1. Correlation of trust and work engagement : a modern organizational approachAna Nešić, Slavica Mitrović Veljković, Maja Meško, Tine Bertoncel, 2020, original scientific article Abstract: In modern organizations, in which changes are happening faster and more unpredictably, employees are gaining a more complex role and increasing importance. New approaches to employee insight, based on the heavy work investment concept (HWI), bring together different theoretical and practical approaches that attempt to explain the causes and consequences of certain organizational behaviors. The fundamental issue is determining whether engagement and trust, remain two of the critical factors of an organizations success, or are their roles in effectively organized systems significantly changed or reduced. This research aims to establish a correlation between trust and work engagement in on 787 respondents from 16 organizations in Serbia. Trust in organizations is measured through the dimensions of benevolence, integrity, competence and predictability. Engagement of employees is measured through the dimensions of energy, dedication and absorption. The results showed a significant correlation between dimensions of trust: benevolence/integrity and competence, with all work engagement dimensions. The strongest correlation is established between the trust dimension of benevolence/integrity and the work engagement dimension - energy. The significance of the research is reflected in the elucidation of behavioral factors of employees in organizations burdened with transitional changes.
Keywords: work engagement, trust, organization, HWI concept, employees, Serbia
Published in DKUM: 30.01.2025; Views: 0; Downloads: 5
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2. Big data usage in European Countries : cluster analysis approachMirjana Pejić Bach, Tine Bertoncel, Maja Meško, Daila Suša-Vugec, Lucija Ivančić, 2020, original scientific article Abstract: The goal of this research was to investigate the level of digital divide among selected European countries according to the big data usage among their enterprises. For that purpose, we apply the K-means clustering methodology on the Eurostat data about the big data usage in European enterprises. The results indicate that there is a significant difference between selected European countries according to the overall usage of big data in their enterprises. Moreover, the enterprises that use internal experts also used diverse big data sources. Since the usage of diverse big data sources allows enterprises to gather more relevant information about their customers and competitors, this indicates that enterprises with stronger internal big data expertise also have a better chance of building strong competitiveness based on big data utilization. Finally, the substantial differences among the industries were found according to the level of big data usage.
Keywords: big data, cluster analysis, digital divide, k-means, enterprise, industry, Europe, quality
Published in DKUM: 14.01.2025; Views: 0; Downloads: 3
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3. Psychosocial factors in the development of low back pain among professional driversFriderika Kresal, Tine Bertoncel, Maja Meško, 2017, original scientific article Abstract: Background and purpose: Professional drivers as a group are exposed to high risk of developing low back pain due to ergonomic factors and work conditions. The purpose of the study was to examine to what extent the low back pain occurs among Slovene professional drivers as a result of the development of various psychosocial factors.
Methodology: The study involved 275 respondents (professional bus drivers, car/van drivers, international truck/ lorry drivers, and ambulance car drivers). Hypotheses were tested using multivariate statistical method (regression analysis) and analysis of variance. Data were collected by structured questionnaire comprised of three parts: socio-demographic data, basic psychosocial factors causing low back pain, and incidence, duration and severity of low back pain as a result of psychosocial risk factors, was implemented.
Results: The results of quantitative survey suggest that low back pain is mostly caused by lifting and carrying heavy loads, inadequate working conditions, poor physical fitness, regular nights out, shift work, and stress. Only the impact of gender on low back pain distress among professional drivers was confirmed, predominantly among bus drivers and lorry drivers on international routes. Low back pain occurrence was less common, albeit not statistically significant, among professional drivers of vans and passenger cars.
Conclusion: Our study suggests that psychosocial factors are also important cause for the development of low back pain among professional drivers and can limit the quality of their social and professional lives.
Keywords: low back pain, psychosocial factors, professional drivers, prevention, Slovenia
Published in DKUM: 18.01.2018; Views: 1427; Downloads: 359
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