Hasil untuk "Shipment of goods. Delivery of goods"

Ei Phyu Kyi, Tao Feng, Jieyuan Lan et al.

The potential for drone delivery services to transform logistics systems and consumer behavior has gained increasing attention. However, comprehensive empirical evidence on consumer delivery choice behavior within the context of transportation and urban air logistics remains limited, particularly in Japan. This study addresses this gap by examining Japanese consumers' preferences and behavioral intentions toward drone delivery services. Using a stated preference (SP) survey and discrete choice modeling approaches, including multinomial logit (MNL) and mixed logit (MMNL) models, the analysis evaluates how delivery cost, delivery time, drop-off location, product type, and social influence affect delivery mode choices across different demographic groups. The results indicate that although consumers express interest in drone delivery, perceived cost and concerns related to reliability continue to constrain adoption. Younger and male consumers exhibit higher preferences for drone delivery, while product type, particularly daily consumer goods and medical or healthcare items, plays a significant role in shaping preferences. Post-estimation willingness-to-pay and elasticity analyses further highlight consumers' sensitivity to delivery pricing and speed attributes. Overall, the findings provide actionable insights for logistics service providers and policymakers regarding pricing strategies, service targeting, and deployment approaches for integrating drone delivery into Japan's evolving logistics system.

Nyashadzashe Chiwawa, Dominique E. Uwizeyimana

Background: South Africa’s air cargo industry is a critical driver of international trade and economic growth. However, outdated infrastructure and limited technology integration have led to inefficiencies, notably cargo delays, which undermine operational performance and competitiveness. Objectives: This study examines the relationship between infrastructural quality, technological adoption and cargo delays in South Africa’s air cargo sector. It aims to identify key operational bottlenecks and provide evidence-based recommendations to enhance efficiency. Method: This study used a survey of 120 key stakeholders across South Africa’s major airports, including cargo operators, airport officials and policymakers, to examine how infrastructure quality and technology adoption influence cargo delays. Results: Findings reveal that improved infrastructural quality and higher levels of technology adoption significantly reduce cargo delays. Regression analysis indicated that each unit increase in infrastructure quality and technology adoption corresponded to marked decreases in delay durations. Additionally, stakeholder perceptions on investment urgency varied, underscoring the importance of aligning operational and regulatory perspectives. Conclusion: Upgrading physical infrastructure and embracing digital innovations are essential for reducing cargo delays and enhancing the overall efficiency of South Africa’s air cargo operations. Contribution: This study offers empirical evidence that informs policy formulation and operational strategies, emphasising the need for public–private partnerships and regulatory reforms to build a more competitive and sustainable air cargo industry.

Egor Gagushin, Marios Mertzanidis, Alexandros Psomas

We study the fundamental problem of fairly allocating a multiset $\mathcal{M}$ of $t$ types of indivisible items among $d$ groups of agents, where all agents within a group have identical additive valuations. Gorantla et al. [GMV23] showed that for every such instance, there exists a finite number $μ$ such that, if each item type appears at least $μ$ times, an envy-free allocation exists. Their proof is non-constructive and only provides explicit upper bounds on $μ$ for the cases of two groups ($d=2$) or two item types ($t=2$). In this work, we resolve one of the main open questions posed by Gorantla et al. [GMV23] by deriving explicit upper bounds on $μ$ that hold for arbitrary numbers of groups and item types. We introduce a significantly simpler, yet powerful technique that not only yields constructive guarantees for indivisible goods but also extends naturally to chores and continuous domains, leading to new results in related fair division settings such as cake cutting.

