Structural Performance of Artisanal Fish Marketing in Ondo State, Nigeria

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The study was carried out in Ilaje and Ese-Odo Local Government areas of Ondo State, Nigeria. These areas were selected for the study because of their suitability for fishing activities as they are close to rivers where fishes are always available for consumption.

2.1.1. Data Sources and Collection

Data collected for the purpose of this study were gotten from primary source through the use of well-structured questionnaires. As a result of low literacy rate of farmers, trained enumerators, who understood the local dialects, were used to administer the questionnaire on the artisanal fish marketers. Multistage sampling technique was employed in the selection of the respondents in the study area. In the first stage, purposive sampling technique was used to select two Local Government Areas (Ilaje and Ese-Odo LGAs) based on the predominance of fishing activities in these areas. The second stage featured random sampling technique to select five (5) fishing communities from each of the selected Local Government areas. The fishing communities selected are Igbokoda, Ayetoro, Orioke-Iwamimo, Araromi-seaside and Mahintedo from Ilaje, while Igbekebo, Ipoke, Agadagba Oboh, Igbotu and Kiribo are the fishing communities selected from Ese-Odo. The third stage also involved the random sampling technique to select 25 artisanal fish sellers from each of the ten selected communities totaling 250 respondents.

2.1.2. Analytical Techniques

Descriptive statistics such as frequency and percentage were used to analyze the socio-economic characteristics of the artisanal fish marketers and problems facing them. Budgeting analysis such as gross margin, net return and marketing margin analysis were used to analyze the profitability of artisanal fish marketing in the study area. Concentration ratio, Gini-coefficient, Lorenz curve and Herfindahl index were used to measure the market structure. Operational efficiency was also used to analyze efficiency growth. The gross margin is mathematically presented as

(1)

where GM=Gross Margin,

TR=Total Revenue,

TVC=Total Variable Cost.

Net returns are also given as;

(2)

where TR=Total Revenue,

TC=Total Cost.

The measures of market structure are presented as follows;

(3)

Where, CRi = Concentration ratio for first i firms

S_i = Share of the largest i firms in the industry

S_n = Share of the n firms in the industry

i = 1, 2, 3, …, n

n = number of respondents ^{[19, 20, 21]}.

(4)

where i= 1, 2, 3,…, n,

HI = Herfindahl Index

n=number of respondents,

S= share of firm in the industry.

(5)

G = Gini-coefficient

A = Area that lies between the line of equality and the lorenz curve

A+B= Total area under the line of equality.

Lorenz curve measures the degree of inequality that exists in the share of the industry’s market size by its firms. It relates the total volume of product handled in a market to the percentage of firms in the market cumulated from the smallest to the largest. The curve bows outwards towards the southeast when there is inequality in the market share of the firms.

3. Results and Discussion

3.1. Socio-economic Characteristics
3.1.1. Age of the Respondents

Table 1 shows the age distribution of the respondents in the study area. The results revealed that the respondents with age range of 31-40 years had the highest frequency with 37.6%. This is followed by the respondents with age range of 21-30 years old with 27.2%. The respondents with 51 years old and above constituted 10% of the total fish marketers sampled for the study. This implies that majority of the respondents between the ages of 21 and 40 years old, who are young and agile, involved in artisanal fish marketing in the study area.

Table 1. Age Distribution

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3.1.2. Gender Distribution of the Respondents

The gender distribution of the respondents as shown in Figure 2 indicates that 78% of the respondents were female, while the remaining 22% were male. This indicates that majority of the artisanal fish marketers were females which is in accordance with the a priori theory that marketing is the business of females in the study area.

Figure 2. Gender distribution of the respondents.

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3.1.3. Marital Status of the Respondents

The results as shown in Figure 3 indicate that about 79.2% of the respondents were married, while just 10.4% were single. Also, the results revealed that 3.6% and 6.8% of the respondents were divorced and widowed respectively. This means that majority of the artisanal fish marketers in the study area were married. This will afford them the opportunity of getting family labour to be used for fish marketing. The low percentage of the divorced could be attributed to the value attributed to the marriage institution in the study area.

Figure 3. Marital distribution

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3.1.4. Level of Education of the Respondents

The distribution of level of education as shown in Table 2 shows that about 41.6% of the respondents, who were involved in artisanal fish marketing, had primary education, while 24% had secondary education. It equally revealed that 19.2% of the respondents had no formal education as just 15.2% had tertiary education. This implies that majority of the farmers in the study area had one form of education or the other which could assist them in the area of adoption of innovations brought to them by the extension agents and in making decisions that will enhance their marketing strategies.

Table 2. Level of Education

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3.1.5. Family Size of the Respondents

Table 3 shows that 44.8% of the respondents had between 4 and 6 household members, while 16.8% of the respondents had between 1 and 3 household members. Also, about 15.2% of the respondents had between 7 and 9 household members, while 12% had between 10 and 12 household members. This implies that majority of the respondents would have access to people who can assist in carrying out their marketing activities, thereby increasing their opportunity of having improved revenue.

