Do Firm and Entrepreneur Characteristics Play a Role in SMEs’ Sustainable Growth in a Middle-Income Economy like Côte d’Ivoire?

Abstract

Globally, small- and medium-sized enterprises (SMEs) play a key role in driving sustainable economic growth in both developed and developing countries. The main objective of this study was to investigate the firm and entrepreneur characteristics influencing the growth of SMEs in Côte d’Ivoire, with special insight into why this country has been a middle-income economy for decades despite its numerous economicpotentialities. Through IBM SPSS version 22.0, 19 hypotheses were tested using data from 160 SMEs operating in Côte d’Ivoire. The results from chi-square tests revealed an association between each of the ‘firm and entrepreneur characteristics’ and at least one of the three growth measurements. However, it was found thatkey factors such as ‘entrepreneur’s ‘age’, ‘work experience’ and ‘level of education’ do not play a role in SMEs’ sustainable growth in Côte d’Ivoire. Results from the binomial logistic regression confirmed that ‘ability to avoid reporting loss’ can be predicted based on ‘entrepreneur’s work experience’, ‘business sector’ and ‘source of funding’. Although this study has practical significance in the business sphere, its results may be of particular help to governments and policymakers in middle-income economies like Côte d’Ivoire for policy formulation and development of frameworks to enhance SMEs’ sustainable growth.

1. Introduction

Small- and medium-sized enterprises (SMEs) are the engines of economic growth for most countries, whether low-, middle- or high-income economies. Factors that affect the performance of SMEs in a country are not just those that improve their profits; they also pertain to country development issues such as creating growth and jobs. Studies in different nations have demonstrated the existence of many factors that contribute to the failure or success of SMEs [1,2,3,4,5,6,7,8].

Van and Storey [1] pointed out ‘lack of access to finance’, ‘inexperience’ (e.g., lack of technical training, inadequate managerial skills and/or limited educational background), ‘default in planning’ and ‘insufficient research into markets’ as causes of SME failure in Great Britain. As for factors promoting success, Al-Mahrouq [2] has demonstrated that business size and its development are correlated, indicating that smaller businesses develop substantially in comparison with medium and large enterprises. While Al-Mahrouq [3] identified ‘technical procedures and technology, firm’s structure, financial structure, marketing and productivity, and human resources structure’ as a set of factors affecting significantly and positively the success of SMEs in Jordan, Franco and Haase [4] found ‘business sector’ and ‘business size’ to be the most influential factors in enhancing the performance of Portuguese firms. In a more advanced study associated with SMEs’ success and failure (which asked the question: What factors drive performance of small and medium-sized enterprises?), Franco and Haase’s [5] research led to the empirical evidence that ‘strategic planning’ is the most determinant factor for success in SMEs operating in Portugal.

In the light of available findings, analyses and literature on the topics associated with SMEs’ performance, it is clear that, owing to the distinctions existing for every individual SME and entrepreneur, there seem to be no specific factors that will in every case steadily promote success or failure. Many studies have led to difficulties in understanding precise causes, since factors considered as reasons for failure may also appear as factors touching on success [9].

If, according to Dun and Bradstreet [10], the failure rate of small businesses is around 50% per year during the first five years, an investigation by Justis and Chan [11] inferred that exact information concerning failure rates has a tendency to confound and perhaps overrate, because of differences in data collection methods and context.

Another gap in previous studies is that most of these studied were conducted in developed, high-income economies or the methodologies have been used in some developing countries where the business environment and context are not the same. Since Côte d’Ivoire is a middle-income economy, Ivorian entrepreneurs cannot rely on conclusions drawn from developed countries to make predictions about the performance of their enterprises. Moreover—despite their contributions—most of the studies are restricted to specific contexts of particular economies (or countries), or are directed at specific categories of business operating in a particular sector. As a palpable example, Ceptureanu, Ceptureanu and Marin [6] limited their study to a specific context of Romanian SMEs operating in the fabric and garments industry. Such results cannot be generalised. In addition, the vast majority of these studies were conducted over 10 years ago, which means that the present circumstances are in need of investigation.

This study, therefore, attempts to investigate the significant ‘firm and entrepreneur characteristics’ currently affecting SMEs’ sustainable growth in Côte d’Ivoire.

This topic—although considered too basic in a developed or emerging country—is of topical interest in an economy like that of Côte d’Ivoire, because there are very few case studies carried out in environments and contexts of the Ivorian economy. The business environment is so unfavourable—i.e., it is a context in which is difficult to grasp that conducting such research in a developing country like Côte d’Ivoire proves to be a great challenge. Moreover, because SMEs in Côte d’Ivoire have long faced many challenges hindering their sustainable growth, any study on any factor that may affect the performance and growth of SMEs is warmly welcomed. Previous studies [12,13,14] have investigated only the constraints of SMEs operating in Côte d’Ivoire, namely lack of financing, and political instability. As for studies about factors influencing SMEs’ sustainable growth in Côte d’Ivoire, there are none.

Three issues are considered in this paper. First, the most important factors relating to growth are determined. Secondly, a demonstration is given of the existence of a relationship (or not) between each of the firm and entrepreneur characteristics and the SME’s growth. Lastly, the effects of a set of firm and entrepreneur characteristics in enhancing SMEs’ growth are described.

This paper is organised as follows. The next section describes the study context, the concept of SMEs, and the concept of growth and its measurements; after which the research hypotheses are presented. In the following section on research methodology, the model is presented, the sampling method and data collection are explained, the variables are specified, and the data analysis method is described. This is followed by the analysis of the major findings. The last section provides a discussion and conclusions covering the major findings, recommendations, contributions, limitations and some suggestions for further studies.

2. Theoretical Background and Research Hypotheses

2.1. Definition and Characteristics of Small- and Medium-Sized Enterprises(SMEs) in Côte d’Ivoire

SMEs are businesses whose personnel numbers, annual turnover and/or balance sheet fall below certain levels. According to the World Bank, many of the countries in sub-Saharan Africa—countries characterised by their small size and by their low- or middle-income economies—report a high number of SMEs in their economies. This is because smaller economies usually have a larger SME sector in terms of the number of firms per inhabitant. In these countries, activity is distributed widely among a large number of more or less formal SMEs, while in China, for example, economic activity is to a much larger extent organised in larger entities. In Côte d’Ivoire, most SMEs are characterized by a low level of organisation, which is a result of their sociological similarity with the informal sector [15].

