Original Research
How do age and location affect a business? Evaluating the objectives, outputs and outcomes of small business policy
South African Journal of Economic and Management Sciences | Vol 19, No 3 | a1335 |
DOI: https://doi.org/10.4102/sajems.v19i3.1335
| © 2016 Menisha Moos, Melodi Botha
| This work is licensed under CC Attribution 4.0
Submitted: 11 March 2015 | Published: 05 September 2016
Submitted: 11 March 2015 | Published: 05 September 2016
About the author(s)
Menisha Moos, University of Pretoria, South AfricaMelodi Botha, University of Pretoria, South Africa
Full Text:
PDF (360KB)Abstract
Many scholars have dedicated their studies to understanding the kind of assistance given to small business. Likewise, numerous studies have concentrated on how government in particular, through a small business policy, can be instrumental in providing business support. This article evaluates South Africa‘s small business policy by concentrating on its objectives, outputs and outcomes. Studies evaluating small business policy according to its objectives, outputs and outcomes, have been limited. Such policy evaluation goes beyond merely reporting to understanding why certain phenomena take place. As an emerging economy, South Africa is in dire need of well-developed policies. This article proposes that understanding the link between small business policy and the age and location of a business may help government to refine policy formulation and design. Using a survey method and cross-sectional research design, the sample size of 340 respondents consisted of start-up and established business owners. This study found that not the age of the business, but only its location (the metropolitan municipality where the business is located) has a statistically significant effect on the objectives, outputs and outcomes of the small business policy. These findings should assist both national and international policymakers to identify specific context-bound interventions relevant to the location of businesses with a view to improving them.
Keywords
No related keywords in the metadata.
Metrics
Total abstract views: 4351Total article views: 1702
Crossref Citations
1. Empirical analysis of organizational quality defect management enabling factors identification based on SMT, interval-valued hesitant fuzzy set ELECTRE and QRA methods
Qiang Liu, Zhifeng Lian, Yu Guo, Juan Luis García Guirao
Journal of Intelligent & Fuzzy Systems vol: 38 issue: 6 first page: 7595 year: 2020
doi: 10.3233/JIFS-179831