Research Article: 2020 Vol: 26 Issue: 3S
Lawrence Mpele Lekhanya, Durban University of Technology
Nirmala Dorasamy, Durban University of Technology
The focus of this research paper is to provide an exploratory study on Entrevolutionizing Township Economy growth strategies in KwaZulu-Natal (KZN), South Africa. With township economy growth still an issue of concern in South African provinces,the study intended to establish the understanding and knowledge of various factors contributing to the growth of township economy and their implications. Empirical data was collected from 241) participants in different townships in KZN. This research was quantitative in nature and a 5-point Likertscaledquestionnairewas used to collect data from the selected places. Findings of the research indicated that township economy growth is affected by many factors such as political connections 58 (24.1%, P-Value < 0.001) and a high rate of unemployment, which impact potential customers 57 (23.7% P- Value <0.001). It further revealed additional issues of concern such as poor infrastructural support and financial support from relevant agencies (P-Value < 0.027). This study will benefit future investors in township economy, prospective entrepreneurs who would consider startingbusiness entities in townships, as well as business policy-makers in the selected municipalities. Most work done on the township economy has concentrated on its importance, with little emphasis on understanding and knowledge of various factors affecting entrepreneurial activities and performance of this sector of the economy. The findings are limited by the study’s exploratory, quantitative nature and small sample. Therefore, generalization of these results should be done with care and further research, with a large sample and consideration of other provinces, is recommended.
Entrevolutionizing Township, Economy growth strategies, Unemployment.
For many years, townships have been regarded as a way of life in South Africa (Cant & Rabie, 2018). It is believed that South African townships havebecome more significant over a period of time, due to their urbanization and continued economic development. The market has become very lucrative, however, a number of risks exist in the process that can only be mitigated through a thorough understanding of township development and establishment processes (UKZN%20Township/01chapter 1-2.pd). According to Scheba & Turok (2019), townships are obviously perceived to be an extremely turbulent environment, with regard to development and economic growth, due to social strainand prevailing competition for scarce resources. The injection of additional resources could simply leak out, unless more conducive conditions are created for enterprises to grow and develop locally (Scheba & Turok, 2019). Charman (2017) indicates that, in South Africa, the idea that the township economy needs to be revitalized has begun to gain significant political traction. “However, to begin with, the township was never originally conceived of, or designed as a place of potential, for possible revitalization. The historical roots of place and location account for the primary challenge faced in township economic development, and are the primary source of every conceivable obstacle faced in the vitalization of the township economy” (Nqapela & Fakir, 2017).
Research Problem
Since South African townships were designed as dormitory towns for the labor required to serve the needs of mining and other industries, they had limited social services, and even less economic infrastructure and wereconsiderably far from promoting local economic development, in a context where apartheid laws curtailed any form of growth (Mahajan, 2014). SME South Africa (2017) highlights that South Africa’s townships have always been a hive of entrepreneurial activity, however, the main challenge has been to unlock the potential in order to generate broader economic benefits. According to Mothobeli (2018), a sad factor is that the township economy has never been accounted for nor thoroughly researched to establish the number of residents, total turnover of businesses, contribution to local GDP and employment levels. Ntombela (2016) supports the premise that the townships have a low rate of entrepreneurial activities in South Africa compared to other countries of the South (Latin America and Asia) and the rest of Africa.
Research objectives
1. To identify and discuss various factors contributing into entrevolutionizing township growth strategies in KZN; 2. To examine to what extend these identified factors affect the entrevolutionizingof township growth strategies in KZN; and 3. To suggest alternative entrevolutionizing township growth strategies in KZN.
