VALUE CHAIN ANALYSIS OF VEGETABLES: THE CASE OF

HABRO AND KOMBOLCHA WOREDAS IN OROMIA REGION,

ETHIOPIA

M.Sc. Thesis

ABRAHAM TEGEGN WOLDESENBET

May, 2013

Haramaya University

VALUE CHAIN ANALYSIS OF VEGETABLES: THE CASE OF

HABRO AND KOMBOLCHA WOREDAS IN OROMIA REGION,

ETHIOPIA

A Thesis Submitted to School of Agricultural Economics and

Agribusiness, School of Graduate Studies

HARAMAYA UNIVERSITY

In Partial Fulfillment of the Requirements for the Degree of

MASTER OF SCIENCE IN AGRICULTURE

(AGRICULTURAL ECONOMICS)

By

ABRAHAM TEGEGN WOLDESENBET

May, 2013

Haramaya University

II

APPROVAL SHEET

SCHOOL OF GRADUATE STUDIES

HARAMAYA UNIVERSITY

As Thesis Research advisors, we hereby certify that we have read and evaluated this thesis

prepared, under our guidance, by Abraham Tegegn entitled Value Chain Analysis of

Vegetables: The Case of Habro and Kombolcha Woredas in Oromia Region,

Ethiopia. We recommend that it be submitted as fulfilling the thesis requirement.

Dr. Lemma Zemedu _________________ _______________

Major Advisor Signature Date

Dr. Mengistu Ketema _________________ _______________

Co-Advisor Signature Date

As member of the Board of Examiners of the M.Sc. Thesis Open Defense Examination,

We certify that we have read, evaluated the Thesis prepared by Abraham Tegegn and

examined the candidate. We recommended that the Thesis be accepted as fulfilling the

Thesis requirement for the Degree of Master of Science in Agriculture (Agricultural

Economics).

______________________ _________________ _______________

Chairperson Signature Date

______________________ _________________ _______________

Internal Examiner Signature Date

______________________ _________________ _______________

External Examiner Signature Date

III

DEDICATION

I dedicate this thesis manuscript to my families for their continuous contribution

throughout my life.

IV

STATEMENT OF AUTHOR

First, I declare that this thesis is my own work and that all sources of materials used for

this thesis have been duly acknowledged. This thesis has been submitted in partial

fulfillment of the requirements for M.Sc. degree at Haramaya University and is deposited

at the University Library to be available to borrowers under rules of the library. I solemnly

declare that this thesis is not submitted to any other institution anywhere for the award of

any academic degree, diploma, or certificate.

Brief quotations from this thesis are allowable without special permission provided that

accurate acknowledgement of the source is made. Requests for permission for extended

quotation from or reproduction of this manuscript in whole or part may be granted by the

head School of Agricultural Economics and Agribusiness or the Dean of the School of

Graduate Studies when in his/her judgment the proposed use of the material is in the

interest of scholarship. In all other instances, however, permission must be obtained from

the author.

Name: Abraham Tegegn Signature:

Place: Haramaya University, Haramaya

Date of submission: May, 2013

V

BIOGRAPHICAL SKETCH

The author was born on 3rd

March, 1983 in Gojeb town of- Kafa zone, SNNP region. He

attended his elementary and junior education at Gojeb and Diry Goma primary and junior

secondary schools at Gojeb and Diry towns respectively, and Secondary School in Gimbo

Senior Secondary School in Gimbo town. After successful passing ESLCE, he joined

Mekelle University in 2003 and graduated with B.Sc. in Natural Resource Economics and

Management (NREM) in 16th

July, 2006. After graduation he served in Chena Woreda

Office of Agriculture and Rural Development for one year and in Kafa Development

Forum Office for about four years. He joined Haramaya University in October 2011 to

pursue his M.Sc. degree in Agricultural Economics program.

VI

ACKNOWLEDGEMENTS

I am indebted to many individuals for their help and encouragement rendered while

conducting this study. First, I would like to appreciate my major advisor Dr. Lemma

Zemedu and my Co-advisor Dr. Mengistu Ketema for their valuable comments, guidance

and encouragement from proposal write up and questionnaire development up to

submission of the final thesis write up.

I would like to thank CASCAPE project at Haramaya University for financial grant for my

research works. It is a great pleasure to extend my appreciation to staff members of

CASCAPE project for their facilitation of the study process and encouragement. I would

like to thank all staff members and development agents of Habro and Kombolcha Woreda

Agriculture and Rural Development offices for their permission and cooperation to use

available data from Woreda offices and all sample respondents for this study.

Above all, I thank the Almighty God for giving me health and strength for the completion

of the study.

VII

ABBREVIATIONS AND ACRONYMS

ADLI Agricultural Development Led Industrialization

BoARD Bureau of Agriculture and Rural Development

CASCAPE Capacity Building for Scaling Up of Evidence Based Best Practices in

Agricultural Production in Ethiopia

CSA Central Statistical Authority

DA Development Agent

EHDA Ethiopian Horticultural Development Agency

GDP Gross Domestic Product

GMM Gross Market Margin

GTP Growth and Transformation Plan

IIA Independent Irrelevant Alternative

MNL Multinomial Logit

MoFED Ministry of Finance and Economic Development

NGO Non Governmental Organization

NMM Net Marketing Margin

OLS Ordinary Least Square

OoARD Office of Agriculture and Rural Development

OCSI Oromia Credit and Saving Institution

OoTI Office of Trade and Industry

PSNP Productive Safety Net Program

RMA Rapid Market Appraisal

VIF Variance Inflation Factor

VIII

TABLE OF CONTENTS

DEDICATION III

STATEMENT OF AUTHOR IV

BIOGRAPHICAL SKETCH V

ACKNOWLEDGEMENTS VI

ABBREVIATIONS AND ACRONYMS VII

LIST OF TABLES XI

LIST OF FIGURES AND MAPS XII

LIST OF TABLES IN THE APPENDIX XIII

ABSTRACT XIV

1. INTRODUCTION 1

1.1. Background of the Study 1

1.2. Problem Statement 3

1.3. Research questions 5

1.4. Objectives of the Study 5

1.5. Scope and Limitations of the Study 5

1.6. Significance of the Study 6

1.7. Organization of the Thesis 6

2. LITERATURE REVIEW 7

2.1. Definitions and Concepts in Vegetables Value Chain Analysis 7

2.1.1. Market chains versus value chains 9

2.1.2. Major concepts guiding agricultural value chain analysis 10

2.1.2.1. Effective demand 10

2.1.2.2. Production 10

2.1.2.3. Value chain governance 11

2.1.2.4. Value chain upgrading 12

2.1.3. Market and marketing 13

2.1.3.1. Marketing efficiency 13

2.1.3.2. Marketing channel 13

2.1.3.3. Marketing performance 14

2.1.3.4. Measuring value chain 15

2.2. Benefit of Value Chain in Agricultural Sector 15

IX

TABLE OF CONTENTS (Continued)

2.3. Developing Value Chain Systems towards the Benefits of the Poor 16

2.5. Development of Market-Driven Vegetable Value Chain 17

2.6. Status of Vegetable Production in Ethiopia 19

2.7. Review of Empirical Studies 19

2.7.1. Value chain approach 19

2.7.2. Determinants of marketable surplus 21

2.7.3. Determinants of market channel choices 22

3. RESEARCH METHODOLOGY 24

3.1. Description of the Study Areas 24

3.2. Types, Sources and Methods of Data Collection 26

3.3. Sampling Procedure and Sample Size 26

3.4. Methods of Data Analysis 27

3.4.1. Descriptive and inferential statistics 27

3.4.1.1. Value chain analysis 27

3.4.1.2. Analysis of vegetable value chain performance 29

3.4.2. Econometric analysis 31

3.4.2.1. Market supply model 31

3.4.2.2. Market outlet choice model 32

3.5. Hypothesis, Variable Selection and Definition 37

3.5.1. Dependent variables 37

3.5.2. Independent variables 37

4. RESULTS AND DISCUSSION 43

4.1. Descriptive Results 43

4.1.1. Demographic characteristics of sample households 43

4.1.2. Production overview 45

4.1.3. Means of livelihood 46

4.1.4. Producers characteristics by the level of market supply 47

4.1.5. Producers characteristics by marketing outlets 50

4.2. Value Chain Analysis 51

4.2.1. Value chain map of vegetables in Habro and Kombolcha Woredas 51

4.2.2. Actors and their role in vegetable value chain 53

X

TABLE OF CONTENTS (Continued)

