Encyclopedia in Operations Management
- 1st Edition - May 1, 2026
- Latest edition
- Editor: Tsan-Ming Jason Choi
- Language: English
Encyclopedia of Operations Management is an indispensable reference guide that offers a comprehensive and authoritative exploration of the field of operations management. Design… Read more
Encyclopedia of Operations Management is an indispensable reference guide that offers a comprehensive and authoritative exploration of the field of operations management. Designed to cater to both students and professionals, this encyclopedia provides a wide range of knowledge, insights, and best practices for optimizing operations within diverse industries and organizations. The encyclopedia incorporates numerous case studies and examples drawn from a diverse range of industries, including manufacturing, services, healthcare, logistics, and e-commerce. These real-world illustrations enable readers to grasp the practical implications of various operations management concepts and techniques. Recognizing the evolving nature of operations management, this encyclopedia incorporates the latest trends, emerging technologies, and industry practices. It addresses topics such as Industry 4.0, digital transformation, sustainability, agile methodologies, and data analytics, ensuring that readers are equipped with up-to-date knowledge.
- Extensive Coverage: This encyclopedia covers a broad spectrum of topics related to operations management, encompassing the entire lifecycle of operations, from planning and design to execution, control, and improvement. It includes both traditional and contemporary aspects of the field, ensuring that readers gain a holistic understanding of operations management in the modern business landscape.
- Expert Contributions: The encyclopedia features contributions from leading experts, practitioners, and academics in the field of operations management. Each entry is meticulously researched and written by subject matter specialists, ensuring accuracy, depth, and relevance.
- Thematic Structure: The content is organized thematically into clearly defined sections, facilitating easy navigation and enabling readers to locate specific topics of interest quickly. The sections cover areas such as operations strategy, supply chain management, process design, quality management, capacity planning, inventory management, lean production, Six Sigma, and more.
Undergraduate students seeking foundational knowledge, to a postgraduate scholar conducting advanced research, to a seasoned industry practitioner seeking to stay informed of the latest trends and developments within operations management.
