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Analysis of Key Impact Factors in New Methods Implementation in Organisations: A Change Management Perspective

Wed, 18 Feb 2026 00:00:00 GMT

Background/Purpose This paper examines the key factors for successful change implementation in organisations, management qualities, and the most common barriers to change implementation. The main change we focus on is implementing new work methods in the organisation, such as Six Sigma, Lean, Lean Six Sigma, Kaizen, and similar methods. Methods The latest findings from the literature about change management, key success factors and barriers to change implementation are presented. An empirical study of 55 organisations from Slovenia is presented. An online questionnaire was used to gather data. Descriptive statistics were used to analyse the data. The research questions concerned the key factors influencing the successful implementation of organisational changes, the qualities necessary for organisational leaders, and the most common barriers to successful implementation. Results The key factors for successful change implementation are strongly connected to cultural and human-related factors, such as top management and employee involvement. Choosing the right leaders and communicating effectively about the implementation of change are key success factors. Key barriers identified include ineffective means of communication and employee habits and mindsets that do not support change. The most important quality of a manager who is leading organisational change is respect for other parties in the change management process, such as employees. Conclusion Understanding key success factors and the barriers to implementing change in organisations can improve change management practices. The findings contribute to a better understanding of change management in the implementation of new methods in organisations and deliver theoretical and practical implications.

Development of a Methodology Based on Fuzzy Logic for Solving the Problem of Evaluating a Startup Team Under Uncertainty

Wed, 18 Feb 2026 00:00:00 GMT

Aim/Purpose The purpose of the article is to develop a methodology for evaluating startup teams and to create a corresponding computer model based on multicriteria analysis and fuzzy-logic decision-making. Particular attention is paid to determining both qualitative and quantitative characteristics of the team, and obtaining a generalized integral assessment of the startup team under uncertainty. Design/methodology/approach An integrated evaluation method is proposed that combines the principles of the fuzzy set approach and expert evaluation and is implemented as a fuzzy inference system in MATLAB. The developed model used different initial characteristics of the startup team as input parameters. For this, formulas were identified, described, and utilized to calculate the values of these evaluation parameters. The set of linguistic variables and a system of rules for processing fuzzy data were defined. Literature data, expert and investor assessments, and case studies of real startup projects served as the empirical basis for the study. Findings The results demonstrate that the proposed approach enables a fairly objective and comprehensive assessment of a startup team’s quality, considering multiple assessment criteria, their interrelationships, and the combination of qualitative and quantitative input data, all within the context of significant uncertainty. The methodology ensures the objectivity and repeatability of the assessment, making it a valuable decision-support tool for various situations and participants within the startup community. Research implications/limitations The study is limited by the amount of data on real startup teams for model verification, which leaves much to be desired, as well as the need for further empirical substantiation and adjustment of the fuzzy model as a whole, including formulas for input parameters, linguistic variables, and decision rules, based on expert opinions. Possible areas for further research include adapting the method to different stages of startup development, taking into account their field of activity, size, and other specific features, and enabling more accurate model adjustment across various practical cases. Originality/value/contribution The article’s originality lies in integrating fuzzy logic with multicriteria analysis to assess the human factor in startups. A useful contribution involves creating a practice-oriented tool that enhances the accuracy and reliability of team analysis, which is essential for startups themselves, business angels, venture funds, accelerators, and other participants in the startup community.

How Academic Context Shapes Students’ Ethical Behaviour: New Evidence from a Transitional Society

Wed, 18 Feb 2026 00:00:00 GMT

Background/Purpose An ongoing problem of the ethical transgression of students poses a fundamental threat to the functioning of higher education institutions and translates to their behaviour in the future workplace. The aim of the paper is to examine the relationship between the academic context in higher education institutions in a transitional society and students’ ethical behaviour. Methods Two-source empirical research was conducted using samples of 235 students and 112 faculty and administrative staff from 12 higher education institutions in Croatia. Data on the ethical infrastructure of higher education institutions and the ethical behaviour of students and employees were collected from both groups. Descriptive statistics were used to provide insights into various aspects of the academic context and the characteristics of students’ and employees’ ethical behaviour. Multiple regression analyses were conducted to examine the relationships between the academic context and the ethical behaviour of students and employees. Results Perceptions of students and employees differed on a number of aspects of the academic context in their higher education institutions, while the formal ethical framework, individual-level ethics, and witnessing and sanctioning of unethical behaviour are found to be the factors that play a role in shaping students’ ethical behaviour. Students enrolled in natural sciences-related programmes are less susceptible to the effects of academic context than those studying programmes in other scientific fields. Conclusion The current state of academic context at higher education institutions in a typical transitional society leaves considerable room for improvement in developing ethical infrastructure and promoting a culture of academic integrity and ethical values. Translating the ‘words’ into ‘actions’ at both organisational and individual levels is a primary goal for these institutions to establish an effective ethical framework and culture, and to be perceived as ethical by their stakeholders.

