Performance Analysis Techniques Research Articles

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

Exploring the linkage between business incubation and entrepreneurship: understanding trends, themes and future research agenda

PurposeThis article aims to conduct a bibliometric study using structural and relational approaches amongst the extracted documents and investigates the connections between business incubation and entrepreneurship-related papers to describe the field comprehensively.Design/methodology/approachA total of 259 articles have been retrieved from Scopus database in order to conduct the bibliometric analysis. Performance analysis and science mapping techniques of bibliometrics have been used along with data visualisation software, i.e. VOSviewer and RStudio. The network collaboration and intellectual structures, i.e. bibliographic coupling, co-occurrence analysis, word cloud and trending topics, have been presented to identify the field’s latest trends, themes and development.FindingsThe findings highlight annual publication trends, including the most frequently cited articles, the most productive authors, countries and highly influential journals that contribute the most to the said field. The intellectual structures have been developed to identify research themes and trends by running co-occurrence analysis and bibliographic coupling. The findings of this study emphasize the value of technology transfer, mentorship programmes, entrepreneurship education and an emphasis on innovation and creativity through entrepreneurial universities and academia. These findings provide policymakers and administrative officials with crucial guidance for fortifying the pillars of entrepreneurship and education for the comprehensive development of the economy. Further, this article attempts to identify the most influential and relevant publications as well as the newest trends in the area of business incubation in combination with entrepreneurship.Research limitations/implicationsThe article contributes not only to broaden the scope of knowledge on the said research discipline but also to comprehend how the field has evolved over a period of time. This study also attracts the interest of scholars/academicians, leading to the significant production of scholarly documents in business incubation and entrepreneurship.Practical implicationsThe field of entrepreneurship and business incubation is one of the important pillars for the growth and development of the economy. This piece contributes to this arena by focusing on the areas that must be taken care of by developing the entrepreneurial ecosystem and fostering the progress of startups. The fundamentals of this research highlight the importance of mentorship programs, entrepreneurship education, technology transfer and a focus on innovation and creativity through entrepreneurial education and efforts by universities/academia, giving an important direction to the policymakers and administration for strengthening the pillar of entrepreneurship and education for the holistic development of the economy.Originality/valueBusiness incubation is an emerging field of academic research connected to startups, venture formation and entrepreneurship ecosystems, making it a potential scholarly discipline. This study presents a thorough bibliometric analysis over the last three decades, offering comprehensive details on the most significant developments in the field of business incubation. Moreover, the various analytical methods applied to this study make it more attractive.

Using a comprehensive DEMATEL-ISM-MICMAC and importance–performance analysis to study sustainable service quality features

PurposeTo gain and differentiate competitive advantage, the sustainable service quality is a determining factor that railway companies can use. The purpose of this study is to identify both the importance and performance of rail transportation service quality factors in a case study as well as determine the most influential quality features.Design/methodology/approachA comprehensive approach namely importance–performance analysis (IPA) technique and decision-making trail and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) and Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) techniques was utilized.FindingsThe relative position of each attribute is specified on the IPA matrix proposing four strategies of concentrate here, keep up the good work, low priority and possible overkill. This study reveals that attributes of “the company cares about having a good society” are the most influential factor, and “having good business relations with shareholders” is the most permeable factor. Actually, consumers pay attention to how companies act toward society and maintain communication with shareholders. Through ISM technique and by summing the row and column of the consistency matrix, the attributes were partitioned into four levels. Also, MICMAC analysis identified the four clusters of linkage, independent, autonomous and dependent status of the attributes in terms of the driving power and dependence power.Research limitations/implicationsDue to the nature of single case study methodology, caution should be taken into consideration regarding the generazability of the obtained results.Originality/valueThe hybrid DEMATEL-ISM technique is used to analyze service quality factors in Iran’s transportation industry, which can be utilized in other industries as well as other countries.