1. Operations and Productivity
1.1 What is Operations Management (OM)?
1.2 Role of OM in an Organization / Importance of OM in Running a Firm
1.3 Role of Operations Management in Organizations
1.4 What Does It Mean by Supply Chain OM
1.5 Operations for Goods and Services
1.6 A Process View of OM
1.7 Heritage of OM
1.8 The Productivity Challenge
1.9 Current Challenges in OM
1.10 Ethics, Social Responsibility, and Sustainability in OM
2. Data Analytics in Operations
2.1 Data-Driven Tools for Operations Management
2.2 AI in Operations Management
2.3 Using Data-Driven Tools to Study Service Operations
2.3.1 Healthcare Operations
2.3.2 Logistics
2.4 Big Data Analytics
3. Project Management
3.1 Definition of Projects and Project Management (Definition and Steps)
3.2 Project Planning
3.2.1 The Project Manager
3.2.2 Work Breakdown Structure
3.3 Project Scheduling
3.3.1 Gantt Chart
3.4 Project Controlling
3.5 Project Management Techniques: PERT and CPM
3.5.1 The Framework of PERT and CPM
3.5.2 Network Diagrams and Approaches
3.5.3 Activity-on-Node Example
3.5.4 Activity-on-Arrow Example
3.6 Determining the Project Schedule
3.7 Variability in Activity Times
3.8 Cost–Time Trade-Offs and Project Crashing, Cost to Cash, Minimizing Costs
3.9 A Critique of PERT and CPM
3.10 Understanding the Project Environment
3.10.1 The Role of Stakeholders in the Project Environment
3.10.2 Understanding Stakeholders and Their Motivations
3.10.3 Prioritizing and Managing Stakeholders
3.11 Assessing and Analyzing Risks
3.11.1 Risk-Management Plans
3.11.2 Statistical Analysis
3.11.3 Analyzing Probabilities
3.11.4 Near-Critical Paths
3.11.5 Risks Caused by Changing
4. Forecasting and Capacity Management
4.1 Definition and Importance of Forecasting
4.2 Key Decisions in Making Forecasts
4.3 Forecasting Approaches – Qualitative Methods
4.4 Forecasting Approaches – Quantitative Methods
4.5 Associative Forecasting Methods: Regression and Correlation Analysis
4.6 What Is Capacity Management
4.7 Managing Demand
4.8 Capacity Planning (Long-Term)
4.9 Constraint Management
4.9.1 Definition of the Theory of Constraints
4.9.2 Bottleneck Management
4.10 Monitoring and Controlling Forecasts
4.10.1 Adaptive Smoothing
4.10.2 Focus Forecasting
4.11 Forecasting in the Service Sector
4.12 Forecast Error
4.12.1 Cumulative Sum of Forecast Errors
4.12.2 Dispersion of Forecast Errors
4.12.3 Mean Absolute Percent Error
4.13 Computer-Supported Judgment Methods
4.14 Big Data and the Forecasting Process
4.14.1 Big Data
4.14.2 A Typical Forecasting Process
4.15 How Is Capacity Measured?
4.15.1 The Effect of Activity Mix on Capacity Measurement
4.15.2 The Effect of Time-Frame on Capacity Measurement
4.15.3 The Effect of Specification on Capacity Measurement
4.15.4 Understanding Changes in Capacity
4.16 What Is Capacity?
4.16.1 Design and Effective Capacity
4.16.2 Capacity and Strategy
4.16.3 Capacity Considerations
4.17 Managing Demand
4.18 Service-Sector Demand and Capacity Management
4.19 Understanding the Consequences of Capacity Management Decisions
4.19.1 Using Cumulative Representations
4.19.2 Using Queuing Principles
4.19.3 Using a Longitudinal Perspective
4.20 Applying the Theory of Constraints to Product Mix Decisions
4.21 Managing Constraints in Line Processes
4.22 Reducing Risk with Incremental Changes
5. Design of Goods and Services
5.1 Stages of Service and Product Design
5.1.1 Concept Generation
5.1.2 Concept Screening
5.1.3 Preliminary Design
5.1.4 Design Evaluation and Improvement
5.1.5 Prototyping and Final Design
5.2 The Innovation Process
5.2.1 Capacity Requirements
5.2.2 Outsourcing Options
5.2.3 Technology Needs
5.2.4 Organizational Structure
5.2.5 Process Compression
5.3 Supporting Technologies for Innovation
5.3.1 Computer-Aided Design
5.3.2 Virtual Reality
5.3.3 AI
5.3.4 Knowledge Management
5.4 Building the Product Development System
5.5 Techniques for Developing Products and Services
5.6 New Service or Product Development Process
5.7 Design, Analysis, Development, and Full Launch
6. Managing Quality
6.1 Defining Quality
6.2 Total Quality Management (TQM)
6.3 Six Sigma
6.4 Tools of TQM
6.5 The Role of Inspection
