Theme park reviews: how text mining cognitive characteristics and emotions can determine theme park image

主题(计算) 主题公园 认知 心理学 社会学 地理 计算机科学 旅游 考古 万维网 神经科学
作者
Yufei Liu,Yunpeng Li,Shihan Ma,Jingjing Li
出处
期刊:Tourism Review [Emerald Publishing Limited]
卷期号:81 (1): 27-47 被引量:4
标识
DOI:10.1108/tr-07-2024-0554
摘要

Graphical abstract Purpose The theme park industry has attracted wide attention and visitors’ perceptions are key to improving theme park management. Applying the cognitive-affective theory, this study aims to explore various cognitive attributes and affective attitudes and how they affect the overall theme park image. Design/methodology/approach A mixed research method was used to analyze tourists’ cognitive, affective and overall evaluations of theme parks through text mining and logistic regression and to verify their internal relationships. Findings Study 1 confirms the impact of six features of theme parks, including food and beverage consumption, merchandising, spatiality, immersive technologies, interactive performances and thematization. Study 2 reveals that finer-grained emotions such as goodness, sadness, disgust, surprise, fear, joy and anger are present in visitor reviews. Study 3 confirms the significant influence of cognitive characteristics and emotions related to theme parks on the overall image through regression analysis. The findings carry meaningful implications for theme park managers, offering guidance on customer needs, perceived negative attributes and how to improve visitor experiences. Originality/value This study explores the attribute characteristics of cognitive and affective images of theme parks and their influence on the overall image, thereby enriching the research on the connotations of cognitive-affective theory. In particular, this study introduces and quantitatively analyses the concept of theme parks for the first time through a large-scale data analysis, which empirically reconciles the contradictions of previous reviews of different definitions of theme parks.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.3应助Zxxxxxxx采纳,获得10
1秒前
1秒前
1秒前
口外彭于晏完成签到,获得积分10
1秒前
鱿鱼的云朵完成签到,获得积分10
2秒前
时尚契发布了新的文献求助10
2秒前
科研dog完成签到,获得积分10
2秒前
小蘑菇应助崔伊凡采纳,获得10
2秒前
2秒前
Ai_niyou发布了新的文献求助10
4秒前
4秒前
yuansongqian发布了新的文献求助10
4秒前
科研通AI6.3应助blawxx采纳,获得10
4秒前
4秒前
蓝色花生豆完成签到,获得积分0
4秒前
科研dog发布了新的文献求助10
5秒前
5秒前
星辰大海应助张无凡采纳,获得10
5秒前
sci大户发布了新的文献求助10
5秒前
Nole应助LiBang采纳,获得10
6秒前
丘比特应助123采纳,获得10
6秒前
研友_Y59685发布了新的文献求助10
6秒前
大力的雪珊完成签到,获得积分10
6秒前
beibei完成签到,获得积分10
6秒前
领导范儿应助兴奋的千筹采纳,获得10
7秒前
vince完成签到,获得积分10
7秒前
机智火车完成签到,获得积分20
7秒前
中级中级发布了新的文献求助10
7秒前
8秒前
8秒前
无聊的曼凝完成签到 ,获得积分10
8秒前
8秒前
乔垣结衣完成签到,获得积分10
9秒前
脑洞疼应助时尚契采纳,获得10
9秒前
HD发布了新的文献求助10
9秒前
10秒前
bkagyin应助fy采纳,获得10
10秒前
cl完成签到,获得积分10
11秒前
11秒前
赘婿应助毕先生采纳,获得30
12秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7238261
求助须知:如何正确求助?哪些是违规求助? 8863565
关于积分的说明 18696583
捐赠科研通 6908576
什么是DOI,文献DOI怎么找? 3194315
关于科研通互助平台的介绍 2366473
邀请新用户注册赠送积分活动 2168919