Quality Management Research in Tourism Literature: A Bibliometric Analysis Approach

Quality is an important indicator for the service sector. Currently, increasingly competitive conditions, technological development and changes in customer demands and needs bring importance to the concept of quality in the tourism sector, as in many other sectors. The key role of quality management in enabling sustainable competitive advantage has guided many researchers in the field of tourism science to focus on this issue. Nevertheless, there are limited bibliometric and systematic assessments, even though they are becoming increasingly popular in the tourism industry. To contribute to further research collaboration and expand knowledge in this subject area, a bibliometric study was conducted. This research examines quality management in the tourism literature, the growth trajectory and geographical distribution of studies, the distribution of publications according to WOS indexes, the most productive authors and countries, the authors and documents that have had the greatest impact, the intellectual structure of quality management, global academic collaboration, and the main themes of publications. This study aims to identify the key issues and gaps in the literature related to quality management in the context of tourism. For this purpose, the Web of Science (WoS) database was scanned. This paper conducts a bibliometric literature evaluation of 993 articles published between 2004 and 2023. Performance analysis and science mapping techniques were used in this study. Visualization of similarities (VOS) viewer software was used to create bibliometric maps. It is concluded that the concepts of service quality and quality of life (QoL) have become prominent in tourism. It is also determined that words related to sustainability and the environment have been used in recent years. According to the results of the study, 2021, 2022 and 2020 are the most productive years. China, the USA, and Spain are the countries that have contributed the most to the development of the literature. The United Kingdom has worked in cooperation with twenty-nine countries, China’s link strength is greater, as it has cooperated with twenty-seven countries. Conversely, the university that has made the greatest collaborative contributions to science is Hong Kong Polytechnic University. Thus, it is anticipated that this research will further scientific contributions to the examination of quality management in the literature related to tourism.

Intellectual and cognitive structures of the agricultural competitiveness research under climate change and structural transformation

Research background: Although agricultural competitiveness is not a new topic, it is worth noting that it has recently come back to the attention of researchers due to various factors such as climate change, food security, price uncertainty, or structural transformation. Consequently, a growing number of articles have emerged on this subject, leading to shifts in overarching research trends and the structure of research within this domain. Purpose of the article: This study aims to facilitate a comprehensive understanding of the research constituents within the field of agricultural competitiveness. Additionally, it seeks to unveil the intellectual and cognitive frameworks spanning the years 1990 to 2022. This exploration will enable the identification of thematic clusters that both shape and guide the field, shedding light on current research trends. Methods: This research employs bibliometric analysis, specifically employing performance analysis and science mapping techniques like bibliographic coupling and co-word analyses. These tools are harnessed to scrutinize the constituents of research and the underlying intellectual and cognitive structures inherent to the agricultural competitiveness field. A dataset of 622 articles from the Web of Science database was subjected to analysis using the VOSviewer software. Findings & value added: The findings prominently illustrate a notable surge in research activity within this domain, with a substantial proportion of articles originating from the United States. The study further identifies six distinct research topics within agricultural competitiveness: (1) energy efficiency and bioenergy, (2) price fluctuation, uncertainty, and market behavior, (3) structural transformation of agriculture, (4) rural development, (5) policy issues, and (6) climate change. Moreover, the research offers insights into potential future research avenues. The uniqueness and value of this work stem from its pioneering approach, being the first to synthesize agricultural competitiveness research through an amalgamation of bibliometric techniques. Furthermore, the study contributes substantially to the theoretical advancement of agricultural competitiveness research.

