Citas bibligráficas
Vega, S., Robladillo, B. (2024). La influencia del aseguramiento estructural, calidad del sitio web y percepción de calidad del producto en la intención de recompra a través de la satisfacción en el sector Marketplace B2 [Trabajo de investigación, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/675357
Vega, S., Robladillo, B. La influencia del aseguramiento estructural, calidad del sitio web y percepción de calidad del producto en la intención de recompra a través de la satisfacción en el sector Marketplace B2 [Trabajo de investigación]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/675357
@misc{renati/502599,
title = "La influencia del aseguramiento estructural, calidad del sitio web y percepción de calidad del producto en la intención de recompra a través de la satisfacción en el sector Marketplace B2",
author = "Robladillo Avila, Balerit Adriana",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
Despite the rise of the online shopping sector, there is still a certain amount of the population that is insecure when making purchases through this medium. Therefore, the main objective of the research is to analyze the influence of structural assurance, website quality and product quality perception on repurchase intention through satisfaction. The study contributes to understanding the B2C Marketplace sector, as well as the online shopping experience from a post-adoption stage and in an emerging economy. The study methodology presents a quantitative and explanatory approach with non-probabilistic and convenience sampling. The population includes individuals over 18 years of age who have made purchases on Marketplaces such as Amazon, Falabella or Mercado Libre in the last six months. Therefore, the sample will be made up of 400 individuals to whom a questionnaire will be applied with the indicators translated from English to Spanish and adapted to the Marketplace context. Finally, for the analysis of results, the SEM model will be used due to its effectiveness for the evaluation of causal relationships and the PLS-SEM technique given its predisposition to model complex relationships between variables.
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