Abstract Seaborne transport plays a crucial role in local, national, and global economies, helping to shift manufacturing from regional to global levels. However, international trade is susceptible to the impacts of changing climate patterns. This paper examines how climate disruptions affect India’s international trade by analysing the seaport traffic of eight major Indian ports from 1982 to 2021. To that effect, using Principal Component Analysis, we create a climate index consisting of wind speed, temperature, relative humidity, and precipitation variables and we show that the index variables significantly impact port activities. Additionally, our analysis also accounts for variables such road and railway infrastructure, since this directly affects cargo flows, port traffic and regional incomes. Moreover, in the context of our analysis, we consider that robust road and rail infrastructure improves resilience against extreme weather events by ensuring better connectivity, quicker recovery, and sustained economic stability. We employ several econometric techniques, and diagnostic checks to draw empirical inferences. Moreover, the analysis distinguishes between east and west coast ports of India, given their markedly different climatic and economic conditions. India’s position as a climate change hotspot heightens the vulnerability of its ports. The methods and findings discussed here provide steps for policymakers to prioritise training, revise insurance policies, upgrade infrastructure, promote stakeholder collaboration, and adopt green solutions to mitigate climate impact.
Shipment of goods. Delivery of goods, Transportation and communications
Abstract The shipping industry aims to achieve full decarbonization at the European Union (EU) level by mid-century. Over the past decade, various alternative fuels have been explored to address this goal. However, challenges such as insufficient bunkering infrastructure, technological immaturity, and high costs have made shipowners hesitant to invest in “clean” propulsion systems. This study conducts a bibliometric analysis, supported by a systematic literature review, to map and critically synthesize current knowledge on alternative fuels for ferry decarbonization and their alignment with emissions reduction policies. Using the Greek ferry fleet as a representative case study, the paper evaluates the regulatory framework and technical characteristics of various fuel options and examines their compatibility with different vessel categories. A qualitative comparative framework is introduced to link policy types with alternative fuel pathways, offering original insights into policy—fuel alignment. The findings highlight methanol and green electricity (battery-electric systems) as highly promising solutions, especially if battery technologies further advance in the coming years. Hydrogen also presents significant potential, but is currently limited by high production costs and infrastructure requirements. Rather than presenting a quantitative decision-making model this review establishes the conceptual basis for such a framework in future research. This paper also offers innovative proposals to accelerate the adoption of zero-emission fuels, addresses key gaps in existing research, and provides insights for advancing ferry decarbonization.
Shipment of goods. Delivery of goods, Transportation and communications
The Forward-Forward (FF) algorithm offers a biologically plausible alternative to backpropagation, enabling neural networks to learn through local updates. However, FF's efficacy relies heavily on the definition of "goodness", which is a scalar measure of neural activity. While current implementations predominantly utilize a simple sum-of-squares metric, it remains unclear if this default choice is optimal. To address this, we benchmarked 21 distinct goodness functions across four standard image datasets (MNIST, FashionMNIST, CIFAR-10, STL-10), evaluating classification accuracy, energy consumption, and carbon footprint. We found that certain alternative goodness functions inspired from various domains significantly outperform the standard baseline. Specifically, \texttt{game\_theoretic\_local} achieved 97.15\% accuracy on MNIST, \texttt{softmax\_energy\_margin\_local} reached 82.84\% on FashionMNIST, and \texttt{triplet\_margin\_local} attained 37.69\% on STL-10. Furthermore, we observed substantial variability in computational efficiency, highlighting a critical trade-off between predictive performance and environmental cost. These findings demonstrate that the goodness function is a pivotal hyperparameter in FF design. We release our code on \href{https://github.com/aryashah2k/In-Search-of-Goodness}{Github} for reference and reproducibility.
Diogo L. Pires, Vincenzo Mancuso, Paolo Castagno
et al.
