Implementation of Agro Processing

IMPLEMENTATION OF AGRO PROCESSING PROJECTS AND SOCIO ECONOMIC DEVELOPMENT OF BENEFICIARIES: A CASE STUDY OF MARABA COFFEE PROJECT IN HUYE DISTRICT SOUTH PROVINCE, RWANDA

VINCENT MWEBAZE MBA/2014/70928

Research Project Submitted in Partial Fulfillment for the Award of the Degree of Master of Business Administration (Project Management Option) of Mount Kenya University

MAY 2016

DECLARATION

This research proposal is my original work and has not been presented to any other institution.

No part of this research should be reproduced without the authors consent or that of Mount

Kenya University.

Student’s Names: Vincent Mwebaze

MBA/2014/70928

Sign ------Date------

Declaration by the supervisor

This research has been submitted with our approval as the Mount Kenya University supervisor.

Name: Dr. Tom Mulegi, PhD

Sign ------Date ------

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DEDICATION

To my beloved wife Nayebare Jeanne, my children Derrick, Dickson, Marvin and Divine. I again dedicate this work to my parents, brothers, lecturers and friends for the immeasurable support during my studies and for this research.

ACKNOWLEDGEMENT

First of all, I thank the Almighty God for watching over me and gave me extra effort, courage and his wisdom for completing my studies and this work in particular.

I express my sincere gratitude to Mount Kenya University staff and lecturers for all the support in one way or the other that enabled me produce this work. It is in this regard that my appreciation goes to the manager for Maraba coffee project and MINICOM; for their support with necessary research data and for the success of this research topic.

In the same way, my sincere thanks and appreciation go to my wife Jeanne, to my children

Derrick, Dickson, Marvin and Divine for they missed me the time they needed me most because of my studies, I comfort you. I thank my parents H. Joseph, late M. Steria my pastor who prayed for me all the time, all family relatives and friends that have kept encouraging me in the journey for my education.

My supervisor Dr Tom Mulegi is highly acknowledged for his guidance to make this research become a success. His professional skills and knowledge enabled me to complete this research project and I owe him a profound appreciation.

In this regard I extend my sincere thanks to Ministry of Defence as my employer to facilitate my education at the time of need.

Finally, I thank my colleagues and classmates whom we shared difficult moments in class and may God bless us all.

ABSTRACT

The study analyzed how implementations of agro processing projects contribute to socio- economic development of beneficiaries. This study had particular concern on examining the role of implementing agro processing projects on employment in Huye district of south province; analyzing factors responsible for development of Maraba Coffee agro processing project in Huye district and to determine the relationship between Maraba coffee agro processing and socio economic development of beneficiaries. The significance for this study is to help policy makers to strengthen functionality and develop a reasonable system for promoting agro processing while considering their role in socio economic development of beneficiaries. It also helped to reduce after harvest wastes due to failure to process the agricultural produce. This gave opportunity to the researcher and others to contribute to socio economic development by investing in agro processing. For this study to be successful there was use of qualitative and quantitative data got from both primary and secondary data in order to have a detailed description of the knowledge levels on implementing agro processing and its role in socio-economic development of beneficiaries. Target population was categorized in terms of age; gender; marital status, education levels and number of children for each respondent. This intended to use stratified sampling among respondents and random sampling techniques; that helped to exhaustively conduct an unbiased research. To conduct survey a questionnaire was designed in order to meet research objectives which was the basis for findings to give appropriate recommendations. The target population was 230 founder members of the project and Slovan’s formula was used to determine sample size of 146 who were respondents. A descriptive research design was chosen to give a detailed description of knowledge levels in implementing agro processing projects and socio-economic development of beneficiaries. Data was collected by use of administered questionnaires that were distributed to respondents. It also concerns to study characteristics in a population for the purpose of investigating probable solutions of a research problem”. Data processing concerns transformation of data gathered from the field into the system and coded it satisfying to analysis and tabulation. Information was interpreted using frequency distribution tables generated by computer program SPSS outputs that make overall interpretation on implementation of agro processing and socio-economic development of beneficiaries in Rwanda. For objective one, the researcher was 95% confident that respondents’ age reflected work experience of those who implemented agro processing project, the dominant activity before the project was traditional cultivation 80 of all respondents followed by retail shops 27, casual labor 23 and commercialized farming 13 of respondents. Then for objective two, respondents’ number of children and presence of infrastructure before the project started also motivated joining the project in order to have improved socio economic condition. Finally for objective three, change of ubudehe category level subsequently led to the change of socio economic status of beneficiaries. Major recommendations were to project beneficiaries in order to improve use of good farming practices and integrated pest management system through focused support from agricultural officers to improve quality of processed coffee for competiveness and to government or local authorities to strengthen functioning mechanism of agro processing projects targeting their contribution to socio economic development of beneficiaries.

TABLE OF CONTENTS

DECLARATION...... ii

DEDICATION...... iv

ACKNOWLEDGEMENT ...... v

ABSTRACT ...... vi

TABLE OF CONTENTS ...... vii

LIST OF TABLES ...... xi

FIGURES ...... xii

LIST OF ACRONYMS AND ABBREVIATIONS ...... xiii

DEFINITION OF KEY TERMS ...... xiv

CHAPTER ONE: INTRODUCTION ...... 1

1.0 Introduction ...... 1

1.1 Background of the Study ...... 1

1.2 Problem Statement ...... 4

1.3 Objectives of the Study ...... 5

1.3.1 General objectives ...... …………………………………..5

1.3.2 Specific objectives ...... 5

1.4 Research Questions...... 6

1.5 Significance of the Study ...... 6

1.6 Limitations of the Study...... 7

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1.7 Scope of the Study ...... 8

1.6 Organization of the Study ...... 8

CHAPTER TWO: REVIEW OF RELATED LITERATURE ...... 10

2.0 Introduction ...... 10

2.1 Theoretical Literature ...... 10

2.1.1 The concept of socio-economic development ...... 13

2.1.2 Indicators of socio-economic development ...... 15

2.1.3 Indicators of socio-economic development in Rwanda ...... 19

2.1.4 Investment opportunities in Agriculture ...... 22

2.1.5 Agro Processing ...... 23

2.2 Empirical Literature Review ...... 26

2.3 Critical Review and Research Gap Identification ...... 33

2.4 Theoretical Framework ...... 36

2.5 Conceptual Framework ...... 38

2.6 Summary ...... 40

CHAPTER THREE: RESEARCH METHODOLOGY ...... 41

3.0 Introduction ...... 41

3.1 Research Design...... 41

3.2 Target Population ...... 42

3.3 Sample Designs ...... 42

3.3.1 Sample Size ...... 42

3.3.2 Sampling Techniques ...... 43

3.4 Data Collection Methods ...... 43

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3.4.1 Data Collection Instruments ...... 44

3. 4. 2 Administration of Data Collection Instruments ...... 46

3.4.3 Reliability and Validity ...... 47

3.5 Data Analysis Procedure ...... 47

3.6 Ethical Consideration ...... 48

CHAPTER FOUR: RESEARCH FINDINGS AND DISCUSSION ...... 49

4.0 Introduction ...... 49

4.1 Demographic Characteristics of Respondents ...... 49

4.1.1 Findings about workers employed in respondents’ own activities...... 50

4.2 Findings on activity that gave earning before the project started...... 52

4.3 Findings on workers employed in Respondents’ own activities ...... 53

4.4 Findings whether infrastructure existed before the project started...... 54

4.5 Findings on Respondents’ experience on the project...... 55

4.6 Findings on the Ubudehe category level after joining the project...... 57

4.7 Findings on how many workers employed by those who joined the project...... 59

4. 8 Findings according to experience motivation to join the project...... 60

CHAPTER FIVE: SUMMARY CONCLUSIONS AND RECOMMENDATIONS ...... 62

5.0 Introduction ...... 62

5.1 Summary of Findings ...... 62

5.1.1 Objective One: Implementing Maraba Coffee agro processing project and employment in Huye district for the 5 year period...... 64

5.1.2 Objective Two: To analyze factors responsible for development of Maraba Coffee agro processing project in Huye district...... ……………………….65

5.1.3 Objective Three: To determine relationship between implementing Maraba Coffee agro processing Project and socio economic development of beneficiaries in Huye district…………… 66

5.2 Conclusion ...... 66

5.3 Recommendations ...... 68

5.4 Suggestions for further study ...... 70

REFERENCES ...... 71

APPENDICES ...... 78

APPENDIX I: LETTER OF INTRODUCTION FROM COORDINATOR SCHOOL OF

POSTGRADUATE STUDIES ...... 79

APPENDIX II: LETTER FROM MARABA AGRO PROCESSING PROJECT ...... 80

APPENDIX 111. QUESTIONNAIRE ...... 81

LIST OF TABLES

Table 4.1 Frequency Table of respondents...... 49

Table 4.2 The cross tabulation of Gender by Number of workers employed in own activities. 50

Table 4.3 Pearson Chi-Square test to indicate significance level ...... 51

Table 4.4 Respondets’Age by sources of earning before the project started...... 52

Table 4.5 Pearson Chi-Square test to indicate significance level ...... 52

Table 4.6 Respondents’ Age by workers employed in own activities ...... 53

Table 4.7 Pearson Chi-Square Tests ...... 53

Table 4.8 Respondents’ Age by Infrastructure that exist before the project started ...... 54

Table 4.9 Pearson Chi-Square statistics Tests ...... 55

Table 4.10 Age of Respondent by years of working experience on the project ...... 55

Table 4. 11 Pearson Chi-Square statistic test ...... 56

Table 4.12 Respondents’ education level by Ubudehe category Level after Project started ..... 57

Table 4.13 Pearson Chi-Square test for Significance level ...... 58

Table 4.14 Respondents’ Children by employed workers in respondents’ own activities...... 59

Table 4.15 Pearson Chi-Square test for Significance level...... 60

Table 4.16 Respondents’ number of children by the motivation to join the project ...... 60

Table 4.17 Results of the Chi-Square Tests ...... 61

FIGURES

Figure 2.1: Structure of the conceptual frame work

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LIST OF ACRONYMS AND ABBREVIATIONS

CPI: Consumer Price Index

EDPRS: Economic Development and Poverty Reduction Strategy

FAO: Food and Agricultural Organization

GDP: Growth Domestic Product

GoR: Government of Rwanda

HIV/AIDS: Human Immuno-deficiency Virus/ Acquired Immuno-Deficiency Syndrome

IMF: International Monetary Fund

ISIC: International Standards Industrial Classification

MDGs: Millennium Development Goals

MINAGRI: Ministry of Agriculture and animal husbandry

MINALOC: Ministry of Local Government

MINECOFIN: Ministry of Economic Planning and Finance

MINICOM: Ministry of commerce

NISR: National Institute of Statistics of Rwanda

PMI: Presidents Malaria Initiative

PRS: Poverty Reduction Strategy

PRSP: Poverty Reduction Strategy Paper

PQLI: Physical Quality of Life Index

RDB: Rwanda Development Goals

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DEFINITION OF KEY TERMS

Agro Processing: It is referred to those activities that change the form of agriculture,

forestry and fisheries products into various forms with the aim of

transforming them into a usable item such as food, fiber, fuel or

industrial material, page 28.

Socio-Economic Development: It is a fundamental change in the structure of the economy in

increase of industry and income levels alongside falling share of

agriculture in national product, page 13.

Supply Chain: Supply chain encompasses the steps it takes to get a good or service from the

supplier to the customer, page 14.

Ubudehe category: This is a local and Kinyarwanda word which is interpreted as an

indicator or a measure of social economic category of people in

Rwanda such as poor, resourceful poor, rich and wealthier. Each of

these categories indicates a different level of socio economic status,

page 66.

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CHAPTER ONE: INTRODUCTION

1.0 Introduction

This chapter presents; the background of the study that gives specifics of the problem to study about, the Problem statement, the general and specific objectives of the study, the research questions, significance of the study indicated in future tense, limitations of the study, the scope of the study and organization of the study.

1.1 Background of the Study

For any development to take place there is a need for sustained economic growth. It is also argued that economic development refers to arise in per capita income and fundamental changes in structure of the economy (Jones, 2015). Over two thirds of the world’s poorest people are located in rural areas and engaged primarily in subsistence agriculture where survival is their basic concern (Todaro, 1997).

