Abstract
Selecting a method for identifying actual crop productivity constraints is an important step for triggering innovation processes. Applied methods can be diverse and although such methods have consequences for the design of intervention strategies, documented comparisons between various methods are scarce. Different variables can be used to characterize these methods. To typify them, we used two of these variables in a heuristic model: control over the research process and represented opinion. Here, we review 16 published papers that present outcomes of different methods to identify productivity constraints. The major findings are the following: (1) Variation in methods is wide. (2) Applying the heuristic model results in three main clusters of methods: farmer-control/farmer-opinion, scientist-control/scientist-opinion, and scientist-control/farmer-opinion. (3) These clusters are scale level dependent. As a follow up, we compared in a case study the three different methods, representative for the three main clusters of the heuristic model, in order to assess their congruency. These methods (focus group discussion, individual surveys, and contextual data collection) were applied in four localities in Tigray, Northern Ethiopia. We found that congruency between the methods, as indicated by Spearman-ρ correlations, was not significant. In addition, we found that outcomes of individual surveys and contextual data collection among the different locations were correlated (R > 0.70). No such correlation was found using focus group discussion. Both findings indicate that for a specific location different methods yielded different constraints and that variability between the locations is not reflected by using individual surveys and contextual data collection. Combined the review and case study demonstrate that process control and represented opinion have a manifest impact on generated outcomes. Because outcomes of productivity constraints assessments are methodology dependent, researchers are recommended to justify a priori their choice of method using the presented heuristic model.
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