Abstract
Purpose
This paper aims to report on the results of a study carried out to establish the contribution of business choice and location decision to the success of small and medium enterprises in an emerging economy like Uganda.
Design/methodology/approach
This study is cross-sectional and correlational. Data were collected through a questionnaire survey of 181 small and medium restaurants. The data were analyzed through correlation coefficients and hierarchical regression using statistical package for social sciences.
Findings
The findings reveal that both business choice and location decisions positively and significantly contribute to the success of small and medium enterprises. However, it was noted that more attention should be paid to location decision than business choice as determinants of SME success.
Originality/value
To the authors' knowledge, this is the first study to investigate the contribution of business choice and location decision to the success of SMEs using evidence from a developing African country like Uganda. Finally, this research offers practical contributions to managers and owners of SMEs who have to make strategic decisions for firm profitability, survival and growth in the competitive business arena.
Keywords
Citation
Kakooza, J., Tusiime, I., Namiyingo, S., Nabwami, R. and Basemera, M. (2023), "Business choice, location decision and success of small and medium enterprises in Uganda", Journal of Money and Business, Vol. 3 No. 1, pp. 108-121. https://doi.org/10.1108/JMB-08-2022-0041
Publisher
:Emerald Publishing Limited
Copyright © 2023, JohnBosco Kakooza, Immaculate Tusiime, Sophia Namiyingo, Ruth Nabwami and Mellan Basemera
License
Published in Journal of Money and Business. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Small and medium enterprises (SMEs) continue to play a vital role in the economic transformation of developing economies like Uganda. They stimulate income generation, private ownership and entrepreneurial skills and contribute significantly to domestic and exporting earnings of a country (Islam et al., 2011; Ngoma et al., 2017). In Uganda, SMEs contribute over 30% of gross domestic product (GDP) in the form of tax revenues, job creation and poverty reduction (Ngoma et al., 2017; Sejjaaka et al., 2015; World Bank, 2013). However, despite this significant contribution, studies on SMEs in Uganda reveal that 90% of SMEs do not live to see their first birthday and even those that survive beyond one year, over 40% do not witness their fifth birthday (Sejjaaka et al., 2015). Prior studies attribute the problem to poor working capital management such as poor planning, cash problems, low debt collection potentials and high operational costs (Orobia et al., 2013; Nyamao et al., 2012). Consequently, practicing and prospective business owners have to know that some SMEs grow and succeed, some stagnant while others decline and collapse after some time. So, what factors affect business success among SMEs? This study examines the contribution of business choice and location decision in the business success of SMEs in Uganda.
Although, prior studies document a number of success determinants of SMEs (Nyamao et al., 2012; Dabić et al., 2022; Ramadani et al., 2018). In addition, Alfoqahaa (2018) studied the critical success factors of SMEs in Palestine and found that brand reputation, excellence of customer of services and reliable delivery significantly influence SME success. In another study, Walker and Brown (2004) examined the success factors important to SMEs and found both financial and non-financial measures predicting business success. Foreman-peck et al. (2006) studied growth and profitability as measures of SMEs success and concluded that profits are necessary for survival and funding of SME growth but growth is not mandatory since some firms intentionally remain small. In this study, the centrality of business choice and location decisions has been explored, given the fact that locations and businesses differ in nature (Dana et al., 2018; Ramadani et al., 2018).
To the researchers' knowledge, no study has investigated the contribution of Business choice and location decision to business success using evidence from Uganda's SMEs. Although success of SMEs has been explored widely, we argue that gaps still exist in literature and the calls for further research are evident (Walker and Brown, 2004; Simpson et al., 2012; Alfoqahaa, 2018; DiPietro, 2017; Shama and Upneja, 2005; Shephard and Williams, 2015; Winnaar and Frances Scholtz, 2019). In this study, we attempt to respond to the calls of Shephard and Williams (2015) on decision-making of independent entrepreneurs and those acting entrepreneurially within the established organizations, and Rahman and Kabir (2019) on location choices of service SMEs as key determinants of success of SMEs. This study also contributes to the current literature by demonstrating aspects like business choice and location decisions as salient predictors of the success of SMEs.
