Transport Delay Research Articles

Public Transport Delay Prediction using Deep Learning

A system of trains, buses, subways, ferries, and other vehicles that are accessible to the public is referred to as public transportation, also known as public transit or mass transit. These networks are usually run by private or public organisations are made to efficiently transport large numbers of people in urban and suburban areas. It usually operates on set schedules and routes and has a listed fare for each journey. Long wait periods and lengthy travel times resulting from delays are two problems that frequently plague public transportation services. There are several things that can cause a delay in public transport, such as an excess of passengers, heavy traffic, accidents, and other unforeseen circumstances. The availability of a more accurate delay prediction for public transportation might increase users’ confidence and their willingness to pay more for transit services. Over the past two decades, a number of studies on prediction algorithms for transportation data have been proposed. Most of the work is on machine learning model development, focusing on delay prediction and taking into account several factors such as weather conditions and infrastructure issues. This paper proposes a deep learning model to predict public transportation delays using data from public transportation and the weather. The results obtained from this research work are compared with several other existing works. Our experiment has demonstrated that the deep neural network (DNN) is the best model to predict transit delay compared to several other machine learning and deep learning models.

Unveiling risk factors influencing the selection of the Northern Sea Route: A conjoint analysis approach for Japanese shippers

This paper explores how Japanese corporations assess risks associated with using the Northern Sea Route (NSR) as a new maritime transport route in Asia and identifies measures to promote its usage. We address two key questions: (1) What risks influence shippers' route choices in maritime transport? (2) Does risk evaluation vary by cargo type and company size? Using choice-based conjoint analysis and a conditional logit model with online survey data, we identified five main risk factors influencing shippers: route unavailability rate, delay probability, piracy probability, transport costs, and war conditions, ranked in importance from highest to lowest as war conditions, delay probability, transport costs, route unavailability rate, and piracy probability. Additionally, the risk factors significantly influencing route selection were found to be robust, showing minimal variation across company size, type of trade (import/export), and the nature of the goods transported. Our findings suggest several policy implications. Diplomatic efforts are crucial for safe vessel navigation on the NSR. Government initiatives should focus on reducing transport delays through technology investments and implementing strategies to decrease NSR delay rates without increasing shippers' costs. Additionally, emphasizing the lower piracy risks on the NSR compared to Suez Canal Route could boost its attractiveness.

Mobile Critical Care in Resource-Limited Settings: An Unmet Need.

Care of the critically ill in resource-limited areas, inside or outside the intensive care unit (ICU), is indispensable. Murthy and Adhikari noted that about 70% of patients in low-middle income (LMIC) areas could benefit from good critical care. Many patients in resource-limited settings still die before getting to the hospital. Investing in capacity building by strengthening and expanding ICU capability and training intensivists, critical care nurses, respiratory therapists, and other ICU staff is essential, but this process will take years. Also, having advanced healthcare facilities that are still far from remote areas will not do much to alleviate distance and mode of transportation as barriers to achieving good critical care. This paper discusses the importance of mobile critical care units (MCCUs) in supporting and enhancing existing emergency medical systems. MCCUs will be crucial in addressing critical delays in transportation and time to receive appropriate lifesaving critical care in remote areas. They are incredibly versatile and could be used to transfer severely ill patients to a higher level of care from the field, safely transfer critically ill patients between hospitals, and, sometimes, almost more importantly, provide standalone short-term critical care in regions where ICUs might be absent or immediately inaccessible. MCCUs should not be used as a substitute for primary care or to bypass readily available services at local healthcare centers. It is essential to rethink the traditional paradigm of 'prehospital care' and 'hospital care' and focus on improving the care of critically ill patients from the field to the hospital.

Management of Patients With Cardiac Arrest Requiring Interfacility Transport: A Scientific Statement From the American Heart Association.

