Late Delivery Research Articles

Gambaran Hasil Pemeriksaan Keton Urin Segera dan Ditunda Metode Dipstik

Laboratory testing is part of a medical process, both from the beginning to the monitoring of diagnostic development, often the urine tested experiences delays due to late delivery of samples or other factors. One element in the urine is the body of ketone (acetoacetate, 3-hydroxybutyrate, and acetone). Acetone includes the classification of ketones with easily evaporating properties due to temperature. Urine ketone is checked by dipstick methods. There's a 10-90% decrease in urine ketone if urine tests are delayed for 2 hours. Of the 30 urine samples with varying results, which are decreasing and increasing but still touch the normal value limit of urine ketone 0.5 mmol/L. Optimal handling and time of urine sampling for urine ketone testing should be observed to maintain medical protocol and ensure more accurate diagnostic results on the public health service network.

Analysis of Revenue Recognition Based on PSAK Number 23: Case Study In Trading Company PT. Solusindo Ganda Kharisma

This study aims to analyze the implementation of revenue recognition based on the Statement of Financial Accounting Standards (PSAK) No. 23 in the trading company PT. Solusindo Ganda Kharisma. In an increasingly competitive business environment, companies are required to implement an effective accounting information system to produce accurate and timely financial information. Revenue is one of the key elements in financial statements, where its recognition and measurement affect the quality of the information presented. This research uses a descriptive qualitative approach. Primary data were obtained through interviews with relevant parties in the company, while secondary data were sourced from the company’s financial statements, internal accounting policies, and other documents. The results of the study indicate that PT. Solusindo Ganda Kharisma has effectively implemented PSAK Number 23 in the recognition of revenue from the sale of goods and services. Revenue from the sale of goods is recognized when the goods have been received by the customer, while service revenue is recognized based on the percentage of work completion. However, several challenges remain, such as delayed revenue recognition due to late delivery of goods and discrepancies in estimating the percentage of work completion for service sales.

Investigating cross-docking criteria for raw materials with hybrid MCDM

The cross-docking process involves unloading raw materials from incoming vehicles and immediately loading them onto outgoing vehicles. This can greatly improve supply chain operations and expedite transportation to the factory. By minimizing warehouse storage expenses, space requirements, and inventory management, the process can be streamlined effectively. In industries where production profiles need to be responsive to market demands, the location of the cross-docking facility and transportation planning are crucial. This article aims to investigate the criteria for selecting a cross-docking location, using a case study of Arta Profile Company in Ardabil. The research population includes all industrial engineers and production planners in the company, with 10 industry experts selected for this study. The analytic network process (ANP) and grey complex proportional assessment (COPRAS-G) methods were used to compare and prioritize cross-docking locations. Additionally, the fuzzy DEMATEL method was used to determine the strength of connections between different locations. The COPRAS-G approach helps decision-makers make informed decisions by evaluating different options and their importance. The industry experts identified 28 criteria for this study. The results from the network analysis method showed that the most important criterion is the vehicle routing problem (VRP), with a value of 0.46. According to the ANP technique, strategic decision-making is the best option. The fuzzy DEMATEL method revealed that distribution centers are the most important factor, followed by reduced delivery/distribution operations, and finally, the cost of late or early delivery.

Betamethasone Exposure and Neonatal Respiratory Morbidity Among Late Preterm Births by Planned Mode of Delivery and Gestational Age.

To estimate the effect of late preterm antenatal steroids on the risk of respiratory morbidity among subgroups of patients on the basis of the planned mode of delivery and gestational age at presentation. This was a secondary analysis of the ALPS (Antenatal Late Preterm Steroid) Trial, a multicenter trial conducted within the Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network of individuals with singleton gestations and without preexisting diabetes who were at high risk for late preterm delivery (34-36 weeks of gestation). We fit binomial regression models to estimate the risk of respiratory morbidity, with and without steroid administration, by gestational age and planned mode of delivery at the time of presentation. We assumed a homogeneous effect of steroids on the log-odds scale, as was reported in the ALPS trial. The primary outcome was neonatal respiratory morbidity, as defined in the ALPS Trial. The analysis included 2,825 patients at risk for late preterm birth. The risk of respiratory morbidity varied significantly by planned mode of delivery (adjusted risk ratio [RR] 1.90, 95% CI, 1.55-2.33 for cesarean delivery vs vaginal delivery) and week of gestation at presentation (adjusted RR 0.56, 95% CI, 0.50-0.63). For those planning cesarean delivery and presenting in the 34th week of gestation, the risk of neonatal respiratory morbidity was 39.4% (95% CI, 30.8-47.9%) without steroids and 32.0% (95% CI, 24.6-39.4%) with steroids. In contrast, for patients presenting in the 36th week and planning vaginal delivery, the risk of neonatal respiratory morbidity was 6.9% (95% CI, 5.2-8.6%) without steroids and 5.6% (95% CI, 4.2-7.0%) with steroids. The absolute risk difference of neonatal respiratory morbidity between those exposed and those unexposed to late preterm antenatal steroids varies considerably by gestational age at presentation and planned mode of delivery. Because only communicating the relative risk reduction of antenatal steroids for respiratory morbidity may lead to an inaccurate perception of benefit, more patient-specific estimates of risk expected with and without treatment may inform shared decision making.