Natural and human-made common goods present key challenges due to their susceptibility to degradation, overuse, or congestion. We explore the self-organisation of their usage when individuals have access to several available commons but limited information on them. We propose an extension of the Win-Stay, Lose-Shift (WSLS) strategy for such systems, under which individuals use a resource iteratively until they are unsuccessful and then shift randomly. This simple strategy leads to a distribution of the use of commons with an improvement against random shifting. Selective individuals who retain information on their usage and accordingly adapt their tolerance to failure in each common good improve the average experienced quality for an entire population. Hybrid systems of selective and non-selective individuals can lead to an equilibrium with equalised experienced quality akin to the ideal free distribution. We show that these results can be applied to the server selection problem faced by mobile users accessing Internet services and we perform realistic simulations to test their validity. Furthermore, these findings can be used to understand other real systems such as animal dispersal on grazing and foraging land, and to propose solutions to operators of systems of public transport or other technological commons.
Alina Kovalenko, Terje Andreas Mathisen, Jeroen Pruyn
Abstract Intermodality is regarded as one way of achieving more sustainable transport solutions. To make intermodal transport the preferred solution among shippers, it must be attractive according to the concept of generalized transport costs. An extended model for generalized transport costs is developed which includes elements important for comparing maritime transport solutions in the Artic. This framework forms the basis for a principal discussion on the conditions that make one transport solution preferable to another within the context of maritime logistics. This model is then applied to the context of the Northeast Passage to discuss the necessary requirements for making an intermodal transport solution attractive relative to the current main route from Northeast Asia to Northwest Europe through the Suez Canal. Even though intermodality could be preferable in principle, current solutions cannot compete with either Arctic routes using unimodal solutions with high ice-class vessels or with the Suez route. Due to uncertainty and limited empirical evidence, a sensitivity analysis is conducted, focusing on the variables with the greatest impact on the result. Policymakers and stakeholders can consider the findings to improve transport competitiveness via the Northeast Passage.
Shipment of goods. Delivery of goods, Transportation and communications
This paper aims to develop a learning method for a special class of traveling salesman problems (TSP), namely, the pickup-and-delivery TSP (PDTSP), which finds the shortest tour along a sequence of one-to-one pickup-and-delivery nodes. One-to-one here means that the transported people or goods are associated with designated pairs of pickup and delivery nodes, in contrast to that indistinguishable goods can be delivered to any nodes. In PDTSP, precedence constraints need to be satisfied that each pickup node must be visited before its corresponding delivery node. Classic operations research (OR) algorithms for PDTSP are difficult to scale to large-sized problems. Recently, reinforcement learning (RL) has been applied to TSPs. The basic idea is to explore and evaluate visiting sequences in a solution space. However, this approach could be less computationally efficient, as it has to potentially evaluate many infeasible solutions of which precedence constraints are violated. To restrict solution search within a feasible space, we utilize operators that always map one feasible solution to another, without spending time exploring the infeasible solution space. Such operators are evaluated and selected as policies to solve PDTSPs in an RL framework. We make a comparison of our method and baselines, including classic OR algorithms and existing learning methods. Results show that our approach can find tours shorter than baselines.
Background: With about 80% of world trade being seaborne, seaports’ capacity, efficiency and associated services are vital to ensure seamless, sustainable global supply chains. A lack of investment in marine services capacity and performance in South African ports remains a concern for port users and supply chain practitioners.
Objectives: This study examines the capacity and performance of marine services in South Africa’s ports. The primary example examines marine services performance data for the Port of Durban.
Method: This study uses Transnet National Ports Authority (TNPA) data and descriptive statistics to analyse marine fleet performance, bollard pulls and human capacity in South Africa’s ports to identify causes of shipping delays in the Port of Durban from 2014 to 2021.
Results: The 8 years analysis show five most prominent sources of shipping delays in Ports as; tugboats occupied, shift changes, shipping movements, tugs out of commission and adverse weather conditions. Other factors identified were pilot-boat availability, overbooking slots, port meetings, etc. The performance of marine services are impacted by outdated wet infrastructure and a shortage of marine crafts and critical skills.