People who experience out-of-hospital cardiac arrest often require care at a regional center for continued treatment after resuscitation, but many do not initially present to the hospital where they will be admitted. For patients who require interfacility transport after cardiac arrest, the decision to transfer between centers is complex and often based on individual clinical characteristics, resources at the presenting hospital, and available transport resources. Once the decision has been made to transfer a patient after cardiac arrest, there is little direct guidance on how best to provide interfacility transport. Accepting centers depend on transferring emergency departments and emergency medical services professionals to make important and nuanced decisions about postresuscitation care that may determine the efficacy of future treatments. The consequences of early care are greater when transport delays occur, which is common in rural areas or due to inclement weather. Challenges of providing interfacility transfer services for patients who have experienced cardiac arrest include varying expertise of clinicians, differing resources available to them, and nonstandardized communication between transferring and receiving centers. Although many aspects of care are insufficiently studied to determine implications for specific out-of-hospital treatment on outcomes, a general approach of maintaining otherwise recommended postresuscitation care during interfacility transfer is reasonable. This includes close attention to airway, vascular access, ventilator management, sedation, cardiopulmonary monitoring, antiarrhythmic treatments, blood pressure control, temperature control, and metabolic management. Patient stability for transfer, equity and inclusion, and communication also must be considered. Many of these aspects can be delivered by protocol-driven care.

Factors Affecting Maternal Mortality Rates in Nigeria: A Review of Challenges and Potential Solutions

Maternal mortality is a significant public health issue in Nigeria, accounting for approximately 23% of global maternal deaths. This review explored the main factors affecting maternal mortality rates in Nigeria and proposed potential solutions. Accurate data collection on maternal health in Nigeria, especially in rural areas, remains challenging. Aims: this paper aimed to identify the key factors contributing to maternal mortality in Nigeria and proposed solutions to address this issue. Study design: A qualitative analysis of literature review narration was employed taking into account the research methodology, instrument interpretation, and data analysis in order to avoid bias and misinterpretation of result findings. Methodology: The methodology was designed to systematically gather, analyse, and synthesise data from multiple sources, including the peer-reviewed academic literature, government reports, and NGO publications. To ensure rigor and reproducibility, in the literature search were utilised several databases and search engines beyond Google, including PubMed, Scopus, Web of Science, Google Scholar, Semantic Scholar, and Research Gate. 50 published papers and articles from credible sources were reviewed in the study, identifying the key issues such as inadequate healthcare infrastructure, socio-economic challenges, cultural and behavioural practices, as well as political factors. Results: The findings revealed that the major causes of maternal mortality in Nigeria included haemorrhage, infection, unsafe abortion, hypertensive diseases of pregnancy, and obstructed labour. There were cases of socio-economic factors such as unavailability of electricity, transportation delay, the lack of skilled medical personal and cultural factors such as traditional beliefs. Despite various interventions, progress in reducing maternal mortality has been limited. Conclusion: This paper emphasised the need for continuous investment in maternal and child health, improvements in healthcare infrastructure, education, and effective policy implementation. A holistic approach that integrates organisational structures, technical expertise, human experiences, and patient needs is essential for effectively reducing maternal mortality rates.

A simulation-based approach to analysing delays in the transport of critically ill neonates

ABSTRACT Neonatal interfacility transport ensures that critically ill neonatal patients can receive higher levels of care when needed. Delays in the transport process impact the quality of care and increase the risk of medical complications. The objective of this study is to investigate the operations-related factors that contribute to transport delays and explore the role of discrete-event simulation in improving the transport process. Semi-structured interviews were conducted with stakeholders to understand the neonatal interfacility transport process. Analysis of historical call logs and transport data was performed to identify inputs to the discrete-event simulation model. Statistical tests were used to identify the effect of various factors on wait time and transport time in the simulation model. High patient volume and limited bed capacity at the receiving hospitals are identified as bottlenecks that lead to extended wait time and transportation time. Additionally, having more geographically distributed ambulance resources does not significantly help with the time delays when the receiving hospital capacity stays unchanged. Discrete-event simulation models can be used to investigate the effects of operations-related factors in the interfacility transport of critically ill neonates to support future process improvement.

Route Planning for Intra-Hospital Patient Transportation Using Metaheuristics and Mixed Integer Linear Programming.

