quantifying farmers preferences: can it be done? steven franzel

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Quantifying farmers preferences: Can it be done? Steven Franzel Use of the bao game for getting farmers’ assessments of alternative trees. Combine Accuracy, precision, and ability to generalize User-friendliness of participatory research

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Quantifying farmers preferences: Can it be done? Steven Franzel. Use of the bao game for getting farmers’ assessments of alternative trees. Combine Accuracy, precision, and ability to generalize User-friendliness of participatory research. Tools for getting farmer evaluations of technologies. - PowerPoint PPT Presentation

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Page 1: Quantifying farmers preferences:  Can it be done? Steven Franzel

Quantifying farmers preferences: Can it be done?Steven Franzel

• Use of the bao game for getting farmers’ assessments of alternative trees.

• Combine– Accuracy, precision, and ability to

generalize– User-friendliness of participatory

research

Page 2: Quantifying farmers preferences:  Can it be done? Steven Franzel

Tools for getting farmer evaluations of technologies

• 1. Scoring questionnaires

– Rating on a ‘1 to x’ basis gives quantitative data, but is problematic in rural, third world setting

Because farmers’ involvement is passive, they become bored

Page 3: Quantifying farmers preferences:  Can it be done? Steven Franzel

Tools for getting farmer evaluations of technologies

• 2. Matrix ranking: diagram with alternatives on one axis, criteria on the other.

Page 4: Quantifying farmers preferences:  Can it be done? Steven Franzel

Matrix ranking: Maize varieties

Local INIAP 180 Imported

Yield/ha

Resistance to pestsMkt. Price

Taste

Prod. Cost

Page 5: Quantifying farmers preferences:  Can it be done? Steven Franzel

• Advantages of matrix ranking:

– Farmers control process

– Visual tool, facilitates discussion and correction

But it is not used for collecting quantitative data (Maxwell 1997)

Page 6: Quantifying farmers preferences:  Can it be done? Steven Franzel

Bao game case study

• Overall research objective: Combine advantages of scoring questionnaires and matrix ranking.

• Case study : Burundi.

• Objective.: Find out how farmers evaluate trees in an on-farm trial.

Page 7: Quantifying farmers preferences:  Can it be done? Steven Franzel
Page 8: Quantifying farmers preferences:  Can it be done? Steven Franzel

First you need to get farmers’ criteria

• Tour the farm asking about the uses, advantage and disadvantage of each tree

• List the farmers’ criteria• Break off a branch of each

tree

Page 9: Quantifying farmers preferences:  Can it be done? Steven Franzel

• Find a comfortable place for the farmer to use the bao game to score different trees

Page 10: Quantifying farmers preferences:  Can it be done? Steven Franzel

Watch out, a crowd quickly forms!

Page 11: Quantifying farmers preferences:  Can it be done? Steven Franzel

Burundi case study

• 45 farmer interviews. • They rated 8 trees for timber and

firewood across 7 criteria

• Ratings from 1(low) to 5 (high)

Page 12: Quantifying farmers preferences:  Can it be done? Steven Franzel

Farmer criteria

• Tree management and growth– Compatibility with crops– Speed of growth– Resistance to pests

• Use for timber– Wood appearance– Straightness

• Use for firewood– Quick in drying– Durability of fire

Page 13: Quantifying farmers preferences:  Can it be done? Steven Franzel

Farmers' mean ratings of tree species using bao game

Trees Compatabi-lity

with crops

Speed of growth

Durability of fire

Cedrela serrata 4.6 (0.5) 4.3 (0.7) - Grevillea robusta 4.9 (0.3) 4.6 (0.5) 2.8 (1.2) Markhamia lutea 3.7 (1.0) 1.9 (0.9) 4.2 (0.7) Eucalyptus spp 1.1 (0.3) 4.3 (0.8) 5.0 (0.0)

(Standard deviation in parentheses)

Page 14: Quantifying farmers preferences:  Can it be done? Steven Franzel

Burundi case study: Main findings

• Eucalyptus and Grevillea, the most common species, also the highest rated– Grevillea for fast growth and

compatibility– Eucalyptus for fast growth and

firewood

• Two other high-rated species, Cedrela and Maesopsis, not commonly grown due to lack of planting material

Page 15: Quantifying farmers preferences:  Can it be done? Steven Franzel

Conclusions• Bao game combines strengths of

scoring questionnaires with those of matrix ranking

• Bao game is useful for generating quantitative data– Accurate– Precise– Permits generalization, hypothesis

testing• Quantitative data on farmer criteria

and preferences are key inputs into tree improvement program.