The SMEs sector in Côte d’Ivoire offers employment to both rural and urban centres. SMEs contribute massively to the creation of employment and financial resources in the economies of states. By 2015, SMEs represented 90%–98% of the formal economy, 18%–20% of national income (GDP), and 23% of jobs in Côte d’Ivoire.

Full-time engagement of employees, legal recognition and tax payment are essential conditions to be considered by SMEs [16]. Since January 2012, there have been two wide parameters defining SMEs in Côte d’Ivoire (Côte d’Ivoire SME charter), namely:

(1)

Micro enterprises:

• Annual turnover not exceeding €45,753
• Fewer than 10 employees

(2)

Small enterprises:

• Annual turnover between €45,753 and €228,674
• Fewer than 50 employees

(3)

Medium-sized enterprises:

• Annual turnover between €228,674 and €1,524,490
• Up to 200 employees

2.2. Overview and Realities of Côte d’Ivoire with Respect to SMEs

Côte d’Ivoire is a member nation of the Economic Community of West African States (ECOWAS), which is made up of 15 countries. With GDP growing on average by 8%–9% per year during the period 2012–2016 [17], Côte d’Ivoire is the second strongest economy in the West African region. The country is one of the world’s largest producers and exporters of agricultural products, being the world’s largest exporter of cocoa beans (yielding 37% of world production); the top producer of natural rubber in Africa; the top producer of cashew nuts in the world; and the third largest producer of coffee beans worldwide. However, the economy is affected severely by international price fluctuations in respect of agricultural products, although the oil sector is flourishing.

Côte d’Ivoire has remained peaceful and stable from its independence in 1960 until 2002. Growth subsequently slowed when the country entered into a period of political tension from 2002 to 2011. As a result, public and private investments dropped to 10.3% during the period 2000–2006, well below the average levels in West African Economic and Monetary Union (20.3%). With the return of political stability and peace from 2011, the country was among the fastest growing economies in sub-Saharan Africa with 8.5% growth in 2014, and 7.9% in 2015. The GDP is expected to reach US$69.27 billion by 2022 [17]. The government of Côte d’Ivoire implemented the National Development Plan (NDP) 2012–2015, which contributed significantly to a strong economic revival. In recognition of its economic achievements, the World Bank has ranked Côte d’Ivoire among the most robust economies on the African continent from 2014. In its Investment Climate Statement–Côte d’Ivoire, 2015, the United States Department of State ranked Côte d’Ivoire among the top 10 reformers in both 2014 and 2015, and stated that Côte d’Ivoire was fertile soil for investments.

There are several constraints experienced by SMEs in Côte d’Ivoire. The presence of numerous difficulties can explain the high failure rate of SMEs in recent years. Access to finance tops the list of constraints faced by Ivorian SMEs [14]. Growth potential is restricted when entrepreneurs are denied credits as a result of outrageous requirements or interest rates that are too high. Moreover, despite more than two-thirds of women having university education, they make up only about 15% of entrepreneurs in Côte d’Ivoire. This entrepreneurial imbalance between men and women is another key obstacle to SME development in Côte d’Ivoire. Furthermore, the poor condition of infrastructure, compared to what exists in developed countries, is a noteworthy constraint in Côte d’Ivoire [16].

Conscious of the existence of difficulties, the government has implemented several policies that promote SME development in Côte d’Ivoire. Practical actions include the establishment of a federation of SMEs, the simplification of the process of establishing a company, a guarantee fund for SMEs, and the preparation of official guidelines on the promotion and development of SMEs. As for fiscal incentives, the business environment in Côte d’Ivoire is supported by some tax deduction measures. Furthermore, the Investment Promotion Centre (CEPICI) was created with the aim of reducing costs and time required for administrative formalities relating to the establishment of a company. Consequently, the country has improved its rankings in the World Bank’s annual Ease of Doing Business index, since the country was among the 10 best reformers in the world for the years 2014 and 2015.

2.3. The Concept of Growth and Its Measurement

First of all, it is important to mention that ‘growth’ and ‘performance’ are two concepts that always go hand-in-hand in any area relating to business or business growth. By investigating major factors affecting the growth of enterprises, the two words can be used interchangeably (i.e., growth instead of performance and vice versa, since both have quasi-similar meanings) or in a complementary manner (i.e., performance refers to survival and evolution, while growth reflects the long-term success).

2.3.1. Business Performance and Its Dimensions

As a rule, business performance is basically characterised by profitability or quantified objectives. Terziovski and Samson [18] distinguished three levels of growth within an SME, namely business performance, organisation performance and financial performance. Some scholars [19,20] have measured the concept of business performance in terms of short-term profitability or long-term growth, where growth measures include items such as sales, sales growth, total assets growth, stock turnover, market share, revenue growth, and profit. Other scholars [21,22,23] insist that business performance measurement should include both financial (e.g., gross and net profit growth) and non-financial (e.g., growth in number of employees) indicators. Factors affecting the performance of the business, such as characteristics of the entrepreneur, characteristics of the firm, management strategies, and the influence of the external environment, constitute elements of a successful or non-successful business [24]. In short, performance can be assessed on the basic of efficiency, effectiveness, and reliability, as well as quantitative measures [25]. This study centres on ‘avoiding having to report a loss’ as a financial measure, ‘ability to repay creditors’ and ‘avoiding having to close up over six months during the last four years of operation’ as non-financial measures of performance.

Profitability: The Best Financial Measures of Performance

No enterprise can survive for a long time without making a profit, hence measuring a business’s profitability is compulsory in assessing its growth. Companies use financial gains to sustain their development by financing projects, by developing more products/services, and by supporting strategic choices.

Although there is no agreement on suitable measures of the performance of SMEs, sales growth should be considered as the most influential indicator to a firm’s performance [26]. Since turnover and gross profit flow from sales, turnover growth and gross profit growth are desirable financial achievements.

Ability to Repay Creditors: A Reliable Measure of Performance

When a business is started, access to financial resources from creditors provides support and enables the business to advance. These creditors (i.e., the government, a commercial bank or a private joint venture) will assess the capacity of the business to meet its commitments. If being financially sustainable means being able to carry debt, then incurring greater debt than the company can handle means greater risk of bankruptcy. The companies that fail to take advantage of business factors and social issues will sooner or later be unable to repay creditors [27].

