Small and medium-sized enterprises (SMEs) are one of the buoyant businesses in the global economy with abundant resources that have not been fully exploited. Despite several revelations on the challenges of SMEs, little to none have comprehensively captured financial factors affecting the performance of SMEs, particularly, in the Kenyan leather sector. This study explores financial factors that are affecting the performance of SMEs using the case of the leather industry sector in Kenya. The study data was collected by administering questionnaires to 300 respondents who were randomly chosen from SMEs within Kenyan leather sector. The study found that financial literacy, credit access and tax are statistically significant financial factors affecting the performances of SMEs. As a result, the study recommends that Government should increase its commitment to develop SMEs by offering favorable tax rates and tax exemptions to SMEs especially those in the leather sector of Kenya. Also, SMEs should heighten their financial literacy which will help augment their access to credit.
Las pequeñas y medianas empresas (PYMES) son uno de los negocios más boyantes de la economía mundial, con abundantes recursos que no han sido explotados en su totalidad. A pesar de las diversas publicaciones sobre los retos de las PYME, casi ninguna ha captado de forma exhaustiva los factores financieros que afectan al rendimiento de las PYME, en particular, en la industria del cuero en Kenia. Al parecer, este estudio explora los factores financieros que afectan al rendimiento de las PYME utilizando el caso del sector de la industria del cuero en Kenia. Los datos del estudio se recogieron mediante la administración de cuestionarios a 300 encuestados elegidos al azar entre las PYME del sector del cuero de Kenia. El estudio concluyó que los conocimientos financieros, el acceso al crédito y los impuestos son factores financieros estadísticamente significativos que afectan a los resultados de las PYME. En consecuencia, el estudio recomienda que el Gobierno aumente su compromiso con el desarrollo de las PYME ofreciendo tipos impositivos favorables y exenciones fiscales a las PYME, especialmente a las del sector del cuero de Kenia. Además, las PYME deberían aumentar sus conocimientos financieros, lo que contribuiría a aumentar su acceso al crédito.
Small and medium-sized enterprises (SMEs) are undoubtedly the key drivers of the global economy. In both third world and developed nations, small and medium enterprises (SMEs) are frequently viewed as an engine that fuel the prosperity of the economy based on their crucial role they play in terms of employment generation
Recent empirical studies indicate that SME‘s contributes to over 55% of GDP and over 65% of total employment in high-income nations. In the European Union countries, for example, there are some 25 million small businesses, constituting 99% of all businesses; they employ almost 95 million people, providing 55% of total jobs in the private sector. Key contribution is also on productivity growth and exports expansion
Given the profound position of SMEs in championing sustainable, long-term and diversified economic growth, they have, in fact, attracted revived attention after the 2008 financial crisis. As such, the creation and growth of SMEs are currently at the heart of many economic policy agenda. It is evident that considerable resources are needed to run any business most especially SMEs efficiently in order to cushion them from collapsing. Good performance enhances enterprises’ ability to lower production costs and enhance customer satisfaction and wade off the competition.
Despite the prominence of SMEs in creation of jobs coupled with other profound economic benefits, most of the SME literature opines that unlike larger corporations, SMEs face more diverse prime obstacles which are dependent on their region of establishment. These obstacles include insufficient market demand, securing finance, unfavorable government regulations, competition and macroeconomic instability (
Certainly, the term “SME” can be defined from different perspectives. Previous studies reveal that different organizations together with different countries establish their definitive guidelines for classifying SMEs is normally pegged on the size of the workforce employed, the worth of intangible and tangible property and sales. World Bank defines SMEs as enterprises with less than or equal to 300 workforce, and assets value and annual revenue pegged at $15 million each. Specifically, in Kenya context, according to the Micro and Small Enterprises Act 2012, a Micro enterprise must attain average annual sales of less than Ksh.500, 000 (approximately $4,600) and engages fewer or exactly 10 individuals. A Small sized enterprise must achieve annual sales level of between Ksh.500, 000 and Ksh. 5 million (approximately $4,600 - $46,000) and employees more than 10 but less than 50 persons. Lastly, a medium enterprise engages more than 50 persons and less than 99 persons accompanied with an average yearly turnover of between Ksh.5 million to Ksh.800 million ($45,646.85 - $ 7,304,442.42) and with employees ranging between 50 and 99.
