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Tourism centres efficiency as spatial unites for applying blue economy approach: A case study of the Southern Red Sea region, Egypt

Author

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  • Moaaz Kabil
  • Ebtehal Ahmed AbdAlmoity
  • Katalin Csobán
  • Lóránt Dénes Dávid

Abstract

This study aims to assess and analyse the efficiency of the tourism centres in the Southern Red Sea region, Egypt to apply coastal tourism development through the blue economy perspective. According to this aim, the study used two efficiency methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). A total of 29 tourism centres were selected to conduct the DEA and FDH methods. These efficiency methods (DEA-FDH) used inputs and outputs variables to estimate the efficiency of the tourism centres. The selected inputs were the length of the shoreline (km), area (ha), tourism investments (million EGP), quality of coral reefs, numbers of hotels, and tourism accommodation capacity. While the outputs were employees’ number and tourists’ number. The results indicate that, generally, the tourism centres in the Southern Red Sea region of Egypt showed high-efficiency scores, which reflects their good preparedness to implement the various coastal tourism development strategies from the blue economy perspective. The tourism centres in the Safaga-Quseir tourism sector were the most efficient ones, regardless of the efficiency models used. While the tourist centres representing the Ras Banas tourism sector were the least efficient centres in the whole sample (29 tourism centres).

Suggested Citation

  • Moaaz Kabil & Ebtehal Ahmed AbdAlmoity & Katalin Csobán & Lóránt Dénes Dávid, 2022. "Tourism centres efficiency as spatial unites for applying blue economy approach: A case study of the Southern Red Sea region, Egypt," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-17, July.
    • Handle: RePEc:plo:pone00:0268047
    DOI: 10.1371/journal.pone.0268047
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    1. Changping Yang & Yongxing Xia & Johnny F I Lam & Hongxi Chen & Huangxin Chen, 2024. "Analyzing the tourism efficiency and its influencing factors of China’s coastal provinces," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-24, May.

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