An Analytical Approach to Assess the Influence of Expert Panel Answer on Decision Making: The Case of Sustainable Land Use in Ribadavia Banda Norte, Salta (Argentina)

Abstract

Many of the techniques for making decisions, including land use, depend on the weight assigned for each criterion. These criteria can be based on a panel of experts’ opinions, who assess certain decisions’ influence on the final objectives. These opinions should be contrasted to decide if they are used or select the ones used to achieve an internal coherence. In this study, we evaluate the responses provided by an expert panel in the context of future environmental management of an agroforestry territory in the Salta Province (Argentina). The experts belong to different entities in the studied area, such as Universities, Research Centers, Administrative Authorities, Associations, and non-governmental organizations. They evaluated five productive techniques’ influence on 31 criteria related to environmental, social, and economic consequences. The Kendall’s Tau correlation coefficient between each pair of experts’ opinions is proposed to measure the rate of agreement among the expert panel answers. From these coefficients, a concordance matrix is generated. Based on this matrix, dendrograms are created to group the experts. In this case study, the results show two productive techniques with a high discordance rate, while the other three have a higher agreement among the expert panelists. The influence of these results in a multicriteria decision about the productive use of land is evaluated.

Combining Markowitz Portfolio Model and Simplex Algorithm to Achieve Sustainable Land Management Objectives: Case Study of Rivadavia Banda Norte, Salta (Argentina)

“…As indices of the adequacy of the techniques, we used the expert-technical qualifications of these techniques collected in previous work [27], which we expressed here as a percentage (Table 1). [27] (see expert description).…”

“…Table 5 shows the differences in return derived from the groups (not all of the experts) founded previously [27] on the experts' opinions concerning techniques T1 and T2. It is observed that there are no differences for the techniques with zero investment/surface areas in a technique; for example, in T1 (precision agriculture) for portfolios 1 and 15 and T2 (forest management with integrated livestock) for portfolios 1, 2, and 15.…”

“…For a realistic approach to a case study (specifically Rivadavia department, Salta, Argentina), we based our work on ten spatially distributed variables describing soil, land coverage and use, and socioeconomic characteristics. Also, an expert panel was selected in the previous first stage of this study to qualify five different techniques for land management, and the agreement among its answers was analyzed [27]. These techniques were precision agriculture (T1), advance livestock farming (T2), payment for ecosystem service (T3), traditional agriculture-livestock farming-Criollo (T4), and traditional forest management-Wichi (T5).…”

“…Ref. [27] evaluated the productive techniques' influence on environmental, social, and economic criteria.…”

“…The averages (r T1-A , r T1-B ; r T2-C , r T2-D ) of each technique considering each expert group with a discrepant opinion (T1-A, T1-B; T2-C and T2-D) are obtained considering only the experts included in these groups for a technique. These are variants of r derived from the detected groups for techniques T1 and T2 in the previous work [27].…”