Doctor of Philosophy in Logistics Management
(International Program)
Admission announcement: admission-announcement-LM-PhD-2021
Application form: phD-application-form
Program specification: LM-PhD-program-specification-2021-08-18
Program Structure
- Remedial courses 6-12 credits (non-credit)
- Core courses 12 credits
- Elective courses 6 credits (minimum)
- Dissertation 42 credits
- Total not less than 60 credits
Courses
Remedial Courses
- English courses
- Advanced Reading and Writing in English for Graduate Studies
- Advanced Integrated English Language Skill Development
- Choose at least 2 courses upon the consideration of the lecturer responsible for the curriculum
- Data Analytics and Decision Models
- Inventory Management Analytics
- Smart Logistics
- Transportation and Network Analytics
- Supply Chain Analytics and Optimization
Core Courses
- Stochastics Process in Logistics and Supply Chain Management
- Logistics Network Optimization
- Research Methodology and Statistics for Logistics Management
- Doctoral Seminar
Elective Courses
Choose at least 2 courses
- Supply Chain Risk Management
- Advanced Project Management
- Advanced Logistics Simulation
- Advanced Spatio-Temporal Data Analysis
- Advanced Revenue Management
- Managing Big Data in Logistics Management
- Applied Machine Learning in Logistics Management
- Qualitative Research
- Multi-Criteria Decision Making and Analytics
- Advanced Production System Analytics
- Sustainable Logistics and Supply Chain Management
Highlights of the program can be found in this slide presentation slide-PHDLM-NIDA
Qualifications of Applicants
- Must be graduated with master degree in Logistics Management, Supply Chain Management, Business and Administration, Economics, Industrial Engineering, Applied Statistics, Applied Mathematics, Engineering Management, System Engineering, Business Analytics and Data Science, or in the related fields, and graduated from the institutes both domestic and abroad, which have been accredited by the Council of National Institute of Development Administration’s approval.
- Have good academic records and good command of English, both written and verbal.
Tuition & Fees
The entire program (60 credits excluding the remedial courses) costs 45X,XXX THB.
Class Time & Place
Classes are on campus (NIDA, 148 Serithai Road, Bangkapi, Bangkok) outside the official hours (“นอกเวลาราชการ”).
Course Description
LM6901 Inventory Management Analytics
This course focuses on inventory classification, deterministic inventory models with constant and time-varying demands. Stochastic inventory models. Single-period, and finite-horizon models. Stochastic lead-time models. Serial systems. Multi-echelon inventory systems. Risk pooling analysis. Reserved area and fast-pick area (FPA) in warehouse design. Computer packages and programming to analyze inventory problems and find solutions. Case studies.
LM6902 Smart Logistics
The topics of this course are as follows: logistics automation. Automation software and components. Artificial intelligence, and machine learning in logistic systems. Smart contracts and blockchain in supply chain management. Big data analytics, predictive analytics, and demand sensing.
LM6903 Transportation and Network Analytics
The topics of this course are as follows: transportation management, transportation modes and transportation cost analysis, mathematical models for transportation network including transportation problem, transshipment problem, vehicle routing problem, facility location model. The method for solving the problem using a computer program and programming. Computer packages and programming to analyze transportation problems and find solutions and case studies are included in this subject.
LM6904 Supply Chain Analytics
The topics of this course are as follows: supply chain and supply chain management. Strategic fit to business. Demand forecast. Aggregate planning. Supply chain uncertainty and its impact to business costs. Supply chain cost reduction under uncertainty. Push- and pull-supply chain management. Models for pricing and contracts. Bullwhip effect. Supplier relationship management. Computer packages and programming to analyze supply chain problems and find solutions. Case studies.
LM7950 Stochastics Process in Logistics and Supply Chain Management
The topics of this course are as follows: applied stochastic models. Discrete- and continuous-time stochastic processes. Poisson processes. Renewal processes. Markov chains and Markov decision processes. Probabilistic models for decision making in logistic and supply chain management. Stochastic inventory models, and queueing models.
LM7951 Logistics Network Optimization
The topics of this course are as follows: graph theory and connectivity analysis. Network efficiency and network science for both local and global scales in a network. Non-Linear Optimization. Traffic assignment methods. Dial Stoch. User Equilibrium and Stochastic User Equilibrium. Logistics network design, and multimodal network analysis. Additional applications in real logistics networks.
