國立虎尾科技大學 |

Economics of Recommender Systems in Online Marketplaces.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Economics of Recommender Systems in Online Marketplaces./
Author:	Li, Lusi.
Description:	1 online resource (136 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.
Contained By:	Dissertation Abstracts International79-03A(E).
Subject:	Management. -
Online resource:	click for full text (PQDT)
ISBN:	9780355392524

Economics of Recommender Systems in Online Marketplaces.
Li, Lusi.

Economics of Recommender Systems in Online Marketplaces. - 1 online resource (136 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.

Thesis (Ph.D.)

Includes bibliographical references

Electronic marketplaces such as Amazon Marketplace and Ebay deploy recommender systems as sales support tools to help consumers find their ideal product among the vast variety of products sold in these platforms. Recommender systems affect consumer decision making by informing consumers about products they may not be aware of and enlarging the consumers' consideration set ("informative role"). In this dissertation, we study the impacts of recommender systems on different players in an online channel structure where a dominant e-commerce platform sells competing products from different manufacturers, and simultaneously recommends a subset of these products to consumers. The dissertation consists of three essays.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355392524Subjects--Topical Terms:

558618
Management.
Index Terms--Genre/Form:

554714
Electronic books.

Economics of Recommender Systems in Online Marketplaces.
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100 1 $a Li, Lusi. $3 1182823
245 1 0 $a Economics of Recommender Systems in Online Marketplaces.
264 0 $c 2017
300 $a 1 online resource (136 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
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500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.
500 $a Advisers: Srinivasan Raghunathan; Jianqing Chen.
502 $a Thesis (Ph.D.) $c The University of Texas at Dallas $d 2017.
504 $a Includes bibliographical references
520 $a Electronic marketplaces such as Amazon Marketplace and Ebay deploy recommender systems as sales support tools to help consumers find their ideal product among the vast variety of products sold in these platforms. Recommender systems affect consumer decision making by informing consumers about products they may not be aware of and enlarging the consumers' consideration set ("informative role"). In this dissertation, we study the impacts of recommender systems on different players in an online channel structure where a dominant e-commerce platform sells competing products from different manufacturers, and simultaneously recommends a subset of these products to consumers. The dissertation consists of three essays.
520 $a The first essay highlights how recommender system design affects the upstream competition between manufacturers and the consequent implications for the recommendation strategy to be adopted by the retail platform. In our setting, consumers are differentiated with respect to their preference for the two products and awareness about the two products. A recommender system is designed to select the recommendation based on a weighted sum of expected retailer profit and expected consumer value. We find that the recommender system may benefit or hurt the retailer and manufacturers, depending on its design and market characteristics. We show that the retailer's optimal recommendation strategy is mildly profit oriented in the sense that it assigns a larger but not too-large a weight to retailer profit than consumer value, and that under the optimal strategy, the price competition is less intense and the retailer profit is higher compared to when there is no recommender system.
520 $a The informative role of the recommender system deployed by an electronic marketplace functions as a medium for targeted advertising for sellers, analogous to traditional advertising media such as TV, newspaper, and the Internet. In the second essay, we examine how a recommender system affects competing sellers in electronic marketplaces regarding their advertising and pricing decisions. We find that sellers advertise less (advertising effect) on their own and decreases product prices (competition effect) in the presence of a recommender system. As a result of these two effects, sellers are more likely to benefit from the recommender system only when it has a high precision.
520 $a While the first two essays consider a recommender system that recommends competing products to help consumers find a better alternative, the third essay considers a mixed recommender system where both competing products and complementary products are included. In particular, we consider four sellers that sell four products in two categories via a common retail platform. Products in the same category are substitutes, and products in different categories are complements. We show that the recommender system does not necessarily benefit the marketplace; on one side, the recommender system increases the total sales, but on the other hand, the recommender system alters the competition in each category. In the presence of the recommender system, the price and profit of each seller critically depends on the degree of complementary among products.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Management. $3 558618
650 4 $a Web studies. $3 1148502
655 7 $a Electronic books. $2 local $3 554714
690 $a 0454
690 $a 0646
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Texas at Dallas. $b Management Science. $3 1181148
773 0 $t Dissertation Abstracts International $g 79-03A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10675230 $z click for full text (PQDT)