Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications (Demystifying Technologies for Computational Excellence)

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Chapter 1 Understanding the Industry 4.0 Revolution Using Twitter Analytics
	1.1 Introduction
	1.2 Literature Review
	1.3 Methodology
		1.3.1 Data Collection
		1.3.2 Data Analysis
			1.3.2.1 Descriptive Analysis
			1.3.2.2 Content Analysis
			1.3.2.3 Network Analysis
			1.3.2.4 Topic Modeling
	1.4 Analysis and Results
		1.4.1 Descriptive Analysis of Tweets
		1.4.2 CA of Tweets
			1.4.2.1 Sentiment Analysis of Tweets
			1.4.2.2 Emotional Scores of Tweets
		1.4.3 Network Analytics of Tweets
		1.4.4 Topic Modeling of Tweets
	1.5 Discussions
		1.5.1 The Fourth Industrial Revolution Is Characterized by What Tweets? Can We See Any Particular Patterns of Communication and Information Diffusion in These Tweets?
		1.5.2 Which Topics and Contents Are Shared in Twitter? Can We Find Any Prevalent Topics or Contents?
		1.5.3 What Are the Features of Those Users Who Discuss These Topics Related to Industry 4.0 on Twitter?
		1.5.4 What Sentiments Do These Tweets Contain? What Types of Tweets Tend to Contain Sentiment?
	1.6 Conclusions
		1.6.1 Professional Use of Twitter
		1.6.2 Organizational Use of Twitter
		1.6.3 Stakeholder Engagement
		1.6.4 Hiring
		1.6.5 Sales Channel
		1.6.6 Social Listening
		1.6.7 Risk Management
	1.7 Limitation and Future Research
	References
Chapter 2 The Role of Universal Product Coding (UPC), Global Data Synchronization Network (GDSN) and Product Category Management in Efficient Consumer Response (ECR)
	2.1 Background of ECR
		2.1.1 ECR as a Profit Center in Supply Chain
		2.1.2 ECR as a Cost Alleviator in Supply Chain
		2.1.3 ECR and Operational Efficiency in Supply Chain
		2.1.4 ECR as Risk Mitigator in Supply Chain
		2.1.5 ECR and the Inventory Management in the Supply Chain
		2.1.6 ECR as a Supply Chain Strategy
	2.2 Framework of a Global ECR Scorecard
	2.3 Prerequisite Initiatives for Participation in ECR
	2.4 Mechanics of ECR
	2.5 Special Application of ECR in Product Category Management
	2.6 Universal Product Code (UPC)
		2.6.1 Features of UPC Barcode
	2.7 Overview of GDSN
		2.7.1 Product Information Sharing through GDSN and Impact on ECR
	2.8 ECR in India
		2.8.1 An Example of ECR Initiative in India
		2.8.2 Workgroups in ECR India
		2.8.3 The Future of ECR in India
	2.9 ECR in World
	2.10 Conclusion
	References
Chapter 3 Delivering Superior Customer Experience through New-Age Technologies
	3.1 Introduction
	3.2 Customer Experience (CX)
	3.3 Augmented Reality (AR)
		3.3.1 Impact of AR on CX
		3.3.2 Industry Examples of Augmented Reality Enhancing CX
	3.4 Artificial Intelligence (AI)
		3.4.1 AI in the Domain of CX
		3.4.2 Industry Examples
		3.4.3 Issues with AI
	3.5 Chatbots
		3.5.1 How Chatbots Deliver a Superior CX
		3.5.2 Issues with Chatbots
	3.6 Conclusion
	References
Chapter 4 Use of Artificial Intelligence-Enabled Features in the Retail Sector: A Perceptual Study of Customers
	4.1 Introduction
	4.2 Artificial Intelligence
		4.2.1 Different Stages of AI
		4.2.2 Different Components of AI
	4.3 Machine Learning
		4.3.1 The Working Process of Machine Learning Model
		4.3.2 Machine Learning Methods
	4.4 Deep Learning
	4.5 Emerging Artificial Intelligence Technologies
		4.5.1 Explainable AI
		4.5.2 Leading AI Companies
	4.6 AI and Retail
		4.6.1 Digital Giants and AI
	4.7 AI Tools
		4.7.1 Chatbots
		4.7.2 Personalized Marketing
		4.7.3 Marketing and Content Automation
		4.7.4 Voice Assistance
		4.7.5 Augmented Reality
		4.7.6 Visual Search
	4.8 Methodology
		4.8.1 Data Analysis and Results
	4.9 Conclusion and Future Trends
	References
Chapter 5 Effective Integration of Lean Operations and Industry 4.0: A Conceptual Overview
	5.1 Introduction
	5.2 Overview of Lean Principles and Industry 4.0 Tools
	5.3 Purpose: How Does I 4.0 Enhance the Ways Organizations Create Value for Long-Term Competitive Advantage? TW #1; L 5P #1