Definition of Township Economy
There is no formal or official definition for the term “township” (Pernegger & Godehart, 2007). On the one hand, Harrison et al. (1997) describe townships as areas formerly set aside for African settlement by the South African apartheid era laws; they include informal settlements, formal townships, as well as site and service areas. Township economy is also explained as microeconomic and related activities that take place within townships areas (McGaffin et al., 2014). According to these authors, both townships and their economies tend to differ significantly in terms of their theories, current dynamics, location characteristics, constraints and future potential.Townships are, nevertheless, part and parcel of the business landscape in South Africa,even though these settlement areas were started during the apartheid era in South Africa (Thulo, 2015). Businesses in townshipsrange from those in survivalist mode to highly organized and sizeable SME operations (Vacy-Lyle, 2017). These include retailers, salons, shisanyama eateries, and motor vehicle and cellular services, as well as repair shops and small-scale manufacturers, as popular businesses in townships (Bophela & Khumalo, 2019). In South Africa, a “township” is a dense urban settlement usually built at a distance from the centers of commercial and industrial activity. In the apartheid era, this was by design, as townships were established as dormitory towns for black workers in mines and factories, with no internal economic logic and limited social services. Moreover, in the post-apartheid period, this pattern has tended to be reproduced, due to large-scale projects on cheap but poorly-located land offer lower unit costs, despite being far from economic opportunities in the core economy. The social, infrastructural and economic costs of this ineffective urban planning are under-estimated and become set in concrete (National Treasury, 2017). “Township economy” refers to enterprises and markets based in the township (Entrepreneurship, 2017).
Characteristics of Township Economy
Township enterprises are involved in wide and diverse economic activities, ranging from spaza shops, street vending, hair salons, shebeens and minibus taxis, to mechanical services, manufacturing, burial societies, and stokvels and child care services. According to du Toit (2020), a convenience shop operated as a small informal retailer in a developing country’s urban landscape and referred to as aspaza shopin South Africa, is an important and vital part of South African townships and play an important role in food security, self-employment and community cohesion.Ashebeen is described as a liquor outlet“run from residential homes and possess the necessary alcohol trading licence to make the business legal”, however, illegal operations are plentiful and the cause of much “moral and public health arguments”. A stokvel, as explained by Biyela, et al. (2019); is an “Indigenous Savings and Credit Association”or simply put, an informal savings scheme.
Township businesses are largely micro-enterprises with low capital and a low skills base (BBQ, 2017). Powell (2014) indicates that exclusion and containment still persist in some of townships; due to their geographical marginal space. Sibiya (2012) stated that these areas were characterized by deliberate exclusion by race (blacks, colored and Indians) from mainstream economic participation and services. Townships were typified by inadequate infrastructure, monotonous housing patterns and low support services, owing to the unfair distribution of resources during apartheid (Lester et al., 2009). All these areas are set apart by low levels of community facilities and commercial investment, high unemployment, low household incomes and poverty (Charman, 2017).While most township businesses are described as necessity microenterprises (delineated by poverty and low-income), some are opportunity enterprises shaping fruitful black entrepreneurs who have graduated from exclusively serving the township economy (Cant & Rabie, 2018).
The Importance of Township Economy
According to Mahajan (2014) a World Bank study on South African townships indicates their combined economy is estimated at 100 billion. Mothobeli (2018) indicates that what cannot be disputed, is the fact that they provide massive turnover on a weekly basis to major local and national retailers that, when accounted for, could be more than R800 million a month. Charman (2016) stipulates that the township economy provides opportunities to acquire skills, gain on-thejob experience, and build social skills and networks. He believes they provide good business opportunities for those youth able to apply their knowledge and skills, and mobilize capital.The enterprises and markets found in townships are described as township economy. These are enterprises operated by townships’ entrepreneurs, to primarily meet the needs of township communities and therefore, can be understood as “Township enterprises”, as distinguished from those operated by entrepreneurs outside the townships (BBQ, 2017).In addition, local practices with Township businesses are contrary to the international trend where businesses are relocating to less congested areas, with easier personal and vehicle access, whereas township businesses are trying to position themselves more proximate to high density population concentrations and large volumes of traffic, rather than away from them (Nqapela & Fakir, 2017).
Factors contributing to the Township Economy
Lack of Infrastructure: Authors such as Thulo (2015) believe that a serious lack of infrastructure is perceived to be the main challenge for township economy. This is due to unfair distribution of resources during the apartheid era. (Lester et al., 2009).Furthermore, township businesses operate in high traffic volume areas and in spaces of high population density, such as taxi ranks, bus stops and train stations, large malls and shopping centres, where infrastructure development is mostly non-existent or poorly developed. Small businesses may have the desire to easily access government and business development services at a one stop central spot, however, current infrastructure does not allow for this and would negate retainingpresentcompetitive and comparative advantages (Nqapela & Fakir, 2017).According to Scheba and Turok (2019), there is considerable policy interest in supporting township economies at present, with the aim of improving the business environment.It is nevertheless important to understand that the township economy will not mirror the established mainstream economy due to infrastructural, spatial and network separation and needs to develop on its own specific, and particular terms, having beeninhibited by the legacy of apartheid history and early transition neglect (Nqapela & Fakir, 2017).
