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Predicting m-commerce adoption determinants: A neural network approach
Alain Yee Loong Chong
Research output
:
Journal Publication
›
Article
›
peer-review
325
Citations (Scopus)
Overview
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Dive into the research topics of 'Predicting m-commerce adoption determinants: A neural network approach'. Together they form a unique fingerprint.
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Keyphrases
Mobile Commerce
100%
Neural Network Method
100%
Adoption Determinants
100%
Perceived Value
20%
Personal Innovativeness
20%
Perceived Enjoyment
20%
Technology Model
20%
Noncompensatory Models
20%
Unified Theory of Acceptance
20%
China
10%
Extended Model
10%
Explosives
10%
Online Survey
10%
Social Influence
10%
Nonlinear Relationship
10%
Regression Analysis
10%
Educational Level
10%
Neural Network Model
10%
Influence Condition
10%
User Demographics
10%
Aging Level
10%
Consumer Information
10%
Performance Expectancy
10%
Chinese Users
10%
Applied Neural Network
10%
Fast-growing
10%
Adoption Prediction
10%
Regression Model
10%
Demographic Profile
10%
Decision Basis
10%
Adoption Decision
10%
Neural Network Analysis
10%
Facilitating Conditions
10%
Effort Expectancy
10%
Computer Science
Neural Network Approach
100%
Commerce Adoption
100%
Neural Network
33%
Personal Innovativeness
33%
Unified Theory
33%
Information System
16%
Educational Level
16%
Neural Network Model
16%
Linear Relationship
16%
Online Survey
16%