Tadlo Sintayehu Yimer University of Gondar, Department of Logistics and Supply Chain Management

Determinates of Value Chain performance of Micro and Small Manufacturing Enterprises’ in the case of North Gondar Zone, Ethiopia

Tadlo Sintayehu Yimer University of Gondar, Department of Logistics and Supply Chain management

ABSTRACT Recently, empowering micro and small enterprises through sustainable value chain and market linkage is one of the top ranked issues in Ethiopia taking in to consideration its tremendous contribution to the socio-economic development for the country; however, there is only little focus on analyzing the value chain of manufacturing MSEs to identify the various actors and factor affecting value chain, identify opportunities and challenges for MSEs’ value chain and the role of integrated value chin for the economic development the zone in the North Gondar zone, Ethiopia. The objective of this study is, therefore, to assess and analyze the value chain of MSEs’ manufacturing sectors. To achieve this objective the researcher was employed both quantitative and qualitative research approaches. The target population of the study was all micro and small manufacturing enterprises in North Gondar zone. A survey questionnaire, semi-structured interview, FGD and observation were used as data collection tools. Descriptive statistics, multiple and binary logistics’ regression and factors analysis will be used as techniques of data analysis, and then analysis results was be interpreted accordingly.

Keywords: MSEs, Value chain performance, Manufacturing, North Gondar, Ethiopia

1. BACKGROUND: RELEVANCE AND THE STATE OF KNOWLEDG The idea of a value chain is very simply focused on the activities needed to turn raw materials into finished products and sell them, and on the value added at each link (Kaplinsky & Readman, 2001; UNIDO, 2002). Adopting a value chain approach could help specially micro and small enterprises (MSEs) to gain from the benefits of integration into global/local value chains and making them competitive (Gereffi et al., 2001). It constitutes whole range of discrete, though interrelated, activities involved in the design, production and marketing of a product (Porter, 1985). In recent years, the concept of value chain is widely used as a facilitation tool for integrating small enterprises into

www.theinternationaljournal.org> RJCBS (ISSN:2251-1547) : Volume: 08, Number: 08, June1, 2019 high value market, and its development programs focus on improving the competitiveness of the industry/sector in which the firm operates (Jones, 2011). The core of the value chain approach is the recognition that, the strategies for enterprise development needs to focus on the entire value chain rather than focusing on a particular aspect of provision of credit or input supply. It emphasizes on identifying the opportunities for and constraints to industrial growth by considering the value chain actors (firms), linkages among firms, supporting markets, end markets, and the business enabling environment at all levels (Kula et al., 2006). It is argued that integration into value chains helps the micro and small firms to increase the efficiency of its internal operation, develop inter-firm linkages that reduce transaction costs and upgrade along the value chain (introduce product branding, new products, and improved version of existing products in the market faster than the rivals) (Kaplinsky, 2000).

Value chain development issues are very relevant to developing countries as traditional production systems are usually isolated and struggle to build relationships with local, regional or global markets. In particular, small-scale entrepreneurs or micro and small enterprises (MSEs) find it difficult to leverage market opportunities provided by advances in information, technology and communication, as well as globalization. Particularly over the last decades, the world has witnessed a gradual relocation of manufacturing activities from developed to developing countries, opening up new opportunities for employment, increased income and economic growth for some of the world’s poorer and less developed countries. However, the process of industrialization has not benefitted all developing countries equally. In the 2009 Industrial Development Report, UNIDO makes a distinction between the countries of the ‘bottom billion’ trying to break into global markets for manufactured goods, and the middle-income countries attempting to move up to more sophisticated manufacturing since the manufacturing sector has got a national and international concern in employment creation and encouraging exports with import substitution of very important manufacturing products.

