Abstract
Because comfort on whale watching vessels is important to tourist satisfaction, this paper aims to identify its associated factors and establish a prediction model of comfort in the Taiwanese context. A survey of 1199 passengers was conducted over 41 voyages. Information on passenger characteristics, prior seasickness experiences, use of anti-seasickness tablets and self-assessed comfort were collected. Results indicate that gender, prior seasickness experiences and sea conditions were significantly associated with self-assessed comfort. A binary logit regression was employed to establish a prediction model of comfort with a correct classification rate of 76.6%. This model, serving as a recreation guide, preferably developed in the form of websites or Apps, facilitates visitors’ decision-making on whether to take trips or take precautions against potential discomfort. Future research was suggested on the robustness and refinement of the model and use of alternative scales in measuring comfort.
| Original language | English |
|---|---|
| Article number | 104915 |
| Journal | Ocean and Coastal Management |
| DOIs | |
| Publication status | Accepted/In press - 2019 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Oceanography
- Aquatic Science
- Management, Monitoring, Policy and Law
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A nuisance at sea : Decoding tourists’ comfort on whale watching vessels. / Chuang, Zsu-Hsin; Chen, Chung Ling; Kung, Che Wei; Shih, Yi Che.
In: Ocean and Coastal Management, 01.01.2019.Research output: Contribution to journal › Article
TY - JOUR
T1 - A nuisance at sea
T2 - Decoding tourists’ comfort on whale watching vessels
AU - Chuang, Zsu-Hsin
AU - Chen, Chung Ling
AU - Kung, Che Wei
AU - Shih, Yi Che
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Because comfort on whale watching vessels is important to tourist satisfaction, this paper aims to identify its associated factors and establish a prediction model of comfort in the Taiwanese context. A survey of 1199 passengers was conducted over 41 voyages. Information on passenger characteristics, prior seasickness experiences, use of anti-seasickness tablets and self-assessed comfort were collected. Results indicate that gender, prior seasickness experiences and sea conditions were significantly associated with self-assessed comfort. A binary logit regression was employed to establish a prediction model of comfort with a correct classification rate of 76.6%. This model, serving as a recreation guide, preferably developed in the form of websites or Apps, facilitates visitors’ decision-making on whether to take trips or take precautions against potential discomfort. Future research was suggested on the robustness and refinement of the model and use of alternative scales in measuring comfort.
AB - Because comfort on whale watching vessels is important to tourist satisfaction, this paper aims to identify its associated factors and establish a prediction model of comfort in the Taiwanese context. A survey of 1199 passengers was conducted over 41 voyages. Information on passenger characteristics, prior seasickness experiences, use of anti-seasickness tablets and self-assessed comfort were collected. Results indicate that gender, prior seasickness experiences and sea conditions were significantly associated with self-assessed comfort. A binary logit regression was employed to establish a prediction model of comfort with a correct classification rate of 76.6%. This model, serving as a recreation guide, preferably developed in the form of websites or Apps, facilitates visitors’ decision-making on whether to take trips or take precautions against potential discomfort. Future research was suggested on the robustness and refinement of the model and use of alternative scales in measuring comfort.
UR - http://www.scopus.com/inward/record.url?scp=85070873340&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070873340&partnerID=8YFLogxK
U2 - 10.1016/j.ocecoaman.2019.104915
DO - 10.1016/j.ocecoaman.2019.104915
M3 - Article
AN - SCOPUS:85070873340
JO - Ocean and Coastal Management
JF - Ocean and Coastal Management
SN - 0964-5691
M1 - 104915
ER -