Turnover intent of new workers: social exchange perspectives

• Main Authors: Felicito Angeles Jabutay, Parisa Rungruang
• Other Authors: Kasem Bundit University
• Format: Article
• Published: 2020
• Subjects: Business, Management and Accounting; Social Sciences
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/59914
• Institution: Mahidol University

© 2020, Emerald Publishing Limited. Purpose: This paper aims to investigate the impact of task interdependence and leader–member exchange, as social exchange variables, on affective commitment and turnover intent of new workers in an industry with high attrition rates. In addition, the paper examines the mediating effects of affective commitment. Design/methodology/approach: The present study drew insights from the literature to formulate hypotheses that link the two social exchange variables on affective commitment and turnover intent. Through the utilization of the data collected from 441 call center agents working for eight call centers in the Philippines, the hypotheses were tested and analyzed using structural equation modeling. Findings: The results reveal that task interdependence and leader–member exchange are positive antecedents of affective commitment and negative predictors of turnover intent. Further analysis reveals that affective commitment fully mediates the effects of the two social exchange variables on turnover intent. Practical implications: The results imply that call centers can help improve new workers' affective commitment and reduce their turnover intent through job designs that can facilitate high task interdependence. Furthermore, training team leaders or supervisors to develop leadership styles that are more focused on people and relationships may also increase the agents' commitment and reduce their quit intention. Originality/value: This paper is the first to demonstrate that social exchange variables can also impact the affective commitment and turnover intent of new workers in an industry known to have heavy supervisorial monitoring, high demands in terms of work quotas and high turnover rates.