Pouya Kananian, Arnesh Sujanani, Seyed Majid Zahedi

We study the fair and truthful allocation of m divisible public items among n agents, each with distinct preferences for the items. To aggregate agents' preferences fairly, we focus on finding a core solution. For divisible items, a core solution always exists and can be calculated by maximizing the Nash welfare objective. However, such a solution is easily manipulated; agents might have incentives to misreport their preferences. To mitigate this, the current state-of-the-art finds an approximate core solution with high probability while ensuring approximate truthfulness. However, this approach has two main limitations. First, due to several approximations, the approximation error in the core could grow with n, resulting in a non-asymptotic core solution. This limitation is particularly significant as public-good allocation mechanisms are frequently applied in scenarios involving a large number of agents, such as the allocation of public tax funds for municipal projects. Second, implementing the current approach for practical applications proves to be a highly nontrivial task. To address these limitations, we introduce PPGA, a (differentially) Private Public-Good Allocation algorithm, and show that it attains asymptotic truthfulness and finds an asymptotic core solution with high probability. Additionally, to demonstrate the practical applicability of our algorithm, we implement PPGA and empirically study its properties using municipal participatory budgeting data.

Yuri Matsumura, Suguru Otani

We propose a constrained generalized method of moments (GMM) estimator with some equilibrium uniqueness conditions for estimating the conduct parameter in a log-linear model with homogeneous goods markets. Monte Carlo simulations demonstrate that merely imposing parameter restrictions leads to not just inaccurate estimations but also some numerical issues, and adding the equilibrium uniqueness conditions resolves them. We also suggest a formulation of the GMM estimation to further avoid the numerical issues.

Khalid Y. Aram

This study focuses on order dispatch decisions within two-echelon supply chains, where order dispatch creates economic shipments to reduce delivery costs. Dispatching orders is often constrained by delivery windows, leading to penalty costs for untimely deliveries. Prolonged dispatch times can increase the lead time of orders and potentially violate these delivery windows. To balance the trade-offs between lead time and economic delivery, this study introduces a simulation-optimization approach for determining optimal ordering and dispatch rules. It emphasizes the intricacies of the order dispatch process and explores how these can be integrated into the simulation-optimization procedure to improve ordering and delivery decisions. The study evaluates various options for implementing dispatch rules, including the number of dispatch queues and prioritized dispatch. The results indicate that a single-queue, quantity-based, first-in-first-out dispatch approach achieves the greatest cost reduction while maintaining a desirable service level.

Dogan Altan, Dusica Marijan, Tetyana Kholodna

Detecting waypoints where vessels change their behavior (i.e., maneuvers, speed changes, etc.) is essential for optimizing vessel trajectories to increase the efficiency and safety of sailing. However, accurately detecting waypoints is challenging due to potential AIS data quality issues (i.e., missing or inaccurate messages). In this paper, we propose a five-step learning approach (SafeWay) to estimate waypoints on a given AIS trajectory. First, we interpolate trajectories to tackle AIS data quality issues. Then, we annotate historical trajectories by using an existing waypoint library that contains historical waypoints. As the historical waypoints are passage plans manually created by port operators considering sailing conditions at that time, they are not specific to other historical trajectories between the same ports. We, therefore, use a similarity metric to determine overlapping segments of historical trajectories with the historical waypoints from the waypoint library. Then, we build a transformer model to capture vessel movement patterns based on speed- and location-related features. We do not process location features directly to avoid learning location-specific context, but take into account tailored delta features. We test our approach on a real-world AIS dataset collected from the Norwegian Sea between Å lesund and Måløy and show its effectiveness in terms of a harmonic mean of purity and coverage, mean absolute error and detection rate on the task of detecting trajectory waypoints compared to a state-of-the-art approach. We also show the effectiveness of the trained model on the trajectories obtained from two other regions, the North Sea (London and Rotterdam) and the North Atlantic Ocean (Setubal and Gibraltar), on which the model has not been trained. The experiments indicate that our interpolation-enabled transformer design provides improvements in the safety of the estimated waypoints.

Israel Jacobovich, Erel Segal-Halevi

We consider the allocation of indivisible objects among agents with different valuations, which can be positive or negative. An egalitarian allocation is an allocation that maximizes the smallest value given to an agent; finding such an allocation is NP-hard. We present a simple polynomial-time algorithm that finds an allocation that is Pareto-efficient and almost-egalitarian: each agent's value is at least his value in an egalitarian allocation, minus the absolute value of a single object. The main tool is an algorithm for rounding a fractional allocation to a discrete allocation, by which each agent loses at most one good or gains at most one chore. Our algorithm generalizes and simplifies three previous algorithms. We discuss several aspects and observations about the algorithm and the problem at hand that open doors for efficient and robust implementations.

