Serviços digitais inteligentes: a influência da motivação e da satisfação com a vida no comportamento inovativo e na usabilidade
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Citações na Scopus
Tipo de produção
Tese
Data
2021
Autores
Lui, M. L. C.
Orientador
Bernardes, Roberto Carlos
Periódico
Título da Revista
ISSN da Revista
Título de Volume
Citação
LUI, M. L. C. Serviços digitais inteligentes/ a influência da motivação e da satisfação com a vida no comportamento inovativo e na usabilidade. 2021. 211 f. Tese (Doutorado em Administração de Empresas) - Centro Universitário FEI, São Paulo, 2021 Disponível em: https://doi.org/10.31414/ADM.2021.T.131686.
Texto completo (DOI)
Palavras-chave
Inteligência artificial,Motivação (Psicologia)
Resumo
A transformação digital, por meio de plataformas inteligentes de e-commerce, canais de consumo on-line e da oferta de novos serviços pessoais, com a aplicação da IA (Inteligência artificial), está modificando dramaticamente a lógica de atuação no mundo dos negócios. Os
desafios das novas estratégias de mercado para a criação de valor, em prol da competitividade digital, estão cada vez mais centrados na compreensão analítica e preditiva do comportamento do consumo e na experiência de uso da inovação digital pelo usuário. A crise pandêmica de Covid-19 acelerou ainda mais tais mudanças, atestadas pela maior interação homem-máquina, proporcionada pelas plataformas digitais. Compreender o comportamento de consumo de serviços digitais, que passam a ser bens de experiência, pode ajudar as empresas em sua
adequação à nova arena competitiva, na busca por novas oportunidades em mercados e por tecnologias emergentes, com alto potencial de impacto, de transformação de mercado e de lock-in do consumo. Grande parte das pesquisas relacionadas ao consumo de produtos tecnológicos, com destaque aos modelos Technology Acceptance Model (TAM) e Unified Theory of Acceptance and Use of Technology (UTAUT), não se interessa ou pouco avançou no esclarecimento do grau de inovatividade do consumidor, assim como na mensuração da usabilidade de inovações, restringindo-se às dimensões clássicas (adoção e aceitação tecnológica) da Teoria de Difusão da Inovação (IDT) (Innovation Diffusion Theory). Refletir criticamente acerca de tal teoria, nesse novo cenário, compreendendo quem são os consumidores, qual é a usabilidade da IA na oferta de serviços digitais, e como se dão as relações com as motivações e a satisfação com a vida, constituem uma oportunidade para responder a um gap teórico existente na literatura. Na era da transformação digital, a complexidade das relações de consumo pessoal aumenta e passa a ser direcionadora das decisões das empresas digitais que, cada vez mais, desenvolvem soluções centradas na personalização e na cognição inteligente do seu comportamento preditivo. O objetivo desta tese, portanto, é eliminar a lacuna teórica existente na agenda de pesquisa sobre o consumo inovativo, verificando as relações estabelecidas entre motivação e satisfação com a vida e o binômio usabilidade e consumo inovativo de serviços digitais inteligentes. Para tanto, realizamos pesquisa com uma amostra de n = 517 participantes, usuários de assistente pessoal inteligente, no período de maio a junho de 2020. Os dados foram analisados por meio da Modelagem de Equações Estruturais e pela técnica de Mínimos Quadrados Parciais (PLS), com o uso do software SmartPLS-3. Optamos por um modelo mais parcimonioso e, por isso, usamos o construto motivação como 2ª ordem. Apoiada nos resultados da Modelagem de Equações
Estruturais, esta pesquisa evidencia – e essa é a sua principal contribuição – que satisfação com a vida e as motivações, esta última, desde que seja mediada por domínio específico de inovatividade e inovação inata têm, ambas, influência na usabilidade e no comportamento inovativo. O modelo utilizado apresentou um ??2 de 32% da variável dependente usabilidade, e 14% da variável dependente comportamento inovativo; e demonstrou validade preditiva, por intermédio do indicador ??2, e tamanho do efeito, pelo indicador ??2 – resultados estes satisfatórios
The digital transformation is dramatically changing the logic of operations in the business world through smart e-commerce platforms, online consumer channels and the provision of new personal services with the application of AI (artificial Intelligence). The challenges for new market strategies for value creation geared towards digital competitiveness are increasingly centered on analytical and predictive understanding of consumer behavior and user experience of using digital innovation. The Covid-19 pandemic crisis further accelerated these changes, attested by the greater human-machine interaction with digital platforms. Understanding the behavior of consumption of digital services, which become goods of experience, can help companies adapt to the new competitive arena in the search for new opportunities in emerging markets and technologies with high impact potential, market transformation and lock-in consumption. Much of the research related to the consumption of technological products with emphasis on the TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) models are not interested, or have made