The Report (2007) called attention to the fact that some 800 million people are considered poor with incomes of less than US$1 per day. Among the world’s poor 75% live in rural areas, having agriculture as a major source of livelihood. In India increased agricultural productivity and rapid growth in agro processing sector for the recent years have contributed to a significant reduction in levels of poverty from 55 percent in 1973 to 26 percent in 1998 leading to socio-economic transformation. Despite this impressive development record, the country is still home to the largest number of poor people with an estimated 250 million people living below the poverty line that accounts for about 20 percent of the world’s poor

(Rao, 2006). To have economic growth and socio-economic development brought to rural

areas goes with fighting poverty which is achieved by proper implementation of agro- processing industries. The accelerated growth of agro-industries in developing countries also poses risks in terms of equity, sustainability and inclusiveness. Where there is unbalanced market power in agri food chains, value addition and capture can be concentrated among one or a few chain participants, to the detriment of the others. Agro-processing industries will be sustainable only if they are competitive in terms of costs, prices, operational efficiencies, product offers and other associated parameters and only if the prices they are able to pay farmers are remunerative for those farmers. An under development of agro processing industry is a missed opportunity to create sustainable jobs and incomes because each additional job in agro processing creates 2.8 extra jobs in the wider economy because of the multiplier effect (MINAGRI, 2012).

In agriculture-based countries the contribution of agro processing to total manufacturing is

66%, while in transforming and urbanized countries the figures are, respectively, 38% and

37% as based on Jaffee (2003). The representative sample countries are the sub-Saharan

African countries, transforming countries (Indonesia and Thailand), urbanized countries

(Latin America and South Africa) and the USA. Agribusiness provides inputs to farmers and connects them to consumers through handling, processing, transportation, marketing and distribution of agricultural products. Investment in agro-processing produces a significant multiplier effect along the supply chain. The investment generates demand for packaging, transportation of agricultural products, which in turn generates demand for associated agricultural inputs like fertilizers, seeds, pesticides and farm equipment.

According to GoR (2011) Rwanda is considered among the world’s poorest nations with highest population density of about 407 persons/sq. km. The country has particular

challenges for socio economic development as a result of its economic structure, the low level of human capital development, its landlocked position and its small size. The country experienced an exciting and fastest period of growth and socio-economic progress in its history during the decade 2000 to 2009. At the same time more than a million people were lifted out of poverty and the country made great pace towards achieving the MDGs and middle income status. This presented framework and key priorities for Rwanda’s socio economic transformation and a guiding tool for the future with ambitions to overcome poverty and achieve socio-economic development.

Therefore agriculture is the foundation and backbone to the economic transformation

EACSOF-Rwanda (2014) that witnessed increased investments in agricultural inputs, postharvest infrastructure and production. In the short and medium terms, Rwanda intends to focus its efforts on the traditional cash crops of tea, coffee and pyrethrum, and also on the emerging, nontraditional crops, flowers, various fruits & vegetables. This will be attained by developing highly into commercialized agriculture, industry and service sectors while reducing economic dependence on subsistence agriculture and to make vision 2020 expectations a reality MINECOFIN, Umurenge Vision 2020 (2007).

This means that the government of Rwanda recognizes the central role of the agriculture sector both in terms of economic growth and poverty reduction EACOF-Rwanda (2014). It is out of all this that MINAGRI took the responsibility for monitoring and overseeing the Grow

Africa process on private sector development and export promotion in the agriculture sector to support the delivery of the activities pertaining to the two primary goals of; transforming

Rwandan agriculture from a subsistence sector to a market-oriented, agro-processing, value

creating sector and to grow the agriculture sector as rapidly as possible in relation to production and commercialization in order to increase rural incomes and reduce poverty.

Agriculture accounts for more than 34% of the gross domestic product (GDP), provides 70% of exports, employs 80% of the workforce and provides raw materials to agro-processing industries and a market for manufactured goods. While the primary sector, boosted by continuing high growth in agricultural production, performed well in 2009, industry and services performed moderately compared to previous periods Claude Bizimana (2012).

Abbott (2012) under the PSTA-II, the Government recognizes low agricultural production and productivity as key hindrance to commercialization. Given the rapidly increasing population and limited agricultural land, strategies to increase land productivity (production intensification) and create more agricultural productive land are considered in the subsequent agricultural policies. According to EACSOF-Rwanda (2014) that Agro-processing especially for nontraditional crops like cassava and maize, present an opportunity for investors. Due to the crop intensification and land use consolidation policies the production of these two crops has increased significantly and it required investment in adding value to the crops for markets.

1.2 Problem Statement

Abbott (2012) after the genocide of 1994, Rwandan government implemented PRS in the period 2000-2005. This marked an insignificant contribution to poverty reduction and progress in the agricultural production sector. In Abott (2012), the greatest concentrations of poverty remained most; in the districts from Southern and Western provinces in their remote rural areas compared to urban areas. This highlights diversity within the provinces, as well as

the importance of larger towns and locations close to the border. A similar map for extreme poverty shows a broadly similar pattern, highlighting the four poorest districts in the country as being Huye, Nyamagabe, Karongi and Nyamasheke; the last two of which are in the

Western Province while the first two in south province (NISR, 2012). Therefore, since poverty remained extreme in rural areas than urban areas; transforming agriculture is assumed to play a supportive role in poverty reduction with in developing economies. The researcher developed interest, to carry out a study on Implementation of agricultural processing projects taking a case study of Maraba Coffee Project in Huye District of south province and how it contributes to socio-economic development of beneficiaries.

1.3 Objectives of the Study

1.3.1 General objectives

The general objective of the study is to analyze the implementation of agro-processing projects on socio-economic development of beneficiaries in Rwanda.

1.3.2 Specific objectives

Specific objectives of this study will be to:

(i) To examine the role of Maraba coffee agro-processing project on employment in

Huye district.

(ii) To analyze factors responsible for development of Maraba Coffee agro processing project in Huye district.

(iii) To determine the relationship between Maraba coffee project agro processing and socio-economic development of beneficiaries in Huye district.

1.4 Research Questions.

Research questions show are those that shall be answered to achieve the objectives of the study as formulated within the problem statement. There are three research questions as indicated below.

(i) What role has Maraba coffee agro-processing project contributed on employment?

(ii) What are factors responsible for growth of Maraba coffee agro processing projects?

(iii) How does Maraba coffee agro processing project contribute to socio-economic development of beneficiaries in Huye south province?

1.5 Significance of the Study

The study puts forward findings reflecting performance of the selected agro-processing plants located is south province of Rwanda and their contributions towards economic development. This is important and will help;

This study will help policy makers in strengthen functioning, formulating a flexible and reasonable system for developing and promoting agro-processing Plants in their contribution to economic development. It will also help to understand contribution of nontraditional crops in economic development. This will enable them to know how to subsidize like for fertilizers, quality seeds, providing social amenities like water, power roads, etc.

It will help MINAGRI and its partner institutions to understand to what extent they should support or finance agro-processing plants, how they will strengthen management aiming at performance improvement, efficiency and effectively utilization of the plant.

Therefore the researcher was able to understand contribution on the economy in terms of poverty reduction and wealth creation in the country leading to socio-economic development.

This study enabled the researcher to contribute to existing knowledge in this field of interest from where other related researchers may be carried out. It also set an opportunity for the researcher and others to invest in agro-processing a sector that greatly contributes to the economy of Rwanda. Again it is very important to the researcher because it is a requirement for the partial fulfillment for the award of Master in Business Administration.

The study will help the general public to understand their contribution to socio-economic development and their need for efficiency and effectiveness in performance.

1.6 Limitations of the Study

The study concerns implementation of agro processing projects and their contribution to socio-economic development of beneficiaries but there are other projects that can also contribute to socio-economic development of project beneficiaries. This means that this field of interest was not necessarily to be the only contributor to socio-economic development.

Factors like leadership, security, nature of political atmosphere may be an indicator of economic development of which the researcher does not have control over.

This is because once there is security; investment ventures are encouraged and perform well but if there is no security, investment potentials are constrained because some people have no

hope for life at all. Cost of low material, factor in puts and inflation have influence performance of agro processing industry. Management is also very important because once some of the projects fail due to lack of managerial skills the intended objectives would not be achieved.

Weather condition in terms of rainy season or drought is unpredictable and a strong factor to consider in performance of agriculture sector and future research may hinge on this. To consider also is population growth rate that does not follow the trend of economic growth resulting in a negative impact on the welfare of the population, especially in rural areas.

1.7 Scope of the Study

The research considered Maraba coffee Project in Huye district, South Province. The choice was based on project that has been operational for at least 5 years in order to have had a significant impact on socio-economic development of beneficiaries. Collected data for analysis in the present research covered a period of 5 years to analyze performance of agro processing industry in Huye district, South Province. Indeed the period under investigation was from the year 2010 and ends in 2014. The researcher found this period as good enough to determine performance on implementation of agro processing projects.

1.6 Organization of the Study

This study is divided into 5 chapters:

Chapter 1: General introduction: This chapter gives explanation of what research is about; why it is important and interesting; the research problem and objectives; research questions, limitations and scope of the study.

Chapter 2: literature Review: This chapter clarifies a critical analysis of what other researchers have said on the subject and where this topic fit and the research gaps to be clearly identified. It clearly shows theoretical and empirical literature. The gap should be identified from the previous research. It should also indicate the theoretical and conceptual frameworks.

Chapter 3: Research Methodology: The chapter gives a research design, target population, sample design and size, sampling technique, data collection instruments and their administration. The chapter also indicates reliability and validity, data analysis procedure and ethical consideration, explanation of how the researcher collects certain data, what data he collects and how he conducts analysis in order to achieve research objectives and produce reliable knowledge.

Chapter 4: Research Findings and Discussion: This chapter shows data analysis, presentations of findings, and all research objectives be addressed.

Chapter 5: This chapter indicates summary of findings starting with general information on each of the study objectives indicating statistical figures. It again shows conclusions, recommendations and suggestions for further research in the same field.

CHAPTER TWO: REVIEW OF RELATED LITERATURE

2.0 Introduction

The chapter introduces the theoretical review where different authors have talked about agro processing projects, socio-economic development of project beneficiaries and socio- economic development indicators in general and for Rwanda in particular. It will also indicate empirical literature, critical review, analysis of the research gap and the conceptual frame work.

2.1 Theoretical Literature

Agriculture is the life blood of the economy in most developing countries. Processing of agricultural production accelerates and promotes sustainable agricultural intensification

(Onwurafor, 2013). Implementation of agro processing projects generates employment and income to beneficiaries using locally available resources. In this case project managers are concerned with applying project management tools and techniques to clearly define the project goals and develop an execution plan to achieve socio-economic development of the project beneficiaries Jack Meredith (2006).

This new approach is the development from the low level through community driven projects based on government support and local entrepreneurial initiatives. This is where poor people need to be encouraged to achieve socio-economic transformation. There are problems of low standard of living, hunger and poverty that stem from low level of food management capacity after production; lack of entrepreneurial initiatives because many farmers labor about how to process; preserve and package of products in order to catch up with season related opportunities Bakare (2011).

Jack Meredith and Samuel Mantel (2006) discussed project management in terms of producing project outcomes within the three objectives of cost, schedule, and specifications.

Project managers are expected to develop and execute project plans that meet cost, schedule and specifications. They added a fourth aspect of project management as the expectations of the client. Project management is the application of everything that a project manager does to meet these parameters focusing on the project outcomes in terms of requirements. The client-centered definition of project management is the application of knowledge, skills, tools and techniques to meet expectations of the client who is also the beneficiary. This definition focuses on delivering a product or service to the client that meets expectations rather than project specifications.

Some organizations fulfill a societal role to meet economic and governance functions. Local factories or hospitals are organizations that provide some social or community need like; wealth, jobs and common social needs for communities and government organizations provide regulations and services that allow for an orderly society. These organizations have different views of time and each organization develops an operational approach to accomplishing the purpose of the organization over a preset time horizon. Economic organizations initiate projects to produce a new product, to introduce work processes that significantly reduce product costs or merge with other organizations to reduce competition, lower costs and generate additional profits Jack Meredith (2006).

Then in developing countries agricultural development is an important area of applied economics in project evaluation, supported by multilateral aid agencies like the WB and

FAO. The development crisis in the Third World countries results mainly as an imbalance between agriculture and manufacturing sectors. This imbalance can be corrected by processing low productive resources out of agriculture products. This sector is the greatest potential to reduce poverty and subsequently lead to socio-economic development within the developing countries of which Rwanda is inclusive Lewis (1954). To improve the understanding of project management is to distinguish project management with operations management. Whether in an economic, socio-religious or government organization, managers are charged with effectively and efficiently achieving the purpose of the organizations. Typically, a manager of an economic organization focuses on maximizing profits and stockholder value. Leaders with socio religious organizations focus on effective and efficient delivery of a service to a community or constituency and governmental managers are focused on meeting goals established by governmental leaders.

