VALUE CHAIN ANALYSIS OF FISH TRADE ALONG NIGERIA … · 3.4.7 Market Structure 21 3.4.7.1 Ease...

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VALUE CHAIN ANALYSIS OF FISH TRADE ALONG NIGERIA

REPUBLIC OF BENIN BORDER

BY

PELUOLA, DEBORAH ABOSEDE

MATRICULATION NO: 189377

A PROJECT REPORT SUBMITTED IN PARTIAL FULFILMENT OF

MASTER OF SCIENCE DEGREE IN THE DEPARTMENT OF

AQUACULTURE AND FISHERIES MANAGEMENT,

FACULTY OF AGRICULTURE AND FORESTRY,

UNIVERSITY OF IBADAN

OCTOBER, 2016

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ABSTRACT

Fish trade is an important tool in the distribution of fish and fish product from production point

to point of demand where it can exchange cost for revenue. However, there have been challenges

in developing inter-regional trade in West Africa as a result of limited empirical evidence and

data on fish trade in the region. Therefore, this study assesses socio-economic characteristics,

profitability, and technical efficiencies of value-chain actors along Nigeria Benin border.

A total of six States (Oyo, Kwara, Ogun, Lagos, Niger and Kebbi states) were purposively

selected for the study, as they lie along Nigeria-Benin borders. Multi-stage sampling technique

was used in the study. Primary data were collected from 132 artisanal fishermen, 132 fish

farmers, 264 fish processors, and 264 fish trader in the study area using group discussion and

structured questionnaires. Socio-economic data collected were subjected to descriptive analysis,

budgetary analysis techniques were used to estimate the profitability, Cobb-Douglas function to

estimate the technical efficiency while regression analysis was used to determine the marketing

structure of the respondent value-chain actors.

Majority (92.42%, 87.88%, 54.55% and 59.09%) of the artisanal fishermen, fish farmer, fish

processors and fish traders respectively were male. In all the sampled States, majority of the

respondents are between the age range of 31-40 and 41-50 years except for Kebbi State where

age range of 51-60 and above 60 dominate. The profitability analysis indicated that respondent

artisanal fishermen and fish farmers in Lagos had the highest mean monthly revenues of

₦278,092.50±229,206.53 and ₦2,408,461.54±1,249,180.37, respectively while respondent

artisanal fishermen and fish farmers in Kwara State had the least revenues of

₦61,349.47±31,665.94 and ₦461,511.58±336,954.31, respectively at P<0.05 (significantly

different). Smoked fish had the highest percentage of the fish product (79.35%) produced by the

respondent fish processors followed by dried fish with 18.02% while spiced fish and fried fish

had the least percentage of 1.11% and 1.52% respectively. Estimate of 1.29% of the smoked fish

processed by the fish processors were produced from fresh fish imported through inter-regional

trade across Nigeria-Benin border by the fish processors in Ogun State. Meanwhile in Lagos

State inter-regional trade of 90.00±36.37kg (66.05%) of dried fish existed, which was

significantly higher than 46.26±13.95kg (33.95%) of dried fish marketed in intra-state trade

through the Seme Border by the respondent fish processors. The regression analysis pointed to

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the fact that scale economies was observed among the respondent dried fish traders in Ogun, Oyo

and Niger States respectively as well as frozen trader in Kebbi State. The Cobb-Douglas function

indicated that the fish farmers and fish processors had average technical efficiency of 0.88±0.02

and 0.89±0.02, respectively.

In conclusion, value-addition is a lucrative business irrespective of the fish products produced by

the respondent value-chain actors. Although, inter-regional trade was observed among the fish

processors and traders, the percentage of processed fish products (dried and smoked fish) traded

and the number of value-chain actors involved was extremely low. This study therefore

recommended the need for provision adequate fish trade facilities to boost inter-regional trade in

the study area.

Keyword: Profitability indices, technical efficiency, inter-regional fish trade, Cobb-Douglas

function.

WORD COUNT: 499.

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DEDICATION

This project is dedicated to Almighty God, the beginning and the end to whom I owe my entire

life.

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ACKNOWLEDGMENTS

I acknowledge supremely the almighty God, my creator, heavenly Father and helper, to whom I

owe my life.

My acknowledgement goes to my supervisor Prof A.E Falaye for giving me the opportunity of

being part of this research, his fatherly help, contributions and encouragement. I profoundly

appreciate the intellectual contributions and indelible supports of the Head of Department of

Aquaculture and Fisheries, University of Ibadan, Prof E.K Ajani as well as the Dean of Faculty

of Agriculture and Forestry, Prof B.O Omitoyin. I appreciate all teaching and non-teaching staff

of the Department of Aquaculture and Fisheries, University of Ibadan, for their support in this

study.

My profound gratitude goes to the World Fish Centre, New Partnership for Africa’s

Development (NEPAD) and African Union Inter African Bureau for Animal Resources (AU-

IBAR), for sponsoring this research. I also appreciate the efforts of the resource persons who

helped in administering the questionnaires in all the states.

It is with great pleasure that I appreciate my beloved husband, Mr Peluola Abolade, for his

support and encouragement. I also appreciate my beloved son, John Peluola with whom we did

this project from pregnancy.

I have the pleasure to honour my parents, Mrs Ige & late Hon. Joshua Ige, whose legacy has

made me and my siblings for their support physically and spiritually. God will continue to enrich

your life in all areas.

I also appreciate Mr O. I. Okeleye for his effort and help towards the success of this project.

Special thanks to all my colleagues for their undeniable supports during the course of this study.

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CERTIFICATION

I certify that this work was carried out by PELUOLA, DEBORAH ABOSEDE in the

Department Of Aquaculture and Fisheries Management, Faculty of Agriculture and Forestry,

University of Ibadan, Ibadan, Oyo State, Nigeria.

__________________________ ________________________

Supervisor Date

Professor A. E. Falayi Ffs.

B.sc. (Plymouth), M.Sc. (Stirling), Ph.D (Ibadan).

Professor of Aquaculture: Fish Nutrition and Environmental Management.

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TABLE OF CONTENTS

Thesis title i

Abstract ii

Dedication iv

Acknowledge v

Certification vi

Table of Content vii

List of Tables xiv

List of Figures xxii

List of Plates xxvi

List of Appendices xxv

CHAPTER ONE 1

1.0 INTRODUCTION 1

1.1 Background of the study 1

1.2 Justification of the Study 2

1.3 Objectives of the Study 4

CHAPTER TWO 5

2.0 LITERATURE REVIEW 5

2.1 Theoretical framework 5

2.1.1 Market Participation and Structure-Conduct-Performance (S-C-P)

Framework 5

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2.1.2 Efficient Market Hypothesis (EMH) 5

2.2 Fish Production in Nigeria 6

2.2 Value Chain 6

2.3 Value-Chain Actors in Fish Marketing in Fisheries and Aquaculture 7

2.3.1 Socio-Economic Characteristics of the Value-Chain Actors in Fish Marketing 7

2.3.2 Profitability of Value Addition in Nigerian States 10

2.4 Fish Trade 11

2.5 Technical Efficiency of Value-Chain Actors 12

2.6 Major constraint of Value-Addition 12

CHAPTER THREE 14

3.0 METHODOLOGY 14

3.1 Study Area 14

3.2 Sampling procedure 18

3.3 Data collection 18

3.3.1 Questionnaire Design 19

3.3.2 Validation of Questionnaire 19

3.4 Data Analysis 19

3.4.1 Socioeconomic Characteristics 19

3.4.2 Profitability and Marketing Efficiency Indices 19

3.4.3 Market Margin Analysis 20

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3.4.4 Marketing Efficiency 20

3.4.5 Gross margin analysis 20

3.4.6 Net Return 21

3.4.7 Market Structure 21

3.4.7.1 Ease of/or Barrier to Entry or Exit 21

3.4.8 Technical Efficiency and Production Function 22

CHAPTER FOUR 23

4.0 RESULT 23

4.1 Socio-economic Characteristics of Actors along the chain 23

4.1.1 Socio-economic characteristics of artisanal fishermen along Nigeria-Benin 23

border

4.1.2 Socio-economic characteristics of Artisanal Fishermen in Sampled States 25

along Nigeria-Benin border

4.1.3 Socio-economic characteristics of Respondent Aquaculture Producer along 29

Nigeria-Benin Border

4.1.4 Socio-economic characteristics of Aquaculture Producers in Sampled States 29


4.1.5 Socio-economic Characteristics of Fish Processor along Nigeria Benin-border 34

4.1.6 Socio-economic Characteristics of Processors in Sampled States along 36

Nigeria-Benin border

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4.1.7 Socio-economic characteristics of fish traders along Nigeria-Benin border 39

4.1.8 Socio-Economic Characteristics of Fish Traders in Sampled States along 39


4.1.9 Socioeconomic characteristics of Consumers in Sampled States along 44


4.2 Profitability Indices of the Respondent Value-Chain Actors 46

4.2.1 Monthly Quantities, Cost Variables and Profitability Indices Associated With 46

Fresh Fish Caught and Marketed By Respondent Artisanal Fishermen along


4.2.2 Mean Monthly Quantities, Cost Variables And Profitability Indices of 48

Respondent Artisanal Fishermen in Sampled Nigeria States along

Nigeria-Benin Border According to Scale of Operation

4.2.3 Mean Monthly Quantities, Cost Variables and Profitability Indices Associated 53

with Fresh Fish Produced and Marketed By Respondent Fish Farmers along


4.2.4 Mean Monthly Quantities, Cost Variables and Profitability Indices of 56

Respondent Fish Farmers in sampled Nigeria States along Nigeria-Benin

Border According to Scale of Operation

4.2.5 Forms of Fish Products Produced By Respondent Fish Processors 59

4.2.6 Average Monthly Quantities, Costs, Profitability and Marketing Efficiency 59

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Indices of Fish Products Marketed

4.2.7 Average quantities, costs, profitability indices and marketing efficiency of 65

dried fish products produced by respondent fish processors in Nigeria States

along Nigeria-Benin Border


Smoked fish products produced by respondent fish processors in Nigeria States



Fried fish products produced by respondent fish processors in Nigeria States


4.2.10 Average quantities, costs, profitability indices and marketing efficiency of Spiced 71

fish products produced by respondent fish processors in Nigeria States along


4.2.11 Average quantities, costs, profitability indices and marketing efficiency 71

of Respondent Fish Processors in Nigeria States along Nigeria-Benin

Border According Scale of Operation

4.2.12 Average quantities, costs, profitability indices and marketing efficiency 71

of Respondent Fish Processors in Nigeria States along Nigeria-Benin


4.2.13 Average Quantities, Costs, Profitability Indices and Marketing Efficiency of 76

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Different Fish Products Marketed by Respondent Fish Traders in Nigeria States



fresh fish products marketed by respondent fish traders in Nigeria States



smoked fish products marketed by respondent fish traders in Nigeria States



dried fish products marketed by respondent fish traders in Nigeria States



frozen fish products marketed by respondent fish traders in Nigeria States


4.3 Inter-regional Trade Flow of Fish Products Along Nigeria-Benin Border 85

4.3.1 Trade flow of smoked fish products produced and marketed by respondent 85

fish processors in Nigeria-Benin border during the period of study.

4.3.2 Average quantities, costs and profitability indices of fish products supplied 90

and sold through intra- and inter-regional trade by respondent fish traders

across Nigeria-Benin Border

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4.4 Scale Economies of the Fish Products Marketed Along Nigeria-Benin Border 99

4.4.1 Scale Economies of the Fish Products Marketed by Respondent Fish 99

Processors along Nigeria-Benin Border

4.4.2 Scale Economies of the Fish Products Marketed by Respondent Fish Traders 99


4.5 Production Function and Technical Efficiency of the Respondent Value-Chain 113

Actors along Nigeria-Benin Border

4.5.1 Model Estimation and Resource Use Efficiency of Respondent Artisanal 113

Fishermen

4.5.2 Estimation of Production Function of the Respondent Fish Farmers 113

4.5.3 Technical Efficiency of the Respondent Fish Farmers 113

4.5.4 Estimation of Production Function of the Respondent Fish Processors 117

4.5.5 Technical Efficiency of the Respondent Fish Processors 117

4.6 Constraints Facing Respondent Value-Chain Actors along Nigeria-Benin Border 120

4.6.1 Constraints of Respondent Artisanal Fishermen along Nigeria-Benin Border 120

4.6.2 Constraints of Respondent Fish Farmers along Nigeria-Benin Border 120

4.6.3 Constraints of Respondent Fish Processors along Nigeria-Benin Border 120

4.6.4 Constraints of Respondent Fish Traders along Nigeria-Benin Border 120

CHAPTER FIVE 133

5.0 DISCUSSIONS 133

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5.1 Socio-economic Characteristics of Value-Chain Actors 133

5.1.1 Socio-economic Characteristics of Artisanal Fishermen 133

5.1.2 Socio-economic characteristics of aquaculture producers. 134

5.1.3 Socio-economic characteristics of fish processors 134

5.1.4 Socio-economic characteristics of fish traders 135

5.2 Profitability of Value-Chain Actors 135

5.2.1 Profitability of Artisanal Fish Producers 135

5.2.2 Profitability of Fish Farmers 137

5.2.3 Profitability of fish processors 138

5.2.4 Profitability of fish traders 139

5.3 Constraint of the Value-Chain Actors 140

CHAPTER SIX 142

6.0 CONCLUSION AND RECOMMENDATION 142

6.1 CONCLUSION 142

6.2 RECOMMENDATION 142

REFERENCES 144

APPENDICES 157

xv

List of Tables

Pages

Table 4.1: Socio-economic characteristics of artisanal fish farmers along 24


Table 4.2: Socio-economic characteristics of artisanal fishermen in Sampled States 25


Table 4.3: Socio-economic characteristics of Respondent Aquaculture Producer 30


Table 4.4: Socio-economic characteristics of Aquaculture Producers in Sampled 31

States along Benin-border

Table 4.5 Socio-economic Characteristics of Fish Processor along Nigeria-Benin 35

border

Table 4.6: Socio-economic characteristics of Fish processors in Sample State 37


Table 4.7: Socio-economic characteristics of fish traders along Nigeria-Benin 40

border

Table 4.8: Socio-economic Characteristics of Fish Traders in Sampled States along 41


Table 4.9: Socio-economic characteristics of consumers in Sampled States along 45


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Table 4.10: Average monthly quantities, cost variables and profitability indices 47

associated with fresh fish caught and marketed by artisanal fishermen

along Nigeria-Benin Border.

Table 4.11: Average monthly quantities, cost variables and profitability indices 49

associated with fresh fish caught and marketed by artisanal fishermen

in Nigerian States along Nigeria-Benin Border during the period of study

Table 4.12: Mean monthly quantities, cost variables and profitability indices of 50

Respondent artisanal fishermen in sampled Nigeria States along

Nigeria-Benin Border according to scale of operation

Table 4.13: Mean monthly quantities, cost variables and profitability indices of small 51

scale artisanal fishermen in sampled Nigeria States along Nigeria-Benin

border

Table 414: Mean monthly quantities, cost variables and profitability indices of 52

medium scale artisanal fishermen in sampled Nigeria States along


Table 4.15: Mean monthly quantities, cost variables and profitability indices 54

associated with fresh fish produced and marketed by respondent fish

farmers along Nigeria-Benin Border

Table 4.16: Mean Monthly Quantities, Cost Variables and Profitability Indices 55

Associated With Fresh Fish Produced and Marketed By Respondent

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Fish Farmers in sampled Nigeria States Along Nigeria-Benin Border

Table 4.17: Mean Monthly Quantities, Cost Variables and Profitability Indices of 57

Respondent Fish Farmers in sampled Nigeria States along Nigeria-Benin



Small Scale Fish Farmers in sampled Nigeria States along Nigeria-Benin

Border


Medium Scale Fish Farmers in sampled Nigeria States along Nigeria-

Benin Border


Large Scale Fish Farmers in sampled Nigeria States along Nigeria-

Benin Border

Table 4.21: Mean quantities, costs, profitability indices and marketing efficiency of 64

value-added fish products produced by respondent fish processors



dried fish products produced by respondent fish processors in Nigeria

States along Nigeria-Benin Border.

Table 4.23: Mean quantities, costs, profitability indices and marketing efficiency 68

xviii

of smoked fish products produced by respondent fish processors in

Nigeria States along Nigeria-Benin Border.


fried fish products produced by respondent fish processors in Nigeria



spiced fish products produced by respondent fish processors in Nigerian



of respondent dried fish processors according to their scale of production

in the study area.


of respondent smoked fish processors according to their scale of

production in the study area.

Table 4.28: Mean monthly quantities, costs, profitability indices and marketing 77

efficiency of different forms of fish products marketed by respondent

fish traders in Nigeria States along Nigeria-Benin Border.


fresh fish products marketed by respondent fish traders in Nigeria States


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of smoked fish products marketed by respondent fish traders in Nigeria



dried fish products marketed by respondent fish traders in Nigeria States



frozen fish products marketed by respondent fish traders in Nigeria


Table 4.33: Pooled Trade flow of smoked fish products produced and marketed 86

by respondent fish processors in Nigeria-Benin border during the

period of study.

Table 4.34: Trade flow of smoked fish products produced and marketed by 87

respondent fish processors in Ogun State along Nigeria-Benin border

during the period of study.

Table 4.35: Pooled Trade flow of dried fish products produced and marketed by 88

respondent fish processors in Nigeria-Benin border during the period of

study.

Table 4.36: Trade flow of dried and smoked fish products produced and marketed 89

by respondent fish processors in Lagos State along Nigeria-Benin

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border during the period of study.

Table 4.37: Mean quantities, costs and profitability indices of fresh fish supplied 92

and sold through intra- and inter-regional trade by respondent fish

traders across Nigeria-Benin Border

Table 4.38: Mean quantities, costs and profitability indices of smoked fish supplied 93


traders across Nigeria-Benin Border

Table 4.39: Mean quantities, costs and profitability indices of dried fish supplied and 94

sold through intra- and inter-regional trade by respondent fish traders

across Nigeria-Benin Border

Table 4.40: Mean quantities, costs and profitability indices of fresh fish supplied and 95

sold through intra- and inter-regional trade by respondent fish traders in

Ogun State across Nigeria-Benin Border

Table 4.41: Mean quantities, costs and profitability indices of fresh fish supplied and 96

sold through intra- and inter-regional trade by respondent fish traders in

Lagos State across Nigeria-Benin Border

Table 4.42: Mean quantities, costs and profitability indices of smoked fish 97

supplied and sold through intra- and inter-regional trade by respondent

fish traders in Lagos State across Nigeria-Benin Border

Table 4.43: Mean quantities, costs and profitability indices of dried fish supplied 98

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traders in Lagos State across Nigeria-Benin Border

Table 4.44: Linear regression estimates indicating the relationship between total 107

quantities sold (kg) and total marketing cost (₦) of the forms of fish

marketed by respondent fish traders in Kebbi State



marketed by respondent fish traders in Lagos State



marketed by respondent fish traders in Ogun State



marketed by respondent fish traders in Kwara State


quantities sold (kg) and total marketing cost (₦) of the forms

of fish marketed by respondent fish traders in Oyo State

Table 4.49: Linear regression estimates indicating the relationship between 112

total quantities sold (kg) and total marketing cost (₦) of the forms of

fish marketed by respondent fish traders in Niger State

xxii

Table 4.50: Model estimation and resource use efficiency of respondent artisanal 114

fishermen along Nigeria-Benin Border

Table 4.51: Estimation of production function of the respondent fish farmers 115


Table 4.52: Estimated production function of respondent fish processors along 118


Table 4.53: Ranking of constraints of respondent artisanal fishermen along 121


Table 4.54: Ranking of constraints of respondent fish farmers along 122


Table 4.55: Ranking of constraints of respondent fish processors along 123


Table 4.56: Ranking of constraints of respondent fish traders along Nigeria-Benin 124

Border

Table 4.57: Severity of Constraints of Respondent Artisanal Fishermen in Sampled 125

States along Nigeria-Benin Border

Table 4.58: Severity of Constraints of Respondent Fish Farmers in Sampled States 127


Table 4.59: Severity of Constraints of Respondent Fish Processors in Sampled 129

States along Nigeria-Benin Border

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Table 4.60: Severity of Constraints of Respondent Fish Traders in Sampled States 131


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List of Figures

Pages

Figure 3.1: Map showing sampled Local Government from each State 15

Figure 3.2: Map showing different geo-political zones sampled 16

Figure 4.1: Percentage of Fish products produced by the respondent fish processors 62


Figure 4.2: Percentage of value added fish products produced by respondent fish 63

processors in Nigeria States along Nigeria-Benin Border.

Figure 4.3: Percentage of respondent fish processors along Nigeria-Benin Border 73

according to scale of operation

Figure 4.4: Percentage of fish products traded by the respondent fish traders along 91

within and across Nigeria-Benin border

Figure 4.5: Relationship between total marketing cost and total monthly quantity 100

of dried fish marketed by fish processors along Nigeria-Benin Border


of smoked fish marketed by fish processors along Nigeria-Benin Border

Figure 4.7: Relationship between total marketing cost and total monthly quantity of 102

fried fish marketed by fish processors along Nigeria-Benin Border

Figure 4.8: Relationship between total marketing cost and total monthly quantity of 103

fresh fish marketed by fish traders along Nigeria-Benin border

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of smoked fish marketed by fish traders along Nigeria-Benin border


of dried fish marketed by fish traders along Nigeria-Benin border


of frozen fish marketed by fish traders along Nigeria-Benin border

Figure 4.12: Technical efficiency of respondent fish farmers in sampled States 116


Figure 4.13: Technical efficiency of respondent fish processors in the sampled States 119


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List of Plates

Pages

Plate 1: Typical setting of Catfish Market in Kwara State 187

Plate 2: Cross-section of fishermen involved in Group discussion in Ogun State 188

Plate 3: Tradition Fish Processing facility in Kwara State 189

Plate 4: Fish Farm Estate at Ikorodu, Lagos State 190

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LIST OF APPENDICES

Pages

Appendix 1: Sample questionnaire administered to the respondent artisanal fishermen 157

in the study area

Appendix 2: Sample questionnaire administered to the respondent aquaculture 163

producers in the study area

Appendix 3: Sample questionnaire administered to the respondent fish processors in 171

the study area

Appendix 4: Sample questionnaire administered to the respondent fish traders in the 178

study area

Appendix 5: Sample questionnaire administered to the respondent fish consumers in 184

the study area

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CHAPTER ONE

1.0 INTRODUCTION

1.1 Background Information

Fish is one of the most important sources of food and income to many people in developing

countries. The demand of fish globally and particularly in Nigeria has been on the increase with

supplies not meeting up the demand (FAO, 2012). With an annual fish demand in Nigeria of

about 2.66 million tonnes, and a paltry domestic production of about 780,000 tonnes, the demand

supply gap stands at staggering 1.8 million tonnes (Oyinbo and Rekwot, 2013). Despite the

popularity of farming in Nigeria, the fish farming industry can be described as being at the infant

stage when compared to the large market potential for its production and market (Nwiro, 2012).

Fish is also one of the important animal protein foods available in Nigeria. At present, fish

constitutes 40% of animal protein intake (Atanda, 2009). The demand for such protein is rising

exponentially with the rapidly accelerating increases in human population. Fish is available in

the market in different forms like fresh, frozen, canned, smoked or dried form (Mshelia et al.,

2007).

According to Spore (2012) value chain refers to actors connected along a chain to produce and

deliver goods and services through a sequenced and coordinated set of activities that adds value

at all stages (production, processing, and distribution).The value chain concept is used to

describe approaches aimed at improving market prospects for producers and scaling up profit

margins. Value chain focuses on the actors (private and public, including service providers) and

the sequence of value adding activities involved in bringing a product from production to the end

consumer.

Fish trade is an important tool in the distribution of fish and fish product, that is, movement of

fish from production point to point of demand where it can exchange cost for revenue. Fish trade

can take place within the country or across borders. Exports of fishery products are still subject

to many trade barriers. Tariffs play important roles in strategic business decisions on whether to

export unprocessed fish products, which normally have zero tariffs in the importing country, or

finished (consumer ready) processed/semi-processed products, which are burdened with

prohibitive tariffs. To gain control over revenue, exporting firms need to gain command of

2

significant parts of the value chain for their products, especially the latter stages where

significant proportions of the total value-adding occurs. However, moving downstream in the

value chain requires acquiring general and specific knowledge about how and where in the value

chain revenues accumulate and values are added through trade flow.

1.2 Justification

According to FAO (2013) documented report, Nigeria supplied about 0.4 percent of global

cultured products. This is far from same report which indicated that countries like china supplied

61.6%; India (7.3%), Indonesia (4.3%), Norway (1.8%) and Egypt (1.6%). In spite of the huge

import bills and the recent government effort towards boosting fish production through

aquaculture and sound fishery policies, the gap between projected fish demand and supply

continues to widen (Bassey et al., 2015). Fish supply and marketing suffer from various setbacks

ranging from shortage of supply, price fluctuations due to drying up of source, poor distribution

and length of chain, spoilage in transit etc. (Esiobu and Onubuogu, 2014). In addition, the value

chain actors involved in the marketing of the commodity appear to be on the increase as a result

of increase in the population and therefore, the demand tends to be high. Also despite the

nutritional and commercial values of fish and fish products, its production and marketing

remains low in Nigeria when compared to other nations of the world (FAO, 2012). Research

development and investment effort have often been focused primarily on production (Esiobu and

Onubuogu, 2014). Production increases without a well developed marketing system lead to all

possible gains from the production effort going into the drains of post-harvest losses. Often

times, marketers are compelled if not forced to sell their product at a very low price to avoid

huge wastage or total loss and this reduces their marketing margins and marketing efficiency.

Furthermore, due to the cumbersome nature of fish distribution channel, the local fish seller is

faced with the problem of profit maximization (Magudu and Edward, 2011). However,

irrespective of the great opportunities embedded in Nigerian fisheries, a lot of the fish resources

are being discarded on a daily basis due to an unorganized or uncoordinated distribution channel

(Aihonsu and Shittu, 2008).

Fish is a widely accepted in forms of fresh, smoked, dried and frozen as source of animal protein

with no religious bias or taboos in Nigeria (Adebo and Toluwase, 2014). Small-scale fisheries

and aquaculture provide employment for over 41 million people, majority of which live in the

3

developing countries (Adebo and Toluwase, 2014). Quite a sizeable proportion of the Nigerian

population depends on fishing as a source of income. Apart from being an income earner to

many Nigerians especially people in coastal, riverine and lake areas of the country, people earn

their living from fish processing and marketing while others engaged in fisheries research

(Adedokun et al., 2006). Analyzing fisheries value chain provides an insight into various

employment opportunities that remain untapped in the fisheries sector (Kaplinsky and Morris,

2000). Efficient farms either produce more output than others for a given set of inputs or produce

a given output with minimum level of inputs. Improvement in farm economic efficiency (EE) is

an important factor of productivity growth in areas where resources are scarce (Singh et al.,

2009). Hence, fish being a highly perishable substance needs to be transported to the consumer

or final user in time (Ali et al, 2008) to avoid post harvest spoilage through a coordinated

marketing channel (fish value chain).

Marketing and distribution channels are important characteristics in the process of getting

produce from source to consumers (Magudu and Edward, 2011). A good marketing organization

directs production along the most suitable needs of the consumers (Esiobu et al., 2014).

Availability of fish to the consumers at the right time, right form, right place and at the lowest

possible cost requires an effective marketing system (Shamsuddoha, 2007). Marketing of fish

passes through various market participants and exchange points before they reach the final

consumers (Ali et al., 2008). Nigeria has a great potential of fish resources whose distribution

and value chain needs to be strengthened and developed to bridge the gap between demand and

supply of fish in Nigeria (Amao et al, 2006).

The crucial role of efficiency in increasing agricultural output has been widely recognized by

researchers and policy makers. It has remained an area of important research both in developed

and developing countries (Adewuyi et al., 2013). This is particularly so in developing economy

where resources are meager and opportunity for developing and adapting better technology are

dwindling (Ali and Chaudhary, l990). The reason behind estimating efficiency is that if decision

making units are not making efficient use of existing technologies, then efforts designed to

improve efficiency would be more cost effective than introducing a new technology as a means

of increasing output (Shapiro, 1983). Efficiency measurement is important because it leads to a

sustainable resource savings, which have important implications for both policy formulations and

management (Bravo-Ureta and Evenson, 1994).

4

The importance of artisanal fish trade within the West African region cannot be underestimated,

there is little information on it and nor is it reflected in statistics, since most such trade is not

recorded. Little is known about the quantities traded, the number of people involved and the type

of trade they engage in, the trade circuits, the products traded, or the problems value-chain actors

face in this work (ICSF, 2002). Furthermore, there is limited empirical evidence and data on

socio-economic characteristics of value-chain actors, costs and return, profitability, technical

efficiency and little information is, however, available about the volumes traded and the routes

used in fish trade in Nigeria. Therefore, this study is determined to provide adequate information

in this regard to help policy makers in enhancing inter-regional fish trade in the study area.

1.3 Objectives of the Study

Main Objective: To analyse the value chain of fish trade along Nigeria Benin border

The specific objectives of the project are to:

• Assess the socio-economic characteristics of value-chain actors in fish market along

Nigeria Benin border.

• Estimate the quantity of fish trade, costs, returns and profitability across the different

actors along the value chain.

• Determining factors influencing the technical efficiency of the respondent value-chain

actors in the study area.

• Identify constraints of actors along the fish market value chain along Nigeria Benin

border.

5

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Theoretical framework

2.1.1 Market Participation and Structure-Conduct-Performance (S-C-P) Framework

According to Onoja et al., (2012), asset-based approaches and agricultural developmental theory

approaches are major theories on market participation developed from different perspectives.

The was Omiti et al (2009), summarized asset-based theory that as the market share of

agricultural output increases, input utilization decisions and output combinations are

progressively guided by profit maximization objectives. However, this process leads to the

systematic substitution of non-traded inputs with purchased inputs, the gradual decline of

integrated farming systems, and the emergence of specialized high-value farm enterprises (Onoja

et al., 2012).

Market structure conduct and performance (S-C-P) framework was derived from the neo-

classical analysis of markets (Edwards et al., 2005). The S-C-P paradigm is mainly focused on

analyzing competitive conditions of the prevailing market framework (Onyango, 2013).

According to Gumbau and Maudos (2000), two alternative hypotheses have been put forward to

explain the positive correlation usually found between performance and concentration. On the

one hand, the so called traditional hypothesis of collusion, or structure-conduct-performance

paradigm (Bain, 1951) affirms that concentration favours the adoption of collusive agreements,

thus leading to the obtaining of monopoly rents. The Structure-Conduct-Performance model (S-

C-P) defined as the relationship between market structure, firm conduct and firm performance

postulates that the existence of entry barriers is the major determinant of firm profits, thus the

greater cost of entry makes it easier for existing firms to maintain monopoly profits (Sinkey,

1986). It postulates that as market structure deviates from the paradigm of a perfect competition,

the degree of competitive conduct will decline and there will be a consequent decrease in output

(supply) and allocative efficiency, and an increase in prices. This implies that the performance of

markets can be assessed based on the level of competition and efficiency in those markets

(Williams et al., 2006).

2.1.2 Efficient Market Hypothesis (EMH)

Lidner, et al. (2010) explained Efficient Market Hypothesis as a cornerstone of modern financial

theory. An alternative to the EMH from a behavioral perspective, the adaptive market hypothesis

6

(AMH), proposed by Lo (2004), states that markets are adaptable and switch between efficiency

and inefficiency at different epochs. Some practical implications of the AMH are: there are

changes over time in the risk-reward relationships due to the preferences of the market

population; current preferences are influenced by the movement of past prices due to the forces

of natural selection, in contrast to the weak form of EMH where history of prices is not taken

into account; arbitrage opportunities, being constantly created and disappearing, exist at different

points in time (Lo, 2004). The efficiency structure hypothesis states that performance of the firm

is positively related to its efficiency. This is because market concentration emerges from

competition where firms with low cost structure increase profits by reducing prices and

expanding market share (Molyneux and Forbes, 1995).

2.2 Fish Production in Nigeria

Fish is the cheapest source of animal protein consumed by the average Nigerian and accounts for

about 50% of the total animal protein intake (FDF, 2009). According to FAO (2013) documented

report, Nigeria supplied about 0.4 percent of global cultured products. This is far from same

report which indicated that countries like china supplied 61.6%; India (7.3%), Indonesia (4.3%),

Norway (1.8%) and Egypt (1.6%). Rondon and Nzeka (2010) reported that Nigeria’s fish

demand amounted to nearly 2.0 million MT (valued at more than $1.8 billion) in 2009, leaving

approximately 600,000 metric tons of untapped market potential and about 800,000 metric tons

valued at approximately $900 million, were imported fresh and frozen fish (mostly frozen

mackerel, herring and croaker). Fish consumption accounts for about 35 percent of animal

protein consumption in Nigeria (USAID, 2014). Fish production in Nigeria comes from three

sources; artisanal (inland rivers, lakes, costal and brackish water), aquaculture (fish farm) and

industrial fishing (Otubusin, 2011). The inland water mass was estimated to be about 12.5

million hectares of inland waters capable of producing 512,000 metric tons of fish annually (

Shimang, 2005). Domestic fish production of about 500,000 metric tonnes is supplied by

artisanal fishers (85%), despite over fishing in many water bodies across the country (Adekoya

and Miller, 2004). Fish farming is the least exploited fishery sub-sector with the vast brackish

water fishing grounds almost unexploited (Ejiola & Yinka, 2012). Fish production in Nigeria has

not been consistent in all the sources (artisanal inland, aquaculture and industrial fishing) despite

7

the considerably high potentials; local fish production has failed to meet the country’s domestic

demand (FAO, 1995). The fish industry remains the most virgin investment in Nigeria compared

with the importation of frozen fish in the domestic market (Ndu, 2006).Total domestic fish

production in Nigeria ranges between 242,525 and 615,507 metric tonnes from 1981-2007 and

has not been consistent (FDF, 2008).

According to USAID (2010), the average Fish consumption in Nigeria is 9.8 kg/caput, while the

demand for fish is 1.4 m MT/annum. Recent data show that Nigeria produced just over 600,000

metric tonnes of fish in 2007 (Kingsway, 2013). Consumer demand, on the other hand, was

reported at 2.66 million metric tons and was met only in part by imports of about 740,000 metric

tons that same year (USAID, 2014). This report confirms the fact that domestic demand for fish

in Nigeria could not be met only by dependence on artisanal fisheries (Ojo and Fagbenro 2004).

According to Olusola and Ajayi (2013), fish farming has the potential to help expand the

resource base for food production and reduce the pressure on conventional sources of fish that

are harvested faster than they can be regenerated. Nigeria has high potentials for aquaculture

development and thus potentials can be realized substantially through extension services

(Adetunji, 2011).

2.3 Value Chain in Fisheries and Aquaculture

Value chain analysis is a versatile tool of economic analysis. As opined by Fries (2007) value

chain analysis refers to the assessment of the actors and factors that influence the performance of

an industry and relationships among participants to identify the main constraints to the increased

efficiency, productivity and competitiveness of an industry and how these constraints can be

overcome. Development interventions now utilise the value chain approach as an important entry

point for engaging target groups, individually or collectively, in various interventions in

marketing or poverty alleviation (GTZ, 2007). Value chains are networks of labour and

production processes where the result is a finished commodity (Hopkins and Wallerstein, 1986).

A value-chain can be seen as a step further in evolution, as it moves beyond just getting the

product to market and aims at providing a more mutually beneficially environment for all

stakeholders (FAO, 2013).

It has the enormous advantage to bring together stakeholders from different production stages

and sectors, to create a productive and innovative dialogue and to draw the attention to

8

‘Collective Competitiveness’ (CYE Consult, 2009). Value creation is used to characterize fish

and fishery products that have incremental value in the marketplace by differentiating them from

similar products based on product attributes such as: geographical location (Mediterranean tuna,

Norway salmon, Thailand Black Tiger shrimp, etc.); environmental stewardship (MSC label,

Eco-labeling, fair trade), organic products; and food safety (HACCP, Free from antibiotics and

heavy metals, etc) (De Silva, 2011). The production systems in fisheries involve value-addition

through production of five different forms; fresh, smoked, dried, salted and frozen in which fish

and fish products are mostly marketed (FAO, 1996). According to Jacinto and Pomeroy (2011),

small-scale fishers need to strengthen their organizations for resource management and market

development, they also need to identify and examine the types of markets with which they can

engage and benefit from.

It enhances the analysis of specific constraints encountered by fishers, processors, cooperatives,

etc. and solutions not merely focus on business development, but in recent years also address

networking, social, institutional and environment issues and/or micro finance (CYE Consult,

2009). Building mutually beneficial relations among the various actors in the value chain while

maintaining priority on improving the livelihoods of small-scale fishers can start from the

hypothesis that the small-scale fishers and their support organizations, that traders can be

potential partners rather than being the adversaries in a zero sum game (Jacinto and Pomeroy,

2011). Fish value chains in Nigeria are not yet developed to meet international market

requirements as limited value addition is done in the industry, with the result that market for fish

and fish products are limited to domestic markets (Investopedia, 2011).

2.3 Value-Chain Actors in Fish Marketing

According to FAO (2013), value-chain actors in domestic and international fish markets include

the artisanal fishermen, fish farmers, fish processors, marketers which could be wholesalers and

retails acting as exporters and importers of fish and fish products. The distinction between

wholesaler and retailer is well known: wholesaling is concerned with the activities of those

persons which sell to retailers and other merchants and commercial users, but do not sell in

significant amounts to final consumers (Kotler, 1997). Wholesale traders can be subdivided into

rural assembling traders, collecting wholesalers and distributing wholesalers (Maina, 2011). The

9

retailers may have a fixed base: a stall, a shop or a place on the ground, or they may be hawkers,

who carry their products around (Kotler, 1997).

2.3.1 Socio-Economic Characteristics of the Value-Chain Actors in Fish Marketing

Age has been identified has one of the factors that determines the efficiency farmers in

agricultural production (Olasunkanmi and Yusuf, 2014). According Olasunkanmi and Yusuf

(2014) and Odebiyi et al. (2013), majority of the value-chain actors (fisherman, fish processors

and fish-marketers) along coastal area of Ogun State in Nigeria were between 31 and 40years of

age, a highly productive and active age when actors could undertake strenuous task. Similar

result was also reported by Lawal et al. (2016) among artisanal fishermen in Lagos State.

Madugu and Edward (2011) reported that both males and females participate equally in

marketing of processed fish in Adadmawa State, Nigeria. A similar study in Benue State about

90% women participated in fish marketing (Lawal and Idega, 2004). This is further supported by

Williams and Awoyemi (1998) who observed that women in small-scale riverine fishing villages

also perform other types of income earning activities to supplement the household income, such

income sources were earned through sales of fisheries products and social services in fish

distribution and marketing. Higher percentage of male to female catfish farmers indicating that

fish farming activities are gender biased was reported by Olasunkanmi and Yusuf (2014). A

research conducted by Olagunju et al. (2010) revealed that the ratio of male to female catfish

farmer in Oyo state was 8:2.

Household size has been identified to have influence on the income of value-chain actors

(Oparinde and Ojo, 2014). Fabusoro et al., (2007) reported that the average household size in

Africa was about 9 persons. Baruwa et al. (2012) established the fact that 94.3 percent and 95.1

percent of the artisanal and aquaculture fish farmers are married conferred an advantage of

family labor because they have substantial household size, 6-10 dominant trends in household

size as observed in Lagos State, Nigeria. Madugu and Edward (2011) data illustrated that

marketers with household size that range between 1-10 persons have the highest percentage

(71.25%). Majority of artisanal fish marketers in Ondo State, Nigeria were reported to have

household size of 4-6persons (Oparinde and Ojo, 2014).

