Predicting Consumer Electronics E-Commerce: Technology Acceptance Model and Logistics Service Quality.

Cheng Feng Wu; Kunkun Zhang; Meng Chen Lin; Chei Chang Chiou

doi:10.9781/ijimai.2024.08.001

Authors

Cheng Feng Wu National Taipei University
Kunkun Zhang Hubei University Of Economics
Meng Chen Lin Chien Hsin University of Science and Technology
Chei Chang Chiou National Changhua University of Education

DOI:

https://doi.org/10.9781/ijimai.2024.08.001

Keywords:

Consumer Behavior, Logistics Service Quality, Machine Learning, SHAP (SHapley Additive ExPlanation), Technology Acceptance Model

Abstract

In 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.

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