Determinants of tourism small and medium enterprises financial performance

ABSTRACT

This study develops and tests a structural model that incorporates the determinants of SME financial performance in Mauritius. Data were collected from 384 tourism SME owners using a structured questionnaire. The results indicate that managerial capability has a significant positive effect on SME performance and is in turn influenced by managers’ autonomy and competence. The study does find a significant relationship between innovation capability and SME performance. Given the socio-economic importance of SMEs to the Mauritian economy, the results provide crucial information to government and policy-makers that can used to develop macro-economic policies that increase their contribution to the socio-economic development of the country. For entrepreneurs, the study provides insights on areas of interventions that can lead to an improvement in the financial performance of their organisations. Despite the study limitations, it contributes to a theoretical understanding of the determinants of financial performance in African economies.

KEYWORDS:

• Small and medium enterprises
• financial performance
• Africa
• Mauritius

1. Introduction

Small and medium enterprises (SMEs) are important for economic growth and contribute to tourism development in an economy (Rogerson 2004a, 2004b, 2005, 2006, 2008; Pillay & Rogerson 2013). They are formed out of existing opportunities and help in satisfying tourism demand and filling the production gaps in the market. For developing countries, SMEs hold particular prominence as they help nurture a culture of entrepreneurship (Kirsten & Rogerson 2002; Huarng & Hui-Kuang Yu 2011). The promotion of entrepreneurial attitude and abilities is also believed to make a positive contribution to poverty reduction. Furthermore, SMEs help reinforce industrial relationships and make use of resources productively and efficiently (Rogerson 2007, 2012). These factors together allow the country to be less reliant on overseas help (Peberdy & Rogerson 2000; Todaro & Smith 2012). Thus, the development of SMEs in a country and economic growth is deeply intertwined (Rogerson 2010). However, in developing countries, SMEs often struggle to sustain, especially during constantly fluctuating economic conditions. Furthermore, the future of an SME relies largely on the entrepreneur. All important decisions, including setting the business direction, its long term strategy, its tactical choices to reach the set destination are all made by that individual (Masurel & Nijkamp 2004). The quality of those decisions often depends on several factors and individual traits of the entrepreneur including technical know-how, past experiences and education level (Onkelinx et al. 2016).

Various studies have been carried out by researchers and policy-makers alike on the determinants of the financial performance of SMEs (Kober et al. 2012; Saunila et al. 2014; Ogunyomi & Bruning 2016). However, most of those studies have been carried out in developed economies and those outside the African region. The latter’s specific socio-economic and political characteristics that influence SME development are different from those of industrialised countries (Rogerson 2000; Visser & Rogerson 2004; Rogerson & Rogerson 2011). Like in several other African countries, SMEs make an important contribution to the economic development of Mauritius. For example, the share of SMEs in gross domestic product and total employment is currently estimated to be around 40% and 54% respectively. The ten-year master plan for the SME sector in Mauritius aims at increasing SME’s contribution to gross domestic product and total employment to 52% and 64% respectively (Ministry of Business, Enterprise and Cooperatives, 2017). Most SMEs operate in tourism and related sectors such as accommodation, tour operations, entertainment, ground transportation, and food services. However, despite their current and anticipated economic contribution to the Mauritian economy, research on this sector is clearing lacking and little is known about their financial performance and its determinants. At present, policies to support SMEs seem to be implemented on an ad-hoc basis, without a proper understanding of the factors influencing their financial performance. In an attempt to contribute to the very limited research on SME performance in Mauritius, this study develops and tests a structural model that incorporates a number of factors that are likely to influence the financial performance of SMEs in the economy.