Identifying Marketing Tools to Promote the Development of the Knowledge Economy: The Case of Lithuania

Wed, 18 Feb 2026 00:00:00 GMT

Background/Purpose The research aims to identify marketing tools that promote the development of the knowledge economy and to design a development model grounded in the research findings. This paper analyses the theoretical aspects of non-profit, social, and political marketing, introduces the concept of self-segmentation, and proposes a strategy to transform society’s readiness to foster the values of the knowledge economy. Methods The research was carried out in two successive stages. The first stage consisted of three separate sub-studies: a case study, quantitative descriptive research, and qualitative exploratory research. The second stage encompassed designing the model based on the findings. Results After conducting the case study, secondary impact factors of the tools were identified, influencing the choice of tools or the formation of their set. Following the study of the survey results, groups of high-priority marketing tools were distinguished. Based on the results of the expert evaluation, a set of the most commonly proposed marketing tools was compiled. As a result of the conducted research, a coherent five-stage model for promoting the development of the knowledge economy was created. Conclusion The model reflects key ideas: the choice of marketing tools is determined by the readiness and openness of the society to accept ideas; the success of dissemination is determined by inter-institutional cooperation; effective dissemination requires identification of the target consumer audience; and a set of marketing tools is designed on the basis of the results of continuous data analysis.

Overview of Research on Higher Education Teachers’ Involvement in Learning Analytics

Wed, 18 Feb 2026 00:00:00 GMT

Background and purpose This systematic literature review focuses on the use of learning analytics among higher education teachers, who play a key role in collecting, analysing, and interpreting data. Empirical studies from the period between 2011 and 2024 were analysed to understand the role of teachers in learning analytics and the antecedents and outcomes of its use. Methods A systematic literature review was conducted to reduce research bias and ensure repeatability. The relevant articles identified were analysed in two phases, first with a descriptive analysis and then with an in-depth qualitative synthesis. Results The literature review reveals two predominant trends in how higher education teachers use learning analytics. The first focuses on the use of learning analytics technologies to solve specific problems, while the second considers learning analytics in the context of broader pedagogical practices of teaching and learning. The paper also discusses antecedents and outcomes of the use of learning analytics among higher education teachers, highlights gaps in existing research, and suggests further research directions in this field. Conclusion This paper provides an overview of recent literature on the use of learning analytics among higher education teachers. The findings clarify the role of teachers in the use of learning analytics and provide insights into the antecedents and outcomes of its use that are also relevant to other stakeholders and decision-makers in higher education.

Relationships between Personal Characteristics, Job Satisfaction and Organisational Behaviour of Work Team Members and the Role of Organisational Agility Maturity

Wed, 18 Feb 2026 00:00:00 GMT

Introduction & Purpose The aim of this study is to analyse the relationships between professional personal competencies, organisational agility, job satisfaction, and organisational citizenship behaviour in work teams, as these factors can influence organisational performance and competitiveness. Methodology The cross-sectional study included a sample of 25 teams (N = 135) from various economic sectors in Slovakia. We conducted multilevel correlation and regression analyses, factor analyses, and structural modelling. Results The multilevel correlation analysis showed positive correlations with job satisfaction for all scales of the Bochum Inventory of Personality (ranging from 0.097 to 0.406), 10 of which were statistically significant. The results indicate that job competencies predict job satisfaction, and that job satisfaction correlates positively with employees’ organisational citizenship behaviour. However, the moderating effect of organisational agility on the relationship between job competencies and job satisfaction could not be demonstrated. We found a statistically significant positive relationship between the maturity level of agility and job satisfaction. We discuss possible causes, highlight the limitations, and suggest implications. Conclusion Appropriate professional skills and a people-centred approach are key to long-term success in a competitive environment and, along with organisational agility, can contribute to employee job satisfaction.

