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Generative AI and knowledge management in higher education: the impact of human development on student perceptions

Andrea Bencsik Szonja Jenei Szilvia Módosné Szalai

Publication Name: Journal of Knowledge Management

Publication Date: 2026-12-14

Volume: 30

Issue: 11

Page Range: 293-318

Description:

Purpose – This study aims to explore how the Human Development Index (HDI) is associated with students’ perceived academic, personal and skill-development outcomes related to the integration of generative artificial intelligence, particularly ChatGPT, into higher education. From a knowledge management perspective, the research examines adaptive use of AI tools, structuring of information and support of autonomous learning in countries with varying development. Design/methodology/approach – The study draws on 11, 910 valid responses from the 2024 Global ChatGPT student survey, covering 58 countries. Based on 33 Likert-scale items, three reflective constructs were identified. To explore the relationships between HDI, usage intensity and perceived impacts, the analysis combined descriptive statistics, K-means clustering and a partial least squares structural equation modeling (PLS-SEM) mediation model. Findings – The regression analysis showed a weak but statistically significant negative correlation between HDI and perceived impacts: students from lower-HDI countries tended to view ChatGPT’s impacts more positively. The PLS-SEM results indicated that higher national development is associated with lower perceived academic, developmental and skill-related benefits. This relationship appears both direct and indirect, as students in more developed countries report using ChatGPT less frequently and less creatively for academic purposes. Practical implications – The findings highlight the need for context-sensitive, pedagogically grounded artificial intelligence strategies, particularly in highly developed countries and in the support of students from disadvantaged backgrounds. Originality/value – This study is among the first to examine how national development levels shape perceived ChatGPT impacts in higher education. By combining HDI, cluster analysis and mediation modeling, it offers a novel perspective on digital inequality.

Open Access: Yes

DOI: 10.1108/JKM-07-2025-0995

The Economic Structure and Performance of the Catchment Area of the Hungarian Regional Centers

Judit Berkes

Publication Name: Deturope

Publication Date: 2020-01-01

Volume: 12

Issue: 3

Page Range: 58-81

Description:

This study examines the economic structure and performance of urban catchment areas. The five largest Hungarian regional centers are a traditional part of the Hungarian city network, as they are the five most populous cities after Budapest. The approach of territorial research is increasingly focused on the fact that the city as a center should not be studied without its immediate surroundings (agglomeration, region, catchment area). This study also keeps this in mind. The data were processed for the period between 1992 and 2015, on the basis of which the change can also be examined. Development trajectories show very different tendencies; Győr operates the catchment area as a strong center, while the surroundings of Pécs became fragmented due to the weakness of the center. Miskolc is characterized by a stagnant area, where the operation of another sub-center is very intensive, thus improving economic performance. Szeged is a solid center, whose catchment area is stabilized by several substations. The area of Debrecen is divided, the center is not able to energize its area.

Open Access: Yes

DOI: 10.32725/det.2020.022

Energy distribution modeling of car body deformation using LPV representations and fuzzy reasoning

Istvan A. Harmati András Rövid Peter Varlaki Lászlõ Szeidl

Publication Name: Wseas Transactions on Systems

Publication Date: 2008-12-01

Volume: 7

Issue: 11

Page Range: 1228-1237

Description:

The main aim of the paper is to introduce a novel method - based on fuzzy control and linear parameter varying (LPV) system representation transformable into HOSVD based Canonical form - for modeling deformation processes with respect to the distribution of the absorbed kinetic energy. Modeling such kind of processes requires many uncertain input parameters. Using the proposed concept we are able to handle them and keep the complexity of the models low by using higher order singular value decomposition (HOSVD) technique.

Open Access: Yes

DOI: DOI not available

Compressive Strength of Corrugated Paperboard Packages with Low and High Cutout Rates: Numerical Modelling and Experimental Validation

Péter Böröcz Renáta Pidl Damian Mrówczyński Lajos Fehér

Publication Name: Materials

Publication Date: 2023-03-01

Volume: 16

Issue: 6

Page Range: Unknown

Description:

The finite element method is a widely used numerical method to analyze structures in virtual space. This method can be used in the packaging industry to determine the mechanical properties of corrugated boxes. This study aims to create and validate a numerical model to predict the compression force of corrugated cardboard boxes by considering the influence of different cutout configurations of sidewalls. The types of investigated boxes are the following: the width and height of the boxes are 300 mm in each case and the length dimension of the boxes varied from 200 mm to 600 mm with a 100 mm increment. The cutout rates were 0%, 4%, 16%, 36%, and 64% with respect to the total surface area of sidewalls of the boxes. For the finite element analysis, a homogenized linear elastic orthotropic material model with Hill plasticity was used. The results of linear regressions show very good estimations to the numerical and experimental box compression test (BCT) values in each tested box group. Therefore, the numerical model can give a good prediction for the BCT force values from 0% cutout to 64% cutout rates. The accuracy of the numerical model decreases a little when the cutout rates are high. Based on the results, this paper presents a numerical model that can be used in the packaging design to estimate the compression strength of corrugated cardboard boxes.

Open Access: Yes

DOI: 10.3390/ma16062360

Robot environment representation based on Quadtree organization of Fuzzy Signatures

Áron Ballagi Csaba Hajdu Ahmet Mehmet Karadeniz Laszlo T. Koczy

Publication Name: Saci 2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2021-05-19

Volume: Unknown

Issue: Unknown

Page Range: 509-514

Description:

This paper presents a novel approach to mobile robot environment representation to hold information on detected obstacles. The method is inspired by fuzzy signature-based formalism and is based on classical quadtrees as a data indexing structure. Each detected feature point is evaluated by a fuzzy-ruleset defining the presumed significance of each detected object. Feature points and their fuzzy-mapping are indexed in a classical quadtree-based fashion. During the reconstruction of the environment representation, inference is done by the traversal on the constructed tree using accumulated fuzzy-ruleset. Our goal is to use this representation format for further robotic tasks such as obstacle avoidance in a distributed computational environment.