Interestingly, in Kenya, SMEs involvement is not restricted to a single segment of the economy but rather operates virtually in every sector of the economy since they are the source of sustenance for the larger portion of the citizen. However, very little is known regarding the operations, ownership structure, source of finance and other impediments that these SMEs face in their effort to realize full potential. It is against this backdrop that the study is enthralled in investigating the financial factors (access to credit, financial literacy and tax) that affect SMEs performance using the Kenyan leather industry. These financial factors are the crucial financial variables established to be significant among other factors influencing SMEs operation and growth in separate extant literature. Most importantly, these financial factors are recognized in literature to have a direct and immediate impact on the financial performances of businesses (
For this study, access to credit can be seen as the absence of both price and non-price barriers in the use of financial services. Due to the inability of most SMEs to access the formal financial services, they end up going to the informal financial institutions such as Savings and Loan Companies, traditional money lenders, friends and relatives for credit. This subsequently reduces their access to credit for expansion and growth
The main objective of this study is to examine whether these three financial factors, access to credit, financial literacy and tax affect the performance of SMEs in the Kenyan leather industry. The study makes use of primary data which was attained through distribution of questionnaires to targeted respondents. The use of questionnaires provided the researchers with first-hand and detailed information on matters underpinning the research objectives. Using the random sampling without replacement technique, 300 respondents were drawn from the population of all SMEs in Kenya, and with the help of statistical tools, analysis were made to establish the impact of access to credit, financial literacy and tax on the performance of SMEs in Kenyan leather industry.
Many researchers have focused on performance by looking at profitability of firms and industries using the DuPont analysis which include ROI and ROA. However, inadequate studies have been carried out on SMEs which is the major driver of today’s economy, and whose contribution cannot be ignored. Thus, this study contributes to literature firstly by estimating performance in terms of quality and cost minimization. Previous studies focused on ROA or ROI as the proxy for performance. However, SMEs are characterized with a lot of inefficiencies which may be attributed to the use of unskilled labour, inadequate technological equipment and others. Hence measuring SMEs performance in terms of quality and cost minimization appears to be appropriate especially in the leather industry where customers place much priority on quality instead of price. In addition, quality and efficient cost minimization mechanisms ensured by firms will translate into higher ROA or ROI. Therefore, the study deployed quality and cost minimization proxy which happens to be the root ingredients translated into ROA or ROI in the Kenyan SMEs leather industry. The study therefore sheds light on the association between quality practices and cost reduction strategies which eventually influence business practices and performance.
Lastly, this study adds to the literature on the challenges of SMEs in the developing countries using the case of Kenyan leather industry. Though a considerable number of studies have been conducted on the challenges of SMEs, a great deal of research work focused essentially on developed economies (
The succeeding section offers the supporting theoretical outline, review of pertinent literature and hypothesis development. Section 3 chats the research methodology, comprising the empirical model, data sources, and data sampling. Section 4 covers the analysis of empirical outcomes, and the last section contains the conclusion and recommendation.
The review in this section seeks to offer a synopsis of the previous body of knowledge on issues especially related to challenges of SMEs. It encompasses the theories underpinning the study and hypothesis thereof.
Given the purpose and nature of this research, a review of theoretical ideas underpinning the three financial factors are not misplaced.
The business environment today is influenced by strategic managerial decisions that firms implement to achieve competitive advantage. The managerial framework that helps businesses to exploit the resources available to them and remain competitive in the market is that resource-based view. The resource-based view of the firm emphasizes the resources firms need to develop to compete. Two forms of resources exist, property-based and knowledge-based. Property-based resources contribute most in stable settings, while knowledge-based resources have the greatest utility in uncertain environments (
The resource-based view in the context of SMEs is of great concern for many researchers as SMEs are faced with lot of constraint in accessing both property-based and knowledge-based resources. Specifically, SMEs face lot of challenges in accessing credit and due to their small capital, are not able to invest more in capital equipment. They are mostly unable to hire a lot of skilled labour and therefore find is difficult to compete with large firms. This clearly indicate that, based on the resource-based view, SMEs are lacking both knowledge-based and property-based resources that will help improve their performance and growth. Since access to capital and credit play a significant role in meeting firms’ objective, this paper focused on how access to credit minimizes SMEs cost and improve quality.