The purpose of this paper was achieved through a questionnaire survey of 181 Small and Medium Restaurants in Uganda. The results suggested that both business choice and location decision and business success are positively and significantly associated. This study results provide initial empirical evidence on the contribution of business choice and location decision to the success of SMEs using evidence from Uganda. This study's results are important to practitioners, academicians, policy makers and the community. This study contributes to the existing literature by expanding on the determinants of business success of SMEs. Given the critical role of SMEs in developing economies like Uganda, we suggest that managers and policy makers create a conducive environment for SMEs to succeed. Such as proving tax subsidies for businesses that are located in less prime areas. Owners of SMEs can use this study results to understand that businesses located in prime areas are more likely to succeed than those located in less prime areas in the event that there are no subsidies. Similarly, the choice of the business is key for its success in an environment of perfect competition where forces of demand and supply determine prices.
The rest of the paper is organized as follows. Section 2 is the literature review and hypothesis development, followed by Section 3, the methodology section and Sections 4 and 5, the results and discussion section. Section 6 is the summary and conclusion.
2. Literature review
2.1 Theoretical framework
In this study, the Location of Industries Theory (LIT) (Weber, 1929) and the rational choice theory have been advanced to explain SMEs' success. According to LIT (Weber, 1929), the ability of firms to locate in areas offering the agglomeration of advantages may induce competitive advantage through easy access to resources and cuts in production costs, respectively. Small firms in a cluster location are able to benefit from the synergy in their business environment and do not necessarily have to own all the resources they need before they have access to them (Lechner and Leyronas, 2012; Felzensztein et al., 2019). SMEs can derive three core benefits of complementary competencies, shared knowledge and collaboration with other enterprises in utilizing common resources due to their location (Banwo et al., 2017). Weber (1929) further based the LIT on the “least cost principle.” Accordingly, industrial location is based on minimization of labor costs, market accessibility and transport costs. Reduced cost of production allows firms to reduce prices and compete favorably in the market thus the success of the SME. Capello (2014), in his study of firm location, posited that the positioning of business firms in a specific area is influenced by the agglomeration of direct and indirect benefits derived from that location. These in return enhance the success of SMEs.
The rational choice theory (Hernstein, 1990; Levin and Milgrom, 2004) assumes that choices individuals make aim at maximizing total utility. It also emphasizes that individuals are rational actors who make rational choices aimed at maximizing rewards and returns. Individuals use logical calculations to make rational choices and achieve results that are aligned with their own personal goals. According to Winnaar and Frances Scholtz (2019), the theory postulates that rational choice can be broken down into steps which are identifying the problem, generating alternatives, evaluating alternatives, choosing an alternative, implementing the decision and evaluating the decision's effectiveness. Shepard et al. (2015) posited that individuals are heterogeneous in their beliefs and motivations for entrepreneurial entry decisions and opportunities. Winnaar and Frances Scholtz (2019) added that maximizing utility is the ultimate goal of all rational decision-makers. Such decision-makers seek thorough and complete knowledge of the problem, its alternatives and the consequences of each option in order to decide. Thus all choices made have a degree of intentionality to achieve set goals (success).
2.2 Business choice and success of SMEs
According to Levin and Milgrom (2004), rational choice is “the process of determining what options are available and then choosing the most preferred one according to some consistent criterion.” This study views business choice as the process of determining what business options are available and then choosing the most preferred one by following a given criterion. The choice of business a prospective entrepreneur should undertake is a complex combination of motives, skills and ambitions with varying types and levels of risks (Louviere and Meyer, 2015; Simpson et al., 2012). Business choice was measured in terms of owner–manager and initial investment (resources) (Simpson et al., 2012). Blackburn et al. (2013) indicated that owner-manager personal qualities refer to an individual's personal attributes that include age, gender, knowledge and skills and values while initial investment (resources) includes financial resources and non-financial resources (Kakooza et al., 2015).
