A Linguistic Group Best–Worst Method for Measuring Good Governance in the Third Sector: A Spanish Case Study

Abstract

The need of Non-profit Organizations (NPOs) of generating trust and credibility, to their stakeholders by an efficient management of their resources, lead them to openly show that they develop adequate good governance practices. But this is not a simple task and few research has been done on measuring methods of good governance in this field; without achieving an agreement about the best procedure. This paper aims at facilitating the measurement of good governance practices in NPOs by a fuzzy linguistic consensus-based group multi-criteria decision-making (MCGDM) model that will provide agreed and easy-understanding weights for a list of indicators proposed by the stakeholders and entities in such good governance practices. To do that, a linguistic 2-tuple BWM method with a consensus reaching process (CRP) will be developed and then applied to a real-world case in Spain, in which a group of experts from significant Spanish NPOs will assess the list of indicators proposed by the most representative entities (the alliance between the non-governmental organizations (NGO) Platform for Social Action, and the NGO Coordinator for Development (CONGDE) to obtain a prioritization of such indicators for measuring the good governance practices in Spanish NPOs.