10

Education has been identified as an important factor which can influence fish production and

determine level of awareness on the rate of return on value addition in fish (Odebiyi et al., 2013).

In studies carried out by Olubanjo et al., (2007) and Alfred et al, (2008), the results confirmed

the general opinion that most fisherfolks were illiterate or semi-illiterates; most of whom have

dropped out of the formal school system. Dogondaji and Baba (2010) who observed that high

literacy level could have positive impact on the adoption of agricultural technologies. Lawal et

al. (2016) recorded that majority of artisanal fishermen in Lagos State, Nigeria had primary

education.

Ali et al., (2008) who observed that marketing experience is important in determining the profit

levels of marketers, the more the experience, the more marketers understand the marketing

system, condition, trends, prices etc. Olasunkanmi and Yusuf (2014) reported that majority of the

respondents small-scale fish farmers (73%) in Osun State, Nigeria have year of experience

ranged between 0 – 5 years. The distribution of years of fishing experience among fisher folks

from Lagos State, Nigeria is parabola with its peak at 11-15 years (Lawal et al. 2016).

2.3.2 Profitability of Value Addition in Nigerian States

Oparinde and Ojo (2014) observed that artisanal fish marketing is a profitable business. In the

study, Oparinde and Ojo (2014) recorded mean revenue, total variable cost, gross margin per kg

and net-return of ₦175,296,274.4 ($1,095,601.7), ₦98,424,781 ($615,154.9), ₦143.58($0.89)

and ₦137.10($0.85) respectively among fish sellers in Ondo State. Lawal et al. (2016) reported

that artisanal fishing operation in Lagos State, Nigeria is lucrative business. In a study, Dawang

et al. (2011) estimated the profitability of artisanal fishermen in Plateau State, Nigeria. This

study revealed that the average total value of fish caught was ₦57,239.10±24, 324.30. Baruwa et

al. (2012) also noted that gross margin of ₦104, 392.07 estimated for aquaculture fishery was

less than ₦271, 175 estimated for artisanal fishery in Lagos State, Nigeria. Meanwhile, the total

net returns for the aquaculture fishery enterprise and artisanal fishery enterprise in Lagos State

were respectively ₦102, 120.04 and ₦225, 761.59 per month according to (Baruwa et al. 2012).

Olasunkanmi and Yusuf (2014) recorded an average gross margin of ₦578414.75 and net

revenue of ₦382, 846.85 among catfish farmer in Osun State, Nigeria indicating profitability of

11

fish farming. Also confirmed by the study of Olasunkanmi and Yusuf (2014) is the fact that an

average fish farmer spends about 45% of its variable costs on feed while 39.96% was spent on

labour. Yusuf et al. (2002) and Mafimisebi (2003) in their independent research conducted on

fish farming in Nigeria revealed that catfish farming is profitable. Ismail et al. (2014) also

revealed that value-addition through production and marketing of fish processing is a lucrative

business in Nigeria. Adebo and Toluwase (2014) inferred that the sales of processed fish are

more profitable than that of fresh fish.

2.4 Fish Trade

Fish remains among the most traded food commodities worldwide trade (FAO, 2014). In 2012,

about 200 countries reported exports of fish and fishery products. Fish has become among the

most highly traded food commodities with nearly 40 percent of all production now exported.

This has particularly benefited developing countries who now account for more than 50 percent

of all fishery exports in value terms and more than 60 percent in quantity (live weight) (FAO,

2012). The fishery trade is especially important for developing nations, in some cases accounting

for more than half of the total value of traded commodities. In 2012, it represented about 10

percent of total agricultural exports and 1 percent of world merchandise trade in value terms. the

share of total fishery production exported in different product forms for human consumption or

non-edible purposes grew from 25 percent in 1976 to 37 percent (58 million tonnes, live-weight

equivalent) in 2012 (FAO, 2014). Fishery exports reached a peak of US$129.8 billion in 2011,

up 17 percent on 2010, but declined slightly to US$129.2 billion in 2012 following downward

pressure on international prices of selected fish and fishery products (FAO, 2014). Demand was

particularly uncertain in many developed countries, thus encouraging exporters to develop new

markets in emerging economies. Preliminary estimates for 2013 point to an increase in fishery

trade (FAO, 2014). Fish have aided in alleviating hunger in many part of the world. In Africa

artisanal fisheries still dominate with 6.9% of the world fishermen engaged in the activity (FAO,

2008). The price dip was the result of a reduced consumer demand in many key markets. These

tendencies were reflected in the FAO Fish Price Index, which shows international fish prices

sliding by almost 6 percent in 2012 compared to 2011 for total fisheries products, but by more

than 17 percent if taking into account only farmed fish (Sapkota et al., 2012).

12

2.5 Technical Efficiency of Value-Chain Actors

The measurement of farm efficiency is an important area of research both in the developed and

developing world (Amaza and Olayemi, 2002 and Kareem et al., 2006) affirmed that at least

73% of all rural Africans are small-scale farmers. Omobepade et al. (2014) opined that

measuring technical efficiency at the farm level, identifying important factors associated with the

efficient production systems would serve as a panacea to assessing potential for developing

sustainable aquaculture. Osawe et al (2008) observed that technical efficiency of the fish farmers

in Oyo State, Nigeria ranged between 0.51 and 0.998, with a mean of 0.906. Similar study by

Kareem (2006) in Ogun State, Nigeria discovered that a typical fish farmer had a technical

efficiency of 88%. Fapounda (2005) documented that fish farmers in Ondo State Nigeria had a

technical efficiency of 83%. Amos et al. (2004) estimated a technical efficiency of 7% for

crustacean farmers in coastal areas of Ondo State, Nigeria. The mean technical efficiency of the

non motorized small scale shrimp fishers in Delta State, Nigeria was 73% (Wategire and Ike,

2015).

2.6 Major constraint of Value-Addition

Most small-scale fish farmers reported lack of funds, stunted growth of stocked fish, inadequate

knowledge on fish farming and unavailability of concentrate feeds as the major constraints to

fish farming (Chenyambuga et al., 2012). Other minor constraints included irregular water

supply, predation, unavailability of fingerlings, floods, theft, and lack of transport. Other studies

(Abiona, 2011) have shown that high input price, price fluctuation, shortage of land, drought,

lack of credits, poor roads, high transportation cost, theft and poor extension services are the

main constraints to development of aquaculture in Africa. According to George et al (2010), the

major problem hindering the promotion and development of the aquaculture industry in Nigeria

has been the scarcity of fish fingerlings. Prominent problems facing fish farming are: Poor

management skills, inadequate supply of good quality seed, lack of capital, high cost of feed,

faulty data collection, lack of environmental impact consideration and marketing of products

(Adewumi & Olaleye, 2011).

Majority of the actors (100%, 68.6% and 38.4% of the fisherman, fish processors and fish-

marketers respectively) were not in any cooperative society; which may be the reason for not

13

benefiting from any source of loan according to the study of Odebiyi et al. (2013). Odebiyi

(2010) stated that cooperative groups ensure that their members derive benefits from the groups

such as they could not derive individually. One of the biggest challenges faced by the seafood

sector in the coastal fishing community is value addition (Odebiyi et al., 2013). A deprivation of

value addition facilities in the study area is a major setback to the fish value chain industry, most

of the respondents regarded poor transportation network and lack of storage facilities as major

constraints to the value chain development (Odebiyi et al., 2013).

Inadequate fund and poor transport network has been identified as constraints facing the fish

marketing activities which could be the reason for the inability of the artisanal fish marketers to

attain better profit margin (Oparinde and Ojo, 2014). Tiri et al. (2014) also observed that

majority (78%) of fish marketers in Katsina State, Nigeria ranked poor access to credit facilities,

poor market infrastructures and poor record keeping habit as the most important constraints

faced by small fish marketers. Major constraints of the fishermen as observed by Dambatta et al.

(2015) were found to be shrinking nature of the dams (63.33%) as they witness gross reduction

in catches over the years since they noticed that the catches are also reducing, 13.33% identified

high cost of fishing gears as their constraint, while 3.33% advanced loses due to deterioration as

their problem; while 20.00% of the respondents identified lack of capital to the fishermen as the

in major constraint.

14

CHAPTER THREE

3.0 METHODOLOGY

3.1 Study Area

The study focused on value addition of fish and fish products in States along Nigeria-Benin

borders. The states considered along this border in Nigeria, are Oyo, Kwara, Ogun, Lagos, Niger,

Kebbi states as indicated in Figures 3.1 and 3.2.

Republic of Benin, formerly known as People’s Republic of Benin, is a West Africa country

sharing border with Nigeria. It consists of a narrow wedge of territory extending northward for

about 420 miles (675 kilometres) from the Gulf of Guinea in the Atlantic Ocean, on which it has

a 75-mile seacoast, to the Niger River, which forms part of Benin’s northern border with Niger.

Benin is bordered to the northwest by Burkina Faso, to the east by Nigeria, and to the west by

Togo. The official capital is Porto-Novo, but Cotonou is Benin’s largest city, its chief port, and

its de facto administrative capital. Benin was a French colony from the late 19th century until

1960.

Kwara State is located between Latitude 8⁰and 10⁰North and Longitude3⁰ and 6⁰ East of

Greenwich Meridian. The State occupies36,825km of land and shares boundary with Niger

State in the North, Kogi and Ekiti States in the East, Osun and Oyo States in the South

and an International boundary with the Republic of Benin. There are sixteen Local

Government Areas in the State.

Niger State is located between latitudes 8°20'N and 11°30'N and longitude 3°30'E and 7°20'E.

The state is bordered to the north by Zarnfara State, to the northwest by Kebbi State, to the south

by Kogi State, to southwest by Kwara State; while Kaduna State and the Federal Capital

Territory border the state to the northeast and southeast, respectively. Furthermore, the State

shares a common international boundary with the Republic of Benin at Babanna in Borgu Local

Government Area of the state. Currently the state covers a total land area of 76,000 sq. km, or

about 9 percent of Nigeria's total land area. This makes the state the largest in the country. The

state has a total population of 3,728,098 according to National Population Commission.

15

Figure 3.1: Map showing sampled Local Government from each State

16

Figure 3.2: Map showing different geo-political zones sampled

17

Ogun State is located in the eastern part of Ogun State sharing boundaries with Ondo State in the

north, Lagos State in the south and Ijebu East Local Government in the west. About half to three

quarter of the length of the local government is surrounded by water extending from Lagos State

to Ondo State; this peculiar feature gave birth to the name waterside. The study area is closely

associated with other maritime states of South-western Nigeria. The area comprises over 50

towns and villages with Headquarter at Abigi at 6°29′N 4°24′E / 6.483°N 4.4°E

(www.wikipedia.com), while the main town in this area are Iwopin, Oni, Ibiade, Abigi, Efire,

Ilushin, Makun-Omi, Ode-Omi and Lomiro. The area consists largely of Yoruba speaking people

of which, the Ijebu comprise about 70%, with the Ikales, Ilajes, Itsekiris and Urhobos making up

the remaining 30%. It has an area of 1,000 km2 and a population of 72,935 at the 2006 census.

This area is also blessed with a large expanse of fertile land (soil) rich in organic matter, well

drained and deep which makes it support cultivation of various crops especially plantation crops

such as oil palm. The choice of the local government is due to its close proximity to the Atlantic

Ocean and its relative endowment with a complex network of streams, rivers, brackish water and

in particular the extension of the Lagos (Lekki) Lagoon to the area. It is the only area of the state

with a coastline.

Oyo State is one of the thirty-six states of the Federal Republic of Nigeria. It came

into existence with the break-up of the old Western State of Nigeria during the state

creation exercise of 1976. Ibadan, the capital which is reputed to be the largest indigenous

city in Africa, South of the Shara, had been the centre of administration of the old

Western Region since the days of the British colonial rule in Nigeria. The state has an

estimated population of over 5,591,589 million people (NPC, 2006). The state is located in

the rainforest vegetation belt of Nigeria within longitude 7⁰23'47"N and 3⁰55'0". It is bounded in

the south by Ogun State and in the north by Kwara State, in the west by the Republic of Benin

while in the east it is bounded by Osun State . Oyo state exhibits the typical tropical

climate of averagely high temperatures, high relative humidity and generally two

rainfall maxima regimes during the rainfall period of March to October. Oyo State now

consists of thirty three Local Governments and the capital of the state is Ibadan. The

main occupations of the people in the state are: Agriculture which is the mainstay of the

economy of the State. (Odebiyi et al, 2013).

18

Lagos State covers about 0.4percent of Nigeria land mass with a marine 3,571 square kilometers

out of which one quarter (800 square kilometer) i.e. 22% is covered by water lagoons creeks and

coastal river, estuaries. Lagos is sand-witched by latitude 6022"N and 6042"N and it straddles

longitudes 2⁰42E to 4⁰20E. It is bounded in the north by Ogun state and in the east by Ondo

state. It shares an international; boundary of about 45kilometers with the Republic of

Benin while the vast, deep blue Atlantic Ocean constricted the approximately

180kilometers along the continual shelf down to the southern limit. However, reclamation

is reducing on size of water surface in a significant way, nevertheless, it is not only man that is

reclaiming surface, and the sea is also claiming more space for itself in the process of coastal

erosion (Hundeyin,2011).

3.2 Sampling procedure

A multi-stage sampling technique was employed in this study. The six states were purposely

selected based on their link with Nigeria-Benin border, where local governments were selected

and respondents (main actors in the fish trade value chain) were randomly sampled from fish

markets and farms was selected randomly. Respondents in the States along Nigeria-Benin border

were sampled from the following forty-six (46) local government areas: Ngaski, Argungu, Yauri,

Shanga, Bunza, Jega, Augie in Kebbi state ,Borgu, Magama, Anfani in Niger state, Ogbomoso

South, Egbeda, Iseyin, Oyo West, Iddo, Ibadan North West, Akinyele, Afijio, Ibarapa, in Oyo

state, Ewekoro, Abeokuta, Ogun Waterside, Yewa North, Ado Odo, Ikenne, Sagamu, ijebuode,

Ifo, Odeda, in Ogun state Badagry, Ikorodu, Eti Osa, Ibeju, Oshodi, Isolo, Ikotun, Ejigbo, in

Lagos state, Asa, Offa, Ifelodun, Patigi, Baruten, Moro, Ilorin south, Ilorin West, Ilorin East in

Kwara state.

3.3 Data collection

The data for the study are mainly primary data. The data was collected by the use of

questionnaires (Appendix 1). In a situation where the respondents could not read or write,

personal interviews were scheduled and then responses would be accordingly entered into the

questionnaires. Group discussions with actors 22 fish farmers, 22 fishermen, 44 traders and 44

fish processors were also made.

19

3.3.1 Questionnaire Design

The instrument used to collect the primary data for this research from fish producers, processors

and marketers in the study area is a structured questionnaire categorized into five basic sections

as revealed in appendix VII. For the value chain analysis, the questionnaire was divided into

parts to cover the specific characteristics of the value chain actors.

Section A: comprised information on socio economic characteristics such as Age, Sex, Marital

Status, Household size, Highest education attained, major occupation of respondents, type of

operation for producers and other sources of income

Section B: comprised information on location like Country, Geopolitical zones, agricultural

extension project zone and village

Section C: comprised information on fishermen and fish farmer operations

Section D: comprised information on market structure- forms of fish sold, price mechanism and

its determinants, the quantity of fish bought and sold, transportation form and cost, capital cost,

operational cost, revenue and constraints faced by the actors in the marketing channel

Section E: comprised information on Informal Cross Border Trade.

3.3.2 Validation of Questionnaire

The questionnaire was reviewed by face validity. The statements in the instrument were

thoroughly examined by lecturers of the department of aquaculture and fisheries management

and department of agricultural extension and rural development.

3.4 Data Analysis

3.4.1 Socioeconomic Characteristics

Descriptive Statistics was used in the analysis of socioeconomic characteristics. It included the

use of mean, frequencies and percentages in tables and charts.

3.4.2 Profitability and Marketing Efficiency Indices

The Budgetary techniques were used to analyse the profitability, efficiency and structure of fish

marketing.

20

3.4.3 Market Margin Analysis:

Market margin if not perfect and static is also measure of market performance (Omonona and

Udoh, 1999). The absolute marketing margin is calculated as follows:

MM =TR-PC.................................................................................................. (i)

Where MM is Marketing Margin, TR is Total marketing Revenue and PC is Purchase cost

3.4.4 Marketing Efficiency

The efficiency of the market channels was measured using the expression (Omonona and Udoh,

1999) below:

ME = TR

TM ...................................................................................................................... (i)

Where: ME = Marketing Efficiency

TR = Total Revenue; TM = Total Marketing Cost

3.4.5 Gross margin analysis

The budgetary technique was used to determine the gross margin income of the fish marketers

using t-test for two sample assuming unequal variances.

Model used in estimating the gross margin is:

GMI= ΣTR-ΣTVC.................................………………………………………………. (ii)

TR=Py. Yi ......................………………………………………………………………. (iii)

Where,

GMI= Gross Margin Income (₦)

TR= Total Revenue (₦)

TVC= Total Variable Cost (₦)

TC=Total Cost (₦)

21

Py= Unit Price of Output Produced (₦)

Y= Quantity of Output (kg)

3.4.6 Net Return

Net returns are also given as;

NR =TR – TC

Where: TR=Total Revenue, TC=Total Cost.

TC=TVC+ TFC ………………………………………………………………. (iv)

TFC - Total Fixed Cost (₦)

TVC= Total Variable Cost (₦)

3.4.7 Market Structure

The structure of dried fish markets was described based on findings on concentration, product

differentiation and ease of/or barrier to entry or exist.

3.5.7.1 Ease of/or Barrier to Entry or Exit

In a perfect competitive market, there is ease of entry or exit by sellers. The market becomes

imperfect when sellers concentration is not even (imbalance). Scale economies is the measure

that was use to determine entry and exit conditions in the market. It is a measure that examines

the average cost function associated with the sellers’ marketing activities. This was computed

using least square regression of the form:

y = b0 + bixi + e (Pomeroy, 1989).

Where:

y = Total cost of marketing per class of seller per week (N).

xi = Number of dried fish (cartoon) sold per week.

bi = Coefficient of explanatory variables.

22

bo = Intercept

e = Error term.

If the coefficient of bi is negative, it means as quantity increases, cost decrease. This increase in

cost could form barrier to entry especially by sellers that are not financially sound.

3.4.8 Technical Efficiency and Production Function

A stochastic production frontier (SPF) function was specified which related the fish production as a

function of inputs used according to Singh et al. (2009). Assumption about the functional form is an

important consideration in the specification of an econometric model. Past studies on technical efficiency

utilizing stochastic frontier approach have used either Cobb-Douglas (CD) or the transcendental

logarithmic (translog) functional forms. When the second order and the interaction terms in translog are

restricted to zero, then the resulting functional form represents a Cobb-Douglas form. The translog and

Cobb-Douglas models are specified as per Equation (1) and (2), respectively:

InY1 = βo + ∑ �� +∑ ∑ ��(��

��

�� ) + �� − μ�……………. (1)

InY1 = βo + ∑ �� +�� − μ�……………………………………………… (2)

where, Y is the fish production, Xjs are the inputs, subscripts ‘i’, ‘ j’/’ k’ denote the ith farm and jth/kth inputs, Vi

is independent and identically distributed random errors having normal distribution N(0, σ2v and

independent of μi., μi is the technical inefficiency effects, and βs are the parameters to be estimated.

��is the random component of error term. The variance parameters σ2u and σ2v are expressed in terms of

parameterization: σ2μ + σ2

ϖ = σ2 and γ = σ2

μ/ σ2, γ can take values from 0 to 1, where 0 implies that the

random component of model is due to noise whereas γ = 1, implies that the random component of model

is entirely due to inefficiency. The independent variables (Xjs) included in the model were cost

of fish seed, lime, feeding, labour, other operational costs (including cost of water, medication

and others) and depreciated fixed cost for the artisanal fish farmers; cost of fresh fish processed,

processing, total variable cost, depreciated fixed cost and production cost for fish processors.

23

CHAPTER FOUR

4.0 RESULTS

4.1 Socio-economic Characteristics of Actors along the chain

4.1.1 Socio-economic characteristics of artisanal fishermen along Nigeria-Benin border

Presented in Table 4.1 are the results of socio-economic characteristics of the artisanal fish

farmers along Nigeria-Benin border. Majority (92.42%) of the artisanal fish farmers were male

while 7.58% were female. Along Nigeria-Benin border, 32.58% of the respondents were within

the age range 31-40 years of age, 27.27% were within the age range 41-50 years, 16.67% were

within 51-60 years, 15.15% were less or equal to 30 years while 8.33% were above 60 years.

97.73% of the respondents were married while 2.27% were single. 68.94% of the respondents

were Muslims while 31.06% were Christians. Majority (43.94%) of the respondent had primary

education while 4.54% had secondary education. The household distribution of the respondents

indicates the majority (46.21%) had an household size of 6-10, while respondents with

household size of above 15 had the least percentage of 7.50%. Highest percentage of the

respondents (37.88%) had 11-20 years of experience, 20.45% had less or equal to 10 years’

experience, 18.94% had 21-30 years, 17.42% had 31-40 years’ experience while 5.33% had

above 40 years’ experience.

4.1.2 Socio-economic characteristics of Artisanal Fishermen in Sampled States along


Table 4.2 indicate the socio-economic characteristics of the respondent artisanal fishermen in the

sampled States along Nigeria-Benin border.

Sex: The results presented in Table 4.2a revealed that majority of the artisanal respondents were

males. In Niger, Oyo, and Kebbi states, respondents were 100% male while in Kwara, Ogun

and Lagos state, artisanal respondents were 72.73% ,86.36%,95.45% male with 22.27% , 13.64%

and 4.55% female respectively.

24

Table 4.1: Socio-economic characteristics of artisanal fish farmers along Nigeria-Benin border

Variable Category Frequency Percentage (%)

Sex Male 122 92.42

Female 10 7.58

Age Less or equal 30 20 15.15

31-40 43 32.58

41-50 36 27.27

51-60 22 16.67

Above 60 11 8.33

Marital status Married 129 97.73

Single 3 2.27

Divorced 0 0.00

Widowed 0 0.00

Separated 0 0.00

Religion Christian 41 31.06

Islamic 91 68.94

Level of Education No formal education 31 23.48

Primary education 58 43.94

Tertiary education 10 7.57

Quranic education 27 20.45

Secondary education 6 4.54

Household size Less or equal 5 50 37.88

6-10 61 46.21

11-15 11 8.33

Above 15 10 7.50

Fish-catching experience Less or equal 10 27 20.45

11-20 50 37.88

21-30 25 18.94

31-40 23 17.42

Above 40 7 5.30

25

Table 4.2a: Socio-economic characteristics of artisanal fishermen in Sampled States along


Variable Category

Kwara Niger Oyo

Frequency Percentage

(%) Frequency Percentage


(%) Sex Male 16 72.73 22 100.00 22 100.00

Female 6 27.27 0 0.00 0 0.00 Age Less or equal 30 6 27.27 4 18.18 2 9.09

31 – 40 7 31.82 10 45.45 8 36.36 41 – 50 8 36.36 6 27.27 7 31.82 51 – 60 1 4.55 2 9.09 3 13.64 Above 60 0 0.00 0 0.00 2 9.09

Marital Status

Married 21 95.45 22 100 22 100.00 Single 1 4.55 0 0.00 0 0.00 Divorced 0 0.00 0 0.00 0 0.00 Widowed 0 0.00 0 0.00 0 0.00 Separated 0 0.00 0 0.00 0 0.00

Religion Christian 9 40.91 1 4.55 10 45.45 Islamic 13 59.09 21 95.45 12 54.55 Others 0 0.00 0 0.00 0 0.00

Level of Education

No Formal Education

6 27.27 0 0.00 6 27.27

Primary Education 11 50.00 9 40.91 9 40.91

Tertiary Education 1 4.55 0 0.00 5 22.73

Quranic Education 3 13.64 13 59.09 2 9.09

Secondary Education

1 4.55 0 0.00 0 0.00

Household size

Less or equal 5 7 31.82 14 63.64 10 45.45

6 – 10 15 68.18 6 27.27 10 45.45

11 – 15 0 0.00 1 4.55 1 4.55 Above 15 0 0.00 1 4.55 1 4.55

Fish catching experience

Less or equal 10 6 27.27 9 40.91 3 13.64

11 – 20 10 45.45 9 40.91 9 40.91

21 – 30 4 18.18 4 18.18 7 31.82

31 - 40 2 9.09 0 0.00 1 4.55

Above 40 0 0.00 0 0.00 2 9.09

26

Table 4.2b: Socio-economic characteristics of artisanal fishermen in Sampled States along Nigeria-Benin border

Variable Category

Ogun Lagos Kebbi

Frequency (%) Frequency (%) Frequency (%) Sex Male 19 86.36 21 95.45 22 100.00

Female 3 13.64 1 4.55 0 0.00 Age Less or equal 30 2 9.09 3 13.64 3 13.64

31 - 40 2 9.09 12 54.55 4 18.18 41 - 50 9 40.91 4 18.18 2 9.09 51 - 60 7 31.82 3 13.64 6 27.27 Above 60 2 9.09 0 0.00 7 31.82

Marital Status

Married 21 95.45 22 100.00 22 100.00 Single 1 4.55 0 0.00 0 0.00 Divorced 0 0.00 0 0.00 0 0.00 Widowed 0 0.00 0 0.00 0 0.00 Separated 0 0.00 0 0.00 0 0.00

Religion

Christian 14 63.64 7 31.82 0 0.00 Islamic 8 36.36 15 68.18 22 100.00 Others 0 0.00 0 0.00 0 0.00

Level of Education

No Formal Education

4 18.18 7 31.82 8 36.36

Primary Education

13 59.09 14 63.64 2 9.09

Tertiary Education

0 0.00 1 4.55 3 13.64

Quranic Education

0 0.00 0 0.00 9 40.91

Secondary Education

5 22.73 0 0.00 0 0.00

Household size

Less or equal 5 8 36.36 8 36.36 3 13.64

6 - 10 11 50.00 12 54.55 7 31.82

11 - 15 3 13.64 1 4.55 5 22.73 Above 15 0 0.00 1 4.55 7 31.82

Years of fishing experience

Less or equal 10 1 4.55 9 40.91 0 0.00

11 - 20 6 27.27 8 36.36 8 36.36

21 - 30 4 18.18 3 13 .64 3 13.64

31 - 40 9 40.91 1 4.55 9 40.91

Above 40 2 9.09 1 4.55 2 9.09

27

Age: About 36.36% of the respondents in Kwara state were within the age range of 41-50

followed by those within 31-40 years while respondents within less or equal to 30 and 51-60

years constituted 31.82%. Estimate of 45.45% of the respondent in Niger state were within the

range of 31-40 years followed by those within 41-50 with 27.27% while respondents within less

or equal to 30years and51-60 years constitute 18.18% and 9.09% respectively. In Oyo state,

36.36% are within the range of 31-40 followed by 31.82% within the range of 41-50 while

respondents within the range of lessor equal to 30 years, 51-60 and above 60 years constitute

13.64%, 9.09% and 9.09% respectively. In Ogun state, 40.91% are within the age range of 41-

50 years, followed by those within 51-60 years while respondents within 31-40 years, less or

equal to 30years and above 60 years were 9.09% each. In Lagos state, 54.55% of the respondents

were within the age range31-40 years followed by those within the age range 41-50 years with

18.18% while respondents within the range of less or equal to 30 and 51-60 years were 13.64%

each. In Kebbi state, 31.82% are within the range of above 60 years followed by those within the

age range of 51-60years with 27.27% while respondents within the age range 31-40,41-50 and

less or equal to 30 years constitute 18.18%, 13.64% and 9.09% respectively. Majority of the

respondents are within the age range 31-40 years and 41-50 years except for Kebbi state where

age range of 51-60 and above 60 dominates.

Marital status: Table 1 and 2 reveals that majority of the respondents in the study area are

married. In Kwara state, 95.5% of the respondents are married, while 4.55% are single. In Niger

state, 100% of the respondents are married. In Oyo state, 100% of the respondents are married.

In Ogun state, 95.45% of the respondents are married while 4.55% are single. In Lagos and

Kebbi states, 100% of the respondents are married.

Level of education: In Kwara state, 50% of the respondents had primary education , 27.27% had

no formal education, while respondents who had Quranic education, secondary, tertiary

education constitute 13.64%, 4.55% and 4.55% respectively. In Niger state, 59.09% of the

respondents had Quranic education while the remaining 49.01% had primary education. In Oyo

state, 40.91% had primary education , 27.27% had no formal education, 22.73% had tertiary

education followed by 9.09% who had Quranic education. In Ogun state, 59.09% had primary

education, 22.73% had secondary education while18.18 % had no formal education. In lagos

state, 63.64% had primary education, followed by 31.82% who had no formal education while

28

4.55% had tertiary education. In Kebbi state, 40.91% had Quranic education, 36.36% had no

formal, 13.64% had tertiary education, 9.09% had primary education.

Religion: In Kwara state, 59.09% of the respondents are Muslims while 40.91% are Christians.

In Niger state,95.45% of the respondents are Muslims while 4.55% are Christians. In Oyo state,

54.55% of the respondents are Muslims while 45.45% are Christians. In Ogun state, 63.64% are

Christians while 36.36% are Muslims. In Lagos state, 68.18% of the respondents are Muslims

while 31.82% are Christians. In Kebbi state, 100% of the respondents are Muslims. Muslim

constitutes the major part of the artisanal fishermen in each of the states except in Ogun state

where Christian fishermen constitute the majority.

House hold size: In Kwara state, 68.18% of the respondents have household size of 6-10, and

31.82% had a household size of less than 5. In Niger state, 63.64% had household size of less or

equal to 5, 27.27% had a household size of 6-10, 4.55% had household size of 11-15 and

household size of above 15 constitute 4.55%. In Oyo state, 45.45% of the respondents had

household size of less or equal to5, 45.45% had a household size of 6-10, while 9% had a

household size of above 11. In Ogun state, 50% had a household size of 6-10, followed by

household size of 36.36% with household size of less or equal to 5, 13.64% had household size

of 11-15. In Lagos state, 54.55% of the respondents had a household size of 6-10, 36.36 had an

household size of less or equal to 5, while household size above 11 constitute 9%.

Years of experience: In Kwara state, 45.45% of the respondents had fishing experience of 11-

20, 27.27% had less or equal to 10 years of fishing experience,18.18% and 9.09% had 21-30

years and 31-40 years of fishing experience respectively. In Niger state, 40.91% of the

respondents had fishing experience of less than or equal to 10 years, 40.91% had fishing

experience of 11-20years, 18.18% had fishing experience of 21-30 years. In Oyo state, 40.91%

of the respondents had fishing experience of 11-20 years, 31.82% had fishing experience of 21-

30 years, 13.64% had fishing experience of 21-30 years while 9.09% and 4.55% had fishing

experience of 31-40years and above 40years respectively. In Ogun state, 40.91% of the

respondents had fishing experience of 31-40 years, 27.27% had 11-20 years of experience,

18.18% had fishing experience of 21-30 years, while 9.09% and 4.55% had above 40 years of

fishing experience and less than or equal to 10 years of fishing experience. In Lagos state,

40.91% of the respondents had fishing experience of less than or equal to 10 years, 36.36% had

29

11-20 years of fishing experience, 13.64% had 21-30 years of fishing experience while 9.09%

had fishing experience of 31 years and above. In Kebbi state, 40.91% of the respondents had 31-

40 years of fishing experience, 36.36% had 11-20 years of fishing experience while 13.64% and

9.09% constitute those with 21-30 and above 40 years of fishing experience.

4.1.3 Socio-economic characteristics of Respondent Aquaculture Producer along Nigeria-

Benin Border

Table 4.3 consists of the results of socio-economic characteristics of respondent aquaculture

producer along Nigeria-Benin border. This result indicated that 87.88% (majority) of the

respondents were male while 12.12% were females. Estimate of 29.54% of the respondents were

within the age range of 41-50 years, 28.79% were within 51-60 years, 28.03% were within 31-40

years, 9.09% were above 60 years while 4.04% were less or equal to 30 years. About 87.12%

(majority) of the respondents were married, 11.36% were single, 0.07% were divorced and

0.07% were widowed. Majority (53.79%) of the respondents were Muslims while 46.21% were

Christians. 35.61% of the respondents had secondary education, 22.73% had no formal

education, 19.70% had Quranic education, 12.12% had primary education while 9.85% had

tertiary education. 65.91% had an household size of less or equal 5, 25.00% had an household

size of 6-10, 6.06% had house hold size of 11-15, while 3.03% had household size 0f above 15.

54.54% of the respondents had less or equal to 5 years’ experience, 22.73% had within 6-10

years’ experience, 12.12% had 11-15 years’ experience, 10.61% had above 15 years’ experience.

4.1.4 Socio-economic characteristics of Aquaculture Producers in Sampled States along


Tables 4.4a and 4.4b consist of the results of socio-economic characteristics of respondent

aquaculture producer in sampled States along Nigeria-Benin border.

Sex: In Kwara state, majority (77.27%) of the respondents are male while 22.73% are females. In

Niger state, 100% of the respondents are male. In Oyo state, majority (72.73%) are male while

27.27% are female. In Ogun state, majority (90.91%) of the respondents are male while 9.09%

30

Table 4.3: Socio-economic characteristics of Respondent Aquaculture Producer along Nigeria-Benin Border Variable Category Frequency Percentage (%)

Sex Male 116 87.88

Female 10 12.12


31-40 37 28.03

41-50 39 29.54

51-60 38 28.79

Above 60 12 9.09


Single 15 11.36

Divorced 1 0.07

Widowed 1 0.07

Separated 0 0.00


Islamic 71 53.79







6-10 33 25.00

11-15 8 6.06

Above 15 4 3.03

Fish-catching experience Less or equal 5 72 54.54

6-10 30 22.73

10-15 16 12.12

Above 15 14 10.61

31

Table 4.4a: Socio-economic characteristics of Aquaculture Producers in Sampled States along Benin-border Kwara State Niger State Oyo State

Variable Frequency Percentage



(%) Male 17 68.18 22 100.00 16 72.73 Female 5 18.18 0 0.00 6 27.27 Less or equal 30 0 0.00 1 4.55 4 18.18

31 – 40 7 31.82 11 50.00 11 50.00 41 – 50 7 31.82 6 27.27 2 9.09 51 – 60 7 31.82 5 22.73 3 13.64 Above 60 1 4.55 0 0.00 2 9.09 Married 18 81.81 20 90.91 19 86.36 Single 3 13.64 2 9.09 3 13.64 Divorced 0 0.00 0 0.00 0 0.00 Widowed 1 4.55 0 0.00 0 0.00 Seperated 0 0.00 0 0.00 0 0.00 Less equal 5 16 72.72 14 63.64 15 68.18

6 – 10 5 22.73 6 27.27 5 22.73 11 – 15 1 4.55 2 9.09 2 9.09 Above 15 0 0.00 0 0.00 0 0.00 Less equal 5 19 86.36 19 86.36 9 40.91

6 – 10 0 0.00 3 13.64 0 0.00 11 – 15 0 0.00 0 0.00 0 0.00 Above 15 0 0.00 0 0.00 0 0.00 Christian 9 40.91 5 22.73 16 72.73 Islamic 13 59.09 17 77.27 6 27.27 No formal education

10 27.27 2 9.09 7 31.81

Primary education

0 0.00 4 18.18 1 4.55

Quranic Education

1 4.55 15 68.18 0 0.00

Secondary education

11 50.00 0 0.00 13 59.09

Tertiary 0 0.00 1 4.55 1 4.55 Less equal 3 21 95.45 22 100 22 100

3 – 6 1 4.55 0 0.00 0 0.00 6 – 9 0 0.00 0 0.00 0 0.00 Above 9 0 0.00 0 0.00 0 0.00 Less equal 5 11 50.00 19 86.36 4 18.18 6 – 10 3 13.64 3 13.64 7 31.82 11 – 15 1 4.55 0 0.00 3 13.64 Above 15 2 9.09 0 0.00 3 13.64

32

Table 4.4b: Socio-economic characteristics of Aquaculture Producers in Sampled States along Benin-border

Variable Category

Ogun State Lagos State Kebbi State

Frequency Percentage (%) Frequency

Percentage (%) Frequency

Percentage (%)

Sex Male 20 90.91 21 95.45 20 90.91 Female 2 9.09 1 4.55 2 9.09

Age Less or equal 30

1 4.55 0 0.00 0 0.00

31 – 40 4 18.18 1 4.55 4 18.18 41 – 50 6 27.27 13 59.09 5 22.73 51 – 60 8 36.36 5 22.73 10 45.45 Above 60 3 13.64 3 13.64 3 13.64

Marital Status Married 19 86.36 20 90.91 19 86.36 Single 2 9.09 2 9.09 3 13.64 Divorced 1 4.55 0 0.00 0 0.00 Widowed 0 0.00 0 0.00 0 0.00 Separated 0 0.00 0 0.00 0 0.00

Household size Less equal 5 17 77.27 21 95.45 4 18.18

6 – 10 5 22.73 1 4.55 11 50.00 11 – 15 0 0.00 0 0.00 3 13.64 Above 15 0 0.00 0 0.00 4 18.18

Number of Dependants Less equal 5 22 100.00 21 95.45 15 68.18

6 – 10 0 0.00 1 4.55 2 9.09 11 - 15 0 0.00 0 0.00 4 18.18 Above 15 0 0.00 0 0.00 1 4.55

Religion Christian 14 63.64 15 68.18 2 9.09

Islamic 8 36.36 7 31.82 20 90.91 Level of Education No formal 0 0.00 5 22.73 6 27.27

Primary 8 36.36 3 13.64 0 0.00 Quaranic 2 9.09 0 0.00 8 36.36 Secondary 12 54.55 3 13.64 8 36.36 Tertiary 0 0.00 11 50.00 0 0.00

Years of experience in aquaculture

Less equal 5 7 31.82 9 40.91 12 54.54

6 – 10 10 45.45 4 18.18 3 13.64

11 – 15 3 13.64 6 27.27 3 13.64

Above 15 2 9.09 3 13.64 4 18.18

33

are female. In Lagos state, majority (95.45%) of the respondents were male while 4.55% are

female. In Kebbi state, majority (90.91%) of the respondents were male while 9.09% are

females.

Age : In kwara state, respondents within the age range 31-40years,41-50 years, 51-60years

constitute 31.82% each while 4.55% were within age range of above 60 years. In Niger state,

50% of the respondents are within age range 31-40 years followed by age range 41-50 with

27.27% while those with age range 51-60 years constitute 22.73%. In Oyo state, 50% of the

respondents are within the age range 31-40 years followed by age range less or equal to 30years

and above 60years with 18.18% each while age range 41-50years and 51-60years constitute

22.73%. In Ogun state,36.36% of the respondents were within the age range 51-60 years,27.27%

are within the age range 41-50years, 18.18% are within age range 31-40years while those within

age range of less than or equal to 30 and above 30 constitute 13.64%. In Lagos state, 59.09% of

the respondents were within age range 41-50 years, 27.27% were within 51-60 years,13.64% are

above 60 and only 4.55% were within 31-40 years. In Kebbi state, 45.45% of the respondents are

within age range of 51-60 years,22.73% were within 41-50 years,18.18% were within 31-40

years while 13.64% are above 60years.

Marital status: In Kwara state, 81.82% of the respondents were married, 13.64% were single

while 4.55% are widowed. In Niger state, 90.91% of the respondents are married,while 9.09%

were single. In Oyo state, 86.36% of the respondents are married, while 13.64% were single. In

Ogun state, 86.36% of the respondents were married, 9.09% were single, 4.55% were divorced.

In Lagos state, 90.91% of the respondents were married while 9.09% were single. In Kebbi state,

86.36% of the respondents were married while 13.64% were single.

