Big Data and Blockchain for Service Operations Management

Preface
Acknowledgments
Contents
Characteristics and Trends in Big Data for Service Operations Management Research: A Blend of Descriptive Statistics and Bibliometric Analysis
	1 Introduction
	2 Methods and Materials
	3 Results
		3.1 Descriptive Summary Statistics of Published Material
		3.2 Bibliometric Analysis of Published Material
		3.3 Bibliometric Analysis of Journal Articles
	4 Conclusions
	References
Strategy Formulation and Service Operations in the Big Data Age: The Essentialness of Technology, People, and Ethics
	1 Introduction
	2 The Concept of Service Operations Management
	3 Traditional Misconceptions in Service Operations Management
	4 Current State-Of-The-Art in Service Operations Management
	5 The Concept of Big Data
	6 Types of Analytics
	7 The Big Data Pipeline
	8 Service Operations Management in the Big Data Age: Strategic Considerations
		8.1 Technology
		8.2 People
		8.3 Ethics
	9 The Future Ahead and Final Thoughts
	References
Modeling Big Data Enablers for Service Operations Management
	1 Introduction
	2 Research Methodology
	3 Identification of Enablers for Big Data in SOM
		3.1 Identifying the Initial Enablers
		3.2 Validity, Reliability and Normality Tests
		3.3 Sampling Adequacy Test
		3.4 Factor Analysis
	4 Modeling Enablers for Big Data in SOM Using ISM
		4.1 Identification of Enablers for Big Data in SOM
		4.2 Structural Self-Interaction Matrix (SSIM)
		4.3 Reachability Matrix from the SSIM
		4.4 Partitioning the Reachability Matrix in Different Levels
		4.5 Developing ISM Model
		4.6 MICMAC Analysis
	5 Modeling Enablers for Big Data in SOM Using Fuzzy-DEMATEL
		5.1 Fuzzy-DEMATEL Method
		5.2 Modeling Enablers
	6 Discussion
	7 Conclusions and Future Direction
	References
Data Architecture for Big Data Service Operations Management (The New Vision of Data Architecture for the Future Human Society)
	1 Introduction
		1.1 The Challenge and Requirements of Big Data Service Operations Management in a Complex and Synthetical Situation
		1.2 Traditional Methods Could not Meet the Requirements of Big Data Service Operations Management
		1.3 The New Data Architecture (DA) is Introduced to Solve the Problems
	2 The Re-understanding of Data
		2.1 Civilizations, Data and the Virtual Data World
		2.2 The Material Civilizations and the Data Civilizations
		2.3 Data Characteristics in Future Cyber Society
		2.4 Basic Characteristics and Classification of Data
		2.5 Data Assets and Values
		2.6 Data Method and Engineering
		2.7 Data Ownership and Confirmation
		2.8 Data Opening, Sharing and Security Grading Classification (Data Security Hierarchy Grading System and Application)
		2.9 Data Manageable Method and Technology System
		2.10 Requirements in Data Platform
	3 The Concept of Data Architecture (DA)
		3.1 The Description of DA
		3.2 Data Platform Supported by the DA
		3.3 The Preliminary Application of DA
		3.4 The Significance of the DA
		3.5 The Key Characters of DA
		3.6 Ten Steps Make the Data Architecture Work
	4 DA Application Cases Study
		4.1 The Tourism Platform Based on DA
		4.2 Government Information Resources Sharing and Application System Under DA
		4.3 Personal Privacy Protection Based on DA
		4.4 Data Trading Platform Based on DA
		4.5 Data Acquisition and Management System of IoT Based on DA
		4.6 Digital Copyright Works Protection and Trading Systems Based on DA
		4.7 Big Data Service to Civil People Based on DA
		4.8 Security Mobile Phone Based on DA
		4.9 The Future Civilization Vision Map
	5 Conclusion
	References
Big Data for Educational Service Management
	1 Introduction
	2 Big Data to Improve the Learning Experience
	3 Big Data to Improve Student Retention Rate
	4 Big Data to Improve Teaching and Research
	5 Big Data in Making Marketing Strategies for Higher Education
	6 Big Data and Library Services
	7 Big Data and Other Services in Education Systems
	8 Challenges in Implementing Big Data
	9 Conclusion and Future Directions
	References