4.2.2.1. Primary actors 53

4.2.2.2. Supporting actors 59

4.2.3. Value chain governance 61

4.3. Marketing Channels and Performance Analysis 61

4.3.1. Marketing channels 61

4.3.1.1. Tomato marketing channel 62

4.3.1.2. Potato marketing channel 63

4.3.1.3. Cabbage marketing channel 65

4.3.2. Performance of vegetables market 66

4.3.2.1. Tomato market performance 67

4.3.2.2. Potato market performance 70

4.3.2.3. Cabbage market performance 72

4.4. Econometric Model Outputs 74

4.4.1. Determinants of vegetables market supply 74

4.4.2. Determinants of vegetable market outlet choices 79

4.5. Challenges and Opportunities in Vegetables Value Chain 83

4.5.1. Production constraints 84

4.5.2. Production opportunities 85

4.5.3. Marketing constraints 86

4.5.4. Marketing opportunities 87

5. SUMMARY, CONCLUSION AND RECOMMENDATIONS 88

5.1. Summary and Conclusion 88

5.2. Recommendations 90

6. REFERENCES 93

7. APPENDICES 101

Appendix A. Tables 102

Appendix B. Interview Schedules 108

XI

LIST OF TABLES

Table Page

1. Enterprise relations: production chain versus value chain. ............................................. 9

2. Sample size distribution in the sample rural Kebeles ................................................... 27

3. Demographic and socioeconomic characteristics of samples (categorical variables) .... 44

4. Demographic and socioeconomic characteristics of samples (continuous variables) .... 44

5. Type of vegetable crops produced by sample households ............................................ 45

6. Mean productivity of vegetables per hectare ............................................................... 46

7. Statistical test of continues variables by the level of market supply ............................. 48

8. Statistical test of dummy variables by the level market supply .................................... 49

9. Producers by demographic characteristics across marketing outlets ............................ 50

10. Percentage of producers by demographic characteristics across marketing outlets ..... 51

11. Source of vegetable seeds for sample respondents ..................................................... 54

12. Chemical fertilizer use by sample respondents .......................................................... 54

13. Cropping systems, value addition and irrigation use .................................................. 55

14. Post-harvest loss of vegetables in percent of production ............................................ 56

15. Access to services by sample respondents ................................................................. 60

16. Tomato marketing costs and benefit shares of actors ................................................. 68

17. Marketing margins of actors in different marketing channel of tomato ...................... 69

18. Potato marketing costs and benefit shares of actors ................................................... 70

19. Marketing margins of actors in different marketing channel of potato ....................... 71

20. Cabbage marketing costs and benefit share of actors ................................................. 73

21. Marketing margins of actors in different marketing channel of cabbage .................... 74

22. Factors affecting potato production ........................................................................... 76

23. Determinants of vegetables quantity supplied to the market ...................................... 77

24. Coefficients and marginal effects of Multinomial Logit Model for the choice of

marketing outlets ............................................................................................................ 81

25. Major production constraints of vegetable producers ................................................ 84

26. Major marketing constraints of vegetable producers.................................................. 87

XII

LIST OF FIGURES AND MAPS

Figure Page

1. Typical agricultural value chain and associated business development services. ............ 8

2. Geographical location of the study areas ..................................................................... 25

3. Value chain map of vegetables .................................................................................... 52

4. Tomato market channel .............................................................................................. 63

5. Potato market channel ................................................................................................. 64

6. Cabbage market channel ............................................................................................. 66

XIII

LIST OF TABLES IN THE APPENDIX

Appendix tables Page

1. The result of multicillinearity test ............................................................................. 102

2. Hausman tests of IIA assumption for MNL model .................................................... 102

3. Conversion factors used to compute tropical livestock units (TLU) ........................... 103

4. Conversion factor used to compute adult equivalent.................................................. 103

5. Mean land allocation of sample households for different crops in hectare ................. 104

6. Income sources by woreda ........................................................................................ 104

7. Means of transportation for sample respondents ........................................................ 104

8. Market place for selected vegetables ......................................................................... 105

9. Quantity purchased and income of vegetable consumers ........................................... 105

10. Source of extension service ..................................................................................... 106

11. Source of credit by sample farm households in numbers ......................................... 106

12. Need of respondents to expand vegetables production and marketing...................... 106

13. Marketing problems mentioned by traders .............................................................. 107

XIV

VALUE CHAIN ANALYSIS OF VEGETABLES: THE CASE OF

HABRO AND KOMBOLCHA WOREDAS IN OROMIA REGION,

ETHIOPIA

ABSTRACT

This study was aimed at analyzing value chain of vegetables in Habro and Kombolcha

Woredas of Oromia Region with specific objectives of identifying vegetable value chain

and examining the performance of actors in the chain; analyzing the determinants of

vegetable supply to the market in the study area; and identifying marketing channels and

factors affecting outlet choice decisions of farm households. The data were collected from

both primary and secondary sources. The primary data for this study were collected from

162 farmers, 37 traders and 30 consumers through application of appropriate statistical

procedures. The study result showed that vegetable producers are faced with lack of

modern input supply and high postharvest losses. On marketing side, limited access to

market, low price of product, lack of storage, lack of transport, low quality of product and

lack of policy framework to control the illegal Ethio-Somalia trade route are the major

problems. The value chain analysis revealed that the major actors in the Woredas are

input suppliers, vegetable producers, collectors, wholesalers, retailers, exporters and

consumers. Accordingly, the value chain activities in the survey period were input supply,

production, marketing and consumption. It is also found out that vegetable passes through

several intermediaries with little value being added before reaching the end users. The

chain is governed by wholesalers and exporters who have capital advantage over the

other chain actors. Therefore, farmers are forced to capture a lower share of profit

margin. The result of the multiple regression model indicated that marketable supply is

significantly affected by access to market information and quantity of tomato produced in

the case of tomato; access to extension service, access to market information, vegetable

farming experience and quantity of potato produced in the case of potato; and Woreda

dummy, non/off-farm activities, distance to the nearest market and quantity of cabbage

produced in the case of cabbage. The multinomial logit model results also indicated that

the probability to choose the collector outlet was significantly affected by access to

extension service, owning transport facility, membership to any cooperatives and post

harvest value addition compared to wholesale outlet. Similarly, the probability of

choosing retailer marketing outlet was affected by Woreda dummy, educational status of

household head, access to extension service and owning transport facility compared to

wholesale outlet. Therefore, policy aiming at increasing farmers access to modern inputs, developing and improving infrastructure, gender consideration, cooperative development

and improving extension system are recommended to accelerate the chains development.

Key words: Value chain analysis, Vegetables, Actors, Multiple regression model,

Multinomial logit model.

1

1. INTRODUCTION

1.1. Background of the Study

Agriculture is the main stay of Ethiopian economy contributing about 43% of the GDP,

80% of employment and 90% of the export (MoFED, 2011). Having all these importance,

agriculture continues to face a number of problems and challenges. The major ones are

adverse climatic conditions, lack of appropriate land use system resulting in soil and other

natural resources degradation, limited use of improved agricultural technologies, the

predominance of subsistence agriculture and lack and/or absence of business oriented

agricultural production system, limited or no access to market facilities resulting in low

participation of the smallholder farmers in value chain or value addition of their produces

(Bezabih, 2010).

Ethiopia adopted Agricultural Development Led Industrialization (ADLI) development

strategy in 1994/95. The strategy argues that growth starts from agriculture and initiates

the growth of other sectors especially the industry sector through backward and forward

linkages (MoFED, 2006). Furthermore, Ethiopia launched and commenced implementing

earnestly its Growth and Transformation Plan (GTP) in 2009/10. GTP envisages the ADLI

strategy to continue with the bid to transform Ethiopian economy from agriculture

domination and using agriculture itself as a stepping board (MoFED, 2010). Therefore, it

is becoming increasingly crucial for policy makers to focus immediate attention on agro-

industries. Such industries, established along efficient value chains, can increase

significantly the rate and scope of industrial growth (UNIDO, 2009).

