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Abstract(s)
Vários são os estudos recentes relativos às aplicações da inteligência artificial e,
muitos deles, abordam como estas podem ter um impacto positivo na
otimização de processos no contexto empresarial. Para além disso, também são
apresentadas várias investigações sobre como a inteligência artificial
generativa tem alterado a forma como os agentes conversacionais se
liberalizaram junto dos utilizadores. Contudo, o estudo do efeito das
capacidades sociais nos chatbots enquanto estímulo da experiência do
consumidor continua a ser um objeto pouco explorado. Assim, a presente
investigação procurou analisar a empatia enquanto uma capacidade social
implementada nos agentes conversacionais dotados de inteligência artificial
generativa e como esta pode afetar a experiência do consumidor. Para tal,
foram criados dois cenários distintos, um em que o chatbot demonstrava altos
níveis de empatia e outro com baixos níveis de empatia, que foram aplicados a
uma amostra. Cada participante dessa amostra teve acesso a apenas um dos
cenários criados, sendo avaliadas a satisfação, lealdade e electronic word of
mouth, como variáveis dependentes, e a confiança, self-disclosure e apego
afetivo, como variáveis mediadoras. O estudo foi concluído com a confirmação
de duas das seis hipóteses, afirmando que a satisfação e o eWOM são
impactados positivamente quando a empatia é integrada no chatbot. Algumas
das limitações passaram pelo tipo de amostra escolhido, porém foi
demonstrado que empresas que querem seguir os desenvolvimentos
tecnológicos devem apostar na potencialização do uso da inteligência artificial
nas suas ferramentas, de modo a acompanharem as necessidades dos
consumidores.
Several recent studies have focused on the applications of artificial intelligence, and many of them discuss how these can positively impact process optimization in a business context. Additionally, there are various investigations into how generative artificial intelligence has changed the way conversational agents have become widespread among users. However, the study of the effect of social capabilities in chatbots as a stimulus for consumer experience remains an underexplored topic. Therefore, the present research aimed to analyze empathy as a social capability implemented in generative AI-powered conversational agents and how it can affect consumer experience. To achieve this, two distinct scenarios were created: one where the chatbot demonstrated high levels of empathy and another with low levels of empathy. These scenarios were applied to a sample, with each participant having access to only one of the created scenarios. Satisfaction, loyalty, and electronic word of mouth (eWOM) were evaluated as dependent variables, while trust, self-disclosure, and emotional attachment were evaluated as mediating variables. The study concluded by confirming two of the six hypotheses, asserting that satisfaction and eWOM are positively impacted when empathy is integrated into the chatbot. Some limitations included the type of sample chosen, but it was demonstrated that companies aiming to keep up with technological advancements should invest in enhancing the use of artificial intelligence in their tools to meet consumer needs
Several recent studies have focused on the applications of artificial intelligence, and many of them discuss how these can positively impact process optimization in a business context. Additionally, there are various investigations into how generative artificial intelligence has changed the way conversational agents have become widespread among users. However, the study of the effect of social capabilities in chatbots as a stimulus for consumer experience remains an underexplored topic. Therefore, the present research aimed to analyze empathy as a social capability implemented in generative AI-powered conversational agents and how it can affect consumer experience. To achieve this, two distinct scenarios were created: one where the chatbot demonstrated high levels of empathy and another with low levels of empathy. These scenarios were applied to a sample, with each participant having access to only one of the created scenarios. Satisfaction, loyalty, and electronic word of mouth (eWOM) were evaluated as dependent variables, while trust, self-disclosure, and emotional attachment were evaluated as mediating variables. The study concluded by confirming two of the six hypotheses, asserting that satisfaction and eWOM are positively impacted when empathy is integrated into the chatbot. Some limitations included the type of sample chosen, but it was demonstrated that companies aiming to keep up with technological advancements should invest in enhancing the use of artificial intelligence in their tools to meet consumer needs
Description
Keywords
Inteligência artificial Capacidades sociais Agentes conversacionais Experiência do consumidor