Performance Analysis Techniques Research Articles

Neuropsychophysiological Aspects of Soccer Performance: A Bibliometric Analysis and Narrative Review.

In recent years, there has been growing scientific interest in the neuropsychophysiological aspects of soccer performance. The purpose of this study was to conduct a bibliometric analysis to identify and review key topics within the neuropsychophysiological dimensions of soccer performance and identify any research voids that warrant further attention. We retrieved 192 documents from the Scopus database and anayzed the extracted data using VOSviewer software to conduct a bibliometric analysis. We applied both performance analysis techniques (including the number of documents per year, top 20 authors by citations, and top 15 sources by documents) and science mapping analysis (co-authorship, bibliographic coupling, co-citation, and co-occurrence). The co-occurrence analysis identified three main clusters of research themes. The first cluster focused on the relationship between physical performance and cognitive factors, the second on technical-tactical performance, and the third on health and well-being. Our findings emphasize the significant role of neuropsychophysiological factors in all aspects of soccer performance. We highlight the importance of integrating cognitive and physical training to enhance player performance and underscore the need for further research to deepen our understanding of these relationships.

A Bibliometric Analysis of Ehealth Literacy: Evaluating Approaches to Promote Health and Well-Being in the Context of SDGs

Objective: This study aims to track the current research progress in the field of eHealth literacy by conducting a bibliometric analysis, focusing on trends and developments, particularly during and after the COVID-19 pandemic. Method: A bibliometric analysis was employed to examine the publication trends, key contributors, and predominant research topics within the eHealth literacy domain. Performance analysis and science mapping techniques were used to provide a comprehensive overview of the field. Results and Discussion: The analysis revealed significant publication trends, identified leading contributors to the field, and highlighted key research topics that have emerged. The study visualizes the entire phase of the COVID-19 pandemic, offering insights into how the pandemic has influenced research directions in eHealth literacy. Research Implications: By providing a macroscopic perspective, this study fills gaps left by traditional literature reviews, presenting a more complete picture of the field. The findings also suggest future research directions as the impact of the pandemic on eHealth literacy continues to evolve. Originality/Value: This study presents the first bibliometric analysis of research on eHealth literacy during the COVID-19 pandemic, offering a rigorous review of the latest advancements in the field. By examining emerging trends, the study highlights the critical role of emerging technologies in enhancing eHealth literacy. Furthermore, it provides practical insights into promoting health and well-being through sustainable digital solutions, contributing to the achievement of the Sustainable Development Goals (SDGs), particularly those related to health and innovation.

Online grocery services evolution and trends: a bibliometric approach

PurposeOnline grocery service (OGS) has significantly grown in recent years, particularly during the Covid-19 pandemic. This surge has attracted significant scholarly attention and resulted in many scientific articles in the last five years. Adopting a bibliometric review approach, this study attempts to comprehensively and systematically analyse the academic literature on OGS.Design/methodology/approachA Scopus search using pertinent keywords followed by PRISMA screening identified 384 relevant articles. Articles were analysed using VOSviewer and Biblioshiny, which employed citation and thematic analysis.FindingsThe study identifies the significantly impactful authors, articles, and journals. While the analysis reveals the evolution across four time-frames, it also highlights the clusters representing the literature strands. Six major themes are identified in the literature, and potential future research enquiries are suggested.Originality/valueAs the first study to include over 350 articles, it comprehensively represents the current state of the OGS literature, utilising performance and thematic analysis techniques. The article contributes significantly to the academic discourse surrounding OGS by synthesising and presenting diverse themes. Further, the future research questions provide a foundation for advancing the literature and guiding future scholarly work in the OGS domain.

Enhancing Resilience via Exponential Technologies: Analysing Trends, Focus and Contributions

This article seeks to conduct a bibliometric analysis focusing on exponential technologies such as big data, internet of thing (IoT), artificial intelligence (AI), blockchain and cloud computing. It aims to outline research trends in this domain and explore their correlation with resilience. The study aims to track the evolution of research trends in this field over time and identify less explored dimensions of exponential technologies. Leveraging performance analysis and science mapping techniques, the paper highlights the significant growth and potential in these areas, considering them as pivotal agendas of the twenty-first century. By examining scientific productivity metrics such as publications, authors, institutions, countries and keywords, the article offers insights into emerging areas within exponential technologies. As the first comprehensive study of its kind, it provides a broad overview of the main trends and patterns in resilience research encompassing big data, IoT, AI, blockchain and cloud computing, consolidating them into a single cohesive narrative.

