在 Instagram 上投射的北京目的地形象:序列研究设计

IF 8 2区 管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM
Lingxue Zhan, Mingming Cheng, Jingjie Zhu, Xiaowei Wang
{"title":"在 Instagram 上投射的北京目的地形象:序列研究设计","authors":"Lingxue Zhan, Mingming Cheng, Jingjie Zhu, Xiaowei Wang","doi":"10.1177/00472875231210817","DOIUrl":null,"url":null,"abstract":"Using a sequential research design combining image analytics and Qualitative Comparative Analysis (QCA), this research examines Beijing’s projected destination image and its impacts on social media engagement on Instagram. Deep learning algorithms and convolutional neural networks were used to analyze the images. The image analytic findings show that Beijing’s projected destination image includes: (1) multiple urban and country landscapes; (2) a mixture of modernity and tradition; (3) a range of activities in a dynamic city and (4) cuisine—a variety of traditional Chinese food. QCA identified three paths that lead to high engagement, including “building” and “sky,” “building” and “event,” “sky,” and “event.” This research advances the destination image literature by empirically establishing the relationship between destination image labels and social media engagement. Further, it offers a new configurational perspective for constructing projected destination image by delineating how DMOs effectively increase social media engagement through image semantic content configurations.","PeriodicalId":48435,"journal":{"name":"Journal of Travel Research","volume":null,"pages":null},"PeriodicalIF":8.0000,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Projected Destination Image of Beijing on Instagram: A Sequential Research Design\",\"authors\":\"Lingxue Zhan, Mingming Cheng, Jingjie Zhu, Xiaowei Wang\",\"doi\":\"10.1177/00472875231210817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Using a sequential research design combining image analytics and Qualitative Comparative Analysis (QCA), this research examines Beijing’s projected destination image and its impacts on social media engagement on Instagram. Deep learning algorithms and convolutional neural networks were used to analyze the images. The image analytic findings show that Beijing’s projected destination image includes: (1) multiple urban and country landscapes; (2) a mixture of modernity and tradition; (3) a range of activities in a dynamic city and (4) cuisine—a variety of traditional Chinese food. QCA identified three paths that lead to high engagement, including “building” and “sky,” “building” and “event,” “sky,” and “event.” This research advances the destination image literature by empirically establishing the relationship between destination image labels and social media engagement. Further, it offers a new configurational perspective for constructing projected destination image by delineating how DMOs effectively increase social media engagement through image semantic content configurations.\",\"PeriodicalId\":48435,\"journal\":{\"name\":\"Journal of Travel Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2023-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Travel Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1177/00472875231210817\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Travel Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/00472875231210817","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
引用次数: 0

摘要

本研究采用图像分析和定性比较分析(QCA)相结合的连续研究设计,考察了北京的预测目的地形象及其对 Instagram 社交媒体参与度的影响。深度学习算法和卷积神经网络被用于分析图像。图像分析结果表明,北京的预测目的地形象包括(1) 多重城市和乡村景观;(2) 现代与传统的结合;(3) 动态城市中的一系列活动;(4) 美食--各种中国传统美食。QCA 确定了导致高参与度的三条路径,包括 "建筑 "和 "天空"、"建筑 "和 "活动"、"天空 "和 "活动"。这项研究通过实证方法确定了目的地形象标签与社交媒体参与度之间的关系,从而推动了目的地形象文献的发展。此外,它还通过描述目的地管理组织如何通过图像语义内容配置有效提高社交媒体参与度,为构建预测的目的地形象提供了一个新的配置视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Projected Destination Image of Beijing on Instagram: A Sequential Research Design
Using a sequential research design combining image analytics and Qualitative Comparative Analysis (QCA), this research examines Beijing’s projected destination image and its impacts on social media engagement on Instagram. Deep learning algorithms and convolutional neural networks were used to analyze the images. The image analytic findings show that Beijing’s projected destination image includes: (1) multiple urban and country landscapes; (2) a mixture of modernity and tradition; (3) a range of activities in a dynamic city and (4) cuisine—a variety of traditional Chinese food. QCA identified three paths that lead to high engagement, including “building” and “sky,” “building” and “event,” “sky,” and “event.” This research advances the destination image literature by empirically establishing the relationship between destination image labels and social media engagement. Further, it offers a new configurational perspective for constructing projected destination image by delineating how DMOs effectively increase social media engagement through image semantic content configurations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Travel Research
Journal of Travel Research HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
18.90
自引率
9.00%
发文量
66
期刊介绍: The Journal of Travel Research (JTR) stands as the preeminent, peer-reviewed research journal dedicated to exploring the intricacies of the travel and tourism industry, encompassing development, management, marketing, economics, and behavior. Offering a wealth of up-to-date, meticulously curated research, JTR serves as an invaluable resource for researchers, educators, and industry professionals alike, shedding light on behavioral trends and management theories within one of the most influential and dynamic sectors. Established in 1961, JTR holds the distinction of being the longest-standing among the world’s top-ranked scholarly journals singularly focused on travel and tourism, underscoring the global significance of this multifaceted industry, both economically and socially.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信