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Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Mejora de Procesos Organizacionales bajo Indeterminación: Un Modelo Neutrosófico de Diagnóstico y Optimización basado en Causalidad Parcial

Authors: Malavé Gómez, Andrea Mariel;

Mejora de Procesos Organizacionales bajo Indeterminación: Un Modelo Neutrosófico de Diagnóstico y Optimización basado en Causalidad Parcial

Abstract

La mejora de procesos organizacionales es una actividad crítica para la competitividad empresarial, pero frecuentemente se realiza bajo condiciones de incertidumbre, indeterminación e información incompleta. Este artículo propone un modelo neutrosófico integrado de diagnóstico y optimización de procesos que incorpora explícitamente la causalidad parcial a través de la metodología Neutrosophic Fuzzy-Set Qualitative Comparative Analysis (Neutrosophic fsQCA). El modelo propuesto permite identificar las configuraciones causales complejas que generan tanto el desempeño exitoso como el deficiente en procesos organizacionales, considerando simultáneamente los grados de verdad, indeterminación y falsedad en las relaciones causales. Se desarrolla un ejemplo ilustrativo en el contexto de mejora de procesos de servicio al cliente, demostrando cómo el enfoque neutrosófico de causalidad parcial puede revelar configuraciones causales que los métodos tradicionales no detectan. Los resultados muestran que el modelo es especialmente valioso para organizaciones que operan en entornos complejos, dinámicos e inciertos, permitiendo una comprensión más profunda de los factores que impulsan o inhiben la mejora de procesos.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green