Assessing the Service Quality of Fisherman's Homestays in China: a Hybrid MADM Approach Consisting of DANP and Grey Clustering Evaluation

被引:0
作者
Jiang, Peng [1 ]
Chi, Rui [1 ]
Xin, Hui [1 ]
Zhang, Longyun [1 ]
Ju, Chuandong [2 ]
机构
[1] Shandong Univ, Business Sch, Weihai 264209, Shandong, Peoples R China
[2] Shandong Univ, Data Sci Inst, Jinan 250000, Shandong, Peoples R China
关键词
Fisherman's homestay; Service quality; Multiple-attribute decision-making; Delphi method; DANP; Grey clustering model; DECISION-MAKING; KANO MODEL; DESTINATION IMAGE; SUCCESS FACTORS; PERCEIVED VALUE; DELPHI METHOD; TOURISM; SATISFACTION; EXPERIENCE; INDUSTRY;
D O I
暂无
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Nowadays, a new emerging tourism industry, named fisherman's homestay, has become a very representative marine leisure tourism project, widely promoted in coastal areas in China. However, the development of China's fisherman's homestay industry is not yet mature and there are many problems, such as incomplete laws and regulations, lack of infrastructure, and severe homogenization. Therefore, it is very important to help the owners of fisherman's homestay improve the service quality. Based on the Service Quality Gap Model, this paper establishes an evaluation index that affects the service quality of fishermen's homestay. We apply decision- making trial and evaluation laboratory-based analytic network process (DANP) to identify the critical factors and the causal relationship between them. And the grey clustering model is used to evaluate the service quality of Lisoning province and other five places. Experimental results reveal those six factors, including surrounding facilities, online marketing, room infrastructure, personalized service, community co-prosperity, and attention to harmonization with the environment, contribute to improving the service quality of fisherman's homestays. The fisherman's homestays in Shandong Province, Liaoning Province, and Zhejiang Province are in "excellent" level, and the fisherman's homestays in Fujian Province and Guangxi Zhuang Autonomous Region are in "good" level.
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页数:119
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