Demand for horticultural products tends to grow very rapidly with urbanization and

increased income. Exports of vegetable products from Ethiopia have increased from

25,300 tons in 2002/03 to 63,140 tons in 2009/10 (EHDA, 2011). Horticultural produce is

a high value item. Diversity of fruits and vegetables are demanded by consumers, such

growth provides major opportunities for farmers to diversify their production and increase

their incomes. Such opportunities may be especially valuable for women, who are the

primary producers and marketers of horticultural produce throughout Ethiopia. Finally,

from the farming through retailing, horticultural production employs about twice as much

2

labor as cereals per hectare of production; small farmers, rural laborers, and the urban poor

stand to gain extremely from these employment opportunities (Munguzwe and Tschirley,

2006).

Vegetable production plays important role in poverty alleviation through employment

generation, improving the feeding behavior of the people, and creating new opportunities

for poor farmers. Since the labor to land ratio of vegetable cultivation is high, vegetable

products are bulky and perishable, and vegetable has continuous demand in the market, its

production and marketing allows high productive employment. Increasing horticultural

production and marketing thus contribute to commercialization of the rural economy and

create many off-farm jobs (Weignberger and Lumpkin, 2005).

In 2011/12 production year 293,609 and 266,264 smallholder farmers were engaged in

vegetable production, and 909,776.5 and 710,988.48 quintals of vegetables were produced

in East Hararghe and West Hararghe Zones, respectively (CSA, 2012). Vegetable

production has significant contribution in supporting household income and used as source

of food in both Zones. In Kombolcha Woreda of Eastern Hararghe Zone and Habro

Woreda of Western Harargehe Zone different vegetables are grown with different

intensities depending on environmental condition and level of marketability. In

Kombolcha Woreda 693,899 quintals of vegetables were produced in 2011/12 production

season on 2,607.5 hectares of land (KWOoARD, 2012). In Habro Woreda 223,080

quintals of vegetables were produced in 2011/12 production season on 1309 hectares of

land (HWOoARD, 2012). The most common grown vegetables are potato, cabbage, carrot

and beetroots in Kombolcha Woreda, and tomato, cabbage, beetroot and onion in Habro

Woreda.

Vegetables produced in the eastern part of Ethiopia are supplied to the local markets and

to the neighboring countries. Potato and onion/shallot are the most commonly marketed

vegetables accounting for about 60% and 20% of the marketed products. The other

products such as cabbage, beetroots, carrot, garlic, green pepper and tomato are marketed

at relatively smaller quantities by few farmers (Bezabih and Hadera, 2007). The marketing

of vegetables in Eastern Ethiopia is characterized by seasonal gluts and shortages which in

turn affect the marketing behavior of producers, traders and consumers (Jema, 2008).

Vegetable marketing is an important source of income and employment in the study areas.

3

Being the center of production and marketing of vegetables, the study areas have access to

both domestic and terminal markets.

1.2. Problem Statement

In Africa, per capita supply of fresh produce has fallen since 1970, by an average of 0.3%

per year (USAID, 2005). This decline has been driven by falling real incomes, but also by

increasingly inadequate production and marketing systems that limit yield growth at the

farm level and increase marketing costs throughout the supply chain. Ethiopia probably

has not escaped this trend. Reversing the trend; and realizing the growth potential that

horticulture presents; will require concerted action throughout the supply chain, based on

reliable information and collaboration between the private and public sectors. Value chain

analysis is essential to understand relationships and linkages among buyers and suppliers

and a range of market actors in between (Wenz and Bokelmann, 2011).

A review of literature in agro-industry value chain in Ethiopia indicates that the sector

faces many challenges due to limited market outlets, limited efforts in market linkage

activities and poor market information among actors (Dereje, 2007; Kaleb, 2008; Dendena

et al., 2009). Correspondingly, Mamo (2009) argued that small scale, dispersed and

unorganized producers are unlikely to exploit market opportunities as they cannot attain

the necessary economies of scale and lack bargaining power in negotiating prices.

Development need of vegetables is poorly addressed in Ethiopia. But these days efforts

have been stepped up to improve and support the sector. With this line, the current Growth

and Transformation Plan (GTP) prioritize intensive production and commercialization of

horticulture as a sector for attention. Thus, the development policy initiates the need to

accelerate the transformation of the sub-sector from the subsistence to business oriented

agriculture. But, the existing constraints of production, post-harvest handling and

marketing such as: - input utilization, productivity, packing, warehousing cold storage and

distribution have played their deterring role on production, trade, and consumption of

vegetables in Eastern Ethiopia (Bezabih and Hadera, 2007).

The production of horticultural crops is a major element of the farming system in the

eastern part of Ethiopia such as in East Hararghe Zone and some part of West Hararghe

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4

Zone. In the areas where irrigation water is available and farmers have better agricultural

marketing networks, horticulture production is a major source of cash income for the

households and one of the major sources of livelihood for a large number of transporters,

middlemen and traders in the area (Bezabih and Hadera, 2007). The lack of a shift from

subsistence to commercial farming in spite of such comparative advantage may have

different reasons like high risks, high transaction costs, limited food markets, limited

insurance options and limited access to credit or in general the problem in the value chain.

In spite of the fact that markets are crucial in the process of agricultural

commercialization, transaction costs and other causes of market imperfections could limit

the participation of farm households in different markets (Sadoulet and de Janvry, 1995 as

cited in Moti, 2007). This implies that markets could be physically available but not

accessible to some of the farm households. Value chain analysis is essential to explain the

connection between all the actors in a particular chain of production and distribution and it

shows who adds value and where, along the chain. It helps to identify pressure points and

make improvements in weaker links where returns are low (Schmitz, 2005).

Problems in the vegetables value chain hinder the potential gains that could have been

attained from the existing opportunities. In this regard, vegetable value chain analysis is an

interesting process that has not been investigated much in the study areas. Both buyers and

sellers in the study areas usually do not play collective roles towards one another and there

are no vegetable processing activities. Under such circumstances, a study that focused on

production problems, marketing problems, and roles and responsibilities of actors can play

significant role towards the improvements of the existing system.

Value chain analysis of horticultural crops conducted by Bezabih (2008) in Kombolcha

Woreda identified different production and marketing problems and the gross margin

obtained by different actors. However, the study on factors affecting vegetable market

supply, factors affecting market outlet choice and the benefit share of different actors in

the value chain were not done in the study areas. So, this study was proposed to

investigate the value chain analysis of major vegetables produced in Kombolcha and

Habro Woredas of East and West Harerghe Zones. Therefore, this study would help to

find the weakest link of the chain and to narrow the information gap on the subject.

5

1.3. Research questions

The study tries to answer the following questions:

1. How are production and marketing support services of vegetables functioning?

2. What constraints do farmers encounter to supply vegetables to the market?

3. What are the alternative vegetables market channels in the study areas?

4. What are the key factors affecting farmers vegetable market outlet choice decision?

5. What does vegetable value chain look like and who is more benefiting from

vegetable value chain?

6. What are the opportunities and constraints of vegetable value chains in the study

areas?

1.4. Objectives of the Study

The general objective of the study is to analyze the value chains of vegetables in the study

areas. The specific objectives of the study are:

1. To identify vegetable value chain and examine the performance of actors in the

chain;

2. To analyze the determinants of vegetable supply to the market in the study areas;

3. To identify marketing channels vegetables and factors affecting outlet choice

decisions of vegetable producers.

1.5. Scope and Limitations of the Study

This study was conducted in two Woredas and important information were collected from

sample households and marketing actors involved in the subsector organization in the

study areas. Hence, the study was limited spatially as well as temporally to make the study

more representative in terms of wider range of area, and time horizon. Furthermore, since

Ethiopia has wide range of diverse agro-ecologies, institutional capacities, organizations

and environmental conditions, the result of the study may have limitations to make

generalizations and make them applicable to the country as a whole. However, it may be

useful for areas with similar context with the study areas.

