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Derek Baker, Amos Omore,
David Guillemois and Nadhem Mtimet
23rd annual International Food and Agribusiness Management Association (IFAMA) forum and symposium
17-19 June 2013, Atlanta, GA
A network approach to analysis of the performance of milk
traders, producers and BDS providers in Tanzania and Uganda
Outline
1. Business Development Services (BDS) as a development mechanism 2. Networks in development, and introduction to networks as an approach to value
chain analysis 3. Approach taken, preliminary results
4. Next steps:
• formulation of broader conceptual frameworks for networks
• symposium on networks as value chain configurations, at African Association of
Agricultural Economists’ Conference, September 23-25, 2013, Hammamet, Tunisia
Milk Trader
Training
Service
Providers
(BDS)
Regulatory
Authority
Accreditation & monitoring
Reporting
Training
guides
Business Development Services (BDS) in pro-poor
dairy development in East Africa
Hygienic
cans
(Trialled in Tanzania and Uganda – now being evaluated)
Milk Market Hub (Emphasis on traditional milk
market hubs to grow them)
Milk
Producer
$$
Payment agreement
BDS in pro-poor dairy development in EA: Linkages via marketing, inputs and services
Inputs &
Service
Providers
(BDS)
Milk Traders
Background to research
Representations of the Value Chain in pro-poor development:
• have a poor theoretical basis upon which to base research hypotheses
• lack quantitative intuition
• fail to capture inter-agent interactions
• cannot adequately address analysis of interventions
The research for which this is a preliminary presentation has goals:
1. Evaluate BDS programme for dairy in Uganda and Tanzania
2. Advance knowledge of trader-producer-service linkages and development
orientation
3. Test new empirical methods
Theories of networks, applied to value chain analysis, used to formulate hypotheses
Measures of performance of BDS interventions formulated
Measures of VC-related network characteristics formulated
Data collected
Data processed using network-dedicated software (Pajek)
Preliminary analysis done
The story so far
Sampling
1. Start with BDS providers:
i. select ALL “programme” BDS providers (11 in Mwanza)
ii. mirror with an equal number (11) of “non-programme” BDS providers
iii. Ask each BDS provider for a COMPLETE list of clients (traders and
producers)
2. Randomly select 5 “programme” BDS providers, and 5 “non-programme” BDS
providers from above
i. Randomly select 4 TRADERS from client list of each (i.e. 2*20 = 40)
ii. mirror with an equal number (20) of TRADERS not linked to the programme
iii. Ask ALL actors for contact lists
3. Randomly select 2 “programme-linked” TRADERS and 5 “programme” BDS
providers
i. Randomly select 2 PRODUCERS from each contact list (2*5 + 2*4 = 18)
ii. Mirror with an equal number (18) of PRODUCERS not linked to the
programme
iii. Ask ALL actors for contact lists
Sample
Mwanza Arusha
BDS Providers
Programme 11 9
Non-programme 11 9
Traders-linked to programme 20 16
Traders-non-linked 20 16
Producers-linked to programme 18 15
Producers-non-linked 18 15
Totals
BDS providers 22 18 40
Traders 40 33 73
Producers 36 29 65
Total interviews 98 80 178
Milk supply in Uganda
Blue triangle : Trader
Red cirle: Producer
Thickness line: Quantity of milk traded between producers and traders.
Number: Quantity of milk traded per connection.
Results - Uganda Milk sales, BDS
Blue triangle : Trader
Red circle: Producer
Yellow box: BDS
Dot line: Milk traded
Blue line: BDS service
Results - Uganda Milk sales, BDS (detail)
Blue triangle : Trader
Red circle: Producer
Yellow box: BDS
Dot line: Milk traded
Blue line: BDS service
Results - Uganda milk sales and all BDS
Blue triangle : Trader
Red circle: Producer
Yellow box: BDS
Thickness of the line: Number of exhanges/services
Results - Uganda milk sales and all BDS (detail)
Blue triangle : Trader
Red circle: Producer
Yellow box: BDS
Thickness of the line: Number of exhanges/services
Results - Degree centrality for producers
140 producers have just 1 buyer
38 producers have 2 buyers
10 producers have 3 buyers
8 producers have 4 buyers
….
