The development of information technology in the digital era has encouraged logistics companies to adapt to web-based service systems to improve efficiency and customer satisfaction. PT YA Logistik, as a company engaged in goods delivery services, requires an integrated customer service system to streamline communication and manage service data effectively. This study aims to design and implement a web-based customer service system for PT YA Logistik using the Laravel framework. The software development method applied is Scrum, which enables the system to be developed gradually and adaptively according to changing user needs. The system provides main features such as shipping rate checking, shipment tracking, complaint management, and delivery data administration. System testing using the Black-box testing method shows that all functions operate according to user requirements without any functional errors. The results of this study indicate that the implementation of a web-based customer service system can improve operational efficiency, accelerate information delivery, and provide easier access to services for PT YA Logistik customers in a digital environment.
Zoe D. Wasserlauf-Pepper, Jun Su, A. Trmčić
et al.
E-commerce food distribution has grown drastically in recent years, a trend that was accelerated by the COVID-19 pandemic. The range of perishable products purchased through e-commerce as well as the distance over which these products travel to consumers has also increased considerably. Perishable goods are commonly available through various e-commerce channels (e.g., third-party grocery shopping and delivery, direct processor-to-consumer delivery, and overnight shipment via centralized distribution centers). These e-commerce distribution methods have grown to accommodate the increasing demand for grocery delivery, which can introduce the potential for temperature abuse of these perishable goods, possibly leading to premature spoilage and quality deterioration. To determine the effect of e-commerce distribution on the shelf life of dairy products, we assessed the variability of simulated and real e-commerce time-temperature profiles of fluid milk and Greek yogurt in 3 transportation channels: (1) direct-to-consumer, (2) distributor or business-to-consumer, and (3) business-to-business-to-consumer. To further identify how real dairy products ordered through business-to-business-to-consumer (e.g., grocery delivery to consumers from retail stores through a third party) channels, containers of 1.89 L (1/2 gal) milk and 157 mL (5.3 oz) Greek yogurt were delivered to customers from local retail chains, and temperatures were measured upon delivery. Finally, the temperature profiles measured during 1.89 L milk transportation were used to conduct microbial and sensory shelf-life testing on commercial containers of milk and were also incorporated into a previously developed computational model that predicts milk spoilage based on the initial concentration of primary groups of bacterial contaminants and other relevant conditions (e.g., storage temperature). Our time-temperature profile results showed that product temperature at the time of delivery ranged from 0.2 to 10.1°C for the direct-to-consumer pathway, -0.9 to 19.2°C for the business-to-consumer pathway, and 3.1 to 18.3°C during the simulated business-to-business-to-consumer pathway. Average milk and yogurt arrival temperatures from real business-to-business-to-consumer deliveries were 7.2°C and 7.3°C, respectively, and ranged from 3.1 to 10.5°C and 3.4 to 12.7°C, respectively. Results from fluid milk shelf-life microbial testing and end of shelf-life sensory testing showed limited effect following simulated short-term temperature exposure from e-commerce conditions, although more data are needed. This is supported by our model, which also indicates that there are minimal changes to expected microbial spoilage of fluid milk at the end of shelf life. However, our models only predict microbial growth and not sensory quality, which has a larger effect on consumer acceptance and should be assessed in future studies. Overall, our study provides important information on the exposure of dairy products to temperature variability during e-commerce distribution, which can be used to further develop strategies for controlling and monitoring the cold chain.
The logistics sector is a cornerstone of global supply chains, facilitating the timely and efficient movement of goods and services. Despite its critical role, the industry faces persistent challenges, including inefficiencies in shipment tracking, delivery delays, communication gaps, and reliance on outdated technological infrastructure. This research paper investigates these challenges and evaluates advanced solutions such as modern tracking technologies, predictive analytics, and automation in logistics operations. Adopting a mixed-methods approach, the study combines qualitative and quantitative analysis to examine industry trends and propose actionable interventions. The findings highlight the pivotal role of digital transformation in enhancing operational efficiency, minimizing delays, and improving customer satisfaction, ultimately driving the competitiveness of the logistics sector.
