Editorial Board

A Refereed Monthly International Journal of Management

A Study of Factors that account for the success of SMEs in the Western Region of Cameroon

Ndindah Ndifor Clement

Research Scholar, PhD,

School of Business,

UNICAF University

 

Dr. Abhishek Tripathi

Associate Professor,

Department of Management & Information Systems,

College of Business Administration,

University of Ha’il,

Kingdom of Saudi Arabia

 

Abstract

The extreme relevance of SMEs to the economy is a truism. They generally employ the most significant percentage of the labor force in most economies and contribute considerably to the GDP, economic stability, and growth. They are even more important in developing economies, given that they contribute significantly to the fight against extreme hunger and poverty. However, despite their significant role, this category of businesses still experiences a very high failure rate in most economies, especially in Africa, Cameroon inclusive. Nevertheless, while SMEs in Cameroon suffer a high failure rate, the inhabitants of the Western Region of Cameroon thrive considerably in their entrepreneurial activities. While their success is highly recognized, empirical studies that determine which factors are responsible for this success are inexistent. Therefore, this study aims to identify which factors are determinants of this success empirically. This survey study was conducted on 403 SME owners/managers in the region of Cameroon. Binary Logistic Regression was used to analyses the collected data. This study revealed that access to capital, industry experience and availability of markets are determinants of SME success/failure in this region. From these findings, it is recommended that existing entrepreneurs and potential entrepreneurs consider getting into industries with already established and available markets to increase success chances. In the same light, more has to be done to boost SME access to traditional financing. Finally, entrepreneurship training programs should include modules that provide learners with experience in relevant industries

Keywords: SMEs, ROSCAs, success

 

 

 

 

 

Introduction

Importance of SMEs to the Economy

The extreme importance of Small and Medium-Sized Enterprises (SMEs) to the economy is recognized worldwide (Blackburn, Hart &Wainwright, 2013; &Nowicka, 2015). In Africa, for example, SMEs make up   90% of all businesses; they contribute up to 50% of the African GDP and account for 50% of the total employment (Djoumessi&Akinboade, 2011; Akinboade, 2015; Akinboade&Kinfack, 2012). In Cameroon, SMEs constitute about 99% of all businesses; they account for about 61% of employment and contribute 36% of the GDP (Tsambou&Fomba, 2017). In addition to that, this category of businesses is being more and more recognized as significant contributors to the fight against extreme hunger and poverty in developing economies (Roa, 2014; Ul Haq, Usman, Hussain, & Anjum, 2014).

However, despite their significant contributions, they still experience high failure rates. According to the Small Business Administration (SBA) (2018), only half of all small businesses will not live more than 5years, and only about one-third will survive for up to 10years and above. Acrob (in Muriithi, 2017), on his part, posits that in Africa, five out of seven SMEs die within their first year of operations. It is difficult to determine the SME failure rate in Cameroon due to its considerable informal sector. As for the formal sector, statistics from Research and Analysis Centre on Cameroon's Economic and Social Policies (CAMERCAP-PARC) reveal that 61,366 SMEs were created in Cameroon between 2010 and 2016, with 59,200 being local enterprises and 2,166 foreign. However, 72.24% of these businesses, according to CAMERCAP-PARC (2016), were inexistent on the taxation department’s database as of May 2016. This implies a considerable failure rate as less than 28% of businesses created were still operational by the end of the period.

However, despite this indication of high failure rates in Cameroon, the inhabitants of the Western Region of Cameroon, also known as the Bamilekes, are thriving in business ventures. Multiple studies attest that the Bamilekes are distinguishing themselves through their success in business (Hogenboom, &Jilberto, 2007; Johnson, 2011). In their paper, Komo and Takor (2019) refer to the entrepreneurial success of the Bamileke people as an economic miracle. Henry (2003), on his part, while recognizing the outstanding success of Bamilekes in business, blames this success on the extensive use of tontines or Rotatory Savings and Credit Associations (ROSCA).

