Current Performance Indicators Research Articles

Ethical Distribution and Supply Efficiency of Petroleum Products: A Systematic Literature Review

This study examined ethical distribution and supply efficiency of petroleum products. It explored the contemporary ethical distribution practices adopted by petroleum marketers in extant literature; identified the current key performance indicators (KPIs) for supply efficiency in the petroleum industry; and explored the position of scholars on the influence of ethical distribution on supply efficiency of petroleum products, among other objectives. To that end, a systematic literature review methodology was adopted. Through a thorough search process supported by a set of stringent inclusion-exclusion criteria, 91 relevant articles were included in this review. The articles were analyzed using in-depth content analysis method augmented with descriptive statistics. Consequently, the major finding of the study revealed that the majority of extant scholarly studies reviewed supported the proposition that ethical distribution practices can have significant influences on supply efficiency of petroleum products in extant literature. It was also found that the contemporary ethical distribution practices adopted by petroleum marketers in extant literature can be grouped into 11 categories, while the current key performance indicators (KPIs) for supply efficiency in the petroleum industry can be grouped into 13 categories, among other findings. On that note, the study recommended the need for a robust regulatory and implementation framework that mandates and ensures that petroleum marketers consistently integrate ethical considerations into their distribution operations in order to improve supply efficiency of petroleum products.

Estimating local pavement performance and remaining service interval using neural networks-based models and automation tool

This study introduces an integrated approach to enhance county pavement management, emphasising operational efficiency in determining the Remaining Service Interval (RSI) for rigid and flexible pavements. It establishes a robust methodology for systematically processing raw county road data through dynamic segmentation and summarisation to create a structured pavement database. It also incorporates innovative approaches and input configurations in employing Artificial Neural Networks (ANNs) to predict current and future county pavement performance indicators, including International Roughness Index (IRI), rutting, transverse, and longitudinal cracks, even with limited data. Evaluation of the ANN models on independent county road databases exhibited high prediction accuracies (0.86 < R 2 < 0.99), varying with specific performance indicators. The study results in an automation tool for expediting road performance estimation over multiple years. This tool seamlessly integrates the ANN models, empowering county engineers to make data-driven decisions and optimise resource allocation for effective pavement management, achieving significant cost savings.

Community hospitals of the future-challenges and opportunities.

Medical training through specialization and even subspecialization has contributed significantly to clinical excellence in treating single acute conditions. However, the needs of complex patients go beyond single diseases, and there is a need to identify a group of generalists who are able to deliver cost-effective, holistic care to patients with multiple comorbidities and multi-faceted needs. Community hospitals (CHs) are a critical part of Singapore's shift toward a community-centric care model as the population ages. Community Hospitals of the Future ("CHoF") represent a series of emerging conversations around approaches to reimagine and redesign care delivery in a CH setting in response to changing care needs. An environmental scan in the CH landscape using semi-structured interviews was conducted with 26 senior management, management, and working-level staff from seven community hospitals in Singapore. This environmental scan aims to understand the current barriers and future opportunities for CHs; to guide how CHs would have to shift in terms of (i) care delivery and resourcing, (ii) information flow, and (iii) financing; and to conceptualize CHoF to meet the changing care needs in Singapore. The analysis of all transcripts revealed four broad sections of themes: (i) current care delivery in CHs, (ii) current challenges of CHs, (iii) future opportunities, and (iv) challenges in reimagining CHs. An emerging theme regarding the current key performance indicators used also surfaced. Resource limitations and financing structure of CH surfaced as limitations to expanding its capability. However, room for expansion of CH roles tapping on the current expertise were acknowledged and shared. With the current issues of (i) rapidly aging population, (ii) specialist-centric healthcare system, and (iii) fragmentation of care ecosystem, there is a need to further understand how CHoF can be modeled to better tackle them. Therefore, several important questions have been devised to land us in a microscopic view on how to develop CHoF in the right constructs. Demographic changes, patient segmentation, service and regulatory parameters, patient's perspective, care delivery, and financial levers (or lack of) are some of the categories that the interview questions looked into. Therefore, the data gathered would be used to guide and refine the concept of CHoF.