Studies linking business choice and success of SMEs are scarce. Birley and Westhead (1994) indicate that a combination of attributes and skills are required for the entrepreneur to be successful such as being decisive, being goal orientated, flexible, pragmatic, determined, hardworking and self-confident. Liguori et al. (2020) posited that the owner–manager's mental and technical abilities, human relations skills, high need for achievement and creativity and innovation are pertinent to the success of an entrepreneur. Sadler–Smith et al. (2003) found a positive association between owner–manager entrepreneurial style and business performance as measured by sales growth. Simpson et al. (2012) found that prior knowledge possessed by the owner-manager in the form of training, experience or formal education is a prerequisite for the success of a chosen enterprise. The implications of the above findings are that once the business choice selected matches the owner's managerial personal values and resources required to manage the enterprise, it is expected that the success of such an enterprise will be achieved. We, therefore, hypothesized that:
Business choice is positively related to the success of SMEs.
2.3 Location decisions and success of SMEs
A large number of techniques to aid location decision-making have been studied, developed and advocated for (Zimmerer and Scarborough, 2008; Rahman and Kabir, 2019). Prior studies acknowledge that SME location decision is influenced by a combination of factors; these could be soft or hard factors, internal or external factors (Dana et al., 2018; Felzensztein et al., 2019; Ramadani et al., 2018). Scarborough (2010) asserts that the location decision of a firm has far-reaching and often long-lasting effects on SMEs' competitiveness. SMEs whose locations are chosen with due consideration of their critical success factors are able to establish a competitive advantage over rivals in haphazard locations (Teece and Pisano, 1994). Rahman and Kabir (2019) concluded that a suitable location enhances a firm's market competitiveness in the form of increased production capacity, sustainable profit margin and reduced costs while an unsuitable location curtails a firm's competitiveness. Studies on the location decision have been common but focused on the location of international firms (MacCarthy and Atthirawong, 2003) and retail location decision (Kwong‐yin Fock, Henry, 2001; Hernández and Bennison, 2000). There is a growing appreciation that there are prominent differences in the contributing factors that determine the location decision of an enterprise and thus its success.
Studies linking location decision and success of SMEs are limited. The performance of SMEs has been linked to working capital management (WCM) (Aldubhani et al., 2022), Intellectual Capital (Mollah and Rouf, 2022) and capital structure (Riaz et al., 2022). In his book, Logistics and Supply Chain Management, Christopher (1994) posited that location decision is a fundamental factor of sustainable firm profitability. In addition, Head et al. (1995) found that location proximity generates positive externalities to the firm. In another study, Kozak and Rimmington (1998) concluded that the type and location of the SMEs are interrelated. MacCarthy and Atthirawong (2003) in their Delphi study of locating international operations posited that the determining factors are market, labour costs and competition for locating an SME. Chand and Katou (2007) found that labour is positively related to the performance of an enterprise. Jackson et al. (2008) suggested that a viable location stimulates a successful investment. Further, Freeman and Styles (2014) reported that location-specific advantages positively enhance export performance outcomes. Given the fact that there is minimal literature on the association between location decision and success of SMEs, we try to contribute to the literature by establishing whether location decision can lead to the success of SMEs by hypothesizing that:
Location decision is positively related to the success of SMEs.
3. Methodology
3.1 Design, population and sample
This study followed a cross-sectional research design and a quantitative research approach. The study population was 337 small and medium restaurants drawn from Kampala-district Uganda, Kampala Capital City Authority (KCCA, 2019). A total sample of 181 local restaurants was chosen for this study using Krejcie and Morgan (1970) sample selection approach. Primary data were captured using self-administered questionnaires. This study used a simple random sampling technique to select respondent firms and 370 useable questionnaires were received from 143 SMEs with a response rate of 79%. In total, 21% of respondent information was not considered due to response errors which rendered them unreliable and invalid for use. The results in Table 1 indicate that out of the 370 respondents, 185 were male and 185 were female. The majority of the respondents were 30 years and above, implying that most restaurant business are managed by mature people and had a working experience of more than five years, and the majority of these had a diploma and degree level of education, implying that they had adequate skills and training required to choose and run a restaurant business.