Problem Statement 

The problem that calls for research here is:  while statistics imply alarming failure rates in Cameroon (CAMERCAP-PARC, 2016; Muriithi, 2017), the inhabitants of the Western Region of Cameroon (also called the Bamilekes) are proving to be quite successful in their entrepreneurial ventures. Their business success is strongly recognized, and they are even considered the business tribe of Cameroon (Hogenboom, &Jilberto, 2007; Arriola, 2012). However, despite acknowledging their success, there has been no empirical study that sheds light and establishes which factors are responsible for this success. In addition to this, up till date, most studies on SME and entrepreneurial success studies like those of Tsambou, and Fomba, (2017); Akinboade (2015); Djoumessi&Akinboade, (2011); Akinboade&Kinfack, (2012) have been limited to the Central and Littoral Regions of Cameroon since they are the most populated regions of the country (Mbodiam, 2021). This tendency of focusing research in these two regions has left SMEs in the Western Region of Cameroon without sufficient investigations.

Research Purpose

The purpose of this quantitative study is to shed light and empirically establish which of those factors that determine the success/failure of SMEs around Sub-Saharan Africa also assess the success of businesses owned by inhabitants of the Western Region of Cameroon. Therefore, this study is out to provide generalizable findings of what factors are determinants of the success of entrepreneurial ventures in the Western Region of Cameroon.

Literature Review

The Lussier’s model for the predicting the success or failure of SMEs, which is declared by multiples studies as considerably extensive (Bunyaminu, Mohammed, &Issah, 2019; Rolleri, Nadim, & Lussier, 2016; Lussier, Bandara, Marom, 2016; Gyimah, Marom, & Lussier, 2019). This model contains 15 factors that can predict the success/failure of small businesses. They include Capital, Record keeping and financial control, Industry experience, Planning, Management experience, Professional advisors, Education, Staffing, Product/service timing, Economic timing, Age of owner, Partners, Parents owned a business, Minority, Marketing skills (Lussier, Bandara, Marom, 2016; Gyimah, Marom, & Lussier, 2019). This model has beentestedd in multiple countries worldwide, including Croatia, the USA, Chile, Israel, Pakistan, Sri Lanka, Palestine, and Ghana (Bunyaminu, Mohammed, &Issah, 2019; Hyder, & Lussier, 2016). Despite its declared extensiveness, it can be argued that this model completely excludes external environmental factors which have proven relevant to SME success/failure in sub- Saharan Africa (Balbontin, &Hensher, 2019; Abioye, Adeniyi, & Mustapha, 2017; Akinboade, 2015).

While the factors in the aforementioned model quite relevant, the model is not exhaustive. This limit of the Luissier’s lead to the development of the exploratory business success versus failure prediction model. This model which contains 25 variables in the includes all 15 variables of the Luissier’s model. The 10 other variables contain in the exploratory model come from other SME success / failure studies in Asia. This model has proven to be a better predictor of SME success/failure in Singapore (Siow, Singh & Anwar, 2011). 

The use of a model like that Lussier will usually require modifications to the original model given that the factors that determine SME success/ failure have proven to vary significantly from one economy to another (Hyder, & Lussier, 2016; Lussier, Bandara, Marom, 2016; Bunyaminu, Mohammed, &Issah, 2019). This study follows in the same light by using factors from the Lussier’s that have proven relevant to SME success/ failure in Africa and other success/failure studies conducted around Sub-Saharan Africa. 

 

Table 2.1: The factors considered in this study are found on the below:

Variable	Description
Capital	The greater the access to capital the business has, the greater the likelihood of success given that capital pemits the business to qauire other factors of production. It also enhances the ability to seizing opportunities as well as increased in scale of business activities (Agostini, Nosella, &Soranzo, 2017, Meflinda, Mahyarni, Indrayani, &Wulandari, 2018; Gyimah, Marom, & Lussier, 2019, Foleu, Abdulnour, Nomo, &Fouda, 2015; GICAM, 2017).
Education	The higher the level of education owner/ manager, the higher the chances of success. This is because increased education implies improved knowledge (Gyimah, Marom, & Lussier, 2019; Karadag, 2017).
Record keeping and Financial control.	Paying attention to record keeping and financial control increases the chances of the business succeeding. This factor informs business decision and can improve access to formal financing as it provides relevant information to financial institutions and investors (Ajibade, &Khayundi, 2017; Wamukoya, &Otike, 2017; Andoh, Quaye, & Isaac, 2018; Anggraini, &Purwohedi, 2018).
Planning	Planning, especially written plans improve business success chances. It increases a basis for the evaluation of the business. In addition to that, quality written business plan is increasingly becoming a requirement for obtaining formal financing (Bogáth, 2017; KahMarn, Hin, &Bohari, 2016).
Staffing	Getting and retaining qualified staff increases the chances of success. This is because the staff makes use of the technology and other resources to carry out the required business operations. Staffing is generally a challenge for SMEs because they generally require more work from employees for lesser pay thereby rendering them less attractive for qualified staff (Ugoani, 2016; Waqas, Naqvi, Imran & Anjum, 2018; Al-Bdareen, &Khasawneh, 2019; Kankaras, Kapor, Petrovic, & Petrovic, 2018; Garg, 2018).
Location	A business with good location has increased chances of success. This is because suitable location can contribute to the reduction of the cost of operations as well as enhance exposure to customers (Chang, & Li, 2019; Mutti, &Ohrn, 2019; Balbontin, &Hensher, 2019).
Professional Advisors	Consulting professionals increases the business’ chances of success. Professional guidance in decision making contributes to making better business choices (Gyimah, Marom, & Lussier, 2019; Kavvadia, Hezron, 2019; Haliso, Chima, & Jeremiah, 2019; Idris, & Saad, 2019)
Industry Experience	Prior industry experience of the owner / manager augments the likelihood of success. Experience within the industry improve industry knowledge as well as relevant networks and skills (Gyimah, Marom, & Lussier, 2019; Chinomona ,2013; Agustina, 2018).
Management Experience	More management experience will increase the probability of success. Management experience improves awareness and ability to manage managerial functions (Flynn 2017; Heileman, Pett, &Mayer, 2016 ).
Availability of markets	The more the number of consumers who are willing and capable of paying adequate price for the product/service, greater the chances of success (Bongini, Ferrando, &Rossolini, 2017; Pemer, &Skjølsvik, 2017; Febrianti, 2016).
Corruption	Fraudulent use of power by public authorities on SMEs increases chances of failure for the business. Curroption increases the burden on SMEs as they bear extra cost not relevant to the business (Abioye, Adeniyi, & Mustapha, 2017; Appiah, Possumah, Ahmat, & Sanusi, 2018; Shaikh, &Khoso, 2019).
Public Infrastructure	Poor state of roads, access to water and electricity increases the cost of operations, thereby laying extra burden on SMEs (Abioye, Adeniyi, & Mustapha, 2017; Akinboade, 2015).
Perceived Government Support	Financial, technical and advisory support from government increases the chances of success (Al-Tit, Omri, &Euchi, 2019; Hyder, & Lussier, 2016; Lussier, Bandara, Marom, 2016; Virglerova, Dobes, Kramolis, &Kotaskova, 2017).

 

Methodology

 

Sampling and Data Collection

The primary data collection for this study was done using an adequate questionnaire. Before the actual research, a pilot study was conducted to reduce the chances of misrepresentation and improve the study's internal validity. During the actual study, the questionnaire was administered to a sample of 500 participants in the major settlements of the Western Region of Cameroon: Bafoussam, Dschang, Mbouda, and Bandjoun. The sample was mapped out using the stratified random sampling technique. Data from 403 SMEs were used for analysis after verifying the consistency of returned questionnaires. The sample consisted of SMEs from the retailing, service, handcraft, and manufacturing sectors. Participants were recruited from both the formal and informal sectors. The questionnaire was administered to participants on a face-to-face bases, given that owners/managers in this region are less inclined to respond to internet-administered questionnaires.

Data analysis

The analytical tool used in this study is the binary logistic regression analysis.

Measure of SME Success / Failure.  SME Success/Failure

What criteria should be used to determine whether a business is successful? This question is still debated.  According to Lua and Lim (in Teng, Bhatia, & Anwar, 2011), success means continued business activities. In order words, a successful business survives one that stays alive despite the state of the company. However, this definition is considerably limited, given that a business that depends on non-business financing for survival is considered successful. Alfoqahaa (2018) on his part posits that success should be evaluated based on the goals set by the business. This implies that non-business-related objectives pursued by the business should be considered in assessing whether the business is successful. In addition to that, the difference in standards for the evaluation of success that comes with this approach limits it generalizability as each business is to be compared exclusively with itself and not with other business.  Luissier (in Teng, Bhatia, & Anwar, 2011) on his part, posits that for a business to be considered successful, it should have been making profits that are above the industry’s average profits for three years prior to the period of the evaluation.  While this definition is widely used, it excludes businesses younger than three years.  As for Akinboade (2015), success should be evaluated in terms turnover and turnover growth.  Therefore, a successful business has a constant or positive turnover growth rate for a defined period.  In this study, we will use this definition to evaluate SME success/failure, given that it allows the business to be compared with other businesses and itself. More to that it, reasonably practical compared to the other definition