The cost and availability of credit is a major issue facing SMEs
According to Olatokun and Ayanbode (2009), the accessibility of funds influences the ability of firms in different manner especially the deciding the technology to be adopted, access to markets, and access to necessary resources which in turn incredibly influence the suitability and success of a business. When SMEs are able to access financial assistance from financial institutions and when terms of payments are favorable, business performance becomes good. Adequate finances enable businesses to obtain the capital needed for expansion, cover daily expenses, purchase inventory, hire additional staff and allows businesses to conserve the cash on hand to cover cost of doing business. Also, a study carried out in Nigeria to evaluate access of credit on tomato market performance by
Hence, in line with these arguments, we propose the following hypothesis:
Financial literacy is the familiarity of all the basics of finance and understanding of financial concepts which is used by an individual or company for decision-making
In analyzing how SMEs performance could be enhanced through financial literacy, we integrate the human capital theory and upper echelon theory in support of our argument. Based on the human capital theory, as employees accumulate skills and other abilities through education and training, their value in the work environment is expected to increase as they bring their expertise on the job. The improvement in workers skills and ability could translate into better performance by the firm (
As such businesses and in this case SMEs with good financial literacy will be able to make the proper business decisions, create a good business development orientation and be able to stay alive in their business. By implication SMEs will be able to improve their performance through the acquisition and application of financial knowledge by management and be able to survive business competition. Specifically, SMEs will be able to devise strategies to minimize cost and achieve financial stability which includes being able to invest and make proper financial decisions.
Financial literacy involves the ability to manage financial matters efficiently. Financial literacy equips business owners with the knowledge of making proper financial decisions, such as those on investment, insurance, budgeting and tax planning. As such, business owners that are financially educated are likely to have easier access to formal credit than owners with less financial education.
On the other hand, individuals with financial knowledge have easier access to finances that can make them acquire good quality raw materials, purchase modern machineries and expand their businesses which can lead to the enterprise's growth
Consequently, in formal terms, we predict as follows:
Numerous theories pertaining taxation are present in the study of public economics (
Taxation is an imposition of compulsory levy on individuals or entities by governments of a given economy. Taxation plays a very vital function in the development of SMEs and especially in a middle-income economy such as Kenya where the SMEs are at the forefront in driving forward the socioeconomic development of the nation. Evaluating the impact of tax systems on SMEs normally capture various dimension such as rates, burden, incidence, timing, and multiple taxes. The considerations of these enterprises are to reduce administrative cost, observe compliance, and impacts of carrying out operations in the informal market. In this manner, readjustment of the tax system to the particular SME growth needs can be viewed as critical plan for the policy makers because high tax and tax complicity can stagnant the growth of SMEs which in turn affect economic growth of the country
Tax incentives, such as tax exception enables individuals and businesses to reduce the costs of production since it reduces the amount of tax that business have to pay. Through the reduced tax costs, SMEs can have more money that they can use to improve the quality of their products. Business owners within the leather sector can purchase high quality hides and skins which would be used in production of high-quality leather products to boost their performance. High taxes can demean the performance of a business enterprise. According to the nexus theory of taxation, taxes should be progressive in nature. Mature SMEs with huge income should be charged more than those that are young and with low profit margins. Taxes reduce the profit margins and increase the operation costs of SMEs. High costs of production drain the finances of businesses most especially SMEs which might lead to production of poor-quality products. This proposition is affirmed by the studies of
Therefore, in line with these arguments, we propose the following hypothesis:
This section describes the research design, area of the study, the sample and sampling procedures. It also discusses data collection methods employed in answering the research questions, research quality and data credibility, and data analysis techniques.
