Department of Management Studies

M.Tech

The two-year program includes eleven core courses in the first and second semester. In the second semester the candidate has to choose a specialization paper from thirteen different specializations. Students have to undergo industrial training for six weeks at the end of second semester. In the third and fourth semester the student has to work on a Dissertation for the partial fulfilment of the M.Tech program.

Course No. Course Name L T P C
MSC504/MSC505 Project Management (MSC519) 3 0 0 9
MSC507 Decision Modelling 3 0 0 9
MSC504/MSC505 Financial Accounting and Reporting /Cost and Management Accounting (Modular) 3 0 0 9
MSC512 Operations Management 3 0 0 9
MSC517 Productivity Management 3 0 0 9
MSC502/MSC503 Business Research Methods/ Business Statistics (Modular) 3 0 0 9
MSC518 Productivity Management (Practical) 0 0 3 3
MSC508 Business Analytics Lab. 0 0 2 2
Total 15 0 5 50
Course No. Course Name L T P C
DC xxx Project Management (MSC519) 3 0 0 9
DC xxx Quality Management (MSC520) 3 0 0 9
DE(Any Three) Service Operations Management (MSD512) 3 0 0 9
DE(Any Three) Machine Learning (MSD527) 3 0 0 9
DE(Any Three) Materials Management (MSD505) 3 0 0 9
DE(Any Three) Corporate Finance (MSD528) 3 0 0 9
DE(Any Three) Organizational Behaviour (MSD529) 0 0 3 3
DE(Any Three) Thesis Unit 1 (MSS506) 0 0 0/td> 9
OE xxx Open Elective 1 (MSO501) 3 0 0 9
OE xxx Open Elective 2 (MSO502) 3 0 0 9
OE xxx Software Lab (MSC515) 0 0 3 3
OE xxx Simulation Modelling & Analysis Lab (MSC517) 0 0 2 2
Total 15/12 0 5 50
Course No. Course Name L T P C
MSS506 Thesis Unit 2 0 0 0 9
MSS507 Thesis Unit 3 0 0 0 9
MSS508 Thesis Unit 4 0 0 0 9
MSS509 Thesis Unit 5 0 0 0 36
Course No. Course Name L T P C
DE xxx/ OE xxx(Any Two) Operations Analytics (MSD525) 3 0 0 9
DE xxx/ OE xxx(Any Two) Financial Econometrics (MSD514) 3 0 0 9
DE xxx/ OE xxx(Any Two) Supply Chain Management (MSD526) 3 0 0 9
MSS510 Thesis Unit 6 0 0 0 9
MSS511 Thesis Unit 7 3 0 0 9
Total 6 0 0 36
Course: Financial Accounting and Reporting (M)
Course Objectives: This course will enable students to understand the financial reporting system in a corporate framework. The students will be able to appreciate the usefulness of financial information for decision making and equipped with tools to analyze the financial performance of companies.
Learning Outcomes:
1. To understand the concept of Financial Accounting and Reporting in corporate sector.
2. To develop understanding about the financial statements and tools and techniques for analysis of financial statements.
3. To understand the process of financial decision-making using the financial statements.

New Course
Name Financial Accounting and Reporting (M)
Code
L T P 3-0-0
Status Departmental Core (Modular)
Course Content Unit I: Introduction to accounting, Accounting equation, Preparation of financial statements, Accounting Standards – US GAAP, Indian GAAP, IFRS, Accounting Cycle, Journal, Ledger, Trial Balance, Final Accounts [14L]
Unit II: Introduction to Accounting for Inventories, Accounting for Receivables, Fixed Assets, Depreciation and Amortization, Accounting for Liabilities, Accounting for Shareholder Equity [3L]
Unit III: Statement of Cash Flows, Analysis of Financial Statements, Comparative Statements, Common Size Statements, Ratio Analysis, Du-Pont Analysis [4L]
References Text Books:
1. Financial Accounting – A managerial Perspective by R. Naryanswamy, PHI
2. Financial Accounting for Management by Ramchandran & Kakani, Tata McGraw Hill
References:
1. Financial Accounting – Reporting & Analysis by Stice & Stice, Thomson, South Western
2. Case Studies - to be provided by the instructor
Course: Cost and Management Accounting (M)
Course Objectives: This course will help students appreciate the usefulness of cost and management accounting in management decision making. The students will be equipped with
tools to trace the cost and estimate the cost of the product or service as the case may be.
Learning Outcomes:
1. To understand the concept of Cost and Management Accounting in business decision making.
2. To develop understanding about the various elements of cost and their classification along with analysis of the various cost structures.
3. To understand the various tools and techniques used in cost management.