Reliability Test

Reliability generally refers to the internal consistency and reproducibility of a study (Leung, 2015; Morse, Barrett, Mayan, Olson & Spiers, 2002). In this study makes use of the Cronbach’s alpha test which is one of the most popular reliability tests to measure internal consistency by measuring the correlation between the items used in the measurement.

 

Findings

The findings form this study are presented below.

Reliability Test.

Table 4.1: Cronbach’s Alpha Reliability Test

Variable	Cronbach’s alpha
Capital	0.856
Financial Control and Record keeping	0.935
Planning	0.752
Location	0.901
Professional Advisor	0.879
Availability of Markets	0.803
Corruption	0.789
Public Infrastructure.	0.845
Perceived Government Support	0.967

 

As can be seen from the table above, the Cronbach’s alpha value is greater than 0.70 (which is the minimum) for all variables implying that this study can be considered reliable.

 

Results

Table 4.2: Binary logistic Regression

Variable	Nagelkerke	Significance of Hosmer and Lemeshow Test	Probability of correct prediction without independent variable (%)	Probability of correct prediction with independent variable (%)
Capital	0.712	0.113	57.1	86.1
Education	0.020	0.30	57.1	59.8
Financial Control and Record keeping	0.083	0.952	57.1	62.3
Planning	0.103	.60	57.1	63.0
Staffing	.011	.374	57.1	67.8
Location	0.008	.696	57.1	57.4
Professional Advisor	0.007	0.007	57.1	0.571
Industry Experience	0.543	0.774	57.1	81.6
Management Experience	0.409	0.000	57.1	79.2
Availability of Markets	0.639	0.573	57.1	79.9
Corruption	0.004	0.034	57.1	57.1
Public Infrastructure (state of public infrastructure).	0.017	0.634	57.1	58.6
Perceived Government Support	0.00		57.1	57.1

 

From the analysis of the 13 variables identified as influential to SMEs' success/failure around sub-Saharan Africa, the variables capital, industry experience, and availability of markets proved to be determinants of the success/failures of SMEs in the Western Region of Cameroon. These variables present regression coefficient ( ) 0.712, 0.639, 0.543 respectively. This means they account for substantial variations in the dependent variable. They also show statistically insignificant values of 0.113, 0.774, 0.573 for the Hosmer and Lemeshow test. This test is a goodness of fit test, and statically insignificant values imply that the misspecifications in these variables' predictive capacity are statistically insignificant, thus implying that they are good fits. It can equally be seen from the table above that they all present predictor accuracy of 79.9% and above.

Table 4.3: Source of Capital

Source of Capital		Usage (%)
Informal	Capital from savings, family and friends	20.8%
	Capital from tontine (ROSCA)	38.1%
	Capital from reinvestment	24.4%
Formal	Capital from banks	6.3%
	Capital from microfinances	10.4%
	Total	100.0%

 

From the table above, SMEs in this region make more use of informal sources of financing for their business with ROSCAs being used most extensively.

 

 

Discussion and Conclusion

 