Religion: In Kwara state, 59.09% of the respondents are Muslims while 49.91% are Christians.

In Niger state, 77.27% of the respondents are Muslims while 22.73% are Christians. In Oyo

state, 72.73% of the respondents are Christians while 27.27% are Muslims. In Ogun state,

63.64% of the respondents are Christians while 36.36% are Muslims. In Lagos state,68.18% of

the respondents are Christians while 31.82% are Muslims. In Kebbi state, 90.91% of the

respondents are Muslims while 9.09% are Christians. It is noted that all that there are higher

percentages of Muslims participation in states from the northwest, north central while there are

34

more Christian participation in the south-western states, which might be due to high population

of Muslims in the north and Christians in the south-west.

Household size: In Kwara state, 72.73% of the respondents had a household size of less than or

equal to 5, 22.73% had an household size of 6-10 while 4.55 had an household size of above

60years. In Niger state, 63.64% of the respondents had a household size of less or equal to 5,

27.27% had a household size of 6-10, while 9.09% had a household size of 11-15. In Oyo state,

68.18% of the respondents had a household size of less or equal to 5, 22.73% had a household

size of 6-10 while 9.09% had a household size of 11-15. In Ogun state, 77.27% of the

respondents had a household size of less or equal to 5, while 22.73% had a household size of 6-

10. In Lagos state, 95.45% of the respondents had a household size of less or equal to 5, while

4.55% had a household size of 6-10. In Kebbi state, 50% of the respondent had a household size

of 6-10, household size of less or equal to 5 and above 15 constitute 18%each and 13.64% had an

household size of 11-15.

Years of experience in aquaculture: In Kwara state, 50% of the respondents had less than or

equal to 5 years of experience, 13.64% had 6-10 years of experience, 9.09% had above 15years

and 4.55% had within 11-15 years of experience. In Niger state, 86.36% of the respondents had

less than or equal to 5years of experience while 13.64% had 6-10 years of experience. In Oyo

state, 31.82% of the respondents had 6-10years of experience, 18.18% had less or equal to 5years

experience while 11-15 years and above 15 years constitute 13.64% each. In Ogun state, 45.45%

of the respondents had within 6-10 years’ experience, 31.82% had less or equal to 5 years,

13.64% had within 11-15 years and 9.09% had above 15 years of experience. In Lagos state,

40.91% of the respondents had less or equal to 5 years’ experience in aquaculture, 27.27% had

within 11-15 years, 18.18% had within 6-10 years while9.09% had above 15years of experience.

In Kebbi state, 54.54% of the respondents had less or equal to 5 years’ experience, 18.18% had

above 15 years while 6-10 years and 11-15 years’ experience constitute13.64% each.

4.1.5 Socio-economic Characteristics of Fish Processor along Nigeria Benin-border

The results of socio-economic characteristics of fish processor along Nigeria Benin-border

presented in Table 4.5 indicated that majority (58.71%) of the fish processors were male while

41.28% were female. 29.54% were within the age range of 31-40 years, 28.79% were within 41-

50 years,21.59% were within 51-60 years, 16.67% were less or equal 30 years while 7.20% were

35

Table 4.5 Socio-economic Characteristics of Fish Processor along Nigeria Benin-border Variable Category Frequency Percentage (%)

Sex Male 155 58.71

Female 109 41.28


31-40 78 29.54

41-50 76 28.79

51-60 57 21.59

Above 60 19 7.20


Single 22 16.67

Divorced 4 1.52

Widowed 8 3.03

Separated 1 0.37


Islamic 154 58.33







6-10 91 34.47

11-15 30 22.73

Above 15 14 10.61

Fish Processing experience

Less or equal 5 64 20.45

6-10 72 37.88

11-15 33 18.94

Above 15 95 17.42

36

above 60 years of age. 86.64% of the fish traders were married, 16.67% were single, 3.03% were

widowed, 1.52% were divorced, 0.37% were separated. 58.33% were Muslims while 41.67%

were Christians. 29.54% of the respondents had tertiary education, 28.78% had no formal

education, 23.11% had Quranic education, 10.23% had primary education, while 8.33% had

secondary education.

4.1.6 Socio-economic Characteristics of Processors in Sampled States along Nigeria-Benin

border

Tables 4.6 consist of the results of socio-economic characteristics of respondent fish processors

in sampled States along Nigeria-Benin border.

Sex: In Kwara state, 54.55% of the respondents were male while 45.45% were female. In Niger

state, 95.45% of the respondents were male, 4.55% were female. In Oyo state, 75% of the

respondents were female, while 4.55% were male. In Ogun state, 77.27% of the respondents are

female while 22.73% are male. In Lagos state, 56.82% of the respondents are male while 43.18%

were female. In Kebbi state, 97.73% of the respondents were male while 2.27% were female.

Age: In kwara state, 34.09% of the respondents were within age range 31-40 years, 29.55% were

within 41-50 years, 25% were less or equal to 30 years, 11.36% were above 60 years of age. In

Niger state, 38.64% of the respondents were within age range of 51-60years, 22.73% were less

or equal to 30years, while age ranges 31-40 and 41-50 constitute18.18% each while 2.27% were

above 60years. In Oyo state, 40.91% of the respondents were within age range of 31-40 years,

29.55% were within41-50 years, age ranges of less or equal 30 years and 51-60 years constitute

13.64% each while 6.82% were above 60years. In Ogun state, 38.64% were within age range41-

50 years, 27.27% were within age range 31-40 years, 22.73% were within 51-60 years while

11.36% were above 60 years. In Lagos state, 40.91% of the respondents were within age

range41-50 years, 27.27% were within 31-40 years, 20.45% were within 51-60 years while age

ranges of less or equal to 30 years and above 60 years constitute 11.36%. In Kebbi state, 29.55%

of the respondents were within age range 31-40 years, 27.27% were within 51-60 years, 20.45%

were above 50 years, 15.91% were within 41-50 years while 6.82% were less or equal to 30

years. Higher percentage of the respondent was within 31-50 years of age.

Religion: In Kwara state, 50.00% of the respondents were Muslims and 50.00% were Christians.

In Niger state, 95.45% were Muslims while 4.55% were Christians. In Oyo state, 61.36% of the

37

Table 4.6: Socio-economic characteristics of Fish processors in Sample State along Nigeria-Benin Border

Kwara Niger Oyo Ogun Lagos Kebbi Variable Category Frequency Frequency Frequency Frequency Frequency Frequency Sex Male 24(54.55) 42(95.45) 11(25.00) 10(22.73) 25(56.82) 43(97.73

Female 20(45.45) 2(4.55) 33(75) 34(77.27) 19(43.18) 1(2.27) Age Less or equal

30 11(25) 0(0.00) 6(13.64) 0(0.00) 4(9.09) 3(6.82)

31 - 40 15(34.09) 8(18.18) 18(40.91) 12(27.27) 12(27.27) 13(29.54) 41 - 50 13(29.55) 8(18.18) 13(29.55) 17(38.64) 18(40.91) 7(15.91) 51 - 60 5(11.36) 17(38.64) 4(9.09) 10(22.73) 9(20.45) 12(27.27) Above 60 0(0.00) 1(2.27) 3(6.82 5(11.36)) 1(2.27) 9(20.45)

Religion Christian 22(50.00) 2(4.55) 27(61.36) 27(61.36) 29(65.91) 5(11.36) Islamic 22(50.00) 42(95.45) 17(38.64) 17(38.64) 15(34.09) 39(88.64)

Marital Status Married 29(65.91) 44(100) 39(88.64) 38(86.36) 36(81.82) 43(97.73) Single 12(27.27) 0(0.00) 4(9.09) 2(4.55) 2(4.55) 1(2.27) Divorced 0(0.00) 0(0.00) 0(0.00) 3(6.82 1(2.27) 0(0.00) Widowed 1(2.27) 0(0.00) 1(2.27) 1(2.27) 5(11.36) 0(0.00) Separated 1(2.27) 0(0.00) 0(0.00) 0(0.00) 0(0.00) 0(0.00)

Household Size Less or equal 5

19(43.18) 4(9.09) 34(77.27) 37(84.09) 26(59.09) 9(20.45)

6 - 10 12(27.27) 28(63.64) 10(22.73) 7(15.91) 15(34.09) 19(43.18) 11 - 15 13(29.54) 7(15.91) 0(0.00) 0(0.00) 3(6.82) 7(15.91) Above 15 0(0.00) 5(11.36) 0(0.00) 0(0.00) 0(0.00) 9(20.45)

.Level of Education

No Formal Education

8(18.18) 3(6.82) 26(59.09) 8(18.18) 23(52.27) 8(18.18)

Primary Education

0(0.00) 1(2.27) 2(4.55) 18(40.91) 5(11.36) 1(2.27

Tertiary Education

30(68.18) 4(9.09) 10(22.73) 10(22.73) 16(36.36) 8(18.18)

Secondary Education

6(13.64) 6(13.64) 6(13.64) 3(6.82) 0(0.00) 1(2.27)

Quranic Education

0(0.00) 30(68.18) 0(0.00) 5(11.36) 0(0.00) 26(59.09)

Years of experience

Less or equal to 5

31(70.45) 3(6.82) 12(27.27) 14(31.82) 4(9.09) 0(0.00)

6-10 10(22.73) 13(29.54) 20(45.45) 10(22.73) 8(18.18) 11(25.00) 11-15 3(6.82) 2(4.55) 6(13.64) 6(13.64) 11(25.00) 5(11.36) Above 15 0(0.00) 26(59.09) 6(13.64) 14(31.82) 21(47.73) 28(63.64)

. Note: Percentages are in parenthesis

38

respondents were Christians, 31.84% were Muslims. In Ogun state, 61.36% of the respondents were Christians while 31.84% were Muslims. In Lagos state, 65.91% of the respondents were Christians while 34.09% were Muslims. In Kebbi state, 88.64% were Muslims while 11.36% were Christians.

Marital status: In Kwara state, 68.18% of the respondents were married, 29.54% were single

while the widowed and divorced constitute 4.54%. In Niger state, 100% were married. In Oyo

state, majority (88.64%) of the respondents were married while 9.09% were single.

Educational status: In Kwara state, 68.18% of the respondents had tertiary education, 13.64%

had secondary education while 18.18% had no formal education. In Niger state, 68.18% had

Quranic education, 13.64% had secondary education, 9.09% had tertiary education 6.82% had no

formal education while 2.27% had primary education. In Oyo state, 59.09% of the respondents

had no formal education, 22.73% had tertiary education, 13.64% had secondary education and

4.55% had primary education. In Ogun state, 40.91% had primary education, 22.73% had

tertiary education, while those who had no formal and secondary education constitute 18.18%

each. In Lagos state, 52.27% of the respondents had no formal education,36.36% had tertiary

education, while 11.36% had primary education. In Kebbi state, 59.09% had Quranic education,

those with no formal education and tertiary education constitute 18.18% each while those with

primary and secondary education constitute 4.54%. Higher percentage of the processors had one

form of education.

Household size: In Kwara state, 43.18% of the respondents had a household size of less or equal

to 5, followed by household size of 11-15 with 29.54% while 27.27% had a household size of 6-

10. In Niger state, 63.64% had a household size of 6-10, followed by household size11-15 with

15.91% while household size of less or equal to 5 and above 15 constitute 9.09% and 11.36%

respectively.

Years of Experience: In Kwara state, 70.45% of the respondents had less or equal to 5years

experience, 22.73% had 6-10 years’ experience, 6.82% had 11-15 years’ experience. In Niger

state, 59.09% of the respondents had above 15 years’ experience, 29.54% had 6-10 years, 6.82%

had less or equal to 5 years, while 4.55% had 11-15 years. In Oyo state, 45.45% of the

respondents had 6-10years of experience, 27.27% had less or equal to 5years, while those with

11-15 years and above 15 years constitute 13.64% each. In Ogun state, respondents with less or

39

equal to 5 years and above 15 constitute 31.82% each, 22.73% had 6-10 years while 13.64% had

11-15 years. In Lagos state, 47.73% of the respondents had above 15 years’ experience, 25% had

11-15 years, 18.18% had 6-10 years, while 9.09% had less or equal to 5 years. In Kebbi state,

63.64% of the respondents had above 15 years’ experience, 25% had 6-10 years while 11.36%

had 11-15 year

4.1.7 Socio-economic characteristics of fish traders along Nigeria-Benin border

Presented in Table 4.7 are socio-economic characteristics of fish traders along Nigeria-Benin

border. Majority(59.09%) of the fish traders were male while 40.91% were female. 35.61% of

the fish traders were within age range of 31-40 years, 22.35% were within41-50 years, 19.70%

were less or equal 30, 14.17% were within 41-50 while 7.20% were above 60 years. 76.89% of

the fish traders were married, 16.29% were single,4.54% were divorced, 1.52% were widowed

while 0.78% were separated. 57.20% were Muslims, while 42.80% were Christians. 34.85% had

no formal education, 23.11% had tertiary education, 19.32% had Quranic education while

12.12% had secondary education. 46.59% had an household size of less or equal 5, 32.58% had

within 6-10,13.26% had within 11-15 while 7.58% had above 15. 41.67% had less or equal 10

years’ experience in fish trading, 29.92% had within 11-20 years,16.29% had within 21-30 years,

8.33% had within 31-40 years while 3.79% had above 40 years.

4.1.8 Socio-Economic Characteristics of Fish Traders in Sampled States along Nigeria-

Benin Border

Presented in Table 4.8 are socio-economic characteristics of fish traders along Nigeria-Benin

border

Sex: In kwara state, 72.73% are male while 27.27% are female. In Niger state, 84.09% are male

while 15.91% are female. In Lagos state, 100% of the respondents are female. In Ogun state,

59.09% of the respondents are male while 40.91% are female. In Lagos state, 100% of the

respondents are female. In Kebbi state, all (100%) of the respondents are female except for Ogun

state where the male made up a larger percentage.

Age: In Kwara state, 54.55% of the respondents are within the age range of less or equal to

30years,36.36% were within age range 31-40 while age range 41-60 years made up 9.09%. In

Niger state, 38.64% of the respondents are within age range of 51-60years, 25% represents those

above 60 years while the those within age ranges less or equal to 30years and 31-40 years

40

Table 4.7: Socio-economic characteristics of fish traders along Nigeria-Benin border

Variable Category Frequency Percentage (%)

Sex Male 156 59.09

Female 108 40.91


31-40 94 35.61

41-50 59 22.35

51-60 39 14.17

Above 60 19 7.20


Single 43 16.29

Divorced 12 4.54

Widowed 4 1.52

Separated 2 0.78


Islamic 151 57.20







6-10 86 32.58

11-15 35 13.26

Above 15 20 7.58

Years of experience Less or equal 10 110 41.67

11-20 79 29.92

21-30 43 16.29

31-40 22 8.33

Above 40 10 3.79

41

Table 4.8: Socio-economic Characteristics of Fish Traders in Sampled States along Nigeria-

Benin Border

Variable Category

Kwara Niger Oyo Ogun Lagos Kebbi Frequency

(%) Frequency

(%) Frequency

(%) Frequency

(%) Frequency

(%) Frequency

(%) Sex Male 32(72.73) 37(84.09) 17(38.64) 26(59.09) 0(0.00) 44(100)

Female 12(27.27) 7(15.91) 27(61.36) 18(40.91) 44(100.00) 0(0.00)


24(54.55) 3(6.82) 12(27.27) 1(2.27) 5(11.36) 7(15.91)

31 - 40 16(36.36) 4(9.09) 24(54.55) 9(20.45) 26(59.09) 15(34.09)

41 - 50 2(4.55) 9(20.45) 5(11.36) 18(40.91) 10(22.73) 15(34.09)

51 - 60 2(4.55) 17(38.64) 3(6.82) 10(22.73) 3(6.82) 6(13.64)

Above 60 0(0.00) 11(25.00) 0(0.00) 6(13.64) 0(0.00) 2(4.55)

Marital Status Married 20(45.45) 40(90.91) 33(75.00) 41(93.18) 30(68.18) 39(88.63)

Single 24(54.55) 4(9.09) 8(18.18) 1(2.27) 1(2.27) 5(11.36)

Divorced 0(0.00) 0(0.00) 1(2.27) 1(2.27) 10(22.73) 0(0.00)

Widowed 0(0.00) 0(0.00) 0(0.00) 1(2.27) 3(6.82) 0(0.00)

Separated 0(0.00) 0(0.00) 2(4.55) 0(0.00) 0(0.00) 0(0.00)

Religion Christian 10(22.73) 24(54.55) 20(45.45) 20(45.45) 32(72.73) 7(15.91)

Islamic 34(77.27) 20(45.45) 24(54.55) 24(54.55) 12(27.27) 37(84.09)

others 0 0(0.00) 0(0.00) 0 0 0

Level of Education No formal education

8(18.18) 32(72.73) 15(34.09) 9(20.45) 15(34.09) 13(29.55)

Primary education

1(2.27) 0(0.00) 7(15.91) 9(20.45) 10(22.73) 1(2.27)

Tertiary education

30(68.18) 0(0.00) 13(29.54) 10(22.73) 5(11.36) 3(6.82)

Quaranic 0(0.00) 12(27.27) 1(2.27) 10(22.73) 8(18.18) 20(45.45)

Secondary education

5(11.36) 0(0.00) 8(18.18) 6(13.64) 6(13.64) 7(15.91)

44.00 0 0 0 0 0 3

Household size Less or above 5

30(68.18) 9(20.45) 23(52.27) 28(63.64) 20(45.45) 13(29.55)

6 - 10 14(31.82) 12(27.27) 13(29.54) 11(25.00) 24(54.55) 12(27.27)

11 - 15 o(0.00 9(20.45) 8(18.18) 3(6.82) 0(0.00) 15(34.09)

Above 15 0(0.00) 14(31.82) 0(0.00) 2(4.55) 0(0.00) 4(9.09)

Years of experience marketing

Less or equal 10

35(79.54) 6(13.64) 34(77.27) 13(29.54) 16(36.36) 6(13.64)

11 - 20 6(13.64) 19(43.18) 7(15.91) 12(27.27) 18(40.91) 17(38.64)

21 - 30 2(4.55) 5(11.36) 2(4.55) 11(25.00) 8(18.18) 15(34.09)

31 - 40 1(2.27) 6(13.64) 1(2.27) 8(18.18) 2(4.55) 4(9.09)

Above 40 0(0.00) 8(18.18) 0(0.00) 0(0.00) 0(0.00) 2(4.55)

42

constitute 15.91%. In Oyo state, 54.55% of the respondents are within age range of 31-40 years,

36.36% were within 31-40 years, 27.27% were less or equal to 30 years, while age range 41-

60years made up 18.18%. In Ogun state, 40.91% of the respondents were within 41-50 years,

22.73% were within 51-60 years, 20.45% were within 31-40 years while those within age range

of less or equal to 30 and above 60 constitute 15.91%. In Lagos state, 59.09% of the respondents

were within 31-40 years, 22.73% were within 41-50 years, 11.36% were less or equal to 30 years

and 6.82% were within 51-60years. In Kebbi state, those within the age range 31-50 constitute

68.18% of the respondents while 15.91% were less or equal to 30 years, while 13.64% were

within 51-60 years and 4.55% were above 60years old. Majority of the respondents were middle

aged, between 31-50 years of age, which shows less interest and participation of youths and

older men and women

Marital status: In Kwara state, 54.55% of the respondents were single while 45.45% were

married. In Niger state, 90.91% of the respondents were married while 9.09% were single. In

Oyo state, 75.00%were married while 18.18% were single, 2.27% were divorced. In Ogun state,

93.18% were married, while the remaining 6.82% were either single, divorced, or widowed. In

Lagos state, 68.18% of the respondents were married, 22.73% were divorced, 6.82% were

widowed while 2.27% were single. In Kebbi state, 88.63% were married while 11.36% were

single.

Religion: In Kwara state, 77.27% of the respondents were Muslims while 22.73% were

Christians. In Niger state, 54.55% of the respondents were Christians while 45.45 % were

Muslims. In Oyo state, 54.55% were Muslims while 45.45% were Christians. In Ogun state,

54.55% were Muslims while 45.55% were Christians. In Lagos state, 72.73% of the respondents

were Christians while27.27% were Muslims. In Kebbi state, 84.09% were Muslims while

15.91% were Christians. Across the states, there were more Muslims participating in fish trading

than Christians.

Level of education: In Kwara state, 68.18% of the respondents had tertiary education followed

by 18.18% who had no formal education,11.36% had secondary education while 2.27% had

primary education. In Niger state, 72.73% of the respondents had no formal education while

27.27% had Quranic education. In Oyo state,34.09% of the respondents had no formal education,

followed by 29.54% who had tertiary education, then 18.18% who had secondary education,

15.91% who had primary education and 2.27% who had Quranic education. In Ogun state,

43

respondents who had tertiary education and Quranic education constitute 22.73% each while

those with no formal education and primary education constitute 20.45% each and 13.64% had

secondary education. In Lagos state, 34.09% had no formal education,22.73% had primary

education, 18.18% had Quranic education, 13.64% had secondary education while 11.36% had

tertiary education. In Kebbi state, 45.45% of the respondents had Quranic education, 29.55% had

no formal education, 15.91% had secondary education, 6.82% had tertiary education while

2.27% had primary education.

Household size: In Kwara state, 68.18% of the respondents had household size of less than or

equal 5, while 31.82% had household size of 6-10. In Niger state, 31.82% had hosehold size of

above 15, 27.27% had household size of 6-10, while those who had household size of lessor

equal to 5 and 11-15 constitute20.45% each. In Oyo state, 52.27% of the respondents had

household size of less or equal 5, 29.54% had household size of 6-10 while 18.18% had

household size of 11-15. In Ogun state, 63.64% of the respondents had household size of less or

equal 5, 25.00% had household size of 6-10, 6.82% had household size of 11-15 and 4.55% had

household size of above 15. In Lagos state, 54.55% of the respondents had household size of 6-

10 while 45.45% had household size of less or equal to 5. In Kebbi state, 34.09% had household

size of 11-15, 29.55% had household size of less or equal to 5, 27.27% had household size of 6-

10 while 9.09% had household size of above 15.

Years of experience: In Kwara state, 79.54% of the respondents had less or equal to 10, 13.64%

had 11-20 years,4.55% had 21-30 years, 2.27% had 31-40 years. In Niger state, 43.18% had 11-

20 years of experience, those with less or equal to 10 and 31-40 years constitute 13.64% each,

18.18% had above 40 years while 11.36% had within 21-30 years. In Oyo state, 77.27% had less

or equal to 10 years of experience, 15.91% had 11-20 years, while those who had within 21-40

years constitute 6.82%. In Ogun state, 29.54% of the respondents had less or equal to 10 years of

experience, followed by 27.27% with 11-20 years of experience, 25% had 21-30 years of

experience, while 18.18% had 31-40 years. In Lagos state, 40.91% of the respondents had 11-20

years of experience, 36.36% had less or equal to 10 years of experience, 18.18% had 21-30 years

while 4.55% had 31-40 years.

44

4.1.9 Socioeconomic characteristics of Consumers in Sampled States along Nigeria-Benin

Border

Tables 4.9 consists of the results of socio-economic characteristics of respondent consumers in

sampled States along Nigeria-Benin border

Sex: In Kwara state, 66.36% of the respondents were male while 33.33% are female. In Niger

state, 77.78% of the respondents are male while 22.22% are females. In Oyo state, 55.56% of the

respondents are male while 44.44% were female. In Ogun state, 55.56% of the respondents were

male while 44.44% were females. In Lagos state, 66.67% were male while 33.33% were females.

In Kebbi state, 55.56% of the respondents were male while 44.44% were females.

Age: In Kwara state, 33.33% of the respondents were less than or equal to 30 years of age, while

age ranges 31-40 years, 41-50 years and 51-60years constitute 22.22% each. In Niger state,

44.44% of the respondents were within the age range 31-40 years, age ranges 41-50years, 51-60

years, and less than or equal to 30years constitute 22.22% each. In Oyo state, those within age

ranges 31-40 years and 41-50 years constitute 44.44% each, while 11.11% were less than or

equal to 30years. In Ogun state, 55.56% of the respondents were within 41-50 years of age,

33.33% were within 51-60 years while 11.11% were within 31-40 years. In Lagos state, 44.44%

of the respondents were within 51-60 years of age, those within the age ranges, 31-40years and

41-50 years constitute 22% each while 11.11% were above 60years old.

Household size: In Kwara state, 100% of the respondents had household size of less or equal

to5. In Niger state, 55.56% of the respondents had household size of less or equal 5, 33.33% had

5-10, while 11.11% had10-15. In Oyo state, 88.89% of the respondents had a household size of

less or equal to 5 while 11.11% had 5-10. In Ogun state, 100% of the respondents had a

household size of less or equal to 5. In Lagos state, 66.67% had a household size of less or equal

to 5, 22.22% had within 5-10, and 11.11% had within 11-15. In Kebbi state,66.67% had a

household size of less or equal to 5, 22.22% had within 5-10 while 11.11% had within 11-15.

Religion: 77.78% of the respondents were Christians, while 22.22% were Muslims. In Niger

state, 88.89% were Muslims while 11.11% were Christians. In Oyo state, 66.67% of the

respondents were Christians while 33.33% were Muslims.In Ogun state, 77.78% of the

respondents were Christians while 22.22% were Muslims.

45

Table 4.9: Socio-economic characteristics of consumers in Sampled States along Nigeria-Benin

Border

Variables Categories

Kwara Niger Oyo Ogun Lagos Kebbi

Frequency (%)

Frequency (%)

Frequency (%)

Frequency (%)

Frequency (%)

Frequency (%)

Sex Male 6(66.36) 7(77.78) 5(55.56) 5(55.56) 6(66.67) 5(55.56)

Female 3(33.33) 2(22.22) 4(44.44) 4(44.44) 3(33.33) 4(44.44)


3(33.33) 2(22.22) 1(11.11) 0(0.00) 0(0.00) 0(0.00)

31 – 40 2(22.22) 4(44.44) 4(44.44) 1(11.11) 2(22.22) 4(44.44)

41 – 50 2(22.22) 2(22.22) 4(44.44) 5(55.56) 2(22.22) 3(33.33)

51 – 60 2(22.22) 2(22.22) 0(0.00) 3(33.33) 4(44.44) 2(22.22)

Above 60 0(0.00) 0(0.00) 0(0.00) 0(0.00) 1(11.11) 1(11.11)

Marital Status

Married 7(77.78) 9(100) 7(77.78) 9(100.00) 9(100.00) 8(88,89)

Single 1(11.11) 0(0.00) 2(22.22) 0(0.00) 0(0.00) 0(0.00)

Divorced 1(11.11) 0(0.00) 0(0.00) 0(0.00) 0(0.00) 0(0.00)

Widowed 0(0.00) 0(0.00) 0(0.00) 0(0.00) 0(0.00) 2(22.22)

Household Size

Less equal 5 9(100.00) 0(0.00) 8(88.89) 9(100.00) 6(66.67) 6(66.67)

6 – 10 0(0.00) 5(55.56) 1(11.11) 0(0.00) 2(22.22) 1(11.11)

11 – 15 0(0.00) 3(33.33) 0(0.00) 0(0.00) 1(11.11) 2(22.22)

Above 15 0(0.00) 1(11.11) 0(0.00) 0(0.00) 0(0.00) 0(0.00)

Religion Christian 7(77.78) 1(11.11) 6(66.67) 7(77.78) 8(88.89) 0(0.00)

Muslim 2(22.22) 8(88.89) 3(33.33) 2(22.22) 0(0.00) 9(100.00)

Traditionalist 0(0.00) 0(0.00) 0(0.00) 0(0.00) 1(11.11) 0(0.00)

Level of Education

No formal 0(0.00) 1(11.11) 0(0.00) 0(0.00) 1(11.11) 0(0.00)

Quranic 0(0.00) 6(66.67) 0(0.00) 0(0.00) 0(0.00) 3(33.33)

Adult literacy

0(0.00) 0(0.00) 1(11.11) 1(11.11) 0(0.00) 0(0.00)

Primary 0(0.00) 2(22.22) 0(0.00) 2(22,.22) 2(22.22) 3(33.33)

Secondary 0(0.00) 0(0.00) 6(66.67) 3(33.33) 1(11.11) 0(0.00)

Tertiary 9(100.00) 0(0.00) 2(22.22) 3(33.33) 5(55.56) 3(33.33)

46

In Lagos state, 88.89% were Christians while 11.11% were traditionalist. In Kebbi state, 100%

of the respondents were Muslims.

Level of education: In Kwara state, 100% of the respondents had tertiary education. In Niger

state, 66.67% of the respondents had Quranic education, 22.22% had primary education, while

11.11% had no formal education. In Oyo, 66.67% had secondary education, 22.22% had tertiary

education while 11.11% had adult literacy education. In Ogun state, those with secondary and

tertiary education constitute 33.33% each, 22.22% had primary education while 11.11% had

adult literacy education. In Lagos state, 55.56% had tertiary education, 22.22% had primary

education,11.11% had secondary education, while 11.11% had no formal education. In Kebbi

state, those with tertiary education, primary education and Quranic education constitute 33.33%

each.

4.2 Profitability Indices of the Respondent Value-Chain Actors

4.2.1 Monthly Quantities, Cost Variables and Profitability Indices Associated With Fresh

Fish Caught and Marketed By Respondent Artisanal Fishermen along Nigeria-Benin

Border

It was observed that majority of the respondent artisanal fishermen operated small and medium

scale of operation. Presented in Table 4.10 are the pool of mean monthly quantities, cost

variables and profitability indices of respondent artisanal fishermen in sampled Nigeria States

along Nigeria-Benin Border according to scale of operation. The mean quantity of fish catches of

747.06±233.98kg marketed by medium scale artisanal fishermen was significantly higher

(P<0.05) than 192.79±130.75kg marketed by the small scale artisanal fishermen. Similarly, the

gross margin/kg and marketing efficiency of ₦589.92±159.35 and 138.01±155.96 respectively of

the medium scale artisanal fishermen was significantly higher (P<0.05) than the gross margin/kg

and marketing efficiency of ₦575.98±231.21 and 63.90±85.68 respectively of the small scale

artisanal fishermen.

47

Table 4.10: Average monthly quantities, cost variables and profitability indices associated with fresh fish caught and marketed by artisanal fishermen along Nigeria-Benin Border during the period of study

Variables Artisanal

Mean SD

Total Quantity Sold (kg) 282.53 254.58

Average Selling Price (₦) 655.00 222.00

Operational Cost (₦) 10696.95 10417.18

Maintenance Cost (₦) 5298.02 5192.97

Marketing Cost (₦) 6399.89 956.54

Total Variable Cost (₦) 16045.43 11625.77

Fixed Cost Depreciated (₦) 2673.57 1831.41

Total Cost of Value-addition (₦) 18719.00 12482.05

Total Revenue 181023.38 163591.62

Gross Margin (₦) 166446.97 156446.70

Gross Margin/kg (₦) 578.26 220.47

Net Return (₦) 163759.73 156108.48

Net Return/kg (₦) 560.63 222.65

Marketing Efficiency 76.01 103.28

48

4.2.2 Mean Monthly Quantities, Cost Variables And Profitability Indices Of Respondent

Artisanal Fishermen In Sampled Nigeria States Along Nigeria-Benin Border According To

Scale Of Operation

Presented in Table 4.10 are the average monthly quantities, cost variables and profitability

indices associated with fish marketed by artisanal fishermen along Nigeria-Benin Border during

the period of study. As indicated in Table 4.10, the highest mean monthly quantity of fish caught

of 502.93±241.48kg was recorded by respondent artisanal fishermen in Kebbi State while the

least mean monthly quantity of 119.63±64.21kg was reported by respondents in Kwara State.

There was significant difference (P<0.05) in the mean monthly quantity of fresh fish caught

marketed by artisanal fishermen in the sampled Nigerian States along Nigeria-Benin Border.

Meanwhile, artisanal fishermen in Lagos State had the highest mean selling price of

₦816.00±224.00/kg with the least mean selling price of ₦526.32±145.00/kg recorded in Kwara

State. Furthermore, the mean monthly operational, maintenance, marketing and total production

costs of ₦25,989.37±18,257.63, ₦12,994.68±9.128.82, ₦16,538.69±12,439.54 and

₦42,390.61±27,656.50 respectively incurred by respondent artisanal fishermen in Niger State

was significantly (P<0.05) higher than the least operational, maintenance, marketing and total

production costs of ₦1100.20±20.50, ₦520.04±10.06, ₦575.76±234.17 and ₦3,430.92±1,143.49

recorded in Kwara State.

The results presented in Table 4.11 also indicated that respondent artisanal fishermen in Lagos

had the highest mean monthly revenue, gross margin/kg and net return/kg of

₦278,092.50±229,206.53, ₦741.35±208.12 and ₦726.86±209.00 respectively while respondent

in Kwara State had mean revenue, gross margin/kg and net return/kg of ₦61,349.47±31,665.94,

₦509.10±146.51 and ₦487.83±146.12 respectively which were significantly (P<0.05) lower than

values of similar variables recorded in other Nigerian States along Nigeria-Benin border.

Presented in Tables 4.13 and 4.14 are the mean monthly quantities, cost variables and

profitability indices of small and medium scale artisanal fishermen in sampled Nigeria States


49

Table 4.11: Average monthly quantities, cost variables and profitability indices associated with fresh fish caught and marketed by artisanal fishermen in Nigerian States along Nigeria-Benin Border during the period of study

Variables Niger State Oyo State Kebbi State Ogun State Kwara State Lagos State

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Total Quantity Sold (kg)

279.02bcd 295.17 175.08cd 125.32 502.93a 241.48 293.27bc 179.60 119.63d 64.21 371.82ab 315.29

Average Selling Price (₦)

687.52ab 261.00 574.21bc 143.00 593.33bc 175.00 750.00a 227.00 526.32c 145.00 816.00a 224.00

Operational Cost (₦)

25989.37a 18257.63 3221.05c 206.74 1992.30c 1159.34 16808.85b 12507.01 1100.20c 20.50 14121.08b 14188.22

Maintenance Cost (₦)

12994.68a 9128.82 1610.53c 103.37 933.89c 612.89 8404.42b 6253.51 520.04c 10.06 7060.54b 7094.11

Marketing Cost (₦)

16538.69a 12439.54 2040.00c 498.55 996.15c 887.89 9481.91b 8697.37 575.76c 234.17 9414.05b 9458.81

Total Variable Cost (₦)

38984.05a 27386.45 4831.58c 310.11 2988.44c 1739.01 25213.27b 18760.52 1520.10c 12.10 21181.62b 21282.33

Fixed Cost Depreciated (₦)

3406.56a 691.32 1634.46b 1013.99 2078.85b 2887.94 3868.39a 1315.23 1930.92b 1143.49 3385.49a 2173.25

Total Cost of Value-addition (₦)

42390.61a 27656.50 6466.04c 967.59 5067.29c 4249.18 29081.66b 18642.37 3430.92c 1143.49 24567.11b 22686.06

Total Revenue 172922.14ab 142338.83 106468.42bc 99743.35 273920.00a 119347.20 228809.09a 161626.39 61349.47c 31665.94 278092.50a 229206.53

Gross Margin (₦)

133938.10bc 129393.89 101636.84c 99675.63 270931.56a 119321.51 203595.82ab 159998.58 59849.47c 31665.94 269790.40a 215273.97

Gross Margin/kg (₦)

500.37b 268.14 529.77b 150.03 584.90b 169.65 639.39ab 280.07 509.10b 146.51 741.35a 208.12

Net Return (₦) 130531.54bc 129199.24 100002.38c 99836.58 268852.71a 119901.26 199727.43ab 160380.71 57918.55c 31436.58 266292.64a 214430.28

Net Return/kg (₦)

478.43b 269.34 514.50b 155.57 577.51ab 163.62 612.89ab 288.40 487.83a 146.12 726.86a 209.00

Marketing Efficiency

12.58c 8.04 49.05bc 45.31 268.15a 143.92 24.18c 13.06 92.02b 47.50 35.40c 23.88

Note: There is significant difference (P<0.05) in the mean values of with different superscript alphabets on the same row

50

Table 4.12: Mean monthly quantities, cost variables and profitability indices of respondent artisanal fishermen in sampled Nigeria States along Nigeria-Benin Border according to scale of operation

Variable Small scale Medium scale Sig.-values

Mean SD Mean SD

Total Quantity Sold (kg) 192.79 130.75 747.06 233.98 0.00

Average Selling Price (₦) 662.00 231.00 622.00 173.00 0.50

Operational Cost (₦) 9936.08 14278.06 14635.59 14929.38 0.22

Maintenance Cost (₦) 4968.04 7139.03 7317.79 7464.69 0.24

Marketing Cost (₦) 6624.05 9518.71 9757.06 9952.92 0.24

Total Variable Cost (₦) 14904.12 21417.09 21953.38 22394.07 0.22

Fixed Cost Depreciated (₦) 2571.89 1629.42 3199.91 2648.32 0.22

Total Cost of Value-addition (₦) 17476.01 22178.35 25153.29 23628.37 0.24

Total Revenue 128423.35 102900.33 453305.88 149636.23 0.36

Gross Margin (₦) 114683.82 94253.83 431352.50 143808.56 0.20

Gross Margin/kg (₦) 575.98 231.21 589.92 159.35 0.00

Net Return (₦) 112096.76 94052.88 428152.59 143347.23 0.00

Net Return/kg (₦) 555.79 233.51 585.45 158.91 0.81

Marketing Efficiency 63.90 85.68 138.01 155.96 0.00

51

Table 4.13: Mean monthly quantities, cost variables and profitability indices of small scale artisanal fishermen in sampled Nigeria States along Nigeria-Benin border




208.39bc 137.90 175.08bc 125.32 323.00c 118.48 231.78ab 129.21 119.63c 64.21 195.46bc 150.52


705.37ab 268.28 574.21bc 143.22 662.50bc 200.23 738.89ab 252.01 526.32c 144.83 855.71a 233.64

Operational Cost (₦)

24549.47a 18492.12 3221.05c 206.74 1526.11c 1074.61 16210.81ab 13873.66 1000.00c 0.00 12116.34b 14180.16

Maintenance Cost (₦)

12274.74a 9246.06 1610.53c 103.37 763.06c 537.31 8105.41ab 6936.83 500.00c 0.00 6058.17b 7090.08

Marketing Cost (₦)

16366.32a 12328.08 2147.37c 137.83 1017.41c 716.41 10807.21ab 9249.11 666.67c 0.00 8077.56b 9453.44


36824.21a 27738.17 4831.58c 310.11 2289.17c 1611.92 24316.22ab 20810.50 1500.00c 0.00 18174.51b 21270.24


3387.08a 724.06 1634.46c 1013.99 1971.21bc 2578.19 3990.69ab 1341.34 1930.92bc 1143.49 3038.85ab 2101.25


40211.29a 28011.24 6466.04c 967.59 4260.37a 4086.56 28306.91ab 20666.81 3430.92c 1143.49 21213.36b 22489.69

Total Revenue 143208.68ab 100248.66 106468.42bc 99743.35 195600.00a 42433.41 178322.22ab 129376.96 61349.47c 31665.94 158717.86ab 132000.33

Gross Margin (₦)

106384.47bc 84486.49 101636.84bc 99675.63 193310.83a 43828.44 154006.00ab 128858.64 59849.47c 31665.94 150415.91ab 112068.31


507.72b 281.41 529.77b 150.03 651.54ab 191.33 615.19ab 307.26 509.10b 146.51 767.37a 227.16

Net Return (₦) 102997.39bc 84192.36 100002.38bc 99836.58 191339.63a 45984.37 150015.31ab 129105.61 57918.55c 31436.58 147239.64ab 111227.35

Net Return/kg (₦)

484.00b 283.16 514.50b 155.57 640.27ab 182.66 584.12ab 314.36 487.83a 146.12 748.76a 230.14


11.92c 7.59 49.05c 45.31 264.34a 131.35 21.65c 12.92 92.02b 47.50 26.37c 18.94


52

Table 4.14: Mean monthly quantities, cost variables and profitability indices of medium scale artisanal fishermen in sampled Nigeria States along Nigeria-Benin Border

Niger State Kebbi State Ogun State Lagos State

Mean SD Mean SD Mean SD Mean SD


950.00a 636.40 708.57a 164.87 570.00a 42.43 783.33a 168.96


518.00b 116.00 514.00b 107.00 800.00a 0.00 723.00ab 183.00

Operational Cost (₦) 39668.33a 9897.14 2525.08b 1080.73 19500.00b 2592.72 18798.79b 14305.61 Maintenance Cost (₦)

19834.17a 4948.57 1262.54b 540.37 9750.00b 1296.36 9399.40b 7152.81

Marketing Cost (₦) 26445.56a 6598.09 1683.39b 720.49 13000.00b 1728.48 12532.53b 9537.07 Total Variable Cost (₦)

59502.50a 14845.71 3787.62b 1621.10 29250.00b 3889.09 28198.19b 21458.41


3591.61a 214.18 2201.86a 3416.50 3318.05a 1471.18 4194.34a 2312.21


63094.11a 15059.88 5989.48b 4559.16 32568.05b 5360.27 32392.54b 23144.67

Total Revenue 455200.00a 219485.94 363428.57a 116657.41 456000.00a 33941.13 556633.33a 146047.69 Gross Margin (₦) 395697.50a 234331.65 359640.95a 117327.81 426750.00a 37830.21 528435.14a 139157.54 Gross Margin/kg (₦) 430.50c 41.72 508.74bc 108.43 748.29a 10.67 684.97ab 162.83 Net Return (₦) 392105.90a 234545.83 357439.09a 117945.88 423431.95a 39301.39 524240.80a 138352.73 Net Return/kg (₦) 425.53c 38.17 505.79bc 110.84 742.35a 13.69 679.40ab 161.81 Marketing Efficiency

18.83b 13.00 272.51a 167.81 35.56b 7.34 54.97b 22.80


53

4.2.3 Mean Monthly Quantities, Cost Variables and Profitability Indices Associated With

Fresh Fish Produced and Marketed By Respondent Fish Farmers along Nigeria-Benin

Border

An average of 2,250.02±1,814.41kg of fresh fish produced monthly by respondent fish farmers

were marketed in fish markets along Nigeria-Benin border at an average selling price, total

monthly variable and production costs of ₦542.36±88.09/kg, ₦466,786.67±417,175.18 and

₦469,288.97±417,937.72 respectively. The profitability analysis results indicated mean monthly

revenue, gross margin/kg, net return/kg and marketing efficiency of

₦1,262,725.87±1,126,674.74, ₦300.28±131.73/kg, ₦298.41±132.62/kg and 42.91±14.29

correspondingly were recorded from the marketed fresh fish produced by the fish farmers in the

study area as indicated in Table 4.15.