Low income: For township entrepreneurs, local residents provide an obvious target market. Yetthis market includes a large proportion of people who are poor. They have limiteddisposable income and buy a predictable range of goods. InSouth Africa, small-scale production of these goods puts producers into directcompetition with the giants of the core economy in relation to price, packaging, brand-recognition and consumer habits, with brands holding strong sway. Often, small-scale producers cannot compete on these terms (National Treasury 2017). In many cases, rural income earned from family farming with no hired help, no mortgage and no off-farm income, can be classified the same as farm household income (Kym, Anderson, van der Mensbrugghe, 2013).As explained by Seo (2016) some rural income is earned from natural resources found in the surrounding areas. These include forest products, tree fruits, fuel wood, and fodder, along with timber, grass/thatch, wild medicine, as well as forest products such as fruits, nuts, plants, and resins, along with barks and fibers.
Lack of job opportunities: Township job opportunities include petty trading, handicrafts and cottage industries, simple processing, and artisan work, in addition to casual laboring, and employment locally and away through migration (Sida, 2004).The government of the day has not attempted to change the makeup of the township and rural areas. Despite slogans to reduce poverty, unemployment and inequality, townships have largely remained the same. Every day, a hopeless and desperate army of mostly young women and men roam the streets of townships without work (Voices360, 2019).
Lack of manufacturing activities: Manufacturing activities are notably limited, along with the jobs and business services often associated with their presence. Those that exist are rarely linked into value chains or markets outside the township (National Treasury 2017). While manufacturing may, to a limited degree, be attracted by cheap land in the townships where infrastructure and networks are in place, elsewhere in the townships the distinct lack of infrastructure, access to suppliers and modern distribution networks negate this potential income activity (McGaffin, et al.,2015). According to South Africa Insights (2020), large manufacturing companies in South Africa are struggling, with asack of demand for goods in South Africa, unreliable power supply from ESKOM and the continued use of imported products instead of locally manufactured goods are all contributingfactors dragging down the local manufacturing industry.
Land shortages: While pathways to formalization are an important part of township economic growth strategies, certain current features of townships mitigate against this, with landuse management arrangements posing a particular obstacle. Land-related processeswhich people have to navigateto obtain business compliance are fraught with rules are nightmarishlycomplex, incomprehensibleand illogical (National Treasury 2017). The great majority of township informal micro-enterprises do not comply with land management system requirements (Sustainable Livelihoods Foundation, 2017).Municipalities have an important role in liberating the spaces and places where township informal enterprises can and should be permitted to trade, as well as in creating a more favorable business environment (Charman, 2017).
Changing expenditure patterns: The low-income and shallow local market support mainly smaller enterprises and a limited number of large shopping centers, hence, retail activities benefit from changing consumer patterns but will also require deeper markets than those available in the township (McGaffin, et al., 2015). Moreover, in the last decade, spaza shop businesses, described as “Dedicated, signposted businesses with a range of foodstuffs and open five days per week or more” and seen as the predominant businesses within the ‘township economy,’ have undergone extensive change towards a new class of entrepreneurial traders – mostly foreign nationals (Petersen, et al., 2019). Nonetheless, a recent study by the Institute for Land, Policy and Agrarian studies (Petersen, et al., 2019) determined that of South Africa’s township microenterprises, approximately 54% trade in food or drink, with grocery retail businesses accounting for more than two-thirds of these; in the form of spaza and smaller ‘house shops’.”