The study principally applied primary data. This primary data was attained through distribution of questionnaires to targeted respondents. The use of questionnaires provided the researchers with first-hand and detailed information on matters underpinning the research objectives. The study was carried out among SMEs in the leather manufacture industry of Kenya. A sample of 300 respondent or firms were drawn from the population of all SMEs in the leather manufacturing industry following the random sampling without replacement techniques. The respondents drawn were mainly entrepreneurs or business owners, managers and employees whose responsibilities are directly or indirectly link to the managerial operations of the enterprises and mostly involves some level of financial/monetary roles. The sample posits a fair representation of the SMEs in the leather manufacturing industry of Kenya. Only around 1% of MSMEs (7.41 million) in Kenya are involved in leather-related manufacture (1,786 firms) of which about 50% of leather-producing firms are categorized as medium-sized. The study primarily utilized questionnaires and interviews. The questionnaire was tailored to contain both closed and open-ended questions. Interviews aided in cases where questionnaires couldn’t serve the purpose. The data collection covered a period of eight months (from July 2020 to February 2021). Descriptive statistical tools (SPSS and STATA statistical software) were applied on the primary data collected and inferential statistics was used to analyze, interpret, and draw conclusion from the results.
The socio-economic features of the respondents were examined according to gender, age, marital status and educational level. The analysis is offered in table below.
Source: Own elaboration
| Variable | Type | Frequency | Percent | Cumulative percent |
|---|---|---|---|---|
|
|
Male | 146 | 48.7 | 48.7 |
| Female | 154 | 51.3 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
16-20 | 23 | 7.7 | 7.7 |
| 21-30 | 59 | 19.7 | 27.4 | |
| 31-40 | 103 | 34.3 | 61.7 | |
| 41-50 | 83 | 27.7 | 89.4 | |
| 51-60 | 31 | 10.3 | 99.7 | |
| 61 and above | 1 | 0.3 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Single | 42 | 14.0 | 14.0 |
| Married | 162 | 54.0 | 68.0 | |
| Divorce | 96 | 32.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
No education | 105 | 35.0 | 35.0 |
| Certificate | 156 | 52.0 | 87.0 | |
| Bachelors | 33 | 11.0 | 98.0 | |
| Masters | 6 | 2.0 | 100.0 | |
| Total | 300 | 100.0 |
Specific responses were also drawn from the respondents on the three main financial factors being investigated namely, access to finance, financial literacy and taxation (see appendix for full details on the questionnaire). The results are offered in
It is also evident from
Furthermore, 156 (52%) out of the 300 respondents indicated that outsourcing for financial expertise cost large amount of money, and 87 (29%) respondents also indicated that it cost moderately large amount of money to outsource people to do SMEs finances. This is a clear indication that outsourcing is a bad option as it is an extra cost for a small profit enterprise.
With regards to taxation, 246 (82%) out of the 300 respondents see tax as a huge financial burden for the SMEs. This is an obvious indication that people in SMEs are most often than not tax overburden. Taxes are classified as operational costs and therefore when taxes are high for SMEs, they may hurt the income of the business. In view of the tax burden, more than half of the 30 respondents believe that tax exemption would be of great help to the SMEs growth. As such, 126 (42%) of respondents said that tax exemption would bring a very large change to their business and 69 (23%) said that that tax exemption would bring a large change. This is a strong hint that indeed tax exemption to SMEs would be a game changer in the SMEs industry and in this case the Kenyan leather industry. This is affirmed further by the results as 75% of respondents indicated that after tax SMEs have small and sometimes very small profits to plough back into the business for expansion which is part of the growth of SMEs.
