The adoption of photovoltaic (PV) systems by micro- and small enterprises (MSEs) continues to represent a major challenge in emerging economies, even though the economic, environmental, and energy-security benefits of solar technologies are widely recognized. In contexts such as Colombia, where MSEs account for a substantial share of economic activity and electricity demand, the diffusion of distributed solar energy remains limited. This situation highlights the need to better understand the factors that shape adoption decisions beyond purely technical or financial considerations, particularly those related to individual perceptions, organizational conditions, and the broader institutional environment. This study investigates the determinants of MSEs’ intention to adopt photovoltaic systems by integrating the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) framework into a unified explanatory model. This integrated approach allows for a comprehensive assessment of both individual-level cognitive factors and organizational and environmental influences affecting technology adoption. Data were collected from micro- and small enterprises operating across diverse economic sectors, ensuring heterogeneity in organizational characteristics and energy use profiles. The proposed model was empirically tested using partial least squares structural equation modeling (PLS-SEM), a method well suited for exploratory analysis and prediction-oriented research.

The analytical procedure followed several stages, including the validation of the measurement model, the estimation of direct and indirect relationships through bootstrapping, and predictive performance assessment using the root-mean-square error (RMSE) and Stone–Geisser’s Q². Additionally, importance–performance map analysis (IPMA) was applied to identify the most relevant constructs for managerial and policy intervention. The results reveal that TAM-related variables, perceived usefulness, perceived ease of use, and attitude toward photovoltaic systems, are the strongest predictors of adoption intention, explaining a substantial proportion of its variance. In contrast, organizational and environmental factors, such as management support, regulatory incentives, and energy cost pressure, show mainly indirect or comparatively weaker effects. Overall, the findings suggest that photovoltaic adoption among MSEs is driven primarily by individual cognitive and evaluative processes rather than external pressures. This underscores the importance of user-oriented system design, simplified financing mechanisms, and targeted capacity-building strategies aimed at enhancing perceptions of usefulness and ease of use, thereby accelerating the energy transition in small businesses.