modelling and strategic slot scheduling. Furthermore, it goes beyond the critical review of current research developments by identifying future research issues and gaps and developing concrete directions towards modelling and solving advanced single airport and network-based slot scheduling problems. Our research findings suggest that the next generation of slot scheduling models should explore variations of currently used objectives (e.g., alternative expressions of schedule delay) and most importantly enrich them with fairness and equity, resource utilisation and environmental considerations. Future modelling efforts should also aim to further investigate airlines’ utility of alternative slot allocation outcomes, including various acceptability measures and levels of tolerance against schedule displacements. Last but not least, future research should intensively focus on the development and validation of computationally viable and robust slot scheduling models being able to capture the complexity, dynamic nature and weather-induced uncertainty of airport operations, along with hybrid solution approaches being able to deal with the size and complexity of slot allocation at network level.

The agribusiness sector shows tremendous growth and sustainability prospects by exploiting the challenges of “AgriFood-Tech” business models in the digital environment, by encouraging innovation, accelerating institutional and structural change, enhancing productivity, and introducing new products and services to the market. The purpose of this study is to investigate different types of “AgriFood-Tech” digital models and analyze their role in the agribusiness and AgriFood sector. Based on relevant literature research, the authors present and discuss five indicative examples of “AgriFood-Tech” models, using the Business Model Canvas (BMC) framework. The methodology included the analysis of the components of innovative AgriFood innovative business models paradigms, such as distribution channels, key partnerships, customer selection and relationships, financial viability, and value proposition. The goal was to explore their building blocks and the required decisions that create, deliver, and capture value. Our findings highlight the importance of specific features of the models, including online sharing of information between the stakeholders, online searches of agri-products, and logistics services in the agribusiness sector.

Background: Information and communication technologies (ICT) have introduced “smart” concepts across industries, including ports. Smart ports, leveraging IoT, cybersecurity, and cloud computing, are trending in maritime operations. They optimize data for informed decision-making, cutting costs, enhancing efficiency, mitigating risks, and fostering growth. Methods: To consolidate knowledge in this area, we are conducting a systematic literature review and meta-analysis using the PRISMA framework. Our goal is to synthesize existing insights, minimize biases, increase reliability, and effectively communicate our findings. To address the research needs mentioned, the current study focuses on implementing a systematic literature review (SLR). Results: The goals of this review are: (i) to present and describe the main categories and themes within the research topic, and (ii) to identify research gaps that will aid future research. Key findings include the identification and classification of current literature trends in the smart port performance evaluation framework and the examination of fundamental themes discussed within this area of research. Conclusions: In our review, we emphasize the smart port concept, clarifying its common interpretations amid the industry 4.0 revolution. We discuss recent advancements in emerging technologies and identify key challenges driving researchers’ exploration of the evolving smart port landscape.

Urban Consolidation Centers (UCCs) constitute an appealing solution to urban freight distribution that ensures environmental-friendly and cost-efficient distribution in densely populated areas. Existing relevant research has placed the emphasis on the analysis of the underlying characteristics, services and operational advantages of UCCs, with limited focus on key determinants of long-term viability of UCC initiatives. The objective of this paper is to provide a comprehensive state-of-practice review of UCCs in Europe. The research capitalises on positive and negative experiences and practices so that it comes up with key success factors and viability drivers, common sources of failure, as well as key determinants for the successful operation and management of UCCs. A hybrid approach combining Systematic Literature Review (SLR) methodology with multiple case study research was adopted. Our analysis highlights specific strategic, tactical and operational factors that directly affect the successful operation and viability of a UCC.

Background: The increasing frequency and severity of extreme weather events (EWEs) as a consequence of climate change pose critical challenges on the transport and logistics sector, hence requiring systematic evaluation and strategic adaptation. Methods: This study conducts a comprehensive systematic literature review (SLR) of 147 peer-reviewed articles and reports through a PRISMA framework to comprehensively identify key weather-induced challenges, quantify their operational, infrastructural and economic impacts, and explore alternative mitigation strategies. Results: With a greater focus on rainfall, flooding and snowfall, this study highlights their notable impacts causing reductions in transport efficiency, increased maintenance costs and substantial financial losses. Also, it emphasizes the role of advanced technologies, resilient infrastructure, and adaptive policy frameworks as critical enablers for enhancing sector resilience while simultaneously formulating a robust roadmap for cities and companies with actions ranging from direct operational adjustments to long-term transformational changes in policy and infrastructure. Conclusions: This work underscores the importance of using a data-driven approach to safeguard transport and logistics systems against evolving climate risks contributing to the broader goal of sustainable urban resilience and operational continuity.

The paper provides a systematic review and analysis of the current literature on big data (BD) applications in the context of food supply chain management (FSCM) in order to categorize the state-of-the-art research trends exploring the adoption and implementation of big data analytics (BDA) across different segments of food supply chain (FSC). The use of BDA brings the digital transformation of FSCs closer providing sustainable implications and added value to their operation. Harnessing BD’s potential is becoming more and more relevant in addressing the constantly evolving complexities in food systems. However, the field of BD applications in the FSCM domain is severely fragmented and relatively “primitive”. The present research is one of the earliest attempts to recognize and present a comprehensive analysis for the BD applications across different segments of FSC proposing a conceptual framework that illustrates the role of BD in a data-driven FSCM environment. For the purposes of our research, we adopted the systematic literature review (SLR) method aiming at the identification of the dominant categories and themes within the research area. Based on the SLR findings, we propose a conceptual framework that captures the interconnection between FSC performance and BD applications by using the input-process-output (IPO) model within a data-driven FSCM context. The main research contribution lies on the thematic classification of relevant research, the conceptualization of this fragmented field, the development of a conceptual framework, and the presentation of a future research agenda pertaining to BD applications in a data-driven FSCM context.