Conclusion: There is a clear and justified need to increase physical and human capital investment in the provision of marine services and improve maintenance spending on critical infrastructure to reduce shipping delays and costs of conducting trade in South African (SA) ports.
Contribution: The study compiles, analyses and provides a contextual understanding of the number of marine crafts, average bollard pulls, human resources capacity and causes of shipping delays in Republic of South Africa (RSA) ports.
Shipment of goods. Delivery of goods, Transportation and communications
Abstract This study applied a Cobb–Douglas production function in an attempt to assess the effect of increased maritime sector investment on economic growth. It did this for the Tunisian economy based on panel data for the 1985–2020 period, thus making it possible to confirm the importance of spillover effects resulting from developing the Tunisian maritime infrastructure. Increases in added value for market services and non-manufacturing industries proves the benefits of investments but also the harm caused by the structuring effects of marine infrastructure. The results reveal, however, that the positive induced effects are not guaranteed, because the development of maritime infrastructure can have the opposite effect, such as by shrinking the size of the manufacturing industries in relation to services, which is a striking example of a negative effect that was suffered by the Tunisian economy.
Shipment of goods. Delivery of goods, Transportation and communications
Among many risk assessment techniques, qualitative, semi-quantitative or quantitative, risk matrix is a common tool to assess risk by allocating frequency and consequence of an accident to one of the pre divided frequency and consequence categories. However, since there is no standardized way to define these categories, risk matrix with its strength of being straightforward to use and easy to interpret has inherent uncertainties including objective categorization determination and consistency of decisions on frequency and consequence among different users, which usually results in multiple risk outcomes leading to incorrect conclusion about decision making on risk initiated from accidents.The purpose of the study is to predict a long term risk of maritime accident using a 5 × 5 probabilistic risk matrix where each category of frequency and consequence is probabilistically estimated by a Markov chain model. The proposed method to calculate accident risk is illustrated using maritime accident data over 2016–2020 years. The findings are that the most probable frequency and consequence ranges of maritime accidents will be between 182 and 235 with probability of 0.3878 and between 6.8 and 11.6 fatalities with probability of 0.3791, respectively. The expected risk value was computed as 4.6506 on a scale of 2–10. For the validation of the proposed method 90 %, 95 %, and 99 % confidence intervals were constructed which were shown to contain the predicted risk value. The probabilistic risk matrix with Markov chain approach can be applied to predicting risks in different fields of industries.
Muhammad Ghous, S. Siddiqui, Publisher International Journal of Economic and Enviromental Geology
Wetlands are the source of vital ecosystems which provide human societies with essential and extremely valuable life-supporting functions. The rapid population growth and resultant exploitation of lands, water bodies, and forests have badly influenced wetland resources. Wetlands are non-market goods as they do not have market value. So, it is important to evaluate these resources economically to identify their significance. Therefore, this study aims to identify the visitors’ willingness to pay for the economic valuation of Salt Range wetlands comprised of Kalar Kahar, Uchali, Jhalar, Khabeki, and Namal Lakes. A qualitative method was used to gather relevant information from the respondents by using a questionnaire. By applying the willingness to pay (WTP) technique it was found that about 85.34% of tourists were agreed to visit these lakes because of their naturalness. Similarly, the mean WTP in Kalar Kahar lake was PKR. 1808, in Uchali lakes was PKR.1820 while in Namal lake it was PKR. 1848. It is concluded that all the lakes are equally important and economically valuable for the tourists as there was a frictional difference in mean WTP. It is suggested that these lakes should be conserved for future generations to sustain the long-term economic benefits for the concerned stakeholders through the initiation of ecotourism.
Background: There has been considerable effort amongst commercially-oriented services firms towards achieving sustainable supplier selection. However, little is known about the specific sustainability factors employed by healthcare supply chain managers when selecting medical materials vendors in developing economies, and the impact that such selection approaches has on the buying firm’s performance.