Healthcare processes are complex and involve uncertainties to influence the service quality and health of patients. Patient transportation takes place between the hospitals or between the departments within the hospital (i.e., Inter- or Intra-Hospital Transportation respectively). The focus of our paper is route planning for transporting patients within the hospital. The route planning task is complex due to multiple factors such as regulations, fairness considerations (i.e., balanced workload amongst transporters), and other dynamic factors (i.e., transport delays, wait times). Transporters perform the physical transportation of patients within the hospital. In principle, each job allocation respects the transition time between the subsequent jobs. The primary objective was to determine the feasible number of transporters, and then generate the route plan for all determined transporters by distributing all transport jobs (i.e., from retrospective data) within each shift. Secondary objectives are to minimize the sum of total travel time and sum of total idle time of all transporters and minimize the deviations in total travel time amongst transporters. Our method used multi-staged Local Search Metaheuristics to attain the primary objective. Metaheuristics incorporate Mixed Integer Linear Programming to allocate fairly the transport jobs by formulating optimization constraints with bounds for satisfying the secondary objectives. The obtained results using formulated optimization constraints represent better efficacy in multi-objective route planning of Intra-Hospital Transportation of patients.

Assessing the stability of uncentrifuged serum and plasma analytes at various post-collection intervals

Abstract Objectives Our study aimed to assess the stability of 26 biochemistry analytes in serum or plasma samples separated from blood samples centrifuged at different time intervals after collection, simulating sample transport via despatch delivery systems. Methods Blood from forty-one volunteers were collected using five serum separator tubes (SST) and five fluoride oxalate tubes (FOT) for each volunteer following written informed consent. Each of the five tubes in both groups of SST and FOT was centrifuged at one of the time intervals: 0.5 h, 4 h, 8 h, 12 and 24 h after collection. These samples were left standing prior to centrifugation at room temperature. We calculated the percentage difference for each analyte between the 0.5 h and other time intervals to assess analyte stability. The percentage difference was compared to the desirable specification for bias and reference change value (RCV). Results Mean concentration of serum potassium showed a significant increase in the percentage RCV after 8 h, while CKMB showed an increase after 12 h of delayed centrifugation compared to the baseline (0.5 h). There were no significant percentage RCV for the other analytes at all timelines. Conclusions Serum potassium and CKMB were stable up to 8 and 12 h of delayed centrifugation respectively whilst all other analytes appear stable up to 24 h, suggesting that sample transport delay of up to 8 h, with the condition that room temperature is maintained, may not have a significant impact on accuracy of the biochemistry/immunochemistry test results.

External quality assurance experience with Royal College of Pathologists of Australasia Program at an academic hospital in South Africa.

Laboratories use their performance in external quality assurance (EQA) to establish quality planning strategies and to assess whether testing processes require improvement. The EQA performance of the hematology and coagulation test parameters on the Royal College of Pathologists of Australasia EQA program was evaluated over a 4-year cycle at an academic hospital in Johannesburg, South Africa. The test performance was determined from analytical quality specification (APS) and/or z-scores. Bias and imprecision were used to calculate sigma (σ) metric scores. Specifications from European Federation of Laboratory Medicine and/or biological variation were applied. The laboratory achieved a mean testing score of 98.7±4.0%. There were 103 (10.7%) unacceptable results. On investigation, root causes included: presurvey issues (83%), transcription errors (9%), random errors (6%), and test performance errors (3%). All test parameters evaluated achieved an acceptable median APS during the study period. The mean z-scores, however, were >2 and unacceptable for mean cell hemoglobin concentration and hematocrit. On investigation, this was attributed to significant delay in transport and storage of full blood count samples. White cell count and d-dimer achieved a σ ≥ 6. EQA participation assisted the laboratory in maintaining a quality system. Close monitoring is necessary for international laboratories to avoid sample delays that can affect result quality.