New Course
Name Cost and Management Accounting (M)
Code
L T P 3-0-0
Status Departmental Core (Modular)
Course Content Unit I: Introduction to Cost and Management Accounting, Cost Concepts-Absorption Costing [3L] Unit II: Marginal Costing and CVP Analysis [3L]
Unit III: Job Costing - system basic job costing for Manufacturing and Service Companies, Activity Based Costing - Concept, System & Limitations, Preparation
of Budget and Budgetary control [12L]
References Text Books:
1. Cost Accounting – A managerial Perspective by Horngren, Datar & Foster Pearson
2. Management Accounting - Text, Problems & Cases by Khan & Jain, Tata McGraw Hill
References:
1. Handbook of ICAI
2. Case Studies - to be provided by the instructor
Course: Decision Modelling
Course Objectives: This course shall expose the candidates to various quantitative models for decision making that aim at finding optimum or close to optimum results. Major emphasis
shall be on problem formulation and selection of appropriate software packages for solution and interpretation of results.
Learning Outcomes: (1) To understand how to formulate a mathematical model for a business or an industrial engineering problem.
(2) To get familiar with the various types of Operations Research Tools and techniques and their solution procedure.
(3) To get familiar with the some application software like MS Solver, LINDO, LINGO, etc. for solving OR problems.

New Course
Name Decision Modelling
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Linear Programming : Linear programming – Examples from industrial cases, formulation & definitions. Graphical Method and Simplex Algorithm – slack, surplus & artificial variables, computational details, big-M method, identification and resolution of special cases through simplex iterations. [9L]
Unit II: Transportation problems : TP - Examples, Definitions – decision variables, supply & demand constraints, formulation, Balanced & unbalanced situations, Solution methods – NWCR, minimum cost & VAM, test for optimality (MODI method), degeneracy & its resolution . [4L]
Unit III: Assignment problems : AP - Examples, Definitions – decision variables, constraints, formulation, Balanced & unbalanced situations, Solution method –
Hungarian, degeneracy & its resolution [4L]
Unit IV: Queuing Theory : Definitions – queue (waiting line), waiting costs, characteristics (arrival, queue, service discipline) of queuing system, queue types (channel vs. phase), Kendall’s notation, Little’s law, steady state behaviour, Poisson’s Process & queue, Models with examples – single and parallel server and its performance measures [5L]
Unit V: Simulation Methodology : Definition and steps of simulation; random number generator; Discrete Event System Simulation; Monte Carlo simulation; Application in Scheduling, Queuing systems, Inventory systems [5L]
Unit VI: Game Theory : Game theory to determine strategic behavior, Elements of cooperative and non-cooperative games, Two-person zero-sum game
[4L]
Unit VII: Decision Theory : Decision Making under risk and uncertainty, Pay-off matrix, Opportunity Cost Matrix; Decision trees [5L] Unit VIII: Multi Criteria Decision Making : AHP and Goal Programming [5L]
References Text Books:
1. Principles of OR with Application to Managerial Decisions: H.M.Wagner, Prentice Hall.
2. Introduction to Operations Research: F.S. Hiller and G.J. Lieberman, Addison Wesley.
References:
1. Operations Research: An Introduction- H.A. Taha, Macmillan, N.Y.
2. Operations Research and Management Science, Hand Book: Edited By A. Ravi Ravindran, CRC Press, Taylor & Francis Group.
Course: Operations Management
Course Objectives: This course introduces the students to the theory and practice of operations management as a functional area in the management of business enterprise. It also includes the methods, strategies and application of various mathematical tools in solving the production and operation related problems. The objective is to understand the strategic role of operations management in creating and enhancing a firm’s competitive advantages
Learning Outcomes: -At the end of the course the students will be able to: (a) acquire a working understanding of the roles/functions of operation management in the context of
business enterprise; (b) develop skills in solving operation management problems; (c) recognize, appreciate, and perform the job of a competent production or operation manager.

New Course
Name Operations Management
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction to Operations Management and basic concepts. Basic forecasting concepts and related models like Moving Average, Exponential Smoothing and
Regressions. Concepts of forecasting error. [ 8L]
Unit II: Concept of Aggregate Production Planning and related strategies like Chase, level and Mixed. Basic Concept of Materials requirement Planning and numerical
problems. [8L]
Unit III: Job Shop Scheduling and sequencing strategies, Johnson Rule and Extension of Johnson Rule. Introduction to inventory management. Basic inventory models and problems. Case studies [8L]
Unit IV : Facility Layout and various algorithms, Facility Location theories and mathematical models (Fixed charged location allocation problem, capacitated problems). [8 L]
Unit V: Concept of Operations Strategy and related examples, Product and Process Design, Concept of JIT. Case studies [8L]
References Text Books:
1. Operations Management, Jay Heizer, Barry Render, Jagadeesh Rajashekhar, Pearson Publication., 12th Edition, 2017
2. Operations Management, William J. Stevenson, McGrawhill , 11th Edition.
Reference books:
1. Production and Operations Management, R. Panneerselvam, PHI Publication. , 3rd Edition
2. Case studies to be provided by the instructor.
Course: Productivity Management
Course Objectives: Productivity improvement in an enterprise is a function and a result of management efficiency, synonymous with good management. It is a prime management
objective and responsibility to increase productivity. The objectives of this course is for students to acquire the fundamentals of productivity concepts, principles, tools, and techniques
Learning Outcomes: This course shall familiarize the student with various models of productivity in different situations. Students will be able to: calculate the basic work content, analyze the existing methods of working and develop an improved method, and calculate basic, allowed and standard time, of a specific job. The students will also be able to analyze
and calculate the level of risk in the job causing stress, fatigue and musculoskeletal disorders and design appropriate work systems.