LM7952 Research Methodology and Statistics for Logistics Management
The topics of this course are as follows: empirical research methods for logistics management. Controlled experiments. Surveys, archival analysis. Ethnographic action research. Research question formulation. Data analysis with qualitative and quantitative methods. Research design and statistical analyses. Report and publish work for academic journals. Research on human subjects. Research ethics. Case studies
LM7901 Supply Chain Risk Management
The topics of this course are as follows: critical aspects of risk. Trends of risks affecting the supply chain. The goal of risk management in the supply chain. Approaches to risk management and Identify risks. Risk analysis. Response to risk. Network view of risk. Creating resilient supply chains. Business continuity management.
LM7902 Advanced Project Management
The topics of this course are as follows: definition of a project. Project life cycle. Organizational structures. Project selection. Evaluation approaches. Project communications. Project planning and cost estimating. Work breakdown structure. Scheduling techniques e.g., PERT and CPM. Quality and risk management.
LM7903 Advanced Logistics Simulation
The topics of this course are as follows: static simulation. Discrete event simulation. Applications of simulation in logistics. Business and production problems. Data analysis for simulation outputs. Verification and validation of situation models. Design of experiment for simulation. Simulation models by using a computer program. Programming API in the simulation tool.
LM7904 Advanced Spatio-Temporal Data Analysis
The topics of this course are as follows: introduction to spatio-temporal data analysis. Geographical information system and business analytics. Sampling spatial data. Point pattern analysis. Spatially continuous data analysis. Spatial regression. Map and spatio-temporal data visualization. Computer packages and programming to analyze spatio-temporal problems. Managing spatio-temporal big data.
LM7905 Advanced Revenue Management
The topics of this course are as follows: quantitative models for revenue management (RM). Single-resource and network capacity controls. Overbooking models. Price optimization. RM practices in airlines, hotels, automobile rental companies and other related service industries. Stochastic revenue management models. Case studies.
LM7906 Managing Big Data in Logistics Management
The topics of this course are as follows: overview applications of Big Data. Fundamental platforms such as Hadoop, Spark, and other tools such as IBM System G for Linked Big Data. Data storage methods and how to upload, distribute and process Big Data. HDFS, HBase and KV stores. Document database and graph database. Handling analytics algorithms on different platforms. Visualization issues on Big Data analytics.
LM7907 Applied Machine Learning in Logistics Management
The topics of this course are as follows: machine learning classification. Data and data Preprocessing. Data exploration. Decision trees, Bayes classifiers. K-nearest neighbor classifiers. Neural networks. Support vector machines. Logistic regression. Dimension reduction. Clustering algorithms. Association rule analysis. Business analytics and data science applications.
LM7908 Qualitative Research
The topics of this course are as follows: philosophical foundations and applications of qualitative research methods interview. Observations, video and tape recording and fieldwork. Qualitative data analysis, including critical incident technique, phenomenology, grounded theory, discourse analysis, and narratology. Case study. Participative action research. Ethnography. Feminism. Mixed methods. Qualitative research writing and presentation. Ethics for qualitative research.
LM7909 Multi-Criteria Decision Making and Analytics
The topics of this course are as follows: introduction to multi-criteria decision making (MCDM). MCDM methods. MCDM under uncertainty. Quantification of qualitative data for MCDM problems. Fuzzy MCDM. MCDM practices in logistics and supply chain management problems and other related industries.
LM7910 Advanced Production System Analytics
The topics of this course are as follows: the use of operations and events data and technologies in the manufacturing industry to optimize supply chains. Production system fundamental. Production planning. Operation scheduling for a single machine. Job shop and flow shop scheduling. Advance scheduling problems. Statistical control fundamental. Advance statistical analysis for production control. Reliability analysis for a production system.
LM7911 Logistics and Supply Chain Management
The topics of this course are as follows: the environmental issues in the logistics and supply chain. Measure and minimize the ecological impact of logistics activities. Pollution and emission from freight transportation. Sustainable balance of economic and environmental efficiency. Use of advanced technology and equipment to minimize environmental damage during operations.