Citation of this paper |
A study was conducted to characterise existing rural smallholder poultry marketing systems in four villages of Malingunde Extension Planning Area (EPA) in Lilongwe West Rural Development Project (RDP) in Malawi. 147 households were selected through a two - stage cluster sampling procedure from Ishmael, Mankhanga, Sinyala and Kalonga II villages. A survey was done to determine market players, marketing channels, household selling decisions and marketing margins.
The major constraints in rural chicken marketing were identified as low prices (72.0% of the respondents), low marketable output (57.3% of respondents) and long distances to reliable markets (26.6% of the respondents). Farmers' decision to sell chickens was significantly affected by the source of chickens sold and the number of chickens lost. The study also showed that there are three main frequently used chicken marketing channels as follows: 1) direct producer to consumer selling (PC channel); 2) rural assembler selling to retailers for final selling to consumers (RA-R channel) and 3) assembler-retailer (AR channel) where assembly and retailing functions were integrated. The total channel margin generated as a proportion of the producer price was 100%, 75.6% and 28.7% in the PC, RA-R and AR channels respectively. Transport costs constituted the major marketing cost item.
It is suggested that chicken and egg marketing of rural chicken farmers can be improved through formation of marketing groups and training of farmers in enterprise development.
Key words: Chickens, marketing, smallholders
While efforts have been taken to promote rural poultry production in Malawi, the performance of chickens under rural conditions has generally been poor as evidenced by slow growth rates, small body size and low hatchability (Safalaoh 1997); low egg production averaging 40 eggs per annum and high mortalities recording up to 90% due to new castle disease (Government of Malawi 1999). Research in promotion of livestock production has concentrated on improvements in management while ignoring the potential role of socio-economic issues, such as marketing.
Amir and Knipscheer (1989) reported that farmers tend to ignore new technology even when it appears to be better than their current practices due to market limitations. Farmers allocate resources according to relative returns realised from producing for the market or for home consumption (Orr, Mwale and Saiti 1999). This implies that that apart from meeting subsistence needs, engagement and level of investment of smallholder farmers in agricultural enterprises responds to existing market opportunities. Efforts to improve management of poultry should therefore be complemented by a supportive marketing system. The present study was therefore carried out to characterise existing rural smallholder poultry marketing systems in Malawi with three specific objectives: 1) to identify key players, marketing channels and marketing constraints in the rural poultry marketing system in Malawi 2) to identify factors affecting chicken selling decision at household level and 3) to suggest strategies that can be used to improve rural smallholder poultry marketing in Malawi.
The research was conducted in Malingunde Extension Planning Area (E.PA) under Lilongwe West Rural Development Project (RDP) in the Central Region of Malawi. The study site was purposely selected to provide institutional support to the Malawi Smallholder Poultry Production Model (MSPPM) that was being tested in its pilot phase. The study involved four villages; Ishmael Village (model village), Mankhanga and Kalonga II as control villages.
Management interventions in the model village included provision of a loan to targeted women farmers who were organised into functional groups according to the model's production chains. Key Rearers, forming the largest proportion of the farmers, were provided with 5 Hyline or Black Australorp pullets at point of lay to produce eggs for sell. Model Breeders were responsible for production of fertile eggs for hatching using Black Australorp cocks and Hyline hens. The hatching eggs were sold to Key Rearers for brooding through natural incubation using the three local hens. Poultry Workers were involved in selling feed and drugs to the farmers while Egg Sellers were involved in buying eggs from the Key Rearers for sale to consumers.
A Two-Stage Cluster Sampling and Simple Random Sampling techniques were used to select sample households in the control and model villages respectively using a list of farmers prepared by the Assistant Veterinary Officer (AVO) and the Village Livestock Development Committee members.
Data from 60 households from the model village and 87 households from control villages were collected for the individual farm level interviews using structured questionnaires. The Rural Rapid Appraisal technique was used to identify key categories of traders and physical pattern of commodity flow using semi structured questionnaires. A total of 68 households were used (33 households from Ishmael village and 35 households from the control villages of Mankhanga and Kalonga II) during the marketing monitoring phase. The farmers were selected based on their willingness to participate in the study.