2. Theoretical background

A common way to assess SME performance quantitatively is through their financial performance. Financial performance measures allow an organisation to assess whether its overall strategy and operations are effective in improving the bottom-line. These measures traditionally consist of evaluations of profitability, growth, shareholder value, and return on investment (Kaplan & Norton 1992). In some cases, both financial and marketing performance is treated as a singular unit of measure for performance (Weerawardena 2003). Albeit, they can and have also been treated as two distinct units of measure for total performance (Vorhies & Morgan 2005). Moreover, a third method also exists where both measures are treated as distinct constructs for performance (Hooley et al. 2005).

3. Determinants of SME performance

3.1. Management capability

Management capability of SMEs as a determinant of financial performance, is well documented in existing literature, with evidence highlighting its importance in the process and success of innovation within the organisation (Pfirrmann 1995; Soderquist et al. 1997; Cobbenhagen 2000). Existing research posits that management and innovation capability are closely linked, such that usually the former precedes the latter (Hooley et al. 2005). Furthermore, findings from empirical research lend further support to the idea that superior management capability will usually create conditions ideal to optimise innovation capability. A significant relationship between the two has been observed in various studies (Trott 1998; Tidd & Bessant 2013).

3.2. Innovation capability

Innovation can be defined as a process within an organisation to adopt change. The changes can be in terms of implementation of a new process, policy, or in the ways of doing things inside the organisation (Damanpour 1987; Garcia & Calantone 2002). Innovation capability adds value to an organisation by always being willing to adopt changes through the use of knowledge (Hsu et al. 2007; Hult et al. 2004). When studying performance, innovation cannot be ignored. Over the years, it has received significant attention and is perceived as extremely important for SMEs to develop a competitive edge, often through its contribution to marketing performance (Han et al. 1998; Hooley et al. 2005). Hence innovation is regarded as a key determinant of marketing performance. Moreover, innovation has been shown to have a significant role in enhancing the overall performance of an organisation (Weerawardena 2003; Hult et al. 2004; Weerawardena & O’Cass 2004; Weerawardena et al. 2006). The same has been observed in the Chinese context when comparing SME innovation and large enterprise innovation as well – Innovation has been observed to play a major role (Li & Mitchell 2009).

In existing literature, there have been various attempts to classify innovation. Generally, innovation has been classified into three categories: service/product innovation, product method innovation, and market innovation (Jenssen & Randøy 2006). Another approach was to split innovation capability into four distinct dimensions referred to as production innovation, process innovation, position innovation and paradigm innovation (Tidd & Bessant 2013). Due to the rapid changing nature of technology, technological innovations have also been subject to much attention by academics (Teece 1986; Damanpour 1987; Utterback 1994; Tuominen & Hyvönen 2004; Lau & Lo 2019).

3.3. Autonomy

Management scholars have long recognised that reliance on a centralised strategic planning is insufficient and may be detrimental to organisational performance (Andersen 2000). Managers’ ability to make independent decisions is beneficial for businesses operating in a dynamic environment. In an entrepreneurial context, ‘independent spirit and freedom of action’ is necessary to develop new ventures and for value creation (Lumpkin et al. 2009, 47). Autonomy provides managers the freedom and flexibility to develop and enact entrepreneurial initiatives. Autonomy can be defined as the extent to which managers feel that they have enough freedom and flexibility to act within a firm (Pratono et al. 2018). Under such conditions, entrepreneurial initiatives from individuals with the firm flourishes (Johansson et al. 2015). Past findings have identified autonomy as a key component in the creation of value within enterprises (Lumpkin et al. 2009). The presence of autonomy can bring benefits such as better team working, originality and encourage participation (Kakar 2018). Finally, autonomy has also been empirically found to have a significant contribution to the performance level of SMEs (Pratono et al. 2018). Andersen (2000) also demonstrates a positive influence of autonomous actions on corporate performance.