Use of Chatbots in Human Resource Management for More Efficient Knowledge Sharing – Systematic Literature Review

Wed, 19 Nov 2025 00:00:00 GMT

Purpose This study examines how chatbots, as part of generative artificial intelligence (GenAI), can assist human resource (HR) professionals in supporting more effective knowledge management (KM), especially knowledge sharing (KS). The research aims to understand the strategic roles of chatbots in Human Resource Management (HRM). It offers propositions for their effective deployment to support KS and enhance their utilisation within organisations. Methodology A systematic literature review (SLR) was carried out using the databases Web of Science (WoS) and Scopus. After applying inclusion and exclusion criteria, 16 relevant articles were selected for detailed analysis. Results The findings show that chatbots can significantly enhance KS by automating HRM processes. They enable personalised training, offer continuous support, and promote employee performance, engagement, and innovation. Furthermore, chatbots assist HR professionals in focusing on strategic tasks by lowering administrative workload. Several challenges are also identified, including ethical concerns, privacy issues, data quality problems, reduced social interaction, and risks to creativity and critical thinking. Conclusion Chatbots offer a transformative opportunity for HRM to enhance KS, organisational memory, and digital learning, thereby supporting competitive advantage in knowledge-intensive settings.

Business Analytics and Digitalization as Drivers of Startup Evaluation: The Experience of the Baltic States

Wed, 19 Nov 2025 00:00:00 GMT

Purpose This study is motivated by the importance of startups in economic growth and the need for methods to evaluate their success, considering risk and uncertainty. The objective is to analyze factors that influence startups, using factor and cluster analysis. The hypothesis that advanced business analytics in startup evaluation can enhance the quality of investment decision-making was tested. Methods The combination of quantitative and qualitative techniques was used. Statistics about 20 startups from Latvia, Lithuania, and Estonia over five years were processed to identify success drivers and to group startups by similarity. Machine learning and social media sentiment analysis were applied to assess non-financial indicators. Results The results showed that indicators such as projected profitability, social media activity, and innovativeness are significant for startup ranking. The share of traditional methods in the Baltic states was 55%, while modern tools were 45%, highlighting the role of digitalization in risk assessment. Startups with high clustering coefficients and positive mention sentiment demonstrated superior performance. Conclusions The study demonstrated that integrating business analytics and digitalization enhances startup evaluation. The model combines financial metrics with network and sentiment analysis, offering a comprehensive framework for investors. It confirms that data-driven methods improve decision-making, reducing investment risks.

Exploring the Role of Perceived Benefits and Attitudes Toward Web in Modelling Online Purchase Intentions: A Case of Slovenia

Wed, 19 Nov 2025 00:00:00 GMT

Background and Purpose E-commerce has reshaped consumer behaviour by offering unparalleled convenience, variety and accessibility, while creating new opportunities for businesses to grow revenues. Despite its prominence, there remains a need for parsimonious models that explain online purchase intention in terms of core consumer perceptions. This study aims to develop and test a structural equation model (SEM) in which consumer perceived benefits and attitudes toward the web drive intention to purchase online. Methods An online survey was administered to 190 Slovenian consumers. Questionnaire items were drawn from established scales measuring (a) perceived benefits of online shopping, (b) attitude toward the web, and (c) online purchase intention. Internal consistency was assessed via Cronbach’s alpha. SEM was then applied using IBM SPSS AMOS to evaluate both measurement and structural components of the model, testing hypotheses that perceived benefits influence both attitude and intention, and that attitude further mediates intention. Results The survey instrument demonstrated excellent reliability (Cronbach’s α = 0.92). The three-construct SEM explained 74 % of the variance in online purchase intention. Fit indices indicated very good model performance (NFI = 0.969, NNFI = 0.970, CFI = 0.979, IFI = 0.979). All hypothesized paths were significant, confirming that higher perceived benefits enhance both positive web attitudes and purchase intentions, and that web attitudes further bolster intention. Conclusion This streamlined SEM offers a robust and well-fitting explanation of consumer online purchase intentions. E-commerce platforms can leverage these insights by emphasizing the specific benefits consumers value and cultivating positive web experiences to drive sales. The model offers both practical guidance for online retailers and a foundation for future research, such as incorporating environmental consciousness, to refine our understanding of sustainable e-commerce adoption.