6

1.6. Significance of the Study

The study analyzed the entire vegetables value chain from input supplier to the consumer

within the country and from input supplier to exporter for exported vegetables. It also

provides a holistic picture of existing challenges, opportunities and entry points in the

vegetables value chain. Moreover, this study provides information on the determinants of

vegetables supply to the market, the determinants of market outlet choice decisions,

marketing margin, benefit share of actors, and identifies opportunities and constraints of

vegetables value chain in the study areas. Therefore, it could shed light on required efforts

to enhance the production and utilization of vegetables at larger scale to bring about

economic development in the area. The information generated could also help a number of

organizations including: research and development organizations, traders, producers,

policy makers, extension service providers, government and non-governmental

organizations to assess their activities and redesign their mode of operations and

ultimately influence the design and implementation of policies and strategies. It could also

help different actors to identify and analyze new ways of stimulating innovation.

1.7. Organization of the Thesis

With the above brief introduction, the remaining part of the thesis is organized as follows.

Chapter 2 presents review of literature on value chain analysis from different sources.

Subsequently, description of the study area and methodologies are presented in Chapter 3.

In Chapter 4, both descriptive and econometric results are presented and discussed in

detail. Chapter 5, summarizes the main findings of the study and draws conclusion and

appropriate recommendations.

7

2. LITERATURE REVIEW

In this part of the study the basic concepts of value chain, concepts guiding agricultural

value chain, benefit of value chain in agricultural sector, markets and marketing, market

channel, market performance, measuring value chain, developing value chain towards the

benefit of the poor, market deriving development in vegetable value chain, status of

vegetable production in Ethiopia and empirical reviews would be discussed.

2.1. Definitions and Concepts in Vegetables Value Chain Analysis

Industry chains are classified as either supply or value chains. The following

definitions within the general term industry chain are used:

Supply chain: It is taken to mean the physical flow of goods that are required for raw

materials to be transformed into finished products. Supply chain management is about

making the chain as efficient as possible through better flow scheduling and resource use,

improving quality control throughout the chain, reducing the risk associated with food

safety and contamination, and decreasing the agricultural industrys response to changes in

consumer demand for food attributes (Dunne, 2001).

Value chain: It is taken to mean a group of companies working together to satisfy market

demands. It involves a chain of activities that are associated with adding value to a product

through the production and distribution processes of each activity (Schmitz, 2005). An

organizations competitive advantage is based on their products value chain. The goal of

the company is to deliver maximum value to the end user for the least possible total cost to

the company, thereby maximizing profit (Porter, 1985).

A value chain is the full range of activities required to bring a product from conception,

through the different phases of production and transformation. A value chain is made up of

a series of actors (or stakeholders) from input suppliers, producers and processors, to

exporters and buyers engaged in the activities required to bring agricultural product from

its conception to its end use (Kaplinsky and Morris, 2001). Bammann (2007) has

identified three important levels of value chain.

8

Value chain actors: The chain of actors who directly deal with the products, i.e.

produce, process, trade and own them.

Value chain supporters: The services provided by various actors who never directly

deal with the product, but whose services add value to the product.

Value chain influencers: The regulatory framework, policies, infrastructures, etc.

The value chain concept entails the addition of value as the product progresses from input

suppliers to producers and consumers. A value chain, therefore, incorporates productive

transformation and value addition at each stage of the value chain. At each stage in the

value chain, the product changes hands through chain actors, transaction costs are

incurred, and generally, some form of value is added. Value addition results from diverse

activities including bulking, cleaning, grading, and packaging, transporting, storing and

processing (Anandajayasekeram and Berhanu, 2009) as shown in Figure 1 for the case of a

typical agricultural value chain.

Figure 1. Typical agricultural value chain and associated business development services.

Source: Adapted from Anandajayasekeram and Berhanu (2009).

Value chains encompass a set of interdependent organizations, and associated institutions,

resources, actors and activities involved in input supply, production, processing, and

distribution of a commodity. In other words, a value chain can be viewed as a set of actors

and activities, and organizations and the rules governing those activities.

Value chain management is about creating the added value at each link in the chain and a

sustainable competitive advantage for the businesses in the chain. How value is actually

9

created is a major concern for most businesses. Porter (1985) indicates that value can be

created by differentiation along every step of the value chain, through activities resulting

in products and services that lower buyers costs or raise buyers performance. In much of

the food production and distribution value chain, the value creation process has focused on

commodities with relatively generic characteristics, creating relatively small profit

margins.

2.1.1. Market chains versus value chains

The terms production chain, supply chain, market chain and value chain are often used

interchangeably, but in fact there are some important differences (Table 1). In its simplest

definition, the terms production chain, supply chain, market chain are synonymously used

to describe all participants involved in an economic activity which uses inputs and services

to enable a product to be made and delivered to a final consumer. A value chain is

understood as a strategic network between a numbers of independent business

organizations. According to Hobbs et al. (2000), a value chain is differentiated from a

production/supply chain because participants in the value chain have a long-term strategic

vision, disposed to work together, oriented by demand and not by supply, shared

commitment to control product quality and have a high level of confidence in one another

that allows greater security in business and facilitates the development of common goals

and objectives.

Table 1. Enterprise relations: production chain versus value chain

Factors Production market chain Value market chain

Information flow Little or none Extensive

Principal focus Cost / price Value / quality

Strategy Basic product (commodity) Differentiated product

Orientation Led by supply Led by demand

Organizational structure Independent actors Independent actors

Philosophy Competitiveness of the

enterprise

Competitiveness of the

market chain

Source: Hobbs et al. (2000).

10

The goal of a value chain is to optimize performance in that industry using the combined

expertise and abilities of the members of the chain. Successful chains depend on

integration, coordination, communication and cooperation between partners with the

traditional measure of success being the return on investment (Dunne, 2001; Bryceson and

Kandampully, 2004).

2.1.2. Major concepts guiding agricultural value chain analysis

There are four major key concepts guiding agricultural value chain analysis

(Anandajayasekeram and Berhanu, 2009; Kaplinsky and Morris, 2000). These are

effective demand, production, value chain governance, and upgrading.

2.1.2.1. Effective demand

Agricultural value chain analysis views effective demand as the force that pulls goods and

services through the vertical system. Hence, value chain analysis need to understand the

dynamics of how demand is changing at both domestic and international markets, and the

implications for value chain organization and performance. Value chain analysis also

needs to examine barriers to the transmission of information in the changing nature of

demand and incentives back to producers at various levels of the value chain (MSPA,

2010).

2.1.2.2. Production

In agricultural value chain analysis, a stage of production can be referred to as any

operating stage capable of producing a saleable product serving as an input to the next

stage in the chain or for final consumption or use. Typical value chain linkages include

input supply, production, assembly, transport, storage, processing, wholesaling, retailing,

and utilization, with exportation included as a major stage for products destined for

international markets. A stage of production in a value chain performs a function that

makes significant contribution to the effective operation of the value chain and in the

process adds value (Anandajayasekeram and Berhanu, 2009).

11

Producing the required amount effectively is a necessary condition for responsible and

sustainable relationships among chain actors. Thus, one of the aims of agricultural value

chain analysis is to increase the quantity of agricultural production. Understanding the

mechanisms of the agricultural production greatly help to design appropriate policy that

bring more gain to farmers and the whole society at large. For a long time, sector analyses

have been used to measure the different economic aspects of production. However, sector

analyses have not been without weaknesses. In particular, sector analysis tends to be static

and suffers from the weakness of its own bounded parameters. Such analysis struggles to

deal with dynamic linkages between productive activities that go beyond that particular

sector (Kaplinsky and Morris, 2000). By going beyond the traditional narrow focus on

production, value chain analysis scrutinize interactions and synergies among actors. Thus,

it overcomes several important limitations of traditional sector assessments.

