Extracting configurations of values mixing scores from experts and ignoramus using Bayesian modelling

Abstract

The article proposes a method for producing configurations of values in firms. Values have an impact in the long-term survival of businesses and guide managerial decision-making. The method produces cross-comparable latent rates of configurations of values. Data comes from a pool of 37 firms rated by both experts and ignoramus. By using Bayesian inference the researcher can tune the expert rater bias. This generates robust estimates using a clear, overt and systematic procedure. The model is compared with the mean of raters. It produces lower ratings for Economic-Pragmatic values and higher ratings for Ethical-Social values.

Publication
Frontiers in Applied Mathematics and Statistics
Date