Therefore for smallholder farmers to improve incomes from agricultural sector, it is essential to connect them to value chains and investment opportunities. To generate value, agricultural products should be produced in bulk with high quality, quantity and reliability. This means that gains in agriculture and farm employment opportunities play a key role in poverty reduction and effective government support to those in extreme poverty will be critical to protect the poorest, mitigate the worst effects of poverty and support graduation out of extreme poverty leading to economic development (IMF, 2013). Reliance on government to address developmental concerns that can impact on rural lives and poverty in general may not achieve the desired target of rural socio-economic transformation. The new approach is the development from the grassroots through community driven projects based on local

entrepreneurial initiatives, poor people needed to be encouraged in order to achieve real socio-economic development and transformation for all and genuine empowerment

Onwurafor (2013).

2.1.1 The concept of socio-economic development

It was pointed out by Smith (2012), that Agriculture plays a supportive role in socio- economic development. With its primary purpose to provide sufficient low-priced food and employment to the expanding agricultural industrial economy, was thought to be the dynamic

“leading sector” in the overall strategy of socio-economic development. It shows available literature in a broader aspect at the national level. We present the general framework under which the current agricultural policies, related sector strategies and agricultural development plans, down to the lowest community levels where agricultural programs are associated.

Todaro (1986) said that development is a process that involves organizational and orientation of the entire social economic system. In addition to improvements in income and outputs; development typically involves crucial changes in institutional social and administrative structures as well as in popular attitudes, customs and beliefs.

Smith (2012); defines socio-economic development as a process of improving the quality of human lives and capabilities by raising people’s levels of living, self-esteem and freedom.

They again argued that development traditionally meant achieving sustained rates of growth of income per capita to enable a nation to expand its output at a faster rate than the growth rate of its population. Previously, socio-economic development was considered a planned change of the production structure and employment to increase the declined share of agriculture’s manufacturing and service industries. Ellis (1956) in the take off into self

sustained growth, put forward that socio-economic development is a process whereby an economy's real national income as well as per capita income increases over a long period of time. It contains changes in resource supplies, in the rate of capital formation, in demographic composition, in technology, skills and efficiency and in institutional and organizational set-up. Briefly, economic development was considered as a process consisting a long chain of inter-related changes in fundamental factors of supply and in the structure of demand, leading to a rise in the net national product of a country in the long run.

For Rwanda socio-economic development Ansoms (2008) is considered a contribution from agriculture growth, despite the emergence of other significant growth drivers like manufacturing and services sector. In this regard more than 80 percent of the rural population depends on agriculture as the only likely driver for the country’s economic development and this has implemented a comprehensive agricultural development strategy.

The World Bank (2011) on Rwandan economic update indicated that, agriculture sector was considered to play an essential role in attaining the country’s development vision of sustainable growth due to its employment potential. It also focused on macroeconomic developments of income, inflation and employment. Agriculture’s feature outlines a key channel through which it contributes to the economy and these special features analyzes its evolving role over the past years by focusing on economic development for the years to come.

Kuznets (2009) noted four contributions by agriculture to economic development as: the product contribution of inputs for other industries like textiles and food processing; the foreign-exchange contribution of using agricultural export revenues to import capital

equipment; the market contribution of rising rural incomes creating more demand for consumer products and the factor market contribution.

2.1.2 Indicators of socio-economic development

Accordance to Shaw (1989) economic growth, financial intermediation and socio-economic development are closely linked to one another. Goldsmith (1969) said that the financial structure of an economy accelerates economic growth and improves economic performance.

This facilitates the relocation of funds to the best user, in the economic system where funds yield the highest return that establishes a link with socio-economic development. He again presents data showing a well defined upward flow in the ratio of financial institutions' assets to gross national product for both developed and less developed countries for the period

1860-1963. Greenwood (2008) noted that; it is complex to establish with confidence the direction of the causal mechanism of deciding whether financial factors were responsible for the acceleration of socio-economic development or whether financial development reflected economic growth which is a prerequisite for socio-economic development.

In addition to a rise in per capita income, Gillis (2008) said that socio-economic development implies a fundamental change in the structure of the economy as observed in South Korea since 1960. This is reflected by the rising share of industry along the falling share of agriculture in national product because of high increase in agro processing projects. Socio- economic development can be indicated by modernizing traditional agriculture where certain inputs and techniques are combined to yield a higher agricultural production. This concerns the role of chemical fertilizer and relationship of fertilizer’s impacts on improved plant varieties; it also deals with mobilization of agricultural in puts and techniques in developing

countries. For example, in United States implementing agro processing projects was established where by wheat is turned into flour in large mills and farmers buy bread in the local supermarkets as everyone else. In developing countries, only wheat for urban consumption is processed in large mills whereas in rural areas it is processed at home or in village mills, since processing into large and distant mills would be expensive.

This signifies the reason why in large parts of south Sudan where rainy season affect roads condition; hence such regions cannot intensify implementation of the agro processing projects since agricultural output is uncertain and hardly accessible due to poor road condition. Then, the absence of good road net work in rural and remote areas for trucks means that it is costly to move bulky commodities from remote areas. That is improvements in the transport system and in marketing can have a major impact on agricultural productivity raising the need for implementation of agro processing projects. This situation can be solved by construction of all-weather road system and this has worked in South Korea during the

1970s.

According to the Overseas Development Council’s PQLI Morris (2004) the measure of socio-economic development was based on three basic human needs of; Life expectancy, infant mortality rate and literacy rate. Sustainable socio-economic development indicators are often developed through dynamic interactive processes and dialogues among stakeholders, including technical experts, government and civil society representatives. The process allows participants to define sustainability from their own viewpoint, taking relevant aspects as well as value systems into considerations.

According to the Economics of Development by (Kooros, 2007) health is also considered as an effect of economic development and we need to consider its contribution to socio- economic development. It is important to recognize that the validity of health services as a developmental activity does not rest entirely on our ability to prove that health expenditures increase national output. Health increases human potentials of all kinds and is basically regarded as a basic human need. Everyone can benefit from better health, and improved health for young will lead to a healthier population in the future. Healthy workers provide direct and immediate benefits by increasing workers strength, stamina and ability to concentrate while on job. Better child health and nutrition promote future productivity growth directly by helping children develop into stronger and healthier adults.

Good health is an indicator of socio-economic development. In the Ministry of Health the

(Centers for Disease Control and Prevention, 2010), the goal of PMI aimed to reduce malaria deaths by 50% in sub Saharan countries mostly to vulnerable groups like pregnant women and children less than 5 years of age. They were provided with lifesaving services like provision of long lasting insecticide treated mosquito nets and medicines. Under the initiative Rwanda achieved one of the highest national antiretroviral treatment coverage rates in sub Saharan Africa, reaching an estimated 76 % of those in need in 2009. This reduced rate of deaths caused by malaria and HIV/AIDS due to high standards of health, nutrition and a cleaner environment.

To consider also is that education is another contributor to socio-economic development.

This means that educational attainment is a measure of human capital, which is a key element to economic growth that focuses on socio-economic development. At the same time, economic growth is a major determinant of consumption patterns in the areas of energy,

transport or material consumption. Education is an indirect measure of consumption and production that certainly has important direct linkages to consumption patterns, as evidenced in the declaration of the United Nations Decade of Education for Sustainable Development

(Bank, 2007).

It was also observed that technology flow plays a central role in the process of socio- economic development. In contrast to the ordinary growth structure, where technological change was left as a mysterious residual, the recent growth frame work highlighted the dependence of growth rates on the state of internal technology relative to that of the rest of the world. It means that growth rates in developing countries are partly explained by a ‘catch- up’ process in the level of technology. In a typical model of technology flow, the rate of economic growth of a backward country depends on the extent of adoption and implementation of new technologies that are already used in leading countries. Technology flow can take place through a variety of channels that involve the spread of ideas and new technologies. Imports of high-technology products, adoption of foreign technology and acquisition of human capital through various means are certainly important channels for the international flow of technology (De Gregorio, 1998). To consider also is that employment level indicates socio-economic development. The employed are all full-and part-time workers, temporary and irregular employees who receive pay for a specified period that include those on paid vacation or sick leave and exclude business proprietors, self-employed, unpaid family members and volunteers. This reflects a comprehensive national employment and wages earnings status within an economy across all sectors of the economy such as agriculture, manufacturing, construction, retail trade, service sectors which indicate the well- being of the economy and labor force (Primus, 2003).

In Association for Investment Management and Research Consumer (Treasury, 2003) Price

Index measures and changes in the prices paid for goods and services by consumers for the specified month period which also contribute to socio-economic development. The CPI is essentially a measure of individuals’ cost of living changes and provides a measure of the inflation rate related to purchasing of goods and services. However, the CPI does not include every item an individual may buy, but instead takes a sampling of goods and services in different categories. The data may be collected through surveys and visits in areas of interest across the country. Affording regular changes in CPI indicates a standard of living indicating socio-economic development.

2.1.3 Indicators of socio-economic development in Rwanda

Socio-economic development is about growth followed by organizational change (stiglitz,

2000). Without growth, change is unlikely to occur, since a country needs resources to realize other long-term objectives like the growth of income per capita, improvement in quality of life and sustainable socio-economic development. It focuses on the MDGs to address the most pressing problems in developing countries, like poverty, hunger, primary universal education, gender equality, maternal health, HIV/AIDS, environmental sustainability and global partnership. To examine basic indicators of socio-economic development we consider; real income per capita adjusted for purchasing power; health status as measured by life expectancy, undernourishment and child mortality, and educational attainments as measured by literacy and schooling (Smith, 2012).

Real Income

The common measure of the overall economic activity is a measure of the relative economic and well-being of people in different nations. This is Gross domestic product (GDP) which measures the total output produced by an economy; by both residents and nonresidents without making deductions for depreciation of the domestic capital. Other things being equal, there is a positive correlation between the real national income and socio-economic development in an economic system. Higher real national income of a country is considered an indicator of higher socio-economic development and vice versa. We can then say that the real national income is the measuring stick of socio-economic development. Though it may be an imperfect method for measuring development; it is, however, used for global development comparisons. Here emphasis is on the word "real" which signifies that purchasing power of national income should be taken into account for quantifying development. Then, money national income will be discounted by the price index, as indicated in the formula below (Stiglitz, 2000);

Where, Yr = Real national income

Ym = Money national income

P = Price index

The formula signifies that socio-economic development can be meaningful if an increase in money national income is not accompanied by increase in price level. Therefore price

stability is an essential condition for promoting development and economic development signifies higher real national income.

Health

In the same way, people aspire to become healthier and well educated which is collated with per capita income. Life expectancy is the average number of years newborn children would live if subjected to the mortality risks prevailing at their time of birth. Undernourishment means consuming too little food to maintain normal levels of activity which is often considered as the problem of hunger. High fertility can be both a cause and a consequence of underdevelopment, and then birth rate can be reported as another basic indicator. The African

Economic Outlook (2012) asserted that it is important to improve the health status of the nationals and continue to prioritize health-sector spending by increasing public expenditure on health from 10.2% in 2009/10 to 16.1% in 2010/11. This improved health-sector outcomes reducing mortality rate of the Under-five from 103 in 2008 to 76 in 2010 per 1000 live births. This was also followed by decrease of maternal mortality from 750 in 2005 to 540 in 2010, per 100 000 live births although the MDGs target is 325 per 100 000 live births.

Because of improved healthy and living conditions life expectancy shows the average number of years to be lived by those born in the same year. If mortality at each age remains constant life expectancy has increased from 39.34 years in 2000 to 50.52 years in 2009 which is an indicator of economic development. About 80% of Rwandan population live in rural areas and the urban population is approximately 20% with a growth rate that has been falling over the years to the current figures of 4.31% from 14.99% in 2000, whereas the rural

population growth rate has been increasing over the years with an approximate growth rate of

2.5% (Labor Market Information System Report, 2011).

Education

The indicator measures whether entire eligible school age population has access to school and if they complete the full primary cycle. Education is a process by which human beings and societies reach their fullest potential. It is critical for promoting sustainable socio- economic development and improving the capacity of people to address environment and development issues (Indicators of Sustainable Development, 2007). In the Strategic Planning

Guidelines for Public and Private Sector Higher Education Institutions of June (2009);

Literacy is the fraction of adult males and females reported or estimated to have basic abilities to read and write. Education institutions have the challenge to develop their strategy to provide a graduate labor force with knowledge and skills needed to drive the socio- economic development of the country. This will be based on development of a knowledge- based and technology-led economy and move the country to the list of Middle Income

Countries by the year 2020.