Table 3. Family Size

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3.1.6. Major Occupation of the Respondents

Table 4 shows that about 36% of the respondents had fish marketing only as their major occupation, while 32.8% of the respondents indicated fish processing and marketing as their major occupation. The results further showed that 18.4% of the respondents involved themselves in only fish processing, while the remaining 12.8% indicated civil service work as their major occupation. This implies that the respondents with highest frequency (36%) were fish marketers only. This may not be okay enough for them if there is a problem with fish marketing, since the respondents do not have diversification of means of livelihood.

Table 4. Major Occupation

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3.1.7. Experience of the Respondents

The distribution of fish marketing experience of the respondents as shown in Table 5 revealed that 28.4% of the respondents had less than 5 years of fish marketing experience followed by 22.8% of the respondents who had between 6 and 10 years fish marketing experience. The results also showed that about 17.6% of the respondents had between 16 and 20 years’ experience, while another 17.6% had above 20 years fish marketing experience. Therefore, this means that the respondents with highest frequency of 28.4% were relatively new in the business. This could be due to the fact that marketers have just entered the artisanal fish marketing because of some reasons which may include the profitability of the business.

Table 5. Experience

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3.1.8. Source of Finance

Table 6 shows the distribution of source of finance of the respondents in which about 34.4% of the respondents had their source of finance from personal savings, while 28.8% indicated cooperative and “Esusu” as their source of finance. About 17.2% of the respondents also indicated that their source of finance came from friends and relations, while just 14% showed banks as their source of finance. The low percentage of the respondents who indicated banks as their source of finance could be as a result of the inability of the marketers to meet up with the collateral security required by the financial institutions. Therefore, it can be concluded that artisanal fish marketers may not be able to expand their business since majority of them depend on personal savings and cooperative societies where small amount of money could be gathered.

Table 6. Source of Finance

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3.1.9. Constraints Facing Artisanal Fish Marketers

The distribution of constraints facing artisanal fish marketers in the study area as shown in Figure 4 indicates that about 40% of the respondents identified high cost of transportation as the constraint facing them in the marketing of fish. Also, about 23.6% of the respondents indicated inadequate fund as the constraint facing their fish marketing activities, while 20% of them identified poor transport network as the problem facing them. This could be the reason for the inability of the artisanal fish marketers to attain better profit margin compared to what they were having.

Figure 4. Constraints facing artisanal fish marketers

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3.1.10. Profitability Analysis of the Respondents

Table 7 presents profitability analysis with respect to Gross margin and Net returns of the respondents. The variable costs include cost of purchase, cost of transportation, labour cost and other operating expenses, while fixed costs covered cost of implements and interest on loan. The results showed that the mean revenue of the fish sellers was N175,296,274.4 ($1,095,601.7), while the mean total variable cost was N98,424,781 ($615,154.9). Also, the average fixed cost and average total cost were N3,468,564.70($21,678.5) and N101,893,345.7 ($636,833.4) respectively. The gross margin per kg realized by the artisanal fish marketers was N143.58($0.89), while average net-return of the fish marketers in the study area per kg was N137.10($0.85). This implies that artisanal fish marketing in the study area is profitable. Therefore, people are advised to go into this business so as to make a living.

Table 7. Profitability Analysis

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3.1.11. Analysis of Measure of Market Structure

Artisanal fish marketers have some basic functions which include buying, selling, financing, risk bearing and merchandising. The results showed that there were no product differentiations. Also, the prices of fish were determined through bargaining powers of the parties involved (buyers and sellers) since there is non-uniformity of the prices of fish in the study area. As shown in Table 8, the two largest marketers in the artisanal fish marketing business accounted for 25% of the volume of fish sold in the study area. The largest four marketers for 39% of the volume of marketed fish, while the largest eight marketers accounted for 49%. This indicates that the concentration in the industry can be said to be too low. The value of the Herfindahl index estimated was 0.05 which implies some degree of concentration in the industry. The estimated value of the Gini-coefficient determined was 0.64 which means that there was inequality in the share of the market. The value of the Gini-coefficient would have been zero if there was equality in the share of the market.

Table 8. Summary of Concentration Indexes

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3.1.12. Operational Efficiency of Artisanal Fish Marketers in the Study Area

The mean operational efficiency of the Artisanal Fish Marketers was 15.5% which implies that there was no significant difference in operational efficiency of the respondents.

Table 9. Computation of Gini-coefficient for artisanal fish marketing in the study area

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Area between the line of perfect equality and the Lorenz Curve (A) = 0.5-0.182 = 0.318

Total area under the line of equality (A+B) = 0.5

Gini-coefficient

Gini coefficient = = 0.636 = 0.64

Figure 5. Lorenz curve for the artisanal fish marketers

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