Evaluation of solid medical waste management system in Undata Regional General Hospital, Palu city, Central Sulawesi Province, Indonesia

Waste is an environmental problem that is still not fully resolved properly even though the resulting impact has a major effect on environmental pollution, especially solid medical waste. The purpose of this study was to assess the characteristics of solid medical waste at Undata Hospital based on its sources and types, calculate the average weight of solid medical waste generated per day, and evaluate the solid medical waste management system with sorting, packaging, collection and transportation modes in accordance with the criteria of Permen of Environment and Forestry Number 56 of 2015 and Permenkes Number 2 of 2023. This research uses a qualitative approach with a descriptive research type. This research was conducted in August-September 2023. The sampling technique in this study used Purposive Sampling, with 18 informants selected from each unit/room/installation at Undata Hospital, Palu City. Based on the results of the study, it was found that every day Undata Palu Hospital produces domestic waste as much as ± 270 kg / day. The results of the evaluation of the solid medical waste management system at Undata Palu Hospital show that basically it is quite effective but not optimal, because the storage process shows non-compliance with the guidelines for medical waste management by the Ministry of Health Number 2 of 2023, namely storage in TPS which should not be more than 2x24 hours, but in fact the accumulation of solid medical waste is stored for 1 month in the LB3 TPS due to delays in transportation by third parties. This causes a large amount of solid waste in the TPS so that the TPS becomes full and dangerous because the waste undergoes a process of decomposition and decay, which is harmful to the environment and human health. Undata Hospital needs to maximize the procurement of internal medical waste processing equipment (incineration equipment) which needs to be supported by the Environmental Agency and the relevant Health Office to prevent environmental pollution from medical activities.

Aquila Optimized Fuzzy Deep Belief Network for Secure Data Transmission in WSN

A wireless sensor network (WSN) is made up of several independent sensor nodes that are able to interpret, analyze, and work with data. It is generally recognized that security and limited energy are the two challenging tasks with WSNs. To address these challenges, a novel Aquila-optimized fuzzy deep belief network (AO-FDBN) model has been proposed in this paper. The suggested AO-FDBN framework consists of three stages. Initially, the Aggregator has been selected by using the Aquila optimization algorithm. Secondly, the data from the aggregator are encrypted by using the blowfish algorithm. Finally, the optimal route has been selected by using the fuzzy-deep belief network (DBN). Packet delivery ratio (PDR), transport delay, energy usage, and network lifetime are evaluated between the suggested framework and current methods. Experimental results specify that the suggested AO-FDBN approach achieves higher performance of 22.617%, 14.22%, and 15.64% than TEEFCA, HESC, and SEPC methods. This system is more effective and secure for real-time applications.

Selecting Resilient Strategies for Cost Optimization in Prefabricated Building Supply Chains Based on the Non-Dominated Sorting Genetic Algorithm-Ⅱ: Facing Diverse Disruption Scenarios

As a new sustainable building production mode, prefabricated building supply chains can realize energy saving, environmental protection and full cycle value maximization of building products. Prefabricated building supply chains often experience disruptions due to supply instability, transportation delay and force majeure, resulting in project delays and cost escalations and posing challenges to the sustainable development objectives of enterprises. Therefore, it is important and essential to study the strategy of enhancing the resiliency of prefabricated building supply chains, which has not been comprehensively explored in previous papers. This paper constructs decision-making models for supply chain cost resilience strategies under varying scenarios of supply disruptions, incorporating both redundant inventory and back-up supplier strategy. It considers the total cost and resilience of the supply chain as dual objective functions. Parameter-tuned non-dominated sorting genetic algorithm-П (NSGA-П) algorithms were used innovatively to solve the project case, and the impacts of the redundant inventory coefficient and back-up supplier supply price coefficient on the model result were analyzed. The results indicate that the supply chain with resilience construction has a superior capability to cope with disruption. The results show that when there is a mild supply disruption, the general contractor uses the capacity within the supply chain and chooses a redundant inventory strategy to restore resilience. In the event of moderate disruption, both the easy inventory strategy and back-up supplier strategy are selected to maintain supply chain stability. In the event of a severe disruption, only the back-up supplier strategy is selected to cover the losses and maintain the project schedule. In addition, the choice of resilience strategy is impacted by the inventory levels and component prices of back-up suppliers. It further verifies the effectiveness of the model and the impacts of uncertain parameters in the model on the results. This study contributes to enhancing the resilience management of the prefabricated building supply chain by the general contractor, thereby elevating the overall efficiency and competitiveness of the supply chain and furthering the sustainable development of prefabricated buildings.