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Various studies also confirm the importance of value chain analysis specifically for MSEs to assess and identify their competitiveness (Kebede & Abera, 2014, Reji, 2013, Gereffi et al., 2001). The concept of value chain emerged from the realization that appreciable and continual improvements in system design and performance can only occur when businesses seek closer coordination and integration with suppliers and customers than traditional, transactional buyer- seller relationships allow. Developing closer strategic relationships with customers and suppliers through value chain enables businesses to learn and adapt more effectively and this helps even to achieve national development plans (CAPI, 2012). Similarly, the government of Ethiopia is implementing a growth and transformation plan (GTP) as a strategic framework to boost growth in different sectors. As stated in the 2010/11 to 2014/15 GTP plan, one of the major target of the strategy is to conduct training and research for about three million operators in the areas of entrepreneurship, handicraft, technical and manufacturing. Therefore, analysis of value chain specifically on manufacturing micro and small enterprises is one of the eye-catching areas to fight poverty

Value chain analysis offers a theoretical framework to understand the integration of firms into viable market system (Gereffi et al., 2001). Value chain studies, mostly dealt with the process of integration of developing country firms into the value chain of large firms in developed countries, examined the inter-firm relationships, governance and upgrading practices by which firms improve their competitiveness. It is well established that integration into value chain helps the small firms to create opportunities and improve their competitiveness. However, how far these new windows of opportunities are available to small producers is relatively unexplored (Reji, 2013). Moreover, according to Gebrehiwot and Wolday (2006) integration of micro and small scale producers into high value market is a topic of current interest.

In Ethiopia, micro and small enterprises (MSEs) sector is the second largest employment- generating sector following agriculture (CSA, 2008). According to CSA (2008) the sector

www.theinternationaljournal.org> RJCBS (ISSN:2251-1547) : Volume: 08, Number: 08, June1, 2019 contributes 3.4% of GDP, 33% of the industrial sectors contribution and 52% of the manufacturing sector’s contribution to the GDP. In spite of the enormous importance of the MSEs sector to the national economy with regards to job creation and the alleviation of abject poverty in Ethiopia, the sector is facing various challenges, which impeded its role in the economy (Kebede & Abera, 2014). However, Penny et al. (2013) states that to integrate the value chain of small firms in developing countries to participate in international trade with the full range of capabilities, it is necessary to identify the various local factors since there is no one- size-fits-all. Moreover, in Ethiopia the underlying factors affecting MSEs’ value chain are not well addressed (Debele & Verschuur, 2014). Hence, this study will identify the various local factors and actors that affect the MSEs’ value chain performance in the study area.

In addition, MSEs’ manufacturing products are marketed through different channels. However, the concept of its value chain is not well known in Ethiopia and it doesn’t meet even the domestic demand for manufacturing products (Debele & Verschuur, 2014). As a result the country imports large volumes of manufacturing products per annum to meet the domestic demand. Thus, a comprehensive chain aimed at sustainable development of the manufacturing sector is lacking. To build a successful and sustainable manufacturing sector, all possible entry points for intervention across the value chain have to be identified (Penny et al., 2013). Thus, this should be investigated to make sure that different parts of the value chain need different kinds of support and interventions.

Moreover, in Ethiopia, value chain studies were conducted for livestock, sesame seeds, milk, honey, teff, fruits and vegetables, poultry and other products in different localities (Getnet, 2010). But the manufacturing sector (the sector with a bright prospect) is neglected and there is no research to date on this sector. 2. OBJECTIVE OF THE STUDY The general objective of the study is to assess and analyze the value chain of MSEs’ manufacturing sector in North Gondar zone.

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Typically the study has the following specific objectives  To measure the extent of factors affecting MSEs’ value chain performance.  To discuss opportunities and challenges in various stages of the MSEs’ value chain.  To describe the role of value chain factors in local economic development 3. RESEARCH QUESTIONS The broadly stated as well as the specified objectives call for the formulation of basic research questions. Therefore, the following basic and interrelated questions are raised in an attempt to meet the objectives and also guide the course of this research:  What does manufacturing MSE value chain look like in North Gondar Zone?  What major challenges (external) confront the existence/operations of MSEs and their value chains?  What are the major areas of upgrading and forms of inter-firm relations in the manufacturing MSE sector?  What do MSE value-chains contribute to local economic development?

