个性化
拆箱
感知
结构方程建模
心理学
质量(理念)
计算机科学
社会心理学
价值(数学)
知识管理
感知质量
偏最小二乘回归
信息技术
消费者行为
信息质量
信息和通信技术
万维网
计算机辅助网络访谈
调解
数据科学
作者
Gonçalo Sá,Carlos Tam,Manuela Aparício
标识
DOI:10.1108/intr-05-2024-0818
摘要
Purpose The purpose of this study is to understand the determinants of e-commerce shoppers’ well-being. Well-being refers to how positively online consumers experience and are affected by their interactions with digital shopping platforms. Studying how customers perceive their well-being when interacting with artificial intelligence (AI)-powered e-commerce websites is crucial, as it highlights a paradigm shift from traditional online shopping, focused mainly on convenience and speed, toward AI-driven experiences. In this new paradigm, AI actively shapes personalized recommendations, higher usefulness perception and higher responsiveness, confirming user expectations. Design/methodology/approach This study adapts the expectation-confirmation model (ECM), analyzing the role of perceived responsiveness, perceived personalization and perceived information quality in e-commerce shoppers’ well-being. Data were collected from 591 respondents across Portugal and Brazil and analyzed using partial least squares structural equation modeling (PLS-SEM) with multi-group comparison. Findings The findings suggest that perceived responsiveness and personalization significantly influence confirmation. Additionally, perceived usefulness relies primarily on confirmation mediating its relationship with well-being, while perceived information quality moderates the direct impact of confirmation on well-being. Notably, personalization’s impact in Portugal exceeds that of responsiveness, while it is the opposite in Brazil. Originality/value The value of this study lies first in its unique context. To the best of our knowledge, it is the first to assess customers’ well-being in AI-powered e-commerce platforms. Second, the multi-group analysis provides new and unique insights into the differences between Portugal and Brazil. Third, the study challenges ECM’s elasticity with original model adjustments. Finally, it explores the significance of perceived responsiveness, personalization and quality on e-commerce customer well-being.
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