2.1.4 Investment opportunities in Agriculture

According to EACSOF-Rwanda (2014), RDB considers agriculture sector as one of the priority sectors for investment and ranked 5th in registered private investments for the period

2000–2012; after tourism as number one, construction, energy and ICT respectively. This confirms the commitment of the GoR to transform agriculture sector from subsistence to a professional activity through processing, as well as moving from largely depended public sector to market-oriented private sector (RDB, 2013).

2.1.5 Agro Processing

Mhalanga (2011), said that investments in agro-industries have significant multiplier effects through both their backward and forward linkages along the value chains. Establishment of agro-processing projects generate demand for agricultural raw materials; which in turn creates work opportunities at the farm level; and contributes to increased demand for agricultural inputs like fertilizers, tools, sprays and veterinary products. The demand for additional agro-processing inputs, like packaging items and product ingredients, tends to rise with new investments in agro-processing projects. By the same indication, economic activity is generated in the downstream areas of logistics, distribution and service provision. Carlos da Silva (2009) still emphasized that implementation of agro processing projects are important sources of employment and income generation to both skilled and unskilled workers. Wilkinson and Rocha (2009) said that agro-processing projects are dominant in terms of their contribution to value-added after refinement where in agriculture-based countries contribution is as high as 66 percent, whereas in transforming and urbanized countries it reaches 38 percent and 37 percent respectively.

Norman Mhazo (2003) argued that Agro-processing activities comprise two major categories which are; primary and secondary operations. Primary processing operations involve activities like crop drying, threshing, cleaning, grading, and packaging. He still asserted that these activities are mainly carried out at the farm for only transforming the commodity into a slightly different form before storage, marketing or further processing. Then secondary processing operations involve increasing nutritional or market value of the commodity and the physical form or appearance of the commodity that totally changes the original nature.

Some examples of secondary processing are milling grain into flour, grinding groundnuts

into peanut butter, pressing oil out of vegetable seeds, pressing juice out of fruit, making cheese out of milk and manufacturing of crushed meat. Depending on the type of commodity, equipment needed for primary processing is completely different from that used in secondary processing because the latter applies more of skilled labor and equipment than the former.

According to (Diouf, 2008) the agro-industrial sector is defined as the subset of the manufacturing sector that processes raw materials and intermediate products derived from agriculture, fisheries and forestry. It includes manufacturers of food, beverages and tobacco, textiles and clothing, wood products and furniture, paper, printing and rubber products.

Carlos da Silva, (2009), agro processing may be considered as transformation of agricultural production that take place in the agro-economy of developing countries in the emergence of agro-industrial enterprises as part of broader processes of agribusiness development.

The Republic of South Africa national policy framework on small and medium agro- processing enterprises (2015), put forward that agro-processing refers to those activities that change the form of agriculture, forestry and fisheries products into various forms to facilitate easier handling, increase storage life and market access. The wide-ranging nature of the agro- processing sector implies a very wide range and heterogeneity of activities, which make classification quite complex.

However, the United Nations’ (ISIC, 2013) has alleviated some of the uncertainty around how to classify agro-processing projects by coming up with a standard classification of the agro-industry as consisting; Food and beverages, Tobacco products, Paper and wood products, Textiles, footwear and clothing, Leather and Rubber products.

Carlos da Silva (2009); said that one of the changes taking place in the agro-food economy of developing countries is the emergence of agro-industrial projects as part of the agribusiness development. In turn, implementation of agro-processing projects from the informal to the formal sectors has critical implications for participants along the supply chain of those engaged in agriculture, fisheries and forestry through food retailers and traders to the final consumer. Agro-industrialization presents valuable opportunities and benefits for developing countries; in terms of industry and socio-economic development, export performance, food safety and quality. At the same time, however, there are adverse effects on informal sector agro-processing enterprises, such that processes of agro-industrialization must be adjusted with overall processes of economic restructuring. Here, agro-industries are changing globally, presenting not only new opportunities but also challenges for developing countries, and suggesting that the future of agro-industrialization will be relatively different from the past.

Report (2009) estimates; indicated that the developing world experienced faster growth in the value of agricultural output (2.6% per year) than the developed world (0.9% per year) over the period 1980 to 2004. Correspondingly, developing countries’ share of global agricultural

GDP rose from 56% to 65% in the same period, far higher than the 21% share of world nonagricultural GDP leading to the need for introducing agro processing projects.

Carlos A. da Silva (2009) asserted that since the early 1990s, there has been a rapid process of agro-industrialization in many developing countries, characterized by the establishment of private and formal sector firms across an increasing display of food and non-food sectors. In order to understand the nature and consequences of this evolution, however, it viewed in the context of the wider restructuring of the entire agribusiness complex. In this regard we reflect

on three broad set of changes (Reardon, 2007). Firstly, the growth of agro-processing, distribution and provision of agricultural input activities off-farm by agro-industrial firms.

Secondly, institutional and organizational changes to the relations between agro-industrial firms and primary producers, like, increasing levels of vertical integration. Thirdly, changes in the primary production sector in terms of product composition, technology, sectoral and market structures.

Barrett (2000) highlights that we can see the growth of agro industrial sector as being integral to profound changes in the entire way in which the agro-food complex is structured and organized. In turn, this suggests impacts on actors at all levels of the supply chain, from primary production to consumption. The framework they developed provides a useful reflection through which one can understand these processes of agro-industrialization in developing countries the factors driving these processes and their consequences.

2.2 Empirical Literature Review

The empirical literature on socio-economic development has moved from the study of determinants to the deeper analysis of fundamental factors. New empirical works focus on the measurement and estimation of the historical effects of economic variables. Presently, companies manage their businesses by projects which are free for both projects and non- projects driven organizations. Virtually all activities in an organization can be treated as like projects. It is only fitting that well managed companies regard project management methodology as a way to manage the entire business rather than just projects (Kerzner,

2010). The principle of project formation states that the genesis of successful projects should be a clear justification of project need expressed in the first Project Bottom Line success. If

the project cannot be justfied on the basis of a realistically and sufficiently postive contribution to the venture bottom line or on the basis of legal mandates of safety considerations, then the project should not go forward (Pinkerton, 2003).

It is also agreed that business processes and projects management processes will be merged together as the project manager is viewed as the manager of part of a business rather than just the manager of a project. With any project one needs to be accomplished and define how the project will achieve those objectives. Each project begins with an idea, vision, or business opportunity tied to the organisations objectives of improving socio economic well being of beneficiaries. It includes a statement of business needs, an agreement of what the business is committed to deliver, an identification of project dependicies or beneficiaries, roles and responsibilities of the team members involved (Kerzner, 2010). Each organisation will implement project management to the best of their ability. For this case, agro processing projects and whether or not that is a true level of best for which there is no globally defined standard, it will be the level most appropriate for that time and space for socio-economic transformation of beneficiaries. However, there appears to be an equality in the mind of many senior managers that the implementation of standard practices can only be realised with the implementation of project management tools like clarity. It has been observed that companies that try to short-cut the establishment of process first and instead chase a tool to solve their project management challenges typically do not succeed with the implementation of any good practices, atleast in areasonable period of time Harold Kerzner (2010).

Pinkerton (2003) pointed out that poorly executed projects with long, drawn-out start-ups can seriously weaken a project, and even lead to its ruin that negatively impacts the projects ability to be profitable to beneficiaries. On the other hand, he explained that well managed

projects enhance company’s profit making and competetive abilities, hence impacting positively to beneficaries. It was also found out that an un profitable venture that shows little sign of righting it self, investors will no longer back it and will find better, more profitable places to invest. Investors naturally desire that their investment be spent wisely and their profit on investment be realised so quickly to improve socio-economic status of beneficiaries.

Supporters of food security explain that implementing agro-processing activities comprise primary and secondary operations and transformation of agricultural commodities into different forms that add value to the product, Norman Mhazo (2003). They have expressed that manufacturing of tobacco and textiles processing that dominate the commercial industrial sector are owned by multinational corporations with interest in farm produce supplied by large-scale commercial farmers. However, his findings did not show that processing activities are employed within established processing projects to increase earning level of those employed Norman Mhazo (2003).

Norman Mhazo (2003) pointed out that agro-processing industries refer to those activities that transform agricultural commodities into different forms that add value to the product.

These may be especially food manufacturing, tobacco and textile processing that dominate the commercial industrial sector. The study emphasized that these projects are mainly owned by multinational corporations with interest in farm produce supplied by large-scale commercial farmers like the largest food processing company, Cairns in Zimbabwe.

Although new local farmers currently fight to raise production along with lack of funding, agricultural inputs and commercial farming skills, given enough time there should be an increase in productivity. Again (Pinkerton, 2003) contributed to this study saying that project teams wishes to go beyond the traditional criteria of project success and evaluate success in

PBLS. In this sense success concerns improving the socio-economic conditions of beneficiaries. When evaluating project success, project teams should compare the original project scope with the finished product to see how well they stayed the course and to calculate the cost of expanding the scope envelope.

Simalenga (1996) complemented studies on implementing agro processing concurring that small-scale food processing activities represent a potential source of livelihood for many poor people in Sub-Saharan Africa. The overall potential of implementing agro-processing is huge and can; increase the value of crops of poor farmers in remote areas and yield higher returns; expand marketing opportunities; improve livelihoods of people; extend storage-life of commodities; improve attractiveness of commodities; enhance food security; overcome seasonality and perishability constraints and even empower women who are often involved in agro-processing sector. He further found out that those activities may be for food, they took example of Cairns which is the largest food processing company in Zimbabwe that required about 100 tones of groundnuts per year for peanut butter processing and its small proportion was produced by small-scale farmers Norman Mhazo (2003).

The agro-industrial sector includes manufacturers of food, beverages and tobacco, textiles and clothing, wood products and furniture, paper, printing and rubber products. This goes with the increase in number of employees; imagine the number of jobs created in processing of coffee, cassava and tea. Therefore it forms part of the broader concept of agribusiness that includes suppliers of inputs from the agricultural sector and distributes food and non-food outputs from agro-industry to consumers. In the same way Carlos da Silva (2009) confirmed that implementing agro processing results in improving agricultural transformation that take

place in the agro-economy within developing countries as part of broader processes of agribusiness development.

Under the same spirit Simalenga, (1996) contributed to this study adding that small-scale farming in Zimbabwe rarely provides sufficient means of survival in many of the rural areas.

It was therefore found to be very important to look at alternative income generating opportunities to support poor families who can no longer support themselves from the land- based activities alone. The Republic of South Africa National policy framework on small and medium agro-processing enterprises (2015), described that Agro-processing refers to those activities that change the form of agriculture, forestry and fisheries products into various forms to facilitate easier handling, increase storage life of agricultural output and market access. The wide-ranging nature of agro-processing implies a very wide range and heterogeneity of activities, which make their classification complex. He identified the concealed potential of agro-processing activities to promote growth and development. It is realized through its strong backward linkage with the primary sector or other input suppliers and also forward linkages related to income generated from other sectors of the economy like agriculture, forestry and fisheries. This displayed growth and created jobs leading to the highest employment multipliers in the economy which is validated by the fact that food processing sub sector is a largest sub-component of the manufacturing sector, as one of the sectors with the highest employment multipliers in the economy, that lead to economic development.

(Yakwezi, undated) put forward that development of agro-processing projects in developing countries was mostly associated with the production of export commodities and modern processing facilities that have been established as a consequence to this. This is because

traditional methods may not be able to compete with the modern technologies that are replacing them where local and indigenous knowledge may play a particularly important role in the food sector of developing agro-industries. Various economic conditions like fast urbanization as well as change in consumer habits have to be met by agro-industrial projects development in developing countries. Processing technologies includes harvest, storage and conservation, transport, processing of primary products together with recycling technologies.

Environmental conditions in developing countries present challenges to the development and application of these technologies.

(Yakwezi, undated) in his study found out how simple agro processing activities could give value-added products such as meat and cassava. He said that economic scenery of a rural village should be improved by such projects of agro processing. His study showed that implementing agro processing creates employment opportunities for different categories of people. This increases profit, as most of the products have a longer shelf-life in comparison to the raw material. Food processing leads to value addition that is needed to greatly improve livelihood of the farmers who are project beneficiaries. The topic of local and indigenous knowledge may play a particularly important role in the food sector of developing agro- industries. Processing increases the availability of quality products such as coffee along with opportunities for the beneficiaries to generate more income, since processing by its very nature is value- addition and to make this study the researcher used survey method to come to the findings of the research (Yakwezi, undated).

