Assessing efficiency and determinants of tourist attractions based on a two-subprocess perspective: A case of Chengdu, southwestern China

Abstract

Abstract: This paper divides the entire operating process of a tourist attraction into the production subprocess and the environmental governance subprocess from a two-subprocess perspective, and evaluates the overall efficiency and the respective subprocess efficiency by establishing a range-adjusted measure (RAM) network data envelopment analysis (DEA) model and further identifies the determinants of efficiency using a panel Tobit regression model. The applicability of the proposed model was examined using 25 tourist attractions in Chengdu during the period 2012–2016 as cases. The first-stage efficiency results show that only a few tourist attractions perform efficiently in two sub-processes and achieve overall efficiency during the observed period. In particular, most tourist attractions outperform environmental governance in the production subprocess. The overall efficiency is highly correlated with production efficiency and environmental governance efficiency. The second-stage regression analysis implies that the scale effect and technology effect have significant positive impacts on efficiency improvement, while the capital effect and resource endowment effect have significant negative impacts. The structure effect has no significant impacts, and environmental regulation has a significant positive impact on environmental governance efficiency and overall efficiency. Overall, the proposed model has better discriminatory power in distinguishing inefficient subprocesses than the traditional ‘black box’ models and provides process-specific guidance for efficiency improvement. This study broadens the perspective of efficiency benchmarking and improves the performance evaluation of tourist attractions, and the empirical results provide some valuable policy implications for destination management in tourist attractions.