Marketing Margin and Total Gross Marketing Margins were estimated with the Microsoft Excel package using equations [1] and [2] below (Amir and Knipscheer 1989):
MM = {(S P- B P) ¸ F C P}* 100…[1] |
TGMM ={(FCP-FP)÷FCP}* 100....[2] |
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|
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SP = selling price at each level |
FP = Farmer’s price (MK). |
BP = Buying price at each level; and |
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FCP= final consumer price |
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SPSS Version 11.0 (2001) was used to generate descriptive statistics in order to explain observed market performance. Because of the dichotomous nature of the response variable, a Logit model was used to determine factors that influence occurrence or non-occurrence of chicken sales at household level in the year 2000. The dependent variable (Sellchick) was equal to one, if the household had sold any chickens, and zero if it had not (Gujarati 1988; Maddala 1988). Model precision was assessed through a multicolinearity test for model variables. The GLM procedure of Statistical Analysis System Institute (SAS), Version 6.12 (1985) was used to analyze variance in chicken and egg sales volume and margin between model and control villages.
Exchange organization defines the structure of the market in terms of nature of marketing chains, bargaining relationships, prices paid for products and functions performed by various participants in the marketing system. Figure 1 below summarises the chicken marketing channels used in the study area.
Figure 1: Chicken marketing
channels
As is evident in Figure 1, transactions handled by traders fall into two major categories; transactions occurring between traders as rural assemblers constituting 29.6% of the traders' total transactions and those between traders and consumers as assembler-retailers (55.6%). Rural assemblers are involved in accumulating supplies from producers for re-sale to retailers mostly in urban markets. Assembler-retailers concentrate supplies from producers in the rural assembly markets for final selling to consumers mostly in urban markets. About 15% of the traders' transactions are carried out with restaurant operators. Some rural assemblers forge contracts with urban retailers to supply chickens.
Most farmers sell chickens in markets within their vicinity. This can be attributed to the small number of chickens offered for sale, long distances to the high-demand urban and peri-urban markets and that selling of chickens is occasional and based on prevalent pressing needs. Small quantities of chickens offered for sale restrict most farmers to take advantage of spatial arbitrage (Shepherd 1997). As such, transaction costs and opportunity cost of time for the farmers to mediate exchange are high since their output levels are low. As a result of high transaction costs, an individual group of people or company can gain unfair advantage at the expense of others (Upton 1996). With knowledge of good markets and the profitable opportunities envisaged, rural assemblers and itinerant traders concentrate their time and resources in spatial arbitrage. Farmers can therefore exploit other rewarding market avenues in high-demand urban areas if they sell large numbers of chickens through economies of scale that may reduce marketing expenses appreciably.
The three major constraints in marketing village chickens were identified as low prices (72.0% of the respondents), low marketable output (57.3% of respondents) and long distances to reliable markets (26.6% of the respondents (Table 1).
Table 1. Chicken marketing constraints in traditional village markets |
||
Constraint |
n=147 |
Percent |
103 |
72.0 |
|
Low marketable output |
82 |
57.3 |
Reliable markets very far |
38 |
26.6 |
Limited market outlets |
23 |
16.1 |
Lack of buyers |
13 |
9.1 |
Disease outbreaks |
12 |
8.4 |
No problem |
11 |
7.7 |
Lack of marketing information |
4 |
2.8 |
Theft |
1 |
0.7 |
Lack of capital |
1 |
0.7 |
Constraints that farmers face in chicken marketing have been attributed to the nature of the production system. Minga et al (2000) reported that the nearly zero-input extensive husbandry system, to which free-range local chickens are subjected, cannot be expected to have any significant output The supply of indigenous chickens is therefore frustrated by absence of adequate quantities under the low management regimes typical of the smallholder farming sector (Kusina and Mhlanga 2000). The low marketable output generates limitations to explore other distant but rewarding markets due to high transaction costs arising from high transportation costs and time involved. Consequently, chickens are sold within the villages where market outlets tend to be limited and trader cartels erode their bargaining power. The prices, which markets generate, are the means through which they determine what and how much is produced from finite resources, which methods are used in production and how products are distributed (Scarborough and Kydd 1992). Therefore, access to input and output markets by rural households needs to be improved so that they can be assured of reasonable prices for the wide range of products from which they earn a living (Debrah and Sissoko 1992).
