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Orientador(es)
Resumo(s)
Technology has changed how consumers live their lives and make purchases, which has forced
businesses to adjust to a more competitive market environment. Artificial Intelligence (AI) is
one example of a disruptive technology that has revolutionised corporate processes and
offered creative ways to improve customer experiences. In contrast to conventional decisionmaking processes, this thesis examines the effects of AI-driven Recommendation Agents
(RAs), on online retail, with a special emphasis on customer satisfaction and purchase
intention. By evaluating customer data and forecasting their preferences, RAs use AI to
customise the online purchasing experience, which enhances decision-making and reduces
information overload. There is no empirical study on AI personalisation's substantial impact
on customer behaviour, despite the industry's increased investment in this area. To close this
gap, this study compares consumer responses when supported in making decisions by RAs vs
traditional techniques. The main study topic looks at how customer satisfaction and purchase
intention are affected by decision-making supported by RAs. Furthermore, the research
explores how factors like algorithm aversion, perceived decision autonomy, and trust affect
these results. This study attempts to advance knowledge of AI's revolutionary potential in
marketing and its function in promoting improved customer interactions by offering insightful
information about the strategic implications of RAs for online businesses. To accomplish the
intended objective, quantitative analytic research using an online questionnaire with 150
replies was used to develop this thesis.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and Analytics
Palavras-chave
Recommender Agents Artificial Intelligence Customer Satisfaction Purchase Intention Consumer Decision-Making SDG 8 - Decent work and economic growth
