Stakeholder ranking of watershed goals with the vector analytic hierarchy process: Effects of participant grouping scenarios

  • Authors:

  • A. Arnette;C. Zobel;D. Bosch;J. Pease;T. Metcalfe

  • Affiliations:

  • Department of Business Information Technology, 1007 Pamplin Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0235, USA;Department of Business Information Technology, 1007 Pamplin Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0235, USA;Department of Agricultural and Applied Economics, 208 Hutcheson Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0401, USA;Department of Agricultural and Applied Economics, 208 Hutcheson Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0401, USA;Department of Agricultural and Applied Economics, 208 Hutcheson Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0401, USA

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

More effective methods of eliciting and summarizing stakeholders' goals can assist in improving watershed management. This paper discusses the process of summarizing the goals that were generated during a workshop of watershed stakeholders in Virginia by using the Vector Analytic Hierarchy Process, and then grouping them into homogeneous subgroups by using two different methods: 1) assigning subgroups based on individuals' stated affiliations from a participant bio-sheet; and 2) assigning subgroups based on the similarity of individuals' actual preferences between the goals. Several different clustering approaches are considered for creating the preference-based subgroups, and the relative advantages and disadvantages of each approach are discussed. The process of combining the subgroups to generate a single overall preference structure for the group as a whole is also considered, and the final results are compared based on both the resulting rankings and the coherence, or variability of opinion, that they reflect. Determining the ''best'' set of subgroups can be valuable not only in exploring the underlying nature of the population's preferences, but also in supporting additional discussion and analysis of the results. As such, it can ultimately lead to much stronger and better informed decision-making by the stakeholders.