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

✍ Scribed by Shivani Bali (editor), Sugandha Aggarwal (editor), Sunil Sharma (editor)

• Publisher: CRC Press
• Year: 2021
• Tongue: English
• Leaves: 289
• Edition: 1
• Category: Library

✦ Synopsis

This book captures deploying Industry 4.0 technologies for business excellence and moving towards society 5.0. The book addresses applications of Industry 4.0 in the areas of Marketing, Operations, Supply Chain, Finance, and HR to achieve business excellence.

Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications focuses on the use of AI in management across different sectors. It explores the benefits through a human-centered approach to resolving social problems by integrating cyberspace and physical space. It discusses the framework for moving towards society 5.0 and keeping a balance between economic gains and social gains. This book brings together researchers, developers, practitioners, and users interested in exploring new ideas, techniques, tools and exchanging their experiences to provide the most recent information on Industry 4.0 applications in the field of business excellence.

Graduate or postgraduate students, professionals, and researchers in the fields of operations management, manufacturing, healthcare, supply chain, marketing, finance, and HR will find this book full of new ideas, techniques, and tools related to Industry 4.0.

✦ Table of Contents

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