Source: Own elaboration
| Variable | Type | Frequency | Percent | Cumulative percent |
|---|---|---|---|---|
|
|
||||
|
|
Savings | 45 | 15.0 | 15.0 |
| Loans | 24 | 8.0 | 23.0 | |
| Friends and relatives | 231 | 77.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Never | 6 | 2.0 | 2.0 |
| Rarely | 24 | 8.0 | 10.0 | |
| Sometimes | 144 | 48.0 | 58.0 | |
| Not sure | 18 | 6.0 | 64.0 | |
| Very often | 3 | 1.0 | 65.0 | |
| Often | 84 | 28.0 | 93.0 | |
| Always | 21 | 7.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Never | 126 | 42.0 | 42.0 |
| Rarely | 90 | 30.0 | 72.0 | |
| Sometimes | 51 | 17.0 | 89.0 | |
| Not sure | 6 | 2.0 | 91.0 | |
| Very often | 12 | 4.0 | 95.0 | |
| Often | 12 | 4.0 | 99.0 | |
| Always | 3 | 1.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
||||
|
|
No | 216 | 72.0 | 72.0 |
| Yes | 84 | 28.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Very small | 6 | 2.0 | 2.0 |
| Small | 9 | 3.0 | 5.0 | |
| Moderate | 30 | 10.0 | 15.0 | |
| Not sure | 12 | 4.0 | 19.0 | |
| Moderately large | 87 | 29.0 | 48.0 | |
| Large | 156 | 52.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
||||
|
|
Yes | 246 | 82.0 | 82.0 |
| No | 54 | 18.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Very small | 9 | 3.0 | 3.0 |
| Small | 24 | 8.0 | 11.0 | |
| Moderate | 33 | 11.0 | 22.0 | |
| Not sure | 3 | 1.0 | 23.0 | |
| Moderately large | 36 | 12.0 | 35.0 | |
| Large | 69 | 23.0 | 58.0 | |
| Very Large | 126 | 42.0 | 100.0 | |
| Total | 300 | 100.0 | ||
|
|
Very small | 159 | 53.0 | 53.0 |
| Small | 75 | 25.0 | 78.0 | |
| Moderate | 33 | 11.0 | 89.0 | |
| Not sure | 3 | 1.0 | 90.0 | |
| Moderately large | 18 | 6.0 | 96.0 | |
| Large | 9 | 3.0 | 99.0 | |
| Very Large | 3 | 1.0 | 100.0 | |
| Total | 300 | 100.0 | ||
Firm age is estimated by subtracting the number of years the firm has been in operation or deducting the business setup year from the year 2020 which the survey was carried out. Firm size is also measure by the number of permanent employees hired by the business. Growth is the growth of the firm and is estimated by a question indicating whether the business experience an increment in sales in the current year of the study as against the previous years.
Where; β0 is constant term, β is coefficient of explanatory variable, Ti is taxation, Zi is credit access, Xi is financial literacy, Di is control variable (firm idiosyncratic characteristics) and εi is the error term (assumed to have zero mean and independent across period). A comprehensive break down of the study model is given below as
Where in the above two equations; β0 is constant term, β1 to β6 are coefficients of explanatory variables, TPi is taxation, CAi is credit access, FLi is financial literacy, Firmage, Growth and Firmsize are control variables (firm idiosyncratic characteristics) and εi is the error term (assumed to have zero mean and independent across period.
This section offers the analysis of the data gathered and the discussion of the results thereof. It covers the response on the 3 main financial factors deployed for this very study.
As a culmination of the analysis in this study, separate regression models were built using quality and cost minimization as the two dependent variables. For the two regression models, three independent variables were included, namely: credit access, financial literacy, and taxation and three control variables were also included in each of the two models. The control variables included in the models are firm age, firm growth, and firm size.
Source: Own elaboration
Standard errors in parentheses and significant levels 1%(***), 5%(**) and 10%(*)
| Quality | Cost minimization | |
|---|---|---|
| Financial literacy | 0.398** | 0.673*** |
| (0.189) | (0.122) | |
| Credit Access | 0.435*** | 0.273*** |
| (0.126) | (0.057) | |
| Tax payment | -0.316** | -0.682** |
| (0.111) | (0.288) | |
| Growth | 0.125** | 0.211** |
| (0.062) | (0.024) | |
| Firm age | 0.211** | 0.132** |
| (0.102) | (0.117) | |
| Firm size | 0.184*** | 0.297*** |
| (0.054) | (0.101) | |
| CONSTANT | 3.256*** | 5.970*** |
| (0.812) | (0.428) | |
| R | 0.953 | 0.853 |
| Adj. R2 | 0.914 | 0.801 |
| F Test | 169.860 | 129.620 |
| CHI value | 0.000 | 0.000 |
From
The results further revealed that all the control variables deployed by the study have an empirical significant impact on both SMEs product quality and production cost minimization. Firm age, firm size and firm growth were found to have a positive effect on performance of SMEs within the leather manufacturing industry of Kenya. Firm size was established to be statistically significant at 1% whereas both firm age and firm growth were established at 5% percent level of significance. In line with these results, a unit increase in the age, size and growth of SMEs will have a corresponding increase in the product quality and cost minimization, ceteris paribus.