little progress, in clarifying the degree of consumer innovation, as well as how to measure the usability of innovations, restricting the classic dimensions of diffusion of innovation by theories of adoption and technological acceptance. Critically reflect on the diffusion of innovation (Innovation Diffusion Theory – IDT) in this new scenario, understanding who these consumers are, the usability of AI in the offer of digital services and what is the influence of motivations, and satisfaction with life, present as an opportunity to answer a theoretical gap in the literature. In the era of digital transformation, the complexity of personal consumer relations increases and becomes the driving force behind the decisions of digital companies that increasingly develop solutions focused on personalization and the intelligent cognition of their predictive behavior. The objective of this Thesis is to contribute by responding to a theoretical gap existing in the research agenda on innovative consumption, verifying the influence of motivation and satisfaction with life on usability and innovative behavior for intelligent digital services. For this, we conducted a survey with a sample of n = 517 participants using intelligent personal assistants, from May to June 2020. The data were analyzed using structural equation modeling and the partial least squares (PLS) technique with SmartPLS-3 software. We decided on a more parsimonious model, which is why we use the motivation construct as a second order. The main contribution of the research is based on the results of modeling structural equations and revealed that life satisfaction and motivations, the latter, provided it is mediated by a domain – specific of innovativeness and innate innovativeness, both have an influence on usability and innovative behavior. The model presented an ??2 of 32% of the dependent variable usability and 14% of the dependent variable innovative behavior and demonstrated predictive validity through the ??2 indicator and satisfactory effect size through the ??2 indicator
The digital transformation is dramatically changing the logic of operations in the business world through smart e-commerce platforms, online consumer channels and the provision of new personal services with the application of AI (artificial Intelligence). The challenges for new market strategies for value creation geared towards digital competitiveness are increasingly centered on analytical and predictive understanding of consumer behavior and user experience of using digital innovation. The Covid-19 pandemic crisis further accelerated these changes, attested by the greater human-machine interaction with digital platforms. Understanding the behavior of consumption of digital services, which become goods of experience, can help companies adapt to the new competitive arena in the search for new opportunities in emerging markets and technologies with high impact potential, market transformation and lock-in consumption. Much of the research related to the consumption of technological products with emphasis on the TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) models are not interested, or have made little progress, in clarifying the degree of consumer innovation, as well as how to measure the usability of innovations, restricting the classic dimensions of diffusion of innovation by theories of adoption and technological acceptance. Critically reflect on the diffusion of innovation (Innovation Diffusion Theory – IDT) in this new scenario, understanding who these consumers are, the usability of AI in the offer of digital services and what is the influence of motivations, and satisfaction with life, present as an opportunity to answer a theoretical gap in the literature. In the era of digital transformation, the complexity of personal consumer relations increases and becomes the driving force behind the decisions of digital companies that increasingly develop solutions focused on personalization and the intelligent cognition of their predictive behavior. The objective of this Thesis is to contribute by responding to a theoretical gap existing in the research agenda on innovative consumption, verifying the influence of motivation and satisfaction with life on usability and innovative behavior for intelligent digital services. For this, we conducted a survey with a sample of n = 517 participants using intelligent personal assistants, from May to June 2020. The data were analyzed using structural equation modeling and the partial least squares (PLS) technique with SmartPLS-3 software. We decided on a more parsimonious model, which is why we use the motivation construct as a second order. The main contribution of the research is based on the results of modeling structural equations and revealed that life satisfaction and motivations, the latter, provided it is mediated by a domain – specific of innovativeness and innate innovativeness, both have an influence on usability and innovative behavior. The model presented an ??2 of 32% of the dependent variable usability and 14% of the dependent variable innovative behavior and demonstrated predictive validity through the ??2 indicator and satisfactory effect size through the ??2 indicator