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Publications - 6674

Consumer impulse buying in Hungary: A CB-SEM analysis of Hungarian consumer behaviour towards mobile short video applications based on a Chinese reference model

Judit Petra Koltai Vinkóczi Tamás Izabella Mária Végvári Martina Németh

Publication Name: Computers in Human Behavior Reports

Publication Date: 2024-12-01

Volume: 16

Issue: Unknown

Page Range: Unknown

Description:

Mobile Short Video Applications are becoming increasingly popular worldwide. The appropriate content can shape, improve or change consumers' purchasing decisions. This paper examines the attitudinal differences in impulse buying related to the use and acceptance of MSAs by adapting a model already validated in China to Hungarian users. The analysis was conducted using Covariance-Based Structural Equation Modelling (CB-SEM). A structured questionnaire survey of 283 respondents in Hungary shows that the Chinese model cannot fully be applied to Hungary. A major difference between the results of the two models is that in the Hungarian model, perceived expertise shows a positive relationship with flow experience. This indicates that video makers - in the case of Hungarian videos - should produce content including introductory information and the operation of the product. The results suggest that in the case of MSA use in Hungary, perceived expertise affects impulse buying indirectly, but flow experience directly. Flow experience is only influenced by perceived expertise (β = 0.31, ρ < 0.05), with an explained variance of 10%. Flow experience (β = 0.46, ρ < 0.05) with its direct effect on impulse buying behaviour accounts for 21% of the variance. Hungarian and Chinese MSA users have different preferences in terms of content, thus the results provide important information for both international short video creators and companies entering the international market.

Open Access: Yes

DOI: 10.1016/j.chbr.2024.100522

Combined Barrier–Target Coverage for Directional Sensor Network

Tamas V. Michaletzky Balázs Kósa Márk Bukovinszki Viktor R. Tihanyi

Publication Name: Sensors

Publication Date: 2024-12-01

Volume: 24

Issue: 24

Page Range: Unknown

Description:

Over the past twenty years, camera networks have become increasingly popular. In response to various demands imposed on these networks, several coverage models have been developed in the scientific literature, such as area, trap, barrier, and target coverage. In this paper, a new type of coverage task, the Maximum Target Coverage with k-Barrier Coverage (MTCBC-k) problem, is defined. Here, the goal is to cover as many moving targets as possible from time step to time step while continuously maintaining k-barrier coverage over the region of interest (ROI). This approach is different from independently solving the two tasks and then merging the results. An Integer Linear Programming (ILP) formulation for the MTCBC-k problem is presented. Additionally, two types of camera clustering methods have been developed. This approach allows for solving smaller ILPs within clusters, and combining their solutions. Furthermore, a polynomial-time greedy algorithm has been introduced as an alternative to solve the MTCBC-k problem. An example was also provided of how the aforementioned methods can be modified to handle a more realistic scenario, where only the targets detected by the cameras are known, rather than all the targets within the ROI. The simulations were run with both dense and sparse camera placements, convincingly supporting the usefulness of the clustering and greedy methods.

Open Access: Yes

DOI: 10.3390/s24248093

Nonlinear Identification of Lateral Dynamics of an Autonomous Car Vehicle †

Dániel Pup Gyorgy Istenes Ferenc Szauter József Bokor

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this paper, the nonlinear identification of the lateral dynamics of a road vehicle and the velocity dependence of the dynamics are presented. One of the most useful methods to define the mathematical model is system identification based on measured data. A test vehicle for autonomous driving was constrained to move in a straight line while the vehicle’s steering servo was artificially excited. The input of the system is therefore the sum of the artificial excitation and the control signal of the autonomous function, and the output is the lateral acceleration of the vehicle. The measurements are used to identify Wiener and Hammerstein models of the lateral dynamics at different speeds using nonlinear methods. The aim is to investigate the velocity dependence of the dynamics.

Open Access: Yes

DOI: 10.3390/engproc2024079053

Learning Nonlinear Models of Dynamic Systems

Zoltan Szabo József Bokor

Publication Name: Sisy 2024 IEEE 22nd International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 11-15

Description:

Modeling dynamic systems is an important part in analysing and control of various systems arising either in health sciences or in the engineering word. Recent approaches to learn models from data are the so-called kernel-based methods and SVMs. There are strong relations to the theory of reproducing kernel Hilbert space (RKHS), to principal component analysis and canonic correlation analysis known previously from statistics. In recent form their use was extended from statistics to obtain models for dynamic systems. First we summarise the basics for the reproducing kernel based Hilbert space (RKHS) and the support vector machine (SVM) approaches. Following this it will be shown how some frequently used nonlinear models can be obtained by using these concepts. In the last part we discuss the structure estimation problem, i.e. how to determine the (least) number of features (observables) to describe the nonlinear system with a sparse representation.

Open Access: Yes

DOI: 10.1109/SISY62279.2024.10737570

Assessing the Urban Climate Resilience of Cities in Hungary Using an Index-based Approach

Gergely Zoltán Macher Dóra Sipos Judit Pécsinger Dalma Bódizs Éva Veronika Pestiné Rác

Publication Name: Journal of Sustainable Development of Energy Water and Environment Systems

Publication Date: 2025-09-01

Volume: 13

Issue: 3

Page Range: Unknown

Description:

