全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

网红数据资产价值影响因素研究——以新浪微博账号为例
Research on Influencing Factors of Data Asset Value of Internet Celebrities—Taking Sina Weibo Account as an Example

DOI: 10.12677/SD.2023.132052, PP. 487-497

Keywords: 网红,数据资产,价值,影响因素,新浪微博
Internet Celebrity
, Data Asset, Value, Influencing Factor, Sina Weibo

Full-Text   Cite this paper   Add to My Lib

Abstract:

随着数据成为重要的生产要素,数据及数据资产价值的衡量引起了学术界和产业界的关注,本文基于特定情境,探究数据资产价值的影响因素。以新浪微博账号为例,将其看作网红用户,从专业度、活跃度、丰富度、传播度4个方面探究网红数据资产价值的影响因素,借助云自媒平台上微博账号定价数据、微博平台上的微博账号数据进行实证研究。结果发现传播广度、传播深度、账号信用、公司认证、发博活跃度、时间特征显著正向影响微博网红数据资产价值,创建时间、学历水平、丰富度、关注数显著负向影响微博网红数据资产价值,并据此为网红价值提升提出建议。本文从网红数据资产定价出发,为数据资产价值研究及其定价策略提供理论和方法支持。
As data becomes an important factor of production, the measurement of data and data asset value has attracted the attention of academia and industry. Based on a specific situation, this paper ex-plores the factors that affect the value of data asset. Taking the Sina Weibo account as an example, and considering it an Internet celebrity, its influencing factors are explored from degree of profes-sionalism, activity, richness and spread. Empirical research is carried out with the help of Weibo account pricing data on YunZiMei and Weibo account data on Sina Weibo. The results show that the spread breadth, spread depth, account credit, company certification, blog activity and time characteristics have a significant positive impact on the data asset value of Weibo network celeb-rities, while the creation time, education level, richness and number of focuses have a significant negative impact on the data asset value of Weibo network celebrities. Based on this, suggestions are put forward for the value improvement of Weibo network celebrities. Starting from the data asset pricing of Internet celebrities, this paper provides theoretical and methodological support for the study of data asset value and its pricing strategy.

