國立虎尾科技大學 |

Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market./
Author:	Zhang, Chengjun.
Description:	1 online resource (111 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
Subject:	Home economics. -
Online resource:	click for full text (PQDT)
ISBN:	9798382741529

Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market.
Zhang, Chengjun.

Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market. - 1 online resource (111 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (Ph.D.)--Georgetown University, 2024.

Includes bibliographical references

This thesis delves into consumer heterogeneity in an online marketplace from an empirical lens on business practices. Furthermore, it evaluates the welfare consequences of employing personalized discounts as a strategic marketing approach. The first chapter utilizes comprehensive consumer clickstream data to construct and refine demand models for smartphones on an e-commerce platform. The narrative unfolds through the exploration of increasing levels of consumer heterogeneity, built upon the conditional logit framework. The last model directly leverages consumer historical clickstreams with a recurrent neural network (RNN), offering detailed individual-level preferences and realistic product substitution patterns. This model excels by outperforming other models in both in-sample and out-of-sample fit.The second chapter, building upon the demand model established in the first, conducts a counterfactual analysis that enables the issuance of personalized discounts tailored to individual consumer preference parameters. Using a numerically stable algorithm, this chapter presents empirical evidence that highlights the welfare implications. The findings illuminate a mutually beneficial scenario for firm profitability and consumer welfare, in conditional expected terms.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382741529Subjects--Topical Terms:

568501
Home economics.
Subjects--Index Terms:

Consumer clickstreamIndex Terms--Genre/Form:

554714
Electronic books.

Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market.
LDR:02767ntm a22004337 4500 001 1148037
005 20240916070009.5
006 m o d
007 cr bn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798382741529
035 $a (MiAaPQ)AAI31149217
035 $a AAI31149217
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Zhang, Chengjun. $3 1473914
245 1 0 $a Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market.
264 0 $c 2024
300 $a 1 online resource (111 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
500 $a Advisor: Rust, John.
502 $a Thesis (Ph.D.)--Georgetown University, 2024.
504 $a Includes bibliographical references
520 $a This thesis delves into consumer heterogeneity in an online marketplace from an empirical lens on business practices. Furthermore, it evaluates the welfare consequences of employing personalized discounts as a strategic marketing approach. The first chapter utilizes comprehensive consumer clickstream data to construct and refine demand models for smartphones on an e-commerce platform. The narrative unfolds through the exploration of increasing levels of consumer heterogeneity, built upon the conditional logit framework. The last model directly leverages consumer historical clickstreams with a recurrent neural network (RNN), offering detailed individual-level preferences and realistic product substitution patterns. This model excels by outperforming other models in both in-sample and out-of-sample fit.The second chapter, building upon the demand model established in the first, conducts a counterfactual analysis that enables the issuance of personalized discounts tailored to individual consumer preference parameters. Using a numerically stable algorithm, this chapter presents empirical evidence that highlights the welfare implications. The findings illuminate a mutually beneficial scenario for firm profitability and consumer welfare, in conditional expected terms.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Home economics. $3 568501
650 4 $a Finance. $3 559073
653 $a Consumer clickstream
653 $a Consumer heterogeneity
653 $a E-commerce
653 $a Machine learning
653 $a Multi-layer perceptron
653 $a Recurrent neural network
653 $a Personalized discount
655 7 $a Electronic books. $2 local $3 554714
690 $a 0501
690 $a 0338
690 $a 0508
690 $a 0386
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Georgetown University. $b Economics. $3 1179096
773 0 $t Dissertations Abstracts International $g 85-11B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31149217 $z click for full text (PQDT)