2.1.2.3. Value chain governance

Governance refers to the role of coordination and associated roles of identifying dynamic

profitable opportunities and apportioning roles to key players (Kaplinsky and Morries,

2000). Value chains imply repetitiveness of linkage interactions. Governance ensures that

interactions between actors along a value chain reflect organization, rather than

randomness. The governance of value chains emanate from the requirement to set product,

process, and logistic standards, which then influence upstream or downstream chain actors

and results in activities, roles and functions.

It is important to note that governance and coordination sometimes appear as synonymous

or interchangeable terms in the literature. Already in the 1980s, Williamson (1979, 1985)

used the term governance to define the set of institutional arrangements in which a

transaction is organized. As Gereffis work on Global Comodity Chains and the role of

governance appeared, the term coordination took on a new meaning, basically, the vertical

organization of activities. The application of contract/private ordering/governance leads

naturally into the reconceptualization of the firm not as a production function (in the

science of choice tradition) but as a governance structure (Williamson, 2002).

According to Raikes et al. (2000), trust-based coordination is central for goods and

services, whose characteristics change frequently, making a standardized quality

12

determination for the purposes of industrial coordination difficult. This applies to the

manufacturing industry as well as agri-food chains. It is possible to identify in one

industry several coordination forms used by different firms where the choices rely on the

trust existent between the firms.

Value chains can be classified into two based on the governance structures: buyer-driven

value chains, and producer-driven value chains (Kaplinisky and Morris, 2000). Buyer-

driven chains are usually labor intensive industries, and so more important in international

development and agriculture. In such industries, buyers undertake the lead coordination

activities and influence product specifications. In producer-driven value chains which are

more capital intensive, key producers in the chain, usually controlling key technologies,

influence product specifications and play the lead role in coordinating the various links.

Some chains may involve both producer and buyer driven governance. Yet in further work

(Humphrey and Schmitz, 2002; Gibbon and Ponte, 2005) it is argued that governance, in

the sense of a clear dominance structure, is not necessary a constitutive element of value

chains. Some value chains may exhibit no governance at all, or very thin governance. In

most value chains, there may be multiple points of governance, involved in setting rules,

monitoring performance and/or assisting producers.

Chain governance should also be viewed in terms of richness and reach, i.e., in terms

of its depth and pervasiveness (Evans and Wurster, 2000). Richness or depth of value

chain governance refers to the extent to which governance affects the core activities of

individual actors in the chain. Reach or pervasiveness refers to how widely the governance

is applied and whether or not competing bases of power exists. In the real world, value

chains may be subject to multiplicity of governance structure, often laying down

conflicting rules to the poor producers (MSPA, 2010).

2.1.2.4. Value chain upgrading

Upgrading refers to the acquisition of technological capabilities and market linkages that

enable firms to improve their competitiveness and move into higher-value activities

(Kaplinsky and Morris, 2000). Upgrading in firms can take place in the form of process

upgrading, product upgrading, functional upgrading and chain upgrading. Upgrading

entails not only improvements in products, but also investments in people, knowhow,

13

processes, equipment and favorable work conditions. Empirical research in a number of

countries and sectors (e.g. Humphrey and Schmitz, 2000; Humphrey, 2003; Humphrey

and Memedovic, 2006) provide evidence of the importance of upgrading in the

agricultural sector.

2.1.3. Market and marketing

Market can be defined as an area in which one or more sellers of given products/services

and their close substitutes exchange with and compete for the patronage of a group of

buyers. Originally, the term market stood for the place where buyers and sellers are

gathered to exchange their goods, such as village square. A market is a point, or a place or

sphere within which price making force operates and in which exchanges of title tend to be

accompanied by the actual movement of the goods affected (Backman and Davidson,

1962). The concept of exchange and relationships lead to the concept of market. It is the

set of the actual and potential buyers of a product (Kotler and Armstong, 2003).

Conceptually, a market can be visualized as a process in which ownership of goods is

transferred from sellers to buyers who may be final consumers or intermediaries.

2.1.3.1. Marketing efficiency

Efficiency in marketing is the most used measure of market performance. Improved

marketing efficiency is a common goal of farmers, marketing organizations, consumers

and society. It is a commonplace notation that higher efficiency means better performance

whereas declining efficiency denotes poor performance. Most of the changes proposed in

marketing are justified on the grounds of improved efficiency (Kohls and Uhl, 1985).

2.1.3.2. Marketing channel

Formally, a marketing channel is a business structure of interdependent organizations that

reach from the point of product or origin to the consumer with the purpose of moving

products to their final consumption or destination (Kotler and Armstong, 2003). This

channel may be short or long depending on kind and quality of the product marketed,

available marketing services, and prevailing social and physical environment (Islam et al.,

2001).

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2.1.3.3. Marketing Performance

Market performance can be evaluated by analyzing costs and margins of marketing agents

in different channels. A commonly used measure of system performance is the marketing

margin or price spread. Margin or spread can be useful descriptive statistics if it used to

show how the consumers price is divided among participants at different levels of

marketing system (Mendoza, 1995).

Marketing costs: Marketing costs are the embodiment of barriers to access to market

participation by resource poor smallholders. It refers to those costs, which are incurred to

perform various marketing activities in the transportation of goods from producer to

consumers. Marketing costs includes handling cost (labour, loading and unloading, costs

of damage, transportation and etc) to reach an agreement, transferring the product,

monitoring the agreement to see that its conditions are fulfilled, and enforcing the

exchange agreement (Holloway et al., 2002).

Marketing margin: It is a commonly used measure of the performance of a marketing

system (Abbot and Makeham, 1981). It is defined as the difference between the price the

consumer pays and the price that is obtained by producers, or as the price of a collection of

marketing services, which is the outcome of the demand for and supply of such services

(Cramers and Jensen, 1982; William and Robinson, 1990 and Holt, 1993). The size of

market margins is largely dependent upon a combination of the quality and quantity of

marketing services provided the cost of providing such services, and the efficiency with

which they are undertaken and priced. For instance, a big margin may result in little or no

profit or even a loss for the seller involved depending upon the marketing costs as well as

on the selling and buying prices (Mendoza, 1995).

Under competitive market conditions, the size of market margins would be the outcome of

the supply and demand for marketing services, and they would be equal to the minimum

costs of service provision plus normal profit. Therefore, analyzing market margins is an

important means of assessing the efficiency of price formation in and transmission through

the system. There are three methods generally used in estimating marketing margin: (1)

detailed analyses of the accounts of trading firms at each stage of the marketing channel

(time lag method); (2) computations of share of the consumers price obtained by

15

producers and traders at each stage of the marketing chain; and (3) concurrent method:

comparison of prices at different levels of marketing over the same period of time

(Mendoza, 1995; Scarborough and Kydd, 1992).

2.1.3.4. Measuring value chain

A fundamental aspect of global value chain research is how value itself, is

conceptualized and measured. According to Gereffi (1999) profit, value addition and price

markups are indications of income shares across value chain actors. Valueadded shares

can be calculated for different links in the chain. A second way to calculate value added is

to look its distribution by each value chain actors of vegetable market and decomposing

for each actor to get approximations of each value-added share. Marketing margin is the

difference between the value of a product or a group of products at one stage in the

marketing process and the value of an equivalent product or group of products at another

stage. Measuring this margin indicates how much has been paid for the processing and

marketing services applied to the product(s) at that particular stage in the marketing

process (Smith, 1992).

2.2. Benefit of Value Chain in Agricultural Sector

It is an innovation that enhances or improves an existing product, or introduces new

products or new product uses. This allows the farmer to create new markets, or

differentiate a product from others and thus gain an advantage over competitors. In so

doing, the farmer can ask a higher premium (price) or gain increased market share or

access. Adding value does not necessarily involve altering a product; it can be the

adoption of new production or handling methods that increase a farmers capacity and

reliability in meeting market demand. Value-added can be almost anything that enhances

the dimensions of a business. The key is that the value-adding activity must increase or

stabilize profit margins, and the output must appeal to the consumer (AAFC, 2004).

Value chain is useful as a poverty-reduction tool if it leads to increase on and off farm

rural employment and income. Increased agricultural productivity alone is not a sufficient

route out of poverty within a context of globalization and increasing natural resource

degradation. A focus on post-harvest activities, differentiated value added products and

16

increasing links with access to markets for goods produced by low-income producers

would appear to be the strategy open to smallholders (Lundy et al., 2002).

