Optimal Revenue Model of a Social Networking Service: Ad-Sponsored, Subscription-Based, or Hybrid?

收入 服务(商务) 收益模型 程式化事实 业务 服务提供商 计算机科学 经济 营销 财务 宏观经济学
作者
Zhiyong Li,Donghan Wang,Guofang Nan,Minqiang Li
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:71: 1927-1939 被引量:6
标识
DOI:10.1109/tem.2022.3170051
摘要

We apply a stylized model to investigate the optimal revenue model for a monopolistic online platform that offers social networking services. There are three possible revenue models: an ad-sponsored model that offers a basic service, a SM that offers a premium service, and a hybrid model of both. We study a scenario in which the unit misfit cost of the premium service is lower than that of the basic service (the easy-to-use premium-service case), and a scenario in which the relationship is inverted (the hard-to-use premium-service case). We find that the ad-sponsored revenue model is always dominated by the hybrid model. When the ratio between the quality of the premium service and that of the basic service is too low (high), the hybrid (subscription-based) model is optimal, regardless of whether the unit misfit cost of a premium service is less or more than that of a basic service. Interestingly, we find that, in the easy-to-use premium-service case, as the unit misfit cost of the premium service increases, the hybrid model is more likely to become the optimal revenue model. However, in the hard-to-use premium-service case, when the unit misfit cost of the premium service is below (above) a threshold, as it increases, the subscription-based (hybrid) revenue model is more likely to become the optimal revenue model.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
刚刚
刚刚
刚刚
萌酱完成签到,获得积分10
刚刚
hzh完成签到,获得积分10
刚刚
BCLee发布了新的文献求助20
刚刚
科研通AI6应助syy080837采纳,获得10
1秒前
1秒前
ggg发布了新的文献求助10
1秒前
科研通AI6应助超帅的啤酒采纳,获得10
1秒前
2秒前
2秒前
Alice完成签到,获得积分20
2秒前
StandardR完成签到,获得积分10
2秒前
Jason完成签到,获得积分10
3秒前
奥利奥发布了新的文献求助10
3秒前
菜菜完成签到 ,获得积分10
3秒前
3秒前
招财进宝发布了新的文献求助30
4秒前
天天完成签到,获得积分10
4秒前
4秒前
花花花发布了新的文献求助10
4秒前
5秒前
高贵春天发布了新的文献求助10
5秒前
5秒前
kohu发布了新的文献求助30
5秒前
直率的莺发布了新的文献求助10
5秒前
CipherSage应助鲸鱼采纳,获得10
6秒前
李晨发布了新的文献求助10
6秒前
7秒前
8秒前
量子星尘发布了新的文献求助10
9秒前
9秒前
lbx发布了新的文献求助10
9秒前
科研通AI6应助001采纳,获得10
10秒前
10秒前
10秒前
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exploring Nostalgia 500
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
Advanced Memory Technology: Functional Materials and Devices 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5667995
求助须知:如何正确求助?哪些是违规求助? 4888874
关于积分的说明 15122780
捐赠科研通 4826840
什么是DOI,文献DOI怎么找? 2584376
邀请新用户注册赠送积分活动 1538211
关于科研通互助平台的介绍 1496526