Identifying consumer consideration set at the purchase time from aggregate purchase data in online retailing

Bin Gu, Prabhudev Konana, Hsuan Wei Michelle Chen

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Online retailers provide a substantial amount of product information to their customers. The information includes not only product features and customer reviews, but also information on alternative products that may better fit a consumer's needs. The systematic provision of information on alternative products could have a significant impact on consumers' purchase decision process at online retailers. In this study, we analyze one aspect of the impact - the degree to which consumers consider multiple products at the purchase time. We leverage a popular feature provided by online retailers - What Do Customers Ultimately Buy after Viewing This Item? We show that information contained in this feature can be used to identify consumers' product consideration set and choice at the purchase time when combined with product sales data. The identification is exact in analyzing competition between two products. For competition involving three products, the identification is exact under the assumption that consumer choice follows a discrete choice model. For competition involving more than three products, the information provides a lower bound of the percentage of consumers that consider only one product at the purchase time. We apply the model to 38,400 unique products from Amazon's Electronics category. The results show that more than 78% of consumers purchase a product without considering any other products on Amazon at the purchase time.

Original languageEnglish (US)
Pages (from-to)625-633
Number of pages9
JournalDecision Support Systems
Volume53
Issue number3
DOIs
StatePublished - Jun 2012

Fingerprint

Consumer products
Sales
Electronic equipment
Online retailing
Purchase
Consideration sets
Retailing
Retailers
Amazon

Keywords

  • Consideration set
  • Consumer choice
  • Electronic commerce
  • Information search

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Arts and Humanities (miscellaneous)
  • Developmental and Educational Psychology

Cite this

Identifying consumer consideration set at the purchase time from aggregate purchase data in online retailing. / Gu, Bin; Konana, Prabhudev; Chen, Hsuan Wei Michelle.

In: Decision Support Systems, Vol. 53, No. 3, 06.2012, p. 625-633.

Research output: Contribution to journalArticle

Gu, Bin ; Konana, Prabhudev ; Chen, Hsuan Wei Michelle. / Identifying consumer consideration set at the purchase time from aggregate purchase data in online retailing. In: Decision Support Systems. 2012 ; Vol. 53, No. 3. pp. 625-633.
@article{7d01287896c24f489eb0578ad2043778,
title = "Identifying consumer consideration set at the purchase time from aggregate purchase data in online retailing",
abstract = "Online retailers provide a substantial amount of product information to their customers. The information includes not only product features and customer reviews, but also information on alternative products that may better fit a consumer's needs. The systematic provision of information on alternative products could have a significant impact on consumers' purchase decision process at online retailers. In this study, we analyze one aspect of the impact - the degree to which consumers consider multiple products at the purchase time. We leverage a popular feature provided by online retailers - What Do Customers Ultimately Buy after Viewing This Item? We show that information contained in this feature can be used to identify consumers' product consideration set and choice at the purchase time when combined with product sales data. The identification is exact in analyzing competition between two products. For competition involving three products, the identification is exact under the assumption that consumer choice follows a discrete choice model. For competition involving more than three products, the information provides a lower bound of the percentage of consumers that consider only one product at the purchase time. We apply the model to 38,400 unique products from Amazon's Electronics category. The results show that more than 78{\%} of consumers purchase a product without considering any other products on Amazon at the purchase time.",
keywords = "Consideration set, Consumer choice, Electronic commerce, Information search",
author = "Bin Gu and Prabhudev Konana and Chen, {Hsuan Wei Michelle}",
year = "2012",
month = "6",
doi = "10.1016/j.dss.2012.02.015",
language = "English (US)",
volume = "53",
pages = "625--633",
journal = "Decision Support Systems",
issn = "0167-9236",
publisher = "Elsevier",
number = "3",

}

TY - JOUR

T1 - Identifying consumer consideration set at the purchase time from aggregate purchase data in online retailing

AU - Gu, Bin

AU - Konana, Prabhudev

AU - Chen, Hsuan Wei Michelle

PY - 2012/6

Y1 - 2012/6

N2 - Online retailers provide a substantial amount of product information to their customers. The information includes not only product features and customer reviews, but also information on alternative products that may better fit a consumer's needs. The systematic provision of information on alternative products could have a significant impact on consumers' purchase decision process at online retailers. In this study, we analyze one aspect of the impact - the degree to which consumers consider multiple products at the purchase time. We leverage a popular feature provided by online retailers - What Do Customers Ultimately Buy after Viewing This Item? We show that information contained in this feature can be used to identify consumers' product consideration set and choice at the purchase time when combined with product sales data. The identification is exact in analyzing competition between two products. For competition involving three products, the identification is exact under the assumption that consumer choice follows a discrete choice model. For competition involving more than three products, the information provides a lower bound of the percentage of consumers that consider only one product at the purchase time. We apply the model to 38,400 unique products from Amazon's Electronics category. The results show that more than 78% of consumers purchase a product without considering any other products on Amazon at the purchase time.

AB - Online retailers provide a substantial amount of product information to their customers. The information includes not only product features and customer reviews, but also information on alternative products that may better fit a consumer's needs. The systematic provision of information on alternative products could have a significant impact on consumers' purchase decision process at online retailers. In this study, we analyze one aspect of the impact - the degree to which consumers consider multiple products at the purchase time. We leverage a popular feature provided by online retailers - What Do Customers Ultimately Buy after Viewing This Item? We show that information contained in this feature can be used to identify consumers' product consideration set and choice at the purchase time when combined with product sales data. The identification is exact in analyzing competition between two products. For competition involving three products, the identification is exact under the assumption that consumer choice follows a discrete choice model. For competition involving more than three products, the information provides a lower bound of the percentage of consumers that consider only one product at the purchase time. We apply the model to 38,400 unique products from Amazon's Electronics category. The results show that more than 78% of consumers purchase a product without considering any other products on Amazon at the purchase time.

KW - Consideration set

KW - Consumer choice

KW - Electronic commerce

KW - Information search

UR - http://www.scopus.com/inward/record.url?scp=84862548911&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84862548911&partnerID=8YFLogxK

U2 - 10.1016/j.dss.2012.02.015

DO - 10.1016/j.dss.2012.02.015

M3 - Article

VL - 53

SP - 625

EP - 633

JO - Decision Support Systems

JF - Decision Support Systems

SN - 0167-9236

IS - 3

ER -