A hybrid technique for optimal sizing and performance analysis of hybrid renewable energy sources

A hybrid technique for optimal sizing and performance analysis of hybrid renewable energy sources

Sensitivity of salt intrusion to estuary-scale changes: A systematic modelling study towards nature-based mitigation measures

Estuaries are among the most densely populated and heavily utilised regions in the world, where crucial functions – e.g., freshwater availability and water safety – strongly relate to the natural dynamics of the system. When developing nature-based solutions to safeguard these essential functions, a thorough understanding of estuarine dynamics is required. This study describes an elaborate sensitivity analysis on the salt intrusion length using an idealised estuary, which is parametrically designed using key estuary-scale parameters – e.g., river discharge and tidal flats – to cover a wide range of estuary classes. We were able to systematically investigate such a wide range of estuary classes due to the combination of (1) state-of-the-art hydrodynamic modelling software, (2) high performance computing, and (3) reduction and analysis techniques using machine learning. The results show that the extent of the estuarine salt intrusion length is largely determined by four estuarine features: (1) river discharge; (2) cross-sectional area (especially water depth); (3) tidal damping/amplification; and (4) tidal asymmetry. In general, the salt intrusion length shows clear correlations with (a combination of) estuary-scale parameters, which all put an upper limit on the salt intrusion length. These relations provide crucial insights for successful development of nature-based solutions to mitigate salt intrusion in estuarine environments.

A Review of Non-Destructive Techniques for Lithium-Ion Battery Performance Analysis

Lithium-ion batteries are considered the most suitable option for powering electric vehicles in modern transportation systems due to their high energy density, high energy efficiency, long cycle life, and low weight. Nonetheless, several safety concerns and their tendency to lose charge over time demand methods capable of determining their state of health accurately, as well as estimating a range of relevant parameters in order to ensure their safe and efficient use. In this framework, non-destructive inspection methods play a fundamental role in assessing the condition of lithium-ion batteries, allowing for their thorough examination without causing any damage. This aspect is particularly crucial when batteries are exploited in critical applications and when evaluating the potential second life usage of the cells. This review explores various non-destructive methods for evaluating lithium batteries, i.e., electrochemical impedance spectroscopy, infrared thermography, X-ray computed tomography and ultrasonic testing, considers and compares several aspects such as sensitivity, flexibility, accuracy, complexity, industrial applicability, and cost. Hence, this work aims at providing academic and industrial professionals with a tool for choosing the most appropriate methodology for a given application.

Connecting IFRS and earnings management: a bibliometric analysis

PurposeThe purpose of this study is to identify, recap and evaluate the state-of-the-art linkage between International Financial Reporting Standards (IFRS) and earnings management (EM).Design/methodology/approachA bibliometric analysis of 249 publications from the Web of Science (WoS) database was carried out, employing both the techniques of performance analysis and science mapping and the Bibliometrix R and VOSviewer tools.FindingsThe results of the performance analysis suggest that the publication and citation trends of the interplay of the IFRS and EM fields show an upward trend over time that most of the influential institutions emanate from the US and a significant percentage of articles published in this field emanate from high-quality journals. Science mapping via co-authorship analysis elucidates that more collaborative efforts among authors are needed in the future in this field. Bibliographic coupling analysis bifurcates the studies into six clusters and reveals the major themes and their evolution. Co-word analysis unfolds emerging trends that could be further explored, thus becoming possible future research avenues.Originality/valueTo the best of the authors' knowledge, no other study has attempted a bibliometric analysis of research on the relationship between IFRS and EM. This article fills this research gap and makes its contribution to the scientific community by presenting recent developments in this body of knowledge and suggesting future research avenues.

A Comprehensive Framework for Data-Driven Building End-Use Assessment Utilizing Monitored Operational Parameters