Open Access: Yes

DOI: 10.1109/SACI51354.2021.9465566

The Silent Signal: A Mirror Leadership and Intercultural Communication Beyond Strategic Boundaries

Saeed Banihashemi Katalin Szabó Mohammad Fakhrul Islam Muhammad Atif Bashir Muhammad Taimoor

Publication Name: Journal of Intercultural Communication

Publication Date: 2026-01-01

Volume: 26

Issue: 1

Page Range: 115-130

Description:

The post-pandemic work environment has intensified emotional strain, hybrid-work fatigue, and cognitive disengagement, making it increasingly difficult for leaders to sustain trust and authentic engagement in diverse, digitally disrupted teams. Existing leadership models emphasize cognition and behavior but overlook the real-time emotional, relational, and physiological processes that shape contemporary managerial dynamics. This study introduces Mirror Leadership, a novel theoretical framework grounded in Emotional Appraisal Theory (EAT) and Polyvagal Theory (PVT) to explain how leaders influence team well-being through emotional co-regulation, reflective attunement, and embodied presence. Using a conceptual research design and narrative synthesis across neuroscience, psychology, and leadership studies, the paper advances six propositions that describe how Mirror Leaders cultivate psychological safety, resilience, relational repair, and trust in hybrid and multicultural contexts. The model offers a distinct theoretical contribution by integrating cognitive appraisal mechanisms with neurophysiological processes of safety and connection, thereby reframing leadership as a symbolized, neuro-emotional, and intercultural process rather than a solely cognitive or strategic function. Findings suggest that emotionally attuned and synchronized leaders foster biologically grounded trust, intercultural cohesion, and affective stability during uncertainty. The study further outlines implications for research, including the need for empirical validation using physiological and behavioral measures, and implications for practice, such as enhancing leadership development, cross-cultural training, and emotionally intelligent management in hybrid workplaces. Mirror Leadership thus provides a foundational and globally relevant framework for understanding emotionally intelligent and culturally competent leadership in the new world of work.

Open Access: Yes

DOI: 10.36923/jicc.v26i1.1328

Analysis of a numerical method developed for estimation of the heat transfer coefficient obtained during quenching

Gustavo Sanchez Sarmiento Augusto Moita De Deus B. Smoljan Imre Felde Tamás Réti

Publication Name: Proceedings of the 17th Ifhtse Congress

Publication Date: 2008-01-01

Volume: 2

Issue: Unknown

Page Range: 816-819

Description:

A numerical method for prediction of the Heat Transfer Coefficient (HTC) obtained during quenching is described in this paper. An iterative regularization algorithm is used to solve the inverse problem under study. The unknown HTC function is approximated by polynomial functions of surface temperature. The numerical method developed is verified by using the temperature data measured with a JIS silver probe.

Open Access: Yes

DOI: DOI not available

On the Effectiveness of Congestion Control Algorithms on MPT-GRE Networks

Naseer Al-Imareen G. Lencse

Publication Name: 2024 47th International Conference on Telecommunications and Signal Processing Tsp 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 87-91

Description:

Contemporary academic research is seeing a notable surge in interest in investigating the multifaceted aspects associated with the advancement of multipath technologies, an area of prominence within ongoing research efforts. This burgeoning interest is exemplified by the prominence of protocols such as Multipath TCP (MPTCP) and Multipath UDP (MPT), which have appeared as focal points within contemporary research trends. The continual evolution of networking protocols, containing diverse iterations of the Transmission Control Protocol (TCP), including (CUBIC, Reno, Vegas, BBR, etc.) has been characterized by a sustained effort to congestion detection and control algorithms. This paper demonstrates the effectiveness of TCP congestion control algorithms within a network operating under the MPT -GRE network layer multipath technology. Various factors contributing to congestion were added to one of the two paths, including delay or packet loss. The study illustrates the contribution of congestion control algorithms to the increase in network throughput by resolving transient period issues in MPT -GRE multipath networks. The main objective is to evaluate the effectiveness and efficiency of congestion control algorithms within the MPT network architecture. Through systematic analysis and experimental testing, this study provides valuable insights into the performance of congestion detection algorithms. It gives evidence of their significant positive effect in multipath MPT -GRE networks.

Open Access: Yes

DOI: 10.1109/TSP63128.2024.10605944

The Evolution of Digitalization Transformation and Industry 4.0 in Supply Chain Management: A Systematic Literature Review †

László Buics Tran Nguyen Ngoc Quynh

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

The digital revolution is rapidly reshaping supply chains, driven by the confluence of Industry 4.0 and digitalization transformations. This research aims to investigate the evolution of the digitalization transformation era by integrating machine learning and big data management into supply chain management (SCM). A systematic literature review and mapping study were conducted, analyzing 223 articles from the Scopus database and 60 from Web of Science, selected through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) screening process and the Population, Exposure, and Outcome (PEO) framework. This study provides a narrative summary of the evolution of decision-making and consultation processes, recommendation approaches, and guidelines for enterprises to achieve sustainability in their supply chain management. It also identifies potential areas for future research in navigating the world of digitized supply chains.

Open Access: Yes

DOI: 10.3390/engproc2024079065