The study was conducted in different townships in the KwaZulu–Natal province shows in Table 1. A comprehensive literature review was carried out and used as a source of questionnaire formulation. To obtain empirical data for this survey, 241 participants were asked to complete a questionnaire. A closed-ended questionnaire with 5-pointLikert scaled optionswas distributed to participants’ workplaces with the aid of research assistants. Respondents were afforded seven days to complete the questionnaire. Data were purely quantitative, and were analyzed through the use of the Statistical Package for Social Sciences (SPSS) (version 26.0), to test the significance of the results and later presented in figures.
| Table 1: Summary of Key Questions | |
| Research Area | Research Statement |
|---|---|
| Participant category | Please indicate your category from the following: Alternative response: Business owner; Municipal manager; Government service worker; Business private work; Community member |
| Type of business | Which type of business is mostly perceived as doing well in your area? Alternative response: Agriculture; Mining and quarrying; Manufacturing; Construction; Retail and motor trade and repair services; Wholesale trade commercial agents and allied services; Catering, accommodation and other trade; Transport, storage and communications; Finance and business services; Community, social and personal services |
| Contributing attributes | What do you think makes /contributes to the business success in your area? Alternative response: Size of the products’ potential market; Government business policy towards business environment; Financial support from relevant finance agencies; Proper infrastructure available to make the business prosper and grow; Lack of business-related skills and knowledge |
| Township attractions | What attracts people to visit your township: Alternative response: Historical places; Indigenous products; Local development in my township; Societal peace in my township; Potential market for various products in my township; Indigenous people are mostly attracting visitors in my township; Cultural activities in my township |
This section presents the results and discusses the findings obtained from the study’s questionnaire. The questionnaire was the primary tool used to collect data and was distributed to 241 respondents. The data collected from the responses was analyzed with SPSS version 26.0. The results will present the descriptive statistics in the form of graphs, cross-tabulations and other figures for the quantitative data that were collected. Inferential techniques included the use of correlations and chi square test values; which were interpreted using p-values.
In total, X questionnaires were dispatched and 241 were returned, which gave a Y% response rate. The research instrument consisted of six items, with a level of measurement at a nominal level shows in Table 2.
Question 2
| Table 2: This Question Summarizes The Characteristics Of The Respondents In Terms Of The Category To Which They Belong | |||
| Frequency | Percentage | ||
|---|---|---|---|
| Community number | 116 | 48.1 | |
| Government service worker | 39 | 16.2 | |
| Business private work | 34 | 14.1 | |
| Business owner | 29 | 12.0 | |
| Municipal manager | 12 | 5.0 | |
| Other | 11 | 4.6 | |
| Total | 241 | 100.0 | |
Approximately half of the sample (48.1%) were Community member with smaller and similar numbers (average = 14%) who were Government service workers, in Business private work or Business owners (p < 0.001). Two smaller categories (of approximately 4.8%) were identified as Municipal Managers or unspecified other.
The ratio of the respondents is in proportion to the general statistics of the research locations and is therefore representative.
Section Analysis
The section that follows analyses the scoring patterns of the respondents per variable per section.
The results are first presented using summarized percentages for the variables that constitute each section.
Results are then further analyzed according to the importance of the statements.
Question 3
| Table 3: Summarizes the Scoring Patterns | ||||||||||||
| No | Yes | Chi Square | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Count | Row N % | Count | Row N % | p-value | ||||||||
| Q3.1 | Agriculture | 185 | 76.8% | 56 | 23.2% | < 0.001 | ||||||
| Q3.2 | Mining and quarrying | 231 | 95.9% | 10 | 4.1% | < 0.001 | ||||||
| Q3.3 | Manufacturing | 234 | 97.1% | 7 | 2.9% | < 0.001 | ||||||
| Q3.4 | Construction | 214 | 88.8% | 27 | 11.2% | < 0.001 | ||||||
| Q3.5 | Retail and motor trade and repair services | 226 | 93.8% | 15 | 6.2% | < 0.001 | ||||||
| Q3.6 | Wholesale trade commercial agents and allied services | 203 | 84.2% | 38 | 15.8% | < 0.001 | ||||||
| Q3.7 | Catering, accommodation and other trade | 198 | 82.2% | 43 | 17.8% | < 0.001 | ||||||
| Q3.8 | Transport, storage and communications | 226 | 93.8% | 15 | 6.2% | < 0.001 | ||||||
| Q3.9 | Finance and business services | 240 | 99.6% | 1 | 0.4% | < 0.001 | ||||||
| Q3.10 | Community, social and personal services | 217 | 90.0% | 24 | 10.0% | < 0.001 | ||||||
| Q3.11 | Other | 237 | 98.3% | 4 | 1.7% | < 0.001 | ||||||
This section deals with the type of business that respondents perceive to be doing well in the area shows in Table 3.
