Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model

Based on the idea of coordinated and sustainable development, the photovoltaic poverty alleviation project (PPAP) supplies clean electricity and assists poverty-stricken households, which receives widespread attention from the society. However, the existing efficiency assessment models can neither well consider both the economic and social benefits of the PPAP nor provide pertinent site selection suggestions. To accurately evaluate the performance efficiency and explore the influencing factors, a modified three-phase model is proposed: First of all, a two-step approach combining Pearson correlation coefficient and super-efficiency analysis is adopted to screen out unreasonable variables and outliers, which improves the reliability of subsequent calculations; Next, the bootstrapping algorithm is introduced to optimize the data envelopment analysis model, which effectively corrects the bias and guarantee the model accuracy; Finally, the potential environment variables are extracted from both the electricity conversion process and the poverty alleviation procedure, and further verified by Tobit regression, which provides managers with more comprehensive decision support. According to the results, the performance efficiency of PPAPs in China is generally low due to the unreasonable production scale. Most projects are suffering excessive labor input. Moreover, improper site selection is also a cause for low efficiency, and some corresponding suggestions are proposed.