According to (Phia, 2012) to assess the impact of agro processing project, t-test analysis was used to indicate how implementation of agro processing contributed to the socio economic development of project beneficiaries. The results showed that there was improvement in

quantity of processed products, price of processed products and total income to beneficiaries and was significant at p = 0.05. The research recommended that much emphasis be laid on implementing agro-processing that leads to socio economic development of the beneficiaries with great potentials for poverty eradication.

The study found out that agro-processing, as the process of turning primary agricultural products into other processed commodities has the potential to provide potentially huge opportunities. It reduces wastage, enhance food security, and improve livelihoods for beneficiaries and other low-income groups. The study investigated the effect of implementing agro-processing project and value addition among beneficiaries from Fadama

II communities in relation to the advisory services and productive assets acquired. He gave an example of Fadama II beneficiaries to similar households in similar communities not included in the project as it provides a better estimate of the total impact of the project beneficiaries, (Phia, 2012). The findings of the study also indicated that implementing agro processing led to tremendous improvement of socio economic development of beneficiaries where they are more into processing than the non-beneficiaries. The example of the project given like Fadama II project which is the largest agricultural project in Nigeria aims to reduce poverty by supporting communities to acquire infrastructure, post-harvest processing technology and other productive assets. Implementing agro-processing projects is a vital instrument for enhancing income increases among project beneficiaries and it helped diversified income generating activities among themselves Phia (2012).

2.3 Critical Review and Research Gap Identification

From the literature reviewed authors slightly differ in approach of the topic under study saying that implementing agro processing projects contribute to economic growth leading to socio-economic development. Supporters of food security argued that implementing agro- processing projects concerns primary and secondary operations and transformation of agricultural commodities into different forms that add value to the product, Norman Mhazo,

(2003). He further said that manufacturing, tobacco and textiles processing that dominate the commercial industrial sector are owned by multinational corporations with interest in farm produce supplied by large-scale commercial farmers. But it was not highlighted on how primary and secondary operations are put in place after the implementation of the agro processing project that will lead to the socio-economic development. This justifies the reason for the research to find out contribution of these agro processing projects in terms of income,

Job creation and general life improvement of those employed on the projects.

The World Bank (1991) which talks about the challenges for development as the need to improve the quality of life, involving higher incomes, and standard of health and nutrition; a cleaner environment together with greater individual freedom; more equality of opportunity; better education, a richer cultural life and less poverty. Since 2000 the GoR has pursued the

National Decentralization Policy (MINALOC, 2004) based on the government’s commitment to politically, economically, socially and technically empower the local population to fight poverty. The report did not distinguish economic factors that leads to socio-economic development like income and jobs created and also for the role of agro processing projects as a source of income leading to socio-economic development; it is this that the research intends to point out more clearly.

Since Carlos da Silva (2009), showed that agro-processing concerns transformation of agricultural production that takes place in the agro-economy of developing countries for the emergence of agro-industrial sector as part of broader processes of agribusiness development.

The researcher did not put light on infrastructure development from where processing will be implemented. These structures will provide Jobs to both skilled and semi skilled workers during implementation of the projects.

Under the same spirit Simalenga, (1996) contributed to this study saying that small-scale farming in Zimbabwe rarely provides sufficient means of survival in many of the rural areas.

It was therefore found very important to look at alternative income generating opportunities to support poor households who can no longer support themselves from the land-based activities alone. Although he talked about agro processing but like previous authors did not stress how implementation of agro processing projects will contribute to socio-economic development. To have influence on socio-economic development the establishments of these projects creates more jobs, increase incomes hence improving health status and general well being of the beneficiaries. This motivated the researcher to conduct this study.

Yakwezi (undated) put forward that development of agro-processing projects in developing countries was mostly associated with the production of export commodities and modern processing facilities that have been established. This is because traditional methods may not be able to compete with the modern technologies that are replacing them where local and indigenous knowledge may play a particularly important role in the food sector of developing agro-industries. But in all this the author did not consider likely challenges like; poor access to markets because of high prices, lack and poor road systems in the villages from farms to

market areas; diseases and pests to crops before processing and infrastructure not in good condition which may impose unnecessary expenditure.

In FAO (1997), agro-industrial sector is termed as the subset of the manufacturing sector that processes raw materials and intermediate products derived from agriculture, fisheries and forestry. This included manufacturers of food, beverages and tobacco, textiles and clothing, wood products and furniture, paper products printing and rubber products forming part of the broader concept of agribusiness that includes suppliers of inputs and outputs from agro- industry to consumers. Again the research focuses on processing of raw materials and intermediate products from agriculture, fisheries and forestry but still this would increase output of the project that was not shown in the report.

This study will concern implementation of agro processing and socio-economic development in developing countries which largely depend on agriculture with survival as a major concern. Alinda and Abbott (2012), said government of Rwanda implemented PRS in the period 2000-2005 which marked an insignificant contribution to poverty reduction and progress in the agricultural production sector. The well known benefits of implementing agro-processing industries have led governments and other international development players to pay attention to the experiences and approaches favorable to investments in this sector.

There are lessons learned in agro-industrial development promotion worldwide, that are important to the design of policies and strategies that favor investments, improve efficiency, and foster competitiveness and inclusiveness in this economic sector.

Therefore, since agriculture and agro-industrial development promotion, is crucial in poverty reduction mostly in developing economies of which Rwanda is among; the researcher

developed interest, to carry out a study about transformation of agricultural production by implementing agro processing projects that may increase employment level to both skilled and semi skilled workers, increase income levels and tax revenues leading to socio-economic development.

2.4 Theoretical Framework

To begin with is the probabilistic theory as Program Evaluation and Review Technique suggests that a project schedule that perfectly fits its specified time constraints like concurrent expected and required project completion dates has a less than 50 percent chances of success. To meet the stated time frame, it requires appropriate staffing in implementing agro processing projects that leads to improved socio-economic condition of beneficiaries who are among the project team. Therefore, the degree by which the probability falls below

50 percent is a function of the degree of project uncertainty. This theory tries to explain that even realistic schedule requires some contingency planning for stopgap such as emergency funding. Contingencies tend to be too tempting to ignore as the project draws nearer to completion and they may be put to overzealous to project team members. This theory addresses objective (i) of the research topic Pinkerton (2003).

Also, it was found out that the systematic pursue of both detail and clarity in the development of project specification is absolutely essential to the success of project execution. The process used in pursuing this detail and clarity is referred to as value engineering. It is believed that reputation contribute to project management circles, on the ability of project manager and team to bring a project to a successful conclusion within limits of budget to which they have been committed. Many of the project budgets are overrun because of little money allocated to start with and even for failure to manage well project phases. This may be caused by

insufficient identification of the true project scope; upper management refusal to authorize a certain level of funding that will enable the project team to identify the true scope of the project and finally the refusal by either the project team or upper management to accept true magnitude of the project Pinkerton (2003). He also said that fast trucking as a method of saving time and shortening a project schedule identified two or more identifiable project components concurrently rather than consecutively. That to be successful, fast trucking requires thorough planning and superior execution. Proper execution and implementation enables fast socio-economic development of beneficiaries. Among fields that fast trucking works better are construction start and preoperational testing. Heerkens (2002) said that the most fundamental measure of project success relates to meeting the agreed upon targets such as functionality; if project deliverables cover the expected and quality; if the deliverables perform as well as earlier arranged.

The Lewis Theory of Development

One of the best-known early theoretical models of socio-economic development that focused on the transformation of a subsistence economy was that formulated by Nobel laureate W.

Arthur Lewis in the mid-1950s. The Lewis model became the general theory of the development process in surplus labor, developing nations during the 1960s and early 1970s.

It is still applied to study the recent growth experience in China and labor markets in other developing countries. In the Lewis model the underdeveloped economy consists of two sectors: This is the theory of development in which surplus labor from the traditional agricultural sector is transferred to the modern industrial sector. The growth of which absorbs the surplus labor promotes industrialization and stimulates sustained socio-economic development of project beneficiaries. This is where traditional, overpopulated rural

subsistence sector with no marginal labor productivity that allows Lewis to classify it as surplus labor. This can be withdrawn from the traditional agricultural sector without any loss of output and a high-productivity modern urban industrial sector into which labor from the subsistence sector is progressively transferred. The main focus of this model is on the process of labor transfer and the growth of output and employment in the modern sector or the industrial sector. Finally, Lewis assumed that the level of wages in the urban industrial sector was constant, determined as a given payment over a fixed average subsistence level of wages in the traditional agricultural sector. At the constant urban wage, the supply curve of rural labor to the modern sector is considered to be perfectly elastic. This theory addresses objectives i and iii of the research topic. Therefore, Lewis two-sector development model is simple and reflects the experience of economic growth.

2.5 Conceptual Framework

A conceptual framework helps to identify what to measure. For this particular study we have to clarify indicators of agro processing and for economic development. At the macro level, there are common impediments to the growth of the agro-processing industry that include inadequate infrastructure; policies and regulations that provide disincentives for investments, such as subsidies for imported alternatives; inefficient and non-transparent application of standards and licenses; financial regulations that prevent financial institutions from offering a broad range of financial products; and the absence of insurance products that help entrepreneurs manage the risks associated with sourcing raw materials and shipping perishable goods.

Independent Variable Dependent Variable

Implementing agro-Project Socio - E conomic Development

-Ground Preparation - Job Creation - Harvesting - Increase in income - Product Processing - Improved ubudehe status

Intervening Variable

- Resources availability -Adequate infrastructure,

- Government Policies

Source: Researcher’s (2016)

Figure 2.1: Conceptual Framework

The conceptual framework explains the two variables of the study and how they are related.

This indicates the research topic which talks about implementing agro processing and socio- economic development in Rwanda where by the former is an independent variable where as the later is a dependent variable. Here is that the independent variable which is implementation of agro processing determines or influences the status of dependent variable which is growth and socio-economic development in terms of increased jobs created, increased income levels and improved socio-economic status of project beneficiaries. This will consequently improve socio economic development in Rwanda through, improved life expectancy, literacy rate, personal dignity, freedom of association and personal safety. This intervening variable is this research is the transformation or processing to change the primary

operations to secondary operations so as to contribute on the way objectives of the study may be achieved.

2.6 Summary

This chapter has put forward the literature review of the study from a broader aspect and narrowed it down to our real situation. It highlighted different theories as put forward by different authors and identified the gap citing other studies that have been made on the related studies. It has also highlighted concepts and theories that are used for the particular study demonstrating a clear understanding of the theories and concepts that are relevant to the topic under the research paper.

CHAPTER THREE: RESEARCH METHODOLOGY

3.0 Introduction

According to Cohen (2000) it was stated that methodology in research is a systematic way of gathering data from a given population in order to generalize facts obtained from a larger population. Methodology embraces the research design, population, instruments used to collect data, considerations, data analysis and its ethical interpretation. It helps the researcher and the reader to understand the process of the research giving it a scientific significance.

3.1 Research Design

A qualitative and quantitative research design were chosen for this study in order to give a detailed description of the knowledge levels on implementation of agro processing projects and socio-economic development of beneficiaries. This helps to provide answers for questions associated with the research topic under study. Quantitative research is a formal, objective and systematic process for generating information about the world Burns & Grove

(1997).

According to Wood (1998), a survey was utilized to study characteristics in a population in order to investigate probable solutions of a research problem. A survey was used to investigate implementation of agro processing projects and contribution to socio-economic development in Rwanda taking a case study in Huye district of south province. The research data was collected in a natural setting using an interview or observation Wood (1998). In this study, a case study chosen was Maraba Coffee washing station; where employees who are at the same time beneficiaries of the project were questioned.

3.2 Target Population

Target population is “the entire aggregation of respondents that meet the designated set of criteria” (E. Neter, 2009). The study targets a population of 230 founder members of Maraba coffee washing station (MINICOM, 2011).

3.3 Sample Designs

Sampling involves a process of selecting a sub-section of a population (a sample) that represents the entire population in order to obtain information regarding the phenomenon of interest generalized for the entire population.

3.3.1 Sample Size

Considering the population size of 230 founders of Maraba coffee. Sample size (n) was calculated using Slovin’s formula (Andale, 2015).

n= N/1+N(e)2

Whereby; n = required sample size; N=Entire Population size.

e =Sampling error of 5% (0.05).

Thus;

- N= 230

- e=0.05 n=?

Therefore; n = 230/1+230(0.05)2; 230/1.575= 146

This formula allows the researcher to sample the population with a desired accuracy level

Israel (1992). Kothari (2004) suggested a degree of accuracy as a 95% confidence level and there are (95 chances in 100/ or 0.95 in 1) that the sample results represent the true condition of the population within a specified precision range of 5 chances in 100. Therefore, the calculated sample size is 146 respondents that were calculated from a total population of 230.