Comparative Study on Selection of Suitable Pavement Performance Analysis Technique by Using FWD Measurement

Comparative Study on Selection of Suitable Pavement Performance Analysis Technique by Using FWD Measurement

Evaluating regression techniques for service advisor performance analysis in automotive dealerships

Service advisors are a crucial contributor to the profit and loss of an automotive dealership. It is thus crucial that their performances are continuously evaluated to make decisions that ensure continued profitability. Artificial intelligence (AI) algorithms like the finite mixture of regression (FMR) have been previously explored as a tool for benchmarking the performance of dealerships. However, it is essential that the AI algorithm is trustworthy and that its predictions can be explained. This study aims to develop a performance analytics platform that is reliable and explainable. It develops and evaluates variants of FMR based on different regression techniques, focusing on both reliability and explainability. The results show that the implemented FMR variants not only provide accurate performance assessments but also offer transparent insights into the factors influencing dealership performance.

Performance measurement of Brazilian federal university hospitals: an overview of the public health care services through principal component analysis

PurposeThis paper aimed to contextualize the process of public hospital providing services, based on the measurement of the performance of Federal University Hospitals (HUFs) of Brazil, using the technique of multivariate statistics of principal component analysis.Design/methodology/approachThis research presented a descriptive and quantitative character, as well as exploratory purpose and followed the inductive logic, being empirically structured in two stages, that is, the application of principal component analysis (PCA) in four healthcare performance dimensions; subsequently, the full reapplication of principal component analysis in the most highly correlated variables, in module, with the first three main components (PC1, PC2 and PC3).FindingsFrom the principal component analysis, considering mainly component I, with twice the explanatory power of the second (PC2) and third components (PC3), it was possible to evidence the efficient or inefficient behavior of the HUFs evaluated through the production of medical residency, by specialty area. Finally, it was observed that the formation of two groups composed of seven and eight hospitals, that is, Groups II and IV shows that these groups reflect similarities with respect to the scores and importance of the variables for both hospitals’ groups.Research limitations/implicationsAmong the main limitations it was observed that there was incomplete data for some HUFs, which made it impossible to search for information to explain and better contextualize certain aspects. More specifically, a limited number of hospitals with complete information were dealt with for 60% of SIMEC/REHUF performance indicators.Practical implicationsThe use of PCA multivariate technique was of great contribution to the contextualization of the performance and productivity of homogeneous and autonomous units represented by the hospitals. It was possible to generate a large quantity of information in order to contribute with assumptions to complement the decision-making processes in these organizations.Social implicationsDevelopment of public policies with emphasis on hospitals linked to teaching centers represented by university hospitals. This also involved the projection of improvements in the reach of the efficiency of the services of assistance to the public health, from the qualified formation of professionals, both to academy, as to clinical practice.Originality/valueThe originality of this paper for the scenarios of the Brazilian public health sector and academic area involved the application of a consolidated performance analysis technique, that is, PCA, obtaining a rich work in relation to the extensive exploitation of techniques to support decision-making processes. In addition, the sequence and the way in which the content, formed by object of study and techniques, has been organized, generates a particular scenario for the measurement of performance in hospital organizations.

The Implementation of The Village SDGS Program: Factors and Importance Performance Analysis

The implementation of the Village SDGs program is expected to improve the welfare of village communities. However, the large number of SDGs indicators means that the implementation of this program is not focused and does not get optimal results. This research aims to find out what factors in the Village SDGs program are important issues for the people of the Kepulauan Meranti district and how the performance of the Village SDGs program compares with the expectations of the people of the Kepulauan Meranti District. The theory used is the Theory of Sustainable Development by Jeffrey Sachs in 2015. The method used is cross-sectional quantitative analysis with factor analysis and importance performance analysis techniques. The respondents in this research were the people of Meranti Islands Regency, Riau Province, totaling 382 participants from each sub-district. The research results show that all variables in the Village SDGs program are priority factors and important problems for the people of Meranti Islands Regency, especially the SDGs (X1) program, namely the problem of poverty alleviation. The results of the important performance analysis show that the variables in quadrant I are X1, X6, X9, X12 and the variables in quadrant II are X2, X4, X5, X16. The variables in quadrant III are X8, X10, X11, X13, X15 and the variables in quadrant IV are X3, X7, X14, X17, X18. The novelty in this research is the implementation of the village SDGs program from the local community's perspective.