Objective: This study examines the sustainability factors mostly considered by Nigerian healthcare supply chain managers in their supplier selection processes. It further assesses the supply chain performance impact of the identified sustainable supplier selection factors.
Methodology: The study adopted a quantitative survey approach to randomly collect and analyse primary data from a large sample of 116 logistics and supply chain executives in 58 healthcare organisations in Nigeria. The descriptive scores (mean and standard deviation) were summarised and used to estimate the relationship among variables.
Results: Overall, the results suggest that economic sustainability towers above other sustainability factors for the selection of healthcare suppliers in the context of this study. In addition, economically sustainable supplier selection correlates strongly and positively with supply chain performance, while social sustainability supplier selection had moderate correlation with performance.
Conclusion: Based on these findings, it is our conclusion that most healthcare supply chain managers in Nigeria attaches importance to economic sustainability factors in their supplier selection process than environmental and social sustainability factors.
Shipment of goods. Delivery of goods, Transportation and communications
Abstract The COVID-19 pandemic has augmented pre-existing digitalization and environmental trends. In the maritime industry, one of the marked impacts of the pandemic is how the regard for technology has changed. There is now greater appetite and acceptance of digital solutions across the industry. This study investigates the ways the adoption of a series of digital technologies impact shipping firms’ efficiency, that will shed light on how industry stakeholders may derive value from data solutions, for making better operational decisions. We use cross-country firm-level data to evaluate the efficiency effects of maritime industry-level digital adoption. The results provide robust proof that working in a digitalized ecosystem is a way to promote efficiency, though not to the same extent across shipping firms and divisions. Impacts are relatively stronger in water transport activities than warehousing/support activities for transportation. Digital technologies may add to the growing diffusion in efficiency across shipping firms.
Shipment of goods. Delivery of goods, Transportation and communications
Abstract The Panama Canal expansion has influenced the development of ports within the Latin America and the Caribbean (LAC) region, intending to capitalise on economic opportunities through seaborne trade. Examining port performance is essential to ascertain the PCE impact on port efficiency within the LAC region. Stochastic frontier analysis (SFA) was used to determine the technical efficiency of the 19 major ports within the LAC from 2010 to 2018. The result indicates that, among the four (4) port performance indicators (berth length, port area, the number of cranes (STS gantry and mobile), and the number of berths), the number of STS gantry cranes and berth length had the largest and most significant impact. Some ports with high technical efficiency experienced TEU losses despite port infrastructural development and privatization. The findings also revealed that the increased competition among regional and US East and Gulf Coast ports has negatively impacted some LAC ports’ TEU volumes due to port proximity. The dynamism of the maritime sector, especially containerization, requires ports to implement value-added services and logistics centers in tandem with port performance indicators to remain sustainable and competitive in the maritime industry.
Shipment of goods. Delivery of goods, Transportation and communications
Martin J. du Plessis, Joubert van Eeden, Leila L. Goedhals-Gerber
Background: Globalisation has undoubtedly revolutionised the way modern society functions by connecting different people, economies, cultures and technology. This integration depends on the adequate movement of goods by increasingly more complex and longer global supply chains (SCs). The structure of the distribution chain and the individual activities that jointly facilitate the transportation of commodities such as fresh fruit have not been well defined, making it difficult and ambiguous to determine greenhouse gas emissions. Mapping the various distribution scenarios of fruit and stating the emission-generating activities not only enable the analysis and management of these activities but also provide a basis for calculating emissions.
Objectives: The key objective is to describe all the physical emission-generating distribution activities that take place during the international export of fresh fruit from South Africa. These activities were used to create distribution chain diagrams that define the structure of fresh fruit distribution.
Method: To identify activities, a literature review, direct observation of distribution activities at logistical facilities and unstructured interviews with operational managers at these facilities were performed. Scenario planning was used to combine generic activities into realistic distribution chain diagrams. The activities and diagrams were validated by semistructured interviews with four industry experts.