References

[1]  中国信息通信研究院. 数据资产管理实践白皮书(4.0版) [R]. 北京: 中国信息通信研究院, 2019.
[2]  付熙雯, 郑磊. 开放政府数据的价值: 研究进展与展望[J]. 图书情报工作, 2020, 64(9): 122-132.
[3]  李永红, 张淑雯. 数据资产价值评估模型构建[J]. 财会月刊, 2018(9): 30-35.
[4]  Attard, J., Orlandi, F. and Auer, S. (2016) Value Cre-ation on Open Government Data. 2016 49th Hawaii International Conference on System Sciences, Koloa, 5-8 January 2016, 2605-2614.
https://doi.org/10.1109/HICSS.2016.326
[5]  李菲菲, 关杨, 等. 信息生态视角下供电企业数据资产管理模型及价值评估方法研究[J]. 情报科学, 2019, 37(10): 46-52.
[6]  王汉生. 数据资产论[M]. 北京: 中国人民大学出版社, 2019.
[7]  张兴旺, 廖帅, 张鲜艳. 图书馆大数据资产的内涵、特征及其合理利用研究[J]. 情报理论与实践, 2019, 42(11): 15-20.
[8]  沈宇庭. 打造超级网红: 个人网红和企业网红的进阶必修课[M]. 北京: 中国经济出版社, 2016: 9
[9]  Reinikainen, H., Munnukka, J., Maity, D. and Luoma-aho, V. (2020) ‘You Really Are a Great Big Sister’—Parasocial Relationships, Credibility, and the Moderating Role of Audience Comments in In-fluencer Marketing. Journal of Marketing Management, 36, 279-298.
https://doi.org/10.1080/0267257X.2019.1708781
[10]  De Veirman, M., Cauberghe, V. and Hudders, L. (2017) Marketing through Instagram Influencers: The Impact of Number of Followers and Product Divergence on Brand Atti-tude. International Journal of Advertising, 36, 798-828.
https://doi.org/10.1080/02650487.2017.1348035
[11]  Xiao, M., Wang, R. and Chan-Olmsted, S. (2018) Factors Affecting YouTube Influencer Marketing Credibility: A Heuristic-Systematic Model. Journal of Media Business Studies, 15, 188-213.
https://doi.org/10.1080/16522354.2018.1501146
[12]  Hu, L.X., Min, Q.F., Han, S.N. and Liu, Z.Y. (2020) Un-derstanding Followers’ Stickiness to Digital Influencers: The Effect of Psychological Responses. International Journal of Information Management, 54, 102-169.
https://doi.org/10.1016/j.ijinfomgt.2020.102169
[13]  Jin, S.V. and Muqaddam, A. (2019) Product Placement 2.0: “Do Brands Need Influencers, or Do Influencers Need Brands?” Journal of Brand Management, 26, 522-537.
https://doi.org/10.1057/s41262-019-00151-z
[14]  刘凤军, 孟陆, 陈斯允, 段坤. 网红直播对消费者购买意愿的影响及其机制研究[J]. 管理学报, 2020, 17(1): 94-104.
[15]  Torres, P., Augusto, M. and Matos, M. (2019) Ante-cedents and Outcomes of Digital Influencer Endorsement: An Exploratory Study. Psychology & Marketing, 36, 1267-1276.
https://doi.org/10.1002/mar.21274
[16]  尹珺. 基于用户价值的社交网站数据资产估值研究[D]: [硕士学位论文]. 武汉: 中南财经政法大学, 2019.
[17]  赵阿敏, 曹桂全. 政务微博影响力评价与比较实证研究——基于因子分析和聚类分析[J]. 情报杂志, 2014, 33(3): 107-112.
[18]  白建磊, 张梦霞. 国内外政务微博研究的回顾与展望[J]. 图书情报知识, 2017(3): 95-107.
[19]  杨长春, 王睿. 基于H指数的政务微博影响力研究[J]. 现代情报, 2018, 38(3): 110-115+123.
[20]  Zhe, L. and Jansen, B.J. (2018) Questioner or Question: Predicting the Response Rate in Social Question and Answering on Sina Weibo. Information Processing & Management, 54, 159-174.
https://doi.org/10.1016/j.ipm.2017.10.004
[21]  刘根勤. 从新浪微博热门转发看微博的价值要素[J]. 今传媒, 2012, 20(9): 150-152.
[22]  Hao, X., Zheng, D., Zeng, Q. and Fan, W. (2016) How to Strengthen the Social Media Interactivity of E-Government Evidence from China. Online Information Review, 40, 79-96.
https://doi.org/10.1108/OIR-03-2015-0084
[23]  孟陆, 刘凤军, 陈斯允, 段珅. 我可以唤起你吗——不同类型直播网红信息源特性对消费者购买意愿的影响机制研究[J]. 南开管理评论, 2020, 23(1): 131-143.
[24]  包明林, 刘蓉, 邹凯, 周军. 政务微博服务质量评价指标体系研究[J]. 现代情报, 2015, 35(9): 93-97+110.
[25]  敖鹏. 网红为什么这样红?——基于网红现象的解读和思考[J]. 当代传播, 2016(4): 40-44.
[26]  金晓玲, 金可儿, 汤振亚. 微博转发行为实证研究综述[J]. 情报杂志, 2015, 34(10): 117-122.
[27]  刘晓娟, 王昊贤, 肖雪, 董鑫鑫. 基于微博特征的政务微博影响因素研究[J]. 情报杂志, 2013, 32(12): 35-41.
[28]  曹政, 王宁, 杨学成. 基于层次分析法和模糊综合评判的政务微信影响力评估研究[J]. 电子政务, 2016(7): 42-49.
[29]  张小敏. “内容为王”还是“产品为王”——传统期刊在数字化背景下如何发挥优势[J]. 传媒, 2008(6): 56-57.
[30]  魏萌, 张博. 新浪微博“网红”的微博内容特征及传播效果研究[J]. 情报科学, 2018, 36(2): 88-94.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133