AI-driven resource management strategies for cloud computing systems, services, and applications

Cloud computing is a way for businesses and individuals to It has changed and revolutionized the way we access and use resources. However, efficient resource management in cloud computing systems remains a major challenge due to the scalability, heterogeneity, and dynamic nature of these environments. To address these challenges, artificial intelligence (AI) technology has emerged as an effective solution to improve resource management efficiency. This paper provides an overview of AI-based strategies for efficient resource management in cloud computing systems, services, and applications. This paper first reviews resource management challenges in cloud computing, including scalability, heterogeneity, quality of service requirements, and cost optimization. Below is an overview of the various AI techniques used for resource management. B. Algorithms for machine learning, reinforcement learning, predictive analytics, natural language processing, and genetic algorithms. Next, this paper considers specific AI-based strategies for efficient resource management. These strategies include automated resource provisioning and scaling, intelligent workload planning and task allocation, predictive maintenance and fault detection, and energy-efficient resource management. We also present case studies and applications of AI-driven resource management in various cloud computing scenarios, including large-scale cloud providers, edge computing, serverless computing, and container environments. This paper describes evaluation metrics and performance analysis techniques to evaluate the effectiveness of AI-based resource management approaches. It highlights the importance of ethical considerations, transparency, and explainability in AI-powered resource management systems. Additionally, the integration of AI technologies into existing resource management frameworks is discussed, and future directions are identified, including B. real-time resource optimization and coordination.

Green gross domestic product: A bibliometric analysis

AbstractGreen gross domestic product (GGDP) is a measure of economic performance that takes into account environmental aspects. This paper analyses the bibliographic data of 1321 articles retrieved from the Scopus database to shed some light on the GGDP literature for the past 47 years (1976–2022). Using VOSviewer, a combination of performance analysis (publication trend, top authors, top countries, top journals) and science mapping techniques (co‐citation and co‐occurrence) were employed. The co‐citation analysis reveals three thematic clusters, namely: (1) political and social science dimensions of social and environmental reporting, (2) environmental disclosures, and (3) systematic review of social and environmental accounts. The co‐occurrence analysis indicates a trend towards climate change and corporate governance, with a notable shift in focus from European and Eurasian countries to China. More importantly, this study offers valuable insights into the growing body of literature on GGDP, while emphasising the need for greater geographical representation and collaboration to advance the field.

Gender and Advertising: A 50-Year Bibliometric Analysis

This study aims to provide a comprehensive overview of the state of research on gender and advertising. For this, a bibliometric review of 2,735 research articles was conducted using performance analysis and science mapping techniques to provide valuable insights into publication trends and their relevance to various topics. Visualization of the network and in-depth bibliometric analysis on publications, authors, countries, references, and keywords were performed using CiteSpace and VOSviewer. The findings show that the scholarly literature on gender and advertising has grown exponentially in the last 50 years, especially since 2010, with triple-digit annual publications. The most prolific author is M. Eisend and the journals with the highest number of publications are Sex Roles, the Journal of Advertising, and the International Journal of Advertising. The topic is highly valued both within its field and across other disciplines, including psychology, education, health, and social sciences (economic, and political). A total of 91 countries have contributed to the literature, with the largest contribution from the United States. Brazil is currently experiencing a citation burst. The active keyword hotspots include mental health, social media, purchase intention, engagement, and portrayals.

Comparison of Bioinspired Techniques for Tracking Maximum Power under Variable Environmental Conditions