A Logit model was run to determine factors that affect chicken selling decisions in the traditional poultry marketing system (Table 2).
Table 2. Factors affecting farmer chicken marketing decisions |
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Parameter |
Coefficient |
SEE. |
T-Statistic |
Household head |
-.23187 |
.23811 |
-.97378 |
Literacy |
.05948 |
.21078 |
.28221 |
Flock source |
.37182 |
.20279 |
1.83358* |
Price |
.00120 |
.00241 |
.49658 |
Chickens lost |
-.01737 |
.00789 |
-2.20273* |
Food availability |
-.01471 |
.03945 |
-.37301 |
Constant |
-4.34878 |
.50096 |
-8.68089** |
Pearson Goodness-of-Fit Chi Square |
=244.561 |
Df=134 |
P= 0.001** |
* P<0.05, ** P<0.001 |
The number of chickens lost from a flock was negatively related to the likelihood of selling some. As increasing numbers of chickens are lost, the farmers' inclination is to spare survivors so that a new flock is re-established. In Malawi, chicken losses under village conditions are primarily due to NewCastle disease, and predation (Kampeni 2000; Safalaoh 1997). The predisposition not to sell is a deliberate decision to spare survivors from a diminished flock which is driven by the expectation of a future shock to be drawn upon in times of need. Nyange (2000) reported that most farmers market their chickens when they feel there are too many while others sell chickens regularly to meet their financial requirements. A pressing cash need must arise to warrant sale of chickens. High productivity through high reproductive efficiency, high growth rates and reduced mortality rate is a pre-requisite to attain increased numbers that would yield considerable surplus for home consumption and for sale.
The bulk of the chickens sold by farmers is sourced from own flocks. Fafchamps (1999) reported that households might build up liquid reserves that can be sold or consumed in times of need or in anticipation for future shocks. Farmers are inclined to sell chickens from their own flock to take advantage of the cash benefits because of the poverty trap they fall into.
Table 3 presents Price Build-Up for chickens in the three channels for each group of market players. Channel 1 (P-C) represents direct selling from producer to consumer. Channel 2 (RA-R) represents margin and price build up where chickens were bought from producers by rural assemblers who later sold them to retailers for final consumer selling. Channel 3 (AR) represents margin and price build up where assembly and retailing functions are integrated and carried out by a single trader.
Table 3. Price build-up of chickens (MK/chicken) |
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Group of Market Player |
Cost/Revenue Item |
Channel 1 |
Channel 2 |
Channel 3 |
Producer: |
Buying price |
0.00 |
0.00 |
0.00 |
|
Transport |
0.00 |
0.00 |
0.00 |
|
Handling |
0.00 |
0.00 |
0.00 |
|
Other |
0.00 |
0.00 |
0.00 |
|
Profit margin |
136 |
112 |
161 |
|
Selling Price |
136 |
112 |
161 |
Assembler: |
Buying price |
- |
112 |
- |
|
Transport |
- |
0.90 |
- |
|
Handling |
- |
0.54 |
- |
|
Other |
- |
- |
- |
|
Profit margin |
- |
61.1 |
- |
|
Selling Price |
- |
175 |
- |
Retailer |
Buying price |
- |
175 |
161.11 |
|
Transport |
- |
0.59 |
2.05 |
|
Handling |
- |
0.27 |
0.29 |
|
Other |
- |
0.14 |
0.28 |
|
Profit margin |
- |
24.0 |
46.3 |
Consumer Price |
|
136 |
200 |
210 |
Total marketing Margin |
|
- |
87.5 |
48.9 |
Key:
PC: Producer selling direct to consumer |
From Table 3, it can be observed that the largest contribution of market costs was from transport representing 61.1% in channel 2 and 78.2% in channel 3. From Table 4, the farmer's share of the total consumer price was about 100% in channel 1, about 77% in channel 3 and about 56% in channel 2. This suggests that about 44% of the total consumer price in channel 2 results from marketing activities by traders whereas only about 23% of the consumer price in channel 3 constitutes trader margins and marketing costs. This may indicate that the trader (AR channel), with knowledge of the prevailing consumer prices, is capable of offering a reasonable price to the producers. In this case, price uncertainty is minimized since the trader is the only link between producers and consumers.
