The paper reports results from a use of non-radial DEA i.e., range adjusted measure (RAM) which belongs to data envelopment analysis to evaluate the performances of the truck restriction policy in China. We try to explore what is inside the “black box” on the restriction policy by empirical study. Using the non-radial DEA model, we work with an approach that allows a flexible designation of three input variables and two output variables based on varying perspectives in China. The multipurpose approach reveals whether one policy is truly beneficial instead of officials’ arguments, captured in the form of DEA scores. The modified model can better reflect macro-transportation process while earlier relevant models ignored truckers. This paper contributes to increasing traffic volumes and decreasing traffic accidents from the point of technical efficiency. The results of our paper reveal that: (a) China's truck restriction policies have achieved a significant “level effect” on efficiency improvement. (b) There are remarkable provincial differences in the effectiveness of the restriction policy. (c) Slack decomposition shows that excessive investment is the main source of inefficiency. Moreover, we delivery policy implications that: (a) the restriction policies greatly contribute to the efficiencies, and stringent policies are still needed in the following days; (b) the policy-making should suit local conditions, according to our classification of 30 provinces; (c) based on the worst performance of capital stock variable, the authorities should focus more on regulation of investment in transportation sector at a latter stage.
Xiaodong Chen, Ge Wu, Ding Li*, Efficiency measure on the truck restriction policy in China: A non-radial data envelopment model, Transportation Research Part A: Policy and Practice, Volume 129, November 2019, Pages 140-154.