4. SCOPE OF THE STUDY In recently, the concept of value chain is widely used as a facilitation tool for integrating micro and small enterprises in to high value market especially in developing countries. This study will focus on assessment and analyzing the value chain of manufacturing MSEs which are engaged in metal work, wood work, garment, and food and beverage sub sectors in north Gondar zone. The justification of focusing only on manufacturing sector is that the sector has got a national concern in employment creation, encouraging export with import substitution of very important manufacturing products. Besides, the studies also identify opportunities and challenges that positively and negatively affect of MSEs by using Porters’ value chain model. Moreover, the study will focus the role of having integrated value chain for the job creation and livelihood improvement of entrepreneurs at large.

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5. RESEARCH METHODS AND MATERIALS I. Description of the study area The state of Amhara is located in the north western and north central part of Ethiopia. The state shares common borders with the state of Tigray in the north, Afar in the east, Oromia in the south, Benishangul in the south west and the republic of Sudan in the west. North Gondar zone is found in this region and basically includes the Debark, Aykel and Genda-Wuha districts, in which this project proposal is directed to. The three districts are among 105 districts in the region.

North Gondar is bordered on the south by Lake Tana, West Gojjam, Awi and the Benishangul- Gumuz Region, on the west by Sudan, on the north by the Tigray Region, on the east by Wag Hemra and on the southeast by Debub Gondar. This study mainly focuses on 3 major districts of N/Gondar zone; particularly in Debark, Ayikel and Genda-Wuha districts. These three districts are highly dependent on agriculture and now have started diversifying of their economy through the involvement of MSEs in different activities; such as manufacturing, service and other activities. Therefore, any attempt to minimize dependency on single economy should be supported with a research of this kind to improvement of income diversification or livelihood options and productivity through sustainable value chain of Manufacturing MSEs. Map of the study area

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II. Research design The design of this study was cross-sectional in which data has been shot at a single moment and be analyzed to get findings. To address the objectives stated in the very beginning of this research proposal, questionnaire, interview and observation and focus group discussion will be used as a data gathering methods. Thereby, the researcher used make triangulation to cross validate, confirm and corroborate of the findings within the study (Creswell, 2003). III. Research approach Mixed research paradigms help to make the data collection and analysis more accurate and the inference more useful because it can represent a plurality of interests, voices and perspectives (Patton, 2002). Correspondingly, qualitative and quantitative methods was applied in this research to analyze data that helps to collected from different sources. However, ideologically the priority for quantitative and qualitative data is given equal importance but practically the emphasis is given for qualitative or quantitative (Creswell, 2003). In line with this prevailing fact and so as to meet the research objective of this particular research, the quantitative approach will features much. Besides, this priority is also given because of in business and social responsibility research, qualitative approach may offer an epistemological potential to the research field (Saunders, M. 2009).

IV. Target population The target population of the study was micro and small scale manufacturing enterprises of North Gondar zone. The report from Technical and Vocational Development Office (2013) for North Gondar zone indicates that there are 2180 micro and small manufacturing enterprises in North Gondar zone. In these districts, there are four major types of manufacturing enterprises: metal work, wood work, food and beverage, and garments. The justification behind selecting manufacturing sector is that the sector has got a national concern in employment creation, encouraging export with import substitution of very important manufacturing products. More specifically, the issue is the interest of the Technical and Vocational Development Office of North Gondar zone.

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V. Sample size and sampling technique for survey questionnaire The ultimate objective of sampling is to select a set of elements from a population. Godden (2004) states that to calculate the sample size for infinite population (population > 50,000), the level of precision (sampling error), the level of confidence interval, and the degree of variability in the attributes being measured should be considered. Therefore, for this study:  Confidence level of 95%  Degree of variability (sample proportion) 50% (p)  Maximum tolerable error (sampling error) was 5% (w). Based on the above assumptions, the sample size (SS) for very large population can be calculated as follows: SS = Z2 x (p) x (1 – p) W2 Where: ‘Z’ is 1.96. Since the value of ‘Z’ is depend on tolerable error. SS = (1.962) x 0.5 x 0.5 = 384 0.052 However, the target population in this study is 2180 which is finite according to Godden (2004). Therefore, based on the finite population correction formula the sample size for this study can be reduced as follows:

Moreover the researcher add 10 % of the total sample size for the non response rate and incomplete questionnaire . Therefore the total sample of this study will be 368. Sampling techniques: The study was used a two-stage sampling procedure to select respondents and for distributing survey questionnaire: stratified and simple random sampling techniques sequentially were used. In the first stage, micro and small manufacturing enterprises were be stratified based on the nature of the business (metal work, wood work, food and beverages, and garment). Stratified sampling techniques applied here because according to Creswell (2003) it can ensure that specific groups are represented, even proportionally, in the sample.

