摘要
本文利用问卷调查获取数据,采用描述分析法和因子分析法对影响超山梅花节游客满意度的28个评价指标进行研究,结果表明:1)游客对超山梅花节的总体满意度较高,但部分主因子的评价会影响游客满意度的综合评价;2)因子分析法确定出6个主要影响因子,按其影响程度从大到小依次为:环境与忠诚度因子>旅游景观因子>旅游商品因子>餐饮与食品因子>服务质量因子>交通因子;3)游客对超山梅花节的总体满意度得分为2.83,交通因子得分最高(3.27),但对游客满意度影响程度最小,对游客满意度影响最大的因子是环境与忠诚度因子,满意度得分较低(2.89)。最后,根据游客满意度的分析结果,对超山梅花节提出发展建议。
We obtained the data from the questionnaire survey,and used the descriptive analysis method and factor analysis method to study the 28 evaluation indicators that affect the tourist satisfaction of the Chaoshan Plum Blossom Festival.The results show that:1)The tourist overall satisfaction with the Chaoshan Plum Blossom Festival was higher,but the evaluation of some of the main factors will affect the comprehensive evaluation of tourist satisfaction;2)Six main influencing factors were determined by factor analysis,and the order of influence degree was as follows:environment and loyalty factor>tourism landscape factor>tourism commodity factor>catering and food factor>service quality factor>traffic factor.3)The overall satisfaction score of the tourists to Chaoshan Plum Blossom Festival was 2.83,and the traffic factor score was the highest(3.27),but the degree of impact on tourist satisfaction was the least;the environment and loyalty had the greatest impact on the tourist satisfaction,with the lower satisfaction score(2.89).Finally,according to the analysis results of tourist satisfaction,we made the suggestions on the development of the Chaoshan Plum Blossom Festival.
作者
王莉丽
张建国
杨丽
张明如
WANG Li-li;ZHANG Jian-guo;YANG Li;ZHANG Ming-ru(School of Landscape Architecture and Architecture,School of Tourism and Health/Zhejiang A&F University,Lin'an 311300,China;Huzhou University,Huzhou 313000,China)
出处
《山东农业大学学报（自然科学版）》
北大核心
2020年第4期774-781,共8页
Journal of Shandong Agricultural University：Natural Science Edition
基金
浙江省科技厅公益技术研究农业项目:浙西南山区森林生态养生旅游区发展模式构建与示范(2016C32107)
浙江省农业软科学研究项目:浙江省农耕文化保护与开发研究(ZJNYRKXYJKT201604)
浙江省自然科学基金项目:亚热带低山丘陵区森林环境休憩适宜度的评价指标构建与模型研究(LY16C160008)。
关键词
游客满意度
因子分析法
影响因子
Tourist satisfaction
factor analysis
impact factor
