Examining significant factors in micro and small enterprises performance: case study in Amhara region, Ethiopia

Since 2001, micro and small enterprises (MSEs) in Ethiopia have been confronted with several factors that affect their performance. Major factors include financial problems, lack of qualified employees, lack of proper financial records, marketing problems and lack of work premises, etc. Besides, environmental factor affects the business which includes social, economic, cultural, political, legal and technological factors. In addition, there are also personal attitudes or internal factors that affect the performance of MSEs, which are related to the person’s individual attitude, training and technical know-how (Werotaw 2010). These factors were supported in the study undertaken by Heslina et al. (2016) as entrepreneurial characteristics have significant influence on business performance through business growth strategy and entrepreneurial competence. Olughor (2015) also pinpointed that the role of innovation, which is part of entrepreneurial characteristics, in small and medium enterprises, is essential for the development of business performance.

Furniture manufacturing micro and small enterprises (FMMSEs) are mostly low technology enterprises, which are labor intensive. Even though furniture manufacturing MSEs in Ethiopia have a large economical share in national GDP, some enterprises fail to sustain, and some others remain for a long period of time without transforming into middle level enterprise. When we see most of the furniture manufacturing MSEs, they are producing similar and non-standard products and are not showing competitive performance improvement. Thus, the aim of this paper is to conduct a study that identifies the major factors that affect performance and examines the factors’ correlation and impact using statistical tools.

Micro and small enterprise development projects can serve four major objectives: poverty reduction, empowerment of women, employment generation and enterprise development as an end in itself (FDRE 2010; UN Economic Commission for Africa 2008; Moyi 2013; Markos et al. 2015; Brenda and Gregory 2015). Habtamu et al. (2013) noted MSEs do serve as a means of bringing economic transition by using the skill and the talent of people without requiring high-level training, much capital and sophisticated technology. For people in developing countries, small and micro enterprises are the sources of income, employment, skill development, goods and services delivery, etc. (Anne 2014; Semistatus and Rainer 2014; Markos et al. 2015). MSEs are one of the priorities among the programs addressing African development (UN 2008), and are seen as a means of achieving smooth transition from tradition to modern industrial sector and have a huge contribution to the growth and development of the country in terms of employment generation with a relatively low capital cost (Stephen and Wasiu 2013). In light of this, GFDRE has recognized the contributions of MSEs to the national development efforts, and MSEs’ strategy was formulated and implemented since 1997 (MSE 2011). During the first MSEs’ development strategy (1997–2002) more than 1.5 million people were employed. But plenty of studies indicated that there are many internal and external challenges facing MSEs in their operations which hold back their growth in Ethiopia (MoUDC 2011). A hard look at various studies has revealed a number of deterrents to the growth and survival of the MSEs.

MSEs in Ethiopia have also been confronted with a number of challenges that obstructed their success. Mekonnen et al. (2013) had pinpointed that inadequate infrastructure facilities, inadequate finance, poor managerial and technical skills, and inadequate working premises were the major challenges to MSEs’ successful operations followed by marketing problems, low support from respective institutions, inadequate supply of raw materials, and regulatory issues. According to Commission on Legal Empowerment of the Poor (2006) study, most MSEs in Ethiopia face critical constraints both at the operation and start-up level. Some of these constraints include lack of access to finance, access to premise, infrastructure, training in entrepreneurial and management skills, information on business opportunities, and social and cultural factors particularly related to deficient entrepreneurial culture and excessive corruption. Devereux and Sharp (2006) as cited in Zeleke (2009), and Mbonyane and Ladzani (2011) identified that lack of access to finance is the most influential factor from among all adverse factors hindering the growth and development of the MSE sector in most countries. Furthermore, Haftu et al. (2009) found that lack of finance and working space rank high as the major constraints faced by a large proportion of the enterprises. This result is supported by Hailemichael (2014) and Amasu (2012) that working premises, marketing and financial factors were the major factors significantly affecting performance of MSEs in Addis Ababa.

