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Supporting BLUE Growth: Eliciting Stakeholders' preferences for Multiple-Use Offshore Platforms

Author

Listed:
  • Osiel Gonzalez Davila
  • Phoebe Koundouri
  • Ioannis Souliotis
  • Erasmia Kotroni
  • Wenting Chen
  • Claire Haggett
  • Shiau-Yun Lu
  • David Rudolph

Abstract

The objective of this paper is to elicit stakeholder preferences in relation to different Multiple Use Offshore Platforms (MUOP) designs produced by the TROPOS project (www.troposplatform.eu) for the Liuqiu Island, Taiwan using the Choice Experiment (CE) method. To authors/ acknowledge, this is the first non-market valuation of multiple use offshore platforms and definitely the first using CE in this context. The MUOP concept is defined as a floating platform moored in Taiwan shallow waters located offshore and concerned as a sustainable and ecologic location, which supports the development of the local economy and serves as an example of sustainable development in offshore environments. The CE was conducted on tourists and residents of the area. A ranking preference technique with visual aids was used, in order to obtain a more complete characterization of the respondents� preference structure. The attributes used were the environmental impacts of the modules (using an ecosystem services approach), the level of mitigation, the existence of renewable energy production and leisure facilities. The results show that residents would be less likely to support the development of such a project, compared to tourists that would be willing to pay a daily tax for the leisure and renewable energy facilities.

Suggested Citation

  • Osiel Gonzalez Davila & Phoebe Koundouri & Ioannis Souliotis & Erasmia Kotroni & Wenting Chen & Claire Haggett & Shiau-Yun Lu & David Rudolph, 2015. "Supporting BLUE Growth: Eliciting Stakeholders' preferences for Multiple-Use Offshore Platforms," DEOS Working Papers 1504, Athens University of Economics and Business.
  • Handle: RePEc:aue:wpaper:1504
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    Keywords

    Choice Experiment; Multiple Use Offshore Platform; Ranking Preference technique;
    All these keywords.

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