02111nas a2200253 4500000000100000000000100001008004100002260001200043653002200055653003000077653002100107653004000128653003200168100001800200700001700218700001800235700002100253245010600274856005800380300001000438490000600448520138900454022001401843 2024 d c08/202410aConsumer Behavior10aLogistics Service Quality10aMachine Learning10aSHAP (SHapley Additive ExPlanation)10aTechnology Acceptance Model1 aCheng-Feng Wu1 aKunkun Zhang1 aMeng-Chen Lin1 aChei-Chang Chiou00aPredicting Consumer Electronics E-Commerce: Technology Acceptance Model and Logistics Service Quality uhttps://www.ijimai.org/journal/bibcite/reference/3475 a66-850 v83 aIn online shopping for consumer electronics, information and physical flows are crucial determinants of consumer purchase intentions. This study examines these factors by integrating the Technology Acceptance Model with logistics service quality, analyzing the relationship between retailers and consumers in e-commerce. The focus is on how information and physical flows, as critical supply chain elements, affect consumers' decisions to purchase online. A structural model and machine learning algorithm with SHapley Additive exPlanations are employed to analyze the data, providing a comprehensive analysis of the Technology Acceptance Model in conjunction with logistics service quality. The findings reveal that attitude, perceived usefulness, and informativeness are the most influential factors affecting consumers' purchase intention. This study contributes to the understanding of consumer behavior in the context of e-commerce platforms for consumer electronic products by integrating the Technology Acceptance Model and logistics service quality theoretical perspectives and analyzing the data using innovative techniques, specifically, Shapley Additive Explanations. This research offers valuable insights into the significant role of various features in shaping consumers' purchase intention in the context of online e-commerce platforms for consumer electrical products. a1989-1660