Stability in Doing Business: The Best Indicator of Efficiency and Effectiveness

Stability is seen as the best indicator of efficiency and effectiveness. According to Dictionary.com, being effective is about doing the right thing, while being efficient is about doing things right. According to Thibodeaux and Favilla [28], effectiveness in an organisation is the extent to which it can achieve objectives. Wanjiku [29] stated that being able to do business on a continual basis without ‘closing up the business venture’ over a long period is a sign of stability. For instance, as a regulation criterion, the USA Bureau of Ocean Energy Management (BOEM)states that business stability is based on five years of continuous operation and production of oil and gas or sulphur in the Outer Continental Shelf (OCS) or in the onshore oil and gas industry.

In this study, stability consists in ‘avoiding having to close up over six months during the last four years’. It shows how a company is successfully fulfilling its mission.

2.3.2. Sustainable Growth and Its Measurement

The concept of sustainable growth seems to be highly complex in light of the diversity of definitions and factors to be taken into consideration [30]. However, despite the complexity of its definition, it is admitted without question that the sustainable success of an enterprise results from a combination of various factors including specific characteristics [31].

‘Sustained’ is defined by Cambridge Dictionary [32] as ‘continuing for a long time’. Based on this definition and with regard to the objectives, this study simply defines the concept of ‘sustainable growth’ as the ‘sustained success’ resulting from the capacity of the business to accomplish and keep its objective of long-term growth [21,23,33]. In short, this study conceptualizes sustainable growth as a long-term perspective of growth [34].

As for how to measure the business’s sustainable growth, this study focuses on the contribution of the basic factors, namely maturity (e.g., age and experience), education, business sector and business size in the relationship between ‘firm and entrepreneur characteristics’ and SME growth. The foundation of this assertion is that these basic factors must play invaluable roles in the long-lasting performance of SMEs.

2.4. Hypotheses about the Relation between ‘Entrepreneur and Firm Characteristics’ and Growth

The main hypothesis for the purposes of this study is that entrepreneur’s personal characteristics, firm characteristics, or both firm and entrepreneur characteristics have major effects on the growth of SMEs. Since it has been demonstrated by numerous researchers that many factors (including firm and entrepreneur characteristics) may affect the growth of SMEs, the theory of ‘growth determinism’ can be applied for expressing the relationship between ‘firm and entrepreneur characteristics’ and SME growth.

2.4.1. Impact of Entrepreneur Characteristics on the Growth of SMEs

Numerous authors [35,36,37,38] have demonstrated the influence of owner-managers’ personal characteristics such as age, gender, education, prior experience, family background, and knowledge on the growth of SMEs. Moreover, by presenting an overview of factors aiding South African construction companies, Windapo [8] confirmed the possibility that characteristics and traits of entrepreneurs can affect organisational performance. Wanjiku [29]—in a similar study on management strategies affecting performance of SMEs in Kenya and in a similar context and environment (the Kenyan environment is known to be same as the Ivorian business environment; both Kenya and Côte d’Ivoire are middle-income economies)—found that many entrepreneur characteristics, such as highest level of education, work experience and age, can have an influence on SMEs’ growth.

Entrepreneur’s Age and Performance

Although many studies have found a positive relationship between the age of the entrepreneur and the performance of the enterprise [38,39,40], some scholars found a negative relationship between the two. The maturity (either chronological age or work experience) of the entrepreneur is often seen as a success factor. However, various sources provide evidence of young entrepreneurs in everyday life who have skyrocketed to financial success. If that is so, does age really influence entrepreneurial success? In summary, the findings of the Ewing Marion Kauffman Foundation [39] revealed that people over 55 were twice as likely as people under 35 to launch a high-growth startup. However, Isaga [41] found a negative relationship between the two (age and growth), because ageing and experience, in some cases, increase the likelihood that managers will take risk. Ainsworth and Hardy [42] considered an initiative of an older entrepreneur as a ‘risky project’. The statements above led to the formulation of Hypothesis 1 of this study (see H1 in

Table 1. Summary of research hypotheses.

Factors	H	Hypothesis Formulation
Entrepreneur’s Age versus Growth	H1-1	The entrepreneur’s age could influence his or her business in having a strong tendency to ‘report a loss’.
	H1-2	A relationship could exist between the entrepreneur’s age and his or her ‘inability to repay creditors’.
	H1-3	The entrepreneur’s age could influence the small- and medium-sized enterprise (SME) to avoid ‘having to close up for over six months’.
Education versus Growth	H2-1	The level of education of the entrepreneur determines the propensity of the SME to ‘report a loss’.
	H2-2	The level of education could determine the inability of the SME to ‘repay its creditors’.
	H2-3	The entrepreneur’s level of education could influence (positively or negatively) the SME in ‘closing up for over six months’.
Work Experience versus Growth	H3-1	The entrepreneur’s experience could have an influence on his or her company’s ability to avoid ‘reporting a loss’.
	H3-2	The entrepreneur’s experience could have an influence on his or her company’s ‘ability to repay creditors’.
	H3-3	The entrepreneur’s experience could have an influence on his or her company’s ability to avoid ‘closing up for six months’.
Business Size versus Growth	H4-1	A difference could exist in loss propensity between micro, small and medium-sized enterprises based on category.
	H4-2	A difference could exist in the ‘inability to repay creditors’ between micro, small and medium-sized enterprises based on category.
	H4-3	A difference should exist in ‘closing up’ tendency between micro, small and medium-sized enterprises based on category.
Business Sector versus Growth	H5-1	A direct correlation should exist between ‘reporting loss’ and the sector in which the SME is operating.
	H5-2	A significant positive influence of the business sector should exist on the ‘inability of the SME to repay its creditors’.
	H5-3	There could be a relationship between the ‘sector in which the SME is operating’ and its propensity to ‘close up for six months’.
Source of Funding versus Growth	H6-1	The SME’s tendency to ‘report a loss’ could be related to its source of funding.
	H6-2	The source of funding could determine the inability of the small and medium enterprise to repay its creditors.
	H6-3	The source of funding could influence the SME in ‘closing up for over six months’.
‘Firm and Entrepreneur Characteristics’ versus Growth	H7	The enterprise and entrepreneur characteristics, taken as a whole, could have a significant influence on the SME’s growth.

).