Maximilian Kronmueller, Andres Fielbaum, Javier Alonso-Mora

In this paper, we present a novel approach for fleet sizing in the context of flash delivery, a time-sensitive delivery service that requires the fulfilment of customer requests in minutes. Our approach effectively combines individual delivery requests into groups and generates optimized operational plans that can be executed by a single vehicle or autonomous robot. The groups are formed using a modified routing approach for the flash delivery problem. Combining the groups into operational plans is done by solving an integer linear problem. To evaluate the effectiveness of our approach, we compare it against three alternative methods: fixed vehicle routing, non-pooled deliveries and a strategy encouraging the pooling of requests. The results demonstrate the value of our proposed approach, showcasing its ability to optimize the fleet and improve operational efficiency. Our experimental analysis is based on a real-world dataset provided by a Dutch retailer, allowing us to gain valuable insights into the design of flash delivery operations and to analyze the effect of the maximum allowed delay, the number of stores to pick up goods from and the employed cost functions.

Yuri Matsumura, Suguru Otani

We revisit conduct parameter estimation in homogeneous goods markets to resolve the conflict between Bresnahan (1982) and Perloff and Shen (2012) regarding the identification and the estimation of conduct parameters. We point out that Perloff and Shen's (2012) proof is incorrect and its simulation setting is invalid. Our simulation shows that estimation becomes accurate when demand shifters are properly added in supply estimation and sample sizes are increased, supporting Bresnahan (1982).

Marco Alberto Javarone, Shaurya Pratap Singh

Commonly, the strategy revision phase in evolutionary games relies on payoff comparison. Namely, agents compare their payoff with the opponent, assessing whether changing strategy can be potentially convenient. Even tiny payoff differences can be crucial in this decision process. In this work, we study the dynamics of cooperation in the Public Goods Game, introducing a threshold $ε$ in the strategy revision phase. In doing so, payoff differences narrower than $ε$ entail the decision process reduces to a coin flip. Interestingly, with ordinary agents, results show that payoff thresholds curb the emergence of cooperation. Yet, the latter can be sustained by these thresholds if the population is composed of conformist agents, which replace the random-based revision with selecting the strategy of the majority. To conclude, agents sensible only to consistent payoff differences may represent 'real-world' individuals unable to properly appreciate advantages or disadvantages when facing a dilemma. These agents may be detrimental to the emergence of cooperation or, on the contrary, supportive when endowed with a conformist attitude.

Tenson Kachilala, Smart Dumba

Background: For complex fleet operations (e.g. unpredictable routing multiple corpse destinations, longer driver working hours and rough terrains) witnessed in the funeral assurance companies, it is increasingly difficult to strike a balance between cost-effectiveness and reducing environmental impacts. Existing studies do not address this gap on how firms with complex fleet management practices can or should adopt green fleet management (GFM). Against this background, this study explores the organisational constraints faced by companies to go green, as a starting point for effective and sustainable GFM adoption. Objectives: The aim of this study was to examine the drivers of and barriers to the adoption of sustainable fleet management, particularly in the context of complex transport operations as those prevailing in companies within the funeral assurance sector. Method: A qualitative research paradigm was adopted, based on a case study of three companies with a sizeable fleet size within the funeral assurance sector in Zimbabwe. We conducted extensive key informant interviews with different management levels of the three companies. Documentary analysis was performed on the legislative framework governing fleet management in Zimbabwe to assess its provision for GFM in Zimbabwe and its effectiveness therefrom. Results: An analysis of the institutional frameworks for environmental sustainability shows that Zimbabwe has some Acts of parliament that deal with GFM. However, there is a paucity in terms of enforcement. Furthermore, there are no financial or fiscal incentives for the acquisition of a green fleet. Environmental considerations were peripheral in the fleet acquisition, maintenance and disposal decisions. Conclusion and contribution: Environmental considerations are least prioritised when crafting fleet operations decisions; this is despite the existence of a myriad of Acts of Parliament championing environmental preservation from transport. This article contributes to transport policy and planning by calling for a close examination of the firm specific fleet operational characteristics with a view to develop appropriate strategies for GFM adoption.

