Customer‐Relationship Management: Performance Assessment and Improvement by an Intelligent Algorithm

This study seeks to achieve three main goals with respect to customer‐relationship management (CRM): (1) analysis of the relationship between different factors of CRM, (2) performance assessment of an organization from a CRM viewpoint, and (3) analysis of how each factor of CRM impacts an organization's performance. First, fuzzy DEMATEL is used to identify potential relationships between the factors. Subsequently, these relationships are examined by path analysis to find out which ones are supported. To accomplish the second goal, data‐envelopement analysis (DEA) is used to calculate the efficiency scores of the decision‐making units (DMUs), and an intelligent algorithm based on genetic programming (GP) and artificial neural networks (ANNs) is employed to determine the effectiveness scores. Finally, how each factor of CRM influences the performance is analyzed statistically. To demonstrate the applicability of the framework in the real world, it was used to study the household‐appliances industry in Iran.