Furthermore, the value of R-Squared on quality was found to be 0.951 with an adjusted R-Square of 0.914. This therefore can be interpreted that the variation of the dependent variable which is percentage of how good quality is, is explained by its explanatory variables by 91 % proving that the fitted model was of good fit and there is no presence of misspecification or adoption of wrong functional form. The value of R-Squared on cost minimization was found to be 0.853 with an adjusted R-Square of 0.801. This therefore can be interpreted that the variation of the dependent variable which is percentage of how good cost minimization is, is explained by its explanatory variables by 80% proving that the fitted model was of good fit and there is no presence of misspecification or adoption of wrong functional form. The value of F-Statistic on quality was 169.86 with a p-value of 0.000, indicating that the fitted independent variables were jointly statistically significant at 5% level of significance based on p-value. The value of F-Statistic on cost minimization was also established at 129.620 with a chi value of 0.000, indicating that the fitted independent variables were jointly statistically significant at 1 % level of significance based on p-value.
The regression results give a clear indication that the financial factors deployed by the study are significant factors that influence SMEs performance and, in this case, SMEs in the Kenya leather manufacturing industry. The findings reveal that credit access has a significant positive impact on performance of SMEs. This result corroborates the findings of
In terms of cost minimization by SMEs, credit access has a significant impact of up to 27 % whereas credit access has up to 43% impact on quality. By implication, SMEs can attain some level of cost minimization as and when they are able to access and secure credit. In the same vein, they can improve on their product quality when they are able to attain credit. Therefore, hypothesis 1 which captures the effect of credit access on performance proxied by cost minimization and quality respectively were found significantly positive. The possible reason could be the Kenyan financial institutions coming up with initiatives such as UWEZO funds to ensure that they offer cheap credit facilities to SME owners as a means of boosting economic growth. Also, affordable, and available access to credit ensures that the SMEs have adequate finances that they can use to purchase quality raw materials on timely basis and ensure proper planning of inventory that can lead to cost minimization. The inventory of skins and hides is very delicate since they can rot when not well preserved and hence lead to products of poor quality. Hence, the availability of credit access is therefore very important in leather manufacturing industry to ensure smoot running of SME.
The study results also confirm that the possession of financial knowledge by SMEs tend to boost their cost minimization strategies and product quality decisions which enhances their overall performance. Our study affirms the conclusion of previous study which remark that financial management skills are beneficial for the survival of small firms and lack of financial literacy could be the reason for the failure of SMEs (
Similarly, the study findings on taxation validate the point that tax payment adversely affect SMEs performance in terms of both quality and cost minimization strategies. As we displayed above, the research hypothesis 3 which says that tax payment has a negative impact on SMEs performance was found to be true. This outcome is fully in line with the conclusions of previous studies such as
The study sought to investigate financial factors that affect performance of SMEs using SMEs in the Kenya leather manufacturing industry as a case. A sample of 300 respondents or firms was utilized for the study. To realize the set objectives, frequency tables and ordinary least squares regression estimate were employed on the dataset. The financial factors considered in the study are access to credit, financial literacy, and tax payment. Performance was proxied by cost minimization and product quality.