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As far as the second sampling stage concerned, micro and small manufacturing enterprises from all woredas will be selected by using simple random sampling technique based on the number generated using random number generator, and then they were contacted based on their address. Simple random sampling technique was used because it provides an equal chance of selection for each element of the population (Blumberg et al., 2011). However, the concept of proportionate sampling was applied to eliminate non-representativeness distortions for each sector in all

woredas. The proportionate ratio is 0.135 ( ).

Table 1: Application of proportionate sampling for each sector and district

No manufact Sector Name of the uring Garment Metal work Wood work Food and beverages Sub woredas total popul Sample Population Sample Population Sample Population Sample ation (13.5%) (13.5%) (13.5%) (13.5%) (13.5%) (13.5%) (13.5%) 1 Gondar Ketema 324 74 10 80 11 92 12 78 11 44 2 Debark ketema 91 37 5 22 3 16 2 16 2 12 3 Aykel 92 27 4 15 2 31 4 19 3 13 4 Metema 142 46 6 29 4 14 2 53 7 19 5 Gende weha 20 3 1 7 1 4 1 6 1 4 6 West Armachiho 72 18 3 23 3 16 2 15 2 10 7 chiliga 163 42 6 43 6 32 4 46 6 22 8 Dembia 241 70 10 54 7 39 5 78 11 33 9 Gondar zuria 102 25 4 26 4 37 5 14 2 15 10 Takusa 138 37 5 23 3 45 6 33 5 19 11 Alefa 93 27 4 16 2 35 5 15 2 13 12 West Belesa 199 52 7 49 6 38 5 60 8 26 13 Quara 69 23 3 9 1 21 3 16 2 9 14 Wogera 53 16 2 7 1 15 2 15 2 7 15 Dabat 44 8 1 13 2 10 1 14 2 6 16 Debark 20 7 1 3 1 5 1 5 1 4 17 Lay Armachiho 201 57 8 44 6 46 6 54 7 27 18 Tach Armachiho 75 18 3 20 3 17 2 20 3 11 19 Adi Arkay 108 27 4 28 4 38 5 15 2 15 20 West Armachiho 40 12 2 7 1 15 2 6 1 6 21 Beyeda 22 7 1 3 1 5 1 7 1 4 22 Telemt 53 9 2 15 2 17 2 12 2 8 23 Tegede 53 11 2 13 2 20 3 9 1 8 24 Janamora 55 19 3 21 3 13 2 12 2 10 Total 2470 672 91 570 77 621 83 618 86 341

Source: Organized by researcher, 2018

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VI. Sampling Technique for key Informant Interview To triangulate the survey questionnaire result from the micro and small manufacturing enterprises, the researcher was conducted key informant interview from officials of Technical and Vocational Development Office (TVDO) in all woredas. Accordingly, two officials from the concerned management body of the zone office was selected interviewed purposively. Moreover, one value chain expert was interviewed in each woreda. To select the interviewees, the researcher was employed purposive sampling technique to get the needed information from the experts. VII. Sampling Procedure for Focused Group Discussion Focused group discussion is a rapid assessment, semi‐structured data gathering method in which a purposively selected set of participants gather to discuss issues and concerns based on a list of key themes drawn up by the researcher/facilitator and usually a group member of 6-12 is used within one FGD (Zikmund, 2009). Hence, in this study, mainly respondents that were not be included and addressed in the survey questionnaire were under FGD participants to learn from the target population. The composition of the FGD each woreda with a minimum of two successful enterprise in each sector (metal, wood, garment and food and beverages).and concerned government officials and organizations were selected purposely. VIII. Methods of Data Collection The methods of data collection to be used in this study include focus group discussion, semi- structured interview, questionnaire (open ended and close ended) and observation and focus group discussion. In this study, the research was observeed the challenges and the prospects of value chain at each stage as observation enable to record the behavioral patterns of people, objects, and occurrences as they happen (Zikmund, 2009). The research also used semi-structured interview in order to get basic data on the institutional arrangements and know the performance level of the enterprises. The interview was conducted with value chain experts in each woreda and officials from the concerned management body of the North Gondar zone. The rationale behind using interview is that through the help of this tool, we can gather valid and reliable data that can be relevant to our research question(s) and

