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Organizational social commitment and employee well-being: illustrating a construct mining approach in R
Compromiso social organizacional y bienestar del empleado: ilustrando un enfoque de minería de constructos en R
DOI:
https://doi.org/10.15446/dyna.v89n223.99230Palabras clave:
organizational social commitment; employee well-being; latent variables; structural equation modelling; mining of constructs (en)compromiso social organizacional; bienestar del empleado; variables latentes; modelos de ecuaciones estructurales, minería de constructos (es)
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How employees react to an organization’s ethical/social initiatives has little support in terms of empirical evidence. We examine employee perceptions about organizational social commitment (OSC) and its association with employee well-being (WB). The sample consists of 289 participants of a healthcare organization in Colombia. We use a comprehensive methodology for mining psychological/managerial constructs in R comprising six processes (observe, explore, confirm, explain, predict, and report). We provide information concerning the scales’ plausibility, reliability, convergent/discriminant validity, and equity. We contrast the relationship between OSC and WB by using structural equation modelling with bootstrap approaches. We examine the capability of OSC to predict WB by using machine learning methods. We found a positive relationship between the constructs, which shows that OSC is a valuable strategy for contributing to employee objectives from a ‘being well together’ perspective. The paper stimulates/facilitates future research and teaching-learning initiatives in latent variable analysis using the R language.
La forma en que los empleados reaccionan a las iniciativas éticas/sociales de una organización ha tenido poco soporte empírico. Este artículo examina las percepciones de los empleados sobre el compromiso social organizacional (OSC) y su asocio con el bienestar de los empleados (WB). La muestra consta de 289 participantes de una organización de salud en Colombia. Se emplea una metodología integral para minar constructos psicológicos/gerenciales en R, la cual comprende seis procesos (observar, explorar, confirmar, explicar, predecir e informar). Se provee evidencia sobre plausibilidad, fiabilidad, validez convergente/discriminante y equidad de las escalas. Se contrasta la relación entre OSC y WB con uso de modelos de ecuaciones estructurales con Bootstrap. Se examina la capacidad de OSC para predecir WB usando métodos de aprendizaje automático. Se halla una relación positiva entre los constructos, lo que sugiere que el OSC es una estrategia valiosa para contribuir al bienestar de los empleados desde una perspectiva de 'estar bien juntos'. El artículo estimula/facilita futuras iniciativas de investigación y enseñanza-aprendizaje en el análisis de variables latentes usando lenguaje R.
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