Navigating Success: How Decision– Making Transforms Software Performance into Business Performance in the Logistics Industry from an Emerging Country

Wed, 19 Nov 2025 00:00:00 GMT

Background/Purpose This study investigates the mediating role of decision–making performance in the link between software performance and overall business performance in the logistics sector of an emerging economy. As logistics companies increasingly rely on digital infrastructures, understanding how advanced systems contribute to strategic outcomes is critical for sustaining competitiveness. Methods A conceptual framework was developed integrating ERP systems, big data analytics, and IoT applications. In this model, software performance is positioned as the independent variable, decision–making performance as the mediator, and business performance as the dependent variable. Data were collected from medium- and large–scale logistics firms and analyzed using regression and bootstrapping methods through SPSS and the PROCESS Macro. Results The findings reveal that software performance significantly improves decision–making performance (β = 0.552, p < 0.01), which in turn has a strong positive effect on business performance (β = 0.817, p < 0.01). The mediation analysis confirms that decision–making performance mediates the effect of software performance on business outcomes. Conclusion The results highlight the strategic importance of aligning digital capabilities with organizational decision processes. By demonstrating the mediating role of decision–making, the study highlights that the effective use of advanced analytical tools is crucial for optimizing performance and achieving a sustainable competitive advantage in logistics.

Perceptions of Employer Attractiveness across Employee Cohorts in Slovakia

Wed, 19 Nov 2025 00:00:00 GMT

Background/Purpose This paper investigates employer attractiveness from the perspective of different employee cohorts in Slovakia. The study aims to identify which employer attributes are perceived as most important and to investigate how these perceptions vary across different generational and educational segments. The research addresses current labour market challenges, including shortages of both highly and moderately skilled labour, further exacerbated by demographic ageing. Methods A quantitative research design was applied, using a questionnaire survey with a final sample of 481 respondents. A two-step cluster analysis using SPSS software was employed to group respondents with similar preferences. Results The results reveal that younger cohorts prioritise opportunities for development and reputation, while older generations emphasise salary and job security. Differences in perception were also observed across education levels. The findings highlight the need for a segmented approach in employer branding strategies, tailored to demographic and regional labour market specifics. Conclusions The study contributes to the literature by contextualising employer branding within the Slovak labour market and providing practical insights for organisations seeking to attract and retain diverse talent. These findings are relevant for both academics and HR practitioners aiming to develop more effective employer value propositions.

Understanding the Impact of Burnout on Decision-Making Styles

Wed, 19 Nov 2025 00:00:00 GMT

Background and purpose This study aimed to fill a gap in the literature by identifying how employee burnout shapes decision-making styles in the post-COVID-19 business environment. The main goal was to examine the impact of three dimensions of burnout—exhaustion, cynicism, and professional efficacy—on four conflict-related decision-making styles: vigilance, buck-passing, procrastination, and hypervigilance. Design/Methodology/Approach: A total of 567 employees from various companies in Croatia participated in the online survey conducted in March 2023. Multiple regression analysis examined the impact of exhaustion, cynicism, and professional efficacy on decision-making styles under conflict. Results The results of the multiple regression analysis revealed that professional efficacy leads to a vigilant decision-making style, while simultaneously diminishing procrastination, buck-passing, and hypervigilance. Cynicism, in contrast, was a positive predictor of procrastination, buck-passing, and hypervigilant decision-making. Finally, exhaustion was found to have a positive impact on hypervigilance. Conclusion The study is significant because it contributes to the body of knowledge on the impact of burnout dimensions on professional decision-making styles in organisational settings, and it also offers practical implications of considerable importance.

Organizational and Individual Antecedents of Resistance to Change: Organizational Climate and Technology Readiness

Tue, 12 Aug 2025 00:00:00 GMT

Background and purpose There is interest in barriers to change in organizations. This research discusses factors affecting resistance to change based on employees’ technological competencies. This research aims to determine the mediating role of technology readiness in the effect of organizational climate in health institutions on resistance to change. Methodology Research data were collected from 389 employees working in the healthcare sector. SPSS Process 2.13 macro was used to analyze the model. Results According to the analysis results, organizational climate positively affected technology readiness. Additionally, organizational climate reduced resistance to change. In addition, employees’ readiness for technology reduced resistance to change. Finally, the mediating role of technology readiness (motivating and blocking factors) in the effect of organizational climate on resistance to change was significant. Further, a positive organizational climate in healthcare institutions increased employees’ readiness for new technologies and significantly reduced employees’ resistance to change. Conclusion Creating a positive organizational climate can be vital in successfully implementing change processes in the healthcare sector. At the end of the research, theoretical and practical suggestions were presented. The research contributes to the literature by addressing the antecedents of resistance to change from organizational and individual perspectives.

