A CROSS-SECTIONAL DESCRIPTIVE STUDY OF THE COGNITIVE AND AFFECTIVE FACTORS TOWARDS THE ONLINE SHOPPING DECISION MAKING ABILITY OF INDIAN ONLINE CONSUMERS: AN ARTIFICIAL NEURAL NETWORK (ANN) APPROACH

Authors

  • Sadaf Shah1, Jaiman Preet Kaur1,* Author

Abstract

This study aims to explore the best predictors of online shopping decision making ability (OSDMA) between cognitive factors (CF) and affective factors (AF) amongst the Indian online consumer. The influence of the independent variables (cognitive and affective factors) on the dependent variable (online shopping making ability) is checked using two hypotheses. The data was collected using web-based structured questionnaire. The sample size was 600 respondents. The enter method and stepwise regression were used to generate linear models. Artificial neutral network (ANN) analysis, a machine learning algorithm was employed in the research to generate nonlinear model.  Data was analyzed using SPSS 23.0. The study finally concluded that affective factors is the best predicting factor towards the online shopping decision making ability.

Keywords- Online Shopping Decision Making Ability; Cognitive Factors; Affective Factors Regression Analysis-Enter Method, Artificial Neural Network (ANN)

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Published

2023-06-25

Issue

Vol. 22 No. 1 (2023): International Development Planning Review

Section

Articles

How to Cite

A CROSS-SECTIONAL DESCRIPTIVE STUDY OF THE COGNITIVE AND AFFECTIVE FACTORS TOWARDS THE ONLINE SHOPPING DECISION MAKING ABILITY OF INDIAN ONLINE CONSUMERS: AN ARTIFICIAL NEURAL NETWORK (ANN) APPROACH. (2023). International Development Planning Review, 22(1), 23-39. https://idpr.org.uk/index.php/idpr/article/view/120