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Purpose. The development of general-scale diagnoses is one of the main reasons why policies, lines of action, and strategies do not adequately respond to the dynamics and needs of rural territories. Consequently, there is a recognition of the need to select rural spaces that require a territorial diagnosis due to their particular characteristics and unfavorable conditions toward balanced development. Method. We design four phases in the rural space selection method. In the first phase, of the method’s development, we identify the formation of Technical Working Table(s) as a key factor. The second phase involves a systematic literature review from local sources, tailored to the application context. In the third phase, variables measuring rural space selection are identified and validated, determining the rural zones of interest. Finally, in the fourth phase, two mathematical techniques, the analytic hierarchy process (AHP) and weighted ratings, are proposed. These techniques enable quantification of options and provide information to facilitate the decision-making process for selecting rural spaces. Results. The first phase involves the formation of the Technical Working Table (TWT), identified as a key factor in the design and operation of the proposed research method. The Technical Working Table (TWT) comprises nine institutional actors committed to regional development, who participated in both the design and implementation of the proposed methodology. Similarly, in the phase of systematic literature review, 43 articles are selected, identifying 21, 18, and 26 variables of major significance in the ecological, social, and economic dimensions of the study area. Subsequently, in the third phase, collaboration with the TWT is employed to validate and select the nine variables constituting the criteria for rural space selection. In the final phase, results from applying the two mathematical techniques quantifying the rural space selection are obtained. Conclusions. The rural space selection method enhances the development of specific territorial diagnoses, given the unique characteristics and dynamics of the study area. |
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