Results: Following the identification of emission-generating activities, five generic distribution chain diagrams were created that should represent all possible distribution scenarios for fresh fruit.
Conclusion: The generic distribution scenarios not only capture the various methods by which fresh fruit is exported from South Africa but also form the basis of seven important emission-related managerial practices.
Shipment of goods. Delivery of goods, Transportation and communications
Sebastian Jäger, Alexander Flick, Jessica Adriana Sanchez Garcia
et al.
The production, shipping, usage, and disposal of consumer goods have a substantial impact on greenhouse gas emissions and the depletion of resources. Machine Learning (ML) can help to foster sustainable consumption patterns by accounting for sustainability aspects in product search or recommendations of modern retail platforms. However, the lack of large high quality publicly available product data with trustworthy sustainability information impedes the development of ML technology that can help to reach our sustainability goals. Here we present GreenDB, a database that collects products from European online shops on a weekly basis. As proxy for the products' sustainability, it relies on sustainability labels, which are evaluated by experts. The GreenDB schema extends the well-known schema.org Product definition and can be readily integrated into existing product catalogs. We present initial results demonstrating that ML models trained with our data can reliably (F1 score 96%) predict the sustainability label of products. These contributions can help to complement existing e-commerce experiences and ultimately encourage users to more sustainable consumption patterns.
Ernst Moritz Hahn, Mateo Perez, Sven Schewe
et al.
When omega-regular objectives were first proposed in model-free reinforcement learning (RL) for controlling MDPs, deterministic Rabin automata were used in an attempt to provide a direct translation from their transitions to scalar values. While these translations failed, it has turned out that it is possible to repair them by using good-for-MDPs (GFM) Büchi automata instead. These are nondeterministic Büchi automata with a restricted type of nondeterminism, albeit not as restricted as in good-for-games automata. Indeed, deterministic Rabin automata have a pretty straightforward translation to such GFM automata, which is bi-linear in the number of states and pairs. Interestingly, the same cannot be said for deterministic Streett automata: a translation to nondeterministic Rabin or Büchi automata comes at an exponential cost, even without requiring the target automaton to be good-for-MDPs. Do we have to pay more than that to obtain a good-for-MDP automaton? The surprising answer is that we have to pay significantly less when we instead expand the good-for-MDP property to alternating automata: like the nondeterministic GFM automata obtained from deterministic Rabin automata, the alternating good-for-MDP automata we produce from deterministic Streett automata are bi-linear in the the size of the deterministic automaton and its index, and can therefore be exponentially more succinct than minimal nondeterministic Büchi automata.
To remain successful on the market and efficiently manage warehouses, many large and medium-sized enterprises are implementing and experiencing the benefits of working with cloud-based warehouse management systems (WMS). Contractors quickly install and configure the software on their servers to meet the customer's needs and provide support and updates. Warehouse owners no longer need to worry about hosting servers, providing power, maintaining large IT teams, etc. Machine learning and artificial intelligence algorithms, thanks to the ability to independently collect large volumes of data, improve with experience and adapt to different situations and act accordingly, are increasingly being introduced into warehouse management processes. It helps to analyze balances and deliveries, optimally plan the occupancy of the warehouses, picking of goods for shipments, the number and positions of shift workers, etc. The RFID (Radio Frequency Identification) technology is to put a label on each product unit, which contains encrypted data about weight, volume, reception, storage, etc. Technology is gradually replacing paper carriers with barcodes. After the solution implementation, accounting simplifies, and the number of errors reduces because it is easy to track the movement, find and ship goods. Actively carried out developments that will simplify, minimize the number of errors and speed up the receipt of goods in warehouses and markets. By improving machine learning methods, computer vision technologies will allow correct recognition of the goods by comparing them with templates entered in advance in the database, counting the number of units and separating the damaged ones. The article discusses the following technologies that significantly simplify the processing of goods in modern logistics centres. Outlined the advantages and disadvantages and why not all solutions are possible to implement because it has not yet been possible to achieve acceptable accuracy and price.