Based on the cognitive-affective theoretical model of tourism destination image perception,this study utilizes big data mining technology to obtain Weibo comment texts from Shanghai Citywalk tourists.It then systemati...Based on the cognitive-affective theoretical model of tourism destination image perception,this study utilizes big data mining technology to obtain Weibo comment texts from Shanghai Citywalk tourists.It then systematically explores the characteristics of their tourism destination image perception through content analysis.The key findings are as follows:(1)At the cognitive image level,the attractions chosen by tourists for Citywalk form a“dual-core and multi-axis”network structure,with a preference for characteristic blocks that integrate cultural landscapes and local life scenes.The perception of the tourism environment exhibits multi-sensory interaction characteristics,which are instantaneously influenced by weather conditions.The preferred mode of transportation is the low-carbon combination of“subway+slow travel”.Furthermore,catering is deeply integrated with urban leisure,and accommodation services adequately meet short-term needs.(2)In terms of emotional image,positive emotions are dominant,primarily fueled by urban vitality,cultural collisions,and immersive experiences.Conversely,negative experiences mainly arise from crowds,high consumption costs,and adverse weather conditions.(3)The overall image perception is highly positive,evidenced by a significant willingness to revisit and recommend.However,optimization is needed concerning spatial carrying capacity and consumption affordability.Finally,the study actionable suggestions for optimizing the image of Shanghai’s Citywalk tourism destinations,thereby providing a theoretical foundation for urban micro-tourism design,promoting the development of Shanghai’s all-for-one tourism,and contributing to the establishment of a destination shared harmoniously by both residents and visitors.展开更多
基金The National Natural Science Foundation of China(42130510)。
文摘Based on the cognitive-affective theoretical model of tourism destination image perception,this study utilizes big data mining technology to obtain Weibo comment texts from Shanghai Citywalk tourists.It then systematically explores the characteristics of their tourism destination image perception through content analysis.The key findings are as follows:(1)At the cognitive image level,the attractions chosen by tourists for Citywalk form a“dual-core and multi-axis”network structure,with a preference for characteristic blocks that integrate cultural landscapes and local life scenes.The perception of the tourism environment exhibits multi-sensory interaction characteristics,which are instantaneously influenced by weather conditions.The preferred mode of transportation is the low-carbon combination of“subway+slow travel”.Furthermore,catering is deeply integrated with urban leisure,and accommodation services adequately meet short-term needs.(2)In terms of emotional image,positive emotions are dominant,primarily fueled by urban vitality,cultural collisions,and immersive experiences.Conversely,negative experiences mainly arise from crowds,high consumption costs,and adverse weather conditions.(3)The overall image perception is highly positive,evidenced by a significant willingness to revisit and recommend.However,optimization is needed concerning spatial carrying capacity and consumption affordability.Finally,the study actionable suggestions for optimizing the image of Shanghai’s Citywalk tourism destinations,thereby providing a theoretical foundation for urban micro-tourism design,promoting the development of Shanghai’s all-for-one tourism,and contributing to the establishment of a destination shared harmoniously by both residents and visitors.