The following patterns are observed:
- All of the statements show (significantly) higher levels of disagreement (No)
- The significance of the differences is tested and shown in the table.
The three predominant categories are Agriculture (23.2%), Wholesale trade commercial agents and allied services (15.8%) and Catering, accommodation and other trade (17.8%).
It is observed that Business owners, Municipal managers and Business private work, agreed on average (31.3%) that Agriculture is the predominant type of business.
With regard to Mining and quarrying, Government service workers (17.9%) were the highest number of respondents that identified this category of business as being predominant.
To determine whether the scoring patterns per statement were significantly different per option, a chi square test was done. The null hypothesis claims that similar numbers of respondents scored across each option for each statement (one statement at a time). The alternate hypothesis states there is a significant difference between the levels of agreement (Yes) and disagreement (No).
The results are shown in the Tables 4 & 5. The highlighted sig. values (p-values) are less than 0.05 (the level of significance), which implies that the distributions were not similar. That is, the differences between the way respondents scored (Yes, No) were significant.
Question 4
| Table 4: Results | ||||||||
| No | Yes | Chi Square | ||||||
|---|---|---|---|---|---|---|---|---|
| Count | Row N % | Count | Row N % | p-value | ||||
| Q4.1 | Size of the products potential market | 168 | 69.7% | 73 | 30.3% | < 0.001 | ||
| Q4.2 | Government business policy towards business environment | 187 | 77.6% | 54 | 22.4% | < 0.001 | ||
| Q4.3 | Financial support from relevant finance agencies | 194 | 80.5% | 47 | 19.5% | < 0.001 | ||
| Q4.4 | Proper infrastructure available make it the business to prosper and grow | 196 | 81.3% | 45 | 18.7% | < 0.001 | ||
| Q4.5 | Other | 230 | 95.4% | 11 | 4.6% | < 0.001 | ||
Note: That Municipal managers (41.7%) and Government service workers (38.5%) mostly agreed that the size of the potential market is the most important factor for business success.
Question 5
| Table 5: Results | ||||||||
| No | Yes | Chi Square | ||||||
|---|---|---|---|---|---|---|---|---|
| Count | Row N % | Count | Row N % | p-value | ||||
| Q5.1 | Political connections | 183 | 75.9% | 58 | 24.1% | < 0.001 | ||
| Q5.2 | High rate of unemployment impact on potential customers | 184 | 76.3% | 57 | 23.7% | < 0.001 | ||
| Q5.3 | Social support from local communities | 218 | 90.5% | 23 | 9.5% | < 0.001 | ||
| Q5.4 | Poor technology infrastructure | 229 | 95.0% | 12 | 5.0% | < 0.001 | ||
| Q5.5 | Poor national infrastructural development | 231 | 95.9% | 10 | 4.1% | < 0.001 | ||
| Q5.6 | Lack of professional services availability | 217 | 90.0% | 24 | 10.0% | < 0.001 | ||
| Q5.7 | Lack of business-related skills and knowledge | 197 | 81.7% | 44 | 18.3% | < 0.001 | ||
| Q5.8 | Other | 229 | 95.0% | 12 | 5.0% | < 0.001 | ||
Question 6
| Table 6: Discussion | |||||||||||||||
| No | Yes | Chi Square | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Count | Row N % | Count | Row N % | p-value | |||||||||||
| Q6.1 | Historical places | 212 | 88.0% | 29 | 12.0% | < 0.001 | |||||||||
| Q6.2 | Indigenous products | 222 | 92.1% | 19 | 7.9% | < 0.001 | |||||||||
| Q6.3 | Local development in my township | 191 | 79.3% | 50 | 20.7% | < 0.001 | |||||||||
| Q6.4 | Societal peace in my township | 213 | 88.4% | 28 | 11.6% | < 0.001 | |||||||||
| Q6.5 | Potential market for various products in my township | 191 | 79.3% | 50 | 20.7% | < 0.001 | |||||||||
| Q6.6 | Indigenous people are most attracting visitors in my township | 226 | 93.8% | 15 | 6.2% | < 0.001 | |||||||||
| Q6.7 | Cultural activities in my township | 209 | 86.7% | 32 | 13.3% | < 0.001 | |||||||||
| Q6.8 | Other | 227 | 94.2 | ||||||||||||
Cross-Tabulations
The traditional approach to reporting a result requires a statement of statistical significance. A p-valueis generated from a test statistic.A significant result is indicated by "p< 0.05". A second Chi square test was performed to determine whether there was a statistically significant relationship between the variables (rows vs columns) shows in Table 6.