Predictions of european basketball match results with machine learning algorithms

The goal of this paper is to build and compare methods for the prediction of the final outcomes of basketball games. In this study, we analyzed data from four different European tournaments: Euroleague, Eurocup, Greek Basket League and Spanish Liga ACB. The data-set consists of information collected from box scores of 5214 games for the period of 2013-2018. The predictions obtained by our implemented methods and models were compared with a “vanilla” model using only the team-name information of each game. In our analysis, we have included new performance indicators constructed by using historical statistics, key performance indicators and measurements from three rating systems (Elo, PageRank, pi-rating). For these three rating systems and every tournament under consideration, we tune the rating system parameters using specific training data-sets. These new game features are improving our predictions efficiently and can be easily obtained in any basketball league. Our predictions were obtained by implementing three different statistics and machine learning algorithms: logistic regression, random forest, and extreme gradient boosting trees. Moreover, we report predictions based on the combination of these algorithms (ensemble learning). We evaluate our predictions using three predictive measures: Brier Score, accuracy and F1-score. In addition, we evaluate the performance of our algorithms with three different prediction scenarios (full-season, mid-season, and play-offs predictive evaluation). For the mid-season and the play-offs scenarios, we further explore whether incorporating additional results from previous seasons in the learning data-set enhances the predictive performance of the implemented models and algorithms. Concerning the results, there is no clear winner between the machine learning algorithms since they provide identical predictions with small differences. However, models with predictors suggested in this paper out-perform the “vanilla” model by 3-5% in terms of accuracy. Another conclusion from our results for the play-offs scenarios is that it is not necessary to embed outcomes from previous seasons in our training data-set. Using data from the current season, most of the time, leads to efficient, accurate parameter learning and well-behaved prediction models. Moreover, the Greek league is the least balanced tournament in terms of competitiveness since all our models achieve high predictive accuracy (78%, on the best-performing model). The second less balanced league is the Spanish one with accuracy reaching 72% while for the two European tournaments the prediction accuracy is considerably lower (about 69%). Finally, we present the most important features by counting the percentage of appearance in every machine learning algorithm for every one of the three analyses. From this analysis, we may conclude that the best predictors are the rating systems (pi-rating, PageRank, and ELO) and the current form performance indicators (e.g., the two most frequent ones are the game score of Hollinger and the floor impact counter).

The Competitive Balance of the Ryder Cup: The Key Factor for the Success of the Modern Era of this Competition

The objective of this article, using the example of recent editions of the Ryder Cup, is to discuss the importance of the concept of competitive balance as a factor explaining the interest shown by spectators and TV viewers in sports competitions. To this end, after having constructed indicators to calculate the ex-ante competitive balance of the last 20 editions of this competition, a comparison is made with the results (gaps) observed on the course. The conclusion, which may be of interest to sports economists, future organisers and technicians (captains), is that "the competitive balance does not explain everything". Other concepts need to be developed. Keywords: Ryder Cup, competitive balance, annual performance indicator, current performance indicator, competitive exceptionality

Federal Property Management Agency: Analysis of Current Key Tasks and Target Performance Indicators

The article deals with practical issues of assessing the performance of the Federal Property Management Agency as an organizational institution for managing federal property, which is an important part of the state&amp;apos;s resources; special attention is paid to the assessment of the execution of the federal budget in terms of revenues from the management of federal property. Based on the materials of inspections by the Accounts Chamber of the work of the Federal Property Management Agency and its Territorial Administration in Moscow for 2017-2021, the negative results of the latter’ performance are analyzed. The results of the Federal Property Management Agency performance in 2022 are assessed, the current goals and objectives of the Agency&amp;apos;s work are analyzed.

