Identifying the Effective Factors Contributing to Talent Management in Knowledge-Based Companies with a Focus on Knowledge Worker Retention

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Knowledge workers are the most valuable assets of knowledge-based companies, which necessitates to take measures in order to encourage knowledge worker retention. Definitely, talent management activities constitute an important part of these measures. Accordingly, the current study set out to identify the factors affecting talent management in knowledge-based companies with a focus on the retention of knowledge workers. To this end, after defining the research topic and conducting preliminary exploratory and library studies, the researchers consulted a panel of experts about the factors and components which were identified through Delphi method and a researcher- made questionnaire. Having received qualitative and quantitative feedback from the experts, the related analyses were conducted and ultimately, the model, components and the combination of factors were agreed upon. The study population at this point included 33 academic experts and professionals, familiar with the subject who were recruited through non-probability judgmental sampling. Then, in order to test the researcher-made questionnaire, it was distributed among 295 managers and experts of knowledge-based companies, located in the southeastern provinces of the country who were selected through random cluster sampling. The collected data were analyzed conducting confirmative factor analyses using Smart PLS 3 software. The results revealed that four factors of environmental, organizational, personal and occupational are effective in talent management in knowledge-based companies contributing to the retention of knowledge workers. Among these factors, organizational factors with the effect size of 68.7 were found to have the highest impact on talent management in knowledge-based companies in order to encourage the retention of knowledge workers.

Language:
Persian
Published:
Journal of Productivity Management, Volume:16 Issue: 60, 2022
Pages:
77 to 107
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