The availability of building operational data such as energy use and indoor temperature provides opportunities to enhance the traditional building energy performance calculation. Disaggregated building energy use facilitates informed decision-making to identify cost-saving measures efficiently at the individual building and building stock levels. The existing energy performance analysis techniques with measured input data in the literature are fragmented. Moreover, they frequently approach this issue with varying degrees of complexity depending on the available input data, expertise, and time. The procedure of choosing an appropriate method is often cumbersome with limited indication of the usefulness of the outcomes. This study proposes a data-driven framework for end-use load disaggregation through techniques that exploit various kinds of building consumption data. The results demonstrate the use of different techniques for varied applications. Calibrated theoretical calculation, data-driven heat loss coefficient (HLC), and energy signature curve (ESC) are among the proposed methods in the framework that facilitate individual, and urban scale energy decomposition. It is observed that different methods yield unalike outcomes, while their performance is predictable. While the HLC methods are flexible but also highly sensitive to the input parameters, the ESC needs high-frequency time series but provides stable energy decomposition. The ESC is efficient for large-scale analysis and the HLC method for detailed case-specific applications. Calibrated theoretical energy decomposition has a simple workflow and can supplement the current energy performance assessment method, although it entails sufficient input data.

Implications of Aging in Place in the Context of the Residential Environment: Bibliometric Analysis and Literature Review.

The residential environment's impact on aging in place is a multidisciplinary field that draws from architecture, urban planning, gerontology, psychology, and sociology. This multidisciplinary nature makes it challenging to comprehensively understand the field and identify the connections and interactions among disciplines. A bibliometric analysis is crucial for exploring the field's intellectual structure, identifying interdisciplinary collaborations, and tracking the knowledge flow across disciplines and will facilitate cross-disciplinary dialogue, foster collaboration, and encourage research that integrates diverse perspectives. This study reviewed the literature on aging in place in the context of a residential environment, which required adapting theories and methodologies. It analyzed a dataset of 1500 publications retrieved from the Web of Science, applied performance analysis techniques, and utilized VOSviewer to visualize the intellectual structure and evolving research themes. The results emphasize the increasing strength of academic interest and the growing diversity of fields related to the topic. The findings are discussed in terms of productivity, collaboration, and research themes from the past to the future. The results provide a roadmap for researchers, policymakers, and practitioners worldwide who focus on aging in place and acknowledge the importance of considering the physical, social, and cultural aspects of an older adult's living environment.

A BIBLIOMETRIC ANALYSIS ON GREEN HUMAN RESOURCE MANAGEMENT AND ENVIRONMENTAL PERFORMANCE

The ability to thoroughly investigate the literature pertaining to particular themes is made possible by bibliometric analysis. The goal of this study is to use bibliometric analysis to explain the literature review of research on the topics of green human resource management (GHMR) and environmental performance. GHRM stands for a human resource management strategy that emphasizes sustainability. Environmental performance is defined as how successfully firms carry out their operations while taking the environment into account. Performance analysis and scientific mapping bibliometric analysis techniques were applied in this research. The target literature is the Scopus database, which includes the concepts of GHRM and environmental performance. In the study, Open Access studies were included. According to the bibliometric analysis findings, forty-five publications and two thousand two hundred twenty-four citations were found between the years 2015-2023. It has been determined that eighteen countries are the most contributing countries in this field. The number of co-authorships of the countries was determined and it was observed that China and Pakistan co-authors mostly conducted research on these concepts. In addition, universities and databases that contributed the most to this field were determined. GHRM and environmental performance trends are explained by making inferences based on the findings. As a result of the research, the current situation was revealed and suggestions were presented for future research.

Integrative soft computing approaches for optimizing thermal energy performance in residential buildings.

As is known, early prediction of thermal load in buildings can give valuable insight to engineers and energy experts in order to optimize the building design. Although different machine learning models have been promisingly employed for this problem, newer sophisticated techniques still require proper attention. This study aims at introducing novel hybrid algorithms for estimating building thermal load. The predictive models are artificial neural networks exposed to five optimizer algorithms, namely Archimedes optimization algorithm (AOA), Beluga whale optimization (BWO), forensic-based investigation (FBI), snake optimizer (SO), and transient search algorithm (TSO), for attaining optimal trainings. These five integrations aim at predicting the annual thermal energy demand. The accuracy of the models is broadly assessed using mean absolute percentage error (MAPE), root mean square error (RMSE), and coefficient of determination (R2) indicators and a ranking system is accordingly developed. As the MAPE and R2 reported, all obtained relative errors were below 5% and correlations were above 92% which confirm the general acceptability of the results and all used models. While the models exhibited different performances in training and testing stages, referring to the overall results, the BWO emerged as the most accurate algorithm, followed by the AOA and SO simultaneously in the second position, the FBI as the third, and TSO as the fourth accurate model. Mean absolute error (MAPE) and Considering the wide variety of artificial intelligence techniques that are used nowadays, the findings of this research may shed light on the selection of proper techniques for reliable energy performance analysis in complex buildings.