This paper presents a comparative analysis of bioinspired algorithms employed on a PV system subject to standard conditions, under step-change of irradiance conditions, and a partial shading condition for tracking the global maximum power point (GMPP). Four performance analysis and comparison techniques are artificial bee colony, particle swarm optimization, genetic algorithm, and a new metaheuristic technique called jellyfish optimization, respectively. These existing algorithms are well-known for tracking the GMPP with high efficiency. This paper compares these algorithms based on extracting GMPP in terms of maximum power from a PV module running at a uniform (STC), nonuniform solar irradiation (under step-change of irradiance), and partial shading conditions (PSCs). For analysis and comparison, two modules are taken: 1Soltech-1STH-215P and SolarWorld Industries GmbH Sunmodule plus SW 245 poly module, which are considered to form a panel by connecting four series modules. Comparison is based on maximum power tracking, total execution time, and minimum number of iterations to achieve the GMPP with high tracking efficiency and minimum error. Minitab software finds the regression equation (objective function) for STC, step-changing irradiation, and PSC. The reliability of the data (P-V curves) was measured in terms of p value, R, R2, and VIF. The R2 value comes out to be near 1, which shows the accuracy of the data. The simulation results prove that the new evolutionary jellyfish optimization technique gives better results in terms of higher tracking efficiency with very less time to obtain GMPP in all environmental conditions, with a higher efficiency of 98 to 99.9% with less time of 0.0386 to 0.1219 sec in comparison to ABC, GA, and PSO. The RMSE value for the proposed method JFO (0.59) is much lower than that of ABC, GA, and PSO.

Bibliometric and content analysis of ChatGPT research in nursing education: The rabbit hole in nursing education

AimThis study was conducted to perform the bibliometric and content analysis of ChatGPT studies in nursing education. BackgroundChatGPT is an artificial intelligence-based chatbot developed by OpenAI. The benefits and limitations of the use of ChatGPT in nursing education are still discussed; however, it is a tool having potential to be used in nursing education. DesignBibliometric and content analysis. MethodsThe study data were scanned through Scopus and Web of Science. Bibliometric analysis was carried out with VOSViewer and Bibliometrix software. In the bibliometric analysis, science mapping and performance analysis techniques were used. Various bibliometric data, including most cited publications, journals and countries, were analyzed and visualized. The synthetic knowledge synthesis method was used in content analysis. ResultsWe analyzed 53 publications to which 151 authors contributed. The publications had been published in 29 different journals. The average number of citations of publications is 8.2. It was determined that most of the articles were published in Nurse Education Today and Nurse Educator journals and that the leading countries were the USA and Canada. It was observed that international cooperation on the issue was weak. The most frequently mentioned keywords in the publications were "ChatGPT", "artificial intelligence" and "nursing". The following three themes emerged after the content analysis: (1) Integration of ChatGPT into nursing education; (2) Potential benefits and limitations of ChatGPT; and (3) Stepping down the rabbit hole. ConclusionsWe expect that the results of the study can give nursing faculties and academics ideas about the current status of ChatGPT in nursing education and enable them to make inferences for the future.

CULTURAL TOURISM IN RURAL AREAS: MAPPING RESEARCH TRENDS THROUGH BIBLIOMETRIC AND CONTENT ANALYSIS

The main objective of this paper is to perform a detailed analysis of the scientific literature on cultural tourism in rural areas through a bibliometric study of the papers indexed in the Web of Science database. The bibliometric analysis was carried out using performance analysis and science mapping techniques. Authors’ keywords and KeyWords Plus were analyzed using RapidMiner software, and VOSviewer software was employed to create category maps and visualize the evolution of keywords. Content analysis of influential publications was used to show the evolution of knowledge and discover the most current issues. The results show the evolution of publications on cultural tourism in rural areas and identify the most influential journals, articles, authors, institutions and countries, as well as the most important research topics in the field. The paper concludes with recommendations for future bibliometric studies and offers guidelines for further research on cultural tourism in rural areas.

Public Value Creation in Local Government Context: A Bibliometric Analysis

The purpose of this study is to identify the development of the public value creation’s concept in the context of local government in the last twenty years (2002 – 2022). The 177 scientific publications in the form of articles and conference papers that were selected from the Scopus Database were further analyzed using bibliometric analysis, which combined performance analysis and science mapping techniques. The analysis results show an increase in the number of publications dominated by western countries which can be categorized into five research clusters: e-government, smart city, public governance, co-creation, and public management. The researcher recommends fifteen research topics that can be explored further in future research.

Critical Qualifications for Students Looking for an Internship in Therapeutic Recreation: Evaluated by Agency Supervisors and Academic Supervisors

This research study was conducted to ascertain what qualities agencies seek when selecting interns in relation to the qualities higher learning institutions stress. To date, academic and agency internship supervisors in Therapeutic Recreation (TR) have done no study to identify the critical attributes necessary for successful student internship placement. Because these attributes have not been identified, gaps exist between what agencies expect and what schools teach. To fill these gaps, data collected from both agency and academic supervisors were analyzed using importance by performance analysis (IPA) techniques. The findings of the study showed that both commonalities and differences were present in the actual perception of importance between agency and academic internship supervisors. This study provided recommendations to practitioners, educators, and researchers based on the study findings.