3.4. Competencies

Competencies are the underlying characteristics such as generic and specific knowledge, motives, traits, self-images, social roles, and skills that influence the financial sustainability of SMEs (Li 2009). It is defined as an individual traits such as knowledge, skills and/or abilities need to perform a particular job (Baum et al. 2001) and includes strategic, conceptual, opportunity, organising, relationship, technical and personal attributes (Ahmad & Seet 2009; Ahmad et al. 2010). Strategic competency consists of thinking which reflects the ability of the leader to develop future vision and take action which necessitates them to think beyond day-to-day operations (Stonehouse & Pemberton 2002; Ahmad et al. 2010). Such a vision helps entrepreneurs to focus their actions and decisions more strategically which in turn provides firms advantages over their competitors. These strategies link firm resources and their ability to gain competitive advantage to overcome organisational uncertainty (Parnell et al. 2000). Operating in a dynamic environment often results in misfit between firm strategies and external demand which in turn force organisations to change their strategy and business structure when required. Consequently, the ability to make strategic change helps entrepreneurs to adapt and adjust the business operations to meet the current demand in the industry.

The ability to think analytically and to cope with uncertainty depends heavily on conceptual abilities (Bird & Beechler 1995). Conceptual competency reflects the conceptual capability of entrepreneurs such analysing, problem solving, decision-making, innovating and risk taking (Ahmad et al. 2010; Man et al. 2008). Conceptual competency includes the mental ability to coordinate all of the organisation’s interests and activities (Chandler & Jansen 1992). Being creative, innovative and flexible especially in handling opportunities, risks and uncertainties show the important capability which allow entrepreneurs to make a difference (Thompson 1999). Entrepreneurs, especially those operating in SMEs, face various situations where they need to make quick decisions, therefore having the abilities to carry out high level of conceptual activities are vital for the survival and success of their business (Ahmad et al. 2010). Opportunity competency relates to the ability of an entrepreneur to recognise and take advantage of opportunities. Recognising high quality opportunities triggers the creation of organisations and to embrace the various risks needed to turn the opportunities into profitable outcome. The readiness to seize relevant opportunities is a necessary competency for growing companies (Snell & Lau 1994; Choi & Shepherd 2004).

Relationship competency refers to an entrepreneur’s ability to maintain good relationships with other individuals and organisations so as to be able to have access to information and data (Ahmad et al. 2010). This in line with resource dependency theory, suggesting that entrepreneurs use their social relations to get the resources they need to launch a business (Barringer & Harrison 2000; Jenssen 2001). Networks are essential for small firms to obtain advice and support from lawyers, accountants and consultants (Duchesneau & Gartner 1990; Ramsden & Bennett 2005) as well as government bodies, research and training institutes and even suppliers and customers (Ritter & Gemünden 2004). Some studies validate a positive relationship between managers’ competency and performance (Russell 2001; Levenson et al. 2006). In another study, Junges et al. (2015) find innovation competency to influence performance of firms in the information technology sector.

4. Methodology

4.1. Data collection and questionnaire design

Data were collected using a survey method based on a structured questionnaire. Before the questionnaire was designed, the researchers organised a workshop session with members of the SME community, representatives of Mauritius Tourism Authority, and other key stakeholders on 30 March 2018. The opinions of the participants were sought on the topic and following a review of the existing literature, the questionnaire was designed. Before data collection, the necessary ethical clearance was sought from the relevant authorities. The survey was administered to SMEs operating in the tourism sector of Mauritius between June and November 2018. In the majority of cases, a drop-off pick-up method was used to collect data. This method has the advantages of yielding a high response rate and reducing non-coverage error (Steele et al. 2001). Three hundred and ninety responses were obtained, out of which four were discarded due to several missing responses across the scale items, resulting in a valid sample of 386.

