語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
FindBook
Google Book
Amazon
博客來
Price Discrimination in Large Social Networks.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Price Discrimination in Large Social Networks./
作者:
Huang, Jiali.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
104 p.
附註:
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Contained By:
Dissertations Abstracts International83-02B.
標題:
Operations research. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28496403
ISBN:
9798534692396
Price Discrimination in Large Social Networks.
Huang, Jiali.
Price Discrimination in Large Social Networks.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 104 p.
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Thesis (Ph.D.)--University of Minnesota, 2021.
This item must not be sold to any third party vendors.
Recent trends point to increasing use of social network information by firms and public agencies for personalized policies. However, the cost of implementation can be high and the use of personal information can reduce satisfaction. The value of such policies depends upon network structures, and may be insignificant for certain classes of large networks. Thus, firms and public agencies may need to be more careful about the design of mechanisms within social networks.In this thesis, we focus on a particular application of mechanism design problems with social network effects, i.e., the pricing problem of a single firm selling a product to consumers in social networks, and study the value of price discrimination in large social networks. Recent trends in industry suggest that increasingly firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research has focused on the computation of optimal prices in deterministic networks under positive externalities. We would like to answer the question: how valuable is such discriminative pricing? We find, surprisingly, that the value of such pricing policies (increase in profits due to price discrimination) in very large random networks are often not significant. Particularly, for Erdos-Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a non-negligible value of price discrimination for a small class of moderate-sized Erdos-Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities.
ISBN: 9798534692396Subjects--Topical Terms:
547123
Operations research.
Subjects--Index Terms:
Centrality
Price Discrimination in Large Social Networks.
LDR
:03572nmm a2200421 4500
001
2345809
005
20220613063918.5
008
241004s2021 ||||||||||||||||| ||eng d
020
$a
9798534692396
035
$a
(MiAaPQ)AAI28496403
035
$a
AAI28496403
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Huang, Jiali.
$3
3684817
245
1 0
$a
Price Discrimination in Large Social Networks.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2021
300
$a
104 p.
500
$a
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
500
$a
Advisor: Mani, Ankur.
502
$a
Thesis (Ph.D.)--University of Minnesota, 2021.
506
$a
This item must not be sold to any third party vendors.
520
$a
Recent trends point to increasing use of social network information by firms and public agencies for personalized policies. However, the cost of implementation can be high and the use of personal information can reduce satisfaction. The value of such policies depends upon network structures, and may be insignificant for certain classes of large networks. Thus, firms and public agencies may need to be more careful about the design of mechanisms within social networks.In this thesis, we focus on a particular application of mechanism design problems with social network effects, i.e., the pricing problem of a single firm selling a product to consumers in social networks, and study the value of price discrimination in large social networks. Recent trends in industry suggest that increasingly firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research has focused on the computation of optimal prices in deterministic networks under positive externalities. We would like to answer the question: how valuable is such discriminative pricing? We find, surprisingly, that the value of such pricing policies (increase in profits due to price discrimination) in very large random networks are often not significant. Particularly, for Erdos-Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a non-negligible value of price discrimination for a small class of moderate-sized Erdos-Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities.
590
$a
School code: 0130.
650
4
$a
Operations research.
$3
547123
650
4
$a
Industrial engineering.
$3
526216
650
4
$a
Mathematics.
$3
515831
650
4
$a
Prices.
$3
652651
650
4
$a
Performance evaluation.
$3
3562292
650
4
$a
Influence.
$3
1973172
650
4
$a
Social interaction.
$3
520415
650
4
$a
Experiments.
$3
525909
650
4
$a
Peers.
$3
3435329
650
4
$a
Literature reviews.
$3
3559998
653
$a
Centrality
653
$a
Price discrimination
653
$a
Random networks
653
$a
Revenue management
653
$a
Social network analysis
653
$a
Value of price discrimination
690
$a
0796
690
$a
0546
690
$a
0405
690
$a
0501
690
$a
0454
690
$a
0338
710
2
$a
University of Minnesota.
$b
Industrial and Systems Engineering.
$3
3170834
773
0
$t
Dissertations Abstracts International
$g
83-02B.
790
$a
0130
791
$a
Ph.D.
792
$a
2021
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28496403
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9468247
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入