The null hypothesis states there is no association between the two, while the alternate hypothesis indicates there is an association.
The table summarizes the results of the chi square tests. (SEE EXCEL SHEET – Detailed Statement by Statement). For example, line 11110: The p-value between “Poor national infrastructural development” and “Financial support from relevant finance agencies” is 0.027. This means there is a significant relationship between the variables highlighted in yellow. That is, the level of infrastructural development directly affects the nature / level of financial support.
It is seen that 78.4% of respondents who stated No for Poor Infrastructural Support also stated No for Financial Support from agencies.
All p-values more than 0.05 do not have a significant relationship.
Binary Logistic Regression
Logistic Regression is a classification algorithm used when the aim is to predict a binary categorical variable (for example, Yes / No), constructed on a set of independent variable(s).
In the Logistic Regression model, the log of odds of the dependent variable is modelled as a linear combination of the independent variables.
The dependent variable is “Proper infrastructure available make the business to prosper and grow”
The Nagelkerke R square values are high (0.797).
There is an increase in the percentage in the classification tables from 81.3% to 93.8% (after the introduction of the predictor variables) which implied a correct classification of the subjects where the predicted event was observed sows in Table 7.
| Table 7: The Impact of the Predictor Variables on the Dependent Variable | |||||||||||
| B | S.E. | Wald | df | Sig. | Exp(B) | 95% C.I.for EXP(B) | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||||||
| Agriculture | -2.734 | 1.672 | 2.673 | 1 | 0.102 | 0.065 | 0.002 | 1.722 | |||
| Mining and quarrying | 0.622 | 2.020 | 0.095 | 1 | 0.758 | 1.862 | 0.036 | 97.527 | |||
| Construction | -0.424 | 1.418 | 0.089 | 1 | 0.765 | 0.654 | 0.041 | 10.548 | |||
| Retail and motor trade and repair services | 0.044 | 1.737 | 0.001 | 1 | 0.980 | 1.045 | 0.035 | 31.465 | |||
| Wholesale trade commercial agents and allied services | -0.909 | 1.433 | 0.402 | 1 | 0.526 | 0.403 | 0.024 | 6.687 | |||
| Catering, accommodation and other trade | -1.290 | 1.427 | 0.817 | 1 | 0.366 | 0.275 | 0.017 | 4.511 | |||
| Transport, storage and communications | -2.676 | 1.729 | 2.395 | 1 | 0.122 | 0.069 | 0.002 | 2.040 | |||
| Finance and business services | -15.843 | 40192.970 | 0.000 | 1 | 1.000 | 0.000 | 0.000 | ||||
| Community, social and personal services | -0.916 | 1.452 | 0.399 | 1 | 0.528 | 0.400 | 0.023 | 6.882 | |||
| Size of the products potential market | -23.520 | 4092.090 | 0.000 | 1 | 0.995 | 0.000 | 0.000 | ||||
| Government business policy towards business environment | -6.432 | 1.601 | 16.138 | 1 | 0.000 | 0.002 | 0.000 | 0.037 | |||
| Financial support from relevant finance agencies | -23.131 | 4957.699 | 0.000 | 1 | 0.996 | 0.000 | 0.000 | ||||
| Political connections | 2.206 | 1.631 | 1.828 | 1 | 0.176 | 9.078 | 0.371 | 222.195 | |||
| Rate of unemployment impact on potential customers | -0.789 | 1.190 | 0.440 | 1 | 0.507 | 0.454 | 0.044 | 4.678 | |||
| Social support from local communities | -0.340 | 1.464 | 0.054 | 1 | 0.817 | 0.712 | 0.040 | 12.555 | |||
| Technology infrastructure | 3.542 | 2.122 | 2.788 | 1 | 0.095 | 34.547 | 0.540 | 2209.775 | |||
| National infrastructural development | -20.422 | 9877.550 | 0.000 | 1 | 0.998 | 0.000 | 0.000 | ||||
| Professional services availability | 3.357 | 2.015 | 2.775 | 1 | 0.096 | 28.693 | 0.553 | 1488.661 | |||
| Business-related skills and knowledge | 0.467 | 1.246 | 0.141 | 1 | 0.708 | 1.596 | 0.139 | 18.356 | |||
| Constant | 1.412 | 1.503 | 0.883 | 1 | 0.347 | 4.105 | |||||
Limitations: This study did not include other townships and other provinces. Therefore, the generalization of these results should be done with care. Due to the complexity of the South African geographical profile, further research needs to be done to cover more townships in other provinces.
