Causal Model of Talent Utilization, Engagement and Performance among Employees in the Seafood Processing Industry

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Yuwadi Chunthasiri
Ungsinun Intarakamhang
Nattapong Kongprasert
Stuart C. Carr
Amanda M Young-Hauser


The seafood processing industry in Thailand is facing a significant transition to industry 4.0. Therefore, the need exists to develop a causal model of talent utilization, engagement and performance and its effect on engagement and performance among employees. A sample of 360 talented persons working with the leading seafood processing industry in Southern Thailand were selected through purposive sampling technique.  Data were collected Likert questionnaires with reliability of 0.57-0.91 and analyzed using structural equation modeling (SEM.) The results of this research showed that the proposed model was  fit with the empirical data, c2 = 191.21, p= .00, c2/ df= 2.690,  RMSEA= .069, SRMR= .054,  GFI = .93, CFI= .98,  NFI= .97. The findings also indicated that causal factors had direct effects on performance including engagement and characteristics of talent (β= 68, t= 7.98) and   (β= .32, t= 5.08). Moreover, the characteristics of talent and talent utilization had direct effects on engagement (β= .56, t= 10.14) and (β= .34, t= 6.86). The findings also illustrated that the characteristics of talent and talent utilization had indirect effects on performance (β= .38, t= 6.48) and (β= .23, t= 5.24). All factors could predict performance and engagement with variance of .81% and .55 %. In practical terms, the results could be used by this industrial sector as a framework to improve performance. In addition to creating certain characteristics of talent, and utilizing this talent related with the context. Organizations could also build employee engagement levels through strong strategies, which lead to higher performance.

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Chunthasiri, Y., Intarakamhang, U., Kongprasert, N., Carr, S. C., & Young-Hauser, A. M. (2021). Causal Model of Talent Utilization, Engagement and Performance among Employees in the Seafood Processing Industry. The Journal of Behavioral Science, 16(3), 109–122. Retrieved from
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