IMPACT ON CYBER SHOPPING DURING COVID-19 PANDEMIC

In the pandemic situation around the world caused by COVID-19, cyber shopping plays a crucial role in a customer’s life. Cyber shopping is developing and growing due to the increasing usage of technology such as smartphones and the internet. Cyber shopping allows the customers to stay at home and make purchases. It is vital as social distancing is not always maintained when one leaves their house to purchase goods. The objective of this paper is to analyze the impact COVID-19 has on cyber shopping purchases. It also includes recognizing the factors that have influenced the buying patterns during COVID-19. For this research, data collection is from secondary data. In this research, the data collection method is multiple sources. The study conveys that cyber shopping is growing due to COVID-19. The majority of the customers used cyber shopping to purchase clothes and electronics. Customers are giving priority to safety. The concern that the customers have is sharing their personal information on cyber websites. Supply chain management during COVID-19 lockdowns faced issues. Availability of raw material and transportation delays were the crucial cause of issues in supply chain management during the COVID-19 pandemic. During December 2021, Amazon had the highest number of traffic when compared with the previous year.

System model of risks and trees of alternative solutions for improving the logistics chain at a manufacturing enterprise

The subject of this article is the decision-making processes for improving the elements of the supply chain of a manufacturing enterprise under conditions of uncertainty and risks. The purpose of the research is to reduce the time and cost of in supply and distribution of products of manufacturing enterprises by considering possible risks through making rational management decisions. The article addresses the following tasks: examination of the characteristics of supply chain elements; investigation of the main problems of supply and distribution management and identification of ways to solve them; development of a systemic model of logistic risks for a manufacturing enterprise; and formation of decision trees for alternative decisions in strategic supply chain management at manufacturing enterprises. The methods applied include a systems approach, structural decomposition methods, a risk-oriented approach. The following results were obtained: features and problems of supply chain elements such as supply, production, storage, and distribution were examined and identified; main supply chain management tasks were investigated and solutions identified; problems in warehouse management were pinpointed; internal and external supply risks were identified; a systemic model of logistic risks for a manufacturing enterprise was formed, which main components are logistic problems, partial risks, their consequences, and possible management decisions to mitigate risks; decision trees were built for problems of raw material supply instability and transportation bottlenecks and delays; an alternative decision diagram was constructed for an illustrative example. Conclusions: To overcome the problem of raw material supply instability, it is recommended to develop diversification of supply sources, stock reservation, and the use of alternative transport routes. Building alternative decision trees in strategic management is an effective tool for making rational decisions by manufacturing enterprises in complex conditions of uncertainty and risks. They help to analyze alternatives and their consequences to choose a path to optimize the supply chain.

REVIEW AND ANALYSIS OF THE MAIN DIRECTIONS ON IMPROVING THE EFFICIENCY TRANSPORTATION OF MASS CARGO BY RAIL TRANSPORT

The research found that mass cargo transportation in Ukraine plays a key role in the functioning of the economy, driving the development of many industries and ensuring the country's competitiveness in the global market.Based on the analysis of freight transportation volumes over the recent period, the main trends and factors affecting them were identified. In particular, the growth in rail freight transportation is largely due to the expansion of the sea corridor through the Danube ports. This has made it possible to export Ukrainian products to Europe and other regions of the world, which has stimulated growth in demand for rail transportation. Due to the expansion of the maritime corridor and the change in the geopolitical situation, the share of export cargo transported by rail has increased significantly. These are primarily grain, oilseeds, metallurgical products and chemicals.Induced analyzes scientific research related to the issues of improving the efficiency of mass cargo transportation by rail. Such important problems as the problem of timely provision of loading resources, delays in transportation, inefficient use of empty vehicles, loss of cargo during transportation, etc. are considered. Ways to solve these problems, which are considered in the works of scientists, include infrastructure modernization, introduction of new technologies and optimization of logistics processes.The question was raised the issue of the efficiency of using container and containerized transportation technology. Their advantages, such as reduction of time and costs for transportation, environmental friendliness, are shown, and their disadvantages are considered.The mathematical model of the movement of a container train is analyzed and the feasibility of creating dry port-type structures for optimizing the transportation of mass cargo is investigated.These researches point to the need for a systematic approach to improving the efficiency of mass freight transportation by rail, taking into account various aspects, including technological, infrastructural, logistical and organizational aspects. Such an approach will allow achieving a higher level of efficiency and competitiveness of rail transport in the transportation of mass cargo.Proposed measures for improve the efficiency of mass cargo transportation by rail: optimization of routes, increasing energy efficiency and carrying capacity of railcars, modernization of infrastructure, use of the latest technologies, optimization of loading and unloading, and improvement of safety and quality of service.

