This paper introduces a General Weight Assurance Region (GWAR) model for assessing the efficiency of decision-making units with a two-stage network structure. The proposed model can handle multiple input, output and intermediate variables at both stages, including leakage variables in the first stage and inputs that enter the system in the second stage. The general structure of the model gives greater flexibility to the weights assigned to the two stages relative to the Weight Assurance Region (WAR) and the conventional additive network DEA model. Consequently, the weights of the GWAR model are not strictly non-increasing but they can take on any possible value in the range of 0 to 1. As a result, they do not suffer from the criticism of Ang and Chen (2016). Furthermore, the GWAR model can be considered as the general case of all additive network DEA models. The applicability of the model is demonstrated by evaluating the performance of UK investment trusts for 2019. The overall fund performance is decomposed into operational management performance in the first stage and portfolio management performance in the second stage. The results reveal that the general structure of the model increases the discriminatory power of the overall fund performance. Moreover, there is a large variation in the efficiency scores across the sample of investment trusts and no significant relationship between efficiency and size.
|Publication status||Published - 2020|
|Event||11th North American Productivity Workshop (NAPW XI Virtual) - University of Miami Business School (Virtual), Miami, United States|
Duration: 8 Jun 2020 → 12 Jun 2020
|Conference||11th North American Productivity Workshop (NAPW XI Virtual)|
|Period||8/06/20 → 12/06/20|