TY - GEN
T1 - How AI-Powered Assistance Bridges Attention, Comprehension, Acceptance and Purchase Intention in Online Shopping
AU - Guo, Li Bo
AU - Lo, Ying Tuan
AU - King, Andrew
AU - Luo, Yang
AU - Tan, Andrew Huey Ping
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - This research aims to investigate the mediating role of AI-powered assistance in the relationship between consumer attention, comprehension, acceptance, and purchase intention on e-commerce platforms. By exploring how AI technologies influence consumer behavior, this study seeks to provide a comprehensive understanding of the mechanisms through which AI-driven features enhance the online shopping experience and impact purchasing decisions. The findings will contribute to the growing body of knowledge on AI integration in e-commerce, offering practical insights for online retailers to optimize their use of AI technologies to drive consumer engagement and increase sales. Key areas of focus include the credibility of information sources, the nature of message content, and user characteristics, all of which play critical roles in shaping consumer behavior. This research employs a conceptual model integrating theories from consumer psychology, marketing, and artificial intelligence to analyze and optimize the online shopping experience.
AB - This research aims to investigate the mediating role of AI-powered assistance in the relationship between consumer attention, comprehension, acceptance, and purchase intention on e-commerce platforms. By exploring how AI technologies influence consumer behavior, this study seeks to provide a comprehensive understanding of the mechanisms through which AI-driven features enhance the online shopping experience and impact purchasing decisions. The findings will contribute to the growing body of knowledge on AI integration in e-commerce, offering practical insights for online retailers to optimize their use of AI technologies to drive consumer engagement and increase sales. Key areas of focus include the credibility of information sources, the nature of message content, and user characteristics, all of which play critical roles in shaping consumer behavior. This research employs a conceptual model integrating theories from consumer psychology, marketing, and artificial intelligence to analyze and optimize the online shopping experience.
KW - AI-powered Assistance
KW - Consumer Behavior
KW - Online Shopping
KW - Purchase Intention
UR - http://www.scopus.com/inward/record.url?scp=105002713068&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-3949-6_21
DO - 10.1007/978-981-96-3949-6_21
M3 - Conference Proceeding
AN - SCOPUS:105002713068
SN - 9789819639489
T3 - Lecture Notes in Networks and Systems
SP - 279
EP - 286
BT - Selected Proceedings from the 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024 - Advances in Intelligent Manufacturing and Robotics
A2 - Chen, Wei
A2 - Ping Tan, Andrew Huey
A2 - Luo, Yang
A2 - Huang, Long
A2 - Zhu, Yuyi
A2 - PP Abdul Majeed, Anwar
A2 - Zhang, Fan
A2 - Yan, Yuyao
A2 - Liu, Chenguang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024
Y2 - 22 August 2024 through 23 August 2024
ER -
