Exploring the Impact of Corporate Social Responsibility on Consumer Behavior in E-Commerce Using Fully Connected Neural Networks Models

This study examines how corporate social responsibility (CSR) affects online consumer happiness and loyalty in cross-border e-commerce for tourism services. The study examines if CSR affects online consumer satisfaction and loyalty statistically using theoretical and practical sources. The suggested method includes preprocessing, feature selection, and model training. Data integrity is maintained by standardising and fixing missing values during preprocessing. Using filter-based techniques like chi-square and correlation-based feature selection helps handle high-dimensional data. A Fully Connected Neural Network (FCNN) is used to evaluate CSR's impact on online purchase behaviour. The trained model predicted CSR's impact on customer satisfaction and loyalty with 92.38% accuracy. The results show that CSR programs significantly increase customer happiness and loyalty in e-commerce, providing useful insights for companies looking to strengthen consumer relations through social responsibility.

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Published
2024-12-04
DOI
https://doi.org/10.1109/icmnwc63764.2024.10872235
Primary Topic
E-commerce and Technology Innovations
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article
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Exploring the Impact of Corporate Social Responsibility on Consumer Behavior in E-Commerce Using Fully Connected Neural Networks Models

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E-commerce and Technology Innovations
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Exploring the Impact of Corporate Social Responsibility on Consumer Behavior in E-Commerce Using Fully Connected Neural Networks Models

Rajendra Mahanandia, Sandeep Kumar, Satvinder Singh Bakshi, Pradeep Kumar, Taruna Anand, Neelima Kalidindi
article en

Abstract

This study examines how corporate social responsibility (CSR) affects online consumer happiness and loyalty in cross-border e-commerce for tourism services. The study examines if CSR affects online consumer satisfaction and loyalty statistically using theoretical and practical sources. The suggested method includes preprocessing, feature selection, and model training. Data integrity is maintained by standardising and fixing missing values during preprocessing. Using filter-based techniques like chi-square and correlation-based feature selection helps handle high-dimensional data. A Fully Connected Neural Network (FCNN) is used to evaluate CSR's impact on online purchase behaviour. The trained model predicted CSR's impact on customer satisfaction and loyalty with 92.38% accuracy. The results show that CSR programs significantly increase customer happiness and loyalty in e-commerce, providing useful insights for companies looking to strengthen consumer relations through social responsibility.

Institute of Management Technology (IN), Barkatullah University (IN), Graphic Era University (IN), REVA University (IN)
Reduced inequalities
Openalex Percentile: Top 49%
E-commerce and Technology Innovations
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