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The impacts of natural hazards on Taiwan’s tourism industry

Natural Hazards (Impact Factor: 1.64). 62(1). DOI: 10.1007/s11069-011-0034-z

ABSTRACT Typhoon Morakot hit Taiwan in 2009, severely damaging the Alishan National Forest Recreation Area, a famous tourist resort in Taiwan. The only highway to this area was under repair for 10 months after the typhoon. Consequently, Alishan’s tourism industry suffered losses estimated at NT$1 billion. This work investigates the impacts of natural hazards on Taiwan’s tourism industry. First, government, university, and industry experts were invited to a focus-group interview to update criteria for tourism development in Taiwan. Next, the Analytic Hierarchy Process (AHP) was applied to rank the proposed criteria. Last, two tourist attractions, one urban and one rural, are discussed in detail. This work proposes three novel dimensions for Taiwan’s tourism development—destination attraction, destination arrangement, and contingency planning for natural hazards—which comprise nine criteria. Analytical results will provide Taiwan’s tourism industry with references for future policy-making and sustainable development.

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    ABSTRACT: The Analytical Hierarchy Process (AHP) is a classic and powerful decision support tool. However, the conventional AHP has some disadvantages originating in the expert decision-making process. To minimize the disadvantages of the conventional AHP, a modified analytical hierarchy process (M-AHP), is suggested in this study. This study is conducted in three stages: (i) the theoretical background for the conventional AHP is introduced, (ii) essentials for the proposed M-AHP technique are given with an example solution for the evaluation of snow avalanche source susceptibility, and (iii) a computer code named M-AHP is presented. By applying the methodology suggested in this study, the consistency ratio value for the comparison matrix and the weight vector never exceeds 0.10. The M-AHP program is a complementary tool for natural hazard, natural resource, or nature preservation researchers who apply the M-AHP technique to their decision support problem.
    Computers & Geosciences 09/2013; 59:1–8. · 1.83 Impact Factor