The results presented in Table 4.16 indicated that respondent fish farmers in Lagos State had the

highest mean monthly quantity of fresh fish production of 3,415.38±1,763.45kg while

respondent fish farmers in Kwara State had the least mean monthly production of

922.97±907.46kg which was significantly (P<0.05) lower than the mean production of

respondent fish farmers in Ogun, Niger and Kebbi States. The highest mean buying price of fish

seeds of ₦22.07±8.29 was recorded in Kebbi State as the least mean buying price of

₦12.84±5.58 was reported in Oyo State. In Lagos State the highest mean selling price

(₦702.31±23.15) of fresh fish produced by fish farmers was recorded while fresh fish was

cheapest in Ogun State at a least mean selling price of ₦488.64±45.39 recorded.

It should be noted that the highest mean purchase, feeding, total variable and production cost of

₦343,923.08±218,815.55, ₦590,807.69±320,999.58, ₦999,427.82±461,882.67 and

₦1,004,126.56±462,629.07 respectively were recorded in Lagos State whereas in Kwara State

the least mean purchase, feeding, total variable and production cost of ₦19,455.26±17,386.06,

₦123,892.11±81,558.24, ₦172,737.04±101,121.54 and ₦174,368.47±101,413.47 respectively

were recorded. Similarly, respondent fish farmers in Lagos State also had the highest mean

monthly revenue, gross margin/kg, net return/kg and marketing efficiency of

₦2,408,461.54±1,249,180.37, ₦373.21±128.31/kg, ₦371.20±129.86 and ₦54.55±11.98

respectively while respondent fish farmers in Kwara State had the least mean monthly revenue,

gross margin/kg and net return/kg of ₦461,511.58±336,954.31, ₦249.09±106.03 and

54

Table 4.15: Mean monthly quantities, cost variables and profitability indices associated with fresh fish produced and marketed by respondent fish farmers along Nigeria-Benin Border during the period of study

Variables Producers

Mean SD

Total Quantity Sold (kg) 2250.02 1814.41

Selling Price (₦/kg) 542.36 88.09

Buying Price (₦/fish seed) 14.02 6.07

Total Purchase Cost (₦) 79464.68 29467.40

Other Operational Cost (₦) 18102.88 14310.30

Cost of Feeding (₦) 339316.97 328651.05

Cost of Labour (₦) 29490.75 16788.07


Fixed Cost Depreciated (₦) 2502.29 1760.90


Total Revenue (₦) 1262725.87 1126674.74

Gross Margin (₦) 795939.20 726331.99

Gross Margin/kg (₦) 300.28 131.73

Net Return (₦) 793436.91 725731.21

Net Return/kg (₦) 298.41 132.62


55

Table 4.16: Mean Monthly Quantities, Cost Variables and Profitability Indices Associated With Fresh Fish Produced and Marketed By Respondent Fish Farmers in sampled Nigeria States Along Nigeria-Benin Border




2276.82ab 1509.75 1950.00bc 1860.16 2574.29ab 2543.78 2733.43ab 1428.04 922.97c 907.46 3415.38a 1763.45

Selling Price (₦/kg)

546.72c 42.16 492.62d 79.96 586.43b 81.11 488.64d 45.39 507.37d 56.06 702.31a 23.15

Buying Price (₦/fish seed)

13.41b 4.73 12.84b 5.58 22.07a 8.29 11.82b 4.00 13.11b 5.53 13.15b 2.79

Total Purchase Cost (₦)

39704.55bc 37274.61 37631.58bc 46944.96 91428.57c 56786.66 43295.45bc 45288.14 19455.26c 17386.06 343923.08a 218815.55

Other Operational Cost (₦)

26980.45a 31397.12 17973.68ab 25476.61 20783.14ab 16783.80 23231.82ab 31609.81 7928.95c 5403.43 6571.54c 3690.80

Cost of Feeding (₦)

365022.73bc 392965.79 241300.00cd 188260.23 506107.14ab 473392.43 329563.64bcd 241256.30 123892.11d 81558.24 590807.69a 320999.58

Cost of Labour (₦)

31742.86b 13313.57 20820.00c 5000.64 27650.00bc 16766.61 26333.33bc 8515.16 21133.97c 10081.26 57891.54a 21679.74


1818.22c 737.31 2098.33c 1095.99 3609.05b 2696.50 2285.16c 1565.75 1631.43c 1100.34 4698.74a 1453.08


464018.77bc 447117.02 318341.93cd 236854.99 646781.36b 491586.59 422424.24bc 263260.29 172737.04d 101121.54 999427.82a 461882.67


465836.99bc 447265.28 320440.26cd 236961.44 650390.41b 492169.37 424709.40bc 263229.86 174368.47d 101413.47 1004126.56a 462629.07

Total Revenue (₦)

1255467.26b 831626.14 972379.39bc 893382.36 1595428.57b 1483752.17 1323950.55b 704723.41 461511.58c 336954.31 2408461.54a 1249180.37

Gross Margin (₦)

791448.49bc 570804.68 654037.46bc 773377.68 948647.21ab 405121.28 901526.30ab 613319.26 288774.54c 447844.20 1409033.72a 828259.73


337.79ab 132.30 275.56b 151.01 251.88b 151.44 316.04ab 97.15 249.09a 106.03 373.21a 128.31

Net Return (₦) 789630.27bc 570783.91 651939.14bc 773347.31 945038.17ab 404649.49 899241.14ab 612762.00 287143.11c 447709.12 1404334.98a 827536.69

Net Return/kg (₦)

336.61ab 132.70 273.57b 151.78 249.57b 152.33 314.98ab 97.25 246.03b 107.58 371.20a 129.86


44.49b 14.54 42.19b 14.06 30.49c 14.55 43.52b 10.78 42.31b 13.21 54.55a 11.98


56

₦246.03±107.58 respectively as the least marketing efficiency of 30.49±14.55 was recorded in

Kebbi State.

Significant difference (P<0.05) were recorded in the costs and profitability indices associated

with the production of fresh fish marketed by respondent fish farmers in sampled Nigeria States

along Nigeria-Benin border during the period of study.

4.2.4 Mean Monthly Quantities, Cost Variables and Profitability Indices of Respondent

Fish Farmers in sampled Nigeria States along Nigeria-Benin Border According to Scale of

Operation

The analysis of quantity of fresh fish produced and marketed by respondent fish farmers along

Nigeria-Benin border according to scale of operation as presented in Table 4.17 indicated that

large scale farmer had the highest mean production of 3,596.41±1,643.81kg while small scale

fish farmers had the lowest production of 357.21±126.09kg. Even though the medium scale fish

farmers had the highest buying price of ₦14.81±6.92 per fish seed, this was not significantly

different (P>0.05) from the lowest buying price of ₦11.64±3.44 recorded by the small scale fish

farmers. Similar result was also observed in the selling price of fresh fish by respondents as the

selling price of ₦557.63±94.80/kg of largest scale fish farmer was not significantly different

(P>0.05) from the lowest selling price of ₦513.41±82.60/kg recorded by the small scale fish

farmers.

As indicated in Table 4.18, the highest mean total purchase, labour and production costs of

₦117,563.64±162,805.81, ₦36,199.25±19,564.84 and ₦694,156.92±473,216.06 respectively as

well as the highest mean revenue, gross margin and net return/kg of

₦2,043,697.29±1,110,226.00, ₦1,352,321.80±837,180.00 and ₦358.60±122.11 respectively

were recorded by large scale fish farmer. These values were significantly (P<0.05) higher than

the least mean total purchase, labour and production costs of ₦11,327.27±15,008.85,

₦19,929.92±6,869.45 and ₦120,747.31±47,656.01 respectively and the lowest mean revenue,

gross margin and net return/kg of ₦186,481.71±80,581.53, ₦67,293.46±54,341.02 and

₦165.57±98.03 recorded by the small scale fish farmers in the study area. It is indicative to note

that the marketing efficiency of small scale fish farmers of 45.39±11.04 was higher than

57

Table 4.17: Mean Monthly Quantities, Cost Variables and Profitability Indices of Respondent Fish Farmers in sampled Nigeria States Along Nigeria-Benin Border According to Scale of Operation

Variables Small scale Medium scale Large scale

Mean SD Mean SD Mean SD

Total Quantity Sold (kg) 357.21c 126.09 1012.10b 326.11 3596.41a 1643.81 Selling Price (₦/kg) 513.41a 82.60 530.24a 78.10 557.63a 94.80

Buying Price (₦/fish seed) 11.64a 3.44 14.81a 6.92 13.87a 5.70 Total Purchase Cost (₦) 11327.27b 15008.85 48163.95ab 69638.62 162805.81a 117563.64 Other Operational Cost (₦) 7727.27b 7226.63 14847.77ab 13577.51 22722.91a 31254.14 Cost of Feeding (₦) 79927.27b 30519.92 181654.65b 105154.07 514458.18a 377502.59 Cost of Labour (₦) 19929.92b 6869.45 23355.91b 9996.92 36199.25a 19564.84 Fixed Cost Depreciated (₦) 1559.06b 893.94 2386.56ab 1978.29 2781.43a 1654.81 Total Variable Cost (₦) 119188.25b 47068.08 268442.43b 148666.90 691375.49a 472394.31 Total Cost of Value-addition (₦)

120747.31b 47656.01 270828.99b 149478.24 694156.92a 473216.06

Total Revenue (₦) 186481.71b 80581.53 539127.22b 199286.35 2043697.29a 1110226.00 Gross Margin (₦) 67293.46b 54341.02 270684.78b 164685.86 1352321.80a 837180.00 Gross Margin/kg (₦) 170.22c 96.78 257.89b 111.27 359.43a 122.06 Net Return (₦) 65734.40b 54365.91 268298.23b 164795.34 1349540.37a 836390.85 Net Return/kg (₦) 165.57c 98.03 255.42b 111.86 358.60a 122.11 Marketing Efficiency 45.39a 11.04 40.64a 14.48 44.20a 14.69


58

Table 4.18: Mean Monthly Quantities, Cost Variables and Profitability Indices of Small Scale Fish Farmers in sampled Nigeria States along Nigeria-Benin Border

Variables Oyo State Kwara State Lagos State


Total Quantity Sold (kg) 446.67a 75.72 298.48a 114.72 500.00a 0.00

Selling Price (₦/kg) 449.15a 61.03 521.43 a 69.86 650.00 a 0.00

Buying Price (₦/fish seed) 11.33a 4.16 11.71 a 3.73 12.00 a 0.00

Total Purchase Cost (₦) 5833.33b 2020.73 7300.00b 2731.15 56000.00a 0.00

Other Operational Cost (₦) 10966.67a 14195.19 6300.00 a 3498.09 8000.00 a 0.00

Cost of Feeding (₦) 95666.67b 6658.33 65171.43c 25214.11 136000.00a 0.00

Cost of Labour (₦) 19606.67b 1450.56 17915.58b 5942.24 35000.00a 0.00

Fixed Cost Depreciated (₦) 1565.70a 630.16 1352.84 a 901.17 2982.67 a 0.00

Total Variable Cost (₦) 132073.33c 10525.12 96687.01b 25047.08 238041.67a 0.00

Total Cost of Value-addition (₦) 133639.03c 10945.08 98039.85b 25484.66 241024.34a 0.00

Total Revenue (₦) 203042.94a 57438.03 159595.71 a 74459.65 325000.00 a 0.00

Gross Margin (₦) 70969.60a 60502.25 62908.70 a 60064.68 86958.33 a 0.00

Gross Margin/kg (₦) 147.59a 115.23 179.40 a 104.06 173.92 a 0.00

Net Return (₦) 69403.90a 60211.79 61555.86 a 60291.30 83975.66 a 0.00

Net Return/kg (₦) 144.17a 114.99 174.40 a 106.25 167.95 a 0.00

Marketing Efficiency 40.78a 8.89 46.26 a 12.46 53.17 a 0.00


59

44.20±14.69 recorded by the large scale fish farmers, although no significant difference (P>0.05)

was observed in the mean values.

Presented in Tables 4.19 – 4.20 are the mean monthly quantities, cost variables and profitability

indices of small, medium and large scale fish farmers in the sampled Nigeria states along

Nigeria-Benin border.

4.2.5 Forms of Fish Products Produced By Respondent Fish Processors

Presented in Figure 4.1 are the percentages of forms of fish produced by the respondent fish

processors along Nigeria-Benin Border. Smoked fish had the highest percentage of the fish

product (79.35%) produced by the respondent fish processors followed by dried fish with

18.02% while spiced fish and fried fish had the least percentage of 1.11% and 1.52%

respectively. In the sampled States, respondent fish processors in Kwara, Niger and Ogun State

had the highest percentage of smoked, dried and spiced fish of 84.09%, 31.82% and 4.55%

respectively as forms of fish products produced. About 4.55% of the respondent fish processors

in Kebbi and Ogun States were involved in production of fried fish. It should be noted that no

respondent fish processors in Lagos, Kwara, Kebbi and Niger States were involved in spiced fish

production as indicated in Figure 4.2.

4.2.6 Average Monthly Quantities, Costs, Profitability and Marketing Efficiency Indices

of Fish Products Marketed

The results presented in Table 4.21 indicated that smoked and fried fish had the highest and least

mean monthly quantities of total monthly quantities of processed fish sold, selling prices, total

variable cost and total production cost of 267.42±265.90kg & 68.±11.21kg;

₦3,099.66±247.98/kg & ₦2,137.50±396.60; ₦535,427.83± 523,028.71 &

₦98,644.22±25,423.02; and ₦536,839.74±523,607.41 & ₦99,110.87±25,181.82 respectively.

There was significant difference (P<0.05) in the selling price while no significant variation

(P>0.05) were recorded in the costs variables associated with the different major fish products

marketed by fish processors along Nigeria-Benin border.

60

Table 4.19: Mean Monthly Quantities, Cost Variables and Profitability Indices of Medium Scale Fish Farmers in sampled Nigeria States along Nigeria-Benin Border

Variables Niger State Oyo State Kebbi State Ogun State Kwara State Lagos State Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Total Quantity Sold (kg)

991.67ab 289.78 867.50b 248.18 1030.00ab 348.55 1321.67a 371.08 842.79b 231.70 1300.00a 264.58


533.93bc 39.30 471.86c 29.94 568.75b 65.12 506.67bc 80.66 500.00c 55.90 710.00a 36.06


13.33ab 5.00 15.00ab 7.63 20.50a 9.07 11.67b 4.08 14.11ab 6.86 12.0ab 0.00


20944.44b 15363.20 32812.50 b 22548.26 86250.00 b 74582.17 22916.67 b 19153.11 26283.33 b 19214.19 185333.33a 186776.16


22178.89a 15686.28 11787.50 a 7830.42 23608.00 a 19975.49 7650.00 a 5728.44 9183.33 a 7127.94 9043.33 a 7349.67


162522.22bc 99816.73 142062.50bc 99600.07 260687.50ab 126432.06 183900.00abc 95926.85 129505.56c 33038.43 285833.33a 113477.24


25723.81b 7211.58 19115.00 b 3812.92 22300.00 b 3045.84 23722.22 b 4611.18 18348.48 b 5744.38 44666.67a 26945.93


1618.11a 461.27 2534.85 a 1319.28 3469.23 a 3519.10 2198.61 a 1915.89 1723.40 a 1218.80 3774.66 a 2090.79


231749.00b 104666.12 206311.87 b 126222.71 393366.33a 142526.97 238188.89 b 95531.72 184010.52b 44951.93 524876.67a 212537.93


233367.11 b 104740.93 208846.73 b 126681.95 396835.56a 143306.32 240387.50 b 95702.28

185733.92b 44936.67 528651.32a 214585.44

Total Revenue (₦)

533008.10bc 169061.73 406455.93c 109122.27 586250.00bc 209876.66 653866.67b 142808.78 418950.00c 116055.31 916666.67a 145716.62

Gross Margin (₦)

301259.10ab 153375.78 200144.06b 114687.79 192883.67b 133958.08 415677.78a 159687.44 234939.48ab 121863.75 391790.00a 322980.09


292.92a 116.17 239.30 a 101.67 175.33 a 87.53 310.77 a 81.47 270.92 a 90.98 277.69 a 222.34

Net Return (₦) 299640.99abc 153521.50 197609.20bc 114571.48 189414.44c 132077.79 413479.17a 160956.06 233216.08abc 121696.23 388015.34ab 324742.68 Net Return/kg (₦)

291.07 a 116.78 236.44 a 101.84 172.06 a 87.39 308.82 a 82.49 268.73 a 90.76 274.58 a 224.40


43.74ab 14.56 36.66b 14.88 32.44b 15.34 44.67ab 10.15 39.83b 14.14 58.17a 3.00


61

Table 4.20: Mean Monthly Quantities, Cost Variables and Profitability Indices of Large Scale Fish Farmers in sampled Nigeria States along Nigeria-Benin Border




3166.54ab 1355.20 3596.25ab 1851.86 4633.33a 2784.00 3262.83ab 1308.80 2620.67b 2206.45 4444.44ab 845.74


555.57bc 43.28 529.68cd 107.74 610.00b 100.00 481.88d 23.16 496.67cd 5.77 705.56a 10.14


13.46b 4.74 11.25b 2.76 24.17a 7.36 11.88b 4.10 13.33b 5.77 13.67b 3.28


52692.31b 42748.07 54375.00b 66159.84 98333.33b 22286.02 50937.50b 50206.86 27333.33b 20033.31 428777.78a 187629.14


30304.62a 39138.36 26787.50a 37370.56 17016.67a 11999.57 29075.00a 35417.20 7966.67a 2542.31 5588.89a 1815.52


505215.38abc 459945.41 395150.00bc 183868.80 833333.33a 579154.79 384187.50bc 258358.83 244066.67c 140425.12 743000.00ab 254065.44


35909.89b 15150.42 22980.00b 6314.85 34783.33b 24719.72 27312.50b 9522.27 37000.00b 15099.67 64843.33a 18385.82


1956.76c 871.02 1861.53c 911.81 3795.48b 1222.37 2317.62c 1484.78 2005.55c 1413.79 5197.44a 1051.74


624820.92bc 523518.37 500222.71c 247536.31 984668.06ab 600098.39 491512.50c 274440.90 316366.67c 174087.86 1242210.00a 292380.00


626777.68bc 523617.27 502084.24c 247810.40 988463.53ab 600859.55 493830.12c 274348.23 318372.22c 174523.65 1247407.44a 292187.58

Total Revenue (₦)

1755631.29b 727170.87 1826804.03b 765161.27 2941000.00a 2099704.26 1575232.00b 664480.38 1293666.67b 1076317.95 3137222.22a 600620.05

Gross Margin (₦)

1130810.37ab 499520.57 1326581.32ab 791026.50 1956331.95a 1725059.01 1083719.50ab 623135.51 977300.00b 912226.26 1895012.22ab 361546.02


368.86a 138.11 359.81a 166.95 353.94a 164.41 318.01a 104.81 346.22a 47.77 427.19a 25.96

Net Return (₦) 1128853.61ab 499698.34 1324719.78ab 790624.88 1952536.47a 1724491.57 1081401.89ab 622295.74 975294.45b 912314.38 1889814.78ab 361179.80

Net Return/kg (₦)

368.14a 138.17 359.23a 167.19 352.91a 164.96 317.29a 104.64 345.07a 48.43 425.98a 25.79


45.01a 15.09 48.24a 13.66 27.89b 14.39 43.09ab 11.30 40.50ab 14.72 53.50a 14.37


Figure 4.1: Percentage of Fish products produced by the respondent fish processors along Nigeria-Benin Border.

79.35%

1.52%1.11%

62

: Percentage of Fish products produced by the respondent fish processors along

18.02%

1.11%

Fish Products

Dried

Smoked

Fried

Spiced

: Percentage of Fish products produced by the respondent fish processors along

63

Figure 4.2: Percentage of value added fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin Border.

0

20

40

60

80

100Kebbi

Ogun

Lagos

Kwara

Niger

Oyo Fish Products

Dried

Smoked

Fried

Spiced

64

Table 4.21: Mean quantities, costs, profitability indices and marketing efficiency of value-added fish products produced by respondent fish processors along Nigeria-Benin Border.

Variables Dried Smoked Fried Spiced


Total Quantity of Marketed Products (kg)

171.39a 152.40 267.42a 265.90 68.50a 11.21 141.67a 58.92

Buying Price (₦/kg) 548.70a 80.93 548.69a 63.67 555.00a 40.41 550.00a 0.00

Selling Price (₦/kg) 2971.78a 252.34 3099.66a 247.98 2137.50b 396.60 2400.00b 565.69

Purchase Cost (₦) 296779.60a 243780.50 492356.93a 494862.00 69541.22a 25612.59 77915.75a 32407.76

Other Operational Cost (₦) 7806.19a 5632.15 11797.44a 12461.11 2675.00a 2277.97 5250.00a 6717.51

Total Marketing Cost (₦) 22797.24a 12798.88 31703.20a 23691.50 26428.00a 12661.77 17907.32a 2762.93

Total Variable Cost (₦) 326318.55a 251930.90 535427.83a 523028.71 98644.22a 25423.02 101073.07a 41888.21

Total Fixed Cost (Depreciated) (₦)

835.20a 820.66 1420.02a 1705.30 466.64a 297.87 375.00a 176.78


327153.75a 251818.03 536839.74a 523607.41 99110.87a 25181.82 101448.07a 41711.43

Total Revenue (₦) 482085.86a 385911.11 820169.94a 799328.46 144550.00a 22045.82 323330.00a 61277.87

Gross Margin (₦) 155767.32a 154792.13 284742.11a 294969.75 45905.78a 17150.33 222256.94a 19389.67

Gross Margin/kg (₦/kg) 863.43b 337.94 1059.49b 325.92 656.29b 134.96 1686.29a 564.52

Net Return (₦) 154932.12a 154908.96 283330.20a 294611.52 45439.13a 17164.51 221881.94a 19566.44

Net Return/kg (₦/kg) 853.23b 344.30 1050.81b 328.53 649.24b 134.80 1683.11a 561.94

Marketing Margin (₦) 185306.26a 160755.94 327813.01a 319843.52 75008.78a 16928.28 245414.25a 28870.11

Marketing Margin/kg (₦/kg) 1142.78b 271.61 1270.69b 313.48 1100.39b 228.03 1850.00a 565.69

Marketing Efficiency 23.41a 23.33 23.15a 10.08 6.22a 2.40 18.01a 0.64

Note: Mean values with the same alphabet superscripts are not significantly different (P>0.05); SD-Standard deviation

65

With respect to the profitability indices, smoked fish also had the highest mean total monthly

revenue, gross margin and net return of ₦820,169.94±799,328.46, ₦284,742.11±294,969.75 and

₦283,330.20±294,611.52 respectively. Meanwhile, spiced fish had the highest mean gross

margin/kg, net return/kg and marketing margin of ₦1,686.29±564.52, ₦1,683.11±561.94 and

₦1,850.00±565.69 respectively while the highest mean marketing efficiency of 23.41±23.33 was

recorded in dried fish product produced by fish processors along Nigeria-Benin border. It should

be noted that fried fish had the least mean marketing margin and marketing efficiency of

₦75,008.78±16,928.28 and 6.22±2.40 respectively. Significant difference (P<0.05) existed in the

mean values of gross margin/kg, net return/kg and marketing margin/kg of the processed fish

products marketed by fish processors in the study area.

4.2.7 Average quantities, costs, profitability indices and marketing efficiency of dried fish

products produced by respondent fish processors in Nigeria States along Nigeria-Benin

Border

The results presented in Table 4.22 indicated that in Niger State, the fish processors had the

highest mean monthly dried fish production of 282.92±188.33kg while respondents from Lagos

State had the least mean monthly production of 62.66±31.65kg of dried fish. The mean monthly

quantities of dried fish produced by the respondent fish processors in the sampled States along

Nigeria-Benin border significantly (P<0.05) vary.

Respondent fish processors in Lagos State had the highest mean buying price of fresh fish

processed to dried fish and selling price of the dried product of ₦683.75±10.61/kg and

₦3,216.25±56.80/kg respectively compared to respondents in Niger State that had the least mean

buying and selling prices of ₦498.42±66.49/kg and ₦2,698.45±159.36/kg respectively.

Meanwhile, the highest mean purchase cost and marketing cost of ₦497,478.89±297,776.08 and

₦39,117.87±20,693.15 respectively were recorded by respondents in Kebbi State while those in

Lagos and Ogun States had the least mean purchase cost and marketing cost of

₦142,610±71,412.35 and ₦13,683.07±4,431.51 respectively. The prices, fixed, purchase,

operational and marketing costs associated with the production of value added dried fish

significantly vary (P<0.05) among the respondents in the sampled States along Nigeria-Benin

border.

66

Table 4.22: Mean quantities, costs, profitability indices and marketing efficiency of dried fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin Border.

Variables Kebbi Ogun Lagos Kwara Niger Oyo



256.38ab 148.69 131.25bc 8.38 62.66c 31.65 92.93c 39.23 282.92a 188.33 73.00c 12.04

Buying Price (₦/kg) 576.67b 25.82 552.50bc 37.75 683.75a 10.61 505.71d 7.87 498.42d 66.49 496.98d 27.68

Selling Price (₦/kg) 2825.00c 27.39 3175.00ab 86.60 3216.25a 56.80 3190.00ab 147.76 2698.45c 159.36 3054.00b 102.86

Purchase Cost (₦) 497478.89a 297776.08 241233.33bc 14788.23 142610c 71412.35 156371.43c 65465.87 447568.03ab 276449.18 121412.67c 23718.65

Other Operational Cost (₦) 4691.00bc 1166.61 4345.81bc 4752.16 7307.25abc 2781.58 826.67c 201.33 10563.14ab 5396.26 11743.75a 9214.35

Total Marketing Cost (₦) 39117.87a 20693.15 13683.07b 4431.51 15884.13b 2858.97 19704.69b 6122.74 23283.49b 12079.67 24532.87b 8166.38

Total Variable Cost (₦) 540505.93a 317328.24 259262.21bc 10411.48 165801.38c 73947.75 176430.40c 62855.35 481414.66ab 280083.17 155340.53c 31644.78

Total Fixed Cost (Depreciated) (₦) 697.76b 333.01 712.17b 245.07 1717.35a 1387.45 932.10ab 223.79 353.57b 349.57 900.00ab 884.2

Total Cost of Value-addition (₦) 541203.69a 317202.97 259974.38bc 10424.35 167518.73c 75091.4 177362.51c 62825.69 481768.23ab 280305.51 156240.53c 32077.02

Total Revenue (₦) 724665.00a 422458.21 416850.00ab 30948.18 200628.75b 98044.17 300408.57b 135059.42 740799.86a 465625.51 223460,00b 41959

Gross Margin (₦) 184159.07ab 107947.71 157587.79ab 25203.36 34827.37b 24318.86 123978.17ab 73638.84 259385.20a 217151.73 68119.47b 26401.12

Gross Margin/kg (₦/kg) 709.33cd 96.03 1195.77ab 136.21 497.13d 204.29 1231.18a 339.63 836.17c 263.35 930.02bc 267.47

Net Return (₦) 183461.31ab 108143.72 156875.63ab 25183.41 33110.02b 23250.44 123046.06ab 73635.41 259031.63a 216850.9 67219.47b 27058.21

Net Return/kg (₦/kg) 704.09cd 99.04 1190.31ab 135.92 468.23d 220.40 1219.31a 343.23 834.87c 263.5 917.44bc 276.76

Marketing Margin (₦) 227186.11ab 125933.57 175616.67ab 25240.83 58018.75b 26862.11 144037.14ab 70085.19 293231.83a 222497.43 102047.33b 20979.15

Marketing Margin/kg (₦/kg) 902.78b 86.55 1333.33a 122.47 937.08b 70.29 1504.29a 164.55 1037.04b 213.26 1397.39a 138.53

Marketing Efficiency 18.86a 8.52 33.36a 11.95 12.37a 4.42 17.22a 9.77 36.69a 35.84 10.07a 4.65


67

In Niger State, the highest mean monthly revenue of ₦740,799.86±465,625.51 was generated

from the sales of dried fish while fish processors in Lagos State had the least monthly revenue of

₦200,628.75±98,044.17. Furthermore, respondent fish processors in Kwara State had the highest

mean gross margin/kg, net return/kg and marketing margin/kg of ₦1,231.18±339.63,

₦1,219.31±343.23 and ₦1,504.29±164.55 respectively whereas in Lagos State the least mean

gross margin/kg and net return/kg of ₦497.13±204.29 and ₦468.23±220.40 respectively were

recorded. The statistical analysis indicated that there exist significant difference in the total

monthly revenue, gross margin, net return, marketing margin, gross margin/kg, net return/kg and

marketing margin/kg profitability indices Although there was no significant difference (P>0.05)

in the mean marketing efficiency of dried fish product in the sampled States, the highest and the

least efficiency of 36.69±35.84 and 10.07±4.65 were recorded in Niger and Oyo State

respectively.

4.2.8 Average quantities, costs, profitability indices and marketing efficiency of Smoked

fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin

Border

Indicated in Table 4.23 are the average quantities, costs, profitability indices and marketing

efficiency of Smoked fish products produced by respondent fish processors in Nigeria States

along Nigeria-Benin border. The highest mean quantity of smoked fish of 382.46±390.53kg were

produced by respondent fish processors from Niger State as the least mean quantity of

120.40±76.2kg were produced by fish processors from Oyo State. Significant difference

(P<0.05) was observed in the mean monthly quantity of smoked fish produced by the respondent

fish processors along Nigeria-Benin border during the period of this study.

In the course of the study, it was observed that the highest mean buying price of processed fresh

fish and selling price of value-added smoked fish of ₦650.00±35.20/kg and ₦3,315.31±89.91/kg

respectively were recorded in Lagos State whereas Oyo and Kebbi States had the least mean

buying price of processed fresh fish and selling price of the fish products of ₦485.49±27.96/kg

and ₦2,811.29±99.76/kg respectively. In similar context, significant difference (P<0.05) existed

in the prices of the fish products among the sampled States along Nigeria-Benin border.

68

Table 4.23: Mean quantities, costs, profitability indices and marketing efficiency of smoked fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin Border.

Variables Kebbi Ogun Lagos Kwara Niger Oyo



309.23ab 332.68 196.03bc 165.13 348.93a 260.58 251.86abc 212.67 382.46a 390.53 120.40c 76.20

Buying Price (₦/kg) 579.03b 21.81 530.00c 38.06 650.00a 35.20 508.29d 9.54 518.81cd 45.60 485.49e 27.96

Selling Price (₦/kg) 2811.29d 99.76 3211.67bc 143.65 3315.31a 89.91 3164.00c 111.86 2729.05e 197.71 3268ab 65.57

Purchase Cost (₦) 595704.79abc 640918.04 344510.56cd 288852.6 736098.44a 527254.00 426876.19bcd 361879.06 636521.32ab 644488.34 196073.14e 128999.70

Other Operational Cost (₦) 7311.68c 7172.93 9280.00bc 9745.83 25713.81a 17796.27 6777.14c 6293.30 14559.95b 8084.64 7275.68c 7981.39

Total Marketing Cost (₦) 37944.15ab 28516.91 28310.03abc 20066.79 41043.03a 22814.34 26134.09bc 7957.45 37275.98ab 39596.65 18974.08c 5711.19

Total Variable Cost (₦) 639546.37bcd 670184.75 382100.59cd 316502.9 802855.28a 566254.60 459040.74bcd 371472.13 688357.25ab 678305.63 222322.90d 136934.50


950.70bc 941.79 1373.11b 1081.03 3926.85a 2231.25 679.52c 329.62 566.94c 882.25 602.85c 640.33


640467.36abc 670778.36 383473.70cd 316793.40 806782.13a 566358.70 459720.26bcd 371453.77 688924.19ab 679015.40 222925.74d 137143.90

Total Revenue (₦) 877874.38ab 960223.89 629913.33bc 535223.40 1161303.80a 876959.80 794125.14abc 663676.53 1034770.90ab 1083393.90 394162.88c 253878.60

Gross Margin (₦) 238328.00b 297733.06 247812.74ab 224257.40 358448.47a 315031.90 335084.40ab 293381.38 346413.61a 437160.71 171839.98b 118427.90

Gross Margin/kg (₦/kg) 682.19e 160.90 1227.69b 236.43 917.92c 195.87 1291.04b 136.86 793.87d 248.07 1405.67a 166.43

Net Return (₦) 237407.02ab 297151.08 246439.64ab 224003.30 354521.62a 315004.80 334404.88ab 293403.87 345846.67a 436669.78 171237.14b 118232.70

Net Return/kg (₦/kg) 677.97e 161.69 1217.31b 238.09 895.36c 210.48 1286.30b 138.79 792.29d 248.56 1399.79a 167.99

Marketing Margin (₦) 282169.58ab 327416.88 285402.78ab 249588.90 425205.31a 353270.80 367248.95ab 302990.45 398249.54a 463530.67 198089.74b 125759.90

Marketing Margin/kg (₦/kg)

881.18e 119.93 1445.00b 218.28 1148.65c 168.86 1469.71b 115.25 999.70d 211.73 1649.69a 119.69

Marketing Efficiency 20.86b 11.10 21.03b 6.88 25.27ab 9.26 25.23ab 12.08 26.80a 12.03 20.03b 6.06


69

With respect to the costs incurred during production of value-added smoked fish products by the

respondent fish processors in the course of the study, fish processors in Lagos State had the

highest mean purchase, marketing and total production costs of ₦736,098.44±527,254.00,

₦41,043.03±22,814.34 and ₦806,782.13±566,358.70 respectively as the least mean purchase,

marketing and total production costs of ₦196,073.14±128,999.70, ₦18,974.08±5,711.19 and

₦222,925.74± 137,143.90 respectively. The mean costs variables measured in the sampled States

were significantly different (P<0.05) as indicated in Table 4.23.

The results of profitability indices of smoked fish products produced by respondent fish

processors in the study area indicated that respondents in Lagos State had the highest mean

monthly revenue, gross margin, net return and marketing margin of ₦1,161,303.80±876,959.80,

₦358,448.47±315,031.90, ₦354,521.62±315,004.80 and ₦425,205.31± 353,270.80

respectively. Similarly, fish processors in Oyo State had the highest mean gross margin/kg, net

return/kg and marketing margin/kg of ₦1,405.67±166.43, ₦1,399.79±167.99 and

₦1,649.±119.69. Contrarily, respondent fish processors in Kebbi State had the least mean gross

margin/kg, net return/kg and marketing margin/kg of ₦682.19±160.90, ₦677.97±161.69 and

₦881.18±119.93. Although the results of the marketing efficiency analysis indicated that Niger

State had the highest marketing efficiency of 26.80±12.03, this was not significantly different

(P>0.05) from the mean values of marketing efficiency of smoked recorded in Lagos and Kwara

States.

4.2.9 Average quantities, costs, profitability indices and marketing efficiency of Fried fish

products produced by respondent fish processors in Nigeria States along Nigeria-Benin

Border

During the period of this study, respondent fish processors in Kebbi and Ogun States were

involved in fried fish production as indicated in Table 4.24. Higher buying price of

₦565.00±21.21/kg of fresh fish was recorded in Kebbi State while in Ogun State higher selling

price of ₦2,475.00±106.07 of value added fried fish products was recorded. Although higher

mean monthly quantity of fried fish were produced by fish processors in Kebbi State,

respondents in Ogun State seemed to incur higher purchasing, marketing and total production

costs. Meanwhile, in Kebbi State higher gross margin, gross margin/kg, marketing margin, net

return, net return/kg and marketing efficiency were recorded. However, this was not significantly

70

Table 4.24: Mean quantities, costs, profitability indices and marketing efficiency of fried fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin Border.

Variables Kebbi Ogun

Mean SD Mean SD

Total Quantity of Marketed Products (kg) 75.00a 14.14 62.00a 2.83

Buying Price (₦/kg) 565.00a 21.21 545.00a 63.64

Selling Price (₦/kg) 1800.00b 70.71 2475.00a 106.07

Purchase Cost (₦) 56249.95a 11198.52 82832.50a 33704.24

Other Operational Cost (₦) 2000.00a 2121.32 3350.00a 3040.56

Total Marketing Cost (₦) 20902.00a 989.95 31954.00a 18916.52

Total Variable Cost (₦) 79151.95a 10067.15 118136.50a 17828.28

Total Fixed Cost (Depreciated) (₦) 591.67a 341.77 341.62a 294.69

Total Cost of Value-addition (₦) 79743.61a 9725.38 118478.12a 17533.59

Total Revenue (₦) 135500.00a 30759.14 153600.00a 13576.45

Gross Margin (₦) 56348.05 20692 35463.50a 4251.83

Gross Margin/kg (₦/kg) 738.42a 136.65 574.15a 94.77

Net Return (₦) 55756.39a 21033.76 35121.88a 3957.14

Net Return/kg (₦/kg) 729.95a 142.81 568.53a 89.76

Marketing Margin (₦) 79250.05a 19560.62 70767.50a 20127.79

Marketing Margin/kg (₦/kg) 1050.76a 62.68 1150.01a 377.11

Marketing Efficiency 6.46a 1.17 5.98a 3.97


71

different (P>0.05) from the mean values of the same variables listed above in Ogun State which

recorded lower marketing efficiency of 5.98±3.97.