6.6 TQM in Services
6.7 Costs of Quality
6.7.1 Prevention Costs
6.7.2 Appraisal Costs
6.7.3 Internal Failure Costs
6.7.4 External Failure Costs
6.7.5 Ethical Failure Costs
6.8 Steps Towards Conformance to Specification
6.8.1 Step 1 – Define the Quality Characteristics
6.8.2 Step 2 – Decide How to Measure Each Characteristic
6.8.3 Step 3 – Set Quality Standards
6.8.4 Step 4 – Control Quality Against Those Standards
6.8.5 Steps 5 and 6 – Find and Correct Causes of Poor Quality and Continue Improvements
6.9 Service Quality Models
6.10 Quality Theories: Deming’s 14 Points, etc.
7. Process Strategies
7.1 Four Process Strategies
7.1.1 Process Focus
7.1.2 Repetitive Focus
7.1.3 Product Focus
7.1.4 Mass Customization Focus
7.1.5 Process Comparison
7.2 Process Analysis and Design
7.2.1 Flowchart
7.2.2 Time-Function Mapping
7.2.3 Process Charts
7.2.4 Value-Stream Mapping
7.2.5 Service Blueprinting
7.3 Production Technology
7.3.1 Machine Technology
7.3.2 Automatic Identification Systems (AISs) and RFID
7.3.3 Process Control
7.3.4 Vision Systems
7.3.5 Robots
7.3.6 Automated Storage and Retrieval Systems (ASRSs)
7.3.7 Automated Guided Vehicles (AGVs)
7.3.8 Flexible Manufacturing Systems (FMSs)
7.3.9 Computer-Integrated Manufacturing (CIM)
7.4 Process Redesign
7.4.1 What Is Process Design?
7.4.2 Relationship Between Process Design and Product/Service Design
7.4.3 Objectives of Process Design
7.4.3.1 Micro Process Objectives
7.4.3.2 Standardization of Processes
7.4.3.3 Environmentally Sensitive Process Design
7.5 Effects of Volume and Variety on Process Design
7.5.1 Process Types
7.5.1.1 Project Processes
7.5.1.2 Jobbing Processes
7.5.1.3 Batch Processes
7.5.1.4 Mass Processes
7.5.1.5 Continuous Processes
7.5.1.6 Professional Services
7.5.1.7 Service Shops
7.5.1.8 Mass Services
7.6 Understanding the Potential of New Process Technology
7.7 Evaluating New Process Technologies
7.8 Developing and Implementing New Process Technologies
7.9 Redesigning and Managing Process Improvements
7.9.1 Questioning and Brainstorming
7.9.2 Benchmarking
7.9.3 Implementing
8. Location Strategies
8.1 The Strategic Importance of Location
8.2 Factors Affecting Location Decisions
8.3 Methods of Evaluating Location Alternatives
8.3.1 The Factor-Rating Method
8.3.2 Locational Cost–Volume Analysis
8.3.3 Center-of-Gravity Method
8.3.4 Transportation Model
8.4 Geographic Information Systems (GIS)
8.4.1 Using a GIS
8.4.2 The GIS Method for Locating Multiple Facilities
8.5 Service Location Strategy
8.6 Break-Even Analysis for Location
8.7 Warehouse Strategy in Logistics Networks
8.7.1 Inventory Placement
8.7.2 Autonomous Warehouse Operations
8.8 A Systematic Location Selection Process
9. Layout Strategies
9.1 The Strategic Importance of Layout Decisions
9.2 How Layout and Facility Design Influence Performance
9.3 What Makes a Good Layout?
9.4 Types of Layout
9.5 Choosing the Right Layout for an Operation
9.6 Information and Analysis Needed for Layout and Facility Design
10. Human Resources, Job Design, and Work Measurement in OM
10.1 Importance of Human Resource Strategy in OM
10.2 Labor Planning
10.3 Organizing the Operations Function (Perspectives on Organizations)
10.4 Job Design
10.4.1 Labor Specialization
10.4.2 Job Expansion
10.4.3 Psychological Components of Job Design
10.4.4 Self-Directed Teams
10.4.5 Motivation and Incentive Systems
10.5 Ergonomics and the Work Environment
10.6 Methods Analysis
10.7 The Visual Workplace
10.8 Labor Standards
10.8.1 Historical Experience
10.8.2 Time Studies
10.8.3 Predetermined Time Standards
10.8.4 Work Sampling
10.9 Ethics
11. Supply Chain Management (SCM)
11.1 Importance of Supply Chain Management
11.2 What Is a Supply Chain?
11.3 Global Supply Chain Management
11.4 Supply Chain Risk
11.4.1 Supply Chain Disruptions
11.4.2 Risk Reduction Tactics
11.4.3 Secure Supply Chains
11.4.4 Reduced Bullwhip Effect
11.5 Managing the Integrated Supply Chain
11.5.1 Issues in an Integrated Supply Chain
11.5.2 Opportunities in an Integrated Supply Chain
11.5.3 Managing Supplier Relationships
11.5.4 Ethical Issues in Supply Chain Management
11.5.5 Sustainable Supply Chain Management
