An Analytics Framework for Modeling Residential Photovoltaic Adoption and Decision Dynamics
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866914588661907456 |
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| author | Callau-Boix, Canigó Toral, Raúl Colet, Pere |
| author_facet | Callau-Boix, Canigó Toral, Raúl Colet, Pere |
| contents | Photovoltaic generation plays a central role in the energy transition, yet understanding its adoption dynamics requires robust analytical frameworks that capture both temporal and spatial patterns of decision behavior. This study applies a data-driven decision analytics approach to examine residential self-consumption photovoltaic installations in Catalonia within an innovation diffusion framework. The temporal evolution of adoption is modeled using a logistic growth function, providing evidence that imitation effects are a primary driver of adoption decisions. To extend the analysis, a quantitative methodology is developed to estimate the influence of external factors on adoption behavior, revealing that social perception exerts a stronger impact than regulatory and socioeconomic variables when considered independently. In addition, a spatial analytics component is incorporated to assess territorial heterogeneity, identifying correlations between adoption patterns and demographic and socioeconomic characteristics. The findings contribute to predictive and diagnostic analytics by offering a structured framework to model technology diffusion and inform policy and investment decisions aimed at accelerating sustainable energy adoption. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_22699 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An Analytics Framework for Modeling Residential Photovoltaic Adoption and Decision Dynamics Callau-Boix, Canigó Toral, Raúl Colet, Pere Physics and Society Photovoltaic generation plays a central role in the energy transition, yet understanding its adoption dynamics requires robust analytical frameworks that capture both temporal and spatial patterns of decision behavior. This study applies a data-driven decision analytics approach to examine residential self-consumption photovoltaic installations in Catalonia within an innovation diffusion framework. The temporal evolution of adoption is modeled using a logistic growth function, providing evidence that imitation effects are a primary driver of adoption decisions. To extend the analysis, a quantitative methodology is developed to estimate the influence of external factors on adoption behavior, revealing that social perception exerts a stronger impact than regulatory and socioeconomic variables when considered independently. In addition, a spatial analytics component is incorporated to assess territorial heterogeneity, identifying correlations between adoption patterns and demographic and socioeconomic characteristics. The findings contribute to predictive and diagnostic analytics by offering a structured framework to model technology diffusion and inform policy and investment decisions aimed at accelerating sustainable energy adoption. |
| title | An Analytics Framework for Modeling Residential Photovoltaic Adoption and Decision Dynamics |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2605.22699 |