3.2 The questionnaire and variables measurement
The data was collected using close-ended questionnaires (Saunders et al., 2007). A review of the literature was done on business choice, location decision and success of SMEs. The dependent variable for this study is the success of SMEs, which is operationalized in terms of profitability and growth (foreman-Peck et al., 2006) the independent variables for this study are business choice and location decisions. Business choice was operationalized in terms of owner/manager personal values and initial investment/resources (Shephard and Williams, 2015; Attahir, 1995; Walker and Brown, 2004), and location decision was operationalized in terms of competition, labour and market (Rahman and Kabir, 2019; Balunywa, 2006; MacCarthy and Atthirawong, 2003; Attahir, 1995).
3.3 Validity and reliability
The validity of instrument items was obtained using the Content Validity Index (CVI) and the questionnaire items were modified based on expert advice. The reliability of the questionnaire was ascertained using Cronbach's coefficient alpha to ensure the internal consistency of the scales used to measure the variables (Cronbach, 1951) and the rule of thumb is that Cronbach's alpha should be at least 0.7 to be acceptable. An alpha coefficient of above 0.7 for individual test variables was obtained meaning the instrument was reliable (Nunnally, 1979). Factor analysis was utilized to examine the underlying factors responsible for a majority of the covariance amongst the measures as shown in Tables 2 and 3.
4. Results
4.1 Descriptive statistics
Table 4, presents the descriptive statistics of the study variables. Success of SMEs has a minimum score of 1, maximum score of 5, mean of 3.52 and a standard deviation of 1.06. The results also show that the mean for business choice is 3.15 and a standard deviation of 1.37. For location decision, the mean is 3.44 and the standard deviation is 1.19. The standard deviations for all variables are small as compared to the means, implying that the calculated means are a good representation of the observed data (Field, 2009).
4.1.1 Correlation analysis results
The correlations analysis results are presented in Table 5 following the guidelines of Field (2009). The correlation results show a positive significant relationship between business choice and success of SMEs (r = 0.259, p < 0.05), supporting H1. This means that a positive change in business choice will lead to a positive change in success of SMEs. Further results indicate a positive and significant relationship between location decision and success of SMEs (r = 0.465, p < 0.05); this means that a favorable business location is associated with high levels of success of an SME, therefore H2 is supported. Therefore, preliminarily, H1 and H2 are supported. In terms of control variables, there is a relationship between gender, age and success of SMEs is not significant. Education is positively and significantly associated with success of SMES (r = 0.132, p < 0.05).
4.2 Regression analysis results
We carried out a hierarchical regression analysis to further substantiate our hypothesis after obtaining preliminary results from the bivariate correlations between the independent and the dependent variables. Regression analysis was used because it is powerful in testing which independent variable contributes more to the variances in the dependent variable and it also indicates the incremental power of an additional independent variable to the already existing variable(s) in explaining the dependent variable (Sekaran, 2003; Field, 2009).
In Model 1, control variables were not significant. This means that the control variables do not confound the results of testing the relationship between the study variables and thus the models are highly credible. In Model 2, business choice was entered and found significant (standardized β = 0.251) and contributes 5.8% of the variation in success of SMEs. In Model 3, location decision was entered and found significant (standardized β = 0.473) and location decision accounts for 14.9% of the variation in success of SMEs. The overall model is statistically significant (sig = 0.000) with two predictor variables (business Choice and location decision) accounting for 21.4% of the variance in success of SMEs (Table 6). In terms of hypothesis testing, H1 and H2 are confirmed.
5. Discussion
The major purpose of this paper was to reveal that business choice selection and selection of its location were important explanatory variables in the success of SMEs. The results reveal that both business choice and location decision positively and significantly contribute to the success of SMEs which lends support to H1 and H2. This means that entrepreneurs who carefully choose businesses to undertake in line with their owner–manager personality and their available initial investment resources have a strong possibility of succeeding in their SMEs. It also implies that entrepreneurs who locate their SMEs after a thorough analysis of the competition, market and labour availability in the area have greater potential for success.