	5.4 Processes: How Does  I4.0 Help Design and Improve Right Processes?
		5.4.1 Just-In-Time (JIT ) Pillar. TW #2–4; L5P #2–3
		5.4.2 Jidoka Pillar. TW #2–4; L5P #2–3
		5.4.3 Standardization and Visual Control as the Foundation. TW #6–7; L5P #2–4
		5.4.4 Importance of Technology and Its Integration with People and Processes (L5P #8)
	5.5 People: How Does I4.0 Help Empower and Develop Employees? TW #9–11
	5.6 Problem-Solving: How Does I4.0 Enhance Problem-Solving, Continuous Improvement, and Organization Learning?
	5.7 Conclusion
	References
Chapter 6 Opportunities and Risks: Use of Autonomous Vehicles in Logistics
	6.1 Introduction
	6.2 Introduction to AVs: Strategies and Materials
		6.2.1 Historical Development
		6.2.2 Technology
		6.2.3 Legislation and Liability
		6.2.4 Values
		6.2.5 Human Engineering
	6.3 Autonomous Vehicle in Logistics: Utilization and Outcome
		6.3.1 AVs in Indoor Logistics: Applications
		6.3.2 AVs in Outdoor Logistics: Applications
		6.3.3 Autonomous Vehicles in Long-Haul Freight Transport
		6.3.4 Autonomous Vehicles in Highway Trucking
		6.3.5 Contemplation on Logistics Operation
	6.4 Autonomous Vehicles in Logistics: Risks
	6.5 Conclusion
	References
Chapter 7 Assessment of Challenges for Implementation of Industrial Internet of Things in Industry 4.0
	7.1 Introduction
	7.2 Review of Existing Literature
	7.3 Research Methodology
	7.4 Numerical Illustration
		7.4.1 Research Design
		7.4.2 Application of the Grey DEMATEL Approach
		7.4.3 Result and Analysis
	7.5 Conclusion and Future Scope
	References
Chapter 8 IoT Security Issues and Solutions with Blockchain
	8.1 Introduction
	8.2 Component of IoT
	8.3 Issues with IoT
	8.4 IoT Architecture and Security Challenges
		8.4.1 IoT Reference Model
		8.4.2 IoT Security Goal
		8.4.3 IoT Security Issue Categorization
		8.4.4 IoT Communication Model
		8.4.5 IoT Vulnerabilities
		8.4.6 Why IoT Needs Blockchain
	8.5 How Blockchain Works?
	8.6 Benefits of Blockchain-Based IoT Network
	8.7 Different Configuration of IoT and Blockchain Integration
	8.8 Open Challenges to Develop Blockchain-Based IoT Network
	8.9 Conclusion
	References
Chapter 9 Stabilization of Imbalance between the Naira and the Dollar Using Game Theory and Machine Learning Techniques
