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Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

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Published on: September 27, 2019

Factors Affecting Consumers' Online Choice Intention: A Study Based on Bayesian Network.

Weibin Deng^1,2, Ting Su^1,2, Yiming Zhang³

¹Key Laboratory of Electronic Commerce and Modern Logistics, Chongqing University of Posts and Telecommunications, Chongqing, China.

Frontiers in Psychology

|November 8, 2021

Summary

This summary is machine-generated.

Consumers

Keywords:

Bayesian network purchase intention search intention structural equation model two-stage decision-making theory

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Area of Science:

Consumer Behavior
E-commerce
Marketing Science

Background:

Mature online retail in China offers diverse consumer choices.
Factors influencing online search and purchase decisions are complex.
Two-stage decision-making theory provides a framework for analysis.

Purpose of the Study:

To investigate factors influencing consumers' online search intention and purchase willingness.
To examine the relationship between online search intention and purchase intention.
To quantitatively analyze the influence of perceived benefits, channel trust, and channel transfer costs.

Main Methods:

Experimental research design.
Structural equation modeling (SEM) to analyze relationships.
Bayesian network analysis for quantitative influence assessment.

Main Results:

Online trust significantly impacts online search intention.
Perceived benefits are the most crucial factor for online purchase intention.
A positive correlation exists between online search intention and purchase intention.

Conclusions:

Online trust and perceived benefits are key drivers in e-commerce.
Understanding these factors supports online retail strategy.
Findings aid in promoting the healthy development of online shopping environments.