ZHOU Gang, LI Jing-mei. Impact assessment of the Ulva Prolifera disaster to the non-use value of coastal tourism resources based on dichotomous questionnaire[J]. Chinese Journal of MARINE ENVIRONMENTAL SCIENCE, 2019, 38(3): 335-341. DOI: 10.12111/j.mes20190303
Citation: ZHOU Gang, LI Jing-mei. Impact assessment of the Ulva Prolifera disaster to the non-use value of coastal tourism resources based on dichotomous questionnaire[J]. Chinese Journal of MARINE ENVIRONMENTAL SCIENCE, 2019, 38(3): 335-341. DOI: 10.12111/j.mes20190303

Impact assessment of the Ulva Prolifera disaster to the non-use value of coastal tourism resources based on dichotomous questionnaire

  • Algae blooms disaster has had a considerable impact on the socio-economic aspects of the coastal areas.Among them, the impact of coastal tourism economy and the impact of landscape resources, part of the impact of non-use value, cannot be directly evaluated from the market assessment.In the evaluation method of non-market value, condition evaluation method (CVM) is the one that most widely used.The method CVM collects the information of the respondents through the social survey and collects the questionnaire, and then evaluates the target resource value.In this paper, we use the dichotomous questionnaires to investigate the willingness of tourists to pay for the coastal landscape improving during the period of Ulva prolifera(a green tide).The binary choice model (logit regression model) tries to carry out the impact of the Ulva prolifera disaster on the non-use value of coastal tourism resources in Qingdao.This paper evaluates the general scope of the impact of the Ulva prolifera disaster on the value of coastal tourism resources in an intuitive way.In addition, this research, as a supplement to the socio-economic impact assessment methods and contents of the coastal algae disaster, provides the decision-making basis for the disaster and economic impact of the government and related organizations in the prevention, management and emergency decision-making of seaweed disasters and then help them to make decisions more reasonable and efficient.
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