2095-1124

CN 51-1738/F

注意力经济视角下旅游地形象优化策略以丽江古城为例

Optimization Strategy of Tourism Destination Image from the Perspective of Attention EconomyTaking Lijiang Ancient City as an example

  • 摘要: 旅游业进入了注意力经济时代,科学管理公众稀缺的注意力资源对于推动旅游地形象优化、增强旅游业竞争优势具有重要作用。基于注意力经济视角,本文对注意力经济的内涵以及旅游地形象优化要素进行综合分析,提出了旅游地形象优化常用的注意力策略,并以丽江古城为例,针对其存在的具体问题进一步明确了形象优化路径。结果表明:注意力经济适用于旅游地形象优化,但应特别关注旅游地核心吸引物的变化对注意力流动的影响,注意力经济作为一种新视角在旅游地形象优化中发挥着助推器的作用;根据游客心理特点、客体刺激物属性,利用人−人感知、人−地感知规律以及注意力综合技术,能够优化游客对旅游地的心理感知,助推旅游地形象优化。本文结合旅游学、心理学等多学科知识,为旅游地形象优化研究提供了新视角,对于推动旅游地形象优化具有重要价值。

     

    Abstract: Tourism has entered an era of attention economy, scientific management of the scarce attention resources of the public plays an important role in promoting the optimization of tourist destination image and enhancing the competitive advantage of tourism industry. From the perspective of attention economy, this paper makes a comprehensive analysis of the connotation of attention economy and optimization factors of tourist destination image, and puts forward some attention strategies to optimize tourist destination image. Taking Lijiang ancient city as an example, it further clarifies the image optimization strategy to solve specific problems. The results show that attention economy is suitable for the optimization of tourist destination image, but special attention should be paid to the influence of the change of tourist destination core attraction on the flow of attention, because attention economy, as a new perspective, plays a role as a booster in the image optimization of tourist destinations. According to the psychological characteristics of tourists and object stimulus property, human-human perception, human-earth perception law and attention synthesis technology should be used to optimize tourists' psychological perception of tourist destination and boost the optimization of tourist destination image. This study provides a new perspective by combining the knowledge of tourism, psychology and other disciplines and thus has an important value in tourism destination image optimization.

     

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