Entrepreneur’s Highest Level of Education and Growth

While some claim that education is the door to a prosperous economy; others assert that education is a fundamental driver of personal, group, company, national and global development. This is explains why most governments and economies (whether developed or developing) are investing greater sums in education. Moreover, there is a commonly held conviction that a highly educated entrepreneur has a greater chance to succeed in business. Whatever the differences of opinion, most literature indicates that educational backgrounds increase the ability of entrepreneurs to grasp the opportunities that are vital to the growth of SMEs [41,43,44]. In a study involving 190 respondents, Wanjiku [29] found a significant relationship (p-value was 0.086) between owner-managers’ level of education and growth. It could, therefore, be argued that a good educational background allows managers potentially to conduct effective knowledge management which in turn positively affects the growth of firms. Hence Hypothesis 2 of this study was formulated (see H2 in Table 1).

Entrepreneur’s Work Experience and Growth

Work experience (i.e., number of years of work) is a critical success factor for small firms [45,46,47]. So, a business owned by an experienced entrepreneur tends to be more successful than the one owned by an entrepreneur without working experience [8,46,48]. Nor et al. [46] have demonstrated that the work experience of Malaysian entrepreneurs had a greater positive effect on business growth than educational background.In a study investigating the entrepreneurial factors affecting the sustainable growth of a South African construction company, Windapo [8] told the story of Mr Sam, an entrepreneur who succeeded thanks to his work experience acquired after several years of work within a large construction company, his self-confidence, and other factors.

From this, it can be deduced that entrepreneurs’ work experience may contribute to knowledge management, and thus can positively affect business performance. This formed the basis of Hypothesis 3 of this study (see H3 in Table 1).

2.4.2. Impact of Firm Characteristics on the Growth of SMEs

Do firm-specific characteristics affect SMEs’ growth? In their recent study of agribusiness firms in Dar-es-salaam, Tanzania, Mgeni and Nayak [49] found that age, firm size and ownership are significant moderate predictors of business performance variations. In an empirical review of the determinants influencing firm performance in developing countries, Mohammed, Aminu, Rahama, and Murtala [50]—after reviewing very nearly 50 academic papers—found different factors that influenced the growth of enterprises in developing economies. The findings of the articles reviewed varied: some had positive results, while others had negative results. Consequently, we were able to conclude that firm-specific characteristics such as size, business sector and source of funding could have a significant effect on the success of firms.

Business Size and Growth

Business size signifies how large an enterprise is in terms of infrastructure and employment [49]. In most studies on firms’ characteristics [16,49,51,52,53], firm size is characterised by the number of employees and capital investment. Based on the findings derived from a study performed by Mothibi [54] using the ordinary least squares regression, business size has a significant positive effect on the growth of SMEs. Business size is—from a resource-based view—an invaluable factor that influences performance [55]. As for the trend, Murad, AIthnin and Jabar [56] found SMEs were subject to several disadvantages, when compared with large companies. The observations referred to in this paragraph led to the formulation of Hypothesis 4 (see H4 in Table 1).

Business Sector and Growth

The term ‘business sector’ refers to the industry classification of firms and other commercial enterprises. It is important to know that the business sector in which a firm operates does not directly influence its growth, but that it might indirectly influence its performance, because firms operating in the same business sector, in the same environment, and with the same economic features tend to experience the same challenges that face the sector, which might influence growth [57,58,59]. For example, Abor [60] provided evidence that SMEs operating in the agricultural sector have the strongest capital structure and asset structure, while SMEs from the wholesale and retail sector have the weakest asset structure and the deepest debt ratio. Consequently, there appears to be a trend which implies the existence of a relation (whether positive or not) between the firm’s industry and its success. This trend prompted our formulation of Hypothesis 5 for this study (see H5 in Table 1).

Source of Funding and Growth

Sources of finance for SMEs—according to Gulani and Usman [61]—include owner’s savings, friends, family members, banks, partners and shareholders. The fear of loss of fortune (in the case of personal savings) and pressure from the creditor (in the case of bank loans) will force the owner-manager to avoid mismanaging the company. A study by Kazemy, Yaghoubi, Ghodsi, and Saghafi [62] revealed that financial factors, including source of funding, were considered very significant to the survival of companies in Iran. Oniovosa [63], too, found a significant relationship between business growth and source and availability of funds. In Nigeria, almost all owner-managers set up and finance their businesses from their personal savings, and this has been directly affecting the performance of their enterprises [64]. A study by Muriithi and Matz [65] on 309 companies in Kenya yielded contradictory results that the sources of finance do not affect the financial performance of the companies in Kenya. Based on these discussions, Hypothesis 6 (see H6 in Table 1) was formulated for this study.

2.4.3. Effects of Firm Characteristics Together with the Entrepreneur Characteristics on the Growth of SMEs

In Bangladesh, a study conducted by Islam et al. [45] concluded that SMEs’ growth was affected by a set of factors including both the firm and the entrepreneur characteristics. The findings of many other studies are in keeping with the conclusions of Muzenda [66], who investigated the determinants of performance in tourism SMEs in South Africa, and found a significant relationship between entrepreneur characteristics, firm characteristics, and SME performance. These findings led to the development of Hypothesis 7 for consideration in this study (see H7 in Table 1).

Since the growth of SMEs was measured through ‘reporting loss’ (or not), ‘ability to repay creditors’ (or not) and ‘closing up the business venture for over six months’ during the last four years (or not), three sub-hypotheses were derived from each of the six secondary hypotheses. This led to the formulation of 18 sub-hypotheses (see Table 1).

In order to better express the rational choice of the variables and measurements,

Table 2. Sources of the Growth measurement and hypotheses on the relationship between factors and SMEs’ growth.

Factors	Measurements	Measure Sources
Growth Measurements	Profitability: Reporting loss	[19,20,26].
	Reliability: Ability to repay creditors	[25,27].
	Stability: Closing up for over 6 months	[25,29].
Entrepreneur Characteristics and Growth	Entrepreneur’s age	[35,36,37,38,39,40,41,42].
	Highest level of education	[29,35,36,37,38,41,43,44].
	Work experience	[1,8,36,37,38,45,46,47,48].
Firm Characteristics and Growth	Business size	[2,4,49,54,55,56].
	Business sector	[4,57,58,59,60].
	Source of funding	[1,62,63,64]

was drawn up. It sets out the synthesis of sources of the growth measurement and hypotheses on the relationship between factors and SME growth.