This study contributes to previous literature in several ways. First, our findings revealed that better credit access and financial literacy exert a positive influence on SME performance, while tax payment has a negative impact on SME performance. Particularly, our results confirmed that credit access affects positive and significantly on both quality and cost minimization. This meant that credit is a strong determinant of performance of SMEs in Kenya. Also, the effect of financial literacy on performance, that is, product quality and cost minimization was found to be significantly positive. This suggests that financial literacy is also a strong determinant of performance of SMEs in Kenya. Lastly, the regression results further showed that tax payment adversely affects SMEs businesses by increasing operational cost which in turn hurt the quality of products and performance of SMEs as whole.
Second, this study contributes to literature by estimating performance in terms of quality and cost minimization. Previous studies focused on ROA or ROI as the proxy for performance. However, SMEs are characterized with a lot of inefficiencies which may be attributed to the use of unskilled labour, inadequate technological equipment, and others. Hence measuring SMEs performance in terms of quality and cost minimization appears to be appropriate especially in the leather industry where customers place much priority on quality instead of price. In addition, quality and efficient cost minimization mechanisms ensured by firms will translate into higher ROA or ROI. Therefore, the study deployed quality and cost minimization proxy which happens to be the root ingredients translated into ROA or ROI in the Kenyan SMEs leather industry. The study therefore sheds light on the association between quality practices and cost reduction strategies which eventually influence business practices and performance.
Lastly, this study adds to the literature on the challenges of SMEs in the developing countries using the case of Kenyan leather industry. Though a considerable number of studies have been conducted on the challenges of SMEs, a great deal of research work focused essentially on developed economies (
As a result, the researchers first and foremost, advise that SMEs should strive to attain sufficient financial knowledge which will go a long way to affect their business performances positively. Also, educational programs could also be prearranged for the SMEs as most of the workers have no education and financial literacy which could impede their cost minimization capability and for that matter performance. Lastly, the study recommends that the government should offer accessible, inexpensive, and enough loans to small and medium enterprises. Furthermore, government should also increase its commitment to develop strategies for small and medium enterprises through favorable tax rates and tax exemptions especially to small and medium enterprises dealing with leather products in Kenya.
Our study poses a few limitations and opens the prospect for different lines of future research. The first constraint is about our sample. Most of the firms captured in our study sample are not registered and as such are not required to publish their accounts. Hence not every entrepreneur was willing to provide us with accurate financial information through interview or questionnaire. A future line of fascinating research could be to repeat this same study using registered SMEs where financial information is readily available to the public. Secondly, our variable measure of firm growth is too simple and thus, can be improve upon with a more robust measure of growth. Moreover, future studies can also control for more idiosyncratic firm characteristics to account for possible differences in SMEs. Lastly, the study examined firms in the leather manufacturing industry, so it can be checked whether the results are generalizable to other industries and other countries at large. Therefore, future studies can also consider same variables in different industries such as food and beverage industries from different countries.
I would like to thank Dr. Bismark Addai for his immense contribution and guidance.
Source: Own elaboration
a. Predictors: (Constant), TX, AC, FL b. Dependent Variable: PQ
| R | R Square | Adjusted R Square | Std. Error of the Estimate | Durbin-Watson |
|---|---|---|---|---|
| 0.990a | 0.981 | 0.976 | 0.22513 | 1.879 |
Source: Own elaboration
a. Predictors: (Constant), TX, AC, FL b. Dependent Variable: PQ
| Model | Sum of Squares | DF | Mean Square | F | Sig. | |
|---|---|---|---|---|---|---|
| 1 | Regression | 28.409 | 3 | 9.470 |