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objectives (Saunders, 2009). Additionally a questionnaire was used to collect data on the key actors and the different factors affecting value chain of MSEs. Lastly, focus group discussion was applied in order to get data on the interventions to be implemented at each stage of the value chain and recent innovation activities in relation to MSEs’ future prospects. IX. Methods of data analysis In this study descriptive statistics was used as the first stage of the analysis of data to provide detail information about each relevant variable used (age, gender, number of employees, experience of the enterprise owner, the value chain stages the business applies). At this stage, mean, standard deviation, maximum and minimum values of the required variables will be computed. The study also used qualitative analysis methods in order to analyze the data to be collected by using focus group discussion, interviews and observation. This helps to triangulate results by considering the specific objectives. According to Creswell (2003) triangulation could result in well-validated and substantiated findings through crosschecking the findings of a single approach with others wherever possible. Moreover, the study also used a multiple regression and factor analysis to measure the simultaneous impact of the various factors affecting value chain of manufacturing MSEs and the economic contribution of integrated value chine for entrepreneurs livelihoods improvement and job creation. Furthermore, multiple regression and a mean-comparison tests were employed for comparing the performance of the four manufacturing sectors (metalwork, woodwork, food and beverage and garment).

X. Validity and Reliability of Research Instruments Reliability and validity are the basic principles of social research. A valid measure produces true results that reflect the true situation and condition of the environment that is supposed to study (Blumberg et al., 2011). Therefore, in this study, validity was checked by distributing the questionnaire to senior researchers and by reading various relevant literatures to understand and correctly measure since the items must be consistent with theory and the concept under study. 11

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To achieve reliability, the questionnaire was verified for accuracy and completeness of all the items. Each question was framed succinctly to reduce ambiguity and minimize bias, thereby ensuring the high statistical value of the data. In order to ensure that the questions in the questionnaire reliably measured, Cronbach's alpha will be run using STATA. The value of Cronbach's alpha ≥ 0.6 will be considered as acceptable (Yoshida & James, 2010).

4. RESULTS AND DISCUSSIONS 4.1. Discussion on Demographic variables

The study was sought to establish the information on the respondents employed with regards to the gender, age, their level of education and duration of service. The study participants were 88.9 percent of males and 8.9 are females who are engage in garments (53.3%) , wood work (26.7%), metal work (8.9 %) and food and beverage (6.7%). The educational background of the enterprise owners are majorly below grade 10 (42.2) and 10 completed (37.8%) under the age bracket of 21-30 and 31-45 years of old who has working service on 2 to 5 years (54.6%) and above 5 years (31.8%). This implies that micro and small scale enterprises are running by low education level owners which makes the enterprises are not performed well even to have more than 2 years service experience since establishments. One important thing observed in this study is the owners who run business are productive labor age even though they do have educational gaps to run businesses.

4.2.Basic variables of the study : Correlations and regressions result Value chain performance is positively correlated with enabling environment, supportive market, and vertical integration and horizontal integration at 1 percent. The correlation result shows that enabling environment is correlated with supportive markets, vertical integration and value chain performance at 1 percent level of significance. Support market is correlated with vertical integration and value chain performance at 1 percent level of significance. vertical integration is correlated with horizontal integration is significant at 5 percent and vertical intergradations is

www.theinternationaljournal.org> RJCBS (ISSN:2251-1547) : Volume: 08, Number: 08, June1, 2019 correlated with value chain performance at 1 percent significance. Horizontal integration is correlated with value chain performance and service institutions at 1 percent level of significance. The value chain performance in micro and small scale enterprises is good (2.09) in terms of suppliers’ evaluation, horizontal integration, supportive markets, enabling environment, and vertical integrations. However, the service of institutions is poor for micro and small scale enterprises like cooperatives, insurance and customs operations.