A Bibliometric Analysis of Data Governance Research: Trends, Collaborations, and Future Directions

Research on data governance has been shaped by an excessive number of articles published in recent decades. The research study used bibliometric techniques to examine 757 journal articles in the Scopus database and it shows a dynamic growth of the topic in the selected years from 2012 to 2022. The methodology is based on the performance analysis technique and science mapping technique in bibliometric analysis. The results explore the contribution to the domain in terms of authors, sources, and countries, disclose the network between the countries and scholars relevant to the publications, and provide research areas that need more attention which drives data governance. Data protection, data access, artificial intelligence, data management, cloud computing, blockchain, and data transformation are among the areas where there is a lack of information, therefore academics should pay closer attention to them in the future. The authors observed that a wide range of disciplines have been used to address the topic of data governance. The study lays the foundation for academics, practitioners, and policymakers to conduct more future research and leads to advancing data governance research.

The Saga of Brand Equity: A Comprehensive Bibliometric Analysis

Purpose: The purpose of this research is to undertake a rigorous bibliometric analysis of the trends and patterns in brand equity research; to map the intellectual and social structure of brand equity; and to propose a transition plan for future work in this discipline. Methodology: This study has adopted (SPAR-4) systematic performance analysis and review technique. Following a specified search string, 1,842 journal articles from the previous 31 years (1992–2022) were pulled from the Scopus database. In order to comprehend the field’s knowledge base, various techniques of performance analysis and science mapping were employed using RStudio and VOSviewer. Findings: The results suggest that over the past three decades, both the volume and influence of brand equity studies have surged. Using co-citation analysis, we discovered four distinct subfields within the brand equity literature. Furthermore, the co-authorship network revealed that nations with little geographical, historical, and cultural proximity, such as the United States and South Korea exhibited the most active cross-country brand equity collaborations. Originality/Value: Despite the increasing amount of research being done on brand equity, the current look back is not adequate. This research is the first of its kind to provide practitioners, academics, and future scholars with valuable information about the intellectual and social structure of brand equity.

Modelling research on the effect of nanoscale admixtures on the strength of high-rise building concrete

MWCNTs and ultra-fine steel microwires double-doped RPC are researched to determine the modification law of flexural strength and post-folding compressive strength in order to investigate the impact of nanoscale admixtures on the strength of high-rise building concrete. This research also examines the elastic modulus of the prismatic specimen as well as the flexural toughness and compressive toughness of the load-displacement curve. Through theoretical calculations of composite materials, this paper also investigates how MWCNTs and ultra-fine steel microwires double-doped fillers improve the mechanical properties of RPC. Additionally, this work uses experimental techniques for material preparation, performance analysis and simulation research in conjunction with intelligent models. The method suggested in this research has a certain effect, and has a certain promotion effect on the subsequent performance improvement of concrete materials, as can be observed from the data statistics.