4.2.10 Average quantities, costs, profitability indices and marketing efficiency of Spiced

fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin

Border

It was only in Ogun State that respondent fish processor involved in spiced fish production. The

results of the average quantities, costs, profitability indices and marketing efficiency of spiced

fish products produced by respondent fish processors in Ogun States along Nigeria-Benin Border

are presented in Table 4.25.

4.2.11 Average quantities, costs, profitability indices and marketing efficiency of

Respondent Fish Processors in Nigeria States along Nigeria-Benin Border According Scale

of Operation

Figure 4.3 indicates the percentage of respondent fish processors according to the scale of

operation in the study area. Oyo and Niger States had the highest percentage of small and

medium scale of dried fish processors of 35.18% and 45.57% while no respondent was involved

in large scale production of dried fish in the study area. About 53.49% (highest percentage) of

small scale smoked fish was recorded in Oyo State while 32.93% (highest percentage) of large

scale smoked fish production was recorded in Lagos State. In Kwara State majority of the

respondents of 49.79% were involved in medium scale smoked fish production. As observed in

this study both fried and spiced fish processors operated at small scale level of production. In

Ogun State 19.33% of the respondent involved in spiced fish production while the highest

percentage of respondents (0.89%) involved in fried fish production was recorded in Ogun State.

4.2.12 Average quantities, costs, profitability indices and marketing efficiency of

Respondent Fish Processors in Nigeria States along Nigeria-Benin Border According to

Scale of Operation

Presented in Table 4.26 and 4.27 are the average quantities, costs, profitability indices and

marketing efficiency of respondent fish processors involved in dried and smoked fish production

72

Table 4.25: Mean quantities, costs, profitability indices and marketing efficiency of spiced fish products produced by respondent fish processors in Nigeria States along Nigeria-Benin Border.

Variables Ogun

Mean SD

Total Quantity of Marketed Products (kg) 141.67 58.92

Buying Price (₦/kg) 550.00 0.00

Selling Price (₦/kg) 2400 565.69

Purchase Cost (₦) 77915.75 32407.76

Other Operational Cost (₦) 6717.51 5250.00

Total Marketing Cost (₦) 17907.32 2762.93


Total Fixed Cost (Depreciated) (₦) 375 176.78


Total Revenue (₦) 323330 61277.87

Gross Margin (₦) 222256.94 19389.67

Gross Margin/kg (₦/kg) 1686.29 564.52

Net Return (₦) 221881.94 19566.44

Net Return/kg (₦/kg) 1683.11 561.94

Marketing Margin (₦) 245414.25 28870.11

Marketing Margin/kg (₦/kg) 1850 565.69


73

Figure 4.3: Percentage of respondent fish processors along Nigeria-Benin Border according to scale of operation

0% 20% 40% 60% 80% 100%

Kebbi

Ogun

Lagos

Kwara

Niger

OyoS

am

ple

d S

tate

sDried fish: Small scale

Dried fish: Medium scale

Dried fish: Large scale

Smoked fish: Small scale

Smoked fish: Medium scale

Smoked fish: Large scale

Fried fish: Small scale

Fried fish: Medium scale

Fried fish: Large scale

Spiced fish: Small scale

Spiced fish: Medium scale

Spiced fish: Large scale

74

Table 4.26: Mean quantities, costs, profitability indices and marketing efficiency of respondent dried fish processors according to their scale of production in the study area.

Dried Fish Small scale Medium scale

Mean SD Mean SD


118.84b 93.44 449.14a 83.85

Buying Price (₦/kg) 559.27a 72.79 492.86b 104.04

Selling Price (₦/kg) 3027.93a 226.91 2675.00b 158.77

Purchase Cost (₦) 216707.27b 163786.11 720019.05a 128167.93

Other Operational Cost (₦) 8439.85a 6072.10 5000.00b 0.00

Total Marketing Cost (₦) 18127.18b 6197.46 47481.83a 9907.30

Total Variable Cost (₦) 241905.67b 164198.40 772500.88a 129986.53

Total Fixed Cost (Depreciated) (₦) 852.22a 889.99 745.24b 250.76

Total Cost of Value-addition (₦) 242757.89b 164066.37 773246.12a 129847.83

Total Revenue (₦) 347669.34b 235815.68 1192573.21a 182527.44

Gross Margin (₦) 105763.66b 79748.89 420072.33a 191414.30

Gross Margin/kg (₦/kg) 855.15b 347.64 907.20a 301.13

Net Return (₦) 104911.45b 79993.34 419327.10a 191307.24

Net Return/kg (₦/kg) 843.35b 354.76 905.47a 301.10

Marketing Efficiency 25.23a 22.82 26.53a 8.21

Marketing Margin/kg (₦/kg) 130962.07b 78702.24 472554.17a 183207.27

Marketing Margin (₦) 1163.71a 270.25 1032.14a 271.16


75

Table 4.27: : Mean quantities, costs, profitability indices and marketing efficiency of respondent smoked fish processors according to their scale of production in the study area.

Smoked Small scale Medium scale Large scale



119.10c 47.46 415.74b 176.78 899.00a 216.34

Buying Price (₦/kg) 547.41a 64.09 546.30a 68.19 566.25a 47.59

Selling Price (₦/kg) 3087.39a 237.05 3137.39a 248.98 3073.13a 323.66

Purchase Cost (₦) 217844.02c 91108.46 758000.94b 331233.21 1686970.83a 359304.92

Other Operational Cost (₦) 6975.84c 5539.14 16671.11b 11136.40 31855.34a 22655.13

Total Marketing Cost (₦) 20169.20c 5443.37 39738.79b 11331.10 93388.83a 29852.11

Total Variable Cost (₦) 244989.06c 94996.58 814410.84b 345681.87 1806378.20a 365008.48


1131.89c 1607.87 1719.95b 1718.12 2593.33a 1828.52


246120.95c 95133.39 816130.79b 346306.71 1808971.53a 365652.32

Total Revenue (₦) 363455.43c 136677.07 1286955.49b 494630.26 2735260.00a 589966.77

Gross Margin (₦) 118466.37c 60863.87 472544.65b 188295.63 928881.80a 335033.17

Gross Margin/kg (₦/kg) 1014.96b 353.75 1169.55a 232.78 1046.52b 303.88

Net Return (₦) 117334.47c 61116.41 470824.70b 188405.08 926288.47 334935.53

Net Return/kg (₦/kg) 1003.75b 356.25 1165.04a 234.46 1043.54ab 303.80

Marketing Efficiency 18.57b 6.54 32.25a 8.95 31.33a 10.26

Marketing Margin/kg (₦/kg) 145611.41c 62085.47 528954.55b 195884.89 1048289.17a 330526.11

Marketing Margin (₦) 1262.70ab 343.78 1316.38a 228.54 1185.62b 306.55


76

respectively according to scale of operation in the study area with significant difference (P<0.05) observed.

4.2.13 Average Quantities, Costs, Profitability Indices and Marketing Efficiency of

Different Fish Products Marketed by Respondent Fish Traders in Nigeria States along


The results presented in Table 4.28 indicated that fresh fish had the highest mean monthly

quantity of 1,251.87±895.11kg as the most traded fish product by the respondent fish traders in

the study area while smoked fish had the least mean quantity of 718.96±526.54kg which was not

significantly different (P<0.05) from the mean monthly quantities of dried and frozen fish traded

by the traders. Smoked fish products had the highest mean buying and selling prices of

₦1,493.22±252.38/kg and ₦3,044.26±342.16/kg respectively while fresh fish had the least mean

buying and selling prices of ₦494.38±42.82/kg and ₦758.05±98.41/kg respectively. The highest

mean monthly cost of purchase and marketing of ₦1,082,920.15±1,012,634.44 and

₦30,933.73±18,135.98 respectively were recorded by respondent fish traders dealing with

smoked fish products while frozen and dried fish products had the least mean monthly cost of

purchase and marketing of ₦463,736.21±421,625.94 and ₦24,499.59±7,758.13 respectively.

Smoked fish traders had the highest mean monthly revenue, gross margin/kg, net return/kg and

marketing efficiency of ₦2,196,037.50±1,677,006.52, ₦1,495.10±263.15, ₦1,492.58±263.18

and ₦71.52±32.51 respectively. Meanwhile, frozen fish traders had the least mean monthly

revenue, gross margin/kg, net return/kg and marketing efficiency of ₦683,439.66±688,835.98,

₦173.28±59.78, ₦170.68±60.24 and 22.16±10.18 respectively. There was significant variation

(P<0.05) in the mean monthly revenue, gross margin, net return and marketing efficiency of the

respondent fish traders of smoked, fresh, dried and frozen fish products in the study area.

4.2.14 Average quantities, costs, profitability indices and marketing efficiency of fresh fish

products marketed by respondent fish traders in Nigeria States along Nigeria-Benin

Border

In the fish markets along Nigeria-Benin border, it was observed that respondent fish traders in

Lagos State had the highest mean monthly quantity of fresh fish of 1,653.32±1,198.00kg while

fish traders in Kwara State marketed the least quantity of fresh fish of 597.91±426.60kg. The

buying and selling prices of fresh fish of ₦531.82±23.43 and ₦830.00±110.41 was highest in

77

Table 4.28: Mean monthly quantities, costs, profitability indices and marketing efficiency of different forms of fish products marketed by respondent fish traders in Nigeria States along Nigeria-Benin Border.

Variables Fresh Fish Smoked Fish Dried Fish Frozen Fish


Total Quantity Sold (Kg) 1251.87a 895.11 718.96b 526.54 729.87b 472.41 896.72b 937.84

Selling Price (₦/kg) 758.05c 98.41 3044.26a 342.16 2026.77b 417.27 773.45c 101.96

Buying Price (₦/kg) 494.38c 42.82 1493.22a 252.38 1407.10b 268.83 532.07c 97.63

Cost of Purchase (₦) 620484.47b 457679.52 1082920.15a 1012634.44 968459.00a 554691.31 463736.21b 421625.94

Total Fixed Cost Depreciated (₦)

1199.38ab 519.98 1350.37a 819.30 967.81a 329.69 1326.47a 613.95

Other Operational Cost (₦) 17951.56ab 15062.19 12351.62bc 10567.91 9952.90c 5438.12 20572.99a 20786.81

Total Marketing Cost (₦) 27731.63a 13604.49 30933.73a 18135.98 24499.59a 7758.13 26550.98a 12333.33

Marketing Cost/Kg (₦) 30.13b 20.90 52.77a 29.27 44.35a 22.18 45.46a 30.37

Total Variable Cost (₦) 666167.66b 483876.81 1126205.50a 1031336.77 1002911.49a 563537.09 510860.17b 454127.08

Total Production Cost (₦) 667367.04b 483965.20 1127555.87a 1031522.52 1003879.29a 563554.33 512186.64a 454265.25

Total Monthly Revenue (₦) 965672.98c 727534.07 2196037.50a 1677006.52 1418497.52b 849140.30 683439.66c 688835.98

Gross Margin (₦) 299505.32bc 275487.17 1069832.00a 722400.43 415586.03b 302867.46 172579.48c 245388.65

Gross Margin/kg (₦) 219.64c 103.06 1495.10a 263.15 558.70b 202.56 173.28c 59.78

Net Return (₦) 298305.94bc 275402.64 1068481.63a 722118.78 414618.22b 302874.71 171253.01c 245299.02

Net Return/kg (₦) 217.99c 103.60 1492.58a 263.18 556.83b 202.75 170.68c 60.24

Marketing Efficiency 32.16c 13.18 71.52a 32.51 55.81b 24.31 22.16d 10.18


78

Lagos State while respondent fish traders in Ogun and Kebbi States had the least buying and

selling prices of ₦475.682±6.78 and ₦675.24±41.06 respectively. The statistical analysis

indicated that significant differences (P<0.05) existed in the mean monthly quantities and prices

of fresh fish marketed by fish traders in the sampled States in the study area as indicated in Table

4.29.

Also presented in Table 4.29 are the costs incurred by fish traders marketing fresh fish in the

sampled States with significant differences (P<0.05) among the respondent traders. Although

fresh fish traders in Lagos State had the highest total monthly revenue of

₦1,362,114.55±970,966.43 yet the gross margin/kg and net return/kg of ₦319.72±126.93 and

₦318.76±126.96 of the respondent traders in Niger State was significantly (P<0.05) higher than

the mean gross margin/kg and net return of ₦252.97±99.36 and ₦252.26±99.38 recorded in

Lagos State. The marketing efficiency of fresh fish trader in Kebbi State (34.39±8.98) was

significantly (P<0.05) higher than the least marketing efficiency of 19.13±10.65 recorded in

Kwara State.

4.2.15 Average quantities, costs, profitability indices and marketing efficiency of smoked

fish products marketed by respondent fish traders in Nigeria States along Nigeria-Benin

Border

The results of smoked fish products marketed by fish traders in fish markets along Nigeria-Benin

border, it was observed that respondent fish traders in Ogun State had the highest mean monthly

quantity of smoked fish of 1,450.00±1,252.00kg while respondent fish traders in Oyo State had

the least quantity of smoked fish of 434.64±189.34kg. The buying and selling prices of smoked

fish of ₦1680.00±529.86and ₦3,406.67±119.42 was highest in Ogun and Kwara States

respectively while respondent fish traders in Kebbi States had the least buying and selling prices

of ₦1,142.86±134.25 and ₦2,635.71±108.82 respectively. The statistical analysis indicated that

significant differences (P<0.05) existed in the mean monthly quantities and prices of smoked fish

marketed by fish traders in the sampled States in the study area as indicated in Table 4.30.

79

Table 4.29: Mean quantities, costs, profitability indices and marketing efficiency of fresh fish products marketed by respondent fish traders in Nigeria States along Nigeria-Benin Border.

Variables Kebbi Lagos Ogun Kwara Oyo Niger


Total Quantity Sold (Kg)

852.38b 390.87 1653.32a 1198.00 1425.00a 945.01 597.91b 426.60 1384.20a 1016.11 1536.35a 599.60


675.24d 41.06 830.00a 110.41 694.55cd 74.05 736.82bc 42.69 782.40ab 51.58 816.88a 122.67

Buying Price (₦/kg)

487.14c 41.49 531.82a 23.43 475.68cd 26.78 518.18ab 19.67 497.60bc 45.94 458.33d 43.80

Cost of Purchase (₦)

415428.57b 195201.32 880578.18a 652602.36 683931.82a 467790.23 309804.55b 218404.45 694092.00a 497893.54 711444.51a 302796.77


951.27c 485.91 935.72c 410.55 1686.32a 572.30 938.27c 302.79 1326.62b 479.52 1318.61b 397.49


6819.05c 3126.96 31964.15a 23161.41 19000.00b 12600.08 9167.94c 6541.21 18363.72b 13480.36 21508.86b 8394.46

Total Marketing Cost (₦)

16109.52c 2633.86 39389.46a 22668.68 26922.78b 8446.12 21593.97bc 3538.79 25973.26b 11065.63 35413.91s 7201.95

Marketing Cost/Kg (₦)

23.02b 12.12 25.88b 4.62 27.00b 19.09 52.44a 32.53 28.04b 22.06 24.82b 5.11


438357.14b 200675.76 951931.80a 696364.34 729854.60a 488112.03 340566.45b 227750.82 738428.98a 521352.34 768367.29a 317220.32


439308.42b 200840.96 952867.52a 696417.08 731540.92a 488084.20 341504.73b 227681.40 739755.60a 521473.48 769685.90a 317334.33

Total Monthly Revenue (₦)

572095.24b 256312.10 1362114.55a 970966.43 1018636.36a 735696.26 438207.73b 304618.79 1080480.00a 790451.12 1262018.15a 539859.80

Gross Margin (₦)

133738.10c 78756.79 410182.75ab 299940.99 288781.76b 270963.44 97641.27c 79305.13 342051.02b 281982.71 493650.86s 291516.42


157.07a 67.13 252.97b 99.36 178.53b 83.10 150.86b 53.38 243.50b 49.37 319.72a 126.93

Net Return (₦) 132786.82c 78730.45 409247.03ab 299867.79 287095.44b 271040.13 96703.00c 79330.67 340724.40b 281914.53 492332.25a 291411.09

Net Return/kg (₦)

155.51c 68.06 252.26b 99.38 176.39c 83.96 148.27c 54.41 241.52b 49.01 318.76a 126.96


34.18a 11.03 33.12a 7.42 34.02a 15.52 19.13b 10.65 37.33a 15.65 34.39a 8.98


80

Table 4.30: Mean quantities, costs, profitability indices and marketing efficiency of smoked fish products marketed by respondent fish

traders in Nigeria States along Nigeria-Benin Border.




490.00d 213.43 1002.00b 303.43 1450.00a 1252.00 565.00cd 307.23 434.64d 189.34 914.92bc 521.06

Selling Price (₦/kg) 2635.71d 108.82 3055.00c 127.91 3240.00b 181.66 3406.67a 119.42 3323.57ab 242.73 2765.38d 152.57

Buying Price (₦/kg) 1142.86c 134.25 1464.00b 80.86 1680.00a 529.86 1641.67a 70.17 1627.86a 44.58 1539.15ab 164.38


556035.71c 244267.39 1458660.00b 425678.30 2697500.00a 1971274.98 916500.00bc 475669.15 706821.43bc 307241.61 1298959.23bc 708004.46


917.94b 319.79 2232.20a 1516.80 1399.84b 472.67 1621.75ab 629.64 1180.73b 490.74 1050.88b 375.72


6533.33c 2845.78 18960.00b 11407.94 29566.67a 24730.66 13183.33bc 7168.72 9562.14c 4165.38 9149.23c 5210.57


19679.52c 4796.40 56530.75a 29706.09 36942.83b 15753.74 28161.67bc 5377.03 18992.41c 5064.01 36471.15b 9827.59


46.61ab 22.03 53.88ab 16.80 31.78b 10.06 59.90ab 22.25 50.26ab 20.63 62.75a 51.99


582248.57c 249635.06 1534150.75b 450261.73 2764009.50a 2009886.31 957845.00bc 487131.53 735375.98bc 313316.90 1344579.62bc 718149.64


583166.51c 249758.75 1536382.95b 450891.89 2765409.34a 2010005.67 959466.75bc 487505.03 736556.72bc 313344.78 1345630.49bc 718091.02


1295142.86c 578493.75 3067150.00b 939221.93 4730000.00a 3151830.92 1939125.00bc 1094774.76 1456553.57c 666518.91 2555061.54bc 1501351.98

Gross Margin (₦) 712894.29c 337082.57 1532999.25ab 510676.09 1965990.50a 1239730.28 981280.00bc 610357.22 721177.59c 358015.43 1210481.92bc 877075.76


1432.91b 127.07 1516.33ab 155.18 1507.55ab 379.30 1681.76ab 158.44 1623.46ab 258.15 1230.41c 270.16

Net Return (₦) 711976.34c 336952.81 1530767.05ab 510017.13 1964590.66a 1239573.86 979658.25bc 609997.53 719996.86c 357971.20 1209431.04bc 877058.10

Net Return/kg (₦) 1430.79b 126.85 1514.12ab 154.92 1506.20ab 379.13 1678.41ab 159.15 1620.22ab 258.94 1228.30c 270.93


65.71b 23.87 61.13b 16.47 113.73a 48.86 66.25b 28.99 76.98b 30.79 68.51b 39.27


81

Table 4.30 also indicated that there was significant differences (P<0.05) in the costs incurred by

respondent fish traders in marketing smoked fish in the sampled States with the highest and the

least mean total cost of value-addition of ₦2,765,409.34±2,010,005.67 and

₦583,166.51±249,758.75 recorded in Ogun and Kebbi States respectively. Even though

respondent fish traders in Ogun State had the highest total monthly revenue of

₦4,730,000.00±3,151,830.92 yet the highest mean gross margin/kg and net return/kg of

₦1,681.76±158.44 and ₦1,678.41±159.15 were accounted for in Kwara State at significant level

less than 0.05. The highest and the least marketing efficiency of smoked fish trader of

113.73±48.56 and 61.13±16.47 were recorded in Ogun and Lagos States respectively at P<0.05.

4.2.16 Average quantities, costs, profitability indices and marketing efficiency of dried fish

products marketed by respondent fish traders in Nigeria States along Nigeria-Benin

Border

The results of dried fish products marketed by fish traders in fish markets along Nigeria-Benin

border as presented in Table 4.31 indicated that respondent fish traders in Niger State had the

highest mean monthly quantity of dried fish of 1,190.57±404.46kg while respondent fish traders

in Ogun State had the least quantity of dried fish of 335.00±162.63kg. The buying and selling

prices of dried fish of ₦1,928.00±54.04 and ₦2,886.00±41.59 respectively was highest in Lagos

States while respondent fish traders in Kebbi and Kwara States had the least buying and selling

prices of ₦1,207.14±145.57 and ₦1,768.75±121.59 respectively. The statistical analysis

indicated that significant differences (P<0.05) existed in the mean monthly quantities and prices

of dried fish marketed by fish traders in the sampled States in the study area as indicated in Table

4.31.

Also indicated in Table 4.31 was significant differences (P<0.05) in the costs incurred by

respondent fish traders in marketing dried fish in the sampled States with the highest and the

least mean total cost of value-addition of ₦912,375.04±521,159.45 and

₦561,593.91±241,083.34 recorded in Lagos and Ogun States respectively. Respondent fish

traders in Niger and Ogun State had the highest and the least total monthly revenue of

₦2,229,909.00±759,330.10 and ₦669,500.00±262,336.62 respectively while the highest and the

least mean gross margin/kg and net return/kg of ₦878.17±81.23 and ₦350.72±104.83; and

876.20±81.55 and 347.68±105.35 were accounted for in Lagos and Ogun States respectively at

82

Table 4.31: Mean quantities, costs, profitability indices and marketing efficiency of dried fish products marketed by respondent fish

traders in Nigeria States along Nigeria-Benin Border.




965.71ab 493.35 456.40bc 260.26 335.00c 162.63 477.50bc 301.74 380.00bc 56.57 1190.57a 404.46

Selling Price (₦/kg) 1778.57c 111.27 2886.00a 41.59 2050.00c 212.13 1768.75d 121.59 2300.00b 70.71 1871.43d 48.80

Buying Price (₦/kg) 1207.14c 145.57 1928.00a 54.04 1600.00b 70.71 1316.25c 29.73 1475.00b 106.07 1264.29c 113.85


1137642.86ab 527169.86 879480.00ab 508848.14 530250.00b 236527.22 626637.50b 390199.32 557500.00b 43133.51 1496104.14a 509631.65


825.25ab 238.97 729.04b 348.89 1060.66ab 668.10 1037.81ab 371.86 1281.89a 0.00 1084.64ab 200.20


11588.57a 5920.21 12170.67a 6940.24 7150.00a 3889.09 10505.00a 6638.39 6333.33a 942.81 7937.12a 2696.43


23001.43b 7296.68 19995.33b 5432.25 23133.25b 1.06 21647.92b 3683.72 19235.42b 389.50 34368.56a 7636.41


26.89b 9.94 53.16ab 22.90 78.28a 38.00 52.65ab 15.14 51.26ab 8.66 34.37b 21.50


1172232.86ab 539473.89 911646.00ab 521098.54 560533.25b 240415.24 658790.42b 400351.31 583068.75b 43686.82 1538409.83a 511899.46


1173058.10ab 539291.58 912375.04ab 521159.45 561593.91b 241083.34 659828.23b 400572.37 584350.64b 43686.82 1539494.47a 511943.19


1703857.14ab 828888.30 1323112.00ab 768723.36 669500.00b 262336.62 842312.50b 535414.19 872000.00b 103237.59 2229909.00a 759330.10

Gross Margin (₦) 531624.29ab 318800.04 411466.00abc 248522.43 108966.75c 21921.37 183522.08bc 139336.10 288931.25bc 59550.77 691499.17a 281927.69


532.53bc 97.91 878.17a 81.23 350.72d 104.83 377.85cd 111.28 757.07a 44.01 566.10b 132.31

Net Return (₦) 530799.04ab 318971.12 410736.96abc 248437.07 107906.09c 21253.27 182484.27bc 139140.21 287649.36bc 59550.77 690414.53a 281854.80

Net Return/kg (₦) 531.35bc 98.32 876.20a 81.55 347.68d 105.35 375.37cd 111.41 753.66a 44.52 565.08b 132.45


72.10a 19.46 61.54abc 22.28 28.94c 11.34 36.88bc 14.59 45.40abc 6.29 67.70ab 26.71


83

significant level less than 0.05. The highest and the least marketing efficiency of dried fish trader

of 72.10±19.46 and 28.94±11.34 were recorded in Kebbi and Ogun States respectively at

P<0.05.

4.2.17 Average quantities, costs, profitability indices and marketing efficiency of frozen

fish products marketed by respondent fish traders in Nigeria States along Nigeria-Benin

Border

The results of frozen fish products marketed by fish traders in fish markets along Nigeria-Benin

border as presented in Table 4.32 indicated that respondent fish traders in Lagos State had the

highest mean monthly quantity of frozen fish of 2,900.00±1969.24kg while respondent fish

traders in Kebbi State had the least quantity of dried fish of 225.00±106.07kg. The buying and

selling prices of frozen fish of ₦667.14±58.51 and ₦885.71±114.43 respectively was highest in

Oyo States while respondent fish traders in Lagos State had the least buying and selling prices of

₦430.00±26.46 and ₦700.00±50.00 respectively. The statistical analysis indicated that

significant differences (P<0.05) existed in the mean monthly quantities and prices of frozen fish

marketed by fish traders in the sampled States along Nigeria-Benin border.

Also indicated in Table 4.32 was significant differences (P<0.05) in the costs incurred by

respondent fish traders in marketing frozen fish in the sampled States with the highest and the

least mean total cost of value-addition of ₦1,392,581.26±957,029.02 and

₦124,716.67±39,178.43 recorded in Lagos and Kebbi States respectively. Respondent fish

traders in Lagos and Kebbi State had the highest and the least total monthly revenue of

₦2,093,833.33±1,496,089.43 and ₦180,000.00±63,639.61 respectively while the highest and the

least mean gross margin/kg of ₦227.88±38.97 and ₦144.40±10.99 were accounted for in Lagos

and Kwara States respectively at significant level less than 0.05. The highest and the least

marketing efficiency of frozen fish trader of 37.67±12.91 and 14.96±6.10 respectively were

recorded in Lagos and Kebbi States respectively at P<0.05.

84

Table 4.32: Mean quantities, costs, profitability indices and marketing efficiency of frozen fish products marketed by respondent fish traders in Nigeria States along Nigeria-Benin Border.

Variables Kebbi Oyo Ogun Kwara Lagos

Mean SD Mean SD Mean SD Mean SD Mean SD

Total Quantity Sold (Kg) 225.00b 106.07 799.29b 233.46 665.33b 424.08 640.00b 268.70 2900.00a 1969.24

Selling Price (₦/kg) 825.00ab 106.07 885.71a 114.43 728.67b 62.78 775.00ab 35.36 700.00b 50.00

Buying Price (₦/kg) 505.00bc 63.64 667.14a 58.51 487.33bc 57.00 575.00b 35.36 430.00c 26.46

Cost of Purchase (₦) 110250.00b 39244.43 539121.43b 165685.81 326266.67b 213390.48 363250.00b 131875.41 1277833.33a 887346.09


791.67a 58.93 1339.48a 695.29 1415.71a 693.72 1064.25a 119.15 1381.26a 172.11

Other Operational Cost (₦) 1500.00b 707.11 22073.81b 5733.53 14806.67b 9061.24 12800.00b 5374.01 63800.00a 43323.25

Total Marketing Cost (₦) 12175.00c 714.18 28931.19b 3981.10 23452.67bc 6148.64 21310.00bc 2531.44 49566.67a 26331.79

Marketing Cost/Kg (₦) 61.72a 32.27 39.60a 14.42 52.41a 37.52 35.60a 10.99 20.12a 6.81

Total Variable Cost (₦) 123925.00b 39237.36 590126.43b 173026.60 364526.00b 227839.03 397360.00b 139780.87 1391200.00a 956984.54


124716.67b 39178.43 591465.91b 173279.04 365941.71b 228151.97 398424.25b 139661.72 1392581.26a 957029.02

Total Monthly Revenue (₦) 180000.00b 63639.61 713107.14b 224671.14 480266.67b 304040.58 491250.00b 185615.53 2093833.33a 1496089.43

Gross Margin (₦) 56075.00b 24402.26 122980.71b 80468.08 115740.67b 82648.89 93890.00b 45834.66 702633.33a 548076.59

Gross Margin/kg (₦) 251.62a 10.16 150.87b 84.63 166.22b 43.65 144.40b 10.99 227.88a 38.97

Net Return (₦) 55283.33b 24461.18 121641.23b 80279.10 114324.96b 82343.15 92825.75b 45953.81 701252.07a 548070.72

Net Return/kg (₦) 247.59a 8.00 149.12b 84.64 162.97ab 44.88 142.53b 11.96 227.04ab 39.55

Marketing Efficiency 14.96b 6.10 24.56ab 7.55 18.83b 8.95 22.70ab 6.01 37.67a 12.91


85

4.3 Inter-regional Trade Flow of Fish Products along Nigeria-Benin Border

4.3.1 Trade flow of smoked fish products produced and marketed by respondent fish

processors in Nigeria-Benin border during the period of study.

The analysis results of trade flow of fish products along Nigeria-Benin border indicated that

about 150.88±97.21kg (1.29% of the total smoked fish processed by the fish processors in the

study area) were produced from fresh fish imported into Nigerian fish market through inter-

regional trade across Nigeria-Benin border by the fish processors from Ogun State (see Tables

4.33 and 4.34) while other fish products were not involved in inter-regional trade during the

period of study as indicated by the respondents. It should be indicated that significant difference

(P<0.05) was recorded only in the selling prices of the smoked fish products produced from fish

products supplied through intra-state (₦3240.38±70.74) and inter-regional (₦3025.00±322.75)

trade in Ogun State (Table 4.34). Although the buying prices, costs, revenue and other

profitability indices of smoked fish produced from fish supplied through intra-state trade was

higher than those from inter-regional, there was no significant difference (P>0.05) in the mean

values of the variables listed above.

It should be noted that 1.05% (246.00±246.07kg) of the total smoked fish processed by the

respondent fish processor were exported in inter-regional trade across Nigeria-Benin border as

presented in Table 4.35. Meanwhile exportation of smoked fish through the inter-regional trade

was only observed among smoked fish processors in Lagos State through the Seme border. The

results of the smoked fish sales in Lagos State indicated that 59.12% (355.79±264.04kg) and

40.88% (246.00±246.07) of the total smoked fish produced by the fish processor were involved

in intra- and inter-regional trade respectively. All the variables measured except the prices and

marketing efficiency of the smoked fish involved in intra-state trade were higher than those of

the inter-regional trade with no significant differences (P>0.05) observed (see Table 4.35).

Similarly, majority 66.34% (177.34±156.10kg) of the total dried fish produced by the respondent

fish processors was marketed through the intra-state trade while 33.66% (90.00±36.37kg) of

dried fish were traded through inter-regional trade across Nigeria-Benin border (Table 4.36).

Meanwhile in Lagos State inter-regional trade of dried fish existed, the total quantity of dried

fish, 90.00±36.37kg (66.05%), traded by the respondent fish processors

86

Table 4.33: Pooled Trade flow of smoked fish products produced and marketed by respondent fish processors in Nigeria-Benin border during the period of study.

Variables Trade Flow (Supply of Processed Raw Fish) Trade Flow (Sales of Fish Products)

Intra-state Trade Inter-Regional Trade Sig.-value




272.93 268.42 150.88 97.21 0.37 270.39 267.11 246.00 246.07 0.90

Buying Price (₦/kg) 549.66 64.01 515.00 50.00 0.28 547.62 63.08 655.00 35.36 0.02

Selling Price (₦/kg) 3101.12 247.61 3025.00 322.75 0.55 3096.14 248.18 3375.00 106.07 0.12

Purchase Cost (₦) 502965.76 499502.01 259762.50 162634.33 0.33 497047.15 496856.13 522600.00 508268.35 0.94

Other Operational Cost (₦) 11962.87 12590.95 7287.50 3898.37 0.46 11745.94 12450.89 21160.00 15330.08 0.29

Total Marketing Cost (₦) 31974.64 23952.66 23964.82 9345.63 0.51 31833.57 23841.32 27945.23 15316.72 0.82

Total Variable Cost (₦) 546714.06 527825.02 291014.81 175089.70 0.34 540440.50 525019.68 571705.23 538915.15 0.93


1434.72 1726.92 945.81 514.14 0.57 1404.23 1702.91 3063.89 2078.10 0.17

Total Cost of Value-addition (₦) 548148.78 528404.73 291960.62 174663.40 0.34 541844.73 525609.93 574769.12 536837.05 0.93

Total Revenue (₦) 837306.89 806526.94 450700.00 297469.09 0.34 828193.36 802191.49 843300.00 856589.15 0.98

Gross Margin (₦) 290592.83 297665.54 159685.19 144553.67 0.38 287752.86 296189.71 271594.77 317674.01 0.94

Gross Margin/kg (₦/kg) 1058.52 323.94 1078.47 496.01 0.90 1060.64 327.09 916.89 374.19 0.54

Net Return (₦) 289158.11 297309.98 158739.38 144942.50 0.38 286348.63 295820.70 268530.89 319752.11 0.93

Net Return/kg (₦/kg) 1049.88 326.72 1068.71 493.64 0.91 1052.27 329.31 883.51 416.03 0.47

Marketing Efficiency 23.48 10.01 17.74 4.90 0.26 23.32 9.92 25.63 16.61 0.75

Marketing Margin/kg (₦/kg) 334341.14 322647.86 190937.50 152254.76 0.38 331146.21 321004.25 320700.00 348320.80 0.96

Marketing Margin (₦) 1268.93 311.11 1308.33 487.34 0.81 1270.76 315.45 1191.67 223.92 0.73

87

Table 4.34: Trade flow of smoked fish products produced and marketed by respondent fish processors in Ogun State along Nigeria-Benin border during the period of study.

Smoked Trade Flow (Supply of Processed Raw Fish)


Mean SD Mean SD

Total Quantity of Marketed Products (kg) 202.98 173.56 150.88 97.21 0.566

Buying Price (₦/kg) 532.31 36.58 515.00 50.00 0.407

Selling Price (₦/kg) 3240.38 70.74 3025.00 322.75 0.003

Purchase Cost (₦) 357548.72 303785.48 259762.50 162634.33 0.538

Other Operational Cost (₦) 9586.54 10374.08 7287.50 3898.37 0.668

Total Marketing Cost (₦) 28978.53 21287.03 23964.82 9345.63 0.650


Total Fixed Cost (Depreciated) (₦) 1438.84 1135.86 945.81 514.14 0.405


Total Revenue (₦) 657484.62 561916.74 450700.00 297469.09 0.482

Gross Margin (₦) 261370.83 233230.98 159685.19 144553.67 0.408

Gross Margin/kg (₦/kg) 1250.65 176.67 1078.47 496.01 0.180

Net Return (₦) 259931.99 232948.37 158739.38 144942.50 0.410

Net Return/kg (₦/kg) 1240.17 180.10 1068.71 493.64 0.185


Marketing Margin/kg (₦/kg) 299935.90 260446.76 190937.50 152254.76 0.426

Marketing Margin (₦) 1466.03 152.71 1308.33 487.34 0.183

88

Table 4.35: Pooled Trade flow of dried fish products produced and marketed by respondent fish processors in Nigeria-Benin border

during the period of study.

Variables Trade Flow (Sales of Fish Products)


Mean SD Mean SD


177.34 156.10 90.00 36.37 0.34

Buying Price (₦/kg) 539.09 75.19 680.00 0.00 0.00

Selling Price (₦/kg) 2956.79 254.69 3176.67 63.51 0.15

Purchase Cost (₦) 303568.35 250705.79 204000.00 82445.62 0.50




Total Fixed Cost (Depreciated) (₦) 694.96 503.04 2751.85 1872.29 0.00


Total Revenue (₦) 496529.46 395398.96 284690.00 111389.67 0.37

Gross Margin (₦) 163194.66 157764.80 54260.22 27783.12 0.24

Gross Margin/kg (₦/kg) 883.59 341.24 587.87 64.97 0.15

Net Return (₦) 162499.71 157803.67 51508.37 25928.03 0.24

Net Return/kg (₦/kg) 874.75 346.86 559.13 56.80 0.13


Marketing Margin/kg (₦/kg) 192961.11 163883.13 80690.00 29008.10 0.25

Marketing Margin (₦) 1159.81 273.39 910.00 63.51 0.13

89

Table 4.36: Trade flow of dried and smoked fish products produced and marketed by respondent fish processors in Lagos State along

Nigeria-Benin border during the period of study.

Variables Dried Smoked

Trade Flow (Sales of Fish Products) Sig.-value

Trade Flow (Sales of Fish Products) Sig.-value

Intra-state Trade Inter-Regional Trade Intra-state Trade Inter-Regional Trade Mean SD Mean SD Mean SD Mean SD Total Quantity of Marketed Products (kg)

46.26 13.95 90.00 36.37 0.05 355.79 264.04 246.00 246.07 0.57

Buying Price (₦/kg) 686.00 13.42 680.00 0.00 0.48 649.67 35.77 655.00 35.36 0.84 Selling Price (₦/kg) 3240.00 41.83 3176.67 63.51 0.13 3311.33 89.39 3375.00 106.07 0.34 Purchase Cost (₦) 105776.00 31676.44 204000.00 82445.62 0.05 750331.67 533767.45 522600.00 508268.35 0.56 Other Operational Cost (₦) 6891.60 3311.23 8000.00 2000.00 0.62 26017.40 18136.14 21160.00 15330.08 0.72 Total Marketing Cost (₦) 14356.74 1749.43 18429.78 2633.28 0.04 41916.21 23144.78 27945.23 15316.72 0.41 Total Variable Cost (₦) 127024.34 32270.80 230429.78 83855.49 0.04 818265.28 573421.65 571705.23 538915.15 0.56 Total Fixed Cost (Depreciated) (₦)

1096.65 576.04 2751.85 1872.29 0.10 3984.38 2262.32 3063.89 2078.10 0.58


128120.99 32024.20 233181.63 85653.59 0.04 822249.66 573573.05 574769.12 536837.05 0.56

Total Revenue (₦) 150192.00 46246.86 284690.00 111389.67 0.05 1182504.00 888457.23 843300.00 856589.15 0.61 Gross Margin (₦) 23167.66 13994.58 54260.22 27783.12 0.07 364238.72 319460.12 271594.77 317674.01 0.69 Gross Margin/kg (₦/kg) 442.69 247.07 587.87 64.97 0.37 917.99 190.21 916.89 374.19 0.99 Net Return (₦) 22071.01 14272.00 51508.37 25928.03 0.08 360254.34 319377.18 268530.89 319752.11 0.70 Net Return/kg (₦/kg) 413.69 271.07 559.13 56.80 0.41 896.15 203.41 883.51 416.03 0.94 Marketing Efficiency 10.74 4.27 15.09 3.77 0.20 25.25 9.06 25.63 16.61 0.96 Marketing Margin/kg (₦/kg) 44416.00 15007.80 80690.00 29008.10 0.05 432172.33 358357.41 320700.00 348320.80 0.67 Marketing Margin (₦) 953.33 75.83 910.00 63.51 0.44 1145.78 169.16 1191.67 223.92 0.72

90

which was significantly higher than 46.26±13.95kg (33.95%) of dried fish marketed in intra-state

trade through the Seme Border. Details of the prices, costs, revenue, profitability indices and

marketing efficiency are presented in Table 4.36.