3.3.2 Sampling Techniques

Stratified sampling technique was used to ensure representation of the entire population by category. Then target population was categorized into strata of; Age, Gender, Education

Levels and Number of children for respondents. Age was categorized into: less than 20 years,

20-35 years, 36-45 years and above 45 years; Gender was categorized into Male and Female;

Education level was categorized into: Primary level, O level/ (TVT), Secondary school and

University and lastly number of children for the respondents as: none, 1-3, 4-6 and above 6 children. This helped to optimize group comparison; increase sample’s statistical efficiency; provide adequate data for analyzing various sub populations and to enable different research methods and procedures to be used in different strata. The researcher used this technique to identify how implementing agro processing impacted socio- economic development to beneficiaries Swami (1993).

3.4 Data Collection Methods

Leech (2010) pointed out that sources of data are both primary and secondary. To evaluate the overall value of primary data, the main techniques of primary data collection were interviews and questionnaires were given to project initiators in order provide relevant information to the study topic. Therefore, primary data were collected from respondents in

the form of answers to administered questionnaire as well as responses from interviewees. To get primary data, the researcher carried out field visits for interview and questionnaire distributions to get qualitative data. Secondary data is the data collected from books, journal and other publications to get quantitative data about the topic for determining the possible relationship that exists between implementing agro processing and socio-economic development of beneficiaries.

Vorhoef (1997), said that quantitative research is the numerical representation and manipulation of observation for the purpose of describing the phenomena that those observations reflect to and provide to the researcher the perspective of target audience through immersion in a situation and direct interaction with the people under the study whereby primary and secondary data were needed.

3.4.1 Data Collection Instruments

Data collection tools or instruments are administered questionnaires with an open ended question related to the research question responded by audience; interview guide; both for the sample size representing target population enables the researcher to get primary data.

Questionnaire

A questionnaire is an information guide technique Kendall (1993) that gathers information about; attitudes, beliefs, behaviors and characteristics from several respondents in the enterprise of study. The questionnaire contained closed ended questions addressed to respondents. Data collected was used in the next chapter for analysis, evaluation and interpretation of results. With close-ended questions, respondents had different alternatives

to choose in order to give response and have standard answers and were compared from person to person. They are much easier to code and to analyze which saves time and money.

The whole process of distributing questionnaires was as follows: the researcher first contacted the managing director of the Agro processing Project before the process started.

The researcher also issued a pre-test questionnaire to fill which helped the researcher to verify how understandable the questionnaire was to respondents. The pre-test questionnaire also enabled to identify the gaps and to make corrections where necessary before respondents started filling them.

The questionnaire distribution protocol was organized in a way that facilitated the process of collection. Here the researcher deliberately selected few of the staff members only from the projects and some of the population in close proximity; to whom the questionnaires were given for both distribution and collection after filling. In a few cases, the researcher had to be present personally so as to aid the respondents. Further, respondents were often clear about the meaning of the question and could often answer for what was required.

Interview guide

According to Bailey (1978) an interview is an instrument that is not given directly to respondents, but is filled by an interviewer who reads the questions to the respondent. In case the researcher had access to respondents, he interviewed them and responses were filled in the interview schedule. For better organization of the interview, the researcher made appointments with the respondents in order to have access to them. During the interview process, the researcher had a list of questions that he read to the respondent’s responses, the

researcher prepared a separate schedule as this would later facilitate the coding process. The researcher used interview guide as techniques to collect data from employees of the selected agro processing projects together with other beneficiaries to the projects by involved short and precise closed questions direct to the respondent.

Documentation

Bailey (1978) defines documentary study as a careful reading, understanding and analysis of written documents for some purpose other than social research. Here, the researcher collected from the already existing data, by finding them in the library. During documentary analysis, the researcher read related documents; after understanding and analyzing the relevance of texts to this study, he jotted them down and later typed them on a computer for compilation.

The researcher read from books, manual procedures, newspapers different dissertations, the internet and other publications, in relation to implementation of agro processing and socio- economic development of beneficiaries for presenting the gap in relation to the topic under study. Bailey (1978), asserts that one of the basic advantages of document studies is that they allow the research on a subject to which the researcher does not have physical access and thus where he cannot study by any other methods.

3. 4. 2 Administration of Data Collection Instruments

Before the administration of data collection instruments, the researcher requested for an introductory letter from the coordinator school of business and economics addressed to the managers of the institution from where the researcher collected data. Then the researcher collected answer questionnaires consequently to coding, data processing and analysis using

SPSS computer outputs so as to develop tables, and finally interpretation. The primary data

collected through questionnaires focused on implementation of agro processing and socio- economic development. These questionnaires were distributed among respondents by were trained enumerators. The researcher collected quantitative data from MINICOM about the selected project in the case study. Other materials like Books, reports, financial reports and various presentations were used to get relevant information to the topic under study

“Implementing Agro processing projects and Socio-Economic development of beneficiaries.”

3.4.3 Reliability and Validity

To respond on the issues of validity of data collection tools questionnaire were designed such that they have a link and in form of being related to the research for facilitating and understand of presented phenomenon under the study. To achieve on validity content the researcher used the simple words during interview and during formulating questions that help him to get real response to the asked questions. Reliability is a necessary component to determine the overall validity of a scientific experiment and enhancing the strength of results

Abel (2003). The researcher formulated different factors in relation to implementing agro processing and socio-economic development in Rwanda with Huye district as a case study.

3.5 Data Analysis Procedure

The researcher grouped ordered and structured the collected information for being processed, analyzed and interpreted. Data processing is transforming obtained information into meaningful and relevant information Williamson (1983). It consists of editing, schedules and coding the responses. The data processing began with editing, coding and finally with tabulation. The results for analysis used were results of Pearson Chi-square statistic values to prove significance probability p values in relation to the conventional p value = 0.05.

Roberts (1999) says that, data processing is a link between data collection and data analysis.

It involves the transformation of data gathered from the field into the system and codes it satisfying to quantitative analysis and tabulation. The researcher used techniques to process data before proper analysis so as to give a more meaningful interpretation. Data processing was done in accordance with general and specific objectives of the research study. After interviews and collecting questionnaires, collected information from respondents was grouped in terms of the research questions; they were processed and the information arranged in a meaningful and organized form; it was interpreted using bio data in relation research questions. The proposed study and analysis by using computer program SPSS (Anoloui,

2008) made an overall interpretation on implementing agro processing and socio-economic development of beneficiaries.

3.6 Ethical Consideration

This refers to some ethics that this research was built on. The researcher took care of consent, avoided leading questions and abusive language. Whatever activity related to this research was research purpose oriented, made respondents understand purpose of the research and participated freely. We assured confidentiality of this study and for academic purposes only by not disclosing the names of respondents or even information provided. Respondents were requested for objectivity and to answer questions without bias. Suppressing, Falsifying and inventing findings to meet the researcher’s and/or participants’ needs were eliminated.

CHAPTER FOUR: RESEARCH FINDINGS AND DISCUSSION

4.0 Introduction

In this chapter we find description of demographic characteristics of Respondents such as age, gender, marital status, education level, and number of children of respondents. It also indicates different questionnaires distributed and findings of the study as analyzed from collected primary data to answer research objectives.

4.1 Demographic Characteristics of Respondents

After designing questionnaires, they were sent to One Hundred Forty six (146) respondents and 143 were returned. The return back rate was (98 %). The remaining three (03) questionnaires were not returned due to lack of cooperation. Data were coded and edited for completeness before being generated and presented using SPSS computer packages. Methods of analysis used were summaries of tables showing cumulative frequencies, distribution tables and Pearson Chi square statistics results that were given to indicate the significance of the study.

Table 4.1 Frequency Table of respondents.

Status of Gender of Respondents Level of Marital status Children of

Response Respondent Age education Respondent

Valid 143 143 143 143 143

Missing 3 3 3 3 3

Total 146 146 146 146 146

Source: Primary Data (2016)

Table 4.1 indicates the number of respondents in relation to the selected sample size. There are only 03 respondents who missed out to return answered questionnaires. In this study the researcher recovered one hundred forty three (143) respondents who were cooperative and brought back answered questionnaires.

4.1.1 Findings about workers employed in respondents’ own activities.

Table 4.2 Gender of Respondent by number of workers employed in own activities.

Respondents’ Gender How many workers employed in your own activities Total

None Less than 3 4-6 Workers Above 6 Percent

Male 36 29 13 6 58.7 84

Female 9 33 14 3 41.3 59

Total 45 62 27 9 100.0 143

Source: Primary Data (2016)

Table 4.2 indicates findings about gender by workers employed in respondents’ own activities. Implementation of agro Processing projects and employment are emphasized by high and increasing levels of male involvement as the study put forward. It indicates that

58.7% of respondents were male and female employment was 41.3 %. Strong gender segmentation by age category in preparation, harvesting and processing tends that led more of men to socio economic development of beneficiaries. Results show that a total of 45 respondents were mostly among youths and drop outs from school who employed none of workers in their own activities but 62 respondents employed less than 3 workers. Findings also show that 27 of respondents employed 4-6 workers in their own activities whereas only

9 employed above 6 workers mostly in commercialized farming and retail trade.

Table 4.3 Pearson Chi-Square test to indicate significance level

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 13.538 3 .004

Likelihood Ratio 14.269 3 .003

Linear-by-Linear 4.590 1 .032

Association

Number of Valid Cases 143

Source: Primary Data (2016)

Table 4.3 shows results of Pearson Chi-square value of (χ2 =13.538) with 3 degrees of freedom and a significance probability of 0.004 a very high significant result. In an effort to answer research objectives the different strata of respondents who dealt in implementing agro processing projects were analyzed with the research questions each at a time. The researcher tested for a relationship between gender and number of workers employed in respondents’ own activities. In this case gender is the independent variable and the number of workers employed in respondents’ own activities is the dependent variable. From the interpretation it is a convention that if there is a very small probability (p=0.004) of the observed data less than p=0.05. Then the statistic is considered to be significant and the researcher can be 95% confident that the relationship between the two variables in this case gender and the number of employed workers in own activities, some factor other than chance is operating.

4.2 Findings on activity that gave earning before the project started.

Table 4.4 Respondents’ Age by sources of earning before the project started. Respondents’ What activity that gave you earning before this project started Total Age Casual Labor Cultivation Retail shop Commcial farming Percent Less than 20 4 3 0 1 5.6 8

20-35 15 22 8 1 32.2 46

36-45 4 42 16 7 48.3 69

More than 45 0 13 3 4 14.0 20 Total 23 80 27 13 100.0 143 Source: Primary Data (2016)

Table 4.4 indicates respondents’ sources of earning before the project started. It was assessed in relation to the 4 age brackets of respondents as indicated. From analysis 23 respondents were engaged in casual labor whereas 80 were dominant in traditional cultivation which that gives low earning level. Very few of respondents 13 were active in commercialized farming and about 27 dealt in retail shop.

Table 4.5 Pearson Chi-Square test indicating significance level Value d f Asymp. Sig. (2-sided) Pearson Chi-Square 30.536 9 .000 Likelihood Ratio 33.302 9 .000 Linear-by-Linear Association 14.377 1 .000 N of Valid Cases 143 Source: Primary Data (2016)

According to Table 4.5 Pearson Chi-square result on respondents’ age by types of earning activities before they joined the project. It indicated an association between age of those who implemented agro processing project and activities that gave earning before the project started from the population in which a sample of 230 is drawn for their socio economic

development. The significance p value below 0.001 is less than p value = 0.005. Therefore it

means that the researcher is 95% confident that age of respondents is related to the source of

earning before they joined the project. Respondents below 20 years of age make 5.6 % of the

total sample size and it is generalized to the population under study.

4.3 Findings on workers employed in Respondents’ own activities

Table 4.6 Respondents’ Age by number of workers employed in own activities Respondents’ Age Number of workers employed in own activities Total None Less than 4-6 Workers Above 6 Percent 3 Less than 20 5 2 0 1 5.6 8 20-35 26 15 5 0 32.2 46

36-45 13 35 16 5 48.3 69 More than 45 1 10 6 3 14.0 20 Total 45 62 27 9 100.0 143 Source: Primary Data (2016)

Then Table 4.6 45 respondents employed none of workers in their own activities whereas about 62 they employed less than 3 workers. Even 27 agreed to employ 4-6 workers and only 9 employed more than 6 workers in their own activities. Respondents are dominated by 48.3 % are grown up 36-45 years and very active on the project, 14.0 % are aged above 45 years , 32.2 % are mature 20-35 years and young with below 20 years.