11.6 Supply Chain Decisions and Models
11.6.1 Determining the Number of Facilities
11.6.2 Sourcing Decisions
11.6.3 Inventory Management Decisions
11.6.4 Transportation Decisions
11.7 Supply Chain Performance Measurement
11.7.1 Balanced Scorecard Approach
11.7.2 Key Performance Indicators (KPIs)
12. Inventory Management
12.1 Importance of Inventory
12.2 Functions of Inventory
12.3 Types of Inventory
12.3.1 Raw Material Inventory
12.3.2 Work-in-Process Inventory
12.3.3 Finished Goods Inventory
12.3.4 Maintenance, Repair, and Operating (MRO) Inventory
12.4 Inventory Management Systems
12.4.1 Independent vs. Dependent Demand Inventory Systems
12.4.2 Periodic Review System
12.4.3 Continuous Review System
12.5 Inventory Control Techniques
12.5.1 ABC Analysis
12.5.2 Economic Order Quantity (EOQ)
12.5.3 Just-In-Time (JIT) Inventory
12.5.4 Safety Stock and Reorder Point
12.6 Inventory Accuracy and Cycle Counting
12.7 Inventory in Services
13. Aggregate Planning
13.1 Nature and Strategies of Aggregate Planning
13.1.1 Definition of Aggregate Planning
13.1.2 Strategies for Matching Demand and Capacity
13.2 Aggregate Planning Options
13.2.1 Chase Strategy
13.2.2 Level Strategy
13.2.3 Hybrid Strategy
13.3 Aggregate Planning Methods
13.3.1 Graphical and Charting Methods
13.3.2 Mathematical Approaches
13.3.3 Transportation Model
13.4 Aggregate Planning in Services
13.5 Yield Management
13.6 Aggregate Planning in Global Companies
14. Material Requirements Planning (MRP) and Enterprise Resource Planning (ERP)
14.1 Nature of Material Requirements Planning (MRP)
14.1.1 Dependent Demand
14.1.2 Structure of an MRP System
14.1.3 MRP Inputs (Bill of Materials, Master Production Schedule, Inventory Records)
14.2 MRP Outputs and Benefits
14.3 Limitations of MRP
14.4 Manufacturing Resource Planning (MRP II)
14.5 Enterprise Resource Planning (ERP)
14.5.1 ERP Modules and Capabilities
14.5.2 Benefits of ERP
14.5.3 Challenges in ERP Implementation
14.6 Supply Chain Management and ERP Integration
15. Short-Term Scheduling
15.1 Importance of Scheduling
15.2 Scheduling Issues
15.3 Scheduling Criteria
15.4 Scheduling in Services
15.5 Scheduling in Manufacturing
15.6 Gantt Charts
15.7 Scheduling Approaches
15.7.1 First Come, First Served (FCFS)
15.7.2 Shortest Processing Time (SPT)
15.7.3 Earliest Due Date (EDD)
15.7.4 Critical Ratio (CR)
15.7.5 Johnson’s Rule for Two-Machine Scheduling
15.8 Advanced Scheduling Techniques
15.8.1 Finite Capacity Scheduling
15.8.2 Theory of Constraints (TOC)
15.9 Sequencing Rules and Performance Measures
16. Just-In-Time (JIT) and Lean Operations
16.1 Just-In-Time Philosophy
16.2 Elements of JIT
16.2.1 Continuous Improvement (Kaizen)
16.2.2 Pull System
16.2.3 Small Lot Sizes
16.2.4 Setup Time Reduction
16.2.5 Quality at the Source
16.3 Lean Operations Principles
16.3.1 Waste Elimination (Muda)
16.3.2 Value Stream Mapping
16.3.3 5S Workplace Organization
16.3.4 Cellular Layouts
16.4 JIT Partnerships
16.5 JIT Scheduling
16.6 Benefits of JIT and Lean Systems
16.7 Challenges in Implementing JIT
17. Maintenance and Reliability
17.1 Importance of Maintenance
17.2 Types of Maintenance
17.2.1 Preventive Maintenance
17.2.2 Predictive Maintenance
17.2.3 Corrective Maintenance
17.3 Total Productive Maintenance (TPM)
17.4 Reliability Concepts
17.4.1 Definition of Reliability
17.4.2 Reliability of Systems in Series and Parallel
17.4.3 Reliability Improvement
17.5 Maintenance Metrics and Performance Measurement
17.6 Computerized Maintenance Management Systems (CMMS)
18. Project Management
18.1 Definition and Importance of Project Management
18.2 Project Life Cycle
18.3 Project Planning
18.3.1 Work Breakdown Structure (WBS)
18.3.2 Gantt Charts
18.3.3 Network Diagrams (PERT and CPM)
18.4 Project Scheduling
18.4.1 Critical Path Method (CPM)
18.4.2 Program Evaluation and Review Technique (PERT)
18.5 Project Cost Management
18.5.1 Budgeting and Cost Estimation
18.5.2 Earned Value Management (EVM)
18.6 Project Risk Management
18.7 Project Management Software Tools
18.8 Role of the Project Manager
19. Sustainable Operations Management
19.1 Definition and Importance of Sustainability
19.2 Triple Bottom Line Approach