The Impact of Usability and Reliability on ChatGPT Satisfaction among Gen Z and Gen Y

Tue, 12 Aug 2025 00:00:00 GMT

Background/Purpose ChatGPT’s rapid diffusion has transformed large-language-model (LLM) technology from a specialist tool into a mainstream companion for study and work. However, empirical evidence on what drives user satisfaction outside medical settings remains scarce. Focusing on future business and management professionals in Croatia, this study examines how perceived ease of use and perceived reliability shape satisfaction with ChatGPT and whether those effects differ between Generation Z (18–25 years) and Generation Y (26–35 years). Methodology An online survey administered in August 2024 yielded 357 valid responses. The measurement model met rigorous reliability and validity criteria (CFI = 0.96, SRMR = 0.04). Results Structural-equation modelling showed that, in the pooled sample, ease of use (β = 0.42) and reliability (β = 0.46) jointly explained 72 % of satisfaction. Multi-group analysis revealed a generational split: both predictors were significant for Gen Z. However, only reliability remained significant for Gen Y. Gaussian graphical models corroborated these findings, indicating a densely interconnected attitude network for younger users and a reliability-centred network for older users. Conclusion The study extends technology-acceptance research to the management domain, underscores the moderating role of generation and illustrates the value of combining SEM with network analytics. Insights inform designers and educators aiming to foster informed, responsible and gratifying engagement with generative AI.

Mapping the Evolution of Social Innovation in Scientific Publications: A Topic Modelling and Text Mining Approach

Tue, 12 Aug 2025 00:00:00 GMT

Objective To trace how academic discourse on social innovation has evolved from 2000 – mid-2024 in numbers and leading topics by applying a special topic modelling and text mining methodology. Data & Sources 4,703 full-text journal articles retrieved from Science Direct. Methods Literature review and PDF text extracted with PyPDF2 and pdfplumber; cleaned and tokenised in R; topic modelling performed with Latent Dirichlet Allocation (ldatuning-optimised); temporal and correlation analyses visualised via tidyverse. Results The number of publications increased significantly from 16 (in 2000) to 573 (in 2021), stabilizing thereafter. Seven dominant topics emerged: renewable energy, environmental/resource management, smart-city governance, sustainable food systems, corporate strategy, academic-method studies, and social-governance structures. “Social” and “innovation” became the top word pair after 2006; energy-related terms surged after 2016. Surprisingly, topics typically considered ‘social’ have not dominated the social innovation discourse in scientific communities compared to the aforementioned dominant topics. Discussion Our results largely confirm existing findings from literature reviews and affirm the interdisciplinary, vague, contested, and still intensively evolving nature of social innovation. Dominant social innovation topics in scientific papers reference to social innovation topics in global political and policy documents, notably from the EU (from 2013 onwards) and the 2015 UN SDGs agenda, also emphasising collaboration between scientific, business, political and non-governmental stakeholders, and can thus serve as scientific, evidence-based advocacy for other stakeholders involved in social innovation processes. Conclusions Social innovation research is now an established, systemic, and broadly interdisciplinary field of study, focusing on sustainability, emerging technologies, and governance topics. It is tightly connected with the political and policy agendas of leading international organisations, as well as business and non-governmental ones. Implications Findings guide scholars to under-explored social-related content and niches (such as governance and, especially, equity topics) and help policymakers and other stakeholders involved in social innovation processes locate evidence-based approaches and clusters when designing their socially innovative responses, interventions, solutions, and measures.

User Evaluation of a Machine Learning-Based Student Performance Prediction Platform

Tue, 12 Aug 2025 00:00:00 GMT

Background/Purpose The integration of machine learning in education has opened new possibilities for predicting student performance and enabling early interventions. While most of the work has been focused on prediction algorithms design and evaluations, little work has been done on user-centric evaluations. Methodology This study evaluates a web-based platform designed for student performance prediction using various machine learning algorithms. Users, including students, professors, and career counselors, tested the platform and provided feedback on usability, accuracy, and recommendation likelihood. Results Results indicate that the platform is user-friendly, requires minimal technical support, and delivers reliable predictions. Conclusion Users strongly endorsed its adoption, highlighting its potential to assist educators in identifying at-risk students and improving academic outcomes.

