The effect of company responses to social media negative word of mouth: A text mining approach
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/19428 |
Resumo: | Word-of-mouth (WOM) is emerging in importance for brand reputation and understanding of consumer behavior. Motivations to engage in WOM has been largely studied in marketing literature. How companies respond to WOM online was accounted in marketing literature to deliver distinguishing managerial response strategies to brands. This research project focuses on identifying which response strategy is the most crucial to make customers satisfied after a negative WOM. Text mining and sentiment analysis were used in order to draw conclusions from actual online consumer behavior. Negative WOM (NWOM) was extracted from different brand pages on Facebook, as well as the responses from the companies to these NWOM and the reaction from the NWOM’s writer to the brand’s response. A literature-based framework using Davidow's Facilitation, Apology and Attentiveness, and Benoit's Corrective Action was tested on the data. Further moderation analysis was conducted to test effects of NWOM’s polarity and industry on the relationship between the responses and satisfaction. Results reveal that Facilitation is important to response satisfaction. Whenever brands re-directed original NWOM writers to formal complaint means, their satisfaction increased. This was especially true for hospitality and e-commerce industries. Reversely, for hospitality and e-commerce industries, Apology had a negative impact on response satisfaction. Results yielded that Attentiveness decreased response satisfaction when polarity was a moderator. Managers should provide effective means for consumers to voice their disappointment and not rely on apologies alone. Future research should tackle more in depth the intricacies of languages and the distinction of complainers and brand haters on response strategies. |
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The effect of company responses to social media negative word of mouth: A text mining approachNWOMResponse satisfactionOnlineSatisfação de respostaComportamento do consumidor -- Consumer behaviorMarketingMarcaSatisfação do clienteRede socialWord-of-mouth (WOM) is emerging in importance for brand reputation and understanding of consumer behavior. Motivations to engage in WOM has been largely studied in marketing literature. How companies respond to WOM online was accounted in marketing literature to deliver distinguishing managerial response strategies to brands. This research project focuses on identifying which response strategy is the most crucial to make customers satisfied after a negative WOM. Text mining and sentiment analysis were used in order to draw conclusions from actual online consumer behavior. Negative WOM (NWOM) was extracted from different brand pages on Facebook, as well as the responses from the companies to these NWOM and the reaction from the NWOM’s writer to the brand’s response. A literature-based framework using Davidow's Facilitation, Apology and Attentiveness, and Benoit's Corrective Action was tested on the data. Further moderation analysis was conducted to test effects of NWOM’s polarity and industry on the relationship between the responses and satisfaction. Results reveal that Facilitation is important to response satisfaction. Whenever brands re-directed original NWOM writers to formal complaint means, their satisfaction increased. This was especially true for hospitality and e-commerce industries. Reversely, for hospitality and e-commerce industries, Apology had a negative impact on response satisfaction. Results yielded that Attentiveness decreased response satisfaction when polarity was a moderator. Managers should provide effective means for consumers to voice their disappointment and not rely on apologies alone. Future research should tackle more in depth the intricacies of languages and the distinction of complainers and brand haters on response strategies.O word-of-mouth (WOM) está a crescer em importância no ramo da reputação da marca e a compreensão do comportamento do consumidor. As motivações para engajar em WOM tem sido amplamente estudado na literatura de marketing. A forma como as empresas respondem ao WOM online foi contabilizado na literatura para fornecer às marcas estratégias de resposta diferenciadas. Este projeto concentra-se em identificar qual a estratégia mais crucial para satisfazer os clientes. O método escolhido foi o text mining e sentiment analysis devido à necessidade na literatura de obter respostas sobre comportamentos reais de consumidores. Extraímos WOM negativo (NWOM) de diferentes páginas de marcas no Facebook, as suas respostas e a reação dos escritores do NWOM a essas respostas. Um modelo da literatura utilizando Facilitation, Apology, Attentiveness de Davidow e Corrective Action de Benoit, foi construído. Análises