БЕЗГОТІВКОВИЙ ПЛАТІЖНИЙ ОБОРОТ В УМОВАХ РОЗВИТКУ ФІНТЕХУ В УКРАЇНІ

Fintech is one of the fastest growing industries in the modern world and in Ukraine, which includes the development of new payment solutions, applications and technologies to improve the efficiency of payment systems. There is a general tendency to replace cash with non-cash payments due to the growth of e-commerce, the development of mobile payments and other digital technologies. The introduction of e-governance, e-services and digital tools by the government for the population and business creates a need to improve cashless payment systems. Therefore, the study of features of cashless payment turnover in the context of fintech development in Ukraine has great potential. Іt is connected with real trends in the development of the payment system in the context of the rapid growth of the fintech industry and digital innovations. The article is devoted to the conditions of functioning of cashless payment turnover in Ukraine under the influence of fintech. It considers various aspects, which influence on the efficiency of the payment infrastructure, in particular, the level of development of the banking system, economic growth, stability of the political situation and others. The process of increasing the popularity of non-cash payments and their forms, which are used by both individuals and business, have been studied. The large-scale adoption of e-wallets, mobile payments, contactless cards etc. is facilitating this process. Attention was paid to the importance of constantly monitoring technological innovations in the financial sector, protecting personal data, fighting fraud and ensuring the security of transactions. Main characteristics of the development and active changes in the payment sphere of Ukraine, caused by the influence of fintech, especially in the first quarter of the 21st century, have been highlighted, in particular, the mass implementation of cashless transactions via mobile devices or the Internet, contactless payments, the spread of cashless transactions to online trade, restaurants, utility services etc., regulatory changes. An analysis of current performance indicators of the card market in Ukraine has been done.

A Study of Performance Evaluation for Textile and Garment Enterprises

Vietnam’s textile and garment enterprises make an important contribution to the country with the second largest export turnover. The existence and development of textile and garment enterprises have a significant influence on the socioeconomic development of Vietnam. Currently, Vietnam’s textile and garment industry is facing difficulties caused by the COVID-19 pandemic, along with competition from foreign direct investment (FDI) enterprises. Therefore, it is imperative for managers to assess competitiveness by measuring their past and current performance indicators. This study assesses the performance of Vietnam’s 10 textile and garment enterprises from 2017 to 2020 by combining the DEA–Malmquist productivity index (MPI) and epsilon-based measure (EBM) model. The proposed model considered three inputs (total assets, cost of goods sold, and liabilities) and two outputs (total revenue and gross profit). In addition to showing the best-performing companies from certain aspects during the period (2017–2020), the results show that the EBM method combined with the Malmquist model in the field can be successfully applied. This study is a reference for companies in the textile and garment industry to identify their position to improve their operational efficiency and overcome their weaknesses.

The resource effect in the evaluation of the industrial enterprise development project

The article deals with the formation of a system of project management of the development of an economic entity. It is shown that project management in modern conditions is, to a greater extent, the practical implementation of the methodology for managing the resources of the organization throughout the duration of the project, aimed at effectively achieving its goals.Currently, the activities of enterprises in a market economy are directly related to the development of competition. That is why company executives pay great attention not only to the current performance indicators of the company, but also to strategic development plans. Rational managers in the process of financial and economic activity, based on the available data, make plans for both medium–term and long–term prospects. These plans are based on current performance indicators: the more meaningful and thoughtful plans are made, the more likely it is for the further growth of the organization within the market

Early Student-at-Risk Detection by Current Learning Performance and Learning Behavior Indicators

Abstract The article is focused on the problem of early prediction of students’ learning failures with the purpose of their possible prevention by timely introducing supportive measures. We propose an approach to designing a predictive model for an academic course or module taught in a blended learning format. We introduce certain requirements to predictive models concerning their applicability to the educational process such as interpretability, actionability, and adaptability to a course design. We test three types of classifiers meeting these requirements and choose the one that provides best performance starting from the early stages of the semester, and therefore provides various opportunities to timely support at-risk students. Our empirical studies confirm that the proposed approach is promising for the development of an early warning system in a higher education institution. Such systems can positively influence student retention rates and enhance learning and teaching experience for a long term.

Quality management, performance measurement and indicators in higher education institutions: between burden, inspiration and innovation

ABSTRACT Performance indicators are increasingly used to measure the performance and quality of higher education. The purpose of this article is to discuss their role for reflecting on the challenges faced by high-participation higher education systems, regarding quality of student outcomes, equity of access, societal relevance and financial sustainability. Based on a review of existing international comparable metrics, policy and scholarly literature on higher education performance, the article discusses the strengths and weaknesses of current performance indicators and the perennial tension between the burden of accountability and the inspiration and innovation that may result from the developmental use of performance indicators for improvement. It concludes by summarising some observable results of performance and quality management and reflecting on some possible future trajectories.

Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets

We propose an empirically motivated financial market model in which speculators rely on trend-following, contrarian and fundamental trading rules to determine their orders. Speculators’ probabilistic rule-selection behavior – the only type of intrinsic randomness in our model – depends on past and current performance indicators. Our model replicates a number of important stylized facts of financial markets, most noteworthy their approximate random walk price behavior. For a large number of speculators, the model’s intrinsic randomness vanishes and its dynamics is driven by an analytically tractable nonlinear map. An in-depth investigation into this map provides the key to understanding how the model functions.

Factors related to first-year retention rate in a public minority serving institution with nontraditional students

The authors present a comprehensive study to identify factors that affect the retention rate of first-time freshman business students in a large four-year public university. Factors include background academic and demographic variables, current performance indicators, and course-taking patterns. Based on a logistic regression model and comparison between nonretained students and students who graduate on time, the authors determined that sex, ethnicity, socioeconomic status, grade point average, academic standing, and performance in foundational and remedial courses were significant predictors of nonretention. Underrepresented students were found to struggle more in college and be at a significantly higher risk for nonretention than were others with socioeconomic or financial reasons playing a big role along with poor academic performance.

The Reconstruction of Magnetic Particle Imaging: Current Approaches Based on the System Matrix.

Magnetic particle imaging (MPI) is a novel non-invasive molecular imaging technology that images the distribution of superparamagnetic iron oxide nanoparticles (SPIONs). It is not affected by imaging depth, with high sensitivity, high resolution, and no radiation. The MPI reconstruction with high precision and high quality is of enormous practical importance, and many studies have been conducted to improve the reconstruction accuracy and quality. MPI reconstruction based on the system matrix (SM) is an important part of MPI reconstruction. In this review, the principle of MPI, current construction methods of SM and the theory of SM-based MPI are discussed. For SM-based approaches, MPI reconstruction mainly has the following problems: the reconstruction problem is an inverse and ill-posed problem, the complex background signals seriously affect the reconstruction results, the field of view cannot cover the entire object, and the available 3D datasets are of relatively large volume. In this review, we compared and grouped different studies on the above issues, including SM-based MPI reconstruction based on the state-of-the-art Tikhonov regularization, SM-based MPI reconstruction based on the improved methods, SM-based MPI reconstruction methods to subtract the background signal, SM-based MPI reconstruction approaches to expand the spatial coverage, and matrix transformations to accelerate SM-based MPI reconstruction. In addition, the current phantoms and performance indicators used for SM-based reconstruction are listed. Finally, certain research suggestions for MPI reconstruction are proposed, expecting that this review will provide a certain reference for researchers in MPI reconstruction and will promote the future applications of MPI in clinical medicine.

The Effect of Public-Private Partnership on Service Quality – A Field Study on School Transportation in Al-Makhwah Governorate Saudi Arabia –: تأثير الشراكة بين القطاع العام والخاص على مستوى جودة الخدمات - دراسة ميدانية على النقل المدرسي بمحافظة المخواة - المملكة العربية السعودية –

This research aimed to assess the impact of raising service quality levels that are provided through public and private partnerships. The researchers will analyze the educational transportation in Al-Makhwah Governorate, Al-Baha region. An empirical investigation was performed to illustrate the impact of the partnership on the quality of educational transportation. The researchers targeted the beneficiaries of middle school students to one department of education in the governorate. The number of participating students reached (338) students. The results show there was a statistically significant difference between the quality of public-private partnership buses and the quality of private buses. As such, the quality of services was higher in public-private partnership buses than in buses owned by private companies working by themselves. In addition, a significant improvement in the satisfaction in dex for service recipients after partnering with the private sector, in addition to an improvement in security and safety measures. Therefore, public sector engagement with the private sector provides the possibility for continuous development of services while maintaining current performance indicators.