The Adoption of Blockchain Technology on Company’s Internal Control System in Sales and Purchasing Cycle

ABSTRACT This paper explores the use of blockchain technology to enhance internal control systems for fraud prevention within the sales and purchasing cycle. Despite existing internal controls, significant weaknesses persist in these systems, leading to issues such as poor performance, missing orders, underpricing, rebates, false charges, falsification of order information, late delivery, and order/performance shifting. Using the design science research approach (Hevner, March, Park, and Ram 2004), we propose a conceptual framework that allocates the verification, storage, and management of events to each authorized blockchain node, preventing tampering with verified data. By integrating blockchain’s secure, traceable, and decentralized features with smart contracts, oracles, and the Internet of Things (IoT), our framework aims to automate workflows, track goods in real-time, and measure operational performance accurately. This approach enhances internal control systems, reduces audit workloads, and mitigates the risk of business fraud and misconduct. JEL Classifications: M42; M49.

PAPERLESS ASSIGNMENTS AND CHALLENGES INVOLVED: VOICE OF DISTANCE LEARNERS

The study was planned to explore the challenges faced by distance learners during paperless assignment process. This initiative was introduced a couple of years ago at a distance learning university in Pakistan. Target population comprised on distance learners of M. Phil Education and MBA (col) sessions 2017 to 2019 programs running online through Learning Management System (LMS). Total Population Sampling (TPS) technique was followed and all distance learners of both programs were engaged. It was mixed-method research comprising both structured and open-ended information. The instruments employed were two questionnaires: one on Likert Scale and the other was open-ended. The reliability coefficient was 0.71, and the open-ended questionnaire was validated through six subject experts. The structured questionnaire was sent to all 563 students and in response 132 students filled out the online questionnaire. Quantitative data was analyzed through descriptive statistics while qualitative data was analyzed through NVivo software. The main problems highlighted were study material relevance and late delivery, understanding and processing of paperless assignments, access and skills of ICT, financial constraints, evaluation of paperless assignments, and instructors’ feedback. Students suggested that textbooks should be revised and delivered in time, connectivity issues should be resolved, free internet packages should be introduced, LMS training should be conducted, in time feedback in descriptive form by instructors must be provided to the distance learners.

Association of antenatal steroid administration with neonatal morbidities among late preterm multiple gestation infants.

There is limited evidence on the efficacy of antenatal steroids (ANS) among women with multiple gestations at risk of late preterm delivery. This retrospective study included multiple gestation, late preterm infants (340/7-366/7 weeks' gestational age), born between January 2013 and December 2022. The primary outcome was composite respiratory outcome, defined as the need for respiratory support by 72 hours of age. Logistic and linear regressions were performed to compare the primary and secondary outcomes with and without exposure to any ANS, adjusted for gestational age, sex of infant, histologic chorioamnionitis, and intrauterine growth restriction. The composite respiratory outcome was significantly lower in any ANS group compared to no ANS group (28.6% vs. 33.7%) [adjusted odds ratio 0.50, 95% CI, 0.33-0.75, p < 0.001]. In late preterm multiple gestation infants, any ANS exposure was associated with lower risk of composite respiratory outcome.

A Modeling Approach for Cargo Transportation Considering Energy Saving

This study presents a cargo transportation system management model that enables users to carry out the cargo process efficiently and economically. Cargo transportation is an important part of the transportation systems network. The advantages of cargo transportation are to ensure the safe delivery of products, save time and reduce costs. This study addresses the solution to the problems of high carbon dioxide emissions, and late and expensive deliveries caused by large distribution networks, by taking into account the density and logistics strategies of the cargo companies. The proposed cargo management system focuses on delivering cargo to destinations along the route that users are currently traveling on. This system is built around three main components: optimized route planning by an A* algorithm, a system model controllable through mobile and web interfaces, and nodes designated as drop-off and pick-up points for cargo. The A* algorithm runs with a reward matrix that also takes direction into account to calculate the optimal route. Users carry out the cargo management and tracking processes on mobile and web interfaces. Automatic nodes, which are the model prototype of the study, represent the cargo vending machines where users deliver/receive their cargo. Through this work, users can view and select cargo to carry while traveling between destinations and earn profits by acting as cargo carriers/drivers.