3. Method

3.1. Framework for the Research

The main hypothesis for the purpose of this study is that entrepreneur characteristics, firm characteristics, or both the firm and entrepreneur characteristics have major effects on the growth of SMEs. Since it has been demonstrated in the literature by numerous researchers that many factors (including firm and entrepreneur characteristics) may affect the performance of SMEs, the theory of ‘performance determinism’ can be applied when expressing the relationship between ‘firm and entrepreneur characteristics’ and SME performance. This is the basis from which this study aims to build a theoretical framework for the relationship between ‘firm and entrepreneur characteristics’ and SME growth.

A business’s sustainability or ‘sustained success’ can be considered as the result of the capacity of that business to accomplish and keep up its long-term objectives.

Figure 1 represents the complete research model with hypotheses. It should reflect a concise conceptualisation of firm characteristics and owner-manager’s personal characteristics leading to success (i.e., the growth of the SME).

It is hypothesised that the performance measurements are impacted by ‘firm and entrepreneur characteristics’. The three performance measurements, namely ‘avoiding having to report a loss’ (financial achievements), ‘ability to repay creditors’ (capacity of the business to meet its commitments) and ‘avoiding having to close up over six months during the last four years of operation’(stability in doing business), describe circumstances specific to the SME’s evolution. These conditions will inevitably result in the SME’s sustainable growth, because a firm’s survival stage is a deciding factor for sustainable growth [23,67].

This conceptual framework is presented in a way that clearly shows the growth as the dependent variable (DV), while the other factors are the independent variables (IVs).

3.2. Sampling and Data Collection

The target population for this study consisted of SMEs operating in all sectors in the Côte d’Ivoire economy. Companies were contacted through the Ivorian Movement of SMEs (MPME-CI), the Ivorian Movement of SMEs, a member association of the Ivorian confederation of SMEs. Given that the contribution of the major business sectors to the national GDP in 2015 was 28% for agriculture, 25% for industry, and 47% for services, a stratified random sampling method was applied from the total MPME-CI population to ensure that all the business sectors were proportionately represented in the final sample. This study used a simple random sampling method where each unit of the population within each stratum had a likelihood of being selected as a unit of the required sample size. The final sample was made up of 160 SMEs, comprising 40 (25% of the total population) operating in industry; 45 (28% of the total population) in agriculture, and 75 (47% of the total population) in services.

A questionnaire—as the primary research instrument—was developed and pre-tested by experts in the field of the present study. The structured questionnaires were given to the participants together with the research permit and the letter of introduction explaining the purpose of the study, with the aim of obtaining their personal information, general information on business and useful information on business performance. Depending on their availability, accessibility and location, some managers received the questionnaire files via email, while others received hard copies. Participants were given four weeks to deliver their responses. The researcher picked up the questionnaires on the previously agreed-upon date, and also interviewed the manager (if needed). A total of 160 questionnaires were distributed and the response rate was 100%. During the verbal interaction, open-ended questions were used to obtain general views from the respondents, while closed-ended questions were used to gather specific information [68]. The analysis of the companies’ relevant documents, government documents relating to policies for SMEs, newspaper articles, academic journals and the internet was considered as a secondary source of information for this study.

3.3. Variables Specifications

While investigating the effect of ‘firm and entrepreneur characteristics’ on the growth of SMEs for this study, entrepreneur’s age, highest level of education, work experience, business size, business sector, and source of funding were considered as independent variables.

The growth of SMEs (the dependent variable) measured on a dichotomous scale (i.e., through Yes or No answers) was assessed on the basis of each of the following conditions:

F1: ‘Loss reported’ (or not)

F2: ‘Ability to repay creditors’ (or not)

F3: ‘Closing up the business venture for over six months during the last four years’ (or not)

In addition, any company having achieved a growth rate of more than 10% of annual turnover and/or gross profit is considered as a ‘high-growth enterprise’ (see

Table 3. Variable specifications.

Variable	Factors			Values
Independent Variables	Entrepreneur’s personal characteristics	B1	Gender	1 = Female
				2 = Male
		B2	Entrepreneur’s age	1 = Under 30 years
				2 = 31–40 years
				3 = 41–50 years
				4 = Over 50 years
		B3	Highest level of education	0 = No schooling
				1 = Primary
				2 = Secondary
				3 = Bachelor’s
				4 = Master’s and postgraduate
		B4	Work experience	1 = Under 5 years
				2 = 5–15 years
				3 = Over 15 years
	Firm characteristics	O1	Business size (business category)	1 = Micro
				2 = Small
				3 = Medium
		O2	Duration of business	1 = Under 5 years
				2 = 5–15 years
				3 = Over 15 years
		O3	Business sector	1 = Agriculture
				2 = Services
				3 = Industry
		O4	Business location	1 = Abidjan city
				2 = Out of Abidjan
		S1	Source of start-up funding	1 = Personal savings, or borrowing from friends and/or shareholders
				2 = Bank loans or microfinance institutions
				3 = Non-government organisations
Dependent Variable (Performance measurements)	Stability and financial achievement	F1	Reporting loss?	1 = YES/0 = No
		F2	Inability to repay creditors?	1 = YES/0 = No
		F3	Closed for over six months?	1 = YES/0 = No
	Profitability	P1	10% growth of turnover in 2014?	1 = YES/0 = No
		P2	10% growth of turnover in 2015?	1 = YES/0 = No
		P3	10% growth of gross profit in 2014?	1 = YES/0 = No
		P4	10% growth of gross profit in 2015?	1 = YES/0 = No

).

3.4. Data Analysis Method

The chi-square test for independence, binomial logistic regression (BLR) and other descriptive statistics were used to analyse the data. The chi-square testis used to discover if there is a relationship between two categorical variables. The credibility of chi-square test results depends on the main assumption that none of the cells has an expected frequency <5. In such cases, Fisher’s exact test is ideal to test the association between the DV and IVs at a significance level of 0.05. p-value ≤ 0.05 (i.e., p-value of Pearson chi-square) means a significant statistical relationship between the variables. Correlation analysis was used to evaluate the effects of various factors on SME growth. BLR predicts the probability that an observation falls into 1 of 2 categories of a dichotomous DV based on 1 or more IVs (that can be either continuous or categorical). In this study, BLR was used to understand whether growth (measured on a dichotomous scale—i.e., Yes or No) could be predicted based on entrepreneurs’ age, education, work experience, business size, business sector and source of funding.

Qualitative data gathered consisted of responses from the interviews, observations and document analysis. These data, together with information from questionnaires, supplemented each other as part of the data analysis process.

