Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry

Detalhes bibliográficos
Autor(a) principal: Lazzarini, Sergio Giovanetti
Data de Publicação: 2007
Outros Autores: Moura, Marcelo L., Caetano, Marco Antônio Leonel, Artes, Rinaldo, Goldberg, Marcelo B., Silva, César E.
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do INSPER
Texto Completo: https://repositorio.insper.edu.br/handle/11224/5102
Resumo: Analyzing and anticipating competitor moves has been central to modern competitive strategy. In contexts involving intense interfirm interaction, the value of a particular strategy depends in large part on how competitors will react to it. Despite many developments, anecdotal evidence indicates that the effective use of techniques to gauge decisions based on competitive considerations has been scant in practice. Our paper intends to fill this void. Using data from the auto insurance industry in Brazil, we compare strategies that do and do not anticipate competitor reactions. Basically we show that it does pay to anticipate those reactions. An optimal strategy will explore both demand elasticities and competitors’ patterns of reaction. We show that such “strategic” policy is expected to outperform a “myopic” approach which ignores competitor reactions. We also develop an methodology to compute demand elasticities, reaction functions and numerically compute optimal reaction strategies.
id INSP_ebc20df325df04f698df023d8218c82f
oai_identifier_str oai:repositorio.insper.edu.br:11224/5102
network_acronym_str INSP
network_name_str Biblioteca Digital de Teses e Dissertações do INSPER
repository_id_str
spelling Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance IndustryAnalyzing and anticipating competitor moves has been central to modern competitive strategy. In contexts involving intense interfirm interaction, the value of a particular strategy depends in large part on how competitors will react to it. Despite many developments, anecdotal evidence indicates that the effective use of techniques to gauge decisions based on competitive considerations has been scant in practice. Our paper intends to fill this void. Using data from the auto insurance industry in Brazil, we compare strategies that do and do not anticipate competitor reactions. Basically we show that it does pay to anticipate those reactions. An optimal strategy will explore both demand elasticities and competitors’ patterns of reaction. We show that such “strategic” policy is expected to outperform a “myopic” approach which ignores competitor reactions. We also develop an methodology to compute demand elasticities, reaction functions and numerically compute optimal reaction strategies.Texto completoANPAD2022-12-20T14:50:28Z2022-12-20T14:50:28Z2007conference paperinfo:eu-repo/semantics/publishedVersionp. 1-15Digitalapplication/pdf2177-25762177-2568https://repositorio.insper.edu.br/handle/11224/5102EnANPAD - Encontro da ANPADBrasilRio de JaneiroO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORinfo:eu-repo/semantics/openAccessLazzarini, Sergio GiovanettiMoura, Marcelo L.Caetano, Marco Antônio LeonelArtes, RinaldoGoldberg, Marcelo B.Silva, César E.Lazzarini, Sergio GiovanettiMoura, Marcelo L.Caetano, Marco Antônio LeonelArtes, RinaldoGoldberg, Marcelo B.Silva, César E.porreponame:Biblioteca Digital de Teses e Dissertações do INSPERinstname:Instituição de Ensino Superior e de Pesquisa (INSPER)instacron:INSPER2024-04-01T12:28:58Zoai:repositorio.insper.edu.br:11224/5102Biblioteca Digital de Teses e Dissertaçõeshttps://www.insper.edu.br/biblioteca-telles/PRIhttps://repositorio.insper.edu.br/oai/requestbiblioteca@insper.edu.br ||opendoar:2024-04-01T12:28:58Biblioteca Digital de Teses e Dissertações do INSPER - Instituição de Ensino Superior e de Pesquisa (INSPER)false
dc.title.none.fl_str_mv Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
title Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
spellingShingle Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
Lazzarini, Sergio Giovanetti
title_short Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
title_full Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
title_fullStr Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
title_full_unstemmed Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
title_sort Strategic Pricing Incorporating an Anticipation of Competitors' Reactions: a Study in the Auto Insurance Industry
author Lazzarini, Sergio Giovanetti
author_facet Lazzarini, Sergio Giovanetti
Moura, Marcelo L.
Caetano, Marco Antônio Leonel
Artes, Rinaldo
Goldberg, Marcelo B.
Silva, César E.
author_role author
author2 Moura, Marcelo L.
Caetano, Marco Antônio Leonel
Artes, Rinaldo
Goldberg, Marcelo B.
Silva, César E.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Lazzarini, Sergio Giovanetti
Moura, Marcelo L.
Caetano, Marco Antônio Leonel
Artes, Rinaldo
Goldberg, Marcelo B.
Silva, César E.
Lazzarini, Sergio Giovanetti
Moura, Marcelo L.
Caetano, Marco Antônio Leonel
Artes, Rinaldo
Goldberg, Marcelo B.
Silva, César E.
description Analyzing and anticipating competitor moves has been central to modern competitive strategy. In contexts involving intense interfirm interaction, the value of a particular strategy depends in large part on how competitors will react to it. Despite many developments, anecdotal evidence indicates that the effective use of techniques to gauge decisions based on competitive considerations has been scant in practice. Our paper intends to fill this void. Using data from the auto insurance industry in Brazil, we compare strategies that do and do not anticipate competitor reactions. Basically we show that it does pay to anticipate those reactions. An optimal strategy will explore both demand elasticities and competitors’ patterns of reaction. We show that such “strategic” policy is expected to outperform a “myopic” approach which ignores competitor reactions. We also develop an methodology to compute demand elasticities, reaction functions and numerically compute optimal reaction strategies.
publishDate 2007
dc.date.none.fl_str_mv 2007
2022-12-20T14:50:28Z
2022-12-20T14:50:28Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv 2177-2576
2177-2568
https://repositorio.insper.edu.br/handle/11224/5102
identifier_str_mv 2177-2576
2177-2568
url https://repositorio.insper.edu.br/handle/11224/5102
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv EnANPAD - Encontro da ANPAD
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 1-15
Digital
application/pdf
dc.coverage.none.fl_str_mv Brasil
Rio de Janeiro
dc.publisher.none.fl_str_mv ANPAD
publisher.none.fl_str_mv ANPAD
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações do INSPER
instname:Instituição de Ensino Superior e de Pesquisa (INSPER)
instacron:INSPER
instname_str Instituição de Ensino Superior e de Pesquisa (INSPER)
instacron_str INSPER
institution INSPER
reponame_str Biblioteca Digital de Teses e Dissertações do INSPER
collection Biblioteca Digital de Teses e Dissertações do INSPER
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações do INSPER - Instituição de Ensino Superior e de Pesquisa (INSPER)
repository.mail.fl_str_mv biblioteca@insper.edu.br ||
_version_ 1814986249755164672