19.3 Sustainable Product Design
19.4 Green Supply Chain Management
19.5 Life Cycle Assessment (LCA)
19.6 Reverse Logistics
19.7 Carbon Footprint Reduction Strategies
19.8 Corporate Social Responsibility (CSR) in Operations
19.9 Sustainability Reporting and Metrics
20. Global Operations and Supply Chain
20.1 Nature of Global Operations
20.2 Global Supply Chain Strategies
20.2.1 Outsourcing and Offshoring
20.2.2 Nearshoring and Reshoring
20.2.3 Global Sourcing
20.3 Challenges in Global Operations
20.3.1 Cultural Differences
20.3.2 Political and Economic Risks
20.3.3 Currency Exchange Rate Issues
20.4 Managing Global Risks
20.5 Global Logistics and Distribution
20.6 Technology in Global Operations
20.7 Case Studies in Global Operations
1.1 What is Operations Management (OM)?
1.2 Role of OM in an Organization / Importance of OM in Running a Firm
1.3 Role of Operations Management in Organizations
1.4 What Does It Mean by Supply Chain OM
1.5 Operations for Goods and Services
1.6 A Process View of OM
1.7 Heritage of OM
1.8 The Productivity Challenge
1.9 Current Challenges in OM
1.10 Ethics, Social Responsibility, and Sustainability in OM
2. Data Analytics in Operations
2.1 Data-Driven Tools for Operations Management
2.2 AI in Operations Management
2.3 Using Data-Driven Tools to Study Service Operations
2.3.1 Healthcare Operations
2.3.2 Logistics
2.4 Big Data Analytics
3. Project Management
3.1 Definition of Projects and Project Management (Definition and Steps)
3.2 Project Planning
3.2.1 The Project Manager
3.2.2 Work Breakdown Structure
3.3 Project Scheduling
3.3.1 Gantt Chart
3.4 Project Controlling
3.5 Project Management Techniques: PERT and CPM
3.5.1 The Framework of PERT and CPM
3.5.2 Network Diagrams and Approaches
3.5.3 Activity-on-Node Example
3.5.4 Activity-on-Arrow Example
3.6 Determining the Project Schedule
3.7 Variability in Activity Times
3.8 Cost–Time Trade-Offs and Project Crashing, Cost to Cash, Minimizing Costs
3.9 A Critique of PERT and CPM
3.10 Understanding the Project Environment
3.10.1 The Role of Stakeholders in the Project Environment
3.10.2 Understanding Stakeholders and Their Motivations
3.10.3 Prioritizing and Managing Stakeholders
3.11 Assessing and Analyzing Risks
3.11.1 Risk-Management Plans
3.11.2 Statistical Analysis
3.11.3 Analyzing Probabilities
3.11.4 Near-Critical Paths
3.11.5 Risks Caused by Changing
4. Forecasting and Capacity Management
4.1 Definition and Importance of Forecasting
4.2 Key Decisions in Making Forecasts
4.3 Forecasting Approaches – Qualitative Methods
4.4 Forecasting Approaches – Quantitative Methods
4.5 Associative Forecasting Methods: Regression and Correlation Analysis
4.6 What Is Capacity Management
4.7 Managing Demand
4.8 Capacity Planning (Long-Term)
4.9 Constraint Management
4.9.1 Definition of the Theory of Constraints
4.9.2 Bottleneck Management
4.10 Monitoring and Controlling Forecasts
4.10.1 Adaptive Smoothing
4.10.2 Focus Forecasting
4.11 Forecasting in the Service Sector
4.12 Forecast Error
4.12.1 Cumulative Sum of Forecast Errors
4.12.2 Dispersion of Forecast Errors
4.12.3 Mean Absolute Percent Error
4.13 Computer-Supported Judgment Methods
4.14 Big Data and the Forecasting Process
4.14.1 Big Data
4.14.2 A Typical Forecasting Process
4.15 How Is Capacity Measured?
4.15.1 The Effect of Activity Mix on Capacity Measurement
4.15.2 The Effect of Time-Frame on Capacity Measurement
4.15.3 The Effect of Specification on Capacity Measurement
4.15.4 Understanding Changes in Capacity
4.16 What Is Capacity?
4.16.1 Design and Effective Capacity
4.16.2 Capacity and Strategy
4.16.3 Capacity Considerations
4.17 Managing Demand
4.18 Service-Sector Demand and Capacity Management
4.19 Understanding the Consequences of Capacity Management Decisions
4.19.1 Using Cumulative Representations
4.19.2 Using Queuing Principles
4.19.3 Using a Longitudinal Perspective
4.20 Applying the Theory of Constraints to Product Mix Decisions
4.21 Managing Constraints in Line Processes
4.22 Reducing Risk with Incremental Changes
5. Design of Goods and Services
5.1 Stages of Service and Product Design
5.1.1 Concept Generation
5.1.2 Concept Screening