4.3.2 Average quantities, costs and profitability indices of fish products supplied and sold

through intra- and inter-regional trade by respondent fish traders across Nigeria-Benin

Border

The results of trade flow of fish products through the respondent fish traders along Nigeria-Benin

border indicated that dried, smoked and fresh fish were imported and exported across the border

(inter-regional trade) during the period study. As indicated in Figure 4.4 the percentage of fresh

fish and smoked fish of 65.04% (2300.00±424.26kg) and 61.01% (1088.75±292.76kg)

respectively of the total fish products were imported through inter-regional trade into the fish

market across the Nigeria-Benin border by the fish trader was much higher than 34.96%

(1236.23±891.71kg) and 38.99% (695.84±530.61kg) of fresh and smoked fish respectively

involved in intra-state trade in the study area. Reverse of the results presented earlier was

observed in the quantity of dried fish products marketed by the respondents as higher percentage

of 62.97% (749.79±480.26kg) of the total dried fish traded were marketed through intra-state

trade while the remaining percentage were involved in inter-regional trade.

According to the results presented in Tables 4.37 - 4.43 are mean quantities, costs and

profitability indices of fresh, smoked and dried fish supplied/imported and sold/exported through

intra- and inter-regional trade by respondent fish traders across Nigeria-Benin border. The mean

selling price, total marketing cost and gross margin of ₦842.50±126.06/kg,

₦47,044.79±28,569.94 and ₦608,721.87±428,717.14 of fresh fish sold through the inter-

regional trade was significantly higher (P<0.05) than mean selling price, total marketing cost and

gross margin of ₦755.49±96.92, ₦27,146.39±12,661.22 and ₦290,135.12±266,445.86 of fresh

fish traded in intra-state trade (see Tables 4.28). Similar results was also observed for smoked

and dried fish products the marketing cost of ₦24,843.61±7,824.91 of dried fish recorded in

intra-state trade was significantly higher (P<0.05) than ₦19,511.25±6,167.74 incurred in inter-

regional trade in the study area as indicated in Table 4.43.

91

Figure 4.4: Percentage of fish products traded by the respondent fish traders along within and across Nigeria-Benin border

20.00

30.00

40.00

50.00

60.00

70.00

80.00

Fresh Fish Smoked Fish Dried Fish

Per

cent

age

of F

ish

Pro

duct

s T

rade

d (%

)

Fish Products

Trade Flow

Trade Flow (Supply of Fish Products): Intra-Regional Trade

Trade Flow (Supply of Fish Products): Inter-Regional Trade

Trade Flow (Sales of Fish Products): Intra-Regional Trade

Trade Flow (Sales of Fish Products): Inter-Regional Trade

92

Table 4.37: Mean quantities, costs and profitability indices of fresh fish supplied and sold through intra- and inter-regional trade by respondent fish traders across Nigeria-Benin Border

Variables Trade Flow (Supply of Fish Products) Trade Flow (Sales of Fish Products)

Intra-state Trade Inter-Regional Trade Sig.-value Intra-state Trade Inter-Regional Trade Sig.-value


Total Quantity Sold (Kg) 1236.23 891.71 2300.00 424.26 0.10 1215.18 824.14 2462.50 2093.39 0.01 Selling Price (₦/kg) 758.92 98.89 700.00 0.00 0.40 755.49 96.92 842.50 126.06 0.08 Buying Price (₦/kg) 494.07 42.85 515.00 49.50 0.50 493.14 42.71 535.00 23.80 0.05 Cost of Purchase (₦) 611909.61 454700.47 1195000.00 332340.19 0.07 598847.64 410718.99 1334500.00 1166055.03 0.00 Total Fixed Cost Depreciated (₦)

1194.40 522.26 1533.07 0.00 0.36 1207.87 522.58 919.31 367.12 0.28

Other Operational Cost (₦) 17761.78 15085.53 30666.67 5656.85 0.23 17052.87 12985.22 47608.33 40472.25 0.00 Total Marketing Cost (₦) 27639.41 13668.48 33910.83 7781.71 0.52 27146.39 12661.22 47044.79 28569.94 0.00 Marketing Cost/Kg (₦) 30.36 20.97 14.68 0.68 0.29 30.39 21.15 21.36 3.72 0.40 Total Variable Cost (₦) 657310.80 481024.27 1259577.50 345778.75 0.08 643046.89 433636.41 1429153.13 1235044.19 0.00 Total Production Cost (₦) 658505.20 481108.24 1261110.57 345778.75 0.08 644254.76 433761.92 1430072.43 1234915.82 0.00 Total Monthly Revenue (₦)

956056.16 728193.66 1610000.00 296984.85 0.21 933182.01 668770.81 2037875.00 1646019.86 0.00

Gross Margin (₦) 298745.36 277447.23 350422.50 48793.90 0.79 290135.12 266445.86 608721.87 428717.14 0.02 Gross Margin/kg (₦) 220.58 103.45 156.99 50.17 0.39 218.21 103.02 266.81 107.31 0.36 Net Return (₦) 297550.96 277362.97 348889.43 48793.90 0.80 288927.25 266344.73 607802.57 428739.87 0.02 Net Return/kg (₦) 218.91 104.01 156.31 50.05 0.40 216.52 103.56 266.26 107.05 0.35 Marketing Efficiency 31.93 13.14 47.73 2.19 0.09 31.92 13.25 40.21 7.99 0.22

93

Table 4.38: Mean quantities, costs and profitability indices of smoked fish supplied and sold through intra- and inter-regional trade by

respondent fish traders across Nigeria-Benin Border

Trade Flow (Supply of Fish Products) Trade Flow (Sales of Fish Products)



Total Quantity Sold (Kg) 695.84 530.61 1088.75 292.76 0.15 691.89 533.92 1060.00 261.56 0.13

Selling Price (₦/kg) 3040.00 351.92 3112.50 85.39 0.68 3035.87 353.18 3150.00 111.80 0.48

Buying Price (₦/kg) 1494.36 259.53 1475.00 86.99 0.88 1495.86 261.34 1460.00 82.46 0.76

Cost of Purchase (₦) 1051085.47 1032596.33 1592275.00 377272.72 0.30 1046769.37 1040308.31 1538420.00 348213.77 0.30


1261.50 677.18 2772.22 1580.30 0.00 1228.62 629.00 2884.44 1391.39 0.00

Other Operational Cost (₦) 12019.69 10494.01 17662.50 11901.08 0.30 12093.81 10561.40 15600.00 11291.42 0.48


Marketing Cost/Kg (₦) 52.83 29.86 51.75 20.36 0.94 52.81 30.10 52.24 17.67 0.97

Total Variable Cost (₦) 1092319.16 1050665.80 1668386.88 395801.16 0.28 1087728.12 1058457.70 1611020.50 365989.65 0.28

Total Production Cost (₦) 1093580.66 1050795.49 1671159.10 396617.63 0.28 1088956.73 1058579.21 1613904.94 366564.25 0.28

Total Monthly Revenue (₦) 2121766.41 1690662.75 3384375.00 885142.68 0.15 2105945.24 1699460.10 3331200.00 775722.94 0.12

Gross Margin (₦) 1029447.25 717700.34 1715988.13 496461.07 0.07 1018217.12 717774.45 1720179.50 430050.04 0.04

Gross Margin/kg (₦) 1490.58 270.29 1567.45 70.22 0.58 1485.06 268.80 1621.57 135.43 0.27

Net Return (₦) 1028185.74 717508.22 1713215.90 495760.01 0.07 1016988.50 717612.67 1717295.06 429437.64 0.04

Net Return/kg (₦) 1488.06 270.31 1564.91 71.03 0.58 1482.56 268.85 1618.83 135.35 0.27


94

Table 4.39: Mean quantities, costs and profitability indices of dried fish supplied and sold through intra- and inter-regional trade by respondent

fish traders across Nigeria-Benin Border

Variables Trade Flow (Supply and Sale of Fish Products)


Mean SD Mean SD

Total Quantity Sold (Kg) 749.79 480.26 441.00 241.83 0.38

Selling Price (₦/kg) 1967.24 360.07 2890.00 14.14 0.00

Buying Price (₦/kg) 1371.38 238.55 1925.00 35.36 0.00

Cost of Purchase (₦) 976407.90 566019.93 853200.00 481115.45 0.77

Total Fixed Cost Depreciated (₦) 992.89 326.09 604.17 29.46 0.11



Marketing Cost/Kg (₦) 44.13 22.83 47.56 12.09 0.84


Total Production Cost (₦) 1012072.67 574887.78 885075.42 493702.54 0.76

Total Monthly Revenue (₦) 1428547.00 868208.59 1272780.00 692653.52 0.81

Gross Margin (₦) 417467.22 311144.23 388308.75 198921.51 0.90

Gross Margin/kg (₦) 535.80 188.39 890.77 37.40 0.01

Net Return (₦) 416474.33 311153.54 387704.58 198950.97 0.90

Net Return/kg (₦) 533.91 188.59 889.14 36.44 0.01


95

Table 4.40: : Mean quantities, costs and profitability indices of fresh fish supplied and sold

through intra- and inter-regional trade by respondent fish traders in Ogun State across Nigeria-

Benin Border

Variables Trade Flow (Supply of Fish Products)


Mean SD Mean SD


Selling Price (₦/kg) 694.00 77.83 700.00 0.00 0.92

Buying Price (₦/kg) 471.75 22.02 515.00 49.50 0.03

Cost of Purchase (₦) 632825.00 453658.35 1195000.00 332340.19 0.11

Total Fixed Cost Depreciated (₦) 1701.65 599.41 1533.07 0.00 0.70







Gross Margin (₦) 282617.69 283874.05 350422.50 48793.90 0.75

Gross Margin/kg (₦) 180.68 86.29 156.99 50.17 0.71

Net Return (₦) 280916.04 283951.09 348889.43 48793.90 0.74

Net Return/kg (₦) 178.40 87.25 156.31 50.05 0.73


96

Table 4.41: Mean quantities, costs and profitability indices of fresh fish supplied and sold

through intra- and inter-regional trade by respondent fish traders in Lagos State across Nigeria-

Benin Border

Variables Trade Flow (Sales of Fish Products)


Mean SD Mean SD


Selling Price (₦/kg) 827.22 110.50 842.50 126.06 0.81

Buying Price (₦/kg) 531.11 23.98 535.00 23.80 0.77

Cost of Purchase (₦) 779706.67 476340.37 1334500.00 1166055.03 0.13


939.37 429.35 919.31 367.12 0.93







Gross Margin (₦) 366062.94 259541.70 608721.87 428717.14 0.15

Gross Margin/kg (₦) 249.89 100.54 266.81 107.31 0.77

Net Return (₦) 365123.57 259426.95 607802.57 428739.87 0.15

Net Return/kg (₦) 249.15 100.61 266.26 107.05 0.76


97

Table 4.42: Mean quantities, costs and profitability indices of smoked fish supplied and sold through intra- and inter-regional trade by

respondent fish traders in Lagos State across Nigeria-Benin Border




Quantity of fresh fish (Kg) 944.17 322.9 1088.75 292.76 0.49 944 361.01 1060 261.56 0.58

Selling Price (/kg) 3016.67 143.76 3112.5 85.39 0.27 2960 41.83 3150 111.8 0.01

Buying Price (/kg) 1456.67 84.06 1475 86.99 0.75 1468 88.71 1460 82.46 0.89

Cost of Purchase 1369583.3 465788.41 1592275 377272.72 0.45 1378900 520141.9 1538420 348213.8 0.58

Total Fixed Cost Depreciated

1872.19 1501.33 2772.22 1580.3 0.39 1579.97 1475.48 2884.44 1391.39 0.19

Other Operational Cost 19825 12125.5 17662.5 11901.08 0.79 22320 11708.84 15600 11291.42 0.38

Total Marketing Cost 55251.67 31729.7 58449.38 31003.53 0.88 56061 35405.58 57000.5 27044.6 0.96

Marketing Cost/Kg 55.29 15.91 51.75 20.36 0.77 55.52 17.77 52.24 17.67 0.78

Total Variable Cost 1444660 496893.56 1668386.88 395801.16 0.47 1457281 554467.6 1611021 365989.7 0.62

Total Production Cost 1446532.2 497336.4 1671159.1 396617.63 0.47 1458861 555013 1613905 366564.3 0.62

Total Monthly Revenue 2855666.7 991759.03 3384375 885142.68 0.42 2803100 1099435 3331200 775722.9 0.41

Gross Margin 1411006.7 526204.7 1715988.13 496461.07 0.39 1345819 560574.3 1720180 430050 0.27

Gross Margin/kg 1482.26 192.11 1567.45 70.22 0.43 1411.1 90.32 1621.57 135.43 0.02

Net Return 1409134.5 525700.69 1713215.9 495760.01 0.39 1344239 560237.3 1717295 429437.6 0.27

Net Return/kg 1480.27 191.66 1564.91 71.03 0.43 1409.42 90.95 1618.83 135.35 0.02


98

Table 4.43: Mean quantities, costs and profitability indices of dried fish supplied and sold through intra- and inter-regional trade by

respondent fish traders in Lagos State across Nigeria-Benin Border





Total Quantity Sold (Kg) 466.67 325.32 441 241.83 0.93 466.67 325.32 441 241.83 0.931

Selling Price (₦/kg) 2883.33 57.74 2890 14.14 0.89 2883.33 57.74 2890 14.14 0.888

Buying Price (₦/kg) 1930 72.11 1925 35.36 0.94 1930 72.11 1925 35.36 0.935

Cost of Purchase (₦) 897000 633218.56 853200 481115.45 0.94 897000 633218.6 853200 481115.5 0.94


812.29 465.86 604.17 29.46 0.59 812.29 465.86 604.17 29.46 0.592

Other Operational Cost (₦) 12444.44 8675.21 11760 6448.81 0.93 12444.44 8675.21 11760 6448.81 0.931


Marketing Cost/Kg (₦) 56.9 30.39 47.56 12.09 0.72 56.9 30.39 47.56 12.09 0.718

Total Variable Cost (₦) 929762.5 648051.65 884471.25 493732.01 0.94 929762.5 648051.7 884471.3 493732 0.939

Total Production Cost (₦) 930574.79 648152.09 885075.42 493702.54 0.94 930574.8 648152.1 885075.4 493702.5 0.939


1356666.7 968382.46 1272780 692653.52 0.92 1356667 968382.5 1272780 692653.5 0.924

Gross Margin (₦) 426904.17 320699.47 388308.75 198921.51 0.89 426904.2 320699.5 388308.8 198921.5 0.892

Gross Margin/kg (₦) 869.77 110.59 890.77 37.4 0.82 869.77 110.59 890.77 37.4 0.82

Net Return (₦) 426091.88 320573.02 387704.58 198950.97 0.89 426091.9 320573 387704.6 198951 0.892

Net Return/kg (₦) 867.57 111.17 889.14 36.44 0.82 867.57 111.17 889.14 36.44 0.816


99

4.4 Scale Economies of the Fish Products Marketed Along Nigeria-Benin Border

4.4.1 Scale Economies of the Fish Products Marketed by Respondent Fish Processors


Figures 4.5 and 4.6 indicate linear relationship between total marketing cost and total monthly

quantity of processed fish products marketed by fish processors along Nigeria-Benin Border with

dried and smoked fish having positive slopes (b) values of 54.38 and 77.62 respectively at

P<0.05 with coefficient of determination (R2) of 0.704 and 0.391 respectively, whereas, fried fish

had a negative slope of 485.89 with R2 of 0.185 at P>0.05. These results indicated that scale

economies only existed in the marketing of fried fish by the fish processors along Nigeria-Benin

border during the period of study.

4.4.2 Scale Economies of the Fish Products Marketed by Respondent Fish Traders along


The results regression analysis of total marketing cost and total monthly quantity of fish products

marketed by respondent fish traders along Nigeria-Benin Border indicated that fresh, smoked,

dried and frozen had positive b-values (no scale economies) of 12.76, 21.54, 11.12 and 12.54

respectively (see Figure 4.8 - 4.11) at P<0.05 with the frozen fish model having the highest R2

value of 0.909.

Presented in Tables 4.44 – 4.49 are the linear regression estimates indicating the relationship

between total quantities sold (kg) and total marketing cost (₦) of the forms of fish marketed by

respondent fish traders in the sampled State along Nigeria-Benin border. A scale economy was

observed among the respondent dried fish traders in Ogun, Oyo and Niger States respectively as

well as frozen trader in Kebbi State.

100

Figure 4.5: Relationship between total marketing cost and total monthly quantity of dried fish

marketed by fish processors along Nigeria-Benin Border

Y = 13476.58 + 54.38X R2 = 0.419; Sig. = 0.000

101

Figure 4.6: Relationship between total marketing cost and total monthly quantity of smoked fish


Y = 11119.20 + 77.62X R2 = 0.735; Sig. = 0.000

102

Figure 4.7: Relationship between total marketing cost and total monthly quantity of fried fish


Y = 59711.37 - 485.89X R2 = 0.185; Sig. = 0.570

103

Figure 4.8: Relationship between total marketing cost and total monthly quantity of fresh fish

marketed by fish traders along Nigeria-Benin border

Y = 11763.40 + 12.76X R2 = 0.704; Sig. = 0.000

104

Figure 4.9: Relationship between total marketing cost and total monthly quantity of smoked fish


Y = 15448.30 + 21.54X R2 = 0.391; Sig. = 0.000

105

Figure 4.10: Relationship between total marketing cost and total monthly quantity of dried fish


Y = 16384.38 + 11.12X R2 = 0.458; Sig. = 0.000

106

Figure 4.11: Relationship between total marketing cost and total monthly quantity of frozen fish


Y = 15308.44 + 12.54X R2 = 0.909; Sig. = 0.000

Table 4.44: Linear regression estimates indicating the relationship between total quantities sold (kg) and total marketing cost (₦) of

the forms of fish marketed by respondent fish traders in Kebbi State

Fish Products Independent Variable Coefficients Std. Error T-value Sig. R2 Sig.

Fresh Total Quantity Sold (Kg) 6.205 0.603 10.294 0.000 0.848 0.000

(Constant) 10820.376 562.885 19.223 0.000

Smoked Total Quantity Sold (Kg) 12.102 5.466 2.214 0.047 0.290 0.047

(Constant) 13749.382 2904.805 4.733 0.000

Dried Total Quantity Sold (Kg) 12.752 3.350 3.806 .013 0.743 0.013

(Constant) 10686.451 3579.193 2.986 .031

Frozen Total Quantity of Sold (Kg) -6.733 0.000 1.000

(Constant) 13690.000 0.000

The dependent variable is Total Marketing Cost (₦)

108


the forms of fish marketed by respondent fish traders in Lagos State

Fish Products Independent Variable Coefficients Std. Error T-value Sig. R2 Sig.

Fresh Total Quantity Sold (Kg) 17.209 1.759 9.781 .000 0.827 0.000

(Constant) 10938.232 3563.984 3.069 .006

Smoked Total Quantity Sold (Kg) 80.179 19.862 4.037 .004 0.671 0.004

(Constant) -23809.093 20706.909 -1.150 .283


(Constant) 10630.375 1131.133 9.398 .003

Frozen Total Quantity of Sold (Kg) 7.668 6.812 1.126 .311 0.202 0.311

(Constant) 22802.641 5640.092 4.043 .010


109


the forms of fish marketed by respondent fish traders in Ogun State

Fish Products Independent Variable Coefficients

Std. Error T-value Sig. R2 Sig.

Fresh Total Quantity Sold (Kg) 8.334 .722 11.541 .000 0.869 0.000

(Constant) 15047.116 1226.131 12.272 .000


(Constant) 19739.086 4432.312 4.453 .021

Dried Total Quantity Sold (Kg) -0.007 0.000 1.000

(Constant) 23135.435 0.000

Frozen Total Quantity of Sold (Kg) 12.930 1.819 7.107 .000 0.795 0.000

(Constant) 14849.838 1421.561 10.446 .000


110


the forms of fish marketed by respondent fish traders in Kwara State


Std. Error t-value Sig. R2 Sig.


(Constant) 17694.433 835.412 21.180 .000


(Constant) 20040.846 2011.487 9.963 .000


(Constant) 16084.987 826.202 19.469 .000

Frozen Total Quantity of Sold (Kg) 9.421 0.000 1.000

(Constant) 15280.526 0.000


111


the forms of fish marketed by respondent fish traders in Oyo State




(Constant) 12669.210 1820.438 6.959 .000


(Constant) 14171.561 3311.832 4.279 .001

Dried Total Quantity Sold (Kg) -6.885 0.000 1.000

(Constant) 21851.875 0.000

Frozen Total Quantity of Sold (Kg) 13.363 .489 27.330 .023 0.999 0.023

(Constant) 10815.072 1621.246 6.671 .095


112

Table 4.49: : Linear regression estimates indicating the relationship between total quantities sold (kg) and total marketing cost (₦) of

the forms of fish marketed by respondent fish traders in Niger State




(Constant) 18623.081 1747.028 10.660 .000


(Constant) 26709.887 4890.813 5.461 .000

Dried Total Quantity Sold (Kg) -3.237 8.319 -.389 .713 0.290 0.713

(Constant) 38222.434 10382.076 3.682 .014


113

4.5 Production Function and Technical Efficiency of the Respondent Value-Chain

Actors along Nigeria-Benin Border

4.5.1 Model Estimation and Resource Use Efficiency of Respondent Artisanal

Fishermen

The results of the linear regression model estimation of the respondent artisanal fishermen

presented in Table 4.50 indicated that total quantity of fish catch sold (x3), selling price (x4)

and operational cost (x5) had a significant (P<0.05) regression coefficients while age (x1),

fishing experience (x2), depreciated fixed cost (x6) and marketing efficiency (x7) were not. It

should be noted that only age had a negative influence on the respondent fishermen’s revenue

(value of output) while other variables were positive. The model relationship had a significant

(P<0.05) regression determinant (R2) value of 0.922.

4.5.2 Estimation of Production Function of the Respondent Fish Farmers

The results presented in Table 4.51 are the parameters used in estimation of production

function of the producers according to Cobb-Douglas function. The regression coefficient of

the input variables (cost of fish seed, feeding, labour, depreciated fixed cost and other

operational cost) was less than a unit with positive value. The regression coefficient of the

inputs (β) were positive with cost of fish seed, feeding, labour and other operational cost

having a significant influence (P<0.05) on the output (revenue). The reliability (R2) of 0.672

of the production function was significant (P<0.05). The coefficient of returns to scale of the

input was 1.139.

4.5.3 Technical Efficiency of the Respondent Fish Farmers

The predicted technical efficiency of the respondent fish farmers along Nigeria-Benin border

ranged between 0.84 and 0.93 with an overall average efficiency of 0.88±0.02. Figure 4.12

indicates the variation in the technical efficiency of the respondent fish farmers according to

the sampled States. The highest technical efficiency of 0.90 was recorded in Kwara State

followed by 0.89 in Oyo State while Lagos State had the least value 0.86 with significant

difference of P<0.05.

114

Table 4.50: Model estimation and resource use efficiency of respondent artisanal fishermen


Model Coefficients

Std. Error t Sig.

(Constant) -134626.695 22943.006 -5.868 0.000

Age (x1) -265.383 669.323 -0.396 0.693

Fishing Experience (x2) 33.325 651.978 0.051 0.959

Total Quantity Sold (x3) 568.177 22.717 25.011 0.000

Average Selling Price (x4) 222.294 22.662 9.809 0.000

Operational Cost (x5) 1.011 0.413 2.445 0.016

Fixed Cost Depreciated (x6) 1.893 3.048 0.621 0.536

Marketing Efficiency (x7) 75.031 59.613 1.259 0.211

Dependent Variable: Revenue

115

Table 4.51: Estimation of production function of the respondent fish farmers along Nigeria-

Benin Border

Model Coefficient Std. Error t Sig.

(Constant) 1.052 1.183 0.889 0.376

Ln Cost of fish seed (β1) 0.154 0.062 2.493 0.014

Ln Other Operational Cost (β2) 0.055 0.030 1.846 0.068

Ln Cost of Feeding (β3) 0.517 0.082 6.339 0.000

Ln Cost of Labour (β4) 0.379 0.141 2.698 0.008

Ln Depreciated Fixed Cost (β5) 0.034 0.086 0.392 0.696

116

Figure 4.12: Technical efficiency of respondent fish farmers in sampled States along Nigeria-

Benin border

Note: Mean bars with the same alphabets are not significantly different (P>0.05)

bc

b

c

bc

a

d

0.83

0.84

0.85

0.86

0.87

0.88

0.89

0.90

0.91

Niger State Oyo State Kebbi State Ogun State Kwara State Lagos State

Tec

hnic

al e

ffic

ienc

y

Sampled States

117

4.5.4 Estimation of Production Function of the Respondent Fish Processors

The estimated production function analysis result presented in Table 4.52 indicated that other

operational cost and depreciated fixed cost had negative coefficients less than a unit while

purchasing, processing, total variable and production costs had positive coefficients less than

a unit. Among the input variables, only cost of processing, total variable cost had significant

effect (P<0.05) on the output (revenue) of the fish processors in the study area. The

regression determinant of the production function of 0.964 was significant (P<0.05).

4.5.5 Technical Efficiency of the Respondent Fish Processors

The technical efficiency of the respondent fish processors in the study area ranged between

0.84 and 0.93 with a mean value of 0.89±0.02. The respondent fish processors in Oyo State

had the highest mean technical efficiency of 0.91±0.01 while fish processors in Niger State

had the lowest technical efficiency of 0.89±0.02. There was a significant difference (P<0.05)

in the mean technical efficiency of the respondent fish processors in sampled States along

Nigeria-Benin border as indicated in Figure 4.13.

118

Table 4.52: Estimated production function of respondent fish processors along Nigeria-Benin

Border

Model Coefficient Std. Error T Sig.

(Constant) 0.773 0.250 3.091 0.002

Ln Purchasing Cost (β1) 0.540 0.316 1.708 0.089

Ln Other Operational Cost (β2) -0.038 0.017 -2.270 0.024

Ln Cost of Processing (β3) 0.053 0.052 1.028 0.305

Ln Total Variable cost (β4) 0.421 0.020 3.230 0.001

Ln Depreciated Fixed Cost (β5) -0.016 0.010 -1.561 0.120

Ln Total Production Cost (β6) 0.429 0.362 1.184 0.238

119

Figure 4.13: Technical efficiency of respondent fish processors in the sampled States along


Note: Mean bars with the same alphabets are not significantly different (P>0.05)

c

ab

cbc c

a

0.87

0.88

0.89

0.90

0.91

0.92

Kebbi Ogun Lagos Kwara Niger Oyo

Mea

n T

echn

ical

Eff

icie

ncy

Sampled States

120

4.6 Constraints Facing Respondent Value-Chain Actors along Nigeria-Benin Border

4.6.1 Constraints of Respondent Artisanal Fishermen along Nigeria-Benin Border

Presented in Table 4.53 are the lists of constraints facing respondent artisanal fishermen

along Nigeria-Benin border. On the list, inadequate credit accessibility was ranked fist with

the highest mean score of 2.57, followed by poor transport facilities (2nd) while inadequate

man-power ranked last with the lowest mean of 1.38.


Mean scores of constraints facing respondent fish farmers along Nigeria-Benin border are

presented in Table 4.54. High cost of fish feed had the highest mean score of 3.00 (1st rank)

followed by poor supply of electricity with mean score of 2.57 (2nd rank) while

corruption/pilfering had the least mean score of 1.31 as the least constraint (10th rank) facing

fish farmers along Nigeria-Benin border.


The results of the mean scores of constraints faced by fish processors along Nigeria-Benin

border indicate that poor transport facilities/road condition had the highest mean score of 4.12

(1st rank), followed by poor electricity supply with mean score of 3.02 (2nd rank) while

unskilled man-power had the least mean score of 1.29 (9th rank) as presented in Table 4.55.

4.6.4 Constraints of Respondent Fish Traders along Nigeria-Benin Border

The results presented in Table 4.56 indicate that the highest mean score of 2.87 (1st rank) was

recorded by inadequate credit accessibility with poor transport facilities/road condition

having the mean score of 2.84 (2nd rank) while unskilled man-power had the least mean score

of 1.61 as the 9th on the constraint ranking.

Presented in Tables 4.57 – 4.60 are the percentage of severity of the challenges faced by

respondent value-chain actors according to the sampled States along Nigeria-Benin border.

121

Table 4.53: Ranking of constraints of respondent artisanal fishermen along Nigeria-Benin

Border

Constraints Mean Score Ranking

Inadequate credit accessibility 2.57 1

Poor transport facilities/road condition 2.38 2

Lack of access to modern fishing facilities 2.23 3

Inadequate access to fishing inputs 2.05 4

Lack of storage facilities 2.00 5

Poor electricity supply 1.88 6

Difficulty access to the fishing ground 1.75 7

Drying up of rivers 1.72 8

Lack of training 1.68 9

Corruption/pilfering 1.45 10

Inadequate man-power 1.38 11

122

Table 4.54: Ranking of constraints of respondent fish farmers along Nigeria-Benin Border


High cost of fish feed 3.00 1

Poor Electricity Supply 2.57 2

Inadequate Credit accessibility 1.92 3

Lack of Training 1.72 4

Unskilled man-power 1.58 5

Poor Transport facilities/Road Condition 1.56 6

Inadequate water Availability/Supply 1.55 7

Lack of Storage facilities 1.35 8

Inadequate Land Accessibility 1.32 9

Corruption/Pilfering 1.31 10

123

Table 4.55: Ranking of constraints of respondent fish processors along Nigeria-Benin Border











124

Table 4.56: Ranking of constraints of respondent fish traders along Nigeria-Benin Border











125

Table 4.57: Severity of Constraints of Respondent Artisanal Fishermen in Sampled States


Kwara Niger Oyo




(%) Electric Supply Mild 0 0.00 2 9.09 1 4.55

Severe 2 9.09 0 0.00 2 9.09 Very severe

0 0.00 0 0.00 4 18.18

Transport/Road Condition)

Mild 1 4.55 3 13.64 2 9.09 Severe 6 27.27 0 0.00 5 22.73 Very severe

12 54.55 0 0.00 4 18.18

Corruption/Pilfering Mild 4 18.18 2 9.09 0 0.00 Severe 2 9.09 0 0.00 0 0.00 Very severe

0 0.00 0 0.00 0 0.00

Storage Mild 1 4.55 3 13.64 0 0.00 Severe 6 27.27 0 0.00 3 13.64 Very severe

4 18.18 0 0.00 5 22.73

Access to the fishing ground


0 0.00 0 0.00 2 9.09

Access to modern fishing facilities


11 0 0.00 3 13.64

Access to fishing inputs


6 27.27 0 0.00 1 4.55

Credit accessibility Mild 2 9.09 3 13.64 0 0.00 Severe 2 9.09 0 0.00 8 36.36 Very severe

7 31.82 0 0.00 7 31.82

Man-power Mild 0 0.00 3 13.64 0 0.00 Severe 2 9.09 0 0.00 5 22.73 Very severe

1 4.55 0 0.00 1 4.55

Training Mild 4 18.18 3 13.64 0 0.00 Severe 2 9.09 0 0.00 0 0.00 Very severe

3 13.64 0 0.00 1 4.55

126

Table 4.57 cont’d: Severity of Constraints of Respondent Artisanal Fishermen in Sampled States along


Variable Category

Ogun Lagos Kebbi


% Frequency Percentage


% Electric Supply Mild 4 18.18 0 0.00 1 4.55


1 4.55 0 0.00 0 0.00

Transport/Road Condition


15 68.18 3 13.64 13 59.09

Corruption/Pilfering


0 0.00 0 0.00 0 0.00


1 4.55 0 0.00 0 0.00

Access to the fishing ground


3 13.64 2 9.09 1 4.55



7 31.82 0 0.00 1 4.55

Access to fishing inputs


0 0.00 5 22.73 1 4.55


18 81.82 7 31.82 13 59.09


1 4.55 0 0.00 0 0.00


2 9.09 0 0.00 0 0.00

127

Table 4.58: Severity of Constraints of Respondent Fish Farmers in Sampled States along


Constraints Category

Kwara State Niger State Oyo State



% Frequency Percentage% Water Availability/Supply


4 18.18 0 0.00 5 22.73

Electric Supply Mild 0 0.00 15 68.18 2 9.09 Severe 1 4.55 0 0.00 4 18.18 Very severe

2 9.09 0 0.00 6 27.27



0 0.00 0 0.00 0 0.00


1 4.55 0 0.00 1 4.55


1 4.55 0 0.00 0 0.00

Land Accessibility Mild 1 4.55 15 68.18 3 13.64 Severe 1 4.55 0 0.00 1 4.55 Very severe

0 0.00 0 0.00 3 13.64


3 13.64 0 0.00 8 36.36


3 13.64 0 0.00 3 13.64


3 13.64 0 0.00 6 27.27

Marketing 22 100.00 21 95.45 20 90,91 Raw Materials

0 0.00 0 0.00 1 4.55

128

Table 4.58 cont’d: Severity of Constraints of Respondent Fish Farmers in Sampled States


Variable Category





% Water Availability/Supply


0 0.00 0 0.00 1 4.55

Electric Supply Mild 0 0.00 3 13.64 0 0.00 Severe 0 0.00 7 31.82 0 0.00 Very severe

0 0.00 9 40.91 2 9.09


Mild 0 0.00 7 31,82 1 4.55 Severe 0 0.00 10 45.45 0 0.00 Very severe

0 0.00 1 4.55 0 0.00


0 0.00 0 0.00 1 4.55

(Storage) Mild 0 0.00 8 36.36 0 0.00 Severe 0 0.00 5 22.73 1 4.55 Very severe

0 0.00 1 4.55 0 0.00

Land Accessibility Mild 0 0.00 7 31.82 0 0.00 Severe 0 0.00 2 9.09 1 4.55 Very severe

0 0.00 0 0.00 0 0.00


0 0.00 2 9.09 1 4.55


0 0.00 0 0.00 0 0.00


0 0.00 0 0.00 0 0.00

Marketing 22 100.00 22 100.00 22 100.00 Raw Materials

0 0.00 0 0.00 0 0.00

129

Table 4.59: Severity of Constraints of Respondent Fish Processors in Sampled States along


Constraint Category

Kwara State Niger State Oyo State




% Water availability

Mild 4 9.09 14 31.82 4 9.09 Severe 7 15.91 0 0.00 1 2.27 Very Severe

2 4.55 0 0.00 4 9.09

Electricity Mild 0 0.00 2 4.55 0 0.00 Severe 11 25.00 0 0.00 6 13.64 Very Severe

0 0.00 0 0.00 20 45.45

Transport Mild 3 6.82 26 59.09 7 15.91 Severe 7 15.91 1 2.27 16 36.36 Very severe

7 15.91 11 25.00 14 31.82

Corruption Mild 2 4.55 2 4.55 2 4.55 Severe 6 13.64 13 29.54 2 4.55 Very severe

0 0.00 0 0.00 1 2.27


1 2.27 4 9.09 6 13.64

Land Accessibility


0 0.00 0 0.00 0 0.00

Credit Accessibility

Mild 0 0.00 26 59.09 6 13.64 Severe 3 6.82 0 0.00 14 31.82 Very Severe

6 13.64 17 38.64 17 38.64

Manpower Mild 1 2.27 26 59.09 3 6.82 Severe 1 2.27 0 0.00 4 9.09 Very severe

0 0.00 3 6.82 1 2.27


0 0.00 4 9.09 3 6.82

Market Mild 40 90.91 43 97.73 31 70.45 severe 1 2.27 1 2.27 10 22.73 Very Severe

1 2.27 0 0.00 3 6.82

130

Table 4.59 cont’d: Severity of Constraints of Respondent Fish Processors in Sampled States


Constraint Category






Mild 12 27.27 1 2.27 22 50.00

Severe 3 6.82 0 0.00 5 11.36

Very Severe

2 4.55 0 0.00 0 0.00

Electricity Mild 6 13.64 1 2.27 11 25.00

Severe 7 15.91 7 15.91 0 0.00

Very Severe

16 36.36 26 59.09 0 0.00

Transport Mild 4 9.09 2 4.55 2 4.55

Severe 8 18.18 7 15.91 3 6.82

Very severe

16 36.36 21 47.73 19 43.18

Corruption Mild 11 25.00 0 0.00 1 2.27

Severe 4 9.09 0 0.00 17 38.64

Very severe

2 4.55 0 0.00 1 2.27

Storage Mild 9 20.45 4 9.09 9 20.45

Severe 6 13.64 4 9.09 7 15.91

Very severe

9 20.45 1 2.27 3 6.82

Land Accessibility

Mild 6 13.64 0 0.00 5 11.36

Severe 5 11.36 0 0.00 0 0.00

Very severe

2 4.55 4 9.09 0 0.00


Mild 7 15.91 4 9.09 1 2.27

Severe 8 15.91 7 15.91 10 22.73

Very Severe

26 56.82 8 18.18 19 40.91

Manpower Mild 11 25.00 12 27.27 12 27.27

Severe 2 4.55 0 0.00 0 0.00

Very severe

3 6.82 1 2.27 0 0.00

Training Mild 9 20.45 1 2.27 14 31.82

Severe 12 27.27 0 0.00 12 27.27

Very severe

9 20.45 0 0.00 2 4.55

Market 43 97.73 43 97.73 44 100.00

Mild 1 2.27 1 2.27 0 0.00

Severe 0 0.00 0 0.00 0 0.00

Very severe

0 0.00 0 0.00 0 0.00

131

Table 4.60: Severity of Constraints of Respondent Fish Traders in Sampled States along


Constraint Category

Kwara State Niger Oyo State





Mild 43 97.73 43 97.73 42 95.45

Severe 1 2.27 1 2.27 2 4.55 Very Severe

0 0.00 0 0.00 0 0.00

Electricity Mild 43 97.73 0 0.00 7 15.91 Severe 1 2.27 1 2.27 4 9.09

Very Severe

0 0.00 0 0.00 2 4.55

Transport Mild 2 4.55 0 0.00 7 15.91 Severe 3 6.82 14 31.82 2 4.55

Very severe

13 29.55 0 0.00 18 43.18

Corruption Mild 3 6.82 0 0.00 4 9.09


2 4.55 0 0.00 1 2.27

Storage Mild 6 13.64 0 0.00 6 13.64 Severe 13 29.55 1 2.27 15 34.09

Very severe

5 11.36 0 0.00 3 6.82

Land Accessibility

Mild 1 2.27 0 0.00 1 2.27 Severe 0 0.00 1 2.27 2 4.55

Very severe

0 0.00 0 0.00 0 0.00


Mild 3 6.82 0 0.00 3 6.82

Severe 3 6.82 12 27.27 8 18.18 Very Severe

2 4.55 0 0.00 14 31.82

Manpower Mild 2 4.55 1 2.27 0 0.00 Severe 1 2.27 3 6.82 1 2.27

Very severe

0 0.00 0 0.00 0 0.00

Training Mild 1 2.27 1 2.27 0 0.00 Severe 0 0.00 1 2.27 1 2.27

Very severe

0 0.00 0 0.00 12 27.27

Market

`

Mild 0 0.00 44 100.00 33 75.00


4 9.09 0 0.00 5 11.36

132

Table 4.60 cont’d: Severity of Constraints of Respondent Fish Traders in Sampled States


Constraint Category






Mild 41 93.18 41 93.18 14 31.82

Severe 4 9.09 3 6.82 5 11.36

Very Severe

9 20.45 0 0.00 4 9.09

Electricity Mild 0 0.00 4 9.09 13 29.55

Severe 9 20.45 6 13.64 2 4.55

Very Severe

15 34.09 3 6.82 0 0.00

33.00 1 2.27 0 0.00 0 0.00

Transport Mild 2 4.55 11 25.00 13 29.55

Severe 11 25.00 16 36.36 12 27.27

Very severe

12 27.27 4 9.09 7 15.91

Corruption Mild 6 13.64 1 2.27 9 20.45

Severe 4 9.09 1 2.27 12 27.27

Very severe

1 2.27 1 2.27 8 18.18

Storage Mild 2 4.55 4 9.09 7 15.91

Severe 8 18.18 3 6.82 6 13.64

Very severe

4 9.09 2 4.55 4 9.09

Land Accessibility

Mild 5 11.36 2 4.55 6 13.64

Severe 2 4.55 4 9.09 0 0.00

Very severe

0 0.00 1 2.27 2 4.55


Mild 0 0.00 5 11.36 3 6.82

Severe 3 6.82 16 36.36 7 15.91

Very Severe

36 81.82 11 25.00 15 34.09

Manpower Mild 5 11.36 15 34.09 8 18.18

Severe 4 9.09 12 27.27 3 6.82

Very severe

2 4.55 4 9.09 1 2.27

Training Mild 3 6.82 1 2.27 18 40.91

Severe 5 11.36 2 4.55 5 11.36

Very severe

7 15.91 0 0.00 0 0.00

Challenge: Others

44 100.00 43 97.73 36 81.82

0 0.00 0 0.00 8 18.18

Mild 0 0.00 0 0.00 0 0.00

Severe 0 0.00 1 2.27 0 0.00

Very severe

0 0.00 0 0.00 0 0.00

133

CHAPTER FIVE

5.0 DISCUSSION

5.1 Socio-economic Characteristics of Value-Chain Actors

5.1.1 Socio-economic Characteristics of Artisanal Fishermen

Analysis of sex of the revealed that majority of the respondent artisanal fishermen were male.

