Desarrollo de un indicador compuesto de propensión perceptual a la adopción de biomasa forestal en pellets en el segmento residencial

Otros responsables
Fecha
12/2025
Editorial
Red de Investigadores Latinoamericanos
Revista
Latam
Título del libro
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Institución organizadora
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eISSN
2789-3855
ISBN
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Español
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Resumen
El presente trabajo presenta el desarrollo y aplicación de un indicador compuesto, que refleja la propensión a la adopción de biomasa forestal pelletizada (BFP), como energético sustituto del empleado habitualmente para calefacción en hogares residenciales. Este indicador es de origen perceptual, pues su construcción parte de la percepción que una muestra de usuarios residenciales, manifiestan sobre un conjunto de variables relacionadas con tres dimensiones centrales de la BFP: calidad energética, comercialización y logística, y dificultades operativas de uso. El procedimiento de construcción sigue un enfoque metodológico mixto, en etapas secuenciales, que emplea: técnicas del análisis estadístico multivariado (análisis factorial exploratorio -AFE-, análisis factorial confirmatorio -AFC- Multi-grupo), optimización soportada en análisis envolvente de datos -DEA-IC-, y simulación para configuraciones estables de mínima dispersión del indicador compuesto adoptado como operativo (método de Montecarlo). El indicador compuesto operativo queda, entonces, validado conforme las métricas exigidas para cada etapa, tanto por la literatura como por las buenas prácticas sugeridas por expertos. El estudio se realizó a partir de una encuesta a individuos jefes de hogar, pertenecientes al segmento residencial suburbano (considerado de alto potencial de penetración para la BFP), en una región de las provincias de Córdoba y Santa Fe, Argentina, cuyos perfiles de consumo energético tienen similares características. Los resultados resultaron de gran utilidad para la definición de políticas de incentivos que favorezcan la penetración de la BFP en forma segmentada por región.
This paper presents the development and application of a composite indicator that reflects the propensity to adopt Biomass from Forest Residue Pelletizing (BFRP) as a substitute energy source for heating in residential homes. This indicator is perceptual in origin, as its construction is based on the perceptions expressed by a sample of residential users regarding a set of variables related to three core dimensions of BFRP: energy quality, marketing and logistics, and operational difficulties of use. The construction procedure follows a mixed-methods approach, in sequential stages, employing multivariate statistical analysis techniques (exploratory factor analysis -EFA-, confirmatory factor analysis -CFA- Multi-group), optimization supported by data envelopment analysis -DEA-IC-, and simulation for stable parameters of minimum dispersion of the composite indicator adopted as operational (Montecarlo method). The operational composite indicator is then validated according to the metrics required for each stage, both by the literature and by best practices suggested by experts. The study was based on a survey of heads of households in the suburban residential segment (considered to have high potential for BFRP penetration) in a region encompassing the provinces of Córdoba and Santa Fe, Argentina, whose energy consumption profiles share similar characteristics. The results proved highly useful for defining incentive policies that promote BFRP penetration in a segmented manner by region.
This paper presents the development and application of a composite indicator that reflects the propensity to adopt Biomass from Forest Residue Pelletizing (BFRP) as a substitute energy source for heating in residential homes. This indicator is perceptual in origin, as its construction is based on the perceptions expressed by a sample of residential users regarding a set of variables related to three core dimensions of BFRP: energy quality, marketing and logistics, and operational difficulties of use. The construction procedure follows a mixed-methods approach, in sequential stages, employing multivariate statistical analysis techniques (exploratory factor analysis -EFA-, confirmatory factor analysis -CFA- Multi-group), optimization supported by data envelopment analysis -DEA-IC-, and simulation for stable parameters of minimum dispersion of the composite indicator adopted as operational (Montecarlo method). The operational composite indicator is then validated according to the metrics required for each stage, both by the literature and by best practices suggested by experts. The study was based on a survey of heads of households in the suburban residential segment (considered to have high potential for BFRP penetration) in a region encompassing the provinces of Córdoba and Santa Fe, Argentina, whose energy consumption profiles share similar characteristics. The results proved highly useful for defining incentive policies that promote BFRP penetration in a segmented manner by region.
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