Table 4.7 Pearson Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 33.442 9 .000 Likelihood Ratio 37.991 9 .000 Linear-by-Linear 22.163 1 .000 Association N of Valid Cases 143 Source: Primary Data (2016)

Table 4.7 is showing Chi- Square result of χ 2 = 33.442 with significance probability less than

0.001 which is less than conventional p value = 0.05. Therefore the researcher is confident enough to say that respondents’ age of those who implement agro processing project is related to the number of workers employed in their own activities that contribute to socio economic development of beneficiaries. This is reflected by a chi- Square statistic value that shows a stronger relationship between respondents’ age category that implements agro processing and the number of workers they employed in own activities that leads to improved social economic status of beneficiaries.

4.4 Findings whether infrastructure existed before the project started.

Table 4.8 Respondents’ Age by infrastructure that exist before the Project

Respondent’ Age Did there exist infrastructure before the Project Total

Yes No Percent

Less than 20 3 5 5.6 8

20-35 36 10 32.2 46

36-45 49 20 48.3 69

More than 45 12 8 14.0 20

Total 100 43 100.0 143

Source: Primary Data (2016)

According to Table 4.8 about (100) of respondents accepted that there was infrastructure

compared to (43) who said that there was no infrastructure. Those who agreed have age of

majority and understand required infrastructure to enable development of Maraba coffee agro

processing project.

Table 4.9 Pearson Chi-Square statistics Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 19.948 9 .018

Likelihood Ratio 13.003 9 .162

Linear-by-Linear Association .448 1 .503

N of Valid Cases 143

Source: Primary Data (2016)

Table 4.9 shows significant Chi-Square statistics results χ2 =19.948. This is explained by the

significance probability of 0.018 which is conventionally less than p value = 0.05. It brings

the understanding that the researcher is more that 95% confident that the relationship

between respondents’ age of those who implement agro processing project is related to those

who said there was existence of infrastructure before the project started. Respondents about

5.6 % were above the age of 20 meaning that the remaining total of about 94.4 % of

respondents had an understanding that infrastructure was appropriate to enable development

of the project.

4.5 Findings on Respondents’ experience on the project.

Table 4.10 Age of Respondent by years of working experience on the project Respondents’ Age Years of working experience at the project Total Above 5 years 3-5 years 1-3 years < 1 year Percent Less than 20 2 4 1 1 5.6 8 20-35 6 15 19 6 32.2 46

36-45 7 17 29 16 48.3 69 More than 45 1 2 7 10 14.0 20 Total 16 38 56 33 100.0 143

Source: Primary Data (2016) Table 4.10 is showing findings on how age is related to the years of working experience at the project. It indicates that a few of respondents 16 had spent above 5 years because of conservativeness and it took them time to join the project and about 56 respondents had spent

1 to 3 years. Majority of them (29) were grownups with the age between 36-45 years.

Table 4. 11 Pearson Chi-Square statistic test

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 17.121 9 .047

Likelihood Ratio 16.604 9 .055

Linear-by-Linear Association 12.000 1 .001

N of Valid Cases 143

Source: Primary Data (2016)

From the top row of Table 4.11; Pearson Chi–Square statistic tests is χ2 =17.12 and p value= 0.047 less than the conventional p value = 0.05. The results indicate that the researcher is about 95% confident to generalize from a random sample to the entire population of 230 that there is relationship between the two variables in this case; respondents’ age of those who implement agro processing project is related to the years of working experience at the project that contribute to socio economic development of beneficiaries.

4.6 Findings on the Ubudehe category level after joining the project.

Table 4.12 Respondents’ level of education by Ubudehe category Level.

Respondents’ level of Ubudehe category Level after joining the Project Total education Poor Resourceful Poor Rich Wealthier Percent

Primary 15 50 23 1 62.2 89

O Level(Tvt) 3 7 6 1 11.9 17

Secondary 9 13 5 0 18.9 27

University 2 2 4 2 7.0 10

Total 29 72 38 4 100.0 143

Source: Primary Data (2016)

Table 4.12 is showing that (62.2%) equivalent to (89) of respondents have primary education and among them (50) are falling in Ubudehe category level of the resourceful poor. Findings have indicated that many of respondents have graduated to Ubudehe category level of resourceful poor (72) followed by the rich (38) from the category level of the poor before joining the project. It is evident that education level of respondents who implemented agro processing project as an independent variable is related to socio economic development of beneficiaries as shown by change from one category level to another as an dependent variable. Among respondents those who belonged to the wealthier (4) are still few but as they spend more time on the project the number is likely to increase. This relates to the change of respondents’ livelihood who are also project beneficiaries.

Table 4.13 Pearson Chi-Square test for Significance level

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 20.229 9 .017

Likelihood Ratio 15.103 9 .088

Linear-by-Linear Association .109 1 .741

N of Valid Cases 143

Source: Primary Data (2016)

According to Table 4.13 the Pearson Chi – Square tests indicated that education level has a significant influence on how Ubudehe category Level changed after joining the Project. This is indicated by a significant probability p value = 0.017 and the Chi – Square test (χ2 =20.23) compared to the conventional p value = 0.05. This means therefore that the researcher is

95% confident to say that respondents’ level of education is highly related to the general living condition as indicated by changing of Ubudehe category level from the poor to the resourceful poor 72, the rich 38 and wealthier 4 respectively. There are 29 respondents who are still falling in the category level of the poor mostly those who recently joined the project.

This is because the higher the Pearson chi-square value is the lower the significant probability for the relationship between the 2 variables education level and Ubudehe category level.

4.7 Findings on how many workers employed by those who joined the project.

Table 4.14 Number of Respondents’ Children by wworkers employed in respondents’ own activities.

Respondents’ number Number workers that you employed in your own activities Total of children None Less than 3 4-6 Workers Above 6 Percent

None 23 9 4 2 26.6 38

1-3 6 14 5 1 18.2 26

4-6 12 32 14 4 43.4 62

Above 6 4 7 4 2 11.9 17

Total 45 62 27 9 100.0 143

Source: Primary Data (2016)

In Table 4.14 it is indicated that (45) respondents did not employ workers in their own activities and these are mostly among those who were engaged in casual labor and those who recently joined the project. Here respondents were asked on the number of workers they employed in their own activities compared to the number of children that respondents had. In this case the number of children is an independent variable whereas number of employed workers in their own activities is a dependent variable. It is also observed that 62 respondents employed less than 3 workers in their own activities whereas 27 respondents employed 4-6 workers and only 9 respondents employed above 6 workers. Again, among respondents only 17 represented by 11.9 % had more that 6 children and they employed less of workers because they used their children as source of labor. Those respondents with 4-6

children employs more of the workers because it is an active category of workers as it can be compared to the previous tables where they may have age category of mature people.

Table 4.15 Pearson Chi-Square test for Significance level. Value df Asymp. Sig. (2-sided) Pearson Chi-Square 22.228 9 .008 Likelihood Ratio 21.272 9 .011 Linear-by-Linear Association 9.911 1 .002 N of Valid Cases 143 Source: Primary Data (2016)

Table 4.15 reflects that the Pearson Chi-Square test result χ2 =22.228 with 9 degrees of freedom and a significant probability of 0.008 less than p = 0.05. It indicates that respondents who implemented agro processing with many children employed less of workers in own activities because they used their children as source of labor. It indicates that number of children is significant to the number of workers employed in their own activities that contribute to socio economic development of beneficiaries.

4. 8 Findings according to experience motivation to join the project.

Table 4.16 Number of children by the motivation to join the project Respondents’ no. of What is the motivation to join the project Total Children. Market Lack of Jobs Social Protection Other Percent None 25 8 2 3 26.6 38 1-3 8 15 3 0 18.2 26

4-6 26 23 9 4 43.4 62 Above 6 7 4 5 1 11.9 17 Total 66 50 19 8 100.0 143 Source: Primary Data (2016)

Table 4.16 concerns findings on the number of children for those who implemented agro processing and the motivation to join the project that led to their socio economic development. It was found out that respondents with about 4-6 children were highly motivated to join the project with 62 representing 43,4% of respondents compared to others.

It is also indicated that due to available market for the mountain quality coffee motivated about 66 of respondents to join Maraba coffee agro processing project. Others were motivated by lack of Jobs 50 of respondents whereas 19 motivated by social protection and 8 for other reasons that were not disclosed to the researcher respectively.

Table 4.17 Results of the Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 18.695 9 .028 Likelihood Ratio 19.411 9 .022 Linear-by-Linear Association 3.772 1 .052 N of Valid Cases 143

Source: Primary Data (2016)

According to Table 4.17; findings have indicated that respondents with children ranging between 4-6 have significantly found it necessary to join the project. This is indicated by results of the Pearson Chi square statistics tests χ2 = 18.695 and 9 degrees of freedom with a significance probability p value = 0.028 which is less than the conventional p value = 0.05.

This marks a very highly significant result. This evidences that the data appears to be no doubt that there is an association between respondents’ number of children and motivation to join the project. This means that the researcher can now be 95% confident that the relationship between respondents’ number of children is related to the motivation for joining the project and the relationship between the two is not due to chance.

CHAPTER FIVE: SUMMARY CONCLUSIONS AND

RECOMMENDATIONS

5.0 Introduction

This chapter presents summary of major findings, conclusion and recommendations. Finally, it presents suggestions for further studies that could be carried out in relation to agro processing and socio economic development.

5.1 Summary of Findings

Based on the analysis and discussions presented in chapter four, the researcher has presented the summary of major findings in relation to categories of respondents that represent entire population to answer the research objectives. The researcher started by identifying if respondents who responded back as they were given questionnaires and it was found out that

143 who representing 98% of respondents. Then by gender 58.7 % were men while 41.3% comprised of women. This indicates that implementation of Maraba coffee agro processing project is majority by men compared to women. It is also evident that respondents fell in the age brackets of teenagers with below 20 years, 20-35, 36-45 and finally above 45 years in percentages of 5.6%; 32.2%; 48.3% and 14.0 % respectively, as referred to Table 4.4.

It really shows that respondents with below 20 years representing 5.6% and even the aged whose age is above 45 years is 14.0%. Therefore respondents with middle age 20-35; 32.2 % and mature people 36-45, 48.3% pre-dominantly joined and implemented agro processing project to improve their social economic status. This indicates that few of teenagers joined the project because most of them are still in school except school drop out for personal

reasons. Again this brings to the understanding that 62.2 % of respondents studied primary school and 11.9% attended for ordinary level or TVET. Then 18.9 % completed secondary school that is the 12YBE followed by 7.0 % of respondents who were University graduates that joined the project to improve project management. Those who implemented agro processing were identified in terms of the number of children they had where 26.6 % had no children, about 18.2 % had 1-3 children whereas 43.4 % of respondents had 4-6 children and

11.9 % of respondents had more than six children and it showed a significant relationship to socio economic development of beneficiaries.

It has also indicated that age of respondents that implemented agro processing were identified to the activities used for earning before the project started, they agreed that infrastructure existed before the project started, it also had relationship with working experience and to the number of workers employed in respondents activities. According to table 4.12 it is significant that education level for those who implemented agro processing project as related to the change of Ubudehe category level of respondents who were beneficiaries. This is because the level of education is highly related to the level of living status as reflected by improvement in the Ubudehe category level hence the socio economic status of beneficiaries.

In this case, respondents’ families with children ranging from 4-6 were (43.4 %) of respondents and dominated Maraba coffee agro processing project followed by those with no children 26.6%. These are mostly youth and recently married couples with children from 1 to

3 (11.9%) and lastly those with more than 6 children 11.9 %. This showed that many of respondents have started conceptualizing the importance of family planning campaigns and as time goes on birth rates will slow down. Again for a family with more than 6 children the

elder ones have joined the projects on their own and they are no longer dependants to their fathers and mothers.

5.1.1 Objective One: Implementing Maraba Coffee agro processing project and employment in Huye district for the 5 year period.

Findings show that (56) of respondents have been working at the project for about 1 to 3 years, followed by those with 3 to 5 years who were found to be 38 respondents. It also indicated that 16 of respondents had spent more than 5 years and finally 33 have experience of less than one year. For about 5 years very few had understood importance of the project up to recent years when they started joining the project increasingly in numbers. It was also found out that activities that gave earning to respondents were 80 in traditional cultivation followed by retail shop 27 of respondents, then in casual labor 23 mostly among youth and finally 13 dealing in commercialized farming. Conclusively this means that a big number of respondents relied heavily on traditional cultivation, followed by retail shop, casual labor and lastly in commercial farming. Findings were related to respondents’ age and on the number of children of respondents as indicated in table 4.4. This was the same to the number of workers that were employed in respondents’ personal activities. This confirms that the researcher is confident to say that 95 % of age to working experience, to the activity that gave earning before the project and the number of workers employed in respondents’ activities is not by chance.

