Role of Explainable Artificial Intelligence in E-Commerce

Contents
Contributors
Introduction to Explainable AI (XAI) in E-Commerce
	1 Introduction
	2 XAI
	3 Gaining an Edge Through AI
	4 Artificial Intelligence in eCommerce: Benefits
	5 Need of XAI
	6 Discussion
	7 Conclusion
	References
Explainable Artificial Intelligence (XAI) for Managing Customer Needs in E-Commerce: A Systematic Review
	1 Introduction
	2 XAI Methods/Techniques
		2.1 Layer-Wise Relevance Propagation (LRP)
		2.2 Local Interpretable Model Agnostic Explanations (LIME)
		2.3 Counterfactual Method
		2.4 SHapley Additive Explanations (SHAP)
		2.5 Generalized Additive Model (GAM)
	3 Applications of Explainable AI
	4 Case Study for Compliance and Legal Professionals: XAI in Consumer Lending
		4.1 Target Audiences and AI Explanation Expectations
		4.2 Tools and Procedures
		4.3 Learning Experiences
	5 Modern XAI Technologies
	6 Conclusion and Future Challenges
	References
Decoding the Recommender System: A Comprehensive Guide to Explainable AI in E-commerce
	1 Introduction
	2 The Need for Explainable AI in Recommender Systems
		2.1 Trustworthiness and User Confidence
		2.2 Ethical and Legal Compliance
		2.3 Debugging and Model Improvement
		2.4 Transparency for System Understanding
		2.5 Identifying and Addressing Biases
		2.6 Error Detection and Correction
		2.7 Feature Engineering and Selection
		2.8 Iterative Model Improvement
		2.9 Collaborative Development and Communication
	3 Types of Explanations in Recommender Systems
		3.1 Content-Based Explanations
		3.2 Collaborative-Based Explanations
		3.3 Hybrid Explanations
	4 Techniques for Generating Explanations
		4.1 Model-Agnostic Methods
		4.2 Model-Specific Methods
		4.3 Practical Implementations of Explainable Recommender Systems
	5 Conclusion and Future Recommendation
	References
“The AI Revolution in E-Commerce: Personalization and Predictive Analytics”
	1 Introduction
	2 Personalization
		2.1 Benefits of Personalization for e-commerce Businesses and Consumers
	3 Predictive Analytics
		3.1 Benefits of Predictive Analytics for e-commerce Businesses and Consumers
	4 Integration of Personalization and Predictive Analytics
	5 Applications of AI in E-commerce
	6 Challenges and Considerations
	7 Future of AI in E-Commerce
	8 Conclusion
	References
Impact of Artificial Intelligence on Purchase Intention: A Bibliometric Analysis
	1 Introduction
	2 Conceptual Background
	3 Methodology
	4 Findings
		4.1 Annual Scientific Production
		4.2 Analysis of the Authors, Articles and Journals
		4.3 Top Keywords Clusters and Connection
	5 Conclusion
	6 Future Implication
	References
Chatbot-XAI—The New Age Artificial Intelligence Communication Tool for E-Commerce
	1 Introduction
	2 Understanding Explainable AI (XAI)
	3 Importance of Explainable AI
	4 Chatbot
		4.1 XAI Chatbot and General Chatbot
		4.2 XAI Concepts and Techniques
		4.3 Explainable
		4.4 Machine Learning Model Transparency Factors
		4.5 Linear, Logistic Regression, Decision Tree, and Random Forest
		4.6 Decision Tree
		4.7 Random Forest
		4.8 Black and White Box Models
		4.9 Numerous XAI Systems Can Be Enabled to Different Chatbots as Per Needs
		4.10 Chatbot Types
		4.11 Beneficial Features of XAI Chatbot
		4.12 Challenges with XAI
		4.13 Chatbots and Ecommerce
		4.14 Worth of Chatbots and Support Mechanism in Ecommerce
		4.15 Future of Chatbots in Ecommerce with XAI Facilitation
		4.16 XAI Revolutionizing E-Commerce
		4.17 The Key Areas in E-Commerce Where XAI Can Be a Help Agent
		4.18 Major Hindrances in Incorporating XAI Enabled Chatbots in Ecommerce Industry
		4.19 XAI Chatbot Incorporation Techniques to Be Used in Ecommerce
		4.20 XAI Demand, Supply and Surge Process
		4.21 Some of the Leading Brands Already Using XAI Enabled Chatbots Are:
	5 Conclusion
	References
Demystifying Applications of Explainable Artificial Intelligence (XAI) in e-Commerce
	1 Introduction
	2 Prime Parts of XAI
	3 History of E-Commerce
	4 Impacts of AI in E-Commerce
		4.1 Enhanced Target Marketing
		4.2 Stronger Bonds with Repeat Buyers
		4.3 Simple Mechanization
		4.4 Efficient Sales Process
	5 AI Uses in E-commerce
		5.1 Personalized Attention to Each Client
		5.2 Customer Segregation
		5.3 Superior Arrangements
		5.4 Trying to Guess Sales and Needs
	6 Main Perspectives for the Need for XAI
		6.1 Scientific Perspective
		6.2 Regulatory Perspective
		6.3 Focusing on the Business World
		6.4 Model’s Developmental Perspective
		6.5 User and Societal Viewpoints
	7 Problems with XAI
	8 Deployment-Stage Difficulties and Future Research Priorities for XAI
	9 Conclusion
	References
From Algorithms to Ethics: XAI’s Impact on E-Commerce
	1 Introduction
	2 The E-commerce Revolution
		2.1 The Digital Transformation
		2.2 The Algorithmic Foundation
		2.3 The Ethical Dilemmas
		2.4 The Role of XAI
	3 The Algorithmic Era: Transforming E-commerce
	4 Ethical Dilemmas in E-commerce
	5 Transparency as a Foundation of Trust
		5.1 Ethical Considerations
	6 Fairness and Bias in E-commerce
	7 Balancing Personalization and Privacy
	8 Implementing XAI in E-commerce
		8.1 Ethical Considerations
	9 The Future of Ethical E-commerce with XAI
		9.1 Ethical Retailer Alliances
	10 Conclusion: Toward a More Ethical and Transparent E-commerce
	References