New Course
Name Productivity Management
Code
L T P 3-0-0
Status Specialization Elective
Course Content Unit I: Introduction to Productivity Management : Concept of Productivity- Partial and Total Productivity, Models for Productivity measurement, Productivity
management cycle, Causes for poor productivity in Indian industry [6L]
Unit II: Work Study and Method Study : Steps for conducting method study, Charts and diagrams for conducting method study, Principles of motion economy, Threbligs [6L]
Unit III: Work Measurement techniques : Time Study, Work Measurement, Analytical estimation, etc. and their applications, Incentive Plans [6L] Unit IV: Introduction to Ergonomics : Significance, Manual work design, MSD, CTD, RSI, Common Causes, Signs, Symptoms, Cost [3L]
Unit V: Focus of Ergonomics : Administrative controls, Work practice controls, Design of workstations, Design of tools, Design of Work environment, Design of Cognitive work [18L]
References Text Books:
1. Productivity engineering and management: productivity measurement, evaluation, planning, and improvement in manufacturing and service organizations,
Sumanth, D. J. (1984). . McGraw-Hill College.
2. Niebel's methods, standards, and work design (Vol. 700), Freivalds, A. (2009). Boston, Mass.: Mcgraw-Hill higher education.
References:
1. Motion and time study: design and measurement of work, Ralph, M. B. (1980), John Wiley & Sons
Course: Business Research Methods (M)
Course Objectives: This course is specifically designed to meet the requirements of post graduate students by presenting a comprehensive overview of the conceptual background of
research, and its processes and techniques used specially in business scenario.
Learning Outcomes: The students in their managerial capabilities will learn to analyze the business, economic, or social conditions and in-turn assists then in making major strategic decisions.

New Course
Name Business Research Methods [M]
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction to business research: Research in business; Research process; Defining the research problem and developing an approach. [4L]
Unit II: The designs of business research: Classification of designs; Exploratory studies- Secondary data analysis, Qualitative techniques; Descriptive studies- Surveys
and observations; Causal studies- Experimental research designs. [6L]
Unit III: The sources and collection of data: Measurement concept; Measurement scales ; Questionnaire and instruments; Sampling design. [6L] Unit IV: Analysis and presentation of data: Data preparation, Examination of data, overview of hypothesis testing. [2L]
Unit V: Report preparation and presentation [2L]
References Text Books:
1. Business research Methods (12e Edition), Cooper, Schindler and Sharma (2019), ), Mc Graw Hill Education.
2. Marketing Research: An applied orientation (7th Edition), Malhotra and Dash, (2015), Pearson Pub.
Course: Business Statistics (M)
Course Objectives: This course is expected to provide the student with the fundamentals of statistics which are related to the management and provide a basis for later topics which
utilize these statistical concepts.
Learning Outcomes: To understand the basic concepts of statistical methods and their application to a business or an industrial engineering problem. Moreover, students are supposed to learn some application software like MS Excel, SYSTAT, SPSS for data analysis.

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New Course
Name Business Statistics [M]
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction: the meaning and scope of statistics, some uses of statistical methods, statistical data Presentation of statistical data: tables, graphs and charts.
[2L]
Unit II: Summarization of statistical data: frequency distribution of observations, measures of central tendency, dispersion, skewness and kurtosis of distributions. [3L]
Unit III: Probability: concepts, random variables; Probability Distributions: Binomial, Poisson, Normal distribution [2L]
Unit IV: Sampling distributions; Estimation: Point and Interval Estimates of mean and proportion. [2L]
Unit V: Testing hypotheses of mean and proportion: one/two-sample tests ; chi-square test; Analysis of variance (ANOVA) [6L] Unit VI :Simple regression and correlation: Making inferences about population parameters [3L]
Unit VII: Introduction to Non-parametric tests [2L]
References Text Books:
1. Statistics for Management, 7th edition, Levin & Rubin, Pearson Education Publication
2. Applied Statistics and Probability for Engineers , 6th edition, D. C. Montgomery and G. C. Runger, John Wiley & Sons.
Course: Productivity Management Practical
Course Objectives: Productivity improvement in an enterprise is a function and a result of management efficiency, synonymous with good management. The objectives of this
practical course is for students to acquire the fundamentals of productivity concepts, principles, tools, and techniques
Learning Outcomes: On completion of this practical course, the students shall be able to calculate the basic work content, analyze the existing methods of working and develop an improved method, and calculate basic, allowed and standard time, of a specific job. The students will also be able to analyze and calculate the level of risk in the job causing stress,
fatigue and musculoskeletal disorders and design appropriate work systems.

