Measuring the Human Values That Predominate in the Organization's Culture: A Dynamic Multilevel Linear Mixed Model Based on Genetic Algorithms

Abstract

The alignment between organizational and employee human values is critical in institutions that base their management on values. This research aims to link Schwartz's 10 human values to workplace authenticity, determining prevalent values in organizations. In tandem, nonprofit organizations are intricately intertwined with the values held by their members, forming the bedrock of their identity. To achieve this goal, an in-depth analysis is conducted on three nonprofit and faith-based organizations. The study proposes a hybrid model, merging a genetic algorithm with a linear mixed model, to comprehensively explore the intricate relationship between employees’ human values and authenticity in organizational settings. The underlying model is estimated from data to theory using a genetic algorithm (global optimization) to dynamically determine the best set of human values regressors (also considering interaction effects). The regressors selected to explain the authenticity construct the most from two perspectives, namely, the general model (fixed effects) and the particular model (random effects).