Main drivers for microtransactions as impulse purchases in e-commerce
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/15309 |
Resumo: | With mobile technology evolving at a very fast-paced level, consumers now have many choices of entertainment on their mobile devices. Thousands of games are available to download free of charge on virtually every smartphone and with them a new revenue model has emerged: microtransactions. Characterized by low price points, microtransaction have seldom been studied extensively. With great potential in the future, this type of revenue model is currently outgrowing traditional pay-to-play model types. By focusing on several types of mobile game item drivers and adapting some previous research and models, this study intends to identify and create a model with the main drivers of microtransactions that lead to impulse purchases in mobile game applications and understand if a price increase will lead to a lower purchase intention. A PLS-SEM analysis was conducted on a sample of 301 individuals. The measurement model showed a good fit of parameters, with AVE above 0.50 for all components, composite reliability superior to 0.70 for all components as well as an HTMT value inferior to 0.90 present in each component relationship. The six components considered explained 53.3% of the variance in impulse buying tendency. Significant component drivers from strongest to least robust were flow experience, social, hedonic/emotional and performance drivers. Functionality and low perceived risk were not drivers of impulse buying tendency. |
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Main drivers for microtransactions as impulse purchases in e-commerceMicrotransactionsMobile commerceMobile gamesImpulse purchasesImpulseComércio eletrónicoJogosTelemóvelModelos de negócioWith mobile technology evolving at a very fast-paced level, consumers now have many choices of entertainment on their mobile devices. Thousands of games are available to download free of charge on virtually every smartphone and with them a new revenue model has emerged: microtransactions. Characterized by low price points, microtransaction have seldom been studied extensively. With great potential in the future, this type of revenue model is currently outgrowing traditional pay-to-play model types. By focusing on several types of mobile game item drivers and adapting some previous research and models, this study intends to identify and create a model with the main drivers of microtransactions that lead to impulse purchases in mobile game applications and understand if a price increase will lead to a lower purchase intention. A PLS-SEM analysis was conducted on a sample of 301 individuals. The measurement model showed a good fit of parameters, with AVE above 0.50 for all components, composite reliability superior to 0.70 for all components as well as an HTMT value inferior to 0.90 present in each component relationship. The six components considered explained 53.3% of the variance in impulse buying tendency. Significant component drivers from strongest to least robust were flow experience, social, hedonic/emotional and performance drivers. Functionality and low perceived risk were not drivers of impulse buying tendency.Com a tecnologia móvel a evoluir a um passo cada vez mais acelerado, os consumidores têm agora várias escolhas de entretenimento nos seus dispositivos móveis. Milhares de jogos estão disponíveis para descarregar de forma gratuita em virtualmente qualquer smartphone e com isso, um novo modelo de negócio tem emergido: microtransações. Caracterizado pelos seus preços baixos, as microtransações têm raramente sido estudadas extensivamente. Com um grande potencial no futuro, este tipo de modelo de negócio está a ultrapassar no presente os modelos tradicionais de comprar-para-jogar. Ao focar-se em vários tipos de drivers de itens de jogos móveis e adaptando pesquisas e modelos anteriores, este estudo pretende identificar e criar um modelo com os principais drivers das microtransações que originam compras por impulse em aplicações de jogos móveis e compreender se um aumento de preço leva a uma intenção de compra reduzida. Uma análise de PLS-SEM foi efetuada numa amostra de 301 indivíduos. O modelo medido demonstrou um bom índice dos seus parâmetros, com um AVE superior a 0.50 para todos os componentes, confiabilidade composta também superior a 0.70 para todos os componentes e um valor de HTMT inferior a 0.90 para cada relação entre os componentes. Os seis componentes originais considerados explicam 53.2% da variância da tendência de compra por impulso. Os drivers de conteúdo significantes do mais forte para o menos forte foram: fluidez de experiência, social, hedónico/emocional e performance. Funcionalidade e baixa perceção de risco não foram drivers de tendência de compra por impulso.2018-03-02T12:49:03Z2017-11-15T00:00:00Z2017-11-152017-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/15309TID:201761807engCaetano, Ricardo Gil Fonsecainfo: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:RCAAP2023-11-09T17:25:15Zoai:repositorio.iscte-iul.pt:10071/15309Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:11:27.095717Repositório 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 |
Main drivers for microtransactions as impulse purchases in e-commerce |
title |
Main drivers for microtransactions as impulse purchases in e-commerce |
spellingShingle |
Main drivers for microtransactions as impulse purchases in e-commerce Caetano, Ricardo Gil Fonseca Microtransactions Mobile commerce Mobile games Impulse purchases Impulse Comércio eletrónico Jogos Telemóvel Modelos de negócio |
title_short |
Main drivers for microtransactions as impulse purchases in e-commerce |
title_full |
Main drivers for microtransactions as impulse purchases in e-commerce |
title_fullStr |
Main drivers for microtransactions as impulse purchases in e-commerce |
title_full_unstemmed |
Main drivers for microtransactions as impulse purchases in e-commerce |
title_sort |
Main drivers for microtransactions as impulse purchases in e-commerce |
author |
Caetano, Ricardo Gil Fonseca |
author_facet |
Caetano, Ricardo Gil Fonseca |
author_role |
author |
dc.contributor.author.fl_str_mv |
Caetano, Ricardo Gil Fonseca |
dc.subject.por.fl_str_mv |
Microtransactions Mobile commerce Mobile games Impulse purchases Impulse Comércio eletrónico Jogos Telemóvel Modelos de negócio |
topic |
Microtransactions Mobile commerce Mobile games Impulse purchases Impulse Comércio eletrónico Jogos Telemóvel Modelos de negócio |
description |
With mobile technology evolving at a very fast-paced level, consumers now have many choices of entertainment on their mobile devices. Thousands of games are available to download free of charge on virtually every smartphone and with them a new revenue model has emerged: microtransactions. Characterized by low price points, microtransaction have seldom been studied extensively. With great potential in the future, this type of revenue model is currently outgrowing traditional pay-to-play model types. By focusing on several types of mobile game item drivers and adapting some previous research and models, this study intends to identify and create a model with the main drivers of microtransactions that lead to impulse purchases in mobile game applications and understand if a price increase will lead to a lower purchase intention. A PLS-SEM analysis was conducted on a sample of 301 individuals. The measurement model showed a good fit of parameters, with AVE above 0.50 for all components, composite reliability superior to 0.70 for all components as well as an HTMT value inferior to 0.90 present in each component relationship. The six components considered explained 53.3% of the variance in impulse buying tendency. Significant component drivers from strongest to least robust were flow experience, social, hedonic/emotional and performance drivers. Functionality and low perceived risk were not drivers of impulse buying tendency. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-11-15T00:00:00Z 2017-11-15 2017-09 2018-03-02T12:49:03Z |
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/10071/15309 TID:201761807 |
url |
http://hdl.handle.net/10071/15309 |
identifier_str_mv |
TID:201761807 |
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 application/octet-stream |
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 |
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