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The purpose of personnel selection is to measure knowledge, skills, and abilities that are necessary to perform a job effectively. The process involves various assessments, including personality assessment. This conceptual paper discussed the potential of using a learning factory to develop multiple simulations for assessment center activities in assessing personality in different situations. Although traditional personality assessment contributes to the effectiveness of selection decisions and prediction, it tended to ignore that trait-related behaviors may differ across situations. Study on dynamic personality is essential as empirical studies showed that within-person fluctuations in personality states relate to a variety of work outcomes, including job performance. To further understand this fundamental issue, this paper discussed further how personality–situation interplay influences performance by using a learning factory assessment center method. This study also discussed how the adaptation of exploratory mixed methods approach could be used. The mixed exploratory methods are suitable as this topic is related to fundamental research and empirical study, besides the investigation on this area is still limited. This paper could benefit other researchers, industry players, and policymakers in understanding better how dynamic personality may influence performance, especially in the activities related to Industry 4.0.

Multi-Approach Formulation in Dynamic Personality-Situation Interaction for Personnel Selection