Fatores determinantes da compra on line: como influenciam a geração Z de Fortaleza?

• Ano de defesa: 2020
• Autor(a) principal: Almeida, Jeferson da Silva de
• Orientador(a): Leopoldino, Cláudio Bezerra
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Comportamento do consumidor; Comércio eletrônico; E-commerce; Geração Z; Consumo; Consumo (Economia)
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/53171

Understanding consumer behavior is the best way for companies to win and retain customers. In the digital age, how organizations face the challenge of seeking to understand how the new consumer, who has diverse information in the palm of his hand and who analyzes for an ever increasing speed and quality in all stages of the purchase process, including after sales . Immersed in this digital context, Generation Z individuals emerge as potential consumers of products and services sold on the online market. In this sense, the present research addresses the way in which the determinants of online shopping can influence the purchasing behavior of individuals of Generation Z in the city of Fortaleza. The study had a descriptive and quantitative nature and used variables such as purchase planning and average ticket, in addition to a model developed by Geraldo and Mainardes (2017) that contains five factors that seek to carry out or behave consumers of online purchases: purchase , online store, convenience, offers and promotions. After 384 questionnaires were applied, data analysis was performed using descriptive statistics and cluster analysis technique. How much is the result obtained, the study that proves the online shopping behavior of individuals of Generation Z of Fortaleza as more affected by the “online store” factor and less affected by the “promotion” factor. It was also verified, through the application of the Chi-square test, a statistically applied presence among the study variables, among which we highlight: a) association between "income range" and "purchase frequency"; b) association between “level of planning” and “average ticket” of the interviewees. Finally, from the use of cluster analysis, the presence of 5 clusters with different levels is found in the samples registered in the present study, or that offer a perspective of sub-niches in the analyzed analysis.