Examining the development of human rights strategies for large-scale sport events: the case of the United Bid for the FIFA Men’s World Cup 2026

ABSTRACT Research question Criticism of human rights issues associated with large-scale sport events has led event rights holders to incorporate human rights into bidding and hosting requirements. Bids for FIFA World Cups (men’s and women’s) now require the inclusion of a human rights strategy. Given that these requirements are relatively new, there is limited understanding of how these strategies are developed. This study drew on strategy formulation and contingency theory to examine human rights strategy development of the United Bid – a joint bid between Canada, Mexico, and the United States for the 2026 FIFA Men’s World Cup. Research methods A qualitative instrumental case study was employed using archival data and 12 semi-structured interviews with United Bid members and key stakeholders. Data were analyzed using qualitative content analysis, resulting in three themes. Results and findings Findings highlight the critical roles of stakeholder engagement and individuals with event experience in developing human rights strategies. The novelty of FIFA’s human rights requirements and late delivery of the bid guidelines presented significant challenges for the bid committee. Implications This research advances contingency theory by suggesting the approach to the development of human rights strategies is dependent on prospective hosts’ overall bid strategy. In this case, the bid focused on human rights at the country level and deferred assessment of human rights at the host city level until after the bid was won. This insight can guide prospective host nations in accounting for and integrating human rights into their bids.

Evaluation of Stuffing Out in the Warehouse PT. Lyon Oceanic Trans Surabaya

This study aims to evaluate the obstacles causing delays in the stuffing out process at the warehouse of PT. Lyon Oceanic Trans Surabaya. The research method used is a qualitative approach by collecting data through observations and in-depth interviews with warehouse workers and managers. The results show that the delay in stuffing out is caused by several main factors, namely the late delivery of goods from customers to the warehouse and the lack of support tools such as forklifts, thus relying only on human labor. The conclusion of this study indicates the need for increased efficiency in the delivery of goods as well as the addition of facilities and equipment in the warehouse to expedite the stuffing out process.

Optimalisasi Pemilihan Supplier Komponen Fabric pada Produk Man Shirt X Menggunakan Metode Analytical Hierarchy Process

PT. ABC is a company engaged in the production of ready-to-wear clothing. The main raw materials use fabric from various suppliers. The problem is the poor quality of the fabric raw materials and late delivery from suppliers, which has an impact on production optimization. Supplier selection is a strategic activity, especially if the supplier will supply critical items and be used in the long term. Good raw materials will produce good products. Choosing the right supplier can provide benefits for the company so that the production process runs smoothly. This study aims to determine the best supplier according to the specified criteria using the Analytical Hierarchy Process (AHP) supplier selection method in the selection of fabric component suppliers at PT. ABC. Supplier selection uses the AHP method with subjective assessment input from the company. The expectation of the final result can determine the ranking of alternatives so that it produces the best supplier based on criteria that are in accordance with the company. Based on the results of processing using the AHP method, the order of criteria obtained is quality (0.6554), delivery (0.1867), and price (0.1577). The alternative selection of raw material suppliers with the highest priority is supplier X with the best score of 1.358. This shows the most optimal supplier value in fulfilling the needs of fabric raw materials according to the criteria required by the company.

Optimalisasi Pemilihan Supplier Komponen Fabric pada Produk Man Shirt X Menggunakan Metode Analytical Hierarchy Process

ABC is a company engaged in the production of ready-to-wear clothing. The main raw materials use fabric from various suppliers. The problem is the poor quality of the fabric raw materials and late delivery from suppliers, which has an impact on production optimization. Supplier selection is a strategic activity, especially if the supplier will supply critical items and be used in the long term. Good raw materials will produce good products. Choosing the right supplier can provide benefits for the company so that the production process runs smoothly. This study aims to determine the best supplier according to the specified criteria using the Analytical Hierarchy Process (AHP) supplier selection method in the selection of fabric component suppliers at PT. ABC. Supplier selection uses the AHP method with subjective assessment input from the company. The expectation of the final result can determine the ranking of alternatives so that it produces the best supplier based on criteria that are in accordance with the company. Based on the results of processing using the AHP method, the order of criteria obtained is quality (0.6554), delivery (0.1867), and price (0.1577). The alternative selection of raw material suppliers with the highest priority is supplier X with the best score of 1.358. This shows the most optimal supplier value in fulfilling the needs of fabric raw materials according to the criteria required by the company.