Traditionally, little attention has been paid to the value chains by which agricultural

products reach final consumers and to the intrinsic potential of such chains to generate

value added and employment opportunities. While high-income countries add nearly

US$185 of value by processing one tone of agricultural products, developing countries add

approximately US$40. Furthermore, while 98 percent of agricultural production in high-

income countries undergoes industrial processing, barely 38 percent is processed in

developing countries. These indicate that well developed agro-value chains can utilize the

full potential of the agricultural sector (UNIDO, 2009).

In the process of preparing an agro-industrial master plan for Ethiopia, a prioritization

process was conducted for several commodities to identify those offering the highest

prospects for growth (UNIDO and FAO, 2009). Group 1: Commodities that are highly

important to the economy due to the large population involved in their production and to

their contribution to national food security. This group includes: (i) cereals (wheat, maize,

teff and barley); (ii) oilseeds (sesame, Niger seed, linseed and rapeseed); (iii) coffee; and

(iv) sugar. Group 2: Commodities that are of importance to the economy, due to the

number of people involved in production, processing and marketing as well as to their

contribution to food security. This group includes: (i) dairy products; (ii) meat; (iii) tea;

and (iv) fruit and vegetables. Group 3: Commodities that entail a competitive advantage

for Ethiopia. This group includes: (i) honey; (ii) pulses; (iii) spices; and (iv) grapes/wine.

2.3. Developing Value Chain Systems towards the Benefits of the Poor

In recent years, the pro-poor growth approach has become one of the key concerns of

developmental organizations. The focus of the approach lies in the promotion of economic

potentials of the poor and disadvantaged groups of people (OECD, 2006). The main aim is

to enable them to react and take advantage of new opportunities arising as a result of

economic growth, and thereby overcome poverty (Berg et al., 2006). The promotion of

value chains in agribusiness aims to improve the competitiveness of agriculture in national

and international markets and to generate greater value added within the country or region.

The key criterion in this context is broad impact, i.e. growth that benefits the rural poor to

17

the greatest possible extent or, at least, does not worsen their position relative to other

demographic groups. Pro-poor growth is one of the most commonly quoted objectives of

value chain promotion. In recent years, the need to connect producers to markets has led to

an understanding that it is necessary to verify and analyze markets before engaging in

upgrading activities with value chain operators. Thus, the value chain approach starts from

an understanding of the consumer demand and works its way back through distribution

channels to the different stages of production, processing and marketing (GTZ, 2006).

The value chain approach seeks to identify long-term solutions to reduce the vulnerability

of developing countries to fluctuating world market prices or trade shocks. It does not just

focus on adding value to existing traditional commodity exports (in other words,

diversifying the same product), but also on promoting alternative products. Another

characteristic of the approach is that it does not solely concentrate on functional

dimensions such as supplying appropriate inputs, or applying good agricultural processing,

handling and distribution practices. It emphasizes the importance of institutional

arrangements, or rather governance issues, along the value chains that link and coordinate

producers, processors and distributors of a certain product. Moreover, this aspect covers

authority and power relationships that determine how financial, material and human

resources are allocated and flow within the chain (Gereffi et al., 1994). Dynamic value

chain systems respond to market shifts by developing and transferring knowledge to

intermediaries and producers, so that they can adapt and maintain a competitive market

position over time. Vibrant value chain systems grow and continuously incorporate new

businesses, generating ever-increasing jobs, income, and assets. In this manner, value

chain systems can have the potential to significantly reduce poverty for large numbers of

poor people (Alexandra and Mary, 2006).

2.5. Development of Market-Driven Vegetable Value Chain

The value chain approach considers both the added value of a product and an insight into

the actors roles and relations. The value chain approach analyses a products development

process from input supply through production and processing level, transport, trade and

marketing, to consumption. Despite the fact that, earlier work on agriculture concentrated

mainly on improving the supply side of the respective value chains e.g. production

18

conditions and output, recent studies have also paid attention to the demand side (Diao,

2007). Here the value chain analysis concentrates on both ends of the chain corresponding

with the two sides of a market.

The development of the domestic markets of vegetables is strongly determined by factors

on the supply side; example soils, aridity, agricultural knowledge, competition, weather,

and market infrastructure as well as on the demand side example increase in population,

urbanization, and income-elasticity. As vegetables are highly perishable commodities

there are many difficulties during the marketing process. Natural occurrences such as

aridity, the composition of soils, and the weather are mainly responsible for creating

opportunities and constraints on the supply side of the market. Seasonality strongly

influences the supply side of the vegetable production. Production of vegetables in rain fed

is highly affected by seasonality (high and low supply on the markets), which is mainly

influenced by the climate and weather conditions. Those farmers who have access to

irrigation can operate more independently of the seasons (Koenig et al., 2008).

Furthermore, the importance of market co-ordination and market participation have been

highlighted and described as one of the most important constraints responsible for the poor

performance of vegetables (Dorward et al., 2005). According to estimations by Kelley and

Byerlee (2004) some 60% of the African rural population lives in areas of good

agricultural potential, but with poor market access. Only 22% live in areas of good

agricultural potential and good market access and 18% suffer from poor market access and

poor agricultural potential.

Agricultural potential and market access alone cannot make farmers profitable.

Availability of market infrastructure (storage, transport, etc) is important for farmers to

avoid flooding of markets and enables them to increase their profit by selling in times of

low supply. Due to seasonality, market prices fluctuate depending on the quantity and the

quality of the products on the markets. Especially on the wholesale and retail markets

prices also fluctuate even during one day. Often the limited availability of storage is the

reason that traders and retailers try to sell all their produce by the end of one day, even if

they achieve only a low price. In times of high supply, traders benefit more; in times of

low supply farmers can sell everything they harvest for good prices (Koenig et al., 2008).

19

2.6. Status of Vegetable Production in Ethiopia

Ethiopia has a variety of vegetable crops grown in different agro ecological zones by small

farmers, mainly as a source of income as well as food. The production of vegetables varies

from cultivating a few plants in the backyards, for home consumption, to large-scale

production for the domestic and home markets. According to CSA (2012) the area under

these crops (vegetables and root crops) was estimated to be 359,950.13 hectares with a

total production of 24,267,581.58 tons in the year 2011/12. Root and tuber crops are by

far the dominant product group. Potatoes (32%) stand out as the important products,

followed by taro/Godere (19%), garlic (12%), and onions (nearly 12%). Potatoes are

mostly found in the Amhara Regional State (51%) and Oromia (33%). Among small-scale

producers of vegetables, Ethiopian cabbage (Kale) takes the higher almost 50%, followed

by red pepper with a share of 31%, and green pepper 10%.

Smallholder vegetable farms are based on low input low output production systems. The

use of improved seeds and planting material of high yielding varieties and other inputs

such as fertilizer and plant protection materials is not common in the smallholder sector.

Technical training and extension services on improved crop husbandry techniques are not

available. As a result average productivity levels are low in the small scale farming sector

(EHDA, 2011).

2.7. Review of Empirical Studies

2.7.1. Value chain approach

There are a number of studies that have employed the value chain approach to agricultural

commodities. Fitter and Kaplinsky (2001) used a value chain analysis to examine inter-

country distributional outcomes of the global coffee sector by mapping input-output

relations and identifying power asymmetries along the coffee value chain. Their study

showed that returns to product differentiation taking place in the face of globalization do

not accrue to the coffee producers. They also found that power in the coffee value chain

was asymmetrical. At the importing end of the chain, importers, roasters and retailers

compete with each other for a share of value chain rents but combine to ensure that few of

the rents return to the farmer or the producer country.

20

Value chain study conducted on off-season vegetables by USAID (2011) in Nepal

indicated that the subsector faces some challenges such as unavailability of quality

planting materials, lack of knowledge among the producers of the proper usage of

fertilizers and pesticides as well as poor soil fertility management, lack of irrigation

facilities, labor shortage, postharvest loss due the perishable nature of vegetables, limited

access to reliable market information, unorganized market center, limited collection

centers, and lack of proper packaging and transportation facilities. The study

recommended short-term and long term infrastructural and institutional innovation to

reduce the above challenges.