Table 4 shows the marketing margins as a proportion of final consumer price and total channel marketing margin. In channel 2 the assembler's market margin constituted about 31.3% of the final consumer price whilst the retailer's market margin represented 12.5% of the final consumer price. This indicates that a large portion of the total marketing margin (MK87.50) generated in channel 2 goes to the rural assembler (71.4% vs. 28.6%). The assembler-retailer's market margin constituted about 28.3% of the final consumer price and 100% of the total marketing margin generated in channel 3.
Table 4. Player group’s marketing margin as a proportion of final consumer price and total channel marketing margin |
||||
Group of Market Player |
Revenue Item |
Channel 1 |
Channel 2 |
Channel 3 |
Producer: |
Selling price (MK) |
136.15 |
112.50 |
161.11 |
|
Farmer’s Share % |
100 |
56.25 |
76.72 |
|
TGMM % |
- |
43.75 |
23.28 |
Assembler: |
Selling price (MK) |
- |
175.00 |
- |
|
Margin/ chicken (MK) |
- |
62.50 |
- |
|
Marketing Margin % |
- |
31.25 |
- |
|
TCMM a % |
- |
71.43- |
- |
Retailer |
Selling price (MK) |
- |
200.00 |
210.00 |
|
Margin/chicken (MK) |
- |
25.00 |
48.89 |
|
Marketing Margin % |
- |
12.50 |
23.28 |
|
TCMM r % |
- |
28.57 |
100 |
Final Consumer Price(FCP) |
|
136.15 |
200.00 |
210.00 |
TCMM |
|
- |
87.50 |
48.89 |
TGMM
Total Gross Marketing Margin (%)
|
Table 5 summarizes the volumes and gross margins of local chickens and eggs sold from the model and the control villages. Eggs sold in the model village were from Hyline and Black Australorp hens while those from the control sites were from indigenous village hens.
Table 5. Volume and revenue from chickens and eggs sold in the model and control villages |
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Village |
Chickens Sold/Week, |
Chicken Margins1/Week, |
Total Eggs Sold/Week, |
Egg Margins1/
Week, |
Ishmael (Model) |
1.14b ± 1.67 |
82.73b ± 109.61 |
168.86a ± 42.86 |
219.81a ± 185.32 |
Mankhanga and Kalonga II (Non-Model) |
6.10a ± 6.41 |
493.86a ± 423.45 |
4.25b ± 3.74 |
22.48b ± 24.94 |
abMeans with different superscripts are significantly different (P<0.05). 1 Margins in MK |
Table 5 shows that significantly more chickens were sold in the control villages than in the model village and the reverse was true for eggs. The same trend was observed for gross margins realized from sale of chickens and eggs. This can be attributed to the fact that in the model village (Ishmael), households were getting some income from the sale of eggs. There was therefore no pressing need for them to sell chickens. On the other hand, in the control non-model villages (Mankhanga and Kalonga II), increased chicken sales might have been necessary due to low numbers of eggs that were available for sale. Only 11.4% of the total eggs sold were from the control villages. This may be a deliberate decision to spare eggs for reproductive purposes (De Vries 1993; Gunaratne et al 1993; Ahlers 1997; Guèye 2001). It was also interesting to observe that Hyline birds performed well under village conditions. In Malawi, there has been a general perception that only the Black Australorp and the local chickens can do well under village conditions. With the right type of interventions, farmers can therefore use the Hyline chickens for egg production thereby boosting egg production for both home consumption and for sale. The high gross margins from sale of chickens suggest that interventions that increase numbers of chickens would go a long way to have surplus chickens for sale let alone for home consumption. The results obtained are therefore a clear manifestation that using appropriate mechanisms, chickens can be used to increase people's income hence are a tool for poverty alleviation. This would then justify further development of the MSPPM. Considering that the operational framework of the model makes use of local brooder hens, improvements in general management of village poultry is a prerequisite.
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Received 16 August 2004; Accepted 31 August 2004