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How women manage career change in today’s labour markets
No full textOccupational segregation is one of the main causes of all gender differences today, especially of the gender earnings gap, along with job characteristics and industry. It is empirically proven that educational segregation, work experience and other personal characteristics of workers make a smaller contribution to explaining the existing inequalities between men and women in the labour market and are even less significant. This paper examines conceptually how women cope with professional challenges, particularly in terms of the impact of technology on the labour market, changes in educational structures and occupations. Drawing on existing theoretical concepts and empirical findings, the conclusions will serve to highlight gaps in current approaches and provide some directions for future empirical research on trends in career change and women’s participation in the labour market
Applying Uses and Gratifications Theory to TikTok: A systematic literature review of users‘ motivations
No full textThis paper provides a systematic review of the existing literature that
utilizes Uses and Gratifications Theory
(UGT) to explain users‘ motivations for
using the TikTok platform. The aim of the
paper is to identify and classify the main
motives that drive user engagement on
this social network, as well as to provide
an insight into the research trends, geographical distribution of studies on this
topic and the methodological approaches
that have been applied in the relevant literature. An analysis of selected scientific papers led to the identification of ten
dominant clusters of user gratifications:
cognitive, affective, social/relationship,
self-expression/self-identity, relaxation,
recognition and fame, escapism, hedonistic, trendiness/novelty and agency and
interactivity. This overview contributes to a
deeper understanding of user behavior on
TikTok and provides a basis for future research in this area. Finally, the paper points
out the gaps in the existing literature and
suggests guidelines for future theoretical
and empirical research
Artificial intelligence adoption by enterprises in Serbia
No full textThis paper analyzes the adoption of artificial intelligence (AI)
technologies among enterprises in Serbia, with a comparative view of their
position relative to companies in the European Union. The research is based
on desk analysis of secondary data sourced from Eurostat. Although the
overall number of enterprises using AI in Serbia remains relatively low, it is
steadily growing. Large enterprises are the most active adopters, with the
Information and Communication sector leading in implementation. The most
commonly used AI technologies include text analysis (text mining) and
machine learning methods such as deep learning for data processing. AI is
predominantly applied in areas such as marketing and sales, as well as
research, development, and innovation
Perceptions, trust and action: the role of demographics in shaping influencer impact
No full textResearch Question: How do demographic characteristics shape audience perceptions, trust levels, and behaviour regarding influencers? Motivation: Although the role of influencers in shaping consumer behaviour has been widely studied, there has been little research into how specific demographic groups differently perceive the credibility and influence of influencers. In accordance with that, this research is motivated by the need to examine how demographic differences shape audience perception and trust in influencers. It aims to provide explanation why the same influencer can have different degrees of influence on different demographic segments of the audience, which can contribute to more precise targeting and optimization of marketing strategies. Idea: Research hypotheses assume that gender, age, place of residence, level of education and work status of consumers significantly influence their following of influencers, the level of trust in influencers and their behavioural intentions. The independent variables are demographic characteristics, and the dependent variables: following, trust and behavioural change. Data: The research was conducted by surveying a sample of 317 respondents in the Republic of Serbia during May 2023. The questionnaire was distributed via the Internet and social networks, by using a snowball sampling technique. Tools: The questionnaire consisted of five sections: the first section related to demographic characteristics of respondents; the second related to general social media consumption; the third related to respondents’ attitudes towards influencer following; the fourth related to respondents trust in influencers and the fifth related to respondents’ behavioural change. Findings: female gender and generational affiliation were found to be significant predictors of following influencers. Female gender, lower age and the place of residence were found to be significant predictors of higher trust in influencers. Female gender and generational belonging were significant predictors of higher degree of behavioural change under the impact of influencers’ activities on social media. Contribution: The findings of this paper contribute to the current literature related to influencer marketing and behaviour on social media, by investigating factors which motivate social media users to follow influencers
Empowering Women in Serbian Rural Areas with Entrepreneurial Initiatives
No full textEntrepreneurial initiatives represent an important tool for the economic
empowerment of women in rural areas, allowing them to generate additional
sources of income, reduce poverty rates, and improve their social integration. This
research analyzes the role of entrepreneurial initiatives in empowering women in
rural areas of Serbia, with a particular focus on their economic and social aspects.