Discussion

The findings from this study highlight the relevance the capital for SMEs in this region. It is equally important to note that access to formal capital is still a problem for most SMEs in other economies (Gyimah, Marom, & Lussier, 2019; Hyder& Lussier, 2016; Guzmán, & Lussier, 2015). This study affirms that the formal banking system is failing when it comes to SMEs. This category of businesses that generally have limited collateral security are disadvantaged when it comes to obtaining business financing from these institutions (Agostini, Nosella, &Soranzo, 2017, Meflinda, Mahyarni, Indrayani, &Wulandari, 2018; Gyimah, Marom, & Lussier, 2019; Akinboade, 2015, Bunyaminu, Mohammed, &Issah, 2019). In addition to that, financing from investors is even more difficult given the issue of information asymmetry (Wang, Lin, & Luo, 2019; Rad, Yazdanfar, &Öhman, 2014). Our study also revealed that SMEs in this region are making significant use of informal funding sources. They make extensive use of ROSCA (Rotating Savings and credit associations) as a source of financing. Instead of collateral, ROSCA permits SME owners/managers to leverage social networks for businesses financing (Boutchang, 2019; Nomoto, 2004; Tchuindjo, 1999). In addition to that, the structure of these associations permits them to overcome the information asymmetry barrier that hinders investors from providing financing for SMEs (Wang, Lin, & Luo, 2019; Rad, Yazdanfar, &Öhman, 2014). In the same light, these organizations do not require all transactional costs, which are reported to place a significant burden on SMEs that seek to obtain financing from banks and other financial institutions (Bechri, Najah & Nugent 2001; Ghana, &Darwanto, 2016; Ramlee, &Berma, 2013). This, therefore, renders them an attractive source of financing for SMEs. The extensive use of these ROSCAs suggests that they might be an adequate alternative or substitute for formal financing. However, it is still clear that significant efforts are still to be made to improve SMEs' access to formal financing since formal financial institutions usually have more finances.

As for industry experience, our findings imply that first-hand knowledge about an industry which can be obtained from experience within that industry is essential to success within that industry. This, to some extent, can be considered evident since sectors are different, and the specificity of an industry can be properly captured through experience (Chen, & Cheng, 2019; Snider & Davies, 2017; Awad&Amro, 2017). This might also imply that informal industry learning works for SMEs in this region. This is understandable given that formal learning structures that provide sufficient industry learning are almost inexistent. In addition to that, experience within an industry implies the development of the required skills and the networks necessary to set up and properly run the business. Though not documented, it is observable that this region's inhabitants have developed a culture whereby business owners/managers employ the younger generation from within their families or network of friends and acquaintances. While working for the business, the younger generation gets the necessary industry experience and then moves on to start a business similar to that they worked.

Our findings on the availability of markets imply the apparent need for businesses to succeed and survive. Businesses exist because there exist markets to which they can sell their products/services.  While this finding is consistent with that of other studies (Hyder, & Lussier, 2016; Guzmán, & Lussier, 2015; Cameroon Chamber of Commerce, Industry, mines and handcraft 2016; Febrianti, 2016), it implies that SMEs will do well in industries or sectors that have well-developed markets. Dealing with products or services that are already well known and consumed by the market is beneficial for the business. This implication is not strange given that it is generally advised that SMEs make use of the niche strategy, and this strategy implies that there are already big organizations satisfying the needs of the greater market share while the SME focuses on satisfying the needs of a smaller neglected market segment (Nilasari, 2019; Xie, 2016). Therefore, the product/service the SME deals in is already well known in the market. This might also indicate that SMEs, contrary to popular belief, is not the adequate drivers of innovation since innovation is usually capital and implies entry into a not yet adequately developed (Edwards, 2017; Apanasovich, Heras, &Parrilli, 2016).

Limitations

This study is survival biased as it uses only exiting SMEs. Its findings are therefore generalizable only to existing SMEs in this region. More to that, it is a quantitative survey. The quantitative approach is not designed to get in contact with reality as it focuses on getting generalizable findings (Amina & Rosman, 2015; Alvi, 2016).  Therefore, the use of the quantitative approach might be associated with some risk of misrepresentation (Yilmaz, 2013; Fekede, 2010). However, this risk is mitigated in the pilot study conducted before this actual study. This preliminary study provided adequate adjustments before the actual research.

 

 

Recommendations

It is important that significant actions be taken to enhance SME access to formal capital.  It is also recommended that SME owners/managers who have limited access to formal capital explore informal capital sources like those provided by ROSCAs. In addition to that, entrepreneurship training programs should consecrate significant space for learners to obtain relevant industry experience. It is equally recommended that SME owners/managers in this region go in for business in industries with well-established and developed markets to improve the success rate.

As for future studies, this study is an early one. There is a need for similar studies for triangulation purposes. This research also highlighted the extensive use of ROSCAs as source of SME financing. The lack of studies in this area creates the need for investigation. In addition to that, existing SME S/F models are not quite suitable for sub-Saharan Africa, hence the need for sub-Saharan Africa model(s).

 

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