Kontribusi Kualitas Pelayanan dan Persepsi Harga terhadap Loyalitas Pelanggan di Perusahaan Logistik Nasional

The main problems of the research are the frequently late deliveries that make customers’ inconvenience and the employees often postpone to make Goods Import Notifications and to respond to emails which make customers’ disappointment and finally choose other companies. The research objective is to determine the contribution of service quality, price perception and their implications for loyalty through customer’s satisfaction in Mahkota Logistik Indoraya. The research used Quantitative method with Path analysis techniques of SmartPLS3.3. The total research sample was 100 importers. The result shows that there is a positive and significant direct and indirect effect of the service quality and perceived price on the customer’s satisfaction. The key finding is that there is still a lack of communication between employees and customers related to imported goods delivery. Price perception, such as competitive tariff for imported goods services, good communication, good experience, thoroughness in work, and smooth and fast delivery of goods, should be fulfilled to increase customers’ loyalty to the Company.

Efficiency Strategy for Procurement of Raw Materials for Side Beam for Bogie with Material Requirement Planning at PT XYZ

Companies in Indonesia must find the right solution in order to survive and compete in the era of globalization. Price competition is an important strategy in the competition between similar companies. Based on this, there is a need for a good understanding in the company regarding strategic financing planning in order to achieve predetermined goals efficiently. This efficiency can be characterized by minimal cost expenditure in order to obtain maximum profit. One way to get maximum profit is by implementing good inventory management PT XYZ is a train manufacturing company in Southeast Asia. The company produces various types of trains. There is a production planning for the Train XYZ project with a total production of 526 units of train components for the Side Beam for Bogie. Procurement of these raw materials, PT XYZ uses Lot for Lot (LFL) at a cost of Rp1,411,402. The use of the LFL system still has shortcomings, namely problems due to late delivery and inefficient procurement in terms of financing. The results of production planning research with several MRP methods that have been compared, it is concluded that POQ lot sizing is the most efficient procurement of raw materials other than LFL. In detail, the total cost with the POQ method amounted to Rp1,243,140 and decreased by 11.9%. The cost consists of procurement costs of Rp781,162 and storage costs of Rp461,978.

Streamlining Construction Operations: A Holistic Approach with A3 Methodology and Lean Principles

With the growing trend of urbanisation and the growing number of people migrating to cities, the demand for the development and construction of new buildings and infrastructure has risen, meaning that the construction industry must adapt to these trends. Growing demands with shorter deadlines for an industry already known for its high costs and late delivery means that productivity must be increased without increasing costs. The solution for this might lie in the application of the Lean philosophy to the construction industry. This paper analyses the application of the Lean philosophy in order to increase the productivity of construction work for an airport project. This paper highlights the potential for enhancing productivity in construction workplaces by concurrently fostering continuous improvement and sustainability through the implementation of the A3 methodology and Lean principles, resulting in waste reduction and increased value.

Pregnancy and perinatal outcomes of women with SARS-CoV-2 infection during pregnancy.

This study aimed to compare the pregnancy and perinatal outcomes of women with and without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy. Women who delivered in an obstetric unit from March 2022 to October 2022 were recruited. The history of vaccination and SARS-CoV-2 infection during pregnancy was recorded. The pregnancy and perinatal outcomes of women with and without SARS-CoV-2 infection were compared. A total of 1015 women were recruited - 41.5% had SARS-CoV-2 infection during pregnancy and 25.2% were unvaccinated. The incidences of preeclampsia, gestational diabetes mellitus and caesarean section were similar between the two groups. There were more preterm deliveries (9.0% vs 5.1%, P = 0.01) and more late preterm deliveries of between 33 and 36 + 6 weeks (6.2% vs. 3.7%, P = 0.03) in the SARS-CoV-2 infection group. There were no statistically significant differences between the two groups in perinatal outcomes, including birthweight, incidence of small for gestational age, low Apgar scores, and neonatal intensive care or special care baby unit admissions. There were no differences in pregnancy and perinatal outcomes between women infected in the first/second trimester and those infected in the third trimester, except for lower mean birthweight (3180 g vs. 3292 g, P = 0.04). There were no major differences in pregnancy outcome between vaccinated and unvaccinated women. The pregnancy and perinatal outcomes of women who were infected with SARS-CoV-2 during gestation appear favourable.