5.1.3 Preliminary Design
5.1.4 Design Evaluation and Improvement
5.1.5 Prototyping and Final Design
5.2 The Innovation Process
5.2.1 Capacity Requirements
5.2.2 Outsourcing Options
5.2.3 Technology Needs
5.2.4 Organizational Structure
5.2.5 Process Compression
5.3 Supporting Technologies for Innovation
5.3.1 Computer-Aided Design
5.3.2 Virtual Reality
5.3.3 AI
5.3.4 Knowledge Management
5.4 Building the Product Development System
5.5 Techniques for Developing Products and Services
5.6 New Service or Product Development Process
5.7 Design, Analysis, Development, and Full Launch
6. Managing Quality
6.1 Defining Quality
6.2 Total Quality Management (TQM)
6.3 Six Sigma
6.4 Tools of TQM
6.5 The Role of Inspection
6.6 TQM in Services
6.7 Costs of Quality
6.7.1 Prevention Costs
6.7.2 Appraisal Costs
6.7.3 Internal Failure Costs
6.7.4 External Failure Costs
6.7.5 Ethical Failure Costs
6.8 Steps Towards Conformance to Specification
6.8.1 Step 1 – Define the Quality Characteristics
6.8.2 Step 2 – Decide How to Measure Each Characteristic
6.8.3 Step 3 – Set Quality Standards
6.8.4 Step 4 – Control Quality Against Those Standards
6.8.5 Steps 5 and 6 – Find and Correct Causes of Poor Quality and Continue Improvements
6.9 Service Quality Models
6.10 Quality Theories: Deming’s 14 Points, etc.
7. Process Strategies
7.1 Four Process Strategies
7.1.1 Process Focus
7.1.2 Repetitive Focus
7.1.3 Product Focus
7.1.4 Mass Customization Focus
7.1.5 Process Comparison
7.2 Process Analysis and Design
7.2.1 Flowchart
7.2.2 Time-Function Mapping
7.2.3 Process Charts
7.2.4 Value-Stream Mapping
7.2.5 Service Blueprinting
7.3 Production Technology
7.3.1 Machine Technology
7.3.2 Automatic Identification Systems (AISs) and RFID
7.3.3 Process Control
7.3.4 Vision Systems
7.3.5 Robots
7.3.6 Automated Storage and Retrieval Systems (ASRSs)
7.3.7 Automated Guided Vehicles (AGVs)
7.3.8 Flexible Manufacturing Systems (FMSs)
7.3.9 Computer-Integrated Manufacturing (CIM)
7.4 Process Redesign
7.4.1 What Is Process Design?
7.4.2 Relationship Between Process Design and Product/Service Design
7.4.3 Objectives of Process Design
7.4.3.1 Micro Process Objectives
7.4.3.2 Standardization of Processes
7.4.3.3 Environmentally Sensitive Process Design
7.5 Effects of Volume and Variety on Process Design
7.5.1 Process Types
7.5.1.1 Project Processes
7.5.1.2 Jobbing Processes
7.5.1.3 Batch Processes
7.5.1.4 Mass Processes
7.5.1.5 Continuous Processes
7.5.1.6 Professional Services
7.5.1.7 Service Shops
7.5.1.8 Mass Services
7.6 Understanding the Potential of New Process Technology
7.7 Evaluating New Process Technologies
7.8 Developing and Implementing New Process Technologies
7.9 Redesigning and Managing Process Improvements
7.9.1 Questioning and Brainstorming
7.9.2 Benchmarking
7.9.3 Implementing
8. Location Strategies
8.1 The Strategic Importance of Location
8.2 Factors Affecting Location Decisions
8.3 Methods of Evaluating Location Alternatives
8.3.1 The Factor-Rating Method
8.3.2 Locational Cost–Volume Analysis
8.3.3 Center-of-Gravity Method
8.3.4 Transportation Model
8.4 Geographic Information Systems (GIS)
8.4.1 Using a GIS
8.4.2 The GIS Method for Locating Multiple Facilities
8.5 Service Location Strategy
8.6 Break-Even Analysis for Location
8.7 Warehouse Strategy in Logistics Networks
8.7.1 Inventory Placement
8.7.2 Autonomous Warehouse Operations
8.8 A Systematic Location Selection Process
9. Layout Strategies
9.1 The Strategic Importance of Layout Decisions
9.2 How Layout and Facility Design Influence Performance
9.3 What Makes a Good Layout?
9.4 Types of Layout
9.5 Choosing the Right Layout for an Operation
9.6 Information and Analysis Needed for Layout and Facility Design
10. Human Resources, Job Design, and Work Measurement in OM
10.1 Importance of Human Resource Strategy in OM
10.2 Labor Planning
10.3 Organizing the Operations Function (Perspectives on Organizations)
10.4 Job Design
10.4.1 Labor Specialization
10.4.2 Job Expansion
10.4.3 Psychological Components of Job Design
10.4.4 Self-Directed Teams
10.4.5 Motivation and Incentive Systems
10.5 Ergonomics and the Work Environment
10.6 Methods Analysis
10.7 The Visual Workplace
