World Journal of Agricultural Research. 2014, 2(5), 205-215DOI:
Abstract: Adaptation to changes of temperature and rainfall is a two-stage process, which initially hinges on the farmers’ perception of climate variability and then responding to changes through adaptation strategies. Adaptation evaluation is considered as part of a planned policy coping with consciously planned, primarily anticipatory adaptation initiatives undertaken by decision makers, specifically individual farmers. An evaluation goes beyond the identification, characterization of adaptation approaches and with regards to an adaptation option’s relative merit, superiority or implement-ability. Evaluative criteria do not only mention on principally economic dimension, but also relate to the different considerations. The objectives of this study (1) undertakes an evaluation of adaptation options in level of coffee farms by five alternatives involving in effectiveness, economic efficiency, flexibility, farmer implement-ability and independent benefits and (2) analyzes the determining factors impacting on the farmers’ adaptation level. The study uses data from structured interviews with 176 coffee farmers in Ea H’leo District, Daklak Province, Vietnam. The multiple criteria evaluation, unity based normalization and weighted sum methods are employed to assess the farmers’ adaptation options. The Ordered logit model is also used to estimate the relationship between the farmers’ adaptation level and their demographic and socio-economic characteristics. The result of multiple criteria evaluation indicated that amongst five evaluative criteria, the economic efficiency and effectiveness were assessed with the highest weights about importance level. The outcome of weighted sum of adaptation options highlighted that the level of adaptation was not positive relationship with the number of adaptation options which the farmers adapted to climate pressure for their coffee farm. It depended on the adaptation’s multiple considerations. The findings of regression model also revealed that factors related to the households’ socio-economic characteristics had statistically significant impacted to choosing the adaptation level at significant level 1%, 5%.