How Workplace Friendships Impact Burnout among Social Care Leaders: A Job Demands-Resources Framework Analysis

Tue, 12 Aug 2025 00:00:00 GMT

Background and purpose The purpose of this study, guided by the Job Demands-Resources Model, is to investigate the role of workplace friendships in mitigating burnout. This research is notable for its unique focus on a relatively rare sample: social care leaders. These individuals play a crucial role in shaping and influencing social services, making their insights invaluable for understanding the challenges and opportunities within this sector. Methods Using a cross-sectional and quantitative design, data were collected from a convenience sample of Hungarian social care leaders, including sociodemographic information, the Copenhagen Psychosocial Questionnaire (COPSOQ II), and professional core discussion network (pCDN) questions. The analysis of 449 Hungarian social care leaders employs a saturated model of moderated mediation (controlling for age and gender) to examine how stress mediates the relationship between quantitative demands and burnout and how workplace friendships moderate this mediation effect. Results The results indicate that stress significantly mediates the relationship between quantitative demands and burnout, with workplace friendships acting as a buffer under moderate stress levels. Having at least one workplace friend reduces the impact of stress on burnout; however, this protective effect diminishes under higher stress intensities. Conclusions These findings underscore the importance of fostering quality and balanced workplace friendships rather than merely increasing the number of supportive relationships. Given the systemic challenges in Hungarian social care, these insights are particularly relevant for leaders seeking to improve workforce resilience and well-being.

Evaluating Attitudes Toward Microchip Implants: A Comparative Study of five Eastern European Countries

Tue, 12 Aug 2025 00:00:00 GMT

Background and purpose Technology acceptance has been researched for decades. While some technologies are widely accepted, others are perceived as a threat, such as microchip implants. In this study, a two-step structural equation modeling approach was used to evaluate a new research model on microchip implant acceptance. Methodology A structural equation modeling model was developed to identify what influences the perceived acceptance of microchip implants. To determine differences in attitudes toward microchip implants, the study was conducted in five Eastern European countries. Results The results show that the influence of the factors does not differ significantly across the countries studied. Age, trust, and perceived usefulness affected the overall intention to use microchip implants, while ease of use was significant in only one country. Differences were found in perceptions of the right to privacy and conspiracy theories. The usefulness of microchip implants in pandemic was significant in all countries. Conclusion Small differences in attitudes towards microchip implants suggest that a general model of microchip implant acceptance could be constructed based on the data collected. In addition to these findings, our study noted the lack of legislation for microchip implants in the region and a lack of knowledge about this technology.

The Effect of Work-Family Conflict on the Impact of Role Overload on Turnover Intention and Job Satisfaction

Fri, 23 May 2025 00:00:00 GMT

Purpose This study aims to investigate how role overload and work-family conflict influence turnover intention and job satisfaction among public employees, providing insights for management practices to enhance employee well-being and organizational effectiveness. Design/Methods Quantitative data were collected from 390 public employees in the Central Anatolia region of Turkey. Structural equation modeling (SEM) was employed to analyze the relationships between role overload, work-family conflict, job satisfaction, and turnover intention. Results The study reveals that role overload positively influences work-family conflict, which in turn negatively impacts job satisfaction and increases turnover intention among public sector employees. Furthermore, job satisfaction is found to negatively affect turnover intention. Conclusion The findings highlight the importance of addressing role overload and work-family conflict to mitigate turnover intention and enhance job satisfaction among public employees. From a practical perspective, this study suggests that organizations should prioritize initiatives aimed at reducing role overload and managing work-family conflict to foster a positive work environment and retain talented employees. Socially, the study underscores the significance of supporting employees in balancing work and family responsibilities to promote their overall well-being and contribute to societal welfare.

Open-Source Transformer-Based Information Retrieval System for Energy Efficient Robotics Related Literature

Fri, 23 May 2025 00:00:00 GMT

Background and Purpose This article employs the Hugging Face keyphrase-extraction-kbir-inspec machine learning model to analyze 654 abstracts on the topic of energy efficiency in systems and control, computer science and robotics. Methods This study targeted specific arXiv categories related to energy efficiency, scraping and processing abstracts with a state-of-the-art Transformer-based Hugging Face AI model to extract keyphrases, thereby enabling the creation of related keyphrase networks and the retrieval of relevant scientific preprints. Results The results demonstrate that state-of-the-art open-source machine learning models can extract valuable information from unstructured data, revealing prominent topics in the evolving field of energy-efficiency. Conclusion: This showcases the current landscape and highlights the capability of such information systems to pinpoint both well researched and less researched areas, potentially serving as an information retrieval system or early warning system for emerging technologies that promote environmental sustainability and cost efficiency.