Correlates of Employees‟ Psychological Contract Fulfillment: A Proposed Study Model

Abstract

Leader member exchange (LMX) theory (2016) provides a framework to understand the formation of vertical dyadic work place relationships between leaders and subordinates. The goal of LMX is to explain the effect of leadership on members, teams and organizations. Available literature acknowledges that multiple work-related consequences including psychological contract fulfillment which is understood as a relational and dynamic phenomenon that emerges and develops in every employment relationship would depend on the way employees are being treated by their leader. Meta analysis of the theory has outlined three categories of antecedents as leader characteristics, member characteristics and the nature of their inter-relationship and another category of situational variables as the determinants of leader-member exchange. For the proposed study, psychological variables of general self efficacy, culture orientation of the employees, transformative leadership style and the state of the leader-member relationship will be measured as LMX antecedents. It is hypothesized that these antecedents will positively impact the employees‘ psychological contract fulfillment. Afore mentioned hypothesis will be tested in relation to a population of three hundred executive and staff level employees at an apparel manufacturing company in Ragama, Sri Lanka using explorative research design and survey method. Data collection instruments will be tested for their psychometric properties using Cronbach‘s alpha test, correlation coefficient test and confirmatory factor analysis. MANOVA will be conducted for hypotheses testing. Research findings are stipulated to contribute to strategic decision making in workforce planning of the company in concern and literature on employees‘ psychological contract fulfillment in the Sri Lankan context. Simultaneously the research process is intended to create a platform for interdisciplinary approaches to collaborate and to help organizations make data driven business and workforce decisions in achieving sustainable development.