Seven-point Likert scales were used to measure the constructs of interest, namely: competence, autonomy, managerial capability, innovation capability and SME performance. The measurement scales were adapted from previously validated scales. Competence was measured using indicators adapted from the study of Omerzel & Antončič (2008). It comprised of indicators measuring different skills such as teamwork, leadership, communication skills, accounting and time. Autonomy was measured using a set of items adapted from the study of Menon & Hartmann (2002). The latter included items such as ‘I can influence decisions taken in my department’, ‘I can influence the way work is done in my department’, and ‘I have the authority to make decisions at work’. Scales to measure Managerial and Innovation Capability were adapted from the study of Hooley et al. (2005) and Merrilees et al. (2011). Items used to measure managerial capability included: ‘My business has better operational management expertise’, ‘My business has better overall management capabilities’, ‘My business is able to execute marketing strategies’, ‘My business manages its supply chain better’; Innovation capability was measured through statements such as: ‘Better at developing new ideas to help customers’, ‘More able to fast track new offerings to customers’, ‘More able to manage processes to keep costs down’ and ‘More able to package a total solution to solve customer problems.’ Finally, to measure SME performance, indicators were adapted from the study of Hooley et al. (2005). The measures for SME performance consisted of statements such as ‘is more profitable’, ‘has a better return on investment’, ‘is able to reach financial goals’, ‘stronger growth in sales revenue’, ‘better able to acquire new customers’, ‘has a greater market share’ and ‘able to increase sales to existing customers.’

4.2. Data analysis procedure

The theoretical model of the study is tested using structural equation modelling (SEM). SEM allows researchers to study real-life phenomenon and ‘provides a useful forum for sense-making and in so doing link philosophy of science to theoretical and empirical research’ (Bagozzi & Yi 2012). SEM is a statistical procedure for testing measurement, functional, and predictive hypotheses that approximate world realities (Bagozzi & Yi 2012). Its ability lies in the assessment of latent (unobservable) variables at the observation level (measurement model) and testing hypothesised relationships between latent variables at the theoretical level (structural model) (Hair et al. 2012). SEM has become increasingly popular in social and behavioural sciences and is considered one of the most widely used statistical techniques for testing complex models that involve several dependent and independent variables (MacCallum & Austin 2000; Heene et al. 2012). The two approaches to SEM include co-variance based SEM and partial least square (PLS)-SEM. Given the present study’s focus on prediction of the outcome variable (SME performance), the PLS-SEM technique is of particular relevance (Richter et al. 2016; Rigdon 2016; Sarstedt et al. 2017). The PLS-SEM algorithm relies on the estimation of composites instead of covariances and this allows for the estimating coefficients having optimum effects on the model’s ability to predict the outcome variable (Rigdon et al. 2017). We use the SmartPLS3 software developed by Ringle et al. (2015) to test the model.

5. Analysis and findings

5.1. Analysis of sample profile

A valid sample of 384 respondents was obtained, which is a satisfactory number of observations based on the G-Power analysis. The demographic profile of the survey respondents is presented in Table 1. A slight majority of 52.6% is female. With respect to the age profile, the sample was dominated by respondents between the age of 40 and 60 (44.7%). Around 38% of the sample are holders of an undergraduate degree and around 8% holds a post-graduate qualification. The majority does not have formal university education (52.6%). In terms of the legal status of the SMEs, the majority are sole proprietor owned (60.6%). The SMEs are fairly distributed across different sectors. The majority of them are tourism start-ups (56.7%).

Table 1. Sample profile of respondents and SMEs.

Variables	Frequency (n)	Percentage (%)
Gender (n = 381)
Female	214	55.4
Male	167	43.3
Age group (n = 384)
18–25	13	3.4
26–35	82	21.2
36–45	149	38.6
46–55	99	25.6
56 and above	41	10.6
Highest level of education (n = 383)
Primary level	67	17.4
Secondary level	169	43.8
Undergraduate degree	46	11.9
Post-graduate degree	25	6.5
Vocational/technical	39	10.1
Professional qualification	30	7.8
Non-formal qualification	7	1.8
Field within which highest education (n = 308)
Business management	99	25.6
Economy/finance	66	17.1
Law	9	2.3
Science and technology	13	3.4
Engineering	20	5.2
Others	101	26.2
Marital Status (n = 384)
Single	60	15.5
Married	274	71.0
Divorced	28	7.3
Widow	22	5.7
Legal Status of registered business entity (n = 380)
Sole proprietorship	234	60.6
Partnership	52	13.5
Cooperative	14	3.6
Limited Private Co.	70	18.1
Society	5	1.3
Others	5	1.3
Sector (n = 383)
Manufacturing	60	15.5
Transport and communication	40	10.4
Construction	16	4.1
Services	86	22.3
Wholesale/retail trade	113	29.3
Agriculture	33	8.5
Others	35	9.1
Business originated as a result of (n = 379)
Linkage to an existing business	53	13.7
Inherited family business	68	17.6
Bought an existing business	23	6.0
Managers buying the business	16	4.1
Completely new start-up	219	56.7