5.1.2 Objective Two: To analyze factors responsible for development of Maraba Coffee agro processing project in Huye district.

For the 5 year period under study it was found out that majority of respondents (66) considered potential market of the quality coffee as a motivating factor to develop and join

Maraba Coffee Agro processing project. Some of the respondents said that lack of Jobs (50) in other sectors of employment was also a motivation to join the project, mostly youth and the middle age followed by those who considered social protection 19 and 8 of respondents who said that they joined the project for personal reasons that were not disclosed to the researcher. It really indicates that the first two factors motivated a large number of respondents to have joined implementation of the agro processing project. In terms of

Infrastructure development (100) of respondents responded that there was infrastructure whereas (43) said that there was no infrastructure. About 85 of respondents with age 20-35 and 36-45 accepted there was infrastructure while 30 respondents of the same age group said that there was no infrastructure. This brings the understanding that the researcher is confident to mention that respondents’ age and the number of children that implemented the agro processing project have relationship with the motivation to join the project and the response on the existence of infrastructure before the project started and all these encouraged development of Maraba coffee agro processing project leading to socio economic development of beneficiaries.

5.1.3 Objective Three: To determine relationship between implementing Maraba Coffee agro processing Project and socio economic development of beneficiaries in Huye district

For the 5 years period under study when respondents were asked on how the project contributed to change of the Ubudehe category level and its significant change in the socio economic status of project beneficiaries who were also respondents. In this case the proportion of the poor had improved from the Ubudehe category level of the poor to the resourceful poor which reflect an increase in the socio economic status of the project beneficiaries. Even the numbers for the rich have increased but still there is a slow increase of the wealthier. This indicates that among 143 respondents only 29 were still in the category of the poor and 114 of the respondents graduated to the resourceful poor, the rich and the wealthier respectively. Change of Ubudehe category level to another level indicates change of the socio economic status of project beneficiaries and subsequently changing livelihood.

Respondents accepted that their lives improved because they bought livestock in order to get manure to fertilize coffee and milk to reduce cases of malnutrition and Kwashiorkor among their children where most of youth brought land and houses to get start up for their lives.

5.2 Conclusion

Rwanda is depending largely on agriculture like any other developing country where the economy provides about 90% of national food needs. The country has considered raising agricultural productivity and improvement of food security among its priorities. It is also aiming on promoting human development, population growth and development which hinges on one of the pillars of Vision 2020 “Transformation of agriculture into a productive, high value, market oriented sector by modernizing 50 per cent of its agriculture by 2020. This

goes with improving livelihoods mainly of the rural population, achieve food security and increase exports of agricultural products. This justifies why a large number of the population engages in agriculture and development of agro processing projects because of their employment potential and provision of low cost food to the population. Agriculture contributes about 34% to the national Growth Domestic Product employing about 83% of

Rwandan population. The sector employs a high percentage of nationals but because it is mostly traditional cultivation and its contribution to GDP is still very low and averagely 70

% of exports. This calls for efforts to modernize agriculture while introducing agro processing projects among others. It is therefore evident that this study tried to answer research questions in relation to the achievement of the objectives.

The study has found out that for Maraba coffee agro processing project to develop factors like water and electricity, road network and internet contributed significantly to that. Many of respondents also considered potential market for the quality coffee led to development of the project. There was also lack of Jobs mostly to the youth and middle aged among respondents who joined the project, then consideration of social protection mostly to widows, divorced and other vulnerable groups of people in order to get comfort and lastly for other reasons that were not disclosed to the researcher. It really indicates that the first two motivated a big number among respondents to have joined the project.

Another research question that was addressed concerns how Maraba coffee agro processing project contributed to socio-economic development of beneficiaries in Huye for the 5 year period under study. This was also addressed by the way Ubudehe category level changed from the poor to resourceful poor, to the rich and the wealthier which indicates improvement of socio economic status of the project beneficiaries.

5.3 Recommendations

Agriculture plays a supportive role in socio-economic development. With its primary purpose

of providing sufficient low-priced food and employment it is a leading sector in the overall

strategy of socio-economic development. Among the world’s poor 75% who live in rural

areas, have agriculture as a major source of livelihood. In Rwanda community socio-

economic development is mainly a contributed by agriculture growth, population growth and

development. In this case about 80 percent of the rural population depends on agriculture as

the only driver for the country’s socio economic development and this has implemented a

comprehensive agricultural development strategy that goes with fighting poverty achieved by

proper implementation of agro-processing industries. The researcher would like to put

forward the following as recommendations to project beneficiaries and to policy

makers/government authorities. a. The Project beneficiaries

- It is recommended to improve use of good farming practices and integrated pest management

systems through focused support from agricultural officers. It is recommended to improve

quality of processed coffee for competitiveness.

- It is importance to provide a voluntary and all-round support program for Maraba coffee agro

processing project because of its potentiality to become useful to beneficiaries. It is

necessary to implement value addition activities like harvesting, drying, packaging and

storage in a partnership with the management of Maraba coffee agro processing project.

- It is important to improve sales and distribution mechanisms through capacity building of

project employees and beneficiaries, addressing existing disparities and improve gender

equality in the agriculture sector.

- It is recommended that more of the population within the district should join the project or

even form others. This is because it contributes significantly to curbing unemployment with

in the area and among the youth.

- Emphasis should be put such that university graduates should be encouraged to join the

project to get involved in the management of the project and this may address poor project

management. b. The government/Local Authorities

- The study should help local authorities to strengthen functioning mechanism of agro-

processing Projects and for their contribution to socio economic development of

beneficiaries.

- Efforts should be put in formulating policies and regulations that encourage development of

agro processing projects with a view to socio economic development of beneficiaries.

- Agricultural officers should help to identify hybrid coffee seeds and other crops favorable to

the area in order to increase productivity and increased employment potential. It will help to

understand contribution of nontraditional crops in socio economic development and enable

subsidization of fertilizers, quality seeds, social amenities like water and power.

- The government, MINAGRI and partner institutions to show their support on agro-

processing projects in order to strengthen management aiming at performance improvement,

efficiency and effective utilization of the project.

- The study should focus on other agro processing projects that contribute to socio-economic

development of beneficiaries in Rwanda.

- It is also crucial to exhaustively identify all potential constraints for implementation of the

agro processing project for improvement.

5.4 Suggestions for further study

The researcher suggests the following areas as necessary for further study in the field related

to agro processing and socio economic development of beneficiaries. This would be

contributive to a wide knowledge of researchers to make study on the following.

i) The study on how implementation of agro processing projects of nontraditional crops

contributes to socio economic development of beneficiaries.

ii) The role that microfinance institutions contribute to the development of agro

processing projects.

iii) What are other determinants of socio economic development in Rwanda?

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APPENDICES

APPENDIX I: LETTER OF INTRODUCTION FROM COORDINATOR SCHOOL OF POSTGRADUATE STUDIES

APPENDIX II: LETTER FROM MARABA AGRO PROCESSING PROJECT

APPENDIX 111. QUESTIONNAIRE

Dear Respondent,

My names are Vincent MWEBAZE a student at MKU in Masters program. I am carrying out a study whose topic is “Agro Processing and Economic Development in Rwanda with A

Case Study of Maraba Coffee in Huye district, South Province”. Being one of the respondents to be involved, I would like to thank you for your response and I ensure you that information you provide will be used for the purpose of this study; and will be kept secret and confidential.

Identification/BIO-DATA

1. Indicate your gender/ (Garagaza igistina) a. Male/Gabo ( ) b. Female/Gore ( )

2. Indicate your Age/Imyaka a. Less than 20/Munsi ya 20 ( ) b. 20-35yrs ( ) c. 36- 45 yrs ( ) d. Above 45 yrs/Hejuru ya 45 ( )

3. Mention your Level of Education/ Amashuri wize a. Primary/ Abanza ( ) b. O level/TVET/Ikiciro rusange/imyuga ( ) c. Secondary/Ayisumbuye ( ) d. University/Kaminuza ( )

4. What is your marital status/ Iranga mimerere a. Single/ Ingaragu ( ) b. Married/ Yarashatse ( ) c. Divorced/Yaratandukanye ( ) d. Widow/Yarapfakaye ( )

5. How many children do you have?/ Ufite abana bangahe a. None/Ntawe ( ) b. 1-3 ( ) c. 4-6 ( ) d. Above 6/Hejuru ya batandatu ( )

Objective 1: To examine the role of implementing Maraba coffee agro-processing project on employment in Huye district. (Kureba uruhare rwo gushyira mubikorwa umushinga wa Maraba Coffee mu gutanga akazi mu Karere ka Huye).

6. State how long you have been working at the project. (Vuga igihe umaze ukora kuri uyu mushinga) a. Above 5yrs ( ) b. 3-5yrs ( ) c. 1-3yrs ( ) d. Less than 1 yr ( )

7. What was your monthly earning level before this project started? (Winjizaga amafranga angana iki mbere y’uko utangira gukora muri uyu mushinga?) a. Hagati ya 500- 5000 ( ) b. Hagati ya 5001-15000 ( )

c. Hagati ya 15001- 25000 ( ) d. Above 25000/ Hejuru ya ( )

8. What activity that gave you earning before this project started? (Nibihe bikorwa byaguhaga amafranga mbere y’uyu mushinga gutangira?) a. Nothing/ Ntabyo ( ) b. Traditional cultivation/Guhinga bisanzwe ( ) c. Retail shop/Ubucuruzi bw’iduka ( ) d. Commercialized farming/Ubuhinzi bw’umwuga ( )

9. How many workers that you employ in your own activities in this last 5 years?

(Wakoreshaga abantu bangana iki mubikorwa byawe bwite mu myaka itanu ishize?) a. None/ Ntabo ( ) b. Less than 3/ Munsi ya batatu ( ) c. 4-6 workers/ Hagati ya 4-6 ( ) d. Above 6/ Hejuru ya 6 ( )

Objective 2: To analyze factors responsible for development of Maraba Coffee Agro processing Project in Huye district. (Gusesengura impamvu zateje imbere umishinga ishingiye kubuhinzi bw’ikawa wa Maraba Coffee Project mu Karere ka Huye.)

10. According to your experience what is the motivation to join the project?

(Ukurikije uburambe ufite nizihe mpamvu zatumye mwitabira uyu mushyinga?) a. Market availability/ Kubera isoko ( ) b. Lack of Jobs/ Kutagira akandi Kazi ( ) c. Social Protection ( ) d. Any other/ Indi mpanvu ( )

11. What infrastructure do you have in this area like?/Nibihe bikorwa remezo mufite muri aka Karere nka;) a. Roads/ Imihanda ( ) b. Water and Electricity/ Amashanyarazi ( ) c. Internet/Enterineti ( ) d. All /Byose ( )

12. Did these infrastructures exist before the project started? (Ibi bikorwa remezo byari bihari na mbere?) a. Yes/Yego ( ) b. No/ Oya ( )

Objective 3:). To determine the Relationship between Maraba coffee agro processing project and socio-economic development of beneficiaries in Huye district.

13. Do you find this project beneficial to you in the following?/(Ese uyu mushinga wakubereye ingira kamaro?) a. Buy land/Waguze ubutaka ( ) b. Buy/Build a house/Wubatse inzu ( ) c. Means of transport/Waguze ikinya biziga ( ) d. Buy more livestock/Waguze amatungo ( )

14. Do you find it necessary to improve following? a. Changing Management ( ) b. Modification of coffee seeds ( ) c. Increasing the number of agricultural officers ( ) d. Modify Processing Mechanism ( )

15. What was your category level for UBUDEHE before this project started? a. Poor ( ) b. Resourceful Poor ( ) c. Rich ( ) d. Wealthier ( )

16. Has the category level changed now? If Yes show the new category level. a. Poor/Umukene ( ) b. Resourceful Poor/Umukene wifashije ( ) c. Rich/Umukire ( ) d. Wealthier/Umukungu ( )

17. What do you find as a constraint at this project? a. Poor farming practices and integrated pest management system. ( ) b. Reduced value addition ( ) c. Weak sales and distribution mechanisms ( ) d. Shortage od agricultural officers ( )

18. From your opinion what impact has implementation of Maraba coffee agro processing project brought to your socio economic development? a. Low ( ) b. Average ( ) c. High ( ) d. Very High ( )

Thank you very much for your time allocated to answer this questionnaire and cooperation.