The impact of category prices on store price image formation: an empirical analysis
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/11714 |
Resumo: | The authors empirically explore how consumers update beliefs about a store’s overall expensiveness. They estimate a learning model of store price image (SPI) formation with the impact of actual prices linked to category characteristics on a unique data set combining consumers’ store visit and purchase information with their price perceptions. The results identify characteristics that drive categories’ store price signaling power for different store formats. “Big ticket” categories with a narrow price range strongly shape consumers’ store price beliefs, whereas (volatile) prices of frequently or deeply promoted categories are less influential. At traditional supermarkets, consumers anchor and elaborate on prices of storable categories bought in large quantities and for which quality differentiation is high. For hard discounters, however, SPI is mostly shaped by frequently bought categories with narrow assortments. Notably, categories’ SPI signaling power is not proportional to their share of wallet at either type of chain. Managers can use these results to identify “Lighthouse” categories that signal low prices, yet make up a small portion of store spending, and in which price cuts do not overly hurt revenue. |
id |
RCAP_fd4943c42a5b8c6671d70dc3aeea0990 |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/11714 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
The impact of category prices on store price image formation: an empirical analysisStore price imagePrice perceptionsProduct category characteristicsBayesian learningThe authors empirically explore how consumers update beliefs about a store’s overall expensiveness. They estimate a learning model of store price image (SPI) formation with the impact of actual prices linked to category characteristics on a unique data set combining consumers’ store visit and purchase information with their price perceptions. The results identify characteristics that drive categories’ store price signaling power for different store formats. “Big ticket” categories with a narrow price range strongly shape consumers’ store price beliefs, whereas (volatile) prices of frequently or deeply promoted categories are less influential. At traditional supermarkets, consumers anchor and elaborate on prices of storable categories bought in large quantities and for which quality differentiation is high. For hard discounters, however, SPI is mostly shaped by frequently bought categories with narrow assortments. Notably, categories’ SPI signaling power is not proportional to their share of wallet at either type of chain. Managers can use these results to identify “Lighthouse” categories that signal low prices, yet make up a small portion of store spending, and in which price cuts do not overly hurt revenue.American Marketing Association2016-07-12T13:48:08Z2015-01-01T00:00:00Z20152019-05-13T16:57:36Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/11714eng0022-243710.1509/jmr.11.0536Lourenço, C. J. S.Gijsbrechts, E.Paap, R.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:57:35Zoai:repositorio.iscte-iul.pt:10071/11714Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:29:44.384492Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
The impact of category prices on store price image formation: an empirical analysis |
title |
The impact of category prices on store price image formation: an empirical analysis |
spellingShingle |
The impact of category prices on store price image formation: an empirical analysis Lourenço, C. J. S. Store price image Price perceptions Product category characteristics Bayesian learning |
title_short |
The impact of category prices on store price image formation: an empirical analysis |
title_full |
The impact of category prices on store price image formation: an empirical analysis |
title_fullStr |
The impact of category prices on store price image formation: an empirical analysis |
title_full_unstemmed |
The impact of category prices on store price image formation: an empirical analysis |
title_sort |
The impact of category prices on store price image formation: an empirical analysis |
author |
Lourenço, C. J. S. |
author_facet |
Lourenço, C. J. S. Gijsbrechts, E. Paap, R. |
author_role |
author |
author2 |
Gijsbrechts, E. Paap, R. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Lourenço, C. J. S. Gijsbrechts, E. Paap, R. |
dc.subject.por.fl_str_mv |
Store price image Price perceptions Product category characteristics Bayesian learning |
topic |
Store price image Price perceptions Product category characteristics Bayesian learning |
description |
The authors empirically explore how consumers update beliefs about a store’s overall expensiveness. They estimate a learning model of store price image (SPI) formation with the impact of actual prices linked to category characteristics on a unique data set combining consumers’ store visit and purchase information with their price perceptions. The results identify characteristics that drive categories’ store price signaling power for different store formats. “Big ticket” categories with a narrow price range strongly shape consumers’ store price beliefs, whereas (volatile) prices of frequently or deeply promoted categories are less influential. At traditional supermarkets, consumers anchor and elaborate on prices of storable categories bought in large quantities and for which quality differentiation is high. For hard discounters, however, SPI is mostly shaped by frequently bought categories with narrow assortments. Notably, categories’ SPI signaling power is not proportional to their share of wallet at either type of chain. Managers can use these results to identify “Lighthouse” categories that signal low prices, yet make up a small portion of store spending, and in which price cuts do not overly hurt revenue. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01T00:00:00Z 2015 2016-07-12T13:48:08Z 2019-05-13T16:57:36Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/11714 |
url |
http://hdl.handle.net/10071/11714 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0022-2437 10.1509/jmr.11.0536 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
American Marketing Association |
publisher.none.fl_str_mv |
American Marketing Association |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134859466113024 |