Ponte (2002) also used a value chain analysis to examine the impact of deregulation, new

consumption patterns and evolving corporate strategies in the global coffee chain on the

coffee exporting countries in the developing world. The study concluded that the coffee

chain was increasingly becoming buyer-driven and the coffee farmers and the producing

countries were facing a crisis relating to changes in the governance structure and the

institutional framework of the coffee value chain.

Horticulture value chain study conducted in Eastern parts of Ethiopia identified different

problems on the chain (Bezabih, 2008). The major constraints of marketing identified by

the same study include lack of markets to absorb the production, low price for the

products, large number of middlemen in the marketing system, lack of marketing

institutions safeguarding farmers' interest and rights over their marketable produces (e.g.

cooperatives), lack of coordination among producers to increase their bargaining power,

poor product handling and packaging, imperfect pricing system and lack of transparency

in market information communications.

Dereje (2007) used value chain approach to study the competitiveness of Ethiopian coffee

in the international market. The study indicates that Ethiopian farmers have low level of

education, large family size with small farmland and get only 3% of the retail price in the

German market. Thus, policy intervention was suggested to improve farmers

performance.

Value chain study conducted on mango by Dendena et al. (2009) indicated that the

subsector faces some challenges. Among others: highly disorganized and fragmented

21

industry with weak value chain linkages, long and inefficient supply chains, inadequate

information flows and lack of appropriate production are explained as the major problems.

The study recommended institutional innovation to reduce the above challenges.

2.7.2. Determinants of marketable surplus

The study of marketable surplus turned out to be very vital for agricultural based countries

because the transition of smallholder farmers towards commercial production is

determined by it. Getachew (2009) has noted that the transition of the small-scale sector

towards commercial production will ultimately be determined by the ability and

willingness of producers to provide a commodity. Similarly, Mamo (2009) argued that the

development of markets, trade and the subsequent market supply that characterize

commercialization are fundamental to economic growth.

There are a number of empirical studies on factors affecting the marketable surplus of

agricultural commodities. Ayelech (2011) identified factors affecting the marketable

surplus of fruits by using OLS regressions. She found that fruit marketable supply was

affected by; education level of household head, quantity of fruit produced, fruit production

experience, extension contact, lagged price and distance to market.

Abay (2007) applied Heckman two-stage model to analyze the determinants of vegetable

market supply. Accordingly, the study found out that marketable supply of vegetables

were significantly affected by family size, distance from main road, number of oxen

owned, extension service and lagged price.

According to Wolday (1994) marketable supply of agricultural product could be affected

by different factors including the size of land holding, the output level, family size, market

access, price, inputs, formal education, oxen number, accesses to extension and credit

services, distance to market, time of selling, access to labor and age. In sum, empirical

evidences indicate that marketable supply approach has become an important framework

to analyze economic agents in agricultural sector. In this study an attempt was made to

identify factors affecting the marketable supply of vegetables.

22

2.7.3. Determinants of market channel choices

Regarding factors affecting channel choices of the households, different researchers used

multinomial logit and probit for categorical marketing system for different agricultural

commodities.

A study by Ferto and Szabo (2002) identified variables influencing producers decision for

channel choices. The analysis was based on a survey among three supply channels of fruit

and vegetable producers in Csongrad, Hungary in respect the choice of marketing channels

which are wholesalers, marketing cooperative and producers organization channel. A

multinomial logit model was applied to reveal on the determinants influencing these

choices among various supply channels. Farmers decisions with respects to supply

channels were influenced differently by transaction costs, and producers sell to wholesale

market were strongly and negatively affected by the farmers age, information costs, and

negatively by the bargaining power and monitoring costs. The probability that farmers sell

their product to marketing cooperative is influenced by the age and information costs

positively, whereas by the asset specificity and bargaining power negatively.

Rao et al. (2010) confirmed that educational level of the operator, off-farm employment,

own means of transportation and age of operator had positive effect where as household

size was negatively associated with supper marketing channel choices. In second stage

second stage of treatment model, off-farm employment and own means of transportation

affected income of vegetables growers positively. Furthermore, dummy variable for

channel choices were positive and significant. This indicated that supplying vegetable to

supermarket channels rendered better income gain over spot marketing channel. On the

other hand, ownership of livestock negatively influenced income of vegetables growers

supplying traditional or spot marketing channel.

Jari and Fraser (2009) identified that market information, expertise on grades and

standards, contractual agreements, social capital, market infrastructure, group participation

and tradition significantly influence household marketing behavior. The study uses

multinomial regression model to investigate the factors that influence marketing choices

among smallholder and emerging farmers.

23

Bongiwe and Masuku (2012) identified that age of the farmer, quantity of baby corn

produced and level of education were significant predictors of the choice to sell vegetables

to NAMBoard market channel instead of selling to other-wholesale market channel. The

age of the farmer, distance from production area to market, membership in farmer

organization and marketing agreement were significant determinants of the choice to use

non-wholesale market channel over other-wholesale market channel. The study uses

descriptive and multinomial logistic regression analyses to investigate factors that

influence market channel choices.

Mamo and Degnet (2012) identified that gender and educational status of the household

head together with household access to free aid, agricultural extension services, market

information, non-farm income, adoption of modern livestock inputs, volume of sales, and

time spent to reach the market have statistically significant effect on whether or not a

farmer participates in the livestock market and his/her choice of a market channel. The

study uses binary logit and multinomial logit to explore the patterns and determinants of

smallholder livestock farmers market participation and market channel choice using a

micro-lever survey data from Ethiopia.

24

3. RESEARCH METHODOLOGY

This chapter discusses the research methodology used in the study including location and

description of the study areas, data types and data sources, methods of sampling, methods

of data collection and analysis.

3.1. Description of the Study Areas

This study was undertaken in Eastern Ethiopia in two major vegetable growing Woredas

(namely Kombolcha and Habro Woredas of Oromia Regional State) which are known in

vegetables production (Figure 2). Description of each Woreda is given below.

Kombolcha Woreda: Kombolcha is one of the nineteen Woredas found in East Hararghe

Zone of Oromia Regional State, Ethiopia. The Woreda is composed of 19 rural kebeles

and 1 urban kebele. Komblocha Woreda is located about 542 kms southeast of Addis

Ababa and 16 kms northwest of Harar town, the capital of East Hararghe Zone of Oromia

Region. The Woreda is strategically located between the two main cities Harar and Dire

Dewa. In addition, due to its proximity to Djibouti and Somalia, the Woreda has access to

potential markets in the area.

The Woreda had total population of about 157,444, of which 77,659 were females in

2011(CSA, 2010). About 45.1%, 53.0% and 1.9% of the total population were young,

economically active and old age, respectively. Average family sizes for the Woreda was

4.9 persons per household. The crude population density of the Woreda is estimated as

517 persons per km2.

Lowland and midland agro-ecological zones characterize the Woredas climate. The

Woreda receives mean annual rainfall of 600-900 mm, which is bimodal and erratic in

distribution. The main rainy season in the Woreda is from February to mid-May and from

July to end of August. The economy of the Woreda is dominated by traditional cash crop

farming mixed with livestock husbandry. The major crops produced in the Woreda include

sorghum, maize, vegetables (potato, cabbage, beetroot, and carrot), chat, groundnut, coffee

and sweet potato (KWOoARD, 2012).

25

Figure 2. Geographical location of the study areas

Habro Woreda: Habro is one of the twelve Woredas found in West Hararghe Zone of

Oromia Regional State, Ethiopia. The Woreda is composed of 32 rural kebeles and 5

urban kebeles. Habro Woreda is located about 410 kms southeast of Addis Ababa and 78

kms from Chiro town, the capital of West Hararghe Zone of Oromia Region in the western

central part of West Hararghe Zone. Gelamso town is the administrative seat of the

Woreda.

