Online attention dynamics: The triangle framework of theory, big data and simulations

Lü, Peng; Chen, Dianhan; Zhang, Gang; Ding, Jian

doi:10.1016/j.eswa.2023.120900

Cited by 4 publications

(1 citation statement)

References 49 publications

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“…The research reveals that the public’s attention intensity toward high-quality scenic spots in Yunnan Province is the highest on travel websites, followed by search engines, short videos, and social media. This pattern is attributed to the limited nature of people’s attention ( March, 1994 ), particularly in the age of mass media, where individuals must distribute their attention across various online platforms ( Lu et al, 2023 ), leading to areas of high concentration and attention deficits. Furthermore, scholars have noted that information search significantly influences potential tourists’ purchasing decisions ( Lee et al, 2007 ), which are influenced by factors like travel notes or reviews on prominent travel websites and apps ( Wang et al, 2023 ), as well as the marketing strategies of tourist destinations both online and offline.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

The influencing mechanism of scenic spot online attention and tourists’ purchase behavior: an AISAS model based investigation

Zhao,

Kong,

Yang

et al. 2024

Front. Psychol.

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IntroductionIn the era of the Internet, online digital traces have become a new way to study the online attention of scenic spots and tourists’ purchase behavior. The public’s information search on major search platforms is a series of manifestations of potential tourists’ attention and interest in scenic spots, but there are few studies on how attention, interest and information search affect potential tourists to generate real purchase behavior.MethodThis paper selects four dimensions of short video platform, travel website, search engine and social media to comprehensively measure the online attention of high-quality scenic spots in Yunnan Province, and then establishes a gray association analytic hierarchy process based on the relevant variables of the AISAS model to empirically analyze the primary and secondary factors affecting tourists’ purchase behavior.Results(1) From the perspective of the online attention of scenic spots on different platforms, the intensity of the public’s scenic spots online attention on the four types of media platforms is in the order of travel websites, search engines, short videos and social media (2) From the perspective of spatial distribution characteristics, the online attention of high-quality scenic spots in Yunnan Province is unevenly distributed, that is, there is a big difference between the attention of higher star scenic spots and their star rating and popularity, while the attention of low-star scenic spots is not much different from their star rating and popularity (3) From the perspective of spatial agglomeration characteristics, the comprehensive online attention of high-quality scenic spots in Yunnan Province presents the spatial agglomeration characteristics of “the multi-core linkage of high-density in the east and north, and sub-high-density in the south” (4) The factors influencing the purchase behavior of potential tourists are sharing experience, attracting attention, generating interest and searching information.DiscussionBy exploring the formation mechanism of high-quality scenic spots online attention in Yunnan Province and the mechanism of its spatial differentiation, this study not only enriches the logical chain of “tourism information source → potential tourists → demand driven → tourism information search → travel preference → destination selection → purchase decision → travel experience → real tourists → feelings after traveling → focus on feedback → tourism information source,” but also broadens the application scenarios and application boundaries of travel preference theory and AISAS behavior model to a certain extent.

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