	9.1 Introduction
		9.1.1 General Understanding
			9.1.1.1 Foreign Exchange
			9.1.1.2 Game Theory
			9.1.1.3 Machine Learning
	9.2 Literature Review
	9.3 Data Understanding/Problem Statement
	9.4 Conceptual Framework
	9.5 Conceptual Model
	9.6 Conclusion
	References
Chapter 10 The Emerging Role of Big Data in Financial Services
	10.1 Introduction
	10.2 Literature Review
	10.3 Research Methodology
	10.4 What Is Big Data?
		10.4.1 Evolution of Big Data
		10.4.2 Big Data Lifecycle
	10.5 Reasons for the Proliferation of Big Data
	10.6 Big Data Application: Need in Financial Industry
	10.7 Big Data: Applications in Financial Services Sector
	10.8 Application of Big Data for Crises Redressal in Banking
	10.9 Big Data Analytics Application – Used Case from Indian Banking
		10.9.1 HDFC Bank – Analytics to Provide a Comprehensive Understanding of Customers
		10.9.2 ICICI Bank – Use of BI and Analytics to Reduce Credit Losses
		10.9.3 Axis Bank – Analytics for Customer Intelligence and Risk Management
		10.9.4 State Bank of India – Using Data Analytics
		10.9.5 ING Vysya Bank – Need for BI Implementation
	10.10 Big Data Constraints in Financial Services Sectors
	10.11 Conclusions
	10.12 Scope of Future Research
	References
	Web Reference
Chapter 11 Digital Payments in India: Impact of Emerging Technologies
	11.1 Introduction
	11.2 Digital Payments in India
	11.3 Inhibitors of Digital Payments
		11.3.1 Social Risk
		11.3.2 Psychological Risk
		11.3.3 Time Risk
		11.3.4 Data Security Risk
		11.3.5 Overspending Risk
	11.4 Facilitators of Digital Payments
		11.4.1 Easy and Convenient to Use
		11.4.2 Enabled Transaction from Anywhere
		11.4.3 Easy Tracking of Expenses
		11.4.4 Less Risk of Loss and Theft
	11.5 Role of Emerging Technologies in Digital Payments
		11.5.1 Blockchain and Digital Payments
		11.5.2 Big Data Analytics and Digital Payments
		11.5.3 Social Media Analytics and Digital Payments
		11.5.4 Cloud Computing and Digital Payments
	11.6 Economic Impact of Digital Payments in India
	11.7 Discussion and Conclusion
	11.8 Future Research Direction
	References
Chapter 12 Cryptocurrency: Perspectives, Applications, and Issues
	12.1 Introduction
	12.2 Background
	12.3 Research Objective
	12.4 Perspectives
		12.4.1 Neoclassical Finance and Economics
		12.4.2 Behavioral Economics
		12.4.3 Socioeconomic Perspectives
	12.5 Applications of Cryptocurrencies
		12.5.1 Travel
		12.5.2 Education
		12.5.3 Banking and Financial Services
		12.5.4 Wealth Management
		12.5.5 Wide Usage and Easy Accessibility
	12.6 Legal Issues Associated with Cryptocurrency
	12.7 Environmental Issues Associated with Cryptocurrency
	12.8 Scams
	12.9 Implications of Cryptocurrency
	12.10 Scope of Growth Opportunities for Cryptocurrency
	12.11 Conclusion
	References
Chapter 13 Models for Predicting Student Enrolment for Delhi-Based Schools
	13.1 Introduction
	13.2 Literature Review
		13.2.1 Research Gap
	13.3 Research Objectives
	13.4 Research Methodology
		13.4.1 Research Design
		13.4.2 Data Collection
		13.4.3 Sample Technique
		13.4.4 Sample Size
		13.4.5 Data Analysis
	13.5 Results
	13.6 Findings
	13.7 Conclusion and Implications
	13.8 Limitations of the Study
	References
Chapter 14 Analyzing the Functionality and Efficient Operability of the Youth During COVID 19
	14.1 Introduction
	14.2 Literature Review
	14.3 Technique
	14.4 Key Terminology
	14.5 Results and Findings
	14.6 Conclusions
	14.7 Future Scope
	References
Chapter 15 AI in Talent Management for Business Excellence
	15.1 Introduction
	15.2 Proposed Model
	15.3 Application Framework
	15.4 Application Workflow
	15.5 Key Challenges
	15.6 Methodology/Process Followed
	15.7 Critical Success Factor
	15.8 Quantified Benefits to Business
	References
Index