The impact of Boric Acid tubes on quantitative urinary bacterial cultures in hospitalized patients

IntroductionThe accuracy of urine culture results can be affected by pre-analytical factors such as transport delays and storage conditions. The objectives of this study were to analyze urine collection practices and assess the impact of introducing boric acid tubes for urine collection on quantitative urinary bacterial cultures of hospitalized patients in medical wards.MethodsA quasi-experimental pre-post study conducted in an acute care facility. In the pre-intervention phase (2020–2021), urine samples were transported without preservatives at room temperature. In 2022 (post-intervention), we transitioned to boric acid transport tubes, evaluating its effect on significant bacterial growth (≥ 105 CFU/ml). Bivariate and multivariate analyses identified predictors of culture positivity.ResultsThroughout the duration of the study, a total of 12,660 urine cultures were analyzed. Date and time documentation was complete for 38.3% of specimens. Culture positivity was higher with longer processing times: positivity was 21.3% (220/1034) when specimens were processed within 4 h, 28.4% (955/3364) when processed in 4–24 h, and 32.9% (137/417) when processed after 24 h (p < 0.0001). For 4-24-hour processing, positivity decreased from 30.4% (704/2317) pre-intervention to 24.0% (251/1047) post-intervention (p < 0.001), with no significant changes in < 4 or ≥ 24-hour specimens. Stratified analysis by processing time revealed that the intervention was associated with reduced positivity only in cultures processed within 4–24 h (OR 0.80, 95% CI 0.67–0.94; p = 0.008).ConclusionThe introduction of boric acid transport tubes predominantly influenced cultures transported within a 4–24-hour window. This presents an opportunity to improve urine tract infection diagnostic practices in healthcare settings.

Traffic situation in Yerevan and ways to modernize with the help of current problem of traffic congestion

Introduction. This article addresses the pressing issue of road traffic congestion in the capital of Armenia, Yerevan, and proposes a solution using the Automated Traffic Management System (ATMS). The introduction underscores the significance of effective traffic management in ensuring the safety and comfort of urban residents.Materials and methods. The analysis of the current situation raises concerns about traffic density, congestion, inefficient use of road resources, and their impact on the environment and citizens’ quality of life. In turn, the exploration of ATMS as a solution includes an explanation of the system’s concept, its benefits, and successful global implementation examples. The implementation plan for ATMS encompasses stages from data collection to traffic management, along with necessary technical and infrastructural changes. The assessment of costs and benefits underscores the economic and social components of anticipated outcomes.Conclusions. The introduction of automated traffic management systems (ATMS) leads to a significant reduction in transport delays at intersections by 10–20%, which reduces gasoline consumption for movement by 30%. The number of traffic accidents at intersections is reduced by 10–15%. This leads to economic benefits, improved road safety and improved environmental conditions in cities.

Reducing Inpatient Transport Delays: The Right Patient at the Right Time

Introduction: Transportation of inpatients throughout hospitalization remains a critical aspect of patient care. Transport delays hinder the timely delivery of surgical procedures, radiology, and patient triage, consequently impacting the flow and receipt of treatment. This study reviews transport delays in a quaternary care hospital's inpatient orthopedic unit to the preoperative unit. The goal of the project was to reengineer processes for maximized efficiency and improve on-time starts for all surgical services. Methods: Manufacturing methods of an assembly-line–like model and contemporary process-improvement tools in Lean and Six Sigma were used to gauge, reengineer, and monitor processes to ameliorate patient flow. In addition to value streamlining the flow, evaluating communication triggers, eliminating redundant operations, and shifting roles and responsibilities, multiple data sources were used to assess flow for a redesign. Results: Changes in process operations led to a 40% decrease in delays. The grace period for 100 cases was decreased by 5 minutes, in addition to a savings of $110,000 in operating room costs in the first week and 3.5 full-time equivalents annually. Physician satisfaction with timely patient arrival increased in addition to a simplified workflow, which improved patient readiness on the inpatient surgical floor and increased safety. Discussion: Using data-driven approaches, overnight acuity level was removed as a barrier to the timely care of add-on cases. With a standardized process, prediction model, and simplified evidence-based communication strategies coupled with a “pull” manufacturing model, we implemented a structured, safe, and reliable method of efficient patient transport.