4. Results

4.1. Statistics on Entrepreneurs and SMEs

A summary of entrepreneurs and business information is provided in tabulated form (

Table 4. Summary of entrepreneurs and business information.

Variable			Frequency	Percent
Personal characteristics of entrepreneurs	Gender	Male	135	84.4
		Female	25	15.6
	Age	Under 30 years	0	0
		31–40 years	45	28.1
		41–50 years	80	50
		Over 50 years	35	21.9
	Highest level of education	No schooling	0	0
		Primary	0	0
		Secondary	15	9.4
		Bachelor’s	30	18.7
		Master’s and postgraduate	115	71.9
	Work experience	Under 5 years	25	15.6
		5–15 years	70	43.8
		Over 15 years	65	40.6
Firm characteristics	Business size	Micro	80	50
		Small	40	25
		Medium	40	25
	Duration of business	Under 5 years	65	40.6
		5–15 years	95	59.4
		Over 15 years	0	0
	Business sector	Agriculture	45	28.1
		Services	75	46.9
		Industry: Manufacturing and civil engineering	40	25
	Business location	Abidjan and suburbs	105	65.6
		Out of Abidjan	55	34.4
	Source of start-up funding	Personal savings, or borrowing from friends and/or	145	90.6
		Bank loans and/or microfinance institutions and/or shareholders	15	9.4
		Non-governmental organizations (NGOs)	0	0

). In general, data revealed that both men and women entrepreneurs, all business categories (micro, small, and medium-sized enterprises), and all business sectors (agriculture, services, and industry) were represented in this study. Entrepreneurs below 30 years, entrepreneurs with no schooling or having only a primary level of education, and entrepreneurs with non-government organization (NGO) funding were not found in the samples.

Regarding gender, the percentage of women entrepreneurs (16%) was in line with the statistics of the Ivorian Investment Promotion Centre (CEPICI). According to figures from CEPICI, out of 800 SMEs created from January to May 2013, only 15% were owned by women. This percentage is somewhat less than 25% [69], the average proportion of women entrepreneurs in Africa. When all is considered, women remain under-represented in entrepreneurship in spite of their high number and their advanced educational background [70]. According to the Kauffman Foundation Report [70], all owner-managers and their enterprises endeavour to be successful, but women entrepreneurs are generally helpless to secure funding. Hence, the finding that 68% of investors prefer to finance enterprises when owned or managed by men.

Cross-tabulation between gender and age of the respondents showed an age trend between 40 and 50 for women entrepreneurs in Côte d’Ivoire. Moreover, 72% of the entrepreneurs have a master’s degree or higher, indicating that SMEs are mostly run by highly educated entrepreneurs. In addition, most respondents (71.9%) were above 40 years of age, meaning that the majority of Ivorians set up their businesses when they are mature (i.e., over 40 years old).

Business size is regarded as one of the important parameters of the economic landscape. This survey reveals (Table 4) that half (50%) of the enterprises were micro-sized enterprises, while both small and medium-sized enterprises represented 25%. Major sectors highlighted in the survey were services (46.9%), followed by agriculture (28.1%) and industry (25%). These results are in conformity with the country’s GDP by sector.

In terms of source of start-up funding, no entrepreneur reported financial support from non-governmental organisations (NGOs), despite the fact that many NGOs established in Côte d’Ivoire declare that they want to put up the finances for start-ups. If access to finance is considered as the most critical limitation that negatively affects the growth of organisations [71], lack of funding for start-ups is therefore a major constraint that hinders the development of entrepreneurial activities in Côte [12,13,14,72]. In a study by Kouadio [13], 64% of micro businesses operating in Côte d’Ivoire considered the issue of access to finance as the most serious hindrance to their growth. That may be the reason why the category ‘personal savings or borrowing from friends’ reaches 91% in this study.

4.2. Testing Association between Independent Variables and Growth: Chi-Square Tests

The results obtained from skewness and kurtosis normality tests indicate that the variables of the study globally satisfy the conditions for normal distribution (i.e., for each of the variables, −1 < Skewness < 1 or Kurtosis ≤ 3); hence, data are suitable for further statistical analysis.

The results from the various cross-tabulations between each of the IVs and turnover indicated an increasing trend in turnover from micro to medium-sized enterprises in 2014; the rate of ‘Yes, the company has achieved 10% growth in turnover’ in 2014 was 57%, 63% and 100% for micro, small and medium-sized enterprises, respectively. The trends were similar in 2015 (i.e., 29%, 63%, 88%). As for entrepreneurs’ age, education, work experience, and business sector, there was no pattern to describe an association between these factors and ‘turnover’ over the years. In terms of gender of entrepreneurs, most of the companies owned by men performed better than those owned by women. This is because women SME owners had different goals and employed distinctive strategies contrary to the case of the opposite gender. For example, women entrepreneurs usually aimed at educating children, while men always tried to venture into various risky projects [15,73]. Hence, decision making remains the privilege of men [74].

In terms of gross profit, it could be said—if achieving 10% growth represents performance—that most companies (whether owned by men or women) were not performing well. There was, therefore, no association between gender and gross profit. Regarding entrepreneurs’ age, work experience, size of the company, and business sector, there is no sign to describe a relationship between these factors and gross profit over the years. In the cross-tabulations between variables and gross profit, the rate of ‘No, the company did not achieve 10% growth of gross profit in 2014’ completed by respondents on secondary school, bachelor’s, and master’s degrees level were 100%, 67%, and 52%, respectively. This was a decreasing trend for No (and, therefore, an increasing trend for Yes), meaning that the more advanced the entrepreneur’s education, the more likely it was that the company would achieve 10% growth in gross profit.

With regard to ‘source of start-up funding’, the entrepreneurs who started their companies with ‘personal savings, or borrowing from friends and/or shareholders’ reported that their companies realised ‘10% growth of turnover in 2014’. These managers made up 90.5% (95 out of 105) of the total number of managers whose companies realised ‘10% growth of turnover’. In contrast, only 44.4% of the total population of managers who started their companies with ‘personal savings, or borrowing from friends and/or shareholders’ reported that their companies realised ‘10% growth of gross profit in 2015’. These managers however accounted for 100% (60 out of 60) of the total number of managers whose companies realised ‘10% growth of gross profit in 2015’.