Climate resilience in urban areas is increasingly critical in the face of climate change, particularly in regions where climate variability poses significant challenges. This study introduces the Climate Resilience Index for Town Sustainability, a novel, multidimensional framework designed to evaluate the resilience of 19 Hungarian cities, including Budapest and county capitals. The framework incorporates 41 parameters across environmental, social, and infrastructural dimensions, addressing significant gaps in existing resilience assessments by providing a region-specific, holistic evaluation. The research employs advanced statistical techniques, including principal component analysis and k-means clustering, to analyse the data sourced from the Hungarian Central Statistical Office and the National Adaptation Geo-Information System. This analysis revealed substantial variability in resilience scores among Hungarian county capitals, with Békéscsaba achieving the highest scores due to its extensive green infrastructure, renewable energy adoption, and lower proportion of vulnerable populations. In contrast, Budapest recorded one of the lowest scores, highlighting challenges such as limited green spaces, high population density, and elevated energy consumption. Clustering analysis grouped the cities into eight distinct categories, emphasising the role of geographic and climatic factors in shaping urban resilience. The findings demonstrate the critical importance of targeted interventions, such as expanding green infrastructure, improving energy efficiency, and enhancing sustainable practices. By offering actionable insights for policymakers, this index not only advances resilience research but also provides a replicable framework adaptable to other regions. Its innovative approach to integrating multidimensional parameters represents a significant contribution to the understanding and improvement of urban climate resilience in a changing world.

Open Access: Yes

DOI: 10.13044/j.sdewes.d13.0596

Integrating generative and parametric design with BIM: A literature review of challenges and research gaps in construction design

János Szép Álmos Semjén

Publication Name: Applications in Engineering Science

Publication Date: 2025-09-01

Volume: 23

Issue: Unknown

Page Range: Unknown

Description:

Parametric Design (PD), Generative Design (GD), and Building Information Modelling (BIM) have emerged as transformative tools in the construction industry, offering significant potential for design optimisation, interdisciplinary collaboration, and data-driven decision making. This paper presents a comprehensive literature review to evaluate the current state of PD, GD, and BIM integration, highlighting practical applications and identifying research gaps. In addition to mapping the academic discourse, the review also highlights selected practical implementations from existing literature to illustrate how these technologies are being translated into applied workflows. Furthermore, the methodology section critically reflects on the limitations of the keyword-based search strategy and suggests future directions to mitigate potential literature gaps. While many studies demonstrate efficiency gains in early design phases, the integration of these technologies across the full building lifecycle remains limited. Key challenges include insufficient interoperability between platforms, lack of standardisation, and minimal adoption of GD-BIM combinations in construction and logistics. Furthermore, few studies address the regulatory compliance and real-world scalability of AI-assisted generative models. The review concludes that although these digital methods can accelerate innovation and sustainability, their practical implementation requires further research in construction management, code-based automation, and human-in-the-loop design workflows.

Open Access: Yes

DOI: 10.1016/j.apples.2025.100253

Control of transfer function distortion during RPM-sweep testing of e-drive systems

Balázs Vehovszky Zoltán Gazdagh D. Acs B. Fukker

Publication Name: Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 3779-3787

Description:

This study is focusing on the distortion phenomenon of the vibrational resonance peak when testing an e-drive assembly via RPM-sweep excitation. As the ramp rate increases, the measured response function deviates more and more from the stationary response. This distortion leads to a reduced peak amplitude, a shift in resonant frequency, changes in response shape and consequently, results in an increased half-power bandwidth, eventuating an increased apparent modal damping. These changes in the response are dependent on the sweeping direction and other physical parameters as well, like oil pressure and -temperature. The phenomenon was investigated earlier for linear systems, but not for operational testing of rotary machines, where the characteristics of the spectrum distortion are governed by different principles and are influenced by many other physical factors. A novel way for handling amplitude distortion of e-drives during transient testing is elaborated, which can be used to optimize RPM-sweep rate and other measurement parameters.

Open Access: Yes

DOI: DOI not available

Factors and Variables Shaping Generation Z’s Adoption of FinTech

Vinkóczi Tamás Borbála Tamás Attila Kurucz Ewelina Idziak

Publication Name: Alternative Finance A Framework for Innovative and Sustainable Business Models

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 75-89

Description:

The digital age continues to redefine conventional financial paradigms, and Generation Z is at the forefront, navigating and influencing the trajectory of financial technology (FinTech) applications through their distinct attitudes, behaviors, and expectations. Gen Z is the new archetype and the new behavioral model. The behavioral intention to use FinTech services among Gen Z, explained by the inclusion of factors and in this way being an extension of financial theory, is the hot topic as this is still the beginning of learning the: Facilitating Conditions Intention (FCI), Attitude (A), Behavioral Intention (BI) that define the choices made by Gen Z. In a broader perspective, it is important to point out the main trends among Gen Z toward FinTech services and the conclusions of current research on them. These aspects make it particularly relevant to study the use of FinTech services, which can be done very effectively with social science analysis through structural models. The research presented in this chapter is both descriptive and exploratory, as it presents a theoretical framework that builds on previous research and includes contemporary perspectives based on new research findings.

Open Access: Yes

DOI: 10.4324/9781032713533-8

Mapping IT and Management Challenges in Small and Micro-Businesses: A Path to Digital Maturity in Manufacturing †

Csaba Tápler

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Small and micro-businesses often struggle with poor data accuracy due to a lack of dedicated labor force for non-core business functions. The required efforts and costs associated with improving data accuracy, such as setting up and operating an adequate inventory management system, are unpredictable for these businesses. Despite the data-intensive nature of operating specialized software like MES and WMS, the decision to invest in excessive data manipulation can be challenging for micro-entities, even with the potential benefits. This study aims to empirically determine the challenges, risks, and other non-financial decision factors micro-enterprises face when establishing effective data management and utilization practices. A data model was developed based on interviews with 17 small business manufacturers and service companies to support the essential data entry requirements of micro-businesses. The findings support the concept of a SAAS (Software as a Service) product tailored to the needs of these businesses. Furthermore, this research highlights the under-researched areas of logistics processes and data management in small businesses.

Open Access: Yes

DOI: 10.3390/engproc2024079092