Analisis Resiko Operasional dalam Industri Travel Yuk Kita Tour Untuk Meningkatkan Efisiensi dan Kepuasan Pelanggan

This study aims to investigate the identification, assessment, and control of operational risks in the travel industry, with a focus on PT Yuk Kita Tour. Direct observation and interview methods are used to identify the risks faced by the company. Risk assessment is conducted by considering the likelihood of occurrence and its impact on the company's operations, followed by appropriate mitigation strategies. The analysis results show that risks such as online booking system disruptions, lack of staff training, currency exchange rate fluctuations, regulatory changes, natural disasters, disease outbreaks, transportation delays, and terrorism threats affect operational efficiency and customer satisfaction.To control these risks, PT Yuk Kita Tour implements a comprehensive mitigation strategy, including improved cybersecurity systems, staff training programs, currency hedging strategies, active regulatory monitoring, travel insurance, strict health policies, cooperation with transportation operators, and clear security information to customers. The implementation of these risk control strategies has had a positive impact on the company's performance, with year-on-year increases in revenue and customer satisfaction. This study provides insights into the importance of operational risk management in the travel industry and demonstrates that a proactive approach to risk identification, assessment, and control is possible. This study provides insight into the importance of operational risk management in the travel industry and demonstrates that a proactive approach to risk identification, assessment, and control can improve operational efficiency and customer satisfaction. The practical implication of this study is the importance of continuously monitoring existing risks, adapting control strategies, and involving stakeholders in risk management to ensure sustainable business continuity and superior customer service in a dynamic business environment.

Assessing vessel transportation delays affected by tropical cyclones using AIS data and a bayesian network: A case study of veronica in northwestern Australia

Tropical cyclones frequently disrupt maritime transportation systems, impacting the normal operation of vessels and causing transportation delays. Analyzing the occurrence and degree of vessel transportation delays under disaster conditions is one of the critical aspects of maritime transportation management. This article, based on Automatic Identification System (AIS) data, examined the real behavioral trajectories of vessels and delay characteristics during tropical cyclones. Taking the example of Tropical Cyclone Veronica, which occurred in the waters off northwestern Australia in 2019, we conducted a comprehensive analysis. This involved numerical simulations of the entire disaster process and the cleaning and matching of trajectory data for all affected vessels in the area. We delved deeply into the relationship between vessel behavior characteristics and tropical cyclones, identified factors contributing to delays, and, based on our findings, constructed a Bayesian network inference model for vessel transportation delays under disaster conditions. This model uses information such as tropical cyclone intensity, vessel basic attributes, behavior choices, and port disaster avoidance measures as its primary nodes. The research results indicate that vessel rerouting, vessel loss of control, and waiting for port entry are the three major sources of vessel delays during disasters. Key influencing factors contributing to these consequences include port closure measures, the duration of vessels being adversely affected by strong winds, vessel tendencies toward loss of control, and risk preferences. To control the extent of vessel delays more effectively, it is crucial to prioritize these sensitive factors and strengthen monitoring and management efforts. This model is driven by real data, providing an objective reflection of real-world scenarios, and its effectiveness has been validated through sensitivity analysis. The research perspective and algorithmic framework presented in this paper offer a novel paradigm and fresh perspective for the study of maritime transportation disasters. The research findings have significant implications for bolstering the resilience of maritime transportation networks, enhancing our comprehension and anticipation of delays, and ensuring the continuity, security, and efficiency of the global supply chain for goods.