Modelling and Analysis of a Sigfox-Based IoT Network Using uppaalsmc

Wireless sensor nodes are usually powered by batteries that have limited energy capacity. In many applications, the nodes are installed in inaccessible locations where they are problematic to replace or recharge. Therefore, energy optimisation is crucial for increasing the node’s lifetime. This study presents a method for the analysis and prediction of the energy consumption of Sigfox-based Wireless Sensor Nodes. The method is illustrated in a use case where the nodes monitor the water level in drainage lines in cities to improve surface and wastewater management. We propose a formal model-based technique using the UPPAAL Statistical model checker tool to model and analyse the node’s lifetime. Statistical model checking provides a highly scalable technique for performance analysis of complex cyber-physical systems. The model captures the energy-related behaviour of the node, the Sigfox radio specification, and the sensor, each parameterised with values from the device’s datasheets. Furthermore, we calibrate the model using measurements obtained from real-world hardware. Finally, we evaluate a collection of strategies to optimise the battery lifetime of the node. We simulate the model with a 10,000 mAh battery, and the results indicate that we can extend the node’s lifetime from 202 days to 2.71 years using our most optimised transmission strategy.

Fast Performance Analysis for NoCs With Weighted Round-Robin Arbitration and Finite Buffers

Weighted round-robin (WRR) arbitration provides global fairness in networks-on-chip (NoCs) as opposed to the commonly used round-robin and priority-based arbitration techniques. However, the large number of weights explodes the design space and exacerbates performance (latency-throughput) tuning. Therefore, fast and accurate performance analysis techniques for NoCs are crucial for accelerating design space exploration and accurate pre-silicon evaluation. This article presents the first comprehensive performance analysis technique for NoCs with WRR arbitration and finite buffers. It can handle bursty traffic and is scalable to large NoC sizes. The proposed technique first estimates the probability that a queue is full and uses this result to compute the modified service time and queuing delay. Thorough experimental evaluations with synthetic traffic and real applications show that the proposed analytical model is always more than 10% accurate compared to cycle-accurate simulations. Moreover, the proposed performance analysis technique is five orders of magnitude faster than cycle-accurate simulations for a 16 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> 16 mesh NoC.

Methods of performance analysis in women's Australian football: a scoping review.

The first women's Australian football (AF) professional competition was established in 2017, resulting in advancement in performance analysis capabilities within the sport. Given the specific constraints of women's AF, it is currently unclear what match-play performance analysis methods and techniques are implemented. Therefore, the aim of this scoping review was to describe and critically appraise physical, technical, and tactical performance analysis methods that have been employed in women's and girls' AF match-play. A systematic search was conducted on the 27th of June 2022 through five databases. Eligibility criteria were derived from the PCC framework with the population (P) of women and girls AF players, of any level of play; concepts (C) of interest which were measures, data, and methods related to the sport's physical, technical, and tactical performance; and the context (C) of methods that analysed any match-play performance. A narrative synthesis was conducted using extracted study characteristic data such as sample size, population, time period, collection standards, evaluation metrics for results, and application of thematic categorisations of previous sports performance reviews. Critical appraisal of eligible studies' methodologies was conducted to investigate research quality and identify methodological issues. From 183 studies screened, twelve eligible studies were included, which examined match-play through physical (9/12, 75%), technical (4/12, 33%), and tactical analysis (2/12, 17%). Running demands and game actions analysis were the most researched in senior women's AF. Research into junior girls' AF match-play performance has not been investigated. No research has been conducted on non-running physical demands, contact demands, acceleration, and tactical aspects of women's AF. All studies utilised either inferential statistics or basic predictive models. Critical appraisal deemed most studies as low risk of bias (11/12, 92%), with the remaining study having satisfactory risk. Future research utilising increased longitudinal and greater contextual data is needed to combat the prominent issue of data representativeness to better characterise performance within women's and girls' AF. Additionally, research involving junior and sub-elite AF players across the talent pathways is important to conduct, as it provides greater context and insight regarding development to support the evolving elite women's AF competition. Women's AF has been constrained by its resource environment. As such, suggestions are provided for better utilisation of existing data, as well as for the creation of new data for appropriate future research. Greater data generation enables the use of detailed machine learning predictions, neural networks, and network analysis to better represent the intertwined nature of match-play performance from technical, physical, and tactical data.