Improved scheduling model for a multistage biopharmaceutical process in a multiproduct facility

This study critically evaluates deterministic and stochastic/evolutionary strategies for long-term scheduling of multiproduct facilities in batch and continuous biopharmaceutical manufacturing, as reported in existing literature using discrete-time and continuous-time models. It identifies key limitations in literature model/algorithm, including (i) real-time storage violation, (ii) real-time violation of shelf-life due to its calculation over a single event, (iii) minimum campaign length calculated over single events leading to suboptimal use of resources, and (iv) early product deliveries. To overcome these limitations, a deterministic mathematical model is proposed extending the existing unit-specific event-based model(s) with additional features including (i) modified material balances, (ii) new minimum campaign length constraints captured over multiple events, (iii) new shelf-life constraints captured over multiple events, (iv) new setup constraints based on product sequencing, (v) updated tightening constraints, (vi) updated sales and penalty constraints for late deliveries, (vii) updated bounds, and (viii) updated objective function. These improved features lead to better modeling in terms of handling intermediate and final product storage without real-time violations of storage and shelf-life, handling of initial setup in production tasks, and timely delivery of final products. The proposed improved model yields up to 36 % increase in profit when applied on four literature examples.

Risk factors and the possibility of predicting late premature birth

In the structure of preterm labor, more than half of the cases occur in late preterm labor. Many aspects of this problem remain unexplored. The article analyzes the literature sources from 2018 to 2023 (domestic and foreign scientific studies, meta-analyses, and systematic reviews) devoted to late premature birth. Risk factors, prognosis, and management strategies for preterm birth in the period from 34 to 36 weeks of pregnancy are considered. Understanding risk factors and predictive capabilities are important to prevent late pregnancy and improve pregnancy outcomes. For ease of use, risk factors and prognostic criteria are summarized in tables with references and OR. Based on the analyzed data, an approximate portrait of a patient with late premature birth was compiled and the value of biochemical markers (PAMG-1 and fibronectin), as well as instrumental methods - cervicometry and elastography ultrasound examination of the cervix, as the most informative predictor tests of the onset of late preterm birth was confirmed. It seems optimal to assess risks using several methods for predicting the onset of premature birth. The information provided in this article allows for a correct assessment of the risks of premature birth, including late delivery, and to determine management tactics based on the use of informative and "fast" tests for threatening deliveries, which will improve their outcomes.

Supply chain fraud prediction with machine learning and artificial intelligence

As businesses undergo digital transformation, supply chain fraud poses an increasing threat, necessitating more sophisticated detection and prevention methods. This paper explores the application of machine learning (ML) and artificial intelligence (AI) in detecting and preventing supply chain fraud. The research design involves analyzing a dataset of supply chain operations and employing various ML algorithms to detect consumer-based fraud within the supply chain, which occurs when consumers partake in deceptive practices during the order process of e-commerce transactions. We analyzed 180,000 transactions from an international company recorded between 2015 and 2018. This study emphasises the necessity of human oversight in interpreting the results generated by these technologies. The implications of supply chain fraud on financial stability, legal standing, and reputation are discussed, along with the potential for ML technology to identify irregularities indicative of fraud. Descriptive findings highlight the prevalence of fraudulent transactions in specific payment types. The AI sequential and the CatBoost classifiers were the top-performing algorithms across all performance metrics. The top features to detect unusual orders are delivery status, payment type, and late delivery risks. The discussion emphasises the promising predictive capabilities of the ML and AI models and their implications for detecting supply chain fraud.

Competitive Analysis of Algorithms for an Online Distribution Problem

We study an online distribution problem in which a producer has to send a load from an origin to a destination. At each time period before the deadline, they ask for transportation price quotes and have to decide to either accept or not accept the minimum offered price. If this price is not accepted, they have to pay a penalty cost, which may be the cost to ask for new quotes, the penalty cost for a late delivery, or the inventory cost to store the load for a certain duration. The aim is to minimize the sum of the transportation and the penalty costs. This problem has interesting real-world applications, given that transportation quotes can be obtained from professional websites nowadays. We show that the classical online algorithm used to solve the well-known Secretary problem is not able to provide, on average, effective solutions to our problem, given the trade-off between the transportation and the penalty costs. Therefore, we design two classes of online algorithms. The first class is based on a given time of acceptance, while the second is based on a given threshold price. We formally prove the competitive ratio of each algorithm, i.e., the worst-case performance of the online algorithm with respect to the optimal solution of the offline problem, in which all transportation prices are known at the beginning, rather than being revealed over time. The computational results show the algorithms’ performance on average and in the worst-case scenario when the transportation prices are generated on the basis of given probability distributions.