A Novel Big Data Approach for Text Supported Service Operations Management
	1 Introduction
		1.1 Background
		1.2 Research Objectives
	2 Data Processing
		2.1 Traditional Preprocessing Approaches
		2.2 Traditional Methods in Big Data Environment
		2.3 Word Embeddings
		2.4 Convolutional Feature Extraction
	3 Supporting Decisions with Extracted Knowledge
		3.1 Supporting Decisions Examples for Operations Management
		3.2 Sentiment Analysis for Operations Management
		3.3 Text Similarities for Operations Management
	4 Overall System Architecture
		4.1 Traditional Methods
		4.2 Abstraction Using Big Data
		4.3 Universal Language-Independent Method
	5 Conclusion and Direction for Future Research
	References
Toward a Comprehensive Framework of Social Media Analytics
	1 Introduction
	2 Related Works
	3 Proposed Framework
		3.1 Input
		3.2 Process
		3.3 Output
	4 Actionable Insights
	5 Conclusion And Future Works
	References
Data Mining Approach in Repair and Service Systems of Electronic Products Under Warranty
	1 Introduction
		1.1 Data Mining Discovery Process
		1.2 Industry 4.0, Big Data and Service System
		1.3 Data Mining and Service Systems
		1.4 Electronics Service System and Data Mining Modeling
		1.5 Inventory Management for Servicing Electronic Products Under Warranty
	2 Material and Methods
	3 Results
		3.1 Data Understanding
		3.2 Data Preparation
		3.3 Data Analysis and Data Modelling
	4 Conclusion
	References
Integrative Applications of Blockchain and Contemporary Technologies from a Big Data Perspective
	1 Industry 4.0 and Big Data
	2 Blockchain
		2.1 Blockchain, IoT, Fog Computing, and AI
		2.2 Blockchain and 3D Printing (3DP)
		2.3 Blockchain and Swarm Robotic Systems
		2.4 Blockchain and Geotagging
	3 Managerial Implications and Policy Implications
	4 Conclusion
	References
Blockchain for Disaster Management
	1 Introduction
	2 Existing Blockchain Frameworks
		2.1 Current Frameworks for Blockchain in Humanitarian Aid and Disaster Management
		2.2 Gaps in Current Frameworks
	3 A Novel Blockchain Framework for Disaster Management
		3.1 Framework Overview
		3.2 Key Players
		3.3 Reaching Citizens and Providers
	4 Conclusions and Future Research Directions
		4.1 Concluding Discussion
		4.2 Limitations and Future Research Directions
	References
Blockchain Production Planning in Mass Personalized Environments
	1 Introduction
	2 Advanced Technologies: Concepts
		2.1 The Industry 4.0 Environment
		2.2 Additive Manufacturing
		2.3 Blockchain Technology
	3 Mass Customization/personalization Production Processes
		3.1 Production Planning and Control: ANSI/ISA 95
	4 Production Planning in Mass Personalized Environments
		4.1 The Setting
		4.2 Decision-Making Process
	5 The Blockchain Solution
		5.1 Properties of This Blockchain Solution
	6 Conclusions
	References
Frontiers of Blockchain for Railways
	1 Introduction
	2 Big Data and Blockchain
	3 Comprehending Blockchain Technology
	4 Recent Background Studies
	5 Application Context of Indian Railways
		5.1 Infrastructure
		5.2 Maintenance (Rolling Stock and Infrastructure)
		5.3 Customer Service
	6 Mapping the Railway Application to the Provenance Framework
	7 Conclusion
	References
Blockchain Interoperability Issues in Supply Chain: Exploration of Mass Adoption Procedures
	1 Introduction
	2 Scope of Blockchain Technology
		2.1 Blockchain Definition
		2.2 Blockchain Types
		2.3 Evolution of Blockchain Ecosystem
		2.4 Blockchain in Supply Chains
	3 Blockchain Interoperability
		3.1 Data Interoperability Standards
		3.2 Cross-Chain Interoperability
	4 Blockchain Mass Adoption
		4.1 Blockchain Use Cases in Supply Chains
		4.2 Discussion
	5 Conclusions
	References
Blockchain Technology Enablers in Physical Distribution and Logistics Management
	1 Introduction
	2 Literature Review
		2.1 Challenges in the LPD Sector
		2.2 Blockchain Technology
	3 Research Methodology
		3.1 AHP Methodology
		3.2 Results
	4 Discussion and Implications
		4.1 Managerial Implications
		4.2 Policy Implications
	5 Conclusion and Future Research
	References