Noleen Pisa

No abstract available.

Mehrangiz Shahbakhsh, Gholam Reza Emad, Stephen Cahoon

Digital transformation and automation in the shipping industry is resulting disruptive changes to ship design, operations, and manning that aim to enhance safety, efficiency, and the environmental sustainability of maritime logistics. While there is growing research interest in these areas, examining the role of human element in the new smart shipping context is largely neglected. Through a systematic literature review, this paper aims to explore the multi-dimensional impact of autonomous shipping technology resulting from the application of Industry 4.0 and future industrial revolutions on seafarers. The impacts include the changing role of seafarers on-board and the strategies required to engage seafarers in their transition from traditional shipping to autonomous and smart shipping. The paper concludes that Industry 4.0 is being challenged for its shortfall in recognition of the importance of human role and its intelligence in the expected current industrial revolution. As a result, there is a demand to look further and beyond Industry 4.0 by introducing the next generation of industrial revolution, namely Industry 5.0. This paper suggests that the impact of this revolution in the maritime industry can be defined by concepts such as Maritime 5.0, Shipping 5.0, Seafarer 5.0, Maritime Education and Training 5.0 (MET 5.0).

Peter J. Stavroulakis, Stratos Papadimitriou

Abstract Purpose Shipping is pivotal for global commerce, yet its externalities are not yet fully set into context, especially with reference to environmental impact. Shipping is a practise developed from the dawn of history. Its manifestation requires the introduction of relevant supporting industries as well, such as port, cargo, and logistics operations. The holistic shipping system has been growing with its main parameter pertaining to accounting cost minimisation. Yet, the shipping ecosystem has been able to exacerbate environmental, social, and health costs that in the end may prove that shipping, in the way that it is conducted, may not be as profitable as it may seem. Method This paper introduces a framework for the total cost of ownership in shipping, which includes a holistic approach as to the true costs associated with shipping practises. Through a structured literature review the relevant costs are identified and assessed, providing a complete framework as to the actual cost of shipping. Findings Shipping may appear to be profitable in some cases, but the bulk of its profit is based on practises that incur a plethora of costs that are externalised. This paper provides a clearer understanding of the total cost of shipping and the subsequent need of a paradigm shift, so that shipping may be able to portray its potential with reference to societal and environmental benefits. Conclusion Through frameworks such as the one presented in this work, activities and practises may be assessed as to their true impact and footprint and claim sustainability through a solid prism of holistic analysis and true profit for humanity, rather than focusing on accounting cost and turning a blind eye at other social, environmental, and health costs.

Tanja Blom, Wesley Niemann

Background: The coronavirus disease 2019 (COVID-19) pandemic has opened the world’s eyes to the impact that supply chain disruptions have on our society. Supply chain disruptions can result in various long-term effects, of which reputational risk is one of the biggest. A good reputation can create value for all stakeholders of a firm, however it can also expose a firm to risk. Reputational risk has been extensively studied in supply chain management; however, the management of reputational risk during supply chain disruption recovery (SCDR) has been neglected. Objective: This study explores reputational risk management during SCDR, between a logistics triad consisting of third party logistics providers (3PLs), their upstream suppliers and downstream customers within a South African context. Method: A generic qualitative design was employed to collect data from five logistics triads using semi-structured interviews. Results: The study found that reputational risk has a predominantly positive influence on the SCDR process. Furthermore, the study expands on existing literature by identifying additional approaches to manage corporate reputation during SCDR not evident in literature. These approaches include the use of control centres and involvement of the key account manager. Conclusion: This study creates awareness for the importance of reputational risk during SCDR and also provides managers with valuable insight into how reputational risk should be managed during SCDR.

Debanjan Datta, Sathappan Muthiah, John Simeone et al.

