A study on the tourism efficiency of tourism destination based on DEA model: A case of ten cities in Shaanxi province
Yajun Guo and
Zhuo Cao
PLOS ONE, 2024, vol. 19, issue 1, 1-14
Abstract:
Exploring the of regional tourism efficiency is of great significance in promoting high-quality development of regional tourism. However, there are not many studies that measure the quality development of tourism destinations from the perspective of inputs and output. Based on this, the data envelopment analysis model is used to measure the overall technical efficiency (TECRS), pure technical efficiency (TEVRS), and scale efficiency (SE) with the help of DEA-SOLVER software, taking the ten prefecture-level cities in Shaanxi Province as examples, to further analyze and evaluate the spatial differences of different tourism destinations and the reasons for the differences. The results of the study found that: the efficiency indicators explain the differences in the development quality of tourism destinations from different sides; the development quality of tourism destinations in Shaanxi as a whole is low, with excessive inputs and insufficient outputs; and the tourism destinations with relatively high development quality are distributed in the Guanzhong. On this basis, corresponding countermeasure suggestions are put forward to promote the improvement of governance efficiency of tourism destinations in Shaanxi Province, and then optimize the quality of development.
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0296660 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 96660&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0296660
DOI: 10.1371/journal.pone.0296660
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().