Organizational inclusion through interaction of work meaningfulness and servant leadership: An artificial neural network approach - Omar Khalid Bhatti; Muhammad Irfan; Ali Osman Öztürk; Raj Maham (Cogent Business & Management, 2022)
Modern organizations desire to fully include every organizational member in relevant activities for optimizing performance and reducing conflicts. This inclusion has become a challenge for leaders due to increased diversity in inclusive organizations. On one hand, organizational inclusion requires positive perception of the work itself (meaningfulness) and, on the other hand, needs inspirational leaders who can incite full participation from organizational members. In the absence of these two elements, negative work behaviors are likely to result in emergence of excluded groups and individuals. Consequently, cynicism, discontentment, resentment and conflicts arise which adversely affect organizational inclusion. We infer that servant leadership, through its narrative of "serving others", can play a vital role in creation of organizational inclusion through work meaningfulness. To investigate our inference about the impact of servant leadership directly, as well as through mediation/moderation of work meaningfulness, on organizational inclusion, this study has used structural equation modelling. In addition, artificial neural network (ANN) has also been applied to analyze the data collected from 400 employees working in the services and manufacturing sector of Turkey. An ANN model based on multilayer perceptron has been used to predict the impact of servant leadership and work meaningfulness on inclusion along with mediating roles of gender, age and work experience. The results adequately highlight strong influence of servant leadership and work meaningfulness on organizational inclusion.
Keywords: 650; Artificial Neural Network (ANN); Leadership; Organizational Inclusion; Servant Leadership; Work Behavior; Work Meaningfulness