System of Remote Monitoring of Technical Objects

Currently, digitalization, being implemented in all spheres of human activity, including transport processes, requires efficiency in obtaining and processing information, as well as timeliness of decisions made on its basis. The modern system of operation of railway traction rolling stock is characterized by the lack of online information about the current technical condition and the residual life of its components for decision making.The article proposes to solv e the problem by implementing an adaptive system for remote online monitoring of technical parameters of operated objects into the field of traction rolling stock operation. The adaptive system contains software related to recommendation decision support systems. A distinctive feature of the system is the presence of elements of artificial intelligence, which self-learns by combinatorial processing of the historical database on operation of this or a similar technical object and current performance indicators corresponding to them.The proposed information processing algorithm is versatile and, in principle, can work with a variety of data sources, including existing traction rolling stock safety devices. Online monitoring of technical parameters of operated objects can be extended to both cargo-passenger rolling stock and related auxiliary machinery and devices (track machines, cranes, hump retarders, etc.). Based on the analysis of the information received, the software generates and transmits recommendations regarding current urgent actions for managing staff and maintenance personnel.In addition, the proposed technology makes it possible to predict indicators of accidents at operated objects in real time, providing an opportunity to facilitate the diagnostic process, optimize organisation of maintenance, reduce the cost of maintaining rolling stock, and increase safety of the transportation process.The adaptive system of remote online monitoring of operational safety of technical objects, considered in the article, through a risk-based approach, is a unique development that has no analogues.

Automation of Predictive Maintenance Using Internet of Things (IoT) Technology at University-Based O&amp;M Project

Predictive Maintenance can be defined as a type of advanced maintenance that detects the onset of system degradation allowing causal stressors to be eliminated or controlled prior to any significant deterioration in component physical state. Thru Internet of Things (IoT) Technology, automation, and implementation of Predictive Maintenance are possible. The purpose of this study is to propose the implementation of Predictive Maintenance using IpT Technology at University-based Operation &amp; Maintenance Project that aims to transform the current Key Performance Indicator (KPI) of PM to CM Ratio from 80:20 to 90:10. Six Sigma DMAIC Methodology and Data-Driven Predictive Maintenance Planning Framework were utilized as the methodology of this research. Research’s results show that KPI, 90:10 (PM to CM Ratio) is achievable and maintenance cost can significantly reduce from 25% to 30%. Other valuable benefits are return of investment (10X), elimination of breakdown (70 - 75%), reduction in downtime (35% - 45%) and increase of production (20% - 25%). The proposed concept can be utilized in other industries to achieve high customer satisfaction percentages, sustainable operations, fault prediction, and online monitoring using PC or mobile applications.

Post-Pandemic Development: Sluggish or Rapid Recovery?

Post-Pandemic Development: Sluggish or Rapid Recovery?

Review and evaluation of intermediate temperature monotonic cracking performance assessment testing standards and indicators for asphalt mixes

The main objective of this study was to review and evaluate the current monotonic cracking performance assessment tests and indicators. The testing requirements of various test standards were compared. Also, key publications, concepts, calculation methods, physical meaning, and advantages and disadvantages of various performance indicators were documented. In addition, a comprehensive laboratory evaluation was conducted to examine indicators sensitivity to mix compositions, variability, and statistical grouping as well as mix performance ranking. The results showed that the indirect tension test provided better cracking assessment as compared to semi-circle bending tests. In addition, the Weibull cracking resistance indicator was recommended over other performance indicators.

ON THE EFFICIENCY TECHNOLOGICAL PROCESSES OF PROCESSING CONTAINER FREIGHT FLOWS

The article discusses current issues of the development of transport and logistics infrastructure based on the introduction of modern technologies for processing cargo flow in seaports. The purpose of this article is to develop technical proposals for the implementation of container transshipment at the «TIS» transport and logistics complex. Results. In the work, calculations were carried out taking into account the current performance indicators of the «TIS» container terminal. The basis was taken daily indicators of container handling. The calculations were carried out taking into account all the involved equipment with the corresponding appropriate technical interruptions in work that occur in real time. Proceeding from this, the obtained results have a rather high reliability and made it possible to establish how much it is possible to increase the volumes of container processing after the terminal modernization. The scientific novelty should include the introduction of a set of measures to modernize technological schemes and technical equipment, including: the introduction of a structured distribution of loading and unloading operations, the reconstruction of railway transport lines to ensure direct transshipment of containers from ships. The practical significance lies in the fact that the implementation of the proposed measures allowed the «TIS» terminal to confidently take the first place among the ports of Ukraine in terms of cargo flow processing. The proposed model can be generalized to improve the efficiency of other port transport and logistics centers.