Entrepreneurial intention : perspectives from women in a South African province

Abstract: The objective of this study was to assess the entrepreneurial intention of women in a South African province. The study employed a quantitative, exploratory research design, utilising a self-administered survey of 200 women in South Africa’s North West province. A non-probability sampling approach was followed. Data were analysed using the Statistical Package for Social Sciences (SPSS) by means of an exploratory factor analysis, Pearson’s product-moment correlation and multiple regression analysis. Findings revealed that moderate entrepreneurial intentions exist among women in the North West province. Entrepreneurial self-efficacy was found to yield the greatest influence on entrepreneurial intention, followed by risk-taking attributes and cultural perspectives. It also emerged that attitudes towards entrepreneurship, cultural perspectives, risk-taking and self-efficacy had a significant and positive relationship with entrepreneurial intention. There was no statistical difference in entrepreneurial intention in terms of age, educational qualifications and employment status. The study provides guidelines for governmental and non-governmental role players in harnessing and promoting entrepreneurial intention among women. The study provides insights into the existence of entrepreneurial intention in a rural setting in South Africa, which has been neglected in literature. This study contributes to the existing body of knowledge on entrepreneurial intention in South Africa. The findings can be used to guide policy interventions as they highlight factors which should be integrated into programmes enhancing women’s entrepreneurial intention

Susceptibility of optimal train schedules to stochastic disturbances of process times

This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact on the scheduler performance

Business Management 2A

Exam paper for first semeste

Rescheduling railway traffic taking into account minimization of passengers’ discomfort

Optimization models for railway traffic rescheduling in the last decade tend to develop along two main streams. One the one hand, train scheduling models strives to incorporate any relevant detail of the railway infrastructure having an impact on the feasibility and quality of the solutions from the viewpoint of operations managers. On the other hand, delay management models focus on the impact of rescheduling decisions on the quality of service perceived by the passengers. Models in the first stream are mainly microscopic, while models in the second stream are mainly macroscopic. This paper aims at merging these two streams of research by developing microscopic passenger-centric models, solution algorithms and lower bounds. Fast iterative algorithms are proposed, based on a decomposition of the problem and on the exact resolution of the sub-problems. A new lower bound is proposed, consisting of the resolution of a set of min-cost flow problems with activation constraints. Computational experiments, based on a real-world Dutch railway network, show that good quality solutions and lower bounds can be found within a limited computation time