Gender and the knowledge of financing options by immigrant entrepreneurs in South Africa
Notice bibliographique
Résumé
IntroductionTwo of the major economic challenges facing South Africa are weak economic growth and high rate of unemployment (Mahadea & Simson, 2010; Munyeka, 2014). South Africa's unemployment rate has increased from 24.2% in 2013 to 26.7% in 2016 (Statistics South Africa, 2016). The economic growth moved into the negative territory in the first quarter of 2016 as the South African economy contracted by 1.2% quarter-on-quarter (Statistics South Africa, 2016). The poverty level has gradually reduced since 1994. However, income inequality is still very high (Bhorat & van der Westhuizen, 2012; Statistics South Africa, 2014). To reduce unemployment, poverty and income inequality, South Africa needs a faster and more inclusive economic (National Panning Commission, 2012). However, there is a significant gap between the actual and the desired economic growth rate of South Africa (Fourie, 2013).Entrepreneurship and small business development is one of the solutions to the highlighted development challenges. Entrepreneurship leads to job creation and a reduction in the unemployment rate (Audretsch & Thurik, 2000; Musa & Semasinghe, 2013). Immigrant entrepreneurship is an important part of entrepreneurship and small business resurgence (Kloosterman & Rath, 2002). Immigrant-owned businesses contribute to employment and economic growth of host countries (Organisation for Economic Co-operation and Development (OECD), 2013). Immigrant entrepreneurship can help to drive the economic growth of host countries (Turkina & Thai 2013; Lofstrom, 2014; Anastasia, Dimitrios, Anastasios & Andreas, 2014). OECD (2013) points out that entrepreneurship is marginally higher among immigrants than natives. However, the survival rate of immigrant-owned businesses is often lower than that of their native counterparts (Desiderio, 2014).One of the primary factors that negatively impact on the performance of immigrant entrepreneurs is access to finance. Immigrant entrepreneurs often do not have sufficient capital to start and grow their business. (Rath, 2011; Anastasia, et al. 2014). Immigrant entrepreneurs face greater obstacles in accessing credit from financial institutions than their native born peers (Miller, Abreo, Farmer, Moon & McCullough, 2011; Desiderio, 2014). Capital acquisition is a one of the major issues facing small businesses. Without appropriate level of capital it is difficult for any business to survive and grow (Van Auken, 2003).According to Gregory (2013), access to finance by entrepreneurs can be affected by both demand and supply-side factors. It is of significance to recognise the demand-side factors that impact on access to finance by entrepreneurs ((Matshekga & Urban 2013; Rao 2015). Inadequate knowledge of the financing options available to entrepreneurs can lead to financial constraints (Seghers, Manigart & Vanacker 2009; Pangeran, 2015). In addition, owners' characteristics such as gender can affect the knowledge of financing options by entrepreneurs (Okafor & Amalu 2010; Kamukama & Natamba 2013). This study makes a significant contribution to the knowledge on access to finance by immigrant entrepreneurs. Understanding the factors that can affect the performance of immigrant entrepreneurs is of importance in improving their contribution to the host economy (Fairlie & Lofstrom 2013).The objectives of the studyAccess to finance is one of the major challenges facing immigrant entrepreneurs. The knowledge of the available financing options can help to improve access to finance by immigrant entrepreneurs. The objectives of this study are (1) to investigate the knowledge of financing options by immigrant entrepreneurs (2) to examine if there is a significant gender difference in knowledge of financing options by immigrant entrepreneurs.Immigrant entrepreneurshipAn immigrant can be described as an individual that comes from another country to a particular host country (Dalhammar, 2004). …
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».