This research examines the factors that influence the safety climate in the maritime industry, focusing on employee competence, use of safety equipment, and safety training in Indonesian shipping companies. The research proposes that variations in ship operations contribute to different levels of difficulty and quality of work, with implications for a varying safety climate. The analysis technique used Exploratory Factor Analysis (EFA) and Ordinary Least Squares (OLS) regression with 4 dimensional indicators namely competence, use of safety tools, safety training, and safety climate. The results showed that there is a positive and significant influence between employee competence, use of safety equipment, and safety training on the safety climate in Shipping Companies in Indonesia. The findings indicate the importance of investing in comprehensive safety training and the provision of adequate safety equipment as key factors in improving the safety climate for policy making in the maritime industry to create a safe and productive work environment.
Low Earth Orbit (LEO) satellite ISPs promise universal Internet connectivity, yet their interaction with content delivery remains poorly understood. We present the first comprehensive measurement study decomposing Starlink's web content delivery performance decomposed across Point of Presence (PoP), DNS, and CDN layers. Through two years of measurements combining 225K Cloudflare AIM tests, M-Lab data, and active probing from 99 RIPE Atlas and controlled Starlink probes, we collect 6.1M traceroutes and 10.8M DNS queries to quantify how satellite architecture disrupts terrestrial CDN assumptions. We identify three distinct performance regimes based on infrastructure density. Regions with local content-rich PoPs achieve near-terrestrial latencies with the satellite segment dominating 80-90% of RTT. Infrastructure-sparse regions suffer cascading penalties: remote PoPs force distant resolver selection, which triggers CDN mis-localization, pushing latencies beyond 200 ms. Dense-infrastructure regions show minimal sensitivity to PoP changes. Leveraging Starlink's infrastructure expansion in early 2025 as a natural experiment, we demonstrate that relocating PoPs closer to user location reduces median page-fetch times by 60%. Our findings reveal that infrastructure proximity, not satellite coverage, influences web performance, requiring fundamental changes to CDN mapping and DNS resolution for satellite ISPs.
In this paper, we study a shipment rerouting problem (SRP) which generalizes many NP-hard sequencing and packing problems. A SRP's solution has ample practical applications in vehicle scheduling and transportation logistics. Given a network of hubs, a set of goods must be delivered by trucks from their source-hubs to their respective destination-hubs. The objective is to select a set of trucks and to schedule these trucks' routes so that the total cost is minimized. The problem SRP is NP-hard; only classical approximation algorithms have been known for some of its NP-hard variants. In this work, we design classical algorithms and quantum annealing algorithms for this problem with various capacitated trucks. The algorithms that we design use novel mathematical programming formulations and new insights into solving sequencing and packing problems simultaneously. Such formulations take advantage of network infrastructure, shipments, and truck capacities. We conduct extensive experiments showing that in various scenarios, the quantum annealing solver generates near-optimal or optimal solutions much faster than the classical algorithm solver.
This study aims to analyze the liability of expedition service providers and consumer protection related to the loss of goods, focusing on Decision Number 62/Pdt.Sus-BPSK/2023/PN.Mkd. The expedition business has significant growth potential, driven by increasing logistics demands, which encourages courier companies to offer various delivery services. However, these services are not always satisfactory, as issues of lost goods frequently occur. Such incidents can be categorized as breaches of contract since expedition companies failed to fulfill their obligations to consumers, raising questions about the liability of business actors and consumer protection against the loss of goods during shipment. This research employs a normative juridical method with a statutory approach. The findings indicate that business actors are obliged to compensate for the value of the lost goods in accordance with the provisions of the Consumer Protection Law. In the case of J&T Cargo, the compensation offered was significantly below the value of the lost goods, resulting in consumer dissatisfaction and prompting objections to be filed in court. This study recommends stricter enforcement of the law to protect consumers and ensure that business actors fulfill their obligations under applicable legal provisions. It also highlights the importance of resolving disputes through legal channels to provide certainty for consumers and improve service quality in the goods delivery industry.