5.2. Structural equation model

We followed a two-stage approach process to test the structural model. First, we assess the psychometric properties of the measurement model (Nunkoo & Ramkissoon 2012; Nunkoo et al. 2013). Table 2 shows the results of the measurement model testing. As shown, performance, management capability and innovation capability that are assessed using a reflective measurement models, have satisfactory reliability and validity scores. In the case of reliability, all observed Cronbach’s alpha scores were above the 0.7 threshold value which demonstrate an adequate level of internal consistency. As for the validity all outer loadings were observed to be above the 0.7 value; the AVE scores as well were all observed to be at a satisfactory level above the established threshold value of 0.5. Furthermore, the bias-corrected confidence interval of the HTMT values can be observed not to contain 1, hence making it satisfactory to ascertain discriminant validity (Hair et al. 2017) (Figure 1).

Figure 1. The structural equation model.

Table 2. Properties of the measurement model.

Latent variable	Indicators	Convergent validity		Internal consistency reliability		DV	M	SD
		Loadings	AVE	CR	CA	HTMT CI*
		>0.70	>0.50	>0.70	>0.70
Autonomy	J1	0.871	0.765	0.942	0.923	Yes	4.01	0.923
	J2	0.861					3.95	0.956
	J3	0.897					3.99	1.047
	J4	0.889					4.13	0.948
	J5	0.853					4.23	0.947
Competence	E1	0.717	0.559	0.91	0.887	Yes	4.13	0.756
	E2	0.778					4.14	0.720
	E3	0.752					4.07	0.738
	E4	0.730					4.18	0.813
	E5	0.730					4.23	0.798
	E6	0.708					4.17	0.823
	E7	0.769					4.07	0.775
	E8	0.793					4.12	0.792
Management capability	C1	0.742	0.614	0.864	0.790	Yes	3.65	0.915
	C2	0.843					3.74	0.834
	C3	0.779					3.76	0.839
	C4	0.767					3.75	0.995
Innovation capability	D1	0.855	0.681	0.895	0.842	Yes	3.99	0.795
	D2	0.859					3.87	0.836
	D3	0.710					3.70	0.964
	D4	0.867					3.87	0.880
Performance	P1	0.834					3.50	0.935
	P2	0.839					3.52	0.954
	P3	0.866					3.61	0.995
	P4	0.885	0.675	0.935	0.919	Yes	3.55	0.969
	P5	0.800					3.80	0.886
	P6	0.787					3.31	1.037
	P7	0.730					3.66	1.012

Following the validation of the measurement models, the next step is to test the structural model and evaluate the specific path relationships. It can be observed through the results that 48% (R²= 0.48) of variation in performance can be explained through management and innovation capability. Additionally, the bootstrapping procedure set at 5000 iteration, at a 95% confidence level resulted in confidence interval ranging in values not including zero implying statistical significance. As presented in Table 3 above, managerial capability has a significant positive direct effect on SME performance (β = 0.634; BCa = [0.523–0.737]) while innovation capability does not (β = 0.088; BCa = [−0.030–0.194]). Managerial capability is found to be significantly predicted by both autonomy (β = 0.086; BCa = [0.001–0.171]) and competence (β = 0.484; BCa = [0.402–0.572]). Moreover, the results show that the competence of SME owners has a much stronger effect on overall managerial capability as compared to autonomy. The results also show that innovation capability does not exert a significant effect on SME performance (β = 0.088; BCa = [−0.030–0.194]).