Research implications: The findings of this study revealed that infrastructure development and financial support are the most critical factors for township businesses’ developmental growth and economic prosperity in the province of KwaZulu-Natal. Therefore, the practical implications of this study will benefit township entrepreneurs operating in the province, as well as potential entrepreneurs.
Conclusion and Recommendations of alternative entrevolutionizing township growth strategies
Based on the findings, this study concludes there are many challenges hindering the growth of KwaZulu-Natal townships’ economy and business prospects. These include poorinfrastructure, lack of financial support, small markets, and operating policies enforced by municipalities that affect land/space use.
As part of Entrevolutionzing Township economies, the impact of municipal policies that determine where, when and how micro-enterprises may operate, should be reshaped and redirected to acknowledge the contribution of township entrepreneurs and not simply to control or exclude them. Redress of institutional discrepancies between national, provincial and municipal objectives should be prioritized to free up new market places and spaces outside the township, while ensuring the township poor areprioritized in businesses operations in these contexts. In addition, while adherence to regulations needs to be monitored, this should not be done by authorities who have the power to extract tribute, it should instead be undertaken by technical specialists who can simultaneously advise on corrective action while allowing entrepreneurs to be trained in basic business management and thus be upskilled.
With many entrepreneurs running their businesses from home, the approach to land-use zoning at present is not logical, as townships consist of mixed business areas and should be recognized as such. In order to entrevolutionize the township economy, trading, whether from homes, backyards or street vergesshould be legitimized and respected, and municipal authorities should maximize the use of these informal trading area business activities without overly prescribing the manner in which the space is utilized.
With mobility beingessential to most businesses, diverse entrepreneurial forms of transport such as trolleys, push-carts and similar means should be accommodated bymunicipal authorities. Furthermore, the business day can be lengthened through the installation and maintenance of adequate street lighting, which will allow traders to focus on markets in the early morning and evening, when they are busiest. Through the supply and upkeep of infrastructure, entrepreneurs would be assisted in growing their businesses, specifically in areas where there isdense trading. With the intention to entrevolutionize the Township Economy, public services should allowadaptable and effortless use of facilities that reflect bothspatial requirements and business needs arranged and managed through aprocess of participation between municipalities, township entrepreneurs and SMME.
While there is a need to make land available for business expansion, township residents require title deeds to formalize market transitions and invest in property assets, while also qualifying them to deal with financial institutions. The lack of financial support also highlights a need for micro-credit to establish and grow township enterprises and part of the effort to entrevolutionize township businesses may be to actively support lending through established stokvels, enabling the lending of resources to members on terms that can be upheld contractually. It is further noted that many spaza shops are owned and run by foreigners, which creates its own problems, even while addressing a need within the township. It is suggested that another step in entrevolutionzing the Township economy’s spaza sector, could have government assistance offering stability by encouraging acceptance of the role of immigrant entrepreneurs and formalizing these enterprises, where reasonably possible, with immigrant entrepreneurs enabled to establish bank accounts.