… right hand tail
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12
Number of connections for producers in Uganda on Milk
Num
ber
of
pro
ducers
Number of connections between producers and traders
Results - Degree centrality for traders
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6
Milk. Number of connections for Traders in Uganda
0
2
4
6
8
10
12
14
16
1 2 3 4 5
Number of connections for Traders in Arusha on Milk
0
5
10
15
20
25
1 2 3 4 5 6
Number of connections for Traders in Mwanza on Milk
36 traders buy from just 1 producer
18 traders buy from 2 producers
….
Note small peak (10 traders) buying
from 5 producers
Note different configuration between Arusha and Mwanza
Nu
mb
er
of tr
ad
ers
Number of connections between producers and traders
Results - Network characteristics for BDS provision - 1
PRODUCERS TRADERS BDS
UG
AN
DA
0
5
10
15
20
1 2 3 4 5 6 7 8 9 10 11 12
Connection of BDS. Producers. Uganda
One service received by one BDS is counted as "one"
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11
Connection of BDS. Traders. Uganda One service received by one BDS is counted as
"one"
0
10
20
30
40
1 4 7 10 13 16 19 22 25 28 31 34 37 40
Number connections per BDS. Uganda One service to one entity is counted as
"one
AR
USH
A
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1 3 5 7 9 11 13 15 17 19
Connection of BDS. Producers. Arusha One service received by one BDS is
counted as "one"
0
1
2
3
4
5
6
7
1 3 5 7 9 11 13 15 17 19 21
Connection of BDS. Traders. Arusha One service received by one BDS is counted as
"one"
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10 11
Number connections per BDS. Arusha One service received by one BDS is
counted as "one"
No. of pro
ducers
No. of connections producer to BDS
`
No. of pro
ducers
No
. o
f tr
ad
ers
N
o. o
f tr
ad
ers
No. of connections trader to BDS
No. of connections trader to BDS No. of connections producer to BDS
No. of connections from BDS providers
No. of connections from BDS providers
Results - overview
Characterisation of networks:
Variation in network degree intensities:
i. Numbers of connections to trading partners
• Monopsony
• Monopoly
• Vertical integration
ii. Numbers of actors’ connections to BDS providers
i. Cost-based economics of service delivery: scale and scope effects
ii. Mixes of types of service: bundling
Analysis of networks:
A shift in data interpretation
... Variables....
A
B
C
...
A to B
A & B
C to D
...
... O
bserv
ations..
..
....
Agents
…
....
netw
ork
connections …
Incl. A to B, A
& B, C to D
etc
Sub-network
specific
variables
Future analysis – a logical progression of hypotheses
H01: Actors’ characteristics/performance = f(exogenous data collected)
H02: Actors’ characteristics/performance = f(exogenous data collected,
number and form of network links)
H03: Number and form of links = f(exogenous data collected,
factors affecting linkages)
H04: Actors’ value chain behaviour = f(exogenous data collected,
factors affecting linkages)
H05: Value chain performance = f(exogenous data collected,
actors’ value chain choices)
H06: Development outcomes = f(exogenous data collected,
factors affecting network structure)
Conventional view:
Progression… (nested models?)
Symposium: September 2013
Network analysis applied to livestock value chains:
relationships beyond demand and supply and their
contribution to the impact of upgrading
interventions
African Association of Agricultural Economists’ Conference
September 23-25, 2013, Hammamet, Tunisia
Sponsored by PIM
Contact:
Derek Baker [email protected]
Nadhem Mtimet [email protected]
International Livestock Research Institute www.ilri.org