Tourist attraction efficiency and its determinants using a two stage, double bootstrap data envelopment analysis: a case study in Indonesia.

Tourist attractions account for a critical component of tourism competitiveness. However, empirical research regarding tourist attraction efficiency is absent from literature. Respectively, this paper explores efficiency levels of tourist attractions and its determinants. 34 provinces of Indonesia were selected as the study setting. We employed the two-stage double bootstrap data envelopment analysis (DEA), an innovative approach that weathers the statistical shortcomings of the more traditional approaches. A 3-year data from 2017 to 2019 served for the analysis. Tourist attraction efficiency in Indonesia was relatively low. We revealed negative effects from population size, human development index (HDI), climate, and crime rate towards tourist attraction efficiency. Positive relationships were found for formal workforce, micro and small enterprises, and transportation. This study extends literature on tourism efficiency, and presents useful insights concerning tourism management. [ABSTRACT FROM AUTHOR]