Designing a Model of Talent Turnover from the Perspective of Knowledge Workers Who Have Resigned in the Iranian Offshore Oil Company

The present study aimed to design a model of talent turnover from the perspective of knowledge workers who have resigned in the Iranian Offshore Oil Company. Considering the main objective of this research—explaining and presenting an interpretive structural model of the factors influencing talent turnover in the Iranian Offshore Oil Company—this study falls within the scope of applied research and adopts an exploratory mixed-methods approach. The statistical population in the qualitative section included managers from the Iranian Offshore Oil Company, academics, and experts from the company. Using a purposive sampling method, ۱۲ participants were selected as the sample. In the quantitative section, data were also collected from experts in the Iranian Offshore Oil Company. The sample size in this section was determined using Cochran’s formula and simple random sampling. With a total population of ۲۵۰ individuals, the Cochran formula identified a sample size of ۱۵۲ participants. Data collection employed interviews and a researcher-developed questionnaire. Thematic analysis was used to develop the model, which was ultimately analyzed using structural equation modeling (SEM) with PLS software and the ISM technique. Results indicated that, among the model's components, livelihood status and skills and expertise were prioritized as the most critical factors by the experts, situated at the first level. Cultural and social environments and the political environment were ranked at the second level. Organizational policies, rules and processes, organizational climate, and organizational management were placed at the third level. Finally, influence and impact, along with being overlooked and undervalued, were categorized at the fourth level. From the managers' perspective, the most critical factors driving talent turnover included influence and impact, being overlooked and undervalued, livelihood status, and skills and expertise. The present study aimed to design a model of talent turnover from the perspective of knowledge workers who have resigned in the Iranian Offshore Oil Company. Considering the main objective of this research—explaining and presenting an interpretive structural model of the factors influencing talent turnover in the Iranian Offshore Oil Company—this study falls within the scope of applied research and adopts an exploratory mixed-methods approach. The statistical population in the qualitative section included managers from the Iranian Offshore Oil Company, academics, and experts from the company. Using a purposive sampling method, ۱۲ participants were selected as the sample. In the quantitative section, data were also collected from experts in the Iranian Offshore Oil Company. The sample size in this section was determined using Cochran’s formula and simple random sampling. With a total population of ۲۵۰ individuals, the Cochran formula identified a sample size of ۱۵۲ participants. Data collection employed interviews and a researcher-developed questionnaire. Thematic analysis was used to develop the model, which was ultimately analyzed using structural equation modeling (SEM) with PLS software and the ISM technique. Results indicated that, among the model's components, livelihood status and skills and expertise were prioritized as the most critical factors by the experts, situated at the first level. Cultural and social environments and the political environment were ranked at the second level. Organizational policies, rules and processes, organizational climate, and organizational management were placed at the third level. Finally, influence and impact, along with being overlooked and undervalued, were categorized at the fourth level. From the managers' perspective, the most critical factors driving talent turnover included influence and impact, being overlooked and undervalued, livelihood status, and skills and expertise.

کلیدواژه ها:

Talent turnover ، Knowledge workers ، Experts ، Job satisfaction