From the practical point of view, SMEs in Uganda usually have limited initial resources for investment, therefore, understanding factors critical to their success is of paramount importance. With regard to location decision, the results indicate that Ugandan SMEs in strategic locations have a competitive advantage over their rivals. Location can lead a firm to the desired success since it provides continued access to the market, affordable and plenty labour supply and customer convenience is also guaranteed (Teece and Pisano, 1994). In addition, well-located SMEs can generate cash flows which are pertinent to their survival. The present study findings agree with those of previous scholars; for example, Teece and Pisano (1994) argued that location is a non-tradable asset with the potential of difficult-to-replicate advantages such as superior convenience, reduced competition and abundant labour supply. All these provide the required ambience for the success of an SME. The present study also agrees with Chand and Katou (2007), who found that labour is positively related to the performance of an enterprise.
The present study findings reveal that business choice contributes to success of SMEs. This, therefore, indicates that the level of initial investment influences which business choice you should engage in and which ones to avoid. It also reflects that owner–managers personality traits should be critically examined before entering into a given cluster of SMEs. For example, the traits required for a restaurant business may differ from those deemed necessary for retailing and hairdressing. This is in line with Sadler–Smith et al., (2003), who found positive association between owner–manager entrepreneurial style and business performance as measured by sales growth and profitability. The findings also confirm the LIT (Weber, 1929) which assumes that firms that locate in areas composed of an agglomeration of advantages are able to gain competitive advantage and the rational choice theory which assumes that individuals are rational actors who make rational choices that maximize rewards and returns. The findings are consistent with Teece and Pisano (1994), who postulated that success factors should remain relevant, difficult to copy, unique and difficult to imitate by competitors so as to give the firm a sustainable competitive advantage. Therefore, this study advances the argument that business choice and location decision are significant predictors of success of SMEs that need thorough examination and analysis before starting a business. Our conclusion is that business choice and location decision of a business be given adequate attention in order to foster success of SMEs so as to reap the benefits they yield to both developed and developing economies. Miscellaneous.
6. Summary and conclusion
This study's purpose was to examine the relationship between business choice, location decision and business success of SMEs in Uganda. The study objective was achieved through a questionnaire survey of 181 SME restaurants. The results revealed that business choice and location decisions significantly contribute to the success of SMEs, however, the location decision predicts this trend more than does business choice.
This study has several contributions to the academic community, practitioners and policy makers. To the academic community, this study contributes to the literature about success of SMEs in sub-Saharan African countries like Uganda which is still scanty and limited. This study also contributes to the literature by providing an initial empirical evidence on the association between business choice, location decision and success of SMEs. It is also important to note that managers handle the location decision carefully since it positively influences the profitability and growth of the business for a long time. In addition, business practitioners need to scrutinize the profit potentials and growth abilities of the businesses they choose to undertake. Policy makers at various level have to promote the strategic location of restaurants for convenience and accessibility of those in need of their services.
A few facets limit the scope of this study. The study used hierarchical regression, however, it is prone to problems associated with sampling error, this was minimized by our rigorous interface with the data. Results further indicated that the study variables of business choice and location decisions predict only 21.4% of the variation in SMEs' success in Uganda's restaurant industry. Future research may focus on other factors that explain the remaining 78.6% SMEs success factors. This study focused on SMEs in one developing country, Uganda, in particular, whose market segments are poorly organized. This may not be representative of all developing countries. This necessitates more research on the same variables but in a different developing country. Empirical findings also revealed that limited studies have been conducted into the concept of business choice and how it is done; future research may focus on this gap.