When testing ‘entrepreneur’s age’ against ‘reporting loss’, the percentage of entrepreneurs reporting a loss at each age bracket did not indicate a clear trend in the sampled data (i.e., 55.6%, 73.8%, and 65.7% did not show a clear trend). The chi-square tests were reliable, because there was no cell with an expected frequency less than 5. The p-value of ‘Pearson chi-square’ called Asymp. Sig (2 sided) was 0.115 >0.05. This tells us that there was no statistically significant association between ‘entrepreneur’s age’ and ‘reporting loss’; that is, both young and old entrepreneurs reported loss equally.

The chi-square test which was run to confirm whether there was a trend between the ‘entrepreneur’s highest level of education’ and SME growth did not give any indication of an association between ‘level of education’ and ‘closing up for over six months’. The p-value of Pearson chi-square was 0.608 (non-significant) expressing a non-association between entrepreneur’s ‘level of education’ and ‘closing up the company for over six months during the last four years’.

The results from the chi-square test of independence indicated that the entrepreneurs’ inability to repay their creditors did not depend on their professional experience (work experience).

The overall results from the various chi-square tests is reported below (see

Table 5. Summary of the relationships between ‘firm and entrepreneur characteristics’ and growth.

Factors	Hypothesis		p-Value	Independence or Association
Age versus Performance	H1-1	‘Age’ versus ‘Reporting loss’	0.115	Independence
	H1-2	‘Age’ versus ‘Inability to repay creditors’	0.062	Independence
	H1-3	‘Age’ versus ‘Closing up for over six months’	0.0001	Association
Education versus Performance	H2-1	‘Education’ versus ‘Reporting loss’	0.002	Association
	H2-2	‘Education’ versus ‘Inability to repay creditors’	0.004	Association
	H2-3	‘Education’ versus ‘Closing up for over six months’	0.608	Independence
Work experience versus Performance	H3-1	‘Work experience’ versus ‘Reporting loss’	0.0001	Association
	H3-2	‘Work experience’ versus ‘Inability to repay creditors’	0.093	Independence
	H3-3	‘Work experience’ versus ‘Closing up for six months’	0.0001	Association
Business size versus Performance	H4-1	‘Business size’ versus ‘Reporting loss’	0.319	Independence
	H4-2	‘Business size’ versus ‘Inability to repay creditors’	0.188	Independence
	H4-3	‘Business size’ versus ‘Closing up for six months’	0.0001	Association
Business sector versus Performance	H5-1	‘Business sector’ versus ‘Reporting loss’	0.0001	Association
	H5-2	‘Business sector’ versus ‘Inability to repay creditors’	0.0001	Association
	H5-3	‘Business sector’ versus ‘Closing up for six months’	0.756	Independence
Source of funding versus Performance	H6-1	‘Source of funding’ versus ‘Reporting loss’	0.002	Association
	H6-2	‘Source of funding’ versus ‘Inability to repaycreditors’	0.001	Association
	H8-3	‘Source of funding’ versus ‘Closing up for six months’	0.003	Association

).

4.3. Binomial Logistic Regression between Growth and a Set of Independent Variables

Binomial logistic regression (BLR) was used to understand whether growth can be predicted based on a set of ‘firm and entrepreneur characteristics’. From the numerous chi-square tests, a relationship was found between ‘reporting loss’ and some of the variables. BLR was therefore used to understand whether ‘reporting loss’ (measured on a dichotomous scale—i.e., Yes or No) could be predicted based on entrepreneur’s level of education, entrepreneur’s work experience, business sector, and source of funding.

The test for linearity in IBM SPSS showed no significant interaction (i.e., all Sig. were >0.05) for any of the variables. The Durbin-Watson value was d = 1.891 which is between the two critical values of 1.5 and 2.5, hence there is no multicollinearity in the data. Since all the IVs had tolerance greater than 0.1, and a VIF value less than 10 (see

Table 6. Collinearity test for ‘Inability to repay creditors’.

Model		Collinearity Statistics
		Tolerance	VIF
1	Level of education	0.855	1.170
	Work experience	0.897	1.114
	Business sector	0.737	1.357
	Source of start-up funding	0.881	1.135

), there were no multicollinearity issues. Since the statistical tests on the assumptions were run correctly, with all the assumptions met, the results from the BLR could be valid.

The model explained 77.0% (Nagelkerke R²) of the variance in ‘reporting loss’. Overall, the model correctly predicted 69 cases out of 100 (representing 69%), suggesting further that the model fitted the data well. In addition, results from the BLR revealed that O3_sector(1), O3_sector(2), b4_experience(1), b4_experience(2), S_funding(1), and b3_educat(1) were the factors adding significantly to the model (all Wald were <0.05). This means that there is strong statistical evidence that an SME is more likely ‘to report a loss’ if this company and its owner-manager have these profiles. Since the p-value of the chi-square statistic in the Hosmer and Lemeshow test was greater than 0.05, the model was, therefore, very credible. Hence, the following equation to predict ‘reporting loss’ from the entrepreneur’s highest level of education, entrepreneur’s work experience, business sector, and source of funding is reliable.

$$\begin{array}{l}\mathrm{Reporting}\mathrm{loss}\left(\mathrm{Y}\right)\\ =40.701+1.306\mathrm{Education}\left(1\right)+1.127\mathrm{Education}\left(2\right)\\ -20.575\mathrm{Experience}\left(1\right)-20.249\mathrm{Experience}\left(2\right)\\ +39.783\mathrm{Sector}\left(1\right)+20.445\mathrm{Sector}\left(2\right)\\ -41.264\mathrm{Source}\_\mathrm{funding}\left(1\right)\end{array}$$

5. Conclusions

5.1. Discussion and Suggestions

Since the sustainable success of an enterprise results from a combination of factors including specific characteristics [31], the use of ‘firm and entrepreneur characteristics’ seems logical in assessing the sustainable growth of SMEs.

Although the study reveals that there is an association between each of the ‘firm and entrepreneur characteristics’ and at least one of the growth measurements, some cases of non-association are especially notable.

Mature entrepreneurs represent those individuals who have started their entrepreneurial activity at an advanced age or at later stages of their professional careers. They are more prone to succeed, since they have more work and life experience. Education is an advantage as it is a fundamental driver of personal, group, company, national, and global development. In addition—excluding particular situations and cases—a mature person is generally one who is objective, since he or she has the advantage of education, experience and advanced age.However, for SMEs operating in Côte d’Ivoire, there is no statistically significant association between ‘entrepreneurs’ age’ and growth (i.e., in terms of ‘avoiding having to report a loss’); between ‘work experience’ and growth (i.e., in terms of ‘inability to repay creditors’); and between ‘level of education’ and growth (i.e., in terms of ‘avoiding having to close up over six months’).