The Woreda had the population of about 214,591, of which 103,472 were females in

2011(CSA, 2010). Young, economically active and old age populations accounted for

45.3%, 52.4% and 2.3%, respectively. An average family size for rural area was 4.76

persons. The crude population density of the Woreda is estimated as 288.8 persons per

km2.

26

The altitude of the Woreda stretches between 1500 and 2000 m.a.s.l. Habro classified into

dega (18%), woinadega (57%) and kola (25%) agro climatic zones. Sorghum, maize, teff,

haricot bean, barley, wheat and vegetables (potato, tomato, cabbage, onion, shallot, and

carrot) are the dominant crops in the Woreda (HWOoARD, 2012).

3.2. Types, Sources and Methods of Data Collection

The study used information on different variables such as data on vegetable production,

vegetables marketed, prices of vegetable supplied, distance to Woreda market, distance to

all weather roads, age of the household head, extension service, educational status of the

household head, family size, access to market information, credit facility, and type of

sellers and buyers. Survey was made to obtain these information.

The secondary data were collected from Central Statistical Authority (CSA), Bureau of

Agriculture and Rural Development (BoARD), Capacity Building for Scaling Up of

Evidence Based Best Practices in Agricultural Production in Ethiopia (CASCAPE) project

and other sources. Primary data were collected using informal and formal surveys, and

from key informants. The informal survey used Rapid Market Appraisal (RMA) technique

using checklists. The formal survey was undertaken through formal interviews with

randomly selected farmers, traders and consumers using a pre-tested semi-structured

questionnaire for each group.

3.3. Sampling Procedure and Sample Size

For this study, in order to select a representative sample a multi-stage random sampling

technique were implemented to select vegetables producer kebeles and sample farm

households. In the first stage, with the consultation of Woreda agricultural experts and

development agents, out of 19 and 32 kebeles of Kombolcha and Habro Woredas 7 and 5

vegetables producer kebeles were purposively selected based on the level of production. In

the second stage, from the identified or selected rural kebeles, 4 sample kebeles namely

Bilusuma and Eegu from Kombolcha Woreda, and Harochercher and Bareda from Habro

Woreda were selected randomly. In the third stage, using the household list of the sampled

kebeles 162 sample farmers were selected randomly based on proportional to the

population size of the selected kebeles (Table 2).

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Table 2. Sample size distribution in the sample rural kebeles

Name of Woreda Name of selected

kebeles

Total number of

vegetable producers

Number of sample

households

Kombolcha Bilusuma 214 53

Eegu 178 44

Habro Harochercher 150 37

Bareda 113 28

Total 655 162

Source: Own computation from OoARD and kebele adminstaraion data

For this study, data from traders and consumers were also collected. The sites for the

trader surveys were market towns in which a good sample of vegetable traders existed.

The lists of wholesalers were obtained from the respective Woreda Office of Trade and

Industry (OoTI) and for other traders there is no recorded list. From 55 wholesalers, 12

wholesalers were selected randomly. In addition, 18 retailers and 7 collectors were

randomly selected constituting a total of 37 traders from Melkarafu, Harar, Gelemso,

Karakurikura and Wachu markets. Furthermore, 18 and 12 consumers were interviewed

from Kombolcha and Habro Woredas, respectively by selecting randomly.

3.4. Methods of Data Analysis

Descriptive statistics, inferential statistics and econometric analysis were used to analyze

the data collected from vegetable producers, traders and consumers.

3.4.1. Descriptive and inferential statistics

These methods of data analysis refer to the use of percentages, means, standard deviations,

t-test, 2-test, F-test and maps in the process of examining and describing marketing

functions, facilities, services, and household characteristics.

3.4.1.1. Value chain analysis

As products move successively through the various stages, transactions take place between

multiple chain actors, money and information are exchanged and value was progressively

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added. The analysis of vegetable value chains highlights the need for enterprise

development, enhancement of product quality, and quantitative measurement of value

addition along the chain, promotion of coordinated linkages among producers and

improvement of the competitive position of individual enterprises in the marketplace.

Moreover, individual enterprises may feed into numerous chains; hence, which chain (or

chains) was/were targeted depends largely on the point of entry for the research inquiries

(Kaplinsky and Morris, 2001). The following four steps of value chain analysis were

applied to this study:

1. Mapping the value chain to understand the characteristics of the chain actors and the

relationships among them, including the study of all actors in the chain, of the flow of

vegetables through the chain, of employment features, and of the destination and

volumes of domestic and foreign sales. This information can be obtained by

conducting surveys and interviews as well as by collecting secondary data from

various sources.

2. Identifying the distribution of actors benefits in the chain. This involves analyzing the

margins and profits within the chain and therefore determined who benefits from

participating in the chain and who would need support to improve performance and

gains. In the prevailed context of market liberalization, this step is particularly

important, since the poor involved in value chain promotion were the most vulnerable.

3. Defining upgrading needed within the chain. By assessing profitability within the

chain and identifying chain constraints, upgrading solutions could be defined. These

may include interventions to: (i) improve product design and quality and move into

more sophisticated product lines to gain higher value and/or diversify production; (ii)

reorganize the production system or invest in new technology to upgrade the process

and enhance chain efficiencies; (iii) introduce new functions where in the chain to

increase the overall skill content of activities; and (iv) adapt the knowledge gained in

particular chain functions in order to redeploy it.

4. Emphasizing the governance role. Within the concept of value chain, governance

defines the structure of relationships and coordination mechanisms that exist among

chain actors. By focusing on governance, the analysis identified actors that may

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require support to improve capabilities in the value chain, increase value added in the

sector and correct distributional distortions. Thus, governance constituted a key factor

in defining how the upgrading objectives could be achieved.

Following the above procedure, the main aspects of vegetable value chain analysis was

done by applying some quantitative and qualitative analysis. First, an initial map was

drawn which depicts the structure and flow of the chain in logical clusters. This exercise

was carried out in qualitative and quantitative terms through graphs presenting the various

actors of the chain, their linkages and all operations of the chain from pre-production

(supply of inputs) to consumption. After having developed the general conceptual map of

the value chain, the next step is analyzing the chains economic performance and benefit

share of actors.

3.4.1.2. Analysis of vegetable value chain performance

Estimates of the marketing margins are the best tools to analyse performance of market.

Marketing margin was calculated by taking the difference between producers and retail

prices. The producers share is the commonly employed ratio calculated mathematically

as, the ratio of producers price to consumers price. Mathematically, producers share can

be expressed as:

(1)

where: PS= Producers share

Pp= Producers price

Cp = Consumer price

MM = marketing margin

The above equation tells us that a higher marketing margin, diminishes producers share

and vice versa. It also provides an indication of welfare distribution among production and

marketing agents.

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Calculating the total marketing margin was done by using the following formula.

Computing the Total Gross Marketing Margin (TGMM) is always related to the final price

paid by the end buyer and is expressed as a percentage (Mendoza, 1995)

(2)

where, TGMM=Total gross marketing margin.

Net Marketing Margin (NMM) is the percentage over the final price earned by the

intermediary as his net income once his marketing costs are deducted. The equation tells

us that a higher marketing margin diminishes the producers share and vice-versa. It also

provides an indication of welfare distribution among production and marketing agents.

(3)

From this measure, it is possible to see the allocative efficiency of markets. Higher NMM

or profit of the marketing intermediaries reflects reduced downward and unfair income

distribution, which depresses market participation of smallholders. An efficient marketing

system is where the net margin is near to reasonable profit.

To find the benefit share of each actor the same concept was applied with some

adjustments. In analyzing margins, first the Total Gross Marketing Margin (TGMM) was

calculated. This is the difference between producers (farmers) price and consumers

price (price paid by final consumer) i.e.

TGMM = Consumers price Farmers price (4)

Then, marketing margin at a given stage i (GMMi) was computed as:

(5)

where, SPi is selling price at ith

link and PPi is purchase price at ith

link.

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Total gross profit margin also computed as:

TGPM=TGMM-TOE (6)

where, TGPM is total gross profit margin, TGMM is total gross marketing margin and

TOE is total operating expense.

Similar concept of profit margin that deducts operating expense from marketing margin

was done by Dawit (2010) and Marshal (2011).