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The emergence of gig economy under the impact of digitalization - model of the success factors of freelancers
Ivona Huđek, 2022, doctoral dissertation

Abstract: This dissertation examines the emergence of the gig economy under the impact of digitalisation, focusing on one alternative form of work – freelancing. Over the past two decades, new and contemporary occupational concepts have emerged in the context of technological advances and the reorganisation of employment relationships in the wake of digitalisation. Technology has enabled many things to be done online or remotely, and for work to be broken down into smaller components in the form of projects. Scholars explain that the most important innovations influenced by digitalisation are the development of new business models characterised by less dependence on physical elements or dematerialisation of processes, as seen in the “gig economy”. In the gig economy, very short-term tasks or projects within specific activities are performed by individual self-employed workers, usually coordinated through online platforms or applications. As a result, many workers are able to complete tasks in a more efficient and fragmented manner. Unlike traditional careers characterised by hierarchical advancement, organisational career management, and low mobility, many individuals are also becoming more mobile and self-directed in their careers. As a result of these developments, new work arrangements have emerged that are taking up an increasingly large share of the labour market in major economies (such as the US and UK), heightening concerns about how workers are classified and raising questions about entrepreneurship, future career development, work-life balance, employment law frameworks, and social protections. These flexible work arrangements are often referred to as alternative and are performed by independent contractors, known as freelancers. Therefore, the dissertation was carried out to examine this alternative form of work at the national level in Slovenia, and explore the issue of career satisfaction, and specifically whether freelance work allows fulfilment through project work. In this dissertation, a freelancer refers to a self-employed individual without employees who is responsible for paying their own taxes and welfare contributions, works on projects for multiple clients, and works remotely, usually from home. The development of the research model for the purposes of this dissertation is based on Van den Born and Van Witteloostuijn’s (2013) freelancer success model, which is based on the intelligent career framework that consists of three interrelated variables: knowing why, knowing how, and knowing who. The ‘knowing why’ variable mainly reflects our personality traits and motivation. The ‘knowing how’ variable reflects human capital, while the ‘knowing who’ variable reflects social capital inside and outside the workplace (Parker & Arthur, 2004). However, the external environment is missing in this model. Therefore, the dissertation also included the external part, i.e. the external environment consisting of the characteristics of the entrepreneurial ecosystem: government programs, cultural and social norms, legal system support, and digital support. As Slovenia and other EU member states are implementing national strategies for digital transformation, this dissertation provides insight into freelancers in Slovenia and their perceptions of certain aspects of external environmental factors, which may be helpful in evaluating current digital strategies and future policy proposals and decisions. Therefore, the main objective of the dissertation was to test a conceptual model that links multidimensional variables that influence the perceived success of freelancers based on a review of the literature and empirical research, and thus to learn certain specific characteristics of the group of entrepreneurial, self-employed individuals known as freelancers, and to determine the extent to which personality traits, human and social capital, and motivation of the individual, as well as a supportive environment (entrepreneurial ecosystem),
Keywords: digitalisation, gig economy, freelancers, predictors of success, structural model equation
Published in DKUM: 14.11.2022; Views: 1003; Downloads: 174
.pdf Full text (5,99 MB)

Early predictors of 30-day mortality in non-ST-elevation acute coronary syndrome patients
Suzana Rožič, Melanija Županić, Andreja Sinkovič, 2008, original scientific article

Abstract: Background: The incidence of non-ST-elevation acute coronary syndrome (ACS), including unstable angina pectoris and non-ST-elevation myocardial infarction (MI), is increasing in comparison to ST-elevation ACS. Our aim was to evaluate predictive role of admission variables for 30-day mortality in non-ST-elevation ACS patients. Patients and methods: We retrospectively analysed the data of 415 patients, admitted to University Clinical Center Maribor in 2006 due to non-ST-elevation ACS. Inclusion criteria were rest chest pain, ECG changes (ST-segment depression > or = 0.1 mV, and/or negative T wave > or = 0.1 mV and/or pathologic Q and/or non-specific ECG) and/or increased troponin T levels. Predictors of 30-day mortality were analysed by univariate and multivariate logistic regression. Results: 30-day mortality was 4.3 %. Between nonsurvivors and survivors there were significant differences in mean age, the incidence of arterial hypertension, positive family history of coronary artery disease, in mean admission systolic and diastolic blood pressure, pulse, mean admission troponin T, leukocyte count, CRP, creatinine and the incidence of admission heart failure. Multivariate logistic regression proved that most significant independent early predictor of 30-day mortality was admission heart failure (OR 41.21, 95 % CI 3.50 to 484.66, p = 0.003), followed by admission serum creatinine (OR 0.989, 95 % CI 0.981 to 0.997, p = 0.008) and troponin T (OR 0.263, 95 % CI 0.080 to 0.861). Conclusion: Most significant independent predictor of 30-day mortality of patients with non-ST-elevation ACS, being 4.5 %, was heart failure on admission.
Keywords: mortality, non-ST-elevation acute coronary syndrome, predictors
Published in DKUM: 27.03.2017; Views: 1371; Downloads: 97
.pdf Full text (111,63 KB)
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