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 d.baker@cgiar.org

Nadhem Mtimet n.mtimet@cgiar.org

International Livestock Research Institute www.ilri.org