10.8 Labor Standards
10.8.1 Historical Experience
10.8.2 Time Studies
10.8.3 Predetermined Time Standards
10.8.4 Work Sampling
10.9 Ethics
11. Supply Chain Management (SCM)
11.1 Importance of Supply Chain Management
11.2 What Is a Supply Chain?
11.3 Global Supply Chain Management
11.4 Supply Chain Risk
11.4.1 Supply Chain Disruptions
11.4.2 Risk Reduction Tactics
11.4.3 Secure Supply Chains
11.4.4 Reduced Bullwhip Effect
11.5 Managing the Integrated Supply Chain
11.5.1 Issues in an Integrated Supply Chain
11.5.2 Opportunities in an Integrated Supply Chain
11.5.3 Managing Supplier Relationships
11.5.4 Ethical Issues in Supply Chain Management
11.5.5 Sustainable Supply Chain Management
11.6 Supply Chain Decisions and Models
11.6.1 Determining the Number of Facilities
11.6.2 Sourcing Decisions
11.6.3 Inventory Management Decisions
11.6.4 Transportation Decisions
11.7 Supply Chain Performance Measurement
11.7.1 Balanced Scorecard Approach
11.7.2 Key Performance Indicators (KPIs)
12. Inventory Management
12.1 Importance of Inventory
12.2 Functions of Inventory
12.3 Types of Inventory
12.3.1 Raw Material Inventory
12.3.2 Work-in-Process Inventory
12.3.3 Finished Goods Inventory
12.3.4 Maintenance, Repair, and Operating (MRO) Inventory
12.4 Inventory Management Systems
12.4.1 Independent vs. Dependent Demand Inventory Systems
12.4.2 Periodic Review System
12.4.3 Continuous Review System
12.5 Inventory Control Techniques
12.5.1 ABC Analysis
12.5.2 Economic Order Quantity (EOQ)
12.5.3 Just-In-Time (JIT) Inventory
12.5.4 Safety Stock and Reorder Point
12.6 Inventory Accuracy and Cycle Counting
12.7 Inventory in Services
13. Aggregate Planning
13.1 Nature and Strategies of Aggregate Planning
13.1.1 Definition of Aggregate Planning
13.1.2 Strategies for Matching Demand and Capacity
13.2 Aggregate Planning Options
13.2.1 Chase Strategy
13.2.2 Level Strategy
13.2.3 Hybrid Strategy
13.3 Aggregate Planning Methods
13.3.1 Graphical and Charting Methods
13.3.2 Mathematical Approaches
13.3.3 Transportation Model
13.4 Aggregate Planning in Services
13.5 Yield Management
13.6 Aggregate Planning in Global Companies
14. Material Requirements Planning (MRP) and Enterprise Resource Planning (ERP)
14.1 Nature of Material Requirements Planning (MRP)
14.1.1 Dependent Demand
14.1.2 Structure of an MRP System
14.1.3 MRP Inputs (Bill of Materials, Master Production Schedule, Inventory Records)
14.2 MRP Outputs and Benefits
14.3 Limitations of MRP
14.4 Manufacturing Resource Planning (MRP II)
14.5 Enterprise Resource Planning (ERP)
14.5.1 ERP Modules and Capabilities
14.5.2 Benefits of ERP
14.5.3 Challenges in ERP Implementation
14.6 Supply Chain Management and ERP Integration
15. Short-Term Scheduling
15.1 Importance of Scheduling
15.2 Scheduling Issues
15.3 Scheduling Criteria
15.4 Scheduling in Services
15.5 Scheduling in Manufacturing
15.6 Gantt Charts
15.7 Scheduling Approaches
15.7.1 First Come, First Served (FCFS)
15.7.2 Shortest Processing Time (SPT)
15.7.3 Earliest Due Date (EDD)
15.7.4 Critical Ratio (CR)
15.7.5 Johnson’s Rule for Two-Machine Scheduling
15.8 Advanced Scheduling Techniques
15.8.1 Finite Capacity Scheduling
15.8.2 Theory of Constraints (TOC)
15.9 Sequencing Rules and Performance Measures
16. Just-In-Time (JIT) and Lean Operations
16.1 Just-In-Time Philosophy
16.2 Elements of JIT
16.2.1 Continuous Improvement (Kaizen)
16.2.2 Pull System
16.2.3 Small Lot Sizes
16.2.4 Setup Time Reduction
16.2.5 Quality at the Source
16.3 Lean Operations Principles
16.3.1 Waste Elimination (Muda)
16.3.2 Value Stream Mapping
16.3.3 5S Workplace Organization
16.3.4 Cellular Layouts
16.4 JIT Partnerships
16.5 JIT Scheduling
16.6 Benefits of JIT and Lean Systems
16.7 Challenges in Implementing JIT
17. Maintenance and Reliability
17.1 Importance of Maintenance
17.2 Types of Maintenance
17.2.1 Preventive Maintenance
17.2.2 Predictive Maintenance
17.2.3 Corrective Maintenance
17.3 Total Productive Maintenance (TPM)
17.4 Reliability Concepts
17.4.1 Definition of Reliability
17.4.2 Reliability of Systems in Series and Parallel
17.4.3 Reliability Improvement
17.5 Maintenance Metrics and Performance Measurement
