The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/26368 |
Resumo: | Artificial Intelligence (AI) has been playing an essential role in transforming the business environment, showing its potential to enhance businesses’ productivity, adaptation, and competitiveness. In a period where environmental matters become a concern on top of worldwide agendas, AI is pointed to have the potential to be deployed and implemented to enhance green performances for companies and help mitigating their environmental impacts. This investigation aims to assess the factors influencing managers’ intentionality of implementing AI based systems in their companies to boost environmental sustainability. This study also intends to analyze to what extent these drivers are different between managers based in Portugal and managers based in other European countries. For this purpose, both topics were thoroughly considered through literature review and then, further developed through a qualitative approach where interviews were conducted. The interviews conducted showed that the main drivers of success for the implementation relate with the perception of AI as a key tool to help companies moving towards environmental targets and potential the tool can bring to businesses performances. The main drivers of unsuccess for the implementation related with the complexity and time it takes to develop and implement a system that is capable to run properly, and the initial investment and costs required. Overall, both Portugal based managers and managers based abroad believe in AI as a reliable tool to potentialize environmentally friendly businesses but highlight different aspects as the biggest constraints. |
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The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companiesArtificial intelligenceDecarbonizationEnergy efficiencyInteligência artificialSustentabilidade -- SustainabilityDescarbonizaçãoEficiência energéticaArtificial Intelligence (AI) has been playing an essential role in transforming the business environment, showing its potential to enhance businesses’ productivity, adaptation, and competitiveness. In a period where environmental matters become a concern on top of worldwide agendas, AI is pointed to have the potential to be deployed and implemented to enhance green performances for companies and help mitigating their environmental impacts. This investigation aims to assess the factors influencing managers’ intentionality of implementing AI based systems in their companies to boost environmental sustainability. This study also intends to analyze to what extent these drivers are different between managers based in Portugal and managers based in other European countries. For this purpose, both topics were thoroughly considered through literature review and then, further developed through a qualitative approach where interviews were conducted. The interviews conducted showed that the main drivers of success for the implementation relate with the perception of AI as a key tool to help companies moving towards environmental targets and potential the tool can bring to businesses performances. The main drivers of unsuccess for the implementation related with the complexity and time it takes to develop and implement a system that is capable to run properly, and the initial investment and costs required. Overall, both Portugal based managers and managers based abroad believe in AI as a reliable tool to potentialize environmentally friendly businesses but highlight different aspects as the biggest constraints.A Inteligência Artificial (IA) tem vindo a desempenhar um papel essencial na transformação do setor empresarial, mostrando o seu potencial para aumentar a produtividade, adaptação e competitividade das empresas. Num período em que as questões ambientais se tornam uma preocupação nas agendas mundiais, a IA é apontada como tendo o potencial para ser implementada e explorada para melhorar desempenhos ecológicos e ajudar a mitigar impactos ambientais. Esta investigação visa avaliar os fatores que influenciam a intencionalidade dos gestores na implementação de sistemas baseados em IA nas suas empresas para impulsionar a sustentabilidade ambiental. Este estudo pretende também analisar até que ponto estes fatores são diferentes entre gestores sediados em Portugal e gestores sediados noutros países europeus. Para este efeito, ambos os tópicos foram cuidadosamente considerados através de uma revisão bibliográfica e, posteriormente, desenvolvidos através de uma abordagem qualitativa onde foram realizadas entrevistas. As entrevistas realizadas mostraram que os principais fatores de sucesso para a implementação estão relacionados com a percepção da IA como uma ferramenta chave para ajudar as empresas nos seus objetivos ambientais e o potencial que a ferramenta apresenta no desempenho das empresas. Os principais fatores de insucesso relacionam-se com a complexidade do processo e o tempo necessário para desenvolver e implementar um sistema capaz de funcionar corretamente, bem como o investimento e os custos necessários. Em geral, tanto gestores sediados em Portugal como gestores sediados no estrangeiro acreditam na IA como uma ferramenta fiável para potencializar negócios mais verdes, mas destacam diferentes aspectos como os maiores constrangimentos.2022-10-31T17:02:05Z2022-09-22T00:00:00Z2022-09-22info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/26368TID:203085833engPinto, Beatriz Rosadoinfo: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:RCAAP2023-11-09T17:56:44Zoai:repositorio.iscte-iul.pt:10071/26368Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:29:07.995432Repositório 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 intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
title |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
spellingShingle |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies Pinto, Beatriz Rosado Artificial intelligence Decarbonization Energy efficiency Inteligência artificial Sustentabilidade -- Sustainability Descarbonização Eficiência energética |
title_short |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
title_full |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
title_fullStr |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
title_full_unstemmed |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
title_sort |
The intentionality of implementing artificial intelligence and the respective impact on the environmental sustainability of companies |
author |
Pinto, Beatriz Rosado |
author_facet |
Pinto, Beatriz Rosado |
author_role |
author |
dc.contributor.author.fl_str_mv |
Pinto, Beatriz Rosado |
dc.subject.por.fl_str_mv |
Artificial intelligence Decarbonization Energy efficiency Inteligência artificial Sustentabilidade -- Sustainability Descarbonização Eficiência energética |
topic |
Artificial intelligence Decarbonization Energy efficiency Inteligência artificial Sustentabilidade -- Sustainability Descarbonização Eficiência energética |
description |
Artificial Intelligence (AI) has been playing an essential role in transforming the business environment, showing its potential to enhance businesses’ productivity, adaptation, and competitiveness. In a period where environmental matters become a concern on top of worldwide agendas, AI is pointed to have the potential to be deployed and implemented to enhance green performances for companies and help mitigating their environmental impacts. This investigation aims to assess the factors influencing managers’ intentionality of implementing AI based systems in their companies to boost environmental sustainability. This study also intends to analyze to what extent these drivers are different between managers based in Portugal and managers based in other European countries. For this purpose, both topics were thoroughly considered through literature review and then, further developed through a qualitative approach where interviews were conducted. The interviews conducted showed that the main drivers of success for the implementation relate with the perception of AI as a key tool to help companies moving towards environmental targets and potential the tool can bring to businesses performances. The main drivers of unsuccess for the implementation related with the complexity and time it takes to develop and implement a system that is capable to run properly, and the initial investment and costs required. Overall, both Portugal based managers and managers based abroad believe in AI as a reliable tool to potentialize environmentally friendly businesses but highlight different aspects as the biggest constraints. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10-31T17:02:05Z 2022-09-22T00:00:00Z 2022-09-22 |
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/10071/26368 TID:203085833 |
url |
http://hdl.handle.net/10071/26368 |
identifier_str_mv |
TID:203085833 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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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 |
instacron_str |
RCAAP |
institution |
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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