Analytic Hierarchy Process

Analytic Hierarchy Process

Using Analytical Hierarchy Process to Understand Smallholder Perceptions of Conservation Agriculture Adoption in Nepal and India. Reed, B.F.,1 Chan-Halbrendt, C.,1 Tamang, B.B.,2 Chaudhary, N.,3 Roul, P.4 1 Dept. of Natural Resources and Environmental Management, University of Hawaii, USA 2 Local Initiatives for Biodiversity, Research and Development, Pokhara, Nepal 3 Institute of Agriculture and Animal Science, Rampur, Nepal 4 Orissa University of Agriculture and Technology, Bhubaneswar, India 1 Introduction Analytical Hierarchy Process (AHP) is a multi-criteria decision-making tool that breaks down difficult and complex problems into simple pairwise comparisons (Saaty, 2008). Useful for group situations

Takes into account conflicting viewpoints and strength of preferences Fosters conciliation and consensus Objectively measures qualitative value judgments For these reasons, it is increasingly being used in the field of technology transfer. 2 Objectives 1. Using recent case studies from Nepal and India, demonstrate how AHP can support the adoption of conservation agriculture production systems(CAPS) by: Determining farmers and scientist preferences Identifying knowledge gaps. 2. Identify other uses for AHP results. 3 CAPS

CAPS integrate traditional farming methods with CA practices to: encourage adoption increase long-term soil productivity improve smallholder livelihoods. Each CAPS consists of one or more practices: year-round soil cover, minimal tillage or crop rotation (SANREM CRSP, 2012) 4 Case Study Methods 1. Identify the elements: goal, objectives and alternatives. 2. Construct a decision hierarchy. 3. Make pairwise comparisons of each element of the hierarchy with each other element on its level, and in the level(s) above it. 4. Analyze data: Expert Choice. 5

AHP Hierarchy ' @ / // K @ W >^ z / ^Y @

6 Case Study A: Study Site Conducted by Reed et al. (2002) at five sites in or near Pokhara, Nepal: 1. Local Initiatives for Biodiversity Research and Development (LI-BIRD) 2. The Institute of Agriculture and Animal Science (IAAS) 3. Thumka 4. Hykrang 5. Khola Gaun 7 Case Study A: Alternatives Farmer Practice CAPS 1 CAPS 2

CAPS 3 Maize > Millet Conventional Tillage Maize > Cowpea Conventional Tillage Maize > Cowpea/Millet Intercrop, Conventional Tillage Maize > Cowpea/Millet Intercrop, Minimal Tillage 8 Case Study A: Results IAAS Profit LI-BIRD Thumka Hyrkrang KholaGaun

0.17 0.25 0.101 0.087 0.104 Labor Saving 0.123 0.14 0.087 0.148

0.052 Yield 0.282 0.351 0.229 0.239 0.17 Soil Quality 0.425 0.26 0.583

0.526 0.674 IAAS LI-BIRD Thumka Hyrkrang 0.075 0.094 0.091 0.1 0.169 0.286 0.477 0.491 0.196 0.207 0.254 0.215 0.561 0.413

0.178 0.193 KholaGaun 0.08 0.348 0.221 0.351 Improved Income T1 T2 T3 T4 9 Case Study A: Results Importance of Objectives in terms of Improved Income Profit 1

0.5 Soil Quality 0 Labor Saving IAAS LI-BIRD Thumka Hyrkrang Khola-Gaun Yield 10 Case Study A: Results Preference for Treatments in terms of Improved Income

IAAS 1 0.5 Khola-Gaun LI-BIRD T1 T2 T3 T4 0 Hyrkrang Thumka 11

Case Study A: Findings Objectives Soil quality rated highest overall (49%), indicating shared long term point of view among scientists and farmers. Labor savings rated lowest and may not motivate adoption. Alternatives Intercropped CAPS preferred by all. Farmers in two villages preferred conventional tillage over strip tillage with regard to profit and soil quality, indicating knowledge gap. Khola Gaun farmer preferences more in line with scientists than with other farmers. 12 Case Study B: Study Site Conducted by Lai et al. (2011) at two sites in Odisha, India 1. Orissa University of Agriculture and Technology, Bhubaneswar

2. Tentuli Village, near city of Kendujhar. 13 Case Study B: Alternatives Farmer Practice CAPS 1 CAPS 2 CAPS 3 Maize monocrop Conventional Tillage Maize monocrop Minimum Tillage Maize/Cowpea Intercrop Conventional Tillage Maize/Cowpea Intercrop, Minimum Tillage 14

Case Study B: Results Tentuli Profit Labor Saving Yield Soil Quality Improved Income T1 T2 T3 T4 OUAT 0.274 0.184 0.329 0.213 Tentuli 0.356

0.128 0.245 0.271 OUAT 0.141 0.147 0.366 0.347 0.103 0.175 0.25 0.472 15 Case Study B: Findings Objectives Yield rated highest in villages (33%), profit rated highest by scientists (36%), indicating difference of perception in farmer needs.

Profit rated second in villages (27%), soil quality rated third (21%) suggesting short-term perspective among farmers. Labor savings rated lowest and may not motivate adoption. Alternatives Intercropped CAPS preferred by all. Farmers value conventional tillage (37%) over strip tillage (35%), scientists highly prefer strip tillage (47%) indicating knowledge gap. 16 Conclusions 1. The use of AHP enabled researchers to: Determine that the long-term objective of soil quality was preferred in Nepal while short-term objectives of yield and profit were preferred in India Discover that labor savings may not motivate adoption Identify where extension services might be working best (Kola Guan)

Reveal a clear, unanimous preference for adoption of new production systems and legume intercropping Determine that knowledge gaps regarding the effectiveness of minimum tillage exist in both study areas. 17 Conclusions 2. AHP provided useful data that may be Compared across time periods to evaluate project or extension effectiveness Combined with trial plot results to determine which CAPS are most likely to be adopted Used to re-align training and research efforts. AHP can provide valuable insight where quantitative agriculture information is scarce and complex decisionmaking is required. For this reason, it is an excellent candidate for use in conservation agriculture adoption efforts. 18 References

Lai, C., Chan-Halbrendt C., Halbrendt, J., Naik D. and Ray, C. 2011. Farmers Preference of Conservation Agricultural Practices in Kendujhar, Odisha Using Analytical Hierarchy Process. Published in the proceedings of the Second International Conservation Agriculture Workshop and Conference in Southeast Asia: Phnom Penh, Cambodia, 04-07 July 2011. Reed, B.F, Chan-Halbrendt, C., Tamang, B.B. and Chaudhary, N. 2012. Analysis of conservation agriculture preferences for researchers, extension agents and tribal farmers in Nepal using Analytical Hierarchy Process. Unpublished Results. Saaty, T.L., 2008. Decision making with the analytic hierarchy process. Int. J. Services Sciences 1(1), 83-98. 19

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