Deriving the weights for aggregating judgments in a multi-group problem: an application to curriculum development in entrepreneurship

Jay Wasim, Vijay Vyas, Pietro Amenta, Antonio Lucadamo, Gabriella Marcarelli, Alessio Ishizaka

Research output: Contribution to journalArticlepeer-review

Abstract

In group decisions, two issues need to be tackled: weighting opinions of different decisionmakers and aggregating their evaluations. Many group aggregation techniques analyse these issues. These approaches can be correctly applied only if the weights assigned to all decisionmakers are available. Unfortunately, there are situations where such weights are unavailable or incomplete, the negotiation required to better define them is not possible or decision-makers are unwilling to revise their judgments. These situations could pose a critical problem for the correct application of aggregation procedures. This problem is exaggerated if there are more than one group of decision-makers. In this paper, we present a new algorithm based on the Frobenius norm that considers the choice of the weights in aggregating judgments in a non-negotiable multi-group problem. This approach facilitates the computation of several sets of weights simultaneously, showing the roles played by each decision-maker and by each group in defining the global priority. To illustrate the method, we apply it in designing a new curriculum in entrepreneurship based on an entrepreneurial learning approach informed by perceptions of three stakeholders: entrepreneurship educators, entrepreneurs and entrepreneurship students. Data is collected by pairwise comparison within the analytic hierarchy process and is aggregated using our proposed approach.
Original languageEnglish
JournalAnnals of Operations Research
DOIs
Publication statusPublished - 5 Apr 2022

Keywords

  • Decision analysis
  • Entrepreneurship education
  • Group decision making
  • Multi-criteria

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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