Odebiyi et al (2013) and Jim-Saiki (2016) reported that majority of the respondents are male.

The result is consistent with the findings of Inoni and Oyaide (2007), who reported

male as the dominant (72.3%) fishermen in Delta. These indicate higher participation of male

gender in artisanal fish production. According to Shettimaet al., (2014), this implies that male

dominated the fishing activities in the study area, while the female might mostly be involved

in marketing and processing of the caught fish.

Age is an important socio-economic characteristic because it affects productivity, output and

adoption of innovation. This study revealed that majority of the respondents’ ages in the

study area were within the age group of 31-40years. The implication was that the

respondents were within the productive and economic active age, and could be able to

increase fish catch and improve livelihood of the families. The finding was in

agreement with those of Olaoye (2013), who found that most of the fisher folks are in

their economic active ages to undertake strenuous task associated to the fishing enterprise

This study reveals that the peak of interest in fishing among fishermen in the study area was

11-20 years on the job. The distribution of years of fishing experience among fisher folks is

parabola with its peak at 11-15 years. The study also revealed that there was no much

disparity between each category of fishing experience which implied that the possibility of

smooth transition of the trade from one generation to another was high. This confirms the

assertion of Jim-Saiki (2016).

This study revealed that majority of the respondents was married. Oladimeji et al. (2013),

reported that majority of the fishermen were married. Olaoye et al. (2012) also reported that a

larger proportion of the fisher folks were married. This implies that occupational

mobility will be reduced and family labour will be available for collective responsibility.

This study revealed that the respondent fishermen were Muslims and Christians. This

indicates that fishing in the study area is not religion biased.

134

5.1.2 Socio-economic characteristics of aquaculture producers.

Sex plays a major role in fish farming and agriculture. The results of this study indicate that

higher percentage of the respondent fish farmers in the study area were male. This result was

affirmed by the assertion of Brummett et al., (2010) that fisheries activities are mostly

dominated by men. This could be as a result of gender bias in distribution and access to vital

production resources such as land that are required in aquaculture production.

Aquaculture production was dominated by those within the age bracket 31-40years. Similar

result was also observed by Olaoye et al., (2013) who indicated that this age bracket is the

productive age range. This indicates that an aquaculture practice in the study area attracts

young individual and seen as a noble occupation. In this study, it was discovered that

majority of the fish farmers were married while few were single, widowed, and divorced.

Oladejo et al., (2008) asserted that marriage confer some level of responsibility and

commitment on individuals.

The study revealed that majority of the respondents had above 10 years’ experience.

According to Olaoye (2013), fish farmers with highest number of years of experience should

have good skill and approaches to fish farming business. Also, fish farmers with longer years

of experience would be able to forecast market situation in which they sell their product at

higher prices. Those with less years of experience, especially less than 5years face many risks

in the early days of their fish farming business.

5.1.3 Socio-economic characteristics of fish processors

As indicated by the results of this study, majority of the fish processors were male. This is in

line with the study of Komolafe (2007) and Olaoye (2015) in Ogun state who reported 100%

and 99% female fish processors respectively. The result of this study indicates that there is no

gender discrimination in fish processing business.

Majority of the fish processor in the study area were within the age bracket of 31-40 years, a

highly productive and active age when actors could undertake strenuous task. This

corroborates the observation of Odebiyi et al. (2013) and George et al. (2010) that age had a

positive correlation with productivity of fish processors in Nigeria.

This study has also revealed that majority of the respondent fish processors in the study area

were married. Similar observation was made by Odebiyi et al. (2013) who reported that

marriage is a respected and prestigious institution that bestows social status and recognition

on people. Although the percentage of fish processors that were Christian was high, however,

135

Islam was observed to be the most prevalent religion of the fish processors in the study area.

This was in line with the observation of Madugu and Edward (2011). This was an indication

that religion doesn’t restrict fish processing the study area.

5.1.4 Socio-economic characteristics of fish traders

The results of this study revealed that most people involved in fish traders were married.

This indicated that fish marketing was a source of livelihood for the marketers and their

families. This is in line with the study of Afolabi (2009), who observed that marketers

were dominated by married people. Also, Kainga and Adeyemo (2012) recorded the same

result. This also is in agreement with the findings of Nwabunike 2015 who reported majority

of the fish traders to be married, though each of the categories were represented.

Fish traders were dominated by individuals who had little or no formal education. This agrees

with the findings of Kainga and Adeyemo (2012) who reported that most fish marketers in

Bayelsa State had no formal education. In south-western Nigeria, most agricultural fish marketers

had primary education (Afolabi, 2009). This might be because fish trading is seen as

demeaning. Although, much education is not needed for fish trading except for

accountability, it should be noted that though not much educated possess cognitive skill

needed for success. However, according to Dogondaji and Baba (2010), low literacy level

could have a negative impact on the adoption of agricultural technologies.

5.2 Profitability of Value-Chain Actors

5.2.1 Profitability of Artisanal Fish Producers

This study assesses the economic performance of value chain actors involved in fish traded in

Nigerian States along Nigeria-Benin border. The value chain actors identified in this study

include the artisanal fishermen, fish farmers, fish processors and the fish traders who were

majorly involved in the production as well as marketing of fresh, smoked, dried, spiced and

frozen fish products in the study area. Similar cross-section of value chain actors were also

reported by Odebiyi et al. (2013) in a related study. This was an indication that value addition

to fish produce and products provide livelihood for diverse class of individuals in the value

chain. The results also revealed that a significant variation (P<0.05) existed in the production

output (total quantity of fish marketed), the values of the output (revenue) as well as

profitability of the respondents fishermen from the different sampled States. Okeowo et al.

136

(2015) also made similar observation among artisanal fishermen in different locations in a

State in Nigeria. The variation in the production output and profitability could be as a result

of differences in the productivity of the waterbodies from which the artisanal fishermen

fished from and the incurred costs (operational, maintenance, marketing, variable and

depreciated fixed costs) that were also significantly difference (P<0.05). This observation

was in line with the report of Anene et al. (2010) who also recorded a similar result.

Moreover, the profitability indices analysis indicated that value-addition in artisanal fisheries

was a productive business in all the sampled States.

The model estimation results obtained from the linear regression analysis indicated that

quantity fish catch sold, selling price, depreciated fixed and operational costs, marketing

efficiency and fishing experience variables had a positive relationship with the revenue of the

artisanal fishermen. This implies that as the quantities of the positive variables tend to

increase, the revenue of the artisanal fishermen would also increase. Similarly, Kareem et al.

(2012) reported that fishing experience has positive influence on productivity of the artisanal

fishermen since experience provides better knowledge on distribution as well as season

influence thereby influencing their economic efficiency. Meanwhile, that age and fishing

experience could have a negative influence on the revenue of the fishermen. This could be as

a result of reduction in productivity as a result of negative effective of aging. However, this

negated the observation of Odebiyi et al. (2013) and George et al (2010) who reported that

age had a positive relationship with agricultural productivity.

The results of this study also indicated that majority of the respondent artisanal fishermen

along Nigeria-Benin border operated in a small-scale level of operation. This was also in

consonance with the observation of Olaoye et al. (2012). This could be attributed to low cost

of investment require in starting-up the fisheries. This study has also revealed that scale of

operation does have influence on the quantity of fish catch by the fishermen as medium scale

respondent fishermen tends to record higher catch than the small scale artisanal fishermen.

This could be as a result of high cost of investment in advance fishing equipments which tend

to be more efficient. This could have been responsible for the significant difference in the net

return and gross margin per kg of the small and medium scale artisanal fishermen.

No respondent artisanal fisherman was involved in inter-regional (export) trade of captured

fish in the study area. Similar result was also observed by Odebiyi et al. (2013), who

137

attributed this to lack of value addition facilities which might have been hindering the growth

of the fish value chain industry.

5.2.2 Profitability of Fish Farmers

The profitability results of the respondent fish farmers in the study area indicate that value-

addition through aquaculture is a lucrative business with positive gross margin and net return

per kilogram of fresh fish marketed was greater than a unit. In likewise manner, this result

affirms the observation of Olasunkanmi and Yusuf (2014). Furthermore, this study also

revealed that cost of feeding accounted for an estimate of 72.69% of the total variable cost

while cost of fish seed (fingerling/juvenile), labour and other operational cost (including cost

of fuel, medication, maintenance and miscellaneous) amounted to 17.02%, 6.32% and 3.88%

of the total variable cost. This was an indication that majority of the variable cost incurred by

the respondent fish farmers in the study area was on fish feed, fingerling/juvenile and labour.

This is agreement with the observation of Omobepade et al.(2014) and Olawumi et al. (2010)

who observed that bulk of the variable cost associated with aquaculture fish production was

on labour, fingerlings and feed procurement. Cost of fish feed taking bulk of the total variable

cost has been attributed to high level of dependence of the fish farmers on imported fish feeds

which are expensive (Olasunkanmi and Yusuf, 2014). This study has revealed that the prices

of fish seed and fresh fish products marketed by the respondent fish farmers in the study area

were not the same. This variation could be as a result of difference in the level of production,

source of supply of fish seed and channel of marketing adopted by the fish farmers.

From the production function obtained from Cobb-Douglas function, it was observed that

cost of fish seed, feeding, labour, depreciated fixed cost and other operational cost had

positive influence on the ssoutput (revenue) of the fish farmers in the study area. This implies

that an increase in capital investment on structural and facility development on a fish farm

through expansion of fish rearing facilities (increase in depreciated fixed cost), there is

opportunity for the fish farmer to stock more fish seed which will result to increase in cost of

feeding and other operational cost (medication, maintenance and others). Thus, optimum

supply of personnel may be required to manage the system. The combined effect of this

would result to increase in revenue (output) of the fish farmers. However, only cost of fish

seed, feeding, labour and other operational cost had significant influence on the revenue. This

was in line with the observation of Omobepade et al. (2014) and Osawe et al. (2008).

138

Although in the study of Osawe et al. (2008) it was observed that the size of ponds had a

negative influence on the level of output of the fish farmers.

The results of the elasticity of production implied that the relationship between inputs (cost

variables) and revenue was inelastic as each of the input variables had production elasticity

less than a unit. Meanwhile, the coefficient of return to scale observed in this study indicate

an increase in returns to scale, which implies that fish farmers were operating at the region of

maximum technical efficiency, an irrational region of production. The elasticity of feed,

labour and fish seed were 0.517, 0.379 and 0.154 respectively meaning 100 percent increase

in these input will results to 51.7%, 37.9% and 15.4% increase in the revenue of the fish

farmers. This implies that cost of feeding has a greater influence on the revenue of the fish

farmers.

This study has also revealed that the predicted technical efficiency of fish farmers along

Nigeria-Benin border ranged between 84% and 93% with an average of 88%. This is an

indication that the fish farmers in the study area are efficient and there is possibility of

increasing productivity by about 12% by adoption of advance technology enables better

productivity. In a similar study, Omobepade et al. (2014), Ekunwe and Emokaro (2009),

Osawe et al. (2008) and Fapounda (2005) reported high technical efficiencies of 79%, 85%,

91% and 83% respectively in some States in Nigeria.

It was observed in this study that scale of operation of the farmers had significant influence

on the quantity of fish production, costs and profitability of the fish farmers. Although there

was no significant difference in the buying price of fish seed and selling price of the marketed

fresh fish produced, the difference in the profitability indices could have been as a result of

effect of scale of operation.

With respect to the trade flow analysis, it was also observed that respondent fish farmers are

not involved in inter-regional trade of fresh fish across Nigeria-Benin border. This could have

been as a result of difficulty involved in transportation of live fish over a long distance due to

lack of inter-border trade facilities among the fish farmers.

5.2.3 Profitability of fish processors

The results of this study has revealed smoked and dried fish were the major fish products

produced by majority of the respondent fish processors in sampled States along Nigeria-

139

Benin border. This was similar to the observation of Madugu and Edward (2011) who

reported that smoked and dried fish were major processed fish marketed and distributed in

Adamawa State. This could be as a result of longer shelf-life of these fish products (smoking

and drying) as well as high preference by the consumers. Also, Adewuyi et al.(2013) reported

that smoked fish were the most traded processed fish products in Ondo State, Nigeria.

Explicit from this study were positive profitability indices of the respondent fish processors

in the study area. This was an indication that value-addition through fish processing is a

profitable agro-business. Adebo and Toluwase (2014) also observed high returns for

processed fish products (smoked fish) when compared to fresh fish marketing. Value addition

is known to improve income and reduce challenges of finance in farming (Adebo and

Toluwase, 2014).

The production function analysis obtained from the results of this study pointed that cost of

processing, purchasing cost, total variables and production cost had positive influence on the

revenue of the fish processors. This means that as the costs of value-addition on fish

processed products tend to increase, there is subsequent increase in the output (revenue) of

the fish processors. In a related study, Adewuyi et al (2013) also reported a contrary result the

cost of fish purchase had a negative influence on the revenue of the fish processors in Ondo

State, Nigeria.

In this study, the average technical efficiency of fish processors in the sampled States along

Nigeria-Benin border was 89.0% which indicated that the respondent fish processors were

highly efficient and with better technology their productivity could improve by 11%.

Adewuyi et al (2013) also observed technical efficiency as high as 94.34% among smoked

processors in Ondo State, Nigeria.

5.2.4 Profitability of fish traders

Evident from the results of this study was the fact that fish there was significant different in

the level of profit realized from the trade of different fish products marketed by the fish

traders/marketers along Nigeria-Benin border. Fish traders involved in marketing of

processed fish products had higher profit margin than traders of fresh fish. This result is

corroborated by the findings of Adebo and Toluwase (2014). This could be as a result of

effect of value-addition through processing to the processed fish products which tend to

140

increase their market value when compare to fresh fish with little or no evident of value-

addition. However, irrespective of the fish product marketed by the fish trader the profit

margin was high and positive, indicating that fish marketing is a lucrative business in the

study area.

Also obtained from the results of this study was the fact that fish traders are most involved in

inter-regional trade of fish products along Nigeria-Benin border. This could be as a result of

their access to cross-border trade facilities such as transportation which other actors along the

value chain may not have adequate access to.

The results of economies of scale obtained in this study reveal that the total quantity of fish

products marketed by the traders in the study area had a positive significant influence on the

total cost of marketing. This implies that as the quantity of fish products marketed there is

subsequent increase in the cost of marketing incur by the fish traders. This could be as a

result of need to increase the facilities as well as other related costs associated with marketing

of fish products by the fish traders with increase in marketed product. However, in Ogun,

Oyo and Niger States, scale economies were observed in the marketing of dried fish products.

This implies that there with increase in the quantity of dried fish marketed there was a decline

in the marketing cost with subsequent increase in the profit margin of the concern traders.

Similar result was also recorded by Ismail et al. (2014) in dried fish traded in Borno State,

Nigeria.

5.3 Constraint of the Value-Chain Actors

This study has revealed that the major challenges faced by the artisanal fishermen in the

study area were inadequate access to credit facility and poor storage facilities. Meanwhile,

ranked high among the different challenges faced by the fish farmers was high cost of feeding

and poor electricity supply. This was in line with the observation of Baruwa et al. (2012) who

reported the constraints to fishery production were capital inadequacy, water pollution, and

epileptic electric supply, high cost of labor and high cost of inputs.

Meanwhile, fish processor enlisted poor transport/road condition, lack of training and poor

electricity supply as their major challenges. Similarly, Moshood et al. (2014) perceived lack

of electricity and lack of training on financial management and loan acquisition.

141

This study has also revealed that inadequate credit accessibility with poor transport

facilities/road condition were some of the major challenges encountered by the fish traders in

the study area. This is affirmed by the observation of Udong et al. (2009) who reported that

lack of infrastructure and finance limit economic activities and livelihood strategies.

142

CHAPTER SIX

6.0 CONCLUSION AND RECOMMENDATION

6.1 CONCLUSION

Value-addition has been found to be essential to sustainable development of aquaculture and

fisheries industries. Consequently, several actors namely: artisanal fishermen, fish farmers,

fish processors and marketers/traders were observed to be actively involved in value-addition

of fish products along Nigeria-Benin border. These actors operated small, medium and large

scale operation systems. It was observed that value-addition is a lucrative business

irrespective of the fish products produced and the scale of operation of the actors.

More so, the trade flow analysis indicated that inter-regional trade from Nigeria to Benin

through the Nigeria-Benin border was not common practice among the value-chain actors in

the study area. Although, inter-regional trade was observed among the fish processors and

traders in Ogun and Lagos State respectively, the percentage of processed fish products (dried

and smoked fish) traded and the number of value-chain actors involved were extremely low

when compare to those in intra-state trade. This could have been as a result of lack of

transport facilities, inadequate credit and other relevant infrastructures that could have

enhanced inter-regional trade across Nigeria-Benin border.

Furthermore, the technical efficiencies of the value-chain actors were above 80%, indicating

that there are still opportunities to improve fish productivity in the area.

6.2 RECOMMENDATION

Therefore, in order to boost and encourage inter-regional fish trade across Nigeria-Benin

border, there is need to:

1. Provide transport, storage, packaging facilities and other essential inputs at a

subsidized rate for value-chain actors in the study area by the government agencies

and international organisations

2. Grant access to credit facilities by financing organisations such as banks at a single

digit interest rate.

143

3. Establish an inter-regional fish trade board by the government agencies and/ relevant

international organizations that will oversee inter-regional fish trade and provide

technical supports for fish value-chain actors.

144

REFERENCES

Abiona, B.G. 2011. Constraints to integrated and non-integrated fish farming activities in

Ogun State, Nigeria. Journal of Agricultural Science, 3.4: 233 – 240.

Adebo, G. M. and Toluwase, S. O. W. 2014. Comparative analysis of fresh and smoked

catfish marketing in Ekiti and Ondo States of Nigeria. Journal of Biology, Agriculture

and Healthcare 4.19: 6-11.

Adedokun, O. A., Adereti, F. O. and Opele, A.I. 2006. Factors influencing the adoption of

fisheries innovations by artisanal fishermen in coastal areas of Ogun State, Nigeria

Journal of Applied Science Research, 2.11: 966-971.

Adeogun, O.A., Ogunbadejo, H. K., Ayinla, O. A., Oresegun, A. O., Oguntade, R., Tanko A.

and William, S. B. 2007. Urban Aquaculture: Producer Perceptions and Practice in

Lagos State, Nigeria. Middle East Journal of Scientific Research, 2.1: 21-27.

Adepegba, O. 2001. Problems and Prospects of the Development of Artisanal Fish Trade in

West Africa with particular emphasis on Nigeria. Paper prepared for the Workshop on

Problems and Prospects for Developing Artisanal Fish Trade, 30 May to 1 June

2001, Dakar, Senegal.

Adetunji, A. A. 2011. Fish Production, Poverty Alleviation and Cooperative Success of

Eriwe Cooperative Fish Farm at Ijebu-Ode, Ogun State, Nigeria. Unpublished

Bachelor of Aquaculture and Fisheries Management Project, University of

Agriculture, Abeokuta, Ogun State, Nigeria.

Adewumi, A. A. and Olaleye, V. F. 2011. Catfish culture in Nigeria: Progress, Prospects and

Problems. African Journal of Agricultural Research, 6.6: 1281-1285

Adewuyi, S. A., Okuneye, P. A, Adeosun, I. A and Alaba, O. M. 2013. Profit efficiency in

fish smoking in Ilaje local government area of Ondo State, Nigeria. IJAFS 4.4: 421 –

427.

Aihonsu, J. and Shittu, A. 2008. Value- addition: Comparative economic analysis of fish

processing technologies in two fishing communities in Lagos State, Nigeria. In:

V.M.E, Obinne and A. Lawal eds., Prospects and challenges of adding value to

145

agricultural products. Proceedins of the 22nd Annual National Conference of Farm

Managers Association of Nigeria. Pp. 317 – 321.

Akinbile, L. A. 1998. Paper presented at NAERLS Workshop on Extension Communication

Techniques 11, 15 July to 18 July 1998, Markurdi, Nigeria.

Ali, E. A, Gaya, H. I. M., and Jampada, T. N. 2008. Economic Analysis of fresh fish

marketing in Maiduguri Gamboru Market and Kachallari Alau Dam landing site of

North-Eastern Nigeria. J. Agri. Soc. Sci. 4:23-26.

Ali, M. and Chaudhary, M. A. 1990. Inter-regional farm efficiency in Pakistan Punjab: A

frontier production function study. Journal of Agricultural Economics 41.1: 62-74.

Amao, J. O., Oluwatayo, I. B. and Osuntope, F. K. 2006. Economics of Fish Demands in

Lagos State, Nigeria. Journal of Human Ecology19 1, 25-30.

Amaza, P.S. and J.K. Olayemi 2002. Analysis of Technical Inefficiency in Food Crop

Production in Gombe State, Nigeria. Applied Econs Letters 9.1: 51-54.

Amos, T. T., Chikwendu, D.O., Nmadu, J. N. 2004 Productivity, Technical Efficiency and

Cropping Patterns in the Savannah Zone of Nigeria. Journal of Food, Agriculture and

Environment 2: 173-176.

Anene, A., Ezeh, C. I. and Oputa, C. O. 2010. Resources use and efficiency of artisanal

fishing in Oguta, Imo State, Nigeria. Journal of Food, Agriculture and Environment

3: 32-46.

Areola, F. O. 2007 Fish marketing and export potentials of fish and fisheries products of

Nigeria. A lecture delivered at educative and informative aqua-culture workshop and

aqua-exhibitions tagged: sustainable fisheries livelihood, management and food

security in Nigeria. 23pp.

Atanda AN, 2009. Freshwater fish seed Resources in Nigeria. Fish Network 21: 26 – 57.

Ayanboye A. O., Oluwafemi Z. O. and Rafiu R. A., 2015. Fresh fish Clarias gariepinus

marketing system in major towns of Ibarapa zone, Oyo State, Nigeria. Pp.162-171

Bain, J. S. 1951. Relation of Profit Rate to Industry Concentration, Quarterly Journal of

Economics 65: 293-324.

146

Baruwa, O. I., Tijani, A. A. and Adejobi, A. O. 2012. Profitability and constraints to fishery

enterprises: A case of artisanal and aquaculture fisheries in Lagos State, Nigeria.

Nigerian Journal of Agriculture, Food and Environment. 81:52-58.

Bassey, N. E, Uwemedimo, E. Okon, Uwem, U. I. and Edet, N. E. 2015. Analysis of the

Determinants of Fresh Fish Marketing and Profitability among Captured Fish Traders

in South-South Nigeria: The Case of Akwa Ibom State. British Journal of Economics,

Management and Trade 5.1: 35-45.

Bravo-Ureta, B. E. and Evenson, R. E. 1994. Efficiency in Agricultural Production: The case

study of peasant farmers in Eastern Paraguay. The Journal of the International

Association of Agric. Econs. 14: 23-30.

Brummett, R. E., Youaleu, J. L. N., Tiani, A. M. and Kenmegne, A. 2010. Women’s

traditional fishery and alternative aquatic resources livelihood strategies in the

Southern Cameroonian Rainforest. Fisheries Management and Ecology 17: 221-230.

Chenyambuga. S. W., Nazael, A., M. and Berno V. M. 2012. Management and Value Chain

of Nile Tilapia Cultured In Ponds of Small-Scale Farmers In Morogoro Region,

Tanzania. 16th Conference Paper and Presentation of International Institute and Trade

(IIFET), July 16-20, 2002, Dar es Salaam, Tanzania.

Chilaka, Q. M., Nwabeze, G. O. and Odili, O. E. 2014. Challenges of Inland Artisanal Fish

Production in Nigeria: Economic Perspective. Journal of Fisheries and Aquatic

Science, 9: 501-505.

CYE Consult. 2009. Value chain analysis of selected commodities-Institutional development

across the Agri‐Food Sector IDAF – 9 ACP Mai 19. Final report.

Dambatta, M.A, Sogbesan, A. and Olukayode A. 2015. Socio-Economic and Profitability of

Fisheries Enterprises in Kano State, Nigeria. International Journal of Novel Research

in Humanity and Social Sciences 2.1: 72-83.

Dambatta, O. A. Sogbesan, A., Tafida A. A, Haruna, M. A. and Fagge, A.U. 2016.

Profitability and Constraints of Three Major Fisheries Enterprises in Kano State,

Nigeria. Global Journal of Science Frontier Research: I Interdisciplinary 6.1: 234-

454

147

Dawang Naanpoes Charles, Dasbak Ayuba and Matawal Obed M. 2011. Estimates of

Profitability and Technical Efficiency of Artisanal Fishermen: A Case of Natural

Lakes from Plateau State, Nigeria. Asian Journal of Agricultural Sciences 3.6: 516-

523.

De Silva, D. A. M. 2011. Value chain of fish and fishery products: origin, functions and

application in developed and developing country markets. FAO, Rome. Pp 25-35.

Dongondaji, S. D. and Baba, K. M. 2010: Income distribution in large scale irrigation

projects: A case study of Dry season rice farmers at the Bakolori irrigation project,

Zamfara state, Nigeria. Proceedings of the 24th Annual National Conference of the

Farm Management of Nigeria held at the Adamawa State University, Mubi 11th- 14th

October, 2010

Economic of West African States, ECOWAS, 2000. ECOWAS: 25th Anniversary Report.

Retrieved on 23rd of October, 2015 from http://www.ecowas.int

Edwards, S., Allen, A.J. and Shaik, S. 2005. Market Structure Conduct Performance (SCP)

Hypothesis revisited using Stochastic Frontier Efficiency analysis. Selected paper for

presentation at the American Agricultural Economics Association Annual Meeting,

Long Beach, California, July 23-26, 2006. 4-5.

Ekunwe, P. A and Emokaro, C. O. 2009. Technical efficiency of catfish farmers in Kaduna,

Nigeria. Journal of Applied Sciences Research 5.7: 802-805.

Esiobu, N. S., Nwosu, C. S and Onubuogu, G. C. 2014. Economics of Pineapple Marketing in

Owerri Municipal Council Area, Imo State, Nigeria. Int. J. Appl. Res. Technol.. 3.5: 3

– 12.

Fabusoro, E., Lawal-Adebowale, O. A. and Akinloye A. K. 2007. A study of rural livestock

farmers’ patronage of veterinary services for healthcare of small farm animals in

Ogun State, Nigeria. Journal of Agricultural Science 34 1and2, 132- 138.

FAO 2013. A value-chain analysis of international fish trade and food security with an

impact assessment of the small-scale sector. FAO Fisheries Technical Paper 456

Retrieved http://www.fao.org/valuechaininsmallscalefisheries

148

Fapounda, O. O. 2005 Profitability of homestead fish farming in Ondo State, Nigeria. Journal

of Animal and Veterinary Advances 4: 598-602.

Federal Department of Fisheries FDF 2008. Fisheries Statistics of Nigeria. 4th Edition.,

Federal Department of Fisheries, Garki, Abuja, Nigeria.

Federal Department of Fisheries FDF. 2009. Nigeria National Aquaculture Strategy. Assisted

by FAO. Formally approved by Government. p.18.

Fishery Committee for Eastern Central Atlantic CECAF. 1992. Intra-state Fish Trade:

Characteristics, Problems and Development Prospects. Retrieved on 5th of October,

2016 from http://www.fao.org/docrep/006/w3839e/W3839e01.htm

Food and Agricultural Organization, FAO. 2012. The state of World Fishery and

Aquaculture, Rome. 209 pp.

Food and Agricultural Organization, FAO. 2014. World Review of Fisheries and

Aquaculture, FAO, Rome. 148 pp.

Food and Agriculture Organization and World Fish Centre 2010. Small scale capture

fisheries – a global overview with emphasis on developing countries. A preliminary

report of the Big Numbers Project for Living Aquatic Resources Management

ICLARM technical report no. 46. ICLARM

Food and Agriculture Organization FAO 2012. Fisheries production. Technical Paper 215/

UNP FAO, Rome. Pp. 35-37.

George, F. O. A., Olaoye, O. J., Akande, O. P. and Oghobase, R. R. 2010. Determinants of

Aquaculture Fish Seed Production and Development in Ogun State, Nigeria. Journal

of Sustainable Development in Africa, 12.2: 44-52.

GTZ. 2007. Valuelinks manual. The methodology of value chain promotion. Eschborn,

Germany: Deutsche Gesellschaft für Technische Zusammenarbeit GTZ.

http://www.nigeriamarkets.org/index.php?option=com_contentandview=articleandid=

123andItemid=67.

Gumbau, M. and Maudos, J. 2000. Profitability and Efficiency: An application to the Spanish

Industry. Working paper, Institute of Economic Research (IVIE). 31.

149

Hardy, C. 1992. The Prospects for Intra-state Trade Growth in Africa. In: F. Stewart, S. Lall

and S. Wangwe ed, Alternative Development Strategies in Sub-Saharan Africa.

London: Macmillan Press.

Hundeyin, A. 2011. The socio-economic analysis of small scale fish farming enterprise in

Lagos State fish farming estate.

IIFET, 2014. Markets and marketing of fish and fishery products in Nigeria. Pp1-3

Inoni, O. E. and Oyaide W. J. 2007. Socio-economic analysis of artisanal fishing in the South

Agro-ecological Zone of Delta State, Nigeria. Agricultural tropical and subtropical,

40.4:11-17.

International Collective in Support of Fishworkers ICSF. 2002. Report of the Study on

Problems and Prospects of Artisanal Fish Trade in West Africa. ICSF, Chennai,

India, 92pp.

Investopedia, 2011. Value Chain. Retrieved on 24th of October, 2016 from

http://www.investopedia.com/terms/v/valuechain.as

Ismail, A.B.D, Latif, A., Tijani, B. A., Abdullah, A. M. and Mohammed, B. 2014. Analysis

of marketing channel and market structure of dried fish in Maiduguri metropolis of

Borno State, Nigeria. European Journal of Business and Management 6.7: 147-155.

Jacinto, F.R. and Pomeroy, R.S. 2011. Developing Markets for Sma.lI-scale Fisheries:

Utilizing the Value Chain Approach. In: Small-scale fisheries management:

frameworks and approaches for the developing world.

Jim-Saiki L. 2016. Socio-Economic Analysis of Artisanal Fishing Operation in West and East

Axes of Lagos State, Nigeria. Nigerian Journal of Fisheries and Aquaculture 4.1: 43-

56.

Kareem, R. O, Dipeolu, A. O, Aromolaran, A. B and Akegbejo, S. 2006. Analysis of

Technical, Allocative and Economic Efficiency of different Pond Systems in Ogun

State, Nigeria. African Journal of Agricultural Research 3.4: 246-254

150

Kareem, R.O, Idowu, E.O, Ayinde, I.A and Badmus, M.A. 2012. Economic efficiency of

freshwater artisanal fisheries in Ijebu Waterside of Ogun State, Nigeria. Global

Journal 12.11: 30-43.

Kingsway Fishery Services 2013. Fish Marketing/Market for Fish In Nigeria. Retrieved on

24th of October, 2016 from

http://www.kingswayagroservices.blogspot.com/2012/08/fish-marketingmarket

Komolafe, 2007. Socio-economic characteristics of fish processors in Obantoko area of

Abeokuta, Ogun state, Nigeria.

Kudi, T. M., Bakp, F. P. and Atala, T. K. 2008. Economics of fish Production in Kaduna

State, Nigeria. Asian Research Publishing Network APRN 35.6: 17 – 21.

Lawal, J., P.O. Obatola, E. J. Giwa, and T. A. Alhaji, 2016 “Socio-Economic Analysis of

Artisanal Fishing Operation in West and East Axes of Lagos State, Nigeria.” World

Journal of Agricultural Research 41: 31-35.

Lawal, W. L and Idega, E. O. 2004: Analysis of fish marketing in Benue State. Proceedings

of the 2004 Annual Conference of the National Association of Agricultural

Economists NAAE held at ABU Zaria, Nov 3rd -5th, 2004.

Lindner, A., Fisher, C., Felix, A., Scherer, V., Warkentin, A. 2010. Investment and valuation

of firms. Market efficiency theory. Publication of Universidad de Huelva. Retrieved

on 20th September, 2016 from http://uhu.es/45151/temas/Unit%204_1.pdf. 17.

Lo, A. W. 2004. The adaptive markets hypothesis. The Journal of Portfolio Management 30.5:

15–29

Mafimisebi, T. E. 2003. Yield Performance of Commercialized upland fish farms in Ondo

State. Nigerian Journal of Animal Production, 30.2: 336-342.

Magudu, A. J. and Edward, A. 2011. Marketing and distribution channel of processed fish in

Adamawa State, Nigeria. Global Journal of Management and Business Research

11.4: 23-32.

Miller, A. and da Silva, C. 2007. Value chain financing in agriculture. Enterprise

Development and Microfinance 13.2-3:93-108.

151

Molyneux, P. and Forbes, W. 1995. Market Structure and Performance in European Banking.

Applied Economics 27: 155-159.

Moshood et al.,2014. Assessment of Constraints of Women in Fish Processing and

Accessibility to Extension Activities in Lagos State, Nigeria. OIDA International

Journal of Sustainable Development 7.5: 61-70.

Mshelia M. B., Bankola, N. O., Omorinkoba, W. S., Musa, Y. M., Tafida, A. A., Richard, L.

M, Ago, N. D. and Adedeyi, R. B. 2007. Marketing and Distribution of Fish in New

Bussa fish market area of Niger State. Proceedings of the 22nd Annual Conference of

the FISON, Kebbi, 12th to Nov. 2007, Pp.172 – 178.

Nwabeze, G. O. and Erie, A. P. 2013. Artisanal fishers' use of sustainable fisheries

management practices in the Jebba Lake Basin, Nigeria. J. Agric. Extension 17: 123-

134.

Nwabunike M. O. 2015. The socio-economic characteristics of fish marketers in abakaliki

metropolis of Ebonyi state. International Journal of Animal Health and Livestock

Production Research 1.1:28-36.

Nwiro, E. 2012. Fish Farming a lucrative Business Retrieved on 20 October, 2012 from

http://www.thisdaylive.com/articules/fish-farming-alucrative business/11

Odebiyi, O. C, George, F. O. A, Odulate, D. O., Agbonlahor, M. U. and Olaoye O.J. 2013.

Value-chain analysis for coastal fisheries development in Nigeria. Global Journal of

Science Frontier Research Agriculture and Veterinary 13.11: 6 -15.

Odebiyi, O. C. 2010. Impact of microfinance bank loan on aquaculture development in Ogun

state, Nigeria. A project report submitted to the Department of Aquaculture and

Fisheries management, Federal University of Agriculture Abeokuta.

Ojo S. O, Fagbenro O.A 2004. Poverty Reduction Strategy in Nigeria –Improving

productivity and Technical Efficiency in Artisanal Fisheries in Niger Delta Region.

Paper presented at the 12th Bi-annual conference of the International Institute of

Fisheries Economics and Trade IIFET, Tokyo, Japan

152

Okeowo, T. A., Bolarinwa, J. B. and Ibrahim, D. 2015. Socioeconomic analysis of artisanal

fishing and dominant fish species in lagoon waters of Epe and Badagry areas of Lagos

State. International Journal of Research in Agriculture and Forestry 2.3: 38-45.

Okwu, O. J. and Acheneje, S. Socio-Economic Analysis of Fish Farming in

Makurdi Local Government Area, Benue State. Nigeria European Journal of

Social Sciences 23.4: 508-515.

Oladimeji, Y. U., Abdulsalam, Z. and Damisa, M. A. 2013. Socio-economic characteristics

and returns to rural artisanal fishery households in Asa and Patigi local government

areas of Kwara state, Nigeria. International Journal of Science and Nature 4.3 445-

455.

Olagunju, F. I., Adesiyan, I. O. and Ezekiel, A. A. 2007 Economic Viability of Cat Fish

Production in Oyo State, Nigeria. J. Hum. Ecol. 21.2: 121-124.

Olaoye, O. J., Adegbite, D. A., Oluwalana, E. O., Ashley-Dejo, S. S., Adelaja, O. A. and

Fagbohun, A. E. 2015. Economic analysis of fish processing and marketing in Ogun

Waterside Local Government, Ogun State, Nigeria. Nigerian Journal of Animal

Production 4.22: 23-33.

Olaoye, O. J., Idowu, A. A., Omoyinmi, G. A. K., Akintayo, I. A., Odebiyi, O. C., and

Fasina, A. O. 2012. Socio-economic analysis of artisanal fisher folks in Ogun Water-

Side Local Government Areas of Ogun State, Nigeria. Global Journal 124: 8-22.

Olaoye, O.J, 2013. Assessment of socio-economic analysis of fish farming in Oyo state,

Nigeria. A Ph.D Thesis of Department of Aquaculture and Fisheries Management,

University of Agriculture, Abeokuta, Ogun State, Nigeria. Pp367

Olasunkanmi, N. O. and Yusuf, O. 2014. Resource use efficiency in small scale catfish

farming in Osun State, Nigeria. Sky Journal of Agricultural Research 3.1: 37-45.

Olawumi, A.T., Dipeolu, A.O., Bamiro, O.M. 2010. Economic Analysis of Homestead Fish

Production in Ogun State Nigeria. Journal of Human Ecology 31: 13-17.

Olubanjo, O. O., Akinleye, S. O. and Balogun, M. A. 2007. Occupational characteristics,

technology use and output determinants among fisher-folks in Ogun Waterside Area,

153

Ogun State. FAMAN Farm Management Association of Nigeria Journal, 8.2: 321-

332.

Olukosi, J. O and Erhabor, P. O. 1989. Introduction to Farm Management Economics:

Principle and Application. Pub. Ltd., Zaria.

Olukosi, J. O. and Isitor, S. V. 1990. Introduction to Agricultural Market And Price;

Principles And Application. Living Book Series, G. U Publication Abuja Pp 37-47.

Omiti, J., Otieno, D., Nyanamba, T. and Mc Cullough, E. 2009. Factors influencing the

intensity of market participation by smallholder farmers: A case study of rural and

peri-urban areas of Kenya. African Journal of Agricultural and Resource Economics

3.1: 57-82.