New Course
Name Productivity Management Practical
Code
L T P 0-0-3
Status Departmental core
Course
Content
Unit 1: Method Study
1. Method Study of machining operation
2. Application of multiple activity chart in improving the present method [6L] Unit II: Application of Principles of Motion Economy
1. Application of motion economy principles in improving the design of work place layout [3L] Unit III: Work Measurement
1. Time study and rating practices.
2. Application of work sampling techniques [3L]
Unit IV: Anthropometry and Isometric Strength Data Base
1. Assessment of ideal weight & obesity of the subjects
2. Assessment of body fat
3. Generation of hand grip strength database.
4. Generation of lifting strength database
5. Generation of Anthropometrical database. [9L]
Unit V: Assessment of human capabilities and limitation
1. Assessment of reaction time.
2. Assessment of comparative physical fitness level among the subjects
3. Assessment of hearing acuity status of the subjects. [9L]
Unit VI: Assessment of physical work capacity/aerobic power
1. Assessment of O2 (max) & energy expenditure of the subjects. [3L] Unit VII: Assessment of work environmental stress and its impact/effect
1. Measurement of hand-arm & whole-body vibration of the subjects. [3L]
References Text Books:
1. Sumanth, D. J. (1984). Productivity engineering and management. McGraw-Hill College.
2. Freivalds, A. (2009). Niebel's methods, standards, and work design (Vol. 700). Boston, Mass.: Mcgraw-Hill higher education.
Course: Business Analytics Lab
Course Objectives: Enable students for using the computer program s like MS Excel, SPSS for statistical problems.
Learning Outcomes: On successful completion of this course, student should be able to solve statistical problems using computer.



New Course
Name Business Analytics [Lab]
Code
L T P 0-0-3
Status Departmental Core
Course Content UNIT I: Introduction, Getting Acquainted with Microsoft Excel and SPSS, Using Statistics in Excel, Descriptive Statistics—Central Tendency, Descriptive Statistics—Variability, Development of charts and plotting in excel [6P]
UNIT II: Problems on different Probability Distributions: Binomial, Poisson, Normal distribution using software [9P ] UNIT III: Problems on t-test , Z-test, ANOVA and Chi-square test , Hypothesis testing and cases using software [12P] UNIT IV :Correlation, simple and multiple regression concept and problems using software [6P]
UNIT VI : Factor Analysis concept and application using software [6P]
References Text Books:
1. Understanding Educational Statistics Using Microsoft Excel and SPSS, Martin Lee Abott , Wiley , 2011
2. Statistics for Managers Using Microsoft Excel (5th Edition)David M. Levine David F. Stephan Timothy C. Krehbiel Mark L. Berenson, Prentice Hall, 8th Edition
Reference Books
1. Statistics for Management, 7th edition, Levin & Rubin, Pearson Education Publication
2. Applied Statistics and Probability for Engineers , 6th edition, D. C. Montgomery and G. C. Runger, John Wiley & Sons.
Course: Machine Learning
Course Objectives: In this course, one will be introduced to the foundations of machine learning along with some popular machine learning techniques. This will also give you insights
on how to apply machine learning to solve a new business related problem. The course will be taught with popular software like R and Python.
Learning Outcomes: 1. To understand the concept of machine learning.
2. To develop understanding in various types of machine learning algorithm
3. To develop the skill in application software like Python or R for solving business application problems through machine leaning.

New Course
Name Machine Learning
Code
L T P 3-0-0
Status Departmental Elective
Course Content Unit 1: Introduction: Basic principles, Applications, Challenges. [4L]
Unit 2: Supervised learning: Linear Regression (with one variable and multiple variables), Gradient Descent; Classification (Logistic Regression, Overfitting, Regularization, Support Vector Machines); Artificial Neural Networks (Perceptrons, Multilayer networks, back-propagation); Decision Trees. [14L]
Unit 3: Unsupervised learning: Clustering (K-means, Hierarchical); Dimensionality reduction; Principal Component Analysis; Anomaly detection. [10L] Unit 4: Theory of Generalization: In-sample and out-of-sample error, VC inequality, VC analysis, Bias and Variance analysis. [6L]
Unit