The direct economic effects of entrepreneurial initiatives, such as generating
additional income and creating new jobs, are key aspects of economic
empowerment for women in rural communities. At the same time, women
entrepreneurship in rural areas can serve as a tool to mitigate migration and
promote more balanced regional development. For the purposes of this research, a
survey method was used, and the study was conducted on a sample of 73 women
living in rural areas of the Republic of Serbia from July to September 2024. The
data was analyzed using SPSS software. The results of this research indicate
significant economic and social benefits of entrepreneurial initiatives, which
contribute to the economic independence and social empowerment of women in
rural areas but also highlight challenges such as limited access to finances,
education, and training. This research emphasizes the need for greater support from local and state institutions, as well as the importance of networking among
women entrepreneurs to enhance their access to resources and markets
Harmonization of the agricultural policy of the Republic of Serbia with the agricultural policy of the European Union
No full textThis paper focuses on agricultural policy as a set of measures that influence the functioning, growth, and improvement of agriculture in a country like the Republic of Serbia. Serbia’s agricultural policy is intertwined with various national policy activities and depends on the common budget resources, facing constant pressures and challenges. The key objective is to analize the alignment of Serbia’s agricultural policy (SAP) measures with the agricultural policy of the European Union. The results of this research indicate that although the SAP has experienced decline and serious crises, structural and systemic changes in agricultural policy have occurred in recent years through integration, the adoption of standards and regulations, and significant financial investments. Harmonization with EU laws, accompanied by increasing financial assistance, enables further development of Serbia’s agricultural policy. However, several limiting factors still exist in Serbia concerning alignment with the EU’s agricultural policy, such as the unfavorable position of rural areas, low educational levels of the population, and depopulation of rural regions
The relationship between teaching approaches and engineering students’ life satisfaction
No full textDeterminants of Women's Financial Inclusion: Evidence from the Gulf and the Western Balkan Region
Get PDFWomen's financial inclusion represents a key element in enhancing women's
entrepreneurship. The aim of this study is to investigate the impact of age,
education, employment, income quintile, and region on the level of financial
inclusion (FI). The data for the four Gulf countries (Gulf Cooperation Council)
and five Western Balkan countries were gathered from the Global Findex
Database 2017. The total sample includes 3,973 women. Multiple linear regression
is used to investigate the impact of socio-demographic factors on FI. Additionally,
the paper provides an overview of the latest available data on several indicators
related to FI at the macro level. The results show that education, employment, and
income have a statistically significant positive impact on FI. The relationship
between age and FI is statistically significant, exhibiting an inverted U-shape. This
means that FI increases up to 55 years, and after that transition point, it starts to
decline. Moreover, the region plays a significant role, considering that the level of FI of the respondents from Western Balkan countries is lower than that of those
from the Gulf region
Predictive Insights into Digital Competencies: A Data-Driven Approach to Inclusion
No full textDespite their significant demographic presence, accounting for nearly 16% of the global population, persons with disabilities (PWDs) remain underrepresented in research on their inclusion in digital society, revealing a significant gap in scientific understanding compared to the general population. To address this gap, this study proposes an innovative approach to empowering PWDs by developing predictive models that anticipate PWDs’ digital competence perceptions based on socio-demographic and contextual factors. The study was conducted on a sample of 250 PWDs in Serbia using a validated instrument based on the Digital Competence Framework (DigComp). Standard multiple regression was used to estimate the models for each DigComp competence area. The results show that three variables are statistically significant in all five DigComp areas: age, health conditions (walking impairments) and employment status (employed). The prediction of PWDs’ digital competence is also influenced by gender and education level, which were found to be statistically significant predictors in four DigComp competence areas. The development of predictive models that assess PWDs’ digital competence perceptions based on socio-demographic profiles enables personalized support and promotes digital inclusion through emerging technologies such as artificial intelligence (AI). The limitations of the study lie in the sample size, method of data collection and reliance on self-assessment