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International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

Emotional Intelligence, Transformational Leadership, Training and Development, Employee Engagement as the Predictors of Turnover Intention: A Conceptual Review

Md Yousuf, Hishamuddin Md Som, Amer Hamzah Jantan

http://dx.doi.org/10.6007/IJARBSS/v14-i9/22867

Open access

Medical representatives' high turnover hampered Bangladesh's pharmaceutical industry's long-term growth. Understanding this issue's causes is crucial. This study aims to examine the relationship between emotional intelligence, transformational leadership, training and development, and turnover intention among medical representatives of pharmaceutical companies in Bangladesh. The study examines employee engagement as a mediator. This study proposes a conceptual framework that draws on relevant literature and key theories (Resource Based View Theory and Social Exchange Theory) in the field of organizational attitudes and behavior to analyze these relationships. This study will use positivist quantitative and explanatory research designs. Quantitative methods enable data collection to determine variable correlations. To ensure proportional representation from each population stratum, the study will use stratified sampling, a type of probability sampling. Medical professionals from Bangladeshi pharmaceutical companies are the target population. The size and unit of the sample will determine the distribution of questionnaires to collect primary data on variables. Data analysis requires SPSS (Version 29.0.2.0) and SmartPLS. The researcher expects emotional intelligence, transformational leadership, and training and development to affect turnover intention significantly. Additionally, employee engagement is expected to mediate the relationship. The study will help Bangladeshi pharmaceutical employers, HR managers, and supervisors address turnover intention factors. It will advise on retention strategies during recruitment, onboarding, and training. The impact can be good or bad. Based on results, the researcher will make recommendations.

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