The CMR provides a predictable system of liability for carriers and insurance to both carriers and their clients about the risks involved in the shipment of goods. CMR Convention establishes a strict liability regime for the carrier, meaning that the carrier is generally liable for any loss, damage or delay of the goods from the time they take the goods into custody until delivery. According to CMR provisions, this liability is limited to a fixed amount per kilogram of gross weight lost or damaged. Even if there is a limited amount, the loss, damage or the delay of the goods can lead to substantial claims. CMR insurance mitigate the financial risks associated with this liability, playing thus a crucial role in international road transport.
The advancement of digital technology has driven many service companies to transform toward faster, more efficient, and accurate systems. Himeji Express Banjarmasin, a company engaged in the field of goods delivery services, still faces challenges in data management and service processes that are mostly carried out manually. This condition leads to delays in shipment tracking, data entry errors, and limitations in report generation. To address these issues, a digital application was designed to optimize the delivery service processes at Himeji Express Banjarmasin. The application was developed using the Unified Modeling Language (UML) approach to model system requirements through use case, activity, sequence, and class diagrams. The implementation process utilized Sublime Text and XAMPP software, supported by an integrated database. The results show that the developed digital application can improve the effectiveness of managing customer, employee, pricing, cargo, and transaction data while generating automatic and real-time reports. This application enhances operational efficiency, transparency, and responsiveness to customer needs at Himeji Express.
In the context of machine learning, this study investigates the efficacy of different learning methods in analyzing big data in supply chain and accuracy of predicting logistics late delivery, while exploring impacts of hyperparameters tuning on different model evaluation metrics. The research employed comprehensive variables such as destination, timestamps, and quantity of goods, and evaluated them comprehensively based on multiple indicators including accuracy, recall and precision. The Decision Tree Classifier model after parameter tuning displays the best performance, achieving a 0.7081 test accuracy, as well as a precision score of 0.7601 and recall score of 0.7081, indicating a relatively balanced overall performance. The variable ‘Days for shipment (scheduled)’ comes up as the variable with the highest contribution ranking for predicting, importance doing 0.6840. This study provides a substantial data support for supply chain risk warning system, which is conducive to reduction of logistics waste and raising operational efficiency in supply chain networks.
A multi-period, strategic and tactical planning model was developed to take care of shipment route for these perishable goods from the farm gate to the consumer’s zone with different cold-hubs via different routes options. The S-T model addressed sensitivity and ambiguity associated with seasonal demand and product loss due to delay in shipment, to ensure timely and efficient delivery of products. Five contradicting objectives (Profit, Power Rating, Credit Performance, Response time and Distributors Reputation) were optimized, initially a single objective optimization was employed to attain a single best solution and then a multi-objective optimization to achieve a compromise solution using Chebyshev goal programming. It is indicated from the S-T model, when multiple criteria are considered in long term decision making models, direct shipments from the plant are not always the best supplying alternative, even when the demand is adequate. In Scenario 1 the profit criterion weight was not significant enough to bias the decision to improve the number of direct shipments from the plants. The model recommended to directly supply only 44% (in average) of the monthly demand from the farms whereas the model that only considered profit (Scenario 1) advised to directly ship from the farms for 88% of the monthly demand. On the contrary, Scenario 2 applied a highly magnified profit weight, which led to 62% of the demand being supplied directly from the farms.