These findings are challenging many standpoints made in literature which support the significance of age, experience and, especially, level of education in SME growth. As regards age, findings contradict both the advocates of a ‘positive relationship’ [38,39,40] and those advocating a ‘negative relationship’ [41,42] between entrepreneur’s age and business growth. Some see age as a success factor, while others consider older entrepreneurs as risky project lovers. Concerning work experience, it was found by many scholars that entrepreneurs with prior working experience are more likely to lead their SMEs to success [45,48]. As for education, it is claimed that it is the key to success (both personal and business-wise) and a prosperous national economy. If this is a feasible claim, there should be a positive relationship between entrepreneurs’ level of education and the growth of their enterprises [29,41,43,44].

Although this study contradicts the findings of a number of previous researchers, its outcomes are aligned with the findings of some studies. Yeboah [75] in a study in Ghana—a developing African country—concluded that SMEs owned by highly educated persons did not report the highest sales growth. In a study investigating the entrepreneurial factors affecting the sustainable growth of a South African construction company, Windapo [8] found that the formal education of an entrepreneur is not a prerequisite to succeed in business. The story of Mr Sam—a South African entrepreneur—who succeeded without any educational background [8] is a perfect example. Even if entrepreneurs can succeed through their capabilities such as creativity, proactiveness and personality [76], these factors do not bring sustainable growth.

This being so, the basic factors, namely age, experience and education, are not are not playing invaluable roles in the sustainable growth of SMEs in Côte d’Ivoire. Indeed, it is generally assumed that entrepreneur’s age, experience and education play a fundamental role in enhancing business performance for sustainable growth in all economies. Although this may be demonstrable in developed countries and in some middle-income economies, these results cannot be generalised to Côte d’Ivoire.

Overall, Ivorian SMEs are, to some extent, in an unfavourable situation. The growth of Ivorian SMEs is relatively unsustainable, because some of the existing ‘firm and entrepreneur characteristics’ do not support their performance and long-term development. This observation is in line with the results of numerous studies [30,77,78,79,80], which assert that many SMEs are not able to sustain their businesses. This poor performance results in a failure rate of more than 50% [10,80] or 60% [77,78] within the first five years of establishment.

For the 2017 fiscal year, middle-income economies are defined as those with a gross national income per capita between $996.00 and $12,055.00, while high-income economies are those with a gross national income GNI per capita of $12,056 or more. In this study, the sustainability of SMEs is judged by the ability of the SME to be maintained at a viable level for a long period. If—based on these definitions—Côte d’Ivoire remains a middle-income economy despite its numerous economic potentialities, this may be partly because of the lack of essential personal characteristics in entrepreneurs and a short supply of company characteristics that contribute to sustainable growth. This consideration of sustainability excludes aspects such as social and environmental issues and use of resources. Perhaps because of this, the essential variables (i.e., age, experience and education) in promoting sustainable business do not correlate with the evolution of SMEs in the Ivorian context.

These findings seem to meet the main objective of this study, being the investigation of ‘firm and entrepreneur characteristics’ affecting the growth of SMEs, with special insight into why Côte d’Ivoire remains a middle-income economy in spite of its numerous economic potentialities.

In light of the challenges facing SMEs in Côte d’Ivoire, this study offers suggestions on how to promote the growth of SMEs, which will in turn foster sustainable development in the country. The following recommendations ought to be useful for entrepreneurs, government and policymakers.

Firstly, the findings of this study can be beneficial for managers and entrepreneurs at all levels. They can, for instance, use the findings of the study to identify and overcome barriers to the growth of their enterprises. The prediction of success or failure can thus be made on the basis of the findings of this research.

Secondly, this study recommends that policy makers use the findings of this study to assist in policy formulation and development of a framework of critical factors that influence SME growth in Côte d’Ivoire. The government also ought to create an avenue where entrepreneurs can share their skills, as this will narrow the gap between business failure and success.

Thirdly, the study revealed weaknesses in the education system as one of the major barriers to SMEs achieving their performance goals. This should raise the awareness of the government regarding the need to invest more in education, since education is one of the major determinants of SMEs’ sustainable growth.

Fourthly, it was found that most SMEs were managed by highly educated managers, despite the fact that Ivorian companies are not successful in terms of profitability. It should be noted that any highly qualified manager would be likely to fail at business if he or she cannot develop specific skills obtained through training. As a practical recommendation, the government of Côte d’Ivoire should organise training programmes which equip managers to strengthen essential skills. Moreover, young entrepreneurs and owners of start-ups should be incentivised to seek special training to increase the likelihood of their enterprises ‘being able to repay creditors’.

Finally, the study has highlighted the lack of financing for Ivorian SMEs. This reinforces the veracity of the results of studies previously conducted by Kouadio [13], Ghimire and Abo [14] and Wang [72], which found that the lack of financing is a major constraint affecting private companies in Cote d’Ivoire. Since it is difficult for SMEs to access financing, the study suggests the re-evaluation of collateral laws to facilitate SMEs to acquire funding from banking establishments. The government could also, in the interests of economic progress, act as guarantor of SMEs who approach financial institutions and other backers.

5.2. Limitations of the Study and Recommendations for Further Research

The limitations of this study are all linked to its limited scope. First and foremost, the selection of independent variables in this research was restricted to the characteristics of entrepreneurs and enterprises, and does not consider the many other factors that may affect the growth of SMEs. Therefore, future research may focus on other factors which are likely to affect the performance of SMEs. Secondly, for a better assessment, it is suggested that factors affecting the growth of SMEs in Côte d’Ivoire (as a middle-income economy) be investigated and compared with actual situations in other developed countries, in order to reveal similarities and differences. Thirdly, since the study demonstrated that basic factors, such as age, experience and education, did not play a highly influential role in promoting the sustainable growth of SMEs, future research could aim to identify the really relevant factors for sustainable SME growth in Côte d’Ivoire. Ultimately, since the field of SMEs is wide and diverse, many issues still remain unresolved. Upcoming researchers should, therefore, venture into working on other variables affecting the growth of SMEs that have not been studied in Côte d’Ivoire or in the greater African context. The approach, the methodology and the context of this study can serve as a practical model for future researchers.