Timber and forest products made from wood, like furniture, are valuable commodities, and like the global trade of many highly-valued natural resources, face challenges of corruption, fraud, and illegal harvesting. These grey and black market activities in the wood and forest products sector are not limited to the countries where the wood was harvested, but extend throughout the global supply chain and have been tied to illicit financial flows, like trade-based money laundering, document fraud, species mislabeling, and other illegal activities. The task of finding such fraudulent activities using trade data, in the absence of ground truth, can be modelled as an unsupervised anomaly detection problem. However existing approaches suffer from certain shortcomings in their applicability towards large scale trade data. Trade data is heterogeneous, with both categorical and numerical attributes in a tabular format. The overall challenge lies in the complexity, volume and velocity of data, with large number of entities and lack of ground truth labels. To mitigate these, we propose a novel unsupervised anomaly detection -- Contrastive Learning based Heterogeneous Anomaly Detection (CHAD) that is generally applicable for large-scale heterogeneous tabular data. We demonstrate our model CHAD performs favorably against multiple comparable baselines for public benchmark datasets, and outperforms them in the case of trade data. More importantly we demonstrate our approach reduces assumptions and efforts required hyperparameter tuning, which is a key challenging aspect in an unsupervised training paradigm. Specifically, our overarching objective pertains to detecting suspicious timber shipments and patterns using Bill of Lading trade record data. Detecting anomalous transactions in shipment records can enable further investigation by government agencies and supply chain constituents.

Niclas Boehmer, Robert Bredereck, Klaus Heeger et al.

Fairly dividing a set of indivisible resources to a set of agents is of utmost importance in some applications. However, after an allocation has been implemented the preferences of agents might change and envy might arise. We study the following problem to cope with such situations: Given an allocation of indivisible resources to agents with additive utility-based preferences, is it possible to socially donate some of the resources (which means removing these resources from the allocation instance) such that the resulting modified allocation is envy-free (up to one good). We require that the number of deleted resources and/or the caused utilitarian welfare loss of the allocation are bounded. We conduct a thorough study of the (parameterized) computational complexity of this problem considering various natural and problem-specific parameters (e.g., the number of agents, the number of deleted resources, or the maximum number of resources assigned to an agent in the initial allocation) and different preference models, including unary and 0/1-valuations. In our studies, we obtain a rich set of (parameterized) tractability and intractability results and discover several surprising contrasts, for instance, between the two closely related fairness concepts envy-freeness and envy-freeness up to one good and between the influence of the parameters maximum number and welfare of the deleted resources.

Estie Serfontein, Krishna K. Govender

Background: Organisational control systems, such as quality assurance and corporate governance, configure an organisation’s internal environment to manage the velocity of change and pro-actively stabilise disturbances. Resilience in a socio-technical system is a multi-disciplinary approach to instil a system’s transformability and adaptive capacity to achieve desirable outcomes and continuous improvement. This study confirms theoretical postulations that detachment between the disciplines of quality assurance and corporate governance reduces resilience in a socio-technical system. Coherence between these disciplines in a complex socio-technical system is achieved through four components of organisational resilience: strategic management and company culture, monitoring and awareness, exposure management and responsive adaptation. Objectives: This study aimed to explore stakeholders’ perceptions of the relationship between the components of organisational resilience and organisational control systems in the South African aviation industry. Method: A cross-sectional survey was used to collect data from 203 stakeholders in the South African aviation industry. The data set was subjected to descriptive and inferential statistical analyses. Results: A strong positive linear relationship exists between organisational control systems and organisational resilience and its four components: Strategic management and company culture, Monitoring and awareness, Exposure management and Responsive adaptation. Conclusion: This study revealed that a harmonised application of organisational control systems, such as quality assurance and corporate governance, stimulates organisational resilience in a socio-technical system through the autonomous advancement of four components of organisational resilience. Furthermore, the robustness of organisational control systems activates an organisation’s capacity to adapt sustainably, whilst maintaining stakeholder value within complex socio-technical systems, such as the aviation industry.