Table 6.1. Correlation result

Enabl ing vertica envir supporti l onme ve integra Horizontal Value chain institutional Supplier Local economic nt service tion integration performance service evaluation development ENEVT 1 .525** .538** .117 .490** -.019 -.127 .022 .000 .000 .445 .001 .900 .404 .885 SUPPTSE 1 .565** .106 .524** .158 .041 -.340* R .000 .488 .000 .301 .791 .022 VERINTG 1 .317* .462** .146 .259 -.212 .034 .001 .340 .086 .162 HORINTG 1 .538** .579** .273 -.132 .000 .000 .070 .388 VCPER 1 .275 .097 .174 .068 .526 .254 INSSERV 1 .217 -.275 .152 .068 SUPEVAL 1 -.029 .848 ECO 1

** Correlation is significant at the 0.01 level (2-tailed)., * Correlation is significant at the 0.05 level (2-tailed).

The regression result shows that about 65.5 percent of value chain performance is explained by enabling environment, horizontal integration, vertical integration, support market, institutions service, and supplier evaluations and local economy. Here Support market and horizontal

www.theinternationaljournal.org> RJCBS (ISSN:2251-1547) : Volume: 08, Number: 08, June1, 2019 integration have positive and significant effect on value chain performance at 5 percent and 1percent respectively. As indicated the ANOVA table indicated that Value chain performance and supportive service has positive and significant impact on local economic development. This results that if micro ad small scale manufacturing enterprise has emphasized on value chain analysis and look through the supportive services it results that the local economic development has been improved. As indicated in the one sample test the mean value of enabling environment and institutional service is poor. This implies that, micro and small scale manufacturing enterprises has no conducive working environment to run businesses in terms of transport, taxation, rules and regulations, water supply, electricity, telecommunication and sewerage facilities and services. In addition to this, micro ad small scale an enterprise has been faced a problem of institutional services like cooperatives and unions, customs operation systems. Micro and small scale enterprises should improve horizontal integration to have cooperation with other sectors and entrepreneurs in order to solve problems and challenges, to create conducive working environment, and increase purchasing power in the market. Besides to this, micro and small scale enterprises should work together with customers in terms of product design, sufficient credit availability, raw materials, training, and consultation and demand of products in support market. Table 6.2. Regression results

Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .841a .707 .651 .26214 a. Predictors: (Constant), ECO, ENEVT, SUPEVAL, HORINTG, INSSERV, SUPPTSER, VERINTG b. Dependent Variable: Value chain performance

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ANOVA

Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) -1.600 .582 -2.748 .009 ENEVT .074 .081 .112 .915 .366 SUPPTSER .340 .078 .536 4.339 .000 VERINTG .021 .072 .038 .296 .769 HORINTG .271 .061 .517 4.416 .000 INSSERV .008 .053 .018 .158 .875 SUPEVAL -.048 .091 -.053 -.523 .604 ECO 1.158 .271 .433 4.269 .000

5. CONCUSSIONS AD RECOMMENDATIONS Conclusion Value chain performance in micro ad small scale enterprises is influenced by a number of factors like enabling environment, supportive service, vertical integration, Horizontal integration, Supplier evaluation, institutional service, and Local economic development. Value chain performance is positively correlated with enabling environment, supportive market, and vertical integration and horizontal integration at 1 percent. The working environment is not enabling and institutional services has problems in micro and small scale manufacturing enterprises Micro and small scale manufacturing enterprises Value chain performance has positive and significant impact on local economic development A micro and small scale enterprise has faced a number of challenges like infrastructure, institutional bureaucracy, marketing and capital. However, having these challenges in the study area micro ad small scale manufacturing enterprises have huge opportunities in job creation, capital accumulation and business development.

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Recommendations The government should make emphasis on value chain performance of micro ad small scale manufacturing enterprises in order to have competitive advantage The government needs to improve enabling environment and institutional linkages in order to enhance the enterprises in the market To exploit opportunities of micro and small scale enterprises in value chain analysis the stakeholders need to emphasis on actors integrations

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