IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0268047.html

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0268047
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0268047&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0268047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. F Pedraja-Chaparro & J Salinas-Jiménez & P Smith, 1999. "On the quality of the data envelopment analysis model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(6), pages 636-644, June.
    2. Hilde Reinertsen & Kristin Asdal, 2019. "Calculating the blue economy: producing trust in numbers with business tools and reflexive objectivity," Journal of Cultural Economy, Taylor & Francis Journals, vol. 12(6), pages 552-570, November.
    3. Dominique Deprins & Léopold Simar & Henry Tulkens, 2006. "Measuring Labor-Efficiency in Post Offices," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 285-309, Springer.
    4. Sharon Hadad & Yossi Hadad & Miki Malul & Mosi Rosenboim, 2012. "The Economic Efficiency of the Tourism Industry: A Global Comparison," Tourism Economics, , vol. 18(5), pages 931-940, October.
    5. Moaaz Kabil & Setiawan Priatmoko & Róbert Magda & Lóránt Dénes Dávid, 2021. "Blue Economy and Coastal Tourism: A Comprehensive Visualization Bibliometric Analysis," Sustainability, MDPI, vol. 13(7), pages 1-25, March.
    6. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    7. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    8. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    9. Rashidi, Kamran & Cullinane, Kevin, 2019. "Evaluating the sustainability of national logistics performance using Data Envelopment Analysis," Transport Policy, Elsevier, vol. 74(C), pages 35-46.
    10. Bruno de Borger & Kristiaan Kerstens & Wim Moesen & Jacques Vanneste, 1994. "A non-parametric Free Disposal Hull (FDH) approach to technical efficiency: an illustration of radial and graph efficiency measures and some sensitivity results," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(4), pages 647-667, December.
    11. Benjamin S. Halpern & Catherine Longo & Darren Hardy & Karen L. McLeod & Jameal F. Samhouri & Steven K. Katona & Kristin Kleisner & Sarah E. Lester & Jennifer O’Leary & Marla Ranelletti & Andrew A. Ro, 2012. "An index to assess the health and benefits of the global ocean," Nature, Nature, vol. 488(7413), pages 615-620, August.
    12. Yin, Xu & Wang, Jing & Li, Yurui & Feng, Zhiming & Wang, Qianyi, 2021. "Are small towns really inefficient? A data envelopment analysis of sampled towns in Jiangsu province, China," Land Use Policy, Elsevier, vol. 109(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    2. Dariush Khezrimotlagh & Wade D. Cook & Joe Zhu, 2021. "Number of performance measures versus number of decision making units in DEA," Annals of Operations Research, Springer, vol. 303(1), pages 529-562, August.
    3. M I Gonzalez-Bravo, 2007. "Prior-Ratio-Analysis procedure to improve data envelopment analysis for performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(9), pages 1214-1222, September.
    4. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    5. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    6. Hong, Seock-Jin & Zhang, Anming & Caliskan, Ferhat & Idug, Yavuz, 2025. "Impact of environmental, social, and governance (ESG) on productivity of major air cargo integrators," Transport Policy, Elsevier, vol. 167(C), pages 295-306.
    7. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2015. "Testing the accuracy of DEA estimates under endogeneity through a Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 244(2), pages 511-518.
    8. Hokey Min & Young‐Hyo Ahn & Jin‐Hee Ma, 2024. "Measuring dynamic supply chain risks for the offshoring decision in the post‐COVID‐19 era: A longitudinal study," Transportation Journal, John Wiley & Sons, vol. 63(3), pages 188-206, July.
    9. Ole Bent Olesen & Niels Christian Petersen & Victor V. Podinovski, 2022. "Scale characteristics of variable returns-to-scale production technologies with ratio inputs and outputs," Annals of Operations Research, Springer, vol. 318(1), pages 383-423, November.
    10. repec:fgv:epgrbe:v:68:n:2:a:2 is not listed on IDEAS
    11. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    12. Takashi Hiraide & Shinya Hanaoka & Takuma Matsuda, 2022. "The Efficiency of Document and Border Procedures for International Trade," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    13. Li, Yongjun & Yang, Feng & Liang, Liang & Hua, Zhongsheng, 2009. "Allocating the fixed cost as a complement of other cost inputs: A DEA approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 389-401, August.
    14. Chen, Chih Cheng, 2017. "Measuring departmental and overall regional performance: applying the multi-activity DEA model to Taiwan׳s cities/counties," Omega, Elsevier, vol. 67(C), pages 60-80.
    15. Bojiang Yang & Youliang Zhang & Hongjun Zhang & Rui Zhang & Baoyu Xu, 2016. "Factor-specific Malmquist productivity index based on common weights DEA," Operational Research, Springer, vol. 16(1), pages 51-70, April.
    16. Guillen, Maria D. & Aparicio, Juan & Kapelko, Magdalena & Esteve, Miriam, 2025. "Measuring environmental inefficiency through machine learning: An approach based on efficiency analysis trees and by-production technology," European Journal of Operational Research, Elsevier, vol. 321(2), pages 529-542.
    17. C Kao & H-T Hung, 2005. "Data envelopment analysis with common weights: the compromise solution approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1196-1203, October.
    18. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    19. Benegas, Maurício & da Silva, Francisco Gildemir, 2014. "Estimação da Eficiência Técnica do SUS nos Estados Brasileiros na Presença de Variáveis Contextuais," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(2), June.
    20. Papaioannou, Grammatoula & Podinovski, Victor V., 2023. "Production technologies with ratio inputs and outputs," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1164-1178.
    21. Ole Bent Olesen & Niels Christian Petersen & Victor V. Podinovski, 2022. "The structure of production technologies with ratio inputs and outputs," Journal of Productivity Analysis, Springer, vol. 57(3), pages 255-267, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0268047. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.