The advancement of information technology has facilitated online buying and selling transactions, but it has also led to potential breaches of contract (wanprestasi) by business entities, such as the delivery of non-conforming goods, shipment delays, and unilateral cancellations. This article examines the legal accountability of business actors in online sales agreements through a normative juridical approach, analyzing statutory regulations and judicial decisions. The findings reveal that common types of breach include product discrepancies, delayed deliveries, and failure to fulfill delivery obligations despite completed payments. In accordance with Articles 1239–1243 of the Indonesian Civil Code, Law No. 8 of 1999 on Consumer Protection, and Law No. 19 of 2016 on Electronic Information and Transactions, business entities are legally liable for such breaches. Court decisions, such as Decision No. 629/Pdt.G/2020/PN Jkt.Sel, illustrate how judges evaluate the elements of breach based on evidence, the principle of good faith, and consumer loss. This study underscores the necessity of enhancing legal awareness among business actors and strengthening dispute resolution mechanisms to ensure fairness for consumers within the rapidly evolving digital business ecosystem.
The rising demand for fresh, locally sourced agricultural products, along with the need for efficient distribution approaches, has prompted interest in direct-to-consumer ecommerce models within the agriculture industry. Existing agricultural distribution systems frequently incorporate intermediaries, resulting in inefficiencies, inflated costs and delays in the delivery of perishable goods. The development of advanced technologies, including artificial intelligence (AI), has facilitated the development of more efficient, transparent, and consumer-oriented agricultural distribution systems. This paper outlines the framework of an intelligent business-to-consumer ecommerce platform for the direct distribution of agricultural products using machine learning to improve shipments, transparency and user experience. The proposed framework analyzes key factors such as price, freshness, and shipping conditions to deliver customized product recommendations and improve shipment assignment. The intelligent product recommendation and shipment assignment ensures user preference as well as the freshness of perishable goods while reducing delays and transportation expenses. Also, the proposed framework comprises of overall conceptual framework including, data collection and preprocessing steps, feature extraction, the use of recurrent neural network and singular value decomposition to train data points and evaluation metrics such as RMSA, MAE, ranking quality and cold start testing to validate intelligent model efficiency. Also, it facilitates interaction between consumers and producers, promoting a transparent, efficient, and economical distribution process. The intelligent model continuously adjusts to customer preferences and market dynamics, improving efficiency in operation and user satisfaction.
Lean strategy, aimed at optimizing resources, minimizing energy usage, and achieving zero waste in the production process, has been increasingly embraced to reduce systemwide costs in manufacturing. However, practitioners in small and medium-sized enterprises (SMEs) often lack the necessary expertize to implement lean strategies successfully. This study systematically examines the impact of lean strategy on the financial performance of Chinese SMEs. Specifically, we categorize lean strategy into two components: inventory leanness and operational leanness. We introduce a novel measure, the empirical production leanness indicator (EPLI), to quantify systematic production practices aimed at waste reduction. Drawing on a large sample of SMEs, our empirical findings suggest that both inventory leanness and operational leanness exhibit an inverted U-shaped relationship with an SME’s financial performance. In conclusion, this study contributes to the lean literature and offers significant practical implications for SMEs seeking to benefit from adopting lean strategies.
In recent years, with rising consumer demand, fresh products have gained increasing attention, leading to rapid growth in the fresh food market. However, due to their perishable nature and sensitivity to storage conditions, fresh products are vulnerable to damage during transportation. Improper handling, excessive transit times, and physical impacts can result in significant losses. As a result, enhancing the efficiency of fresh product distribution while maintaining quality has become critical to the further development of the fresh food industry. Using Y chain supermarket as a case study, this paper investigates the logistics of fresh product distribution, identifying current challenges and inefficiencies. Through literature review, expert interviews, and comparative analysis, the study offers strategic recommendations for optimizing fresh product delivery routes to improve distribution efficiency and product quality.
