(University of Belgrade, Technical Faculty in Bor, 2026) Janković, Lidija; Panić, Marija

Online shopping has become a crucial part of today's digital marketplace, but due to concerns about product quality, payment security, privacy, delivery, and scheduling, customers often view it as risky. This paper focuses on assessing and ranking the key perceived risks in online shopping using a modified FMEA methodology. The research covers five critical dimensions: product, security, privacy, time, and delivery risks. On a sample of 94 respondents, by calculating Risk Priority Numbers (RPNs) on the basis of probability, severity, and the possibility of detection, the quantification of users' subjective attitudes was carried out. Methodological validity was confirmed by the high value of the Cronbach's alpha coefficient, while MANOVA and multiple linear regression analysis were used to examine the influence of respondents' demographic characteristics on the overall level of perceived risk. The results indicate the absence of a statistically significant influence of demographic variables, thus affirming the thesis about the universality of perceived risks within the observed sample. Online shops should use the data to identify major perceived risks and create focused initiatives to reduce them, which will increase customer satisfaction and trust.

(University of Belgrade, Technical Faculty in Bor, 2026) Janković, Lidija; Jovanović, Ivan

Failure Mode and Effects Analysis (FMEA) is a methodology for identifying, evaluating, and managing risks in systems, processes, and products, to improve reliability and reduce potential failures. The main objective of the papers is to identify, select, and analyse relevant scientific articles to map the current research landscape, publication trends, keyword usage, and authorship patterns. A structured methodology was applied, including defining keywords, collecting articles, selecting relevant studies, and conducting bibliometric analysis. Data were obtained from the Web of Science database for the period 2019–2025. From an initial set of 4,201 articles, the selection was reduced to 347 articles focused on advanced approaches to the FMEA method, using Python scripts to minimise subjectivity. Bibliometric visualisation was conducted using VOSviewer, highlighting the most productive authors, country collaboration network, and co-occurrence of keywords. The bibliometric analysis identified the most influential authors and research clusters, with cooperation networks indicating pronounced international and interdisciplinary connections among researchers.

(University of Belgrade, Technical Faculty in Bor, 2026) Janković, Lidija; Vuković, Milovan; Urošević, Snežana

Qualitative methods play a significant role in management and business research, particularly in the study of complex organisational and social phenomena. This paper aims to present and compare content analysis and thematic analysis as two important techniques of qualitative data analysis. The paper is based on a review of relevant scientific literature. The results indicate that content analysis is suitable for the systematic processing and categorisation of textual data, while thematic analysis enables deeper interpretation of meaning and experiences. It can be concluded that these methods differ in research approach, but their selection depends on the research objectives and the nature of the data.

(Savez mašinskih i elektrotehničkih inženjera i tehničara Srbije (SMEITS), Društvo za procesnu tehniku, 2026) Janković, Lidija; Arsić, Sanela; Radić, Aleksandra; Milošević, Isidora

The development of mobile technologies has significantly affected the educational environment, emphasizing the importance of quality management and standardization in the provision of educational services. Mobile learning (m-learning), as a continuation of e-learning, allows students flexible and interactive access to educational content via mobile devices, which contributes to the standardization and improvement of the quality of the educational process in higher education. The aim of this research is to examine the factors that shape the perception of the quality of mobile learning services, with a focus on the expected effort, the influence of the lecturer and the personal innovativeness of the students. The proposed research model was tested using partial least squares structural equation modeling (PLS-SEM), based on survey data collected from students at the University of Belgrade, providing insight into the key determinants that contribute to the quality of services in mobile learning. The research results confirm all proposed hypotheses, indicating that effort expectancy, instructor influence, and students’ personal innovativeness have a statistically significant and positive effect on the perceived quality of mobile learning services. The obtained findings provide valuable guidance for decision-makers and higher education institutions in improving the design and implementation of mobile learning platforms, with the aim of achieving higher levels of service quality and standardization in education.

(Obuda University, Keleti Faculty of Business and Management, Budapest, Hungary, 2026) Janković, Lidija; Arsić, Sanela; Radić, Aleksandra

The rapid expansion of mobile banking has redefined modern financial ecosystems, enabling users to perform banking activities anytime and anywhere through digital platforms. Despite its widespread adoption, the mechanisms that shape users’ trust, motivation, and behavioral intention remain insufficiently clarified in the literature. Hence, the aim of this study is to examine how perceived security and perceived privacy influence user trust in mobile banking, and how trust further affects motivation and behavioral intention. The study seeks to better understand how users’ perceptions shape their intention to continue using mobile banking services. The proposed structural model was empirically examined using partial least squares structural equation modeling (PLS-SEM) based on survey data collected from a sample of mobile banking users in Serbia. The findings provide practical implications for financial institutions and enhance understanding of mobile banking usage behavior.

(University of Belgrade, Technical Faculty in Bor, 2026) Radić, Aleksandra; Arsić, Sanela; Nikolić, Đorđe; Bobek, Samo; Sternad Zabukovšek, Simona

Enterprise Resource Planning (ERP) systems represent an important technological infrastructure for enhancing operational efficiency and strategic decision making in various industries. This study examines the key determinants influencing the adoption of ERP systems, with a particular focus on organizations operating in the manufacturing and service sectors in the Western Balkans region. In order to empirically evaluate the proposed conceptual framework, Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA) were employed. In this way, both linear relationships and configuration pathways underlying ERP implementation behavior were captured. The results of the PLS-SEM analysis show that constructs such as work compatibility, perceived usefulness and external factors are statistically significant predictors of users’ attitudes towards using ERP systems. In addition, a significant relationship was found between attitude and actual use of ERP systems, with user experience serving as a moderating variable. Notably, the multi-group analysis revealed no significant differences in intentions, attitudes or preferences between users from the manufacturing and service sectors. The results of the fsQCA study also show that work compatibility and perceived usefulness are the core present conditions necessary for effective ERP adoption. This study contributes to the existing literature by integrating multiple analytical approaches to explore the complexity of ERP usage. Additionally, it provides practical insights for enterprise managers, ERP vendors and policymakers.

(University of Belgrade, Technical Faculty in Bor, 2026) Radić, Aleksandra; Milijić, Nenad; Nikolić, Ivica

Occupational injuries remain a significant issue in European countries, affecting both worker safety and broader socio-economic outcomes. This study groups European countries into homogeneous categories based on workplace injury levels from 2014 to 2023. The analysis uses secondary data from Eurostat, including indicators on fatal and non-fatal workplace accidents within aggregated sectors: agriculture, industry and construction (excluding mining), and business economy services. To achieve the research objective, K-means cluster analysis was applied after data standardisation using Z-score normalisation. The results show substantial variability in occupational injury levels across countries, with particularly high dispersion for non-fatal injuries. The clustering identifies two distinct groups of countries, representing relatively safer and less safe working environments. While most countries show consistent classification across both fatal and non-fatal injury models, a significant number display discrepancies, suggesting that these indicators capture different aspects of workplace safety.