17.6 Computerized Maintenance Management Systems (CMMS)
18. Project Management
18.1 Definition and Importance of Project Management
18.2 Project Life Cycle
18.3 Project Planning
18.3.1 Work Breakdown Structure (WBS)
18.3.2 Gantt Charts
18.3.3 Network Diagrams (PERT and CPM)
18.4 Project Scheduling
18.4.1 Critical Path Method (CPM)
18.4.2 Program Evaluation and Review Technique (PERT)
18.5 Project Cost Management
18.5.1 Budgeting and Cost Estimation
18.5.2 Earned Value Management (EVM)
18.6 Project Risk Management
18.7 Project Management Software Tools
18.8 Role of the Project Manager
19. Sustainable Operations Management
19.1 Definition and Importance of Sustainability
19.2 Triple Bottom Line Approach
19.3 Sustainable Product Design
19.4 Green Supply Chain Management
19.5 Life Cycle Assessment (LCA)
19.6 Reverse Logistics
19.7 Carbon Footprint Reduction Strategies
19.8 Corporate Social Responsibility (CSR) in Operations
19.9 Sustainability Reporting and Metrics
20. Global Operations and Supply Chain
20.1 Nature of Global Operations
20.2 Global Supply Chain Strategies
20.2.1 Outsourcing and Offshoring
20.2.2 Nearshoring and Reshoring
20.2.3 Global Sourcing
20.3 Challenges in Global Operations
20.3.1 Cultural Differences
20.3.2 Political and Economic Risks
20.3.3 Currency Exchange Rate Issues
20.4 Managing Global Risks
20.5 Global Logistics and Distribution
20.6 Technology in Global Operations
20.7 Case Studies in Global Operations
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
TC
Tsan-Ming Jason Choi
Professor Tsan-Ming CHOI (Jason) is a management scientist, operations researcher and systems engineer. He is now Chair in Operations and Supply Chain Management, and Director of the Centre for Supply Chain Research at University of Liverpool Management School (ULMS). He has published extensively in leading journals in the fields of operations management, engineering management, logistics, and supply chain management. His recent research has been funded by many external funding bodies such as Research Grants Council (HK), University Grants Council (HK), M.O.E. (TW), and M.O.S.T. (TW). He is also serving the academic community as the Co-Editor-in-Chief of Transportation Research Part E: Logistics and Transportation Review, a Senior Editor of Production and Operations Management, and Decision Support Systems, a Department Editor of IEEE Transactions on Engineering Management, an Associate Editor of Decision Sciences, and IEEE TSMC-Systems, and an editorial board member of International Journal of Production Economics, International Journal of Production Research, and International Transactions in Operational Research. He is currently an external member of the engineering panel, Research Grants Council (HK) in which he helps handle reviews, give recommendations and monitor the progress of General Research Fund (GRF) proposals and funded projects. In two consecutive years under two different chief editors (2013 and 2014), he received the best associate editor awards of the IEEE SMC Society (USA). Over the past two decades, he served as an officer/exco member/secretary/treasurer of professional societies such as Production and Operations Management Society (HK), IEEE SMC Society (HK), and IEEE TEM Society (HK). Since 2020, he has been consistently ranked by p-ranking as a top 20 most productive researcher (in business and economics) in all related journal ranking lists in the world (including CABS). He is also listed as a Highly Cited Researcher by Clarivate (Web of Science) and a Top 2% scientist by Stanford University. Most recently, in February 2023, he received the JOM Ambassador Paper Award 2023 for his Journal of Operations Management paper on "green supply chain with quick response technology" published in 2020. Before joining ULMS, he taught at The Chinese University of Hong Kong (CUHK), The Hong Kong Polytechnic University (PolyU) and National Taiwan University (NTU), altogether for over two decades. In particular, he was honoured as a Yushan Fellow Professor at NTU, a President’s Award Winning Professor at PolyU, and a distinguished alumnus of CUHK's Faculty of Engineering.