175.674 |
0.000a |
| Residual | 0.593 | 11 | 0.054 | |||
| Total | 29.002 | 14 |
Source: Own elaboration
| Factors | Items | Loadings | Indicator Reliability (loading2) | Cronbach | Composite reliability |
|---|---|---|---|---|---|
|
|
AC1 | 0.916 | 0.8396 | 0.915 | 0.937 |
| AC2 | 0.922 | 0.8500 | |||
| AC3 | 0.855 | 0.7315 | |||
| AC4 | 0.873 | 0.7630 | |||
| AC5 | 0.753 | 0.5665 | |||
| AC6 | 0.970 | 0.9417 | |||
| AC7 | 0.970 | 0.9413 | |||
| AC8 | 0.974 | 0.9484 | |||
| AC9 | 0.880 | 0.7744 | |||
|
|
FL1 | 0.898 | 0.8069 | 0.938 | 0.956 |
| FL2 | 0.939 | 0.8816 | |||
| FL3 | 0.946 | 0.8941 | |||
| FL4 | 0.891 | 0.7941 | |||
| FL5 | 0.988 | 0.9761 | |||
| FL6 | 0.893 | 0.7974 | |||
| FL7 | 0.864 | 0.7465 | |||
| FL8 | 0.819 | 0.6708 | |||
|
|
TX1 | 0.974 | 0.9484 | 0.970 | 0.981 |
| TX2 | 0.970 | 0.9413 | |||
| TX3 | 0.932 | 0.8686 | |||
|
|
PQ1 | 0.957 | 0.9167 | 0.867 | 0.919 |
| PQ2 | 0.747 | 0.5587 | |||
| PQ3 | 0.95 | 0.9022 | |||
| PQ4 | 0.794 | 0.6304 | |||
|
|
PC1 | 0.916 | 0.8394 | 0.877 | 0.916 |
| PC2 | 0.753 | 0.567 | |||
| PC3 | 0.873 | 0.7626 | |||
| PC4 | 0.874 | 0.7633 | |||
| PC3 | 0.861 | 0.741321 | |||
| PC4 | 0.912 | 0.831744 |
Source: Own elaboration
| KMO and Bartlett's Test | ||
|---|---|---|
| Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | 0.773 | |
| Bartlett's Test of Sphericity | Approx. Chi-Square | 241.544 |
| df | 276 | |
| Sig. | 0.034 | |
|
a. Does the business require external source of funding? b. Does the credit services offered by the financial institution(s) affect your business performance? c. Is the credit services offered by your financial provider (s) effective?
a. We did not take a loan b. Smaller than 25 c. 25-100 d. 100–500 e. 500-999 f. Over one million Ksh g) Can’t disclose Note: 1 dollar is equivalent to 109.05 Kenyan Shilling
a. Are the interest rate charged on loans high? b. Is the interest rate charged on some loans dependent on the security provided or nature of business? c. Did any of the credit facility require collateral? d. Has your business loan been declined because of lack of collateral security? f. Banks have outlet or branches closer to the business center
a. Above 80% b. From 60% to below 80% c. From 40% to below 60% d. From 20% to below 40% e. Less than 20% f. Can’t disclose
a. To what extent does the type of your credit access affect cost minimization goals? b. To what extent does access to credit affect products quality of your products? c. To what extent does access to credit affect productivity of the business?
a. Level of education has positive influence on when/how to get loans to improve the business b. Education level equips me with the knowledge and skills that are needed to be more effective in managing our business c. Do the employees attend management training programs related to financial management? d. Trainings have enabled me run my business effectively and I have realized an increase in sales and profitability e. Is the business used to keeping records of income and expenditures?
a. To what extent does financial literacy affect cost minimization of your business? b. To what extent does financial literacy affect quality of your products? c. To what extent does is financial literacy affect productivity of the firm?
a. To what extent does taxation affect cost minimization of business? b. To what extent does taxation affect quality of your products? c. To what extent do you think taxes have affected productivity of the business?
a. Does the business carry out simulation-based analyses to identify and fix quality problems early in the manufacturing process in order to minimize the overall cost? b. Does the business have clear-cut quality goals strategically and precisely based on customer requirements? c. Are all the resources, including time, tools, and materials, dedicated to the quality process through developing and sustaining supplier or vendor relationships? d. Does the technological knowhow used in production process help to optimize costs while achieving the quality goals? e. Is the employer/ employees well trained on cost effective management programs? f. Does the business carryout quality management process to optimize the balance between cost and quality? g. Does the business carryout customer satisfaction survey to monitor customer satisfaction? h. Does the business ensure that people know what work they should do through well-established job descriptions? i. Has the cost of production fallen due to increasing returns to scale over the last years? j. Does the business effectively manage the environmental and community needs by ensuring that they shouldn’t suffer for you to do business? |