The Changing Landscape of Financial Services in the Age of Digitalization: A Bibliometric Analysis

The advent of technology has led to significant changes in many facets of the economy, including financial services industry. To secure the future of financial services, there is a need to streamline it through digitalization. Thus, the focus of the current study is to examine and uncover the emerging trends through bibliometric analysis of Scopus-indexed publications on digital financial services (DFS) and also to highlight the research agenda and thrust areas that may be covered by prospective research studies. The current research study used performance analysis, bibliographic coupling, and co-occurrence analysis techniques to conduct a bibliometric analysis of research publications in the area of DFS. The articles were assessed and visualized utilizing VoSviewer user interface. Descriptive and visual representations were used to portray the discussions on citations, authors, and source contributions toward the evolution of financial services in the digital realm. The study also shed light on the innovations that have penetrated the financial sector, helping service providers and financial institutions to innovate traditional financial products and services and produce new ones with the help of blockchain, machine learning, and advanced analytics. Also, this article offers a comprehensive roadmap for further research as well as a broad perspective on the leading nations, authors, and publications in the field.

Case study of Midea Group’s merger with Little Swan

Faced with fierce market competition and changing markets, many companies choose mergers and acquisitions to expand business scale or achieve new business directions, expand into new areas, achieve business diversification, improve competitiveness, and maintain original business conditions and field. In recent years, other companies that need to merge can refer to the analysis results and make correct merger and acquisition decisions by analyzing the performance of the merged company. This article introduces the merger and acquisition of Swan on the American Stock Exchange, and uses financial performance analysis and case analysis techniques to analyze the financial performance of the Midea Group's merger and acquisition. It is hoped that the analysis results will have certain reference value and relevance to the merged company.

Mapping the research field on product quality: a bibliometric analysis

PurposeThis research intends to undertake a rigorous bibliometric analysis of product quality research trends and patterns, map the intellectual and social structure of the field, identify the predominant themes and propose a transition plan for future work in this discipline.Design/methodology/approachThe procedure was carried out in a step-by-step manner. Following a specified search string, Scopus retrieved 1454 journal articles from the previous 39 years (1984–2022). To comprehend the field’s base, various techniques of performance analysis and science mapping were employed using RStudio and VOSviewer.FindingsIn light of the results, both the volume and influence of product quality studies have surged over the past four decades, with most works appearing in prestigious academic journals. A number of cross-country product quality collaborations took place in nations with little geographic, historical, or cultural proximity. Using co-citation analysis, five distinct subfields were identified within the literature on product quality. Finally, the use of co-word analysis helps understand the field’s underlying themes and concludes with a set of potential research avenues built on a content analysis of the articles from each of the five subfields.Originality/valueTo the authors' understanding, this study represents a pioneering effort to examine the research field on product quality using bibliometric analysis. Notwithstanding being rooted in scientometrics, this research’s outcomes are instructive for practitioners, academics and aspiring researchers in the field.

MEASUREMENT OF HIGHER EDUCATION SERVIVE QUALITY USING HEDPERF AND HIEDQUAL IMPORTANCE PERFORMANCE ANALYSIS METHODS

The image of a tertiary institution is indicated by the quality of service perceived by students because the quality of service can also reflect the academic and non-academic quality of a tertiary institution. There have been many studies focusing on measuring the quality of services in higher education (using the Serqual measurement), therefore, this study aims to measure quality services by combining other approaches, namely HEdPERF and HiEDQUAL. Bung Hatta University was used as the research object (n=370 students). The university was selected because it is a reputable private university which was founded under the name one of the nation's proclamator with significant influence. Based on the results of data analysis using the Importance Performance Analysis (IPA) technique, it can be concluded that aspects of academic facilities and support services are in the quadrant that exceeds student expectations. On the other hand, the campus infrastructure aspect should be the main priority that must receive immediate attention, followed by the reputation, academic and program aspects which are quadrant positions that must be maintained while the administrative service aspect is in low priority positionKeywords: Service Quality, Higher Education, IPA (Importance-Performance Analysis), HedPERF, HiEDQUAL