Modelo Predictivo del Rendimiento de Emprendimientos Asociativos en la Zona 6: Un Estudio en Cuatro Sectores Estratégicos

This research develops a predictive model to evaluate the performance of associative enterprises in Zone 6 of Ecuador, focusing on four strategic sectors: food, agriculture, textile, and cleaning sectors. The methodology integrates objective (business variables) and subjective (socio-organizational variables) approaches, selected from a literature review. A stratified probability sampling was applied to 20 representative associations. The data were analyzed using descriptive statistics, ANOVA and linear regression. The model was trained on 80% of the data and validated on the remaining 20%. Although no significant differences were found between sectors, variables with high impact on performance were identified, such as intangible technological resources, infrastructure, networks, financial profitability and solid waste disposal. This model makes it possible to identify key areas to guide strategies for strengthening associative enterprises in the region.

Publication Details

Journal
Dialnet (Universidad de la Rioja)
Published
2025-01-01
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Modelo Predictivo del Rendimiento de Emprendimientos Asociativos en la Zona 6: Un Estudio en Cuatro Sectores Estratégicos

Dialnet (Universidad de la Rioja)
Geochemistry and Geologic Mapping
article

Modelo Predictivo del Rendimiento de Emprendimientos Asociativos en la Zona 6: Un Estudio en Cuatro Sectores Estratégicos

article en

Abstract

This research develops a predictive model to evaluate the performance of associative enterprises in Zone 6 of Ecuador, focusing on four strategic sectors: food, agriculture, textile, and cleaning sectors. The methodology integrates objective (business variables) and subjective (socio-organizational variables) approaches, selected from a literature review. A stratified probability sampling was applied to 20 representative associations. The data were analyzed using descriptive statistics, ANOVA and linear regression. The model was trained on 80% of the data and validated on the remaining 20%. Although no significant differences were found between sectors, variables with high impact on performance were identified, such as intangible technological resources, infrastructure, networks, financial profitability and solid waste disposal. This model makes it possible to identify key areas to guide strategies for strengthening associative enterprises in the region.

Dialnet (Universidad de la Rioja)
Industry, innovation and infrastructure
Openalex Percentile: Top 64%
Geochemistry and Geologic Mapping
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