Table 3. Results of Structural Model (Assessment of Direct and Total Effects).

	Path coefficients	t-values	p-values	95% Confidence intervals		Sig^a
				2.50%	97.50%
Autonomy -> Innovation capability	0.086	1.958	0.051	0.001	0.171	YES
Autonomy -> Managerial capability	0.155	3.022	0.003	0.047	0.247	YES
Competence -> Innovation capability	0.357	6.179	0.000	0.241	0.473	YES
Competence -> Managerial capability	0.484	11.081	0.000	0.402	0.572	YES
Innovation capability -> SME Performance	0.088	1.526	0.127	−0.03	0.194	NO
Managerial capability -> Innovation capability	0.417	8.016	0.000	0.317	0.517	YES
Managerial capability -> SME Performance	0.634	11.496	0.000	0.523	0.737	YES

^aReference is made to the bootstrap bias-corrected confidence interval.

6. Discussion

Results indicate that managers’ autonomy is a significant determinant of SME performance, suggesting that more autonomous managers lead to improved SME performance. This is because autonomy facilitates entrepreneurial actions by facilitating the exploration of business opportunities, development of new business concepts, and their execution through to completion (Lumpkin et al. 2009). Our study confirms previous research, suggesting that managers who feel they have enough flexibility to take managerial decisions report better firm’s performance (Johansson et al. 2015). In the context of this study, autonomy refers to manager’s freedom to act and the latitude they have when formulating strategic decision in their organisation and the development of the SEM strategy (Montanari 1978). The benefits of the execution of managerial discretion for greater performance consequences have been well discussed in the existing literature (Magnan & Stonge 1997; Keegan & Kabanoff, 2008; Li & Tang 2010; Sirén et al. 2018).

Our results also indicate competence to be a significant determinant of performance. Higher level of managerial competence was positively related to performance. In SMEs, managerial human capital plays an important role in determining the performance of the organisation. Managers’ knowledge helps to develop the required capabilities that are essential and decisive in strategic outcomes. In addition, managers are the main factor behind the initiation, development, sustenance, and success of a firm’s (Freeman et al. 2006). The main approaches in the social science literature to identify competence build from the scientific principles of rationalistic research tradition that focus on job analysis (Cascio 1995). Furthermore, the study also demonstrates that skills of the managers were positively related to managerial competency. The literature identifies skill as an important determinant of competence and indirectly, performance (Yamazaki 2010). Empirical studies have attempted to establish relationships between skills, competence and performance, with the conclusion that performance and competence has to be accompanied by difference types of managerial skills (Black & Mendenhall 1990; Yamazaki & Kayes 2004; Seak & Enderwick 2008).

We also demonstrate empirically that skills are positively related to innovation capabilities of the managers, suggesting that more skillful managers demonstrate more capabilities to bring innovation to their SMEs. The role of skill in innovation has been validated across several studies carried out in different context (Thoenig & Verdier 2003; Compagni et al. 2015). From an economic perspective, skills are considered as an engine for growth and productivity of firms (Nelson & Phelps 1966). Evidence from both theory and empirical analyses suggest that skills drive the capacity of manager to innovate, which consequently influences productivity, growth, and market value of firms.

However, empirical analysis is mainly concentrated with large firms, although from a theoretical perspective, we can extrapolate such evidences to SMEs. The OECD’s Innovation strategy report highlights that in some OECD countries firms now invest as much in the intangible assets such as skill improvement to improve the innovation capabilities of managers (The OECD Innovation Strategy, 2010). Our study has also established a significant positive relationship between management capability and innovation capability. This finding is not surprising given the ample evidence that validate a similar relationship in the existing literature. Several firms have improved the management capability in an attempt to improve innovation capability. For example, FedEx adopts an outside-in approach to create innovative products (Battor et al. 2008).