When individuals interact in groups, the evolution of cooperation is traditionally modeled using the framework of public goods games. These models often assume that the return of the public good depends linearly on the fraction of contributors. In contrast, in real life public goods interactions, the return can depend on the size of the investor pool as well. Here, we consider a model in which the multiplication factor (marginal per capita return) for the public good depends linearly on how many contribute, which results in a nonlinear model of public goods. This simple model breaks the curse of dominant defection found in linear public goods interactions and gives rise to richer dynamical outcomes in evolutionary settings. We provide an in-depth analysis of the more varied decisions by the classical rational player in nonlinear public goods interactions as well as a mechanistic, microscopic derivation of the evolutionary outcomes for the stochastic dynamics in finite populations and in the deterministic limit of infinite populations. This kind of nonlinearity provides a natural way to model public goods with diminishing returns as well as economies of scale.
We formulate the problem of fair and efficient completion of indivisible goods, defined as follows: Given a partial allocation of indivisible goods among agents, does there exist an allocation of the remaining goods (i.e., a completion) that satisfies fairness and economic efficiency guarantees of interest? We study the computational complexity of the completion problem for prominent fairness and efficiency notions such as envy-freeness up one good (EF1), proportionality up to one good (Prop1), maximin share (MMS), and Pareto optimality (PO), and focus on the class of additive valuations as well as its subclasses such as binary additive and lexicographic valuations. We find that while the completion problem is significantly harder than the standard fair division problem (wherein the initial partial allocation is empty), the consideration of restricted preferences facilitates positive algorithmic results for threshold-based fairness notions (Prop1 and MMS). On the other hand, the completion problem remains computationally intractable for envy-based notions such as EF1 and EF1+PO even under restricted preferences.
We consider the problem of fairly allocating a combination of divisible and indivisible goods. While fairness criteria like envy-freeness (EF) and proportionality (PROP) can always be achieved for divisible goods, only their relaxed versions, such as the ''up to one'' relaxations EF1 and PROP1, can be satisfied when the goods are indivisible. The ''up to one'' relaxations require the fairness conditions to be satisfied provided that one good can be completely eliminated or added in the comparison. In this work, we bridge the gap between the two extremes and propose ''up to a fraction'' relaxations for the allocation of mixed divisible and indivisible goods. The fraction is determined based on the proportion of indivisible goods, which we call the indivisibility ratio. The new concepts also introduce asymmetric conditions that are customized for individuals with varying indivisibility ratios. We provide both upper and lower bounds on the fractions of the modified item in order to satisfy the fairness criterion. Our results are tight up to a constant for EF and asymptotically tight for PROP.
RESUMO: O estudo buscou analisar os aspectos jurídicos concernente às questões relacionadas ao juízo de sobrestadia em nexo com os serviços prestados por terminais de armazenagem de contêineres, às relações jurídicas fixadas entre terminais, exportadores e armadores, à estrutura jurídica dos contratos e acordos firmados entre tais sujeitos, bem como, temas polêmicos a respeito de regulamentos e normas publicados pela Agência Nacional de Transportes Aquaviários (ANTAQ). Para terminar, objetiva-se atestar que, a interposição do ente regulador no acaso provoca descumprimento aos princípios da livre iniciativa e de livre concorrência, trabalhando contra a própria regularização do mercado que, em conclusão, resulta em serviços mais caros ao usuário.
Shahrzad Nikghadam, Ratnaji Vanga, Jafar Rezaei
et al.
Cooperation between vessel service providers can improve the performance of ports. However, the potential impact of such cooperation has not yet been quantitatively addressed in the literature. We present an assessment using a port simulation model where the exchange of information has been made explicit. Cooperation is modelled as information exchange between the pilotage and towage service providers for the deployment of pilots and tugboats. A first application of the model is shown for the case of Port of Rotterdam. We find that time savings of up to 30% in waiting times can be achieved, while both service providers improve their performance. These findings provide empirical confirmation of the expected benefits of cooperation in ports as voiced in the literature. Furthermore, the results underscore the importance of moving beyond an ad-hoc synchronizations of these services towards systematic cooperation, to the benefit of ports as well as the service providers.