Title: Statistical modelling of self-employment intentions in higher education

Authors: Josipa Mijoč; Jasna Horvat; Suzana Marković

Addresses: Department of Quantitative Economics and Informatics, Faculty of Economics, Josip Juraj Strossmayer University of Osijek, Trg Ljudevita Gaja 7, 31000 Osijek, Croatia ' Department of Quantitative Economics and Informatics, Faculty of Economics, Josip Juraj Strossmayer University of Osijek, Trg Ljudevita Gaja 7, 31000 Osijek, Croatia ' Department of Quantitative Economics, Faculty of Tourism and Hospitality Management Opatija, University of Rijeka, Primorska 42, p.p. 97, 51410 Opatija, Croatia

Abstract: Self-employment is a fundamental indicator of the proactiveness of individuals, groups or society as a whole, while the measure of success of higher education is the number of participants educated and trained in higher education programs for future proactive inclusion in society. The aim of this paper is to highlight the characteristics of the proposed model (i.e., the SCC model), which is applied to data collected at a higher education institution and used for modelling self-employment intentions. The SCC model tests the predictive ability of different constructs (motivation for achievement, higher education, theory of planned behaviour, and control variables) related to self-employment intentions. The sample (n = 426) consists of graduate students faced with two future career choices - either self-employment or employment in a company (working for someone else). Hierarchical multiple regression was used to analyse the proposed model and it was found that the academic context the students are exposed to affects the process of modelling self-employment intentions.

Keywords: hierarchical regression analysis; measuring intentions; higher education; self-employment intentions; theory of planned behaviour; TPB.

DOI: 10.1504/IJBG.2023.133706

International Journal of Business and Globalisation, 2023 Vol.34 No.4, pp.405 - 422

Received: 24 May 2019
Accepted: 01 Apr 2020
Published online: 02 Oct 2023 *

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