de moderação foram realizadas para testar os efeitos da polaridade e da indústria da NWOM na relação entre os tipos de respostas e a satisfação. Os resultados revelam que Facilitation é importante para a satisfação. Quando as marcas redirecionavam os escritores da NWOM para meios formais de reclamação, a sua satisfação aumentava. Revela-se verdade para as indústrias de hospitalidade e e-commerce. Adicionalmente, Apology teve impacto negativo na satisfação. Attentiveness diminui a satisfação quando a polaridade é moderador. Os gestores devem construir melhores meios de reclamações e não contar somente nas suas desculpas. Futuros investigadores devem abordar a complexidade das línguas e a distinção entre escritores de reclamações e aversão à marca nas estratégias de resposta.2021-11-26T00:00:00Z2019-11-27T00:00:00Z2019-11-272019-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/19428TID:202338916engCorreia, Liliane Patrícia Lopesinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:59:26Zoai:repositorio.iscte-iul.pt:10071/19428Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:31:12.801237Repositório 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 effect of company responses to social media negative word of mouth: A text mining approach |
title |
The effect of company responses to social media negative word of mouth: A text mining approach |
spellingShingle |
The effect of company responses to social media negative word of mouth: A text mining approach Correia, Liliane Patrícia Lopes NWOM Response satisfaction Online Satisfação de resposta Comportamento do consumidor -- Consumer behavior Marketing Marca Satisfação do cliente Rede social |
title_short |
The effect of company responses to social media negative word of mouth: A text mining approach |
title_full |
The effect of company responses to social media negative word of mouth: A text mining approach |
title_fullStr |
The effect of company responses to social media negative word of mouth: A text mining approach |
title_full_unstemmed |
The effect of company responses to social media negative word of mouth: A text mining approach |
title_sort |
The effect of company responses to social media negative word of mouth: A text mining approach |
author |
Correia, Liliane Patrícia Lopes |
author_facet |
Correia, Liliane Patrícia Lopes |
author_role |
author |
dc.contributor.author.fl_str_mv |
Correia, Liliane Patrícia Lopes |
dc.subject.por.fl_str_mv |
NWOM Response satisfaction Online Satisfação de resposta Comportamento do consumidor -- Consumer behavior Marketing Marca Satisfação do cliente Rede social |
topic |
NWOM Response satisfaction Online Satisfação de resposta Comportamento do consumidor -- Consumer behavior Marketing Marca Satisfação do cliente Rede social |
description |
Word-of-mouth (WOM) is emerging in importance for brand reputation and understanding of consumer behavior. Motivations to engage in WOM has been largely studied in marketing literature. How companies respond to WOM online was accounted in marketing literature to deliver distinguishing managerial response strategies to brands. This research project focuses on identifying which response strategy is the most crucial to make customers satisfied after a negative WOM. Text mining and sentiment analysis were used in order to draw conclusions from actual online consumer behavior. Negative WOM (NWOM) was extracted from different brand pages on Facebook, as well as the responses from the companies to these NWOM and the reaction from the NWOM’s writer to the brand’s response. A literature-based framework using Davidow's Facilitation, Apology and Attentiveness, and Benoit's Corrective Action was tested on the data. Further moderation analysis was conducted to test effects of NWOM’s polarity and industry on the relationship between the responses and satisfaction. Results reveal that Facilitation is important to response satisfaction. Whenever brands re-directed original NWOM writers to formal complaint means, their satisfaction increased. This was especially true for hospitality and e-commerce industries. Reversely, for hospitality and e-commerce industries, Apology had a negative impact on response satisfaction. Results yielded that Attentiveness decreased response satisfaction when polarity was a moderator. Managers should provide effective means for consumers to voice their disappointment and not rely on apologies alone. Future research should tackle more in depth the intricacies of languages and the distinction of complainers and brand haters on response strategies. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-27T00:00:00Z 2019-11-27 2019-10 2021-11-26T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/19428 TID:202338916 |
url |
http://hdl.handle.net/10071/19428 |
identifier_str_mv |
TID:202338916 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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