Omobepade B. P., Adebayo, O. T. and Amos, T. T. 2014. Technical Efficiency of

Aquaculturists in Ekiti State, Nigeria. Journal Aquac Res Development 5.5: 1-5.

Omobepade,B.P., Adebayo, O.T,Amos, T.T. and Adedokun, B.C.2015. Profi tability

Analysis of Aquaculture in Ekiti State, Nigeria. Nigerian Journal of Agriculture,

Food and Environment. 111:114-119.

Onoja, A.O., Usoroh, B.B., Adieme, D.T. and Deedam, N.J. 2012. Determinants of Market

Participation in Nigerian Small-Scale Fishery Sector: Evidence from Niger Delta

Region. Consilience: The Journal of Sustainable Development 9.1: 69-84.

Onyango, C.O. 2013. Analysis of Structure, Conduct and Performance of small ruminant

stock market participants of Isiolo-Nairobi trading market, Kenya. M.Sc Project.

Agricultural andApplied Economics of Egerton University. xiii+93pp.

Oparinde, L. O. and Ojo, S. O. 2014. “Structural Performance of Artisanal Fish Marketing in

Ondo State, Nigeria.” American Journal of Rural Development 2.1: 1-7.

Osawe, O.W., Akinyosoye, V.O. and Omonona, B.T. 2008. Technical efficiency of small

scale farmers: an application of the stochastic frontier production function to fish

farmers in Ibadan metropolis, Oyo State, Nigeria. Journal of Economics and Rural

Development 16.1: 71-82.

154

Otubusin, S.O., 2011. Inaugural lecture: Fish! Fish!! Fish!!!. Department of Aquaculture and

Fisheries Management, College of Environmental Resources Management, University

of Agriculture, Abeokuta, Nigeria, pp: 45-55.

Oyinbo O, Rekwot GZ, 2013. Fishery production and economic growth in Nigeria: Pathway

for sustainable economic development. J Sustain Dev Afr, 15.2:99-109.

Rondon, M. and Nzeka, U. 2010. Strong Demand Continues Expanding Fish Exports to

Nigeria. Global Agricultural Information NetworkGAIN.

Sapkota, P. et al. 2012. Price transmission relationships along the seafood value chains in

Bangladesh: aquaculture and capture fishery species. FAO NORAD Project.

Shamsuddoha, M. 2007. Supply and value chain analysis in the marketing of marine dried

fish in Bangladesh and non-tariff measures NTMs in International trading. Retrieved

on 24th of October, 2016 from http://ideas.repec.org/p/ags/eaa106/7941.html.

Shapiro, R.H. 1983. Efficiency differentials in present agriculture and their implications from

development policies. Journal for Development Studies 19: 179-190.

Shettima, B. G., Mohammed S., Ghide A. A. and Zindam, P. L. 2014. Analysis of Socio-

economic Factors Affecting Artisanal Fishermen around Lake Alau, Jere local

government Area of Borno State, Nigeria. Nigerian Journal of Fisheries and

Aquaculture 21: 48-53.

Shimang, G. N. 2005. Fisheries development in Nigeria, problems and prospects. The Federal

Director of Fisheries, The Federal Ministry of Agriculture and Rural Development,

Abuja.

Singh, K., Dey, M. M., Rabbani, A. G., Sudhakaran, P. O. and Thapa, G. 2009. Technical

Efficiency of Freshwater Aquaculture and its Determinants in Tripura, India.

Agricultural Economics Research Review 22: 185-195.

Sinkey, J. F. 1986. Commercial Bank Financial Management in the Financial Services

Industry. New York: MacMillan. 773pp

155

Spore, A. 2012. Making the connection: The rise of agricultural value chains. The magazine

for agricultural and rural development in ACP countries. Technical Centre for

Agricultural and Rural Cooperation CTA, Waganingen, the Netherlands. 3-7

Tiri,G. D.,Oshoke, J., Nabinta, T. R. and Olatinwo, L. K. 2014. Assessment of the

Performance and Barriers to Small-Scale Fish Marketing in Dutsin-Ma Local

Government Area, Katsina State, Nigeria. PAT 10.2: 131-144.

Tomek, W. G and Robinson, L. 1981. Agricultural product prices, 2nd edition. Ihaca, New

York, U.S.A cornel University press.

Udong, E., Niehof, A. and Van T. A. 2009. “Struggle for Surival: Women Fish

Traders Fighting Institutional and Cultural Constraints in Fishing

Communities in the Niger Delta, Nigeria.” Conference On

International Research On Food Security, National Resource Management and

Rural Development.

Ugwumba, C.O.A. 2011. Technical Efficiency and Profitability of Catfish Production in

Anambra State, Nigeria; An Unpublished PhD Thesis, Department of Agricultural

Economics, Delta State University, Abraka, Nigeria.

United State Agency for International Development USAID 2014. Markets, increasing

competitiveness and food security in Nigeria. USAID.

Van den Berg, M., Boomsma, M., Cocco, I., Cuna, I., Jansen, N., Moustier, P., Prota, l.,

Purchel, T., Smith, D. and Van, W. S. 2009. Making Value chain work better for the

poor: Toolbook for practioners of value chain analysis : making market work better

for the poor Mp4. Retrieved on August 20, 2012

Wategire, B. B. and Ike, P. C. 2015. An Analysis of the Technical Efficiency of Non

Motorized Small Scale Shrimp Fishers in the Coastal Areas of Delta State, Nigeria.

Mediterranean Journal of Social Sciences 6.1: 285-291.

Williams T.O., Spycher B. and Okike I. 2006. Improving livestock marketing and intra-

regional trade in West Africa: Determining appropriate economic incentives and

policy framework. ILRI (International Livestock Research Institute),Nairobi, Kenya.

122 pp.

156

Williams, S. B. and Awoyemi, B. 1998. Fish as a Prime Mover of the Economic life of

women in a fishing community. Proceedings of the IIFET Held in Tromso, Norway,

held on July 1998. 286-292.

World Bank 2014. Nigeria Data and Statistics. Retrieved on 24th of October, 2016 from

http://www.worldbank.org/en/country/nigeria.

Yusuf, S. A., Ashiru, A. M. and Adewuyi, S. A. 2002. Economics of Fish Farming in Ibadan

Metropolis. Tropical J. of Animal Sci., 5.2: 116-128.

157

APPENDICES Appendix 1: Sample questionnaire administered to the respondent artisanal fishermen in the

study area

Questionnaire code /_____________ / Date of interview:_____________________ Name of Interviewer: ______________________________

Dear correspondent (Ethics statement),

I/We am/are doing a survey on fish value chains under the Africa Fish Trade Program. . The data we collect will be only used for research purposes and will help come up with policy recommendations to improve benefits from fish trade in the country, region and Africa as a whole. We hope that you will be free to provide me/us with true and accurate data and information. Please feel free to ask any questions or raise any issues you might have. You can terminate this interview at any point should you wish so. I/We hope that I/we can come back to give the results of these surveys to your group, both for your information and your further inputs. Thank you for your participation.

Section A. Demographic and socio-economic characteristics 1. Name: ___________________________________________ 2. Sex: Male ( ) Female ( ) 3. Marital Status: Married ( ) Single ( ) Divorced ( ) Widowed ( ) Separated ( ) 4. Age of respondents……years 5. Religion: Christian ( ) Islamic ( ) others (specify)…………… 6. Level of Education: No formal education ( ) Primary Education ( ) Tertiary

Education( ) Quranic Education ( ) others (specify) …….. 7. Household size: No of wife(s)……

No of children…… Male ………. Female …………… No of other dependants…… Male…………….. Female ……………

8. Group head: Yes ( ) No ( ) 9. Did you receive any formal agricultural training? Yes ( ) No ( ) 10. Number of income earners in the household. ……… Male ……………. Female …………………. Location

11. Country ______________________________________________________________ 12. Region/province _______________________________________________________ 13. Geo-political zone: _____________________________________________________

14. ADP Zone: _______________________________________________

15. Village (if applicable) ___________________________________________________ 16. Water body (if applicable) Brackish ( ) Fresh water ( ) Marine ( )

17. Location of actorGPS___________________________________________________ 18. How long have you been practicing fish catching?___________________years 19. What species of fish have you caught ? (List as many)

158

Past year Present year

20. How would you describe the type of your operations? Small scale( ), Medium scale( ), large scale ( ) 18b. how do you operate? Daily ( ) Weekly ( ), Monthly ( ), Others specify_____________________ 21. Social Assets: Membership in social groups Groups Member

(Yes/No) Position held

Name of Group

Membership size

Benefits Derived

Cooperative Informal work exchange group

Savings and credit group

Religious group Town union Occupational groups

Social groups Section B. Fish Catch System/Technology 22. How many times do you catch fish in a week in the wet season? ____________________ 22b. What is the average total weight caught in a week__________, in a month__________? 23. How many times do you catch fish in a week in the dry season? ____________________ 23b. What is the average total weight caught in a week__________, in a month__________? 24. When do you catch fish? Day( ), Night ( ) Both ( ) 25. Kindly indicate the months of Wet period ______________________ to _______________________

Dry period ____________________ to ______________________ 26. What is the peak period of fish catch? _________________ to __________________ 27. Please indicate the types of technology and list the inputs used in catching fish SN Technologies Wooden/ Fibre Accompanying inputs Cost of

Acquisition (Naira)

1 Motorized

159

2 Unmotorized 3 Others 28. In addition to the fishing activity which other activities do you undertake along the value chain? SN Business Process a Location b 1 2 3 4 a : 1-Grading and sorting, 2-Processing, 3-Packing, 4-Distribution, 5-Cold room/ Freezer, 6-Others (specify)____________ b: 1-within business premises, 2-within locality, 3-other part of the state, 4-other part of country, 5-Others (specify)___________ 29. Indicate the capital equipment /asset owned for your fishing activities in the past years and their running costs.

Equipment Quantity (No)

Date of acquisition

Cost of acquisition (N/one)

Expected life span

Cost of maintenance per month as applicable Repair Fuelling

Nets Hooks and lines Out-board engines(capacity)

maker

Traps Paddle Canoe Small generator Capacity__________

Lighting bulbs Wire Basket Others (specify) 1. 2.

30. Indicate equipment rented or borrowed for production in the last year. Equipment Quantity

Rented (in

Duration of usage Cost of usage ( N: K)

Other expenses incurred ( if applicable) ( N: K)

No of No of Cost / Cost Repair Fuelling

160

number) hour/day days/week hrs /day Nets Hooks and lines

Out-board engines

Traps Paddle Canoe Basket Steering poles

Local mat and bamboo

Others (specify)

1. Section C. Output and Inputs Used in Production 31. Please provide record of your fish catch in the last month in the table below (Actual production figures and average selling prices of various catches) Species caught No Avg. Weight

(kg) Avg. Price (N)

Total amount made from sales

32. Do you have access to credit facility fish catch? Yes ( ), No ( ) 33. If ‘yes’ to question 30, kindly complete the table below Source of capital Amount available for the

last growing season( N) Interest paid(%) per year

Personal Friends/relatives Cooperatives Banks Local money lender Government Others (Specify): Section D. Sales and Marketing 34. Please indicate the average quantity of fish caught by you in the last one month. Species Wet season Dry season

161

of Fish Quantity (kg)

Quantity ( basket)

Quantity in other local measure

Carton Quantity (kg)

Quantity (basket)


Carton

35. In what forms and prices do you normally sell your fish? Forms of sale Response

(yes = 1, No = 0) Farm gate / producers price (N : K)

Live Smoked Frozen Sun-Dried 36. Who are the most important suppliers of your core inputs? (Please note canoe and OBE supplier brands) Supply side ( place) Nature of supply 37. Who are your most important buyers? Buy side (destination) What do they purchase 38. Where do you sell your fish, how do they get to the market and who sells them?

Fish Location/ distance of sale (km) Transportation mode1

Sales person2 Buyer3

Landing site

Middlemen Direct to Market

Landing site

Market Landing site


Landing site


162

*Note: writing down distance (km) indicates someone sells product at that location if not it should be left blank 1 1=by foot, 2=bicycle, 3=motor cycle, 4=motorized vehicle, 5=animals (i.e. donkey), 6=others specify ________________________ 2 1=husband, 2=wife, 3=other adult male, 4=other adult female, 5=male child, 6=female child 3 1=direct consumer, 2=processors, 3=local traders, 4=exporters, 5=others (Specify) 39. What are the major challenges/constraint affecting the rate of your catch? Please tick and then rank with 1= Mild 2= Severe 3= Very severe. Constraints Tick Ranking Water availability/supply Electric supply Transport/Road condition Corruption/pilfering Storage Access to the fishing ground


Access to fishing inputs Credit accessibility Man-power Training Others (specify): 40. Do you sell your fish outside the country? Yes( ) No ( ) 40b.If Yes, list Species Place Quantity ( kg)

Thank you for your time

Address of Enumerator______________________________________________________ Phone Number ________________________________________ Signature &Date ____________________

163

Appendix 2: Sample questionnaire administered to the respondent aquaculture producers in

the study area

Questionnaire code /_____________ / Date of interview:_____________________ Name of Interviewer: ______________________________ Name of Enumerator: ___________________________ Date of interview: _______________________________ Checked by: __________________________________ Dear correspondent (Ethics statement), I/We am/are doing a survey on fish value chains under the Africa Fish Trade Program. . The data we collect will be only used for research purposes and will help come up with policy recommendations to improve benefits from fish trade in the country, region and Africa as a whole. We hope that you will be free to provide me/us with true and accurate data and information. Please feel free to ask any questions or raise any issues you might have. You can terminate this interview at any point should you wish so. I/We hope that I/we can come back to give the results of these surveys to your group, both for your information and your further inputs. Thank you for your participation. Interviewee details (you do not have to give me/us your name if you wish to remain anonymous) Section A. Demographic and socio-economic characteristics The questions are addressed to fish producers as respondents. SOCIO ECONOMIC CHARACTERISTICS

1. Geopolitical zone:_______________________ 2. ADP Zone: …………………………………………. 3. State …………………………. 4. Local government area…………………………………….. 5. Village/community…………………………………………. 6. Water body: Brackish ( ) Marine ( ) 7. Location of actor GPS …………………………………….. 8. Extension Planning Area …………………………………… 9. Sex: Male ( ) Female ( ) 10. Age of respondents……years 11. Marital Status: Married ( ) Single ( ) Divorced ( ) Widowed ( ) Separated ( ) 12. Religion: Christian ( ) Islamic ( ) others (specify)…………… 13. Level of Education: No formal education ( ) Primary Education

Quranic Education ( )others (specify) …….. 14. Household size: No of wife(s)……

No of children…… Male…………. Female …………….. No of other dependants…… Male………………. Female…………………

15. Group Head: Yes ( ) No ( ) 16. Did you receive any formal agricultural training? Yes ( ) No ( ) 17. If yes, where____________________, on what______________________? 18. Number of income earners in the household ……… Male …………. Female ……………. 19. What type of aquaculture farming are you engaged in?

hatchery-fingerlings ( ) Fry production ( ) Nursery-juveniles ( )

164

Fattening- table size ( ) Broodstock ( ) All of the above ( )

20. How long have you been practicing the aquaculture? Hatchery-fingerlings _____________________years Brood stock ___________________________years Fry production _________________________years Nursery-juveniles _______________________years Fattening- table size ______________________years All of the above ____________________________years

21. What species do you farm? Catfish ( ) Tilapia ( ) Others, specify………………………

22. How would you describe the scale of your operations? Commercial/Industrial production ( ) Small scale commercial/small holding ( ) Community project/cooperative ( ) Others ( specify please)…………………………………………………………………………

23. Social Assets: Membership in social groups Groups Member


Name of Group

Membership size

Benefit derived



Religious group Town union Occupational groups

Social groups Section B. Production/System/Technology 24. How many times do you produce fish in a year? ___________________________ 24b. If more than one, please indicate the periods First growing periods ______________________ to _______________________ Second growing periods ____________________ to ______________________ 25. What quantity do you produce per period? 26. What is the peak period of production? _________________ to __________________ 27. Please indicate the types of technology used in your fish production? SN Technologies

a Cost of Acquisition (Naira) Maintainance cost

1 2 3 4 a: 1-Bowl, 2-Tanks, 3-Earthen Pond, 4-Concrete Pond, 5-Flow through, 6-Recirculatory, 7-Other1 (specify)_________, and 8-Other2 (specify)_____________

165

28. Along with your production, which other business processes is included within your company’s / project’s operations? SN

Business Process a Location

b

1 2 3 4 a :1-Spawing, 2-Fry rearing, 3-Grading, 4-Grow-out, 5-Processing, 6-Packing, 7-Distribution, 8-Feed milling, 9-Cold room, 10-Others (specify)____________ b: 1-within business premises, 2-within locality, 3-other part of the state, 4-other part of country, 5-Others (specify)___________ 29. Indicate the capital equipment /asset owned for your farming activities in the last growing season and their running costs for your fish production. Equipment Quantity

(No) Date of acquisition

Cost of acquisition (N/one)

Expected life span

Cost of maintenance per week as applicable Repair Fuelling

Water Pump

Net Vat Basket Basin Concrete Pond

Dam Borehole Well Others (specify)

1. 2. 3. 4. 30. Please indicate the type of water system used and annual cost Types of water system

No of production time used in a year

Water user fees / ha/ season ( N: K)

Water user fees / ha/ annum ( N : K)

Stream/River Dam Well Borehole Municipal water/Tap Water

Others (specify) 1.

166

2. 31. Is there any treatment of effluent before it leaves the farm? ( ) Yes, ( ) No

32. Indicate equipment rented or borrowed for production in the last farming season. Equipment Quantity

Rented (in number)

Duration of usage Cost of usage ( N: K)

Other expenses incurred ( if applicable) ( N: K)

No of hour/day

No of days/week

Cost / hrs

Cost /day Repair Fuelling

Water Pump

Net Vat Basket Basin Concrete Pond

Dam Borehole Well Others (specify)

1. 2. 3. 4. Section C. Output and Inputs Used in Production 33. Please provide record of your fish production in the table below

Description Production capacity of productive assets

Earthen ponds size (m2) Concrete ponds size (m2) Other pond types

Actual production figures and average selling prices of various farm produce / products

Type of products No Avg. Weight

(kg)

Avg. Price (N)

Fingerling/juvenile sold Catfish harvested Tilapia harvested 1. Other fish type harvested:

2.

3.

167

34. Please provide record of inputs used in production in the table below Production Input Use and Costs Stock of fingerlings/juvenile reared Number Unit Cost

• Catfish

• Tilapia

• 1.Others

• 2.

• 3. Feed Used

• Commercial feeds (imported)

• Commercial feeds (local)

• Compounded feed made by the farmer

• Cost of other feeding materials: 1. (e.g. maggot)

• 2.

• 3. Water Cost (N) Veterinary Costs (N) Transportation costs (N) Other direct costs (including marketing)

35. Do you have access to credit facility for production of fish? Yes ( ), No ( ) 36. If ‘yes’ to question 31, kindly complete the table below Source of capital Collateral Amount available for

the last growing season( N)

Interest paid(%) per year

Personal Friends/relatives Cooperatives Cooperative bank Commercial bank Micro finance bank Local money lender Government Others (Specify):

168

37. Indicate the farm activities used in the production of table-size fish by gender

Activity Skilled Labour Unskilled Children

(7≤14 yrs) Adult males (≥15 yrs)

Adult females (≥15 yrs)

Children (7≤14 yrs)

Adult males (≥15 yrs)

Adult females (≥15 yrs)

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Num

ber

Hou

r/d

ay

Day

s

Wag

e ra

te/

Pond preparation

Spawning

Feeding Water Exchange/ Pumping

Marketing

Weeding Fertilizing

Medication

Harvesting

Processing

Administration

Othersspecify

1.

2.

Section D. Sales and Marketing 38. Please indicate the average quantity of fish produced by you in the last growing season Produce Peak season low-season

Quantity (kg)

Quantity ( basket)


Carton Quantity (kg)

Quantity (basket)


Carton

Fingerlings Juveniles Fry Brood

169

stock Table-size 39. In what forms and prices do you normally sell your fish after harvesting? Forms of sale Response

(yes , No ) Farm gate / producers price (N : K)

Fingerlings Juveniles Table-size – Life Table-size – Smoked Table-size – Frozen Table-size – Dried 40. Who are your most important suppliers? (Please note feed supplier brands) Supply side (place) Nature of supply 41. Who are your most important buyers? Buy side (destination /place) What do they purchase 42. Where do you sell your fish, how do they get to the market and who sells them? Fish Location/ distance of

sale (km) Transportation mode1

Sales person2 Buyer3

Home stead

Farm gate

Market Farm gate

Market Home stead

Farm gate

Market

Home stead

Farm gate

Market

Brood stocks

Fingerlings Juveniles Table-size Others-1

Others-2

*Note: writing down distance (km) indicates someone sells product at that location if not it should be left blank 1 1=by foot, 2=bicycle, 3=motor cycle, 4=motorized vehicle, 5=animals (i.e. donkey), 6=others specify ____________________________________________ 2 1=husband, 2=wife, 3=other adult male, 4=other adult female, 5=male child, 6=female child 3 1=direct consumer, 2=processors, 3=local traders, 4=exporters, 5=others (Specify)

170

43. Do you buy, sell or export through Benin border? Yes ( ) No ( ) If yes fill this table Species/ common name Quantity Price

44. What are the major challenges/constraint affecting the growth of your production? Please list and then rank according to severity with 1=Mild 2= severe.3=Very severe Constraints Tick Ranking Water availability/supply Electric supply Transport/Road condition Corruption/pilfering Storage Land accessibility Credit accessibility Man-power Training Others (specify): Others

Thank you for your time Address of Enumerator___________________________________________________ Phone Number ________________________________________ Signature &Date ____________________

171

Appendix 3: Sample questionnaire administered to the respondent fish processors in the study

area

Name of Enumerator: Date of interview: Checked by: Dear correspondent (Ethics statement), I/We am/are doing a survey on fish value chains under the Africa Fish Trade Program. . The data we collect will be only used for research purposes and will help come up with policy recommendations to improve benefits from fish trade in the country, region and Africa as a whole. We hope that you will be free to provide me/us with true and accurate data and information. Please feel free to ask any questions or raise any issues you might have. You can terminate this interview at any point should you wish so. I/We hope that I/we can come back to give the results of these surveys to your group, both for your information and your further inputs. Thank you for your participation. Interviewee details (you do not have to give me/us your name if you wish to remain anonymous) DEMOGRAPHIC AND SOCIO ECONOMIC CHARACTERISTICS

1. Geopolitical Zone ………………………State …………………………. 2. Local government area…………………………………….. 3. Village/community……………………………………Group Head

………………………. 4. Location of actor GPS …………………………………….. 5. ADP Zone …………………………………… 6. Sex: Male ( ) Female ( ) 7. Age of respondents……years 8. Marital Status: Married ( ) Single ( ) Divorced ( ) Widowed ( ) Separated ( ) 9. Religion: Christian ( ) Islamic ( ) others (specify)…………… 10. Level of Education: No formal education ( ) Primary Education Tertiary ( )

Quranic ( ) others (specify) …….. 11. Household size: No of wife(s)……

No of children…… Male…………. Female …………….. No of other dependants…… Male………………. Female…………………

12. Did you receive any formal agricultural training? Yes ( ) No ( ) 13. Number of income earners in the household …………. Male …………. Female

……………. 14. Membership in social groups

Groups Member


Name of Group

Benefits Indicate the activities



Religious group Town union

172

Occupational groups Social groups

15. What type of fish do you produce? Smoked ( ), Dried ( ), Frozen ( ) Spiced( ), Others

specify……………… 16. At what scale of processing do you operate? Small-scale=1 ( ), medium-scale=2 ( ),

large-scale=3( ) 17. Do you import/ export your produce directly? Yes ( ) No ( ) 18. If yes from where ? ………………………………

Export Species

Place Quantity(kg) Import Species

Place Quantity (kg)

19. How long have you been in fish processing?

Small-scale……………..years Medium-scale………… years

Large-scale…………… years Section B. Processing/System/Technology 20. Are there peak and low periods in fish processing? Yes ( ) No ( ) If Yes, a. When is the peak period _____________ to _________________ b. When is the low period ______________ to _________________ 21. What type of fish do you buy for processing? 1. Catfish ( ), 2. Tilapia ( ), 3. Croaker ( ), 4. Imported fish ( ), 5. Others (specify)________ 22. What processing method(s) do you use? SN Fish Processing a Location b 1 2 3 4 a :1-Brining, 2-Drying, 3-Smoking, 4-Pepper/Smoking, 5-Frying, 6-Sun drying, 7-Spicing, 8-Cooling, 9-Others (specify)__________ b: 1-within business premises, 2-within locality, 3-other part of the state, 4-other part of country, 5-Others (specify)___________

173

23. How did you acquire your processing equipment? Method of acquisition

s

Type a

Installation capacity

(tons)

Date of acquisiti

on

Number of

machine

Cost of acquisition (N)

Rent (N) Maintenance

Cost Owned Hour

ly Daily

Monthly

1)

2)

3)

4)

Rented 1)

2)

3)

4)

Given/ Inherited

1)

2)

3)

4)

Note a: Rafter-1, Drum oven-2, Mud oven-3, Charcoal oven-4, Open dug pit-5, Chorkor kiln-6, Electric dryer-7, Solar dryer-8, Gas oven-9, Cool Room-10, Deep Frezer-11

Section C. Input Used in Processing 24. How did you acquire the place you are using for your processing operations? Method of acquisitions

Cost of land acquisition

Cost of building

Cost/month if rented

Expected life span Cost of maintenance

Owned Rented Given/inherited

25. How many Kilogram of fish can your machines process per hour…………, per

day…………………., per week…………………per Month………………………, per cycle_________________

26. Provide the quantity and cost of fish processed below

Product a

Avg. Quantity / month (kg)

Unit cost (N)/kg

Cost per Month

a: 1- Catfish, 2-Tilapia, 3-Croaker, 4-Imported fish, 5-Others (specify)________ 27. What type of packaging do you use? _____________________________ 28. How much do you spend on packaging per day_____________, per

month_______________(Naira) 29. What is the source(s) of power to your processing equipment? ( ) Charcoal, ( )

Firewood, ( ) Petrol, ( ) Diesel, ( ) Electric supply SN Types A Cost Per Production Cycle Cost Per Month 1 2 3 4 5

Note: Charcoal-1, Firewood-2, Petrol-3, Diesel-4, Electric supply-5 Please indicate your own production cycle e.g no of weeks/ month

30. Do you have a generator of your own? Yes ( ) No ( ). If yes complete the following below... Date of Acquisition

Capacity of generator

Cost of Acquisition

Expected life span

Cost of maintenance (N) Monthly repair Fuelling per week

31. How much do you pay on electricity bill per month on the processing equipment? N ______________ 32. How many days do you operate in a week? _________________ 33. Do you have access to credit? Yes ( ) No ( )

175

34. If yes in question 33, fill the following table accordingly. Source of capital Amount (N: K) Interest paid

per year Year collected Pay back

year Personal savings Friends/ relatives Cooperatives Community Bank Microfinance bank Commercial bank Cooperative bank

Local money lender Government 35. How many hours do you work in a day? ___________________ 36. How many workers do you have, please specify: _____________________

Professional Unskilled Children

<15 years

Adult Male >15

years

Adult Female >15

years

Children <15 years

Adult Male >15 years

Children <15 years

Number Monthly pay/person

Weekly pay/person

Daily Pay/ person

Hourly pay/person

Section D Sales and Marketing 37. In what forms and prices do you normally sell your fish after processing? Forms of sale a Response (yes = 1,

No = 0) Farm gate / producers price (N : K)

smoked fish dried fish frozen fish spiced fish others (specify 38. Please indicate the average quantity of fish produced by you in the last month Products a Peak season low-season

Quantity (kg)

Unit price


Quantity (kg)

Unit price


Smoked fish, Sun-Dried fish, Frozen fish, Spiced fish, Others (specify):_____________

176

39. What were the total value of fish processed in a month?

Products a

No Avg. Weight Price (N/kg)

a 1= smoked fish, 2=dried fish, 3=frozen fish, 4=spiced fish, others (specify):_____________ 40. Who are your most important suppliers? Supply side Nature of supply 41. Who are your most important buyers? Buy side What do they purchase? 42. Along with your processing activities, which other business processes are included within your business’s operations? SN Business Process a Location b 1 2 3 4 5 6 1-Spawning, 2-fry rearing,3-grading, 4-Grow-out, 5-Packing, 6-Distribution, 7-Feed milling, 8-Cold room/ freezing, 9-Others (specify)____________ b: 1-within business premises, 2-within locality, 3-other part of the state, 4-other part of country, 5-Others (specify)___________

177

43. What are the major challenges/constraint affecting the growth of your production? Please tick and then rank with 1=Mild 2=Severe 3=Very severe Constraints Tick Ranking Water availability/supply Electric supply Transport/Road condition Corruption/pilfering Storage Land accessibility Credit accessibility Man-power Training Others (specify): Others

This is the end of the questionnaire. Thank you for your time and wish you a very nice day.

Address of enumerator ………………………….. Signature and date ……………………………

Phone No …………………………………………….

178

Appendix 4: Sample questionnaire administered to the respondent fish traders in the study

area

Name of Enumerator: Date of interview: Checked by: Dear correspondent (Ethics statement), I/We am/are doing a survey on fish value chains under the Africa Fish Trade Program. . The data we collect will be only used for research purposes and will help come up with policy recommendations to improve benefits from fish trade in the country, region and Africa as a whole. We hope that you will be free to provide me/us with true and accurate data and information. Please feel free to ask any questions or raise any issues you might have. You can terminate this interview at any point should you wish so. I/We hope that I/we can come back to give the results of these surveys to your group, both for your information and your further inputs. Thank you for your participation. Interviewee details (you do not have to give me/us your name if you wish to remain anonymous) INSTRUCTIONS: Tick appropriate options and write appropriate answers, where options are not available. It should be noted that all information be will treated with utmost confidentiality. DEMOGRAPHIC AND SOCIO ECONOMIC CHARACTERISTICS

1. Geopolitical Zone …………………………….. 2. ADP Zone…………………………………… 3. State ……………………….. 4. Location of actor GPS ………………………………….. 5. Local government area ………………………………….. 6. Sex: Male ( ) Female ( ) 7. Age of respondents……years 8. Marital Status: Married ( ) Single ( ) Divorced ( ) Widowed ( ) Separated ( ) 9. Religion: Christian ( ) Islamic ( ) others (specify)…………… 10. Level of Education: No formal education ( ) Primary Education Tertiary Education ( )

Quranic ( ) Others (specify) …….. 11. Household size: No of wife(s)……

No of children…… Male ………. Female …………… No of other dependants…… Male…………….. Female ……………

12. Group Head 13. Did you receive any formal agricultural training? Yes ( ) No ( ) 14. Number of income earners in the household. ……… Male ……………. Female

………………….

15. What type of fish do you sell? Fresh/Live ( ), Smoked( ), Dried ( ), Frozen ( ) Spiced( ), Others specify………………

16. At what level of market do you operate? Wholesale level ( ) Retail level ( ) 17. Do you import your produce directly? Yes( ) No ( ) 18. How long have you been in fish marketing?…………years

179

19. Social Assets: Membership in social groups

Groups Member


Name of Group

Benefits Indicate the activities



Religious group Town union Occupational groups Social groups 19. Are there peak and low periods in fish marketing? Yes ( ) No( ) a. When is the peak period _____________ to _________________ b. When is the low period ______________ to _________________ 20. What marketing method(s) do you use? SN Business Process a Location b 1 2 3 4 5 6 a :1-Hawker, 2-Neighborhood store, 3-Central Market store, 4-Stall, 5-Cold room operator, 6-Others (specify)__________ b: 1-within locality, 2-other part of the state, 3-other part of country, 4-Others (specify)___________ Section C. Input Used In Marketing Activities 21. How did you acquire this place you are carrying out your operations?

Method of acquisitions

Cost of land

acquisition

Cost of building

Cost/month if rented

Expected life span

Cost of maintenance

Owned Rented Given/inherited 22. Do you have a generator of your own? Yes ( ) No ( ). If yes complete the following below... Date of Acquisition

Cost of Acquisition

Expected life span

Cost of maintenance (N) Capacity of generator Monthly repair

Fuelling per week

23. Do you have your own means of transportation? Yes ( ), No ( )

180

24. If yes to question 23, in what form? Forms Number Year of

acquisition Cost of acquisition (N)

Expected life span (years)

Maintenance cost per (N) Repairs/month Fuelling/week Other

cost Animal Trekking (distance in Km)

Pick-up Van

Lorry Motor-bike

Trekking Bicycle 25. Indicate the source and what you use including the cost of getting your products to those destinations. Source Distance

(km or Mile) Method and cost of transportation of stock per day. By head (N)

Bicycle (N)

Motor bike (N)

Pick-up (N)

Lorry (N)

Animal (N)

From farm to store

From farm to local periodic market

From farm to local market

From farm to urban market

From processor to store

26. Do you make use of electricity in your store/shop? Yes ( ) No ( ) 27. If yes to question 26, how much is your monthly electricity bill with respect to your store/ shop? N ……………………………………... 28. Do you use fuel (petrol/ diesel)? Yes ( ) No ( ) 29. If yes to question 28, how much do you spend on fuel in a week N………………………………., in a month N ……………………………….? 30. How many days do you operate in a week ----------------------month--------------------------? 31. Do you have access to credit? Yes ( ), No ( ) 32. If yes to question 31, fill the following table accordingly. Source of capital Amount Interest paid

per year Year collected Pay back year

Personal savings Friends/ relatives Cooperatives Commercial bank Micro-finance bank Community bank

181

Cooperative bank Local money lend Government 33. Do you preserve your stored produce? Yes ( ) No ( ) 34. If yes to question 35, please complete the table below…. Chemical Quantity / volume / month Period of storage

( days/ months/ years)

Cost ( N: K) Kg Litre Other

measures Kg Liter Other

measure Fungicides Pesticides Insecticide Smoking/Drying Cooling Specify others i ii

35. How many hours do you work in a day __________week __________month_________? 36. How many workers do you have, please specify: ____________________ Professional Unskilled

Children <15 years


Adult Female >15 years

Children <15 years


Children <15 years

Number Monthly pay/person

Weekly pay/person

Daily Pay/ person

Hourly pay/person

Section D. Sales and Marketing 37. A) What species of fish do you sell?

Producta

Avg. Quantity / month (kg)

Unit cost (N)/kg

Cost per Month

a: 1- Catfish, 2-Tilapia, 3-Croaker, 4-Imported fish (Alaran, Express e.t.c), 5-Others (specify)________

182

38. In what form do you buy your fish? Forms of purchase

Quantity (week [ ], month [ ] )

Price at local market (N) Price at the central market (N)

Kg Bag Local measure



Fresh/Life

Smoked

Dried

Frozen

Spiced

Others (Specify)1 :

2:

Indicate the local measure 39. In what form do you sell your fish? Forms of purchase

Quantity sold per week Price ( N: K) Kg Bag Local measure Per Kg Per Bag Per

Local measure

Fresh/Life

Smoked

Dried

Frozen

Spiced

Others (Specify) 1:

40. Who are your most important suppliers? Supply side (including place) Nature of supply

Fresh Dried Smoked Frozen Others (Specify)

183

41. Who are your most important buyers? Buy side (including place) What do they purchase?

Fresh Dried Smoked Frozen Others (Specify)

42. Along with your marketing activities, which other business processes are included within your company’s / business’s operations? SN Business Process a Yes/no Location b Yes/no 1 2 3 4 a :1-Spawning, 2-Fry rearing, 3-Grading, 4-Grow-out, 5-Processing, 6-feed milling, 7-Others (specify)__________________________________ b: 1-within business premises, 2-within locality, 3-other part of the state, 4-other part of country, 5-Others (specify)___________________________________ 43. What are the major challenges/constraint affecting the growth of your business? Please tick and then rank Constraints Tick Mild Severe Very Severe Water availability/supply Electric supply Transport/Road condition Corruption/pilfering Storage Land accessibility Credit accessibility Man-power Training Others (specify) 1:

2:

Thank you for your time

Address of Enumerator___________________________________________________ Phone Number ________________________________________ Signature &Date ____________________

184

Appendix 5: Sample questionnaire administered to the respondent fish consumers in the study

area

Questionnaire code /_____________ / Date of interview:_____________________ Name of Interviewer:______________________________ Dear correspondent (Ethics statement), I/We am/are doing a survey on fish value chains under the Africa Fish Trade Program. . The data we collect will be only used for research purposes and will help come up with policy recommendations to improve benefits from fish trade in the country, region and Africa as a whole. We hope that you will be free to provide me/us with true and accurate data and information. Please feel free to ask any questions or raise any issues you might have. You can terminate this interview at any point should you wish so. I/We hope that I/we can come back to give the results of these surveys to your group, both for your information and your further inputs. Thank you for your participation. Interviewee details (you do not have to give me/us your name if you wish to remain anonymous) Section A. Demographic and socio-economic characteristics 1. State: ………………Village ………………………. GPS location…………………………. 2. Geopolitical Zone ……………………………Local Govt. Area ……………………………… 3. Sex: Male ( ), female ( ) 4. Marital status: Married ( ) single ( )Divorced ( ) Widowed ( ) 5. Age: ________(years) 6. Religion: Christianity ( ), Muslim ( ), Traditionalist ( ) , others species ( ) 7. Type of Education: No formal ( ),Koranic ( ) Adult literacy training ( )Primary ( ) Secondary ( ) Tertiary( ) Others ( ) ______________________________ 8. Number of years of education______ 9. Did you receive any formal agricultural training Yes ( ) No ( ) 10. Household size_____________ 11. Number of income earners in the household _______________________ 12. What type of aquaculture produce do you consume? Catfish ( ) Tilapia ( ) Croaker ( ) Imported Fish ( ) Others (specify) ( ) 13. What influences your choice of fish consumed? __________________

Influence Tick Ranking

Price

Nutritional Value

Taste

Availability

Accessibility

185

Others specify

Rank from 1 as the most important. Rank= 1,2,3 … 14. Where do you buy your fish for consumption, what quantity and at what price?

15. In what form do you normally buy your fish for consumption and at what price?

16. How many times do you consume fish in a month? ___________ 17. How much fish do you buy per consumption? _______________ 18. Do you always get the type of fish you want when it is needed? Yes ( ), No ( )

19. If Yes to question 18, proceed to question 20; if No, what are some of the constraints? Please specify: _____________________________________________________________

____________________________________________________________________ 20. Do you always get the quantity of fish you require when they are requested for?

Yes ( ) , No ( ) 21. If No, what are some of the constraints? Please specify:

__________________________________________________________________________________________________________________________________________

Fish Type Quantity (kg) Home stead Farm gate Market Price (N) / kg Catfish Tilapia Croaker Imported Fish Others:

Fish Type Quantity (kg) Fresh Smoked Dried Frozen Others Price (N) / kg Catfish Tilapia Crocker Imported Fish

Others:

186

22. What are the major challenges/constraints affecting how you consume fish? Please list and then rank with 1 being the most severe. Constraints Tick Ranking Perception of severity

b

Fish Availability Fish Accessibility Price of fish Poor fish handling Fish Packaging Household Income Others (specify):

Note: Rank from1= most important to less important

Thank you for your time Address of Enumerator …………………………………………………………..

Phone Number…………………………………………………………… Signature and Date …………………………………………………………

187

APPENDICES

Plate 1: Typical setting of Catfish Market in Kwara State

188

Plate 2: Cross-section of fishermen involved in Group discussion in Ogun State

189

Plate 3: Tradition Fish Processing facility in Kwara State

190

Plate 4: Fish Farm Estate at Ikorodu, Lagos State

VALUE CHAIN ANALYSIS OF FISH TRADE ALONG NIGERIA … · 3.4.7 Market Structure 21 3.4.7.1 Ease...

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