7. Managerial implications

The study provides important managerial implications for improving the performance of SMEs. For better performance, it is imperative for SMEs to improve their management capability. Our results indicate that SMEs with more autonomous managers’ report improved performance. Thus, it is important that managers of SME are empowered to make strategic decision. The concept of empowerment is originally derived from participative management theories and suggests that manager’s involvement in decision-making leads to several benefits for the organisation. Thus, the organisational structure of SMEs should encourage managers to participate fully in the decision-making processes. SMEs should be a light organisational structure that reduces bureaucratic decision-making processes involving several layers of management. As Martin & Bush (2006) argue,

 … a participative climate that emphasizes individual contribution and employee initiative accepts and fosters the notion that employee creativity and self-determination are critical success factors in a competitive environment. In turn, as work climate perceptions become increasingly positive, employees likely perceive greater meaning, competence, self-determination, and impact in their work. (p. 420)

Improving innovation capabilities remains an important consideration for SME to improve their performance. SME should recognise that innovation provides them with a competitive advantage and help them play a dominate role in the industry. SME therefore has to focus on such processes that lead to more efficient production at the lowest possible costs. Furthermore, SME can use process and system innovation to improve productivity. They can, for example, implement lean principles that aim to eliminate ‘waste’ from production to customer relations, product design, supplier networks and factory management with objective being less human effort, inventory and time to develop products, within minimum space to become highly responsive to customer demand and produce quality products economically.

Developing managerial skills is another path to improve management and innovation capabilities as our findings suggests. The government should recognise the importance of managerial skills for the sustainability of SMEs in Mauritius and should provide incentives or directly support skills development programme for SME managers. Such programmes should at improving skills of SME managers such as those related to people management, business finance, communication, negotiations, project management, business strategy and planning, leadership, and other fundamental management skills.

Despite the value of this study for theory and practice, it is not without limitations. First, the study relied on data collected using self-reported measures. Therefore, common-method bias could have influenced the results, although we took various measures to limit such biases in the study. Second, the theoretical model contains only a limited number of determinants of financial performance. The literature evidences a number of other determinants such as those related to the macro-economic conditions of a country. It is therefore recommended that future research takes into account additional factors that can enhance the predictive power of the model. Third, the study is based on a survey design which is a non-experimental research approach. Therefore, the findings should be interpreted in the light of the caveats inherent to survey research, commonly referred to as the total survey error (Eckman & de Leeuw 2017; Nunkoo et al. 2018). The latter is defined as ‘the accumulation of all errors that may arise in the design, collection, processing, and analysis of survey data. In this context, a survey error is defined as the deviation of a survey response from its underlying true value’ (Biemer 2010, 817). Survey errors can pose challenges to the reliability and validity of research findings. Finally, the specific socio-economic and political conditions of Mauritius limit the extent to which the findings can be generalised to other economies.

8. Conclusion

The purpose of this study was to assess the determinants of SME performance in Mauritius. To this end, a theoretical model was developed based on a review of the existing literature in the field. The model proposes that management capability, autonomy, competence, self-confidence, and skills are the antecedents of SME performance. The model was tested using a structural equation modelling approach on data collected from 384 SME owners/managers. The results indicate managerial capability has a strong influence on SEM performance, while the former is influenced positively by mangers’ autonomy. Given the socio-economic importance of SMEs to the Mauritian economy, the results provide crucial information to government and policy-makers that can used to develop macro-economic policies that increase their contribution to the socio-economic development of the country. For entrepreneurs, the study provides insights on areas of interventions that can lead to an improvement in the financial performance of their organisations. Despite the study limitations, it contributes to a theoretical understanding of the determinants of financial performance in African economies.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by International Development Research Centre.