Model of management variables in a recruitment, selection and performance evaluation process in the framework of economic reincorporation based on systems theories and the human occupation model

Published: 11 June 2024| Version 1 | DOI: 10.17632/y4xbzhm9r7.1
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Description

Resultado de 24 entrevistas en un proceso de investigación sobre procesos de selección, reclutamiento y evaluación de desempeño en el marco de la reincorporación sociolaboral en el escenario productivo del Norte de Santander, basados teoría de Sistemas y modelo de la Ocupación Humana - MOHO-

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Through the inquiry in the employer, of the selection tools, adaptation and labor sustainability based on elements of the volitional subsystem, habituation, performance capabilities of the Human Occupation Model and human management policies of the regional scenario of Norte de Santander. Interest groups were identified by productive sectors and aspects of the labor demand offered, then the interview construct was generated from the review and systematic analysis of the subsystems of the human occupation model. Subsequently, the variables are operationalized and the dimensions and categories underlying the review and identification of the informants are established. The semi-structured interview is organized and validated. Twenty-seven questions are defined. The interview is applied to 24 informants. The application of the interview and analysis of results is framed in the qualitative approach, interpretative paradigm with a phenomenological method supported by field work, assuming from this paradigm in social research; on the one hand, the interpretation made by the employers of the reality of the employability process and on the other hand, the one made by the researchers trying to understand it from the realities observed, documented and narrated by the actors. The Atlas.ti software NVivo 12 Pro TRIAL version was used. The results were plotted in Illustrator.

Institutions

Universidad de Santander

Categories

Data Analysis, Categorization (Cognitive Process), Massive Open Online Course, Open Data

Funding

Universidad de Santander

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