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<title>COMPETITIVENESS OF BROILER CHICKEN VALUE CHAIN IN  SOUTHWESTERN NIGERIA</title>
<link href="http://hdl.handle.net/123456789/1413" rel="alternate"/>
<subtitle/>
<id>http://hdl.handle.net/123456789/1413</id>
<updated>2026-04-04T08:45:29Z</updated>
<dc:date>2026-04-04T08:45:29Z</dc:date>
<entry>
<title>COMPETITIVENESS OF BROILER CHICKEN VALUE CHAIN IN  SOUTHWESTERN NIGERIA</title>
<link href="http://hdl.handle.net/123456789/1414" rel="alternate"/>
<author>
<name>AWOYOMI, Femi Stephen Oyebade</name>
</author>
<id>http://hdl.handle.net/123456789/1414</id>
<updated>2022-02-22T09:31:54Z</updated>
<published>2021-03-01T00:00:00Z</published>
<summary type="text">COMPETITIVENESS OF BROILER CHICKEN VALUE CHAIN IN  SOUTHWESTERN NIGERIA
AWOYOMI, Femi Stephen Oyebade
Broiler chicken is a major source of income and also contributes to gross domestic &#13;
product in Nigeria. The total ban on broiler chicken meat importation was a government &#13;
policy introduced to increase participation and protect local Broiler Value Chain (BVC) &#13;
actors. However, smuggling of imported products still persists and may affect &#13;
competitiveness of the locally produced broiler chicken. Empirical studies on market-led &#13;
profitability of key actors in BVC in southwestern Nigeria are scanty. Therefore, &#13;
competitiveness of BVC in southwestern Nigeria was investigated.&#13;
A three-stage sampling procedure was used. Ogun and Oyo States were selected based on &#13;
prevalence of poultry production in Southwestern Nigeria. Ten Local Government Areas LGAs (4 from Ogun and 6 from Oyo) proportionate to size were selected based on LGAs &#13;
with highest production of broiler chicken. Using structured questionnaire, data were &#13;
collected from 419 randomly selected actors (broiler chicken producers-176, processors 60 and marketers-183). Socioeconomic characteristics observed were age, Household Size &#13;
(HS), Number of Income Earners (NIEs), sex, Marital Status (MS), level of education, &#13;
Association Membership (AM), and Years of Experience (YE). Other variables studied &#13;
were participation decision factors (credit access and tax), inputs, outputs and their prices.&#13;
Indicators of competitiveness used were Private Profitability (PP &gt;1), Private Cost Ratio &#13;
(PCR &lt;1) and Effective Protection Coefficient (EPC &gt;1) for government policy. Data &#13;
were analysed using descriptive statistics, policy analysis matrix and double hurdle model &#13;
at &#13;
a0.05&#13;
. &#13;
Age, HS and NIEs were 38.0±7.6, 4.7±1.9 and 2.4±1.6 for producers; 37.6±8.1, 4.0±2.3 &#13;
and 4.9±1.3 for processors and 38.7±8.2, 4.4±1.5 and 5.1±1.7 for marketers, respectively. &#13;
Major actors were male (54.4%), married (50.6%) and 61.3% had tertiary education. &#13;
Transportation (0.1479) was Participation Increasing Decision Factor (PIDF) for &#13;
producers, while selling price (-0.1389) and inadequate water (-0.0001) were Participation &#13;
Reducing Decision Factors (PRDFs). Tax (0.3082), HS (0.1017) and AM (0.2531) were &#13;
PIDFs for processors. Credit access (0.2570) and theft (0.1401) were PIDFs for marketers, &#13;
while AM (-0.1163) and tax (-0.1096) were PRDFs. Intensity of Participation Increasing &#13;
Decision Factors (IPIDFs) for producers were MS (0.00094) and YE (0.0001), while &#13;
inadequate water (-0.0003) was IPRDF. Selling price (-0.0001) was IPRDF for &#13;
processors. The YE (0.0001) and AM (0.0008) were IPIDFs for marketers, while tax (-&#13;
0.0011), credit access (-0.0005) and selling price (-0.2818) were IPRDFs. Marketers had &#13;
highest PP (N2,042,471.95), while processors had the highest social profit &#13;
(N2,666,268.46). The PCR ranged from 0.51 to 0.61, while EPC ranged from 0.91 to 3.46 &#13;
for all BVC actors. The PP of producers decreased by 26.6%, 36.2% and 56.7% with &#13;
20%, 40% and 60% increase in the price of inputs, respectively. The PP (N590,361.35, &#13;
N1,985,199.82 and N2,042,471.95), PCR (0.69, 0.61 and 0.54) and EPC (3.46, 0.76 and &#13;
0.91) were all positive indicating competitiveness for producers, processors and marketers, &#13;
respectively. &#13;
Broiler chicken value chain was competitive in southwestern Nigeria with marketers being &#13;
the most competitive, while producers were the most policy protected actors.
</summary>
<dc:date>2021-03-01T00:00:00Z</dc:date>
</entry>
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