The study conducted by Ethiopian CSA discloses that the contribution of small enterprises in creating job opportunities and in the development of our economy is vital (CSA 2007). However, their contribution is very low as compared to that of other countries’ due to various reasons. The productivity of furniture manufacturing MSEs is not competitive enough and mostly follows the usual production process. Though these shortcomings may be result of different factors, there is no well conducted and documented studies on the field. Generally, there are external (contextual) and internal factors, which are still affecting performance of furniture manufacturing MSEs. Therefore, this study is designed to identify and analyze the main factors that affect the performance of these furniture manufacturing MSEs.

The study has a general objective of identifying significant factors affecting the performance of the furniture manufacturing MSEs and examining the factors’ impact and correlation. It is also to conduct impact-effort analysis on the identified factors of the field for prioritization in addressing them.

Data was collected from both regional and cities administration selected technical and vocational enterprise development departments with the involvement of concerned officials and MSE operators. During data collection time, physical observation of the general work area and way of doing the business has been done on the selected enterprises. Besides, a questionnaire was prepared by the researchers for randomly selected enterprises at an average of 15 furniture manufacturing MSEs under each town of the selected eight cities in the Amhara region. Totally, 120 MSEs were observed and each individual enterprise’s owners/managers were made to respond to questionnaires prepared for them, especially related to the challenges enterprises face. Discussion was also done with the enterprise owners and MSEs coordinators on each selected area through interview questions. This is basically designed in order to get additional information regarding the working condition, the performance level and the challenges that MSEs are faced with. Focussed group discussion with selected groups from MSEs office experts in the area at urban level and sub-city level was also accomplished and valuable information was collected to reinforce the data analysis process.

To analyze collected primary and secondary data, statistical process control application package called SPSS has been used for correlation and impact analysis with its correlation module and hierarchical clustering approach respectively to find out the factor correlations and their impact among factors for MSEs. Correlation analysis was applied based on the factors Pearson correlation ‘r’ value and Statistical significance p value. Factors having a strong positive r value and statistically significant with a significance level of 0.05 and 0.01 (or with confidence level of 95 and 99%) has been selected as variables that should be considered for impact cluster analysis. Proximity test was the most valuable tool used to identify how much factors have a proximity distance with other factors related to it. Based on small proximity distance between factors, important findings were found for the cluster impact analysis. Finally, impact-effort matrix made by combining separate impact and effort analysis results which indicates how much effort those factors will require and impacts made for the MSE’s.

It is known that a lot of effort has been made by the government to improve the performance and contribution of MSEs in poverty reduction, industrial transformation, and reduction of unemployment and overall economic development. Despite MSEs playing a great role so far, the performance and the impact on economic development are not based on the expected level. MSEs are still facing severe constraints in their activities and their promotion and development are, therefore, hampered.

In this study, internal and external factors affecting the performance of MSEs are examined and identified with their impact level. Among the ten factors which are preliminarily selected for examination, the factors which show strong positive relationship (highly correlated) are politico-legal with infrastructure, leadership with entrepreneurship skills and finance and credit with marketing factors, with Pearson correlation values of r = 0.988, 0.983, and 0.939, respectively.

From the impact analysis made, it is revealed that factors which are highly correlated have a high impact on each other, and addressing one of the correlated factors leads to reduction of challenges by the other factor on the performance of MSEs. Work premises, access to finance, infrastructure, entrepreneurship and business managerial problems are found to be the most critical factors. The study found that these factors took majority of the share for the causes of 50% drop-out. The study also shows that even though working areas are built, around 65% of the MSEs did not start work due to lack of facilities in the sheds. Moreover, due to infrastructure problem of daily power interruption, 25% of their work time is lost.

Though internal and external factors have impact on each other, internal factors need less effort to address. It is shown that addressing internal factors could promote the overall performance by more than 30%. Therefore, MSEs are recommended to focus and strive on solving the internal factors by themselves rather than waiting third party solutions as of the external factors. Moreover, by applying the impact-effort matrix analysis tool could help MSEs to prioritize affecting factors.