Respondents' characteristics
| Background information | Frequency | Percentage |
|---|---|---|
| Gender | ||
| Male | 185 | 50 |
| Female | 185 | 50 |
| Total | 370 | 100 |
| Age of the Respondent | ||
| 18–24 years | 39 | 11 |
| 25–29 years | 108 | 29 |
| 30–34 years | 90 | 24 |
| 35–39 years | 80 | 22 |
| Above 40 years | 53 | 14 |
| Total | 370 | 100 |
| Level of education | ||
| No education | 26 | 7 |
| Certificate | 85 | 23 |
| Diploma | 121 | 33 |
| Degree | 116 | 31 |
| Masters | 22 | 6 |
| Total | 370 | 100 |
| Marital Status | ||
| single | 106 | 29 |
| married | 241 | 65 |
| Divorced | 11 | 3 |
| Widowed | 12 | 3 |
| Total | 370 | 100 |
| Experience | ||
| Less than 1 year | 17 | 5 |
| 1–4 years | 173 | 47 |
| 5–8 years | 115 | 31 |
| Above 8 years | 65 | 18 |
| Total | 370 | 100 |
Source(s): Primary data
Rotated component matrix for business choice
| Component | ||
|---|---|---|
| Initial investment | Owner/manager personal values | |
| Easy access to startup capital | 0.816 | |
| Timely acquisition of startup capital | 0.791 | |
| Presence of adequate capital to start a hotel | 0.732 | |
| Timely acquisition of startup capital while giving up as little control as possible | 0.668 | |
| Government financial incentives in starting up hotel business | 0.502 | |
| Hotel owners tendency to become rich | 0.673 | |
| Interest in hotel business | 0.639 | |
| Experience in hotel business management | 0.636 | |
| Family background in hotel management | 0.491 | |
| Hotel business a modern trend | 0.449 | |
| Hotel owner considered heroes | 0.421 | |
| Eigen values | 26.37 | 14.40 |
| Percentage of variance | 26% | 14% |
| Cumulative % age | 40% | |
| K.M.O | 0.703 | |
| Chi-square | 1029.620 | |
| Degree of freedom | 66 | |
| Statistical significance | 0.000 | |
Source(s): Primary data
Rotated component matrix for location decisions
| Component | |||
|---|---|---|---|
| Market | Competition | Labour | |
| Site of location is easily visible to customers | 0.662 | ||
| Nearness to needed hotel supplies | 0.636 | ||
| Site gives room for expansion of hotel | 0.634 | ||
| Situated in high customer traffic levels | 0.586 | ||
| Nearness to sites | 0.584 | ||
| Presence of large population in the areas | 0.578 | ||
| Situated near appropriate infrastructure | 0.519 | ||
| labour turnover is very low | |||
| Only offering hotel services in the area | 0.724 | ||
| No other hotel offers our services | 0.637 | ||
| Presence of limited number of hotels in the area | 0.595 | ||
| Limited potential for intense competition in the area | 0.586 | ||
| Labour unions are tolerant | 0.535 | ||
| The wage rates are not very high | 0.467 | ||
| labour force in hotel sector is growing | 0.586 | ||
| Workers are passionate about their jobs | 0.561 | ||
| Need to tap into the marketing intermediaries of other hotels | 0.536 | ||
| Workers are readily available | 0.505 | ||
| Desire to be aware of what other hotels are doing | 0.491 | ||
| Workers have positive attitude towards their work | 0.404 | ||
| Eigen values | 14.032 | 13.463 | 8.862 |
| Percentage of variance | 14% | 13% | 9% |
| Cumulative %age | 14% | 27% | 36% |
| K.M.O | 0.760 | ||
| Chi-square | 2833.840 | ||
| Degree of freedom | 351 | ||
| Statistical significance | 0.000 | ||
Source(s): Primary data
Descriptive statistics
| N | Minimum | Maximum | Mean | SD | Skewness | Kurtosis | |||
|---|---|---|---|---|---|---|---|---|---|
| Variable | Statistic | Statistic | Statistic | Statistic | Statistic | Statistic | SE | Statistic | SE |
| SME success | 370 | 1 | 5 | 3.52 | 1.055 | −0.782 | 0.127 | −0.239 | 0.253 |
| Location decision | 370 | 1 | 5 | 3.44 | 1.186 | −0.504 | 0.127 | −0.887 | 0.253 |
| Business choice | 370 | 1 | 5 | 3.15 | 1.368 | −0.419 | 0.127 | −1.249 | 0.253 |
| Sex of the respondent | 370 | 1 | 2 | 1.5 | 0.501 | 0 | 0.127 | −2.011 | 0.253 |
| Age of the respondent | 370 | 1 | 5 | 3 | 1.228 | 0.124 | 0.127 | −1.011 | 0.253 |
| Experience | 370 | 1 | 4 | 2.62 | 0.826 | 0.322 | 0.127 | −0.761 | 0.253 |
Source(s): Primary data
Of correlation results
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Enterprise success (1) | 1 | ||||||||||
| Business choice (2) | 0.259** | 1 | |||||||||
| Owner-manager personal value(3) | 0.165** | 0.844** | 1 | ||||||||
| Initial Invest (4) | 0.265** | 0.784** | 0.329** | 1 | |||||||
| Business Location (5) | 0.465** | 0.520** | 0.394** | 0.460** | 1 | ||||||
| Market (6) | 0.374** | 0.390** | 0.330** | 0.305** | 0.748** | 1 | |||||
| Competition (7) | 0.285** | 0.336** | 0.251** | 0.302** | 0.727** | 0.404** | 1 | ||||
| Labour (8) | 0.351** | 0.406** | 0.276** | 0.395** | 0.719** | 0.219** | 0.297** | 1 | |||
| Gender (9) | 0.004 | −0.110* | −0.102* | −0.076 | −0.036 | −0.005 | −0.080 | −0.007 | 1 | ||
| Age (10) | 0.015 | 0.179** | 0.238** | 0.040 | −0.136** | −0.067 | −0.222** | −0.036 | −0.093 | 1 | |
| Education | 0.132* | 0.227** | 0.168** | 0.205** | 0.189** | 0.175** | 0.067 | 0.158** | −0.097 | 0.116* | 1 |
Note(s): *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed)
Source(s): Primary data
Hierarchical regression analysis
| Model 1 | Model 2 | Model 3 | VIF | Tolerance | |
|---|---|---|---|---|---|
| Constant | 33.767 | 26.181 | 7.489 | ||
| Gender | 0.017 | 0.036 | 0.031 | ||
| Education | 0.133 | 0.082 | 0.037 | ||
| Age | 0.001 | −0.036 | 0.079 | ||
| Business choice | 0.251 | −0.006 | 1.531 | 0.653 | |
| Business Location | 0.473 | 1.500 | 0.667 | ||
| F | 2.182 | 7.446 | 21.12 | ||
| R | 0.133 | 0.275 | 0.474 | ||
| R2 | 0.018 | 0.075 | 0.225 | ||
| Adjusted R2 | 0.010 | 0.065 | 0.214 | ||
| R2 Change | 0.018 | 0.058 | 0.149 | ||
| Sig.F change | 0.090 | 0.000 | 0.000 | ||
| Durbin Watson | 1.613 |
Source(s): Primary data
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Further reading
Ahmed, A. and Nwankwo, S. (2013), “Entrepreneurship development in Africa: an overview”, World Journal of Entrepreneurship, Management and Sustainable Development, Vol. 9 Nos 2/3, pp. 82-86.
Bruderl, J. and Preisendorfer, P. (1998), “Network support and the success of newly founded businesses”, Small Business Economics, Vol. 10 No. 2, pp. 213-235.
Dana, L.P. and Dana, T.E. (2005), “Expanding the scope of methodologies used in entrepreneurship research”, International Journal Entrepreneurship and Small Business, Vol. 2 No. 1, pp. 79-88, doi: 10.1504/ijesb.2005.006071.
Kwong‐yin Fock, Henry (2001), “Retail outlet location decision maker – franchisor or franchisee?”, Marketing Intelligence and Planning, Vol. 19 No. 3, pp. 171-179, doi: 10.1108/02634500110391717.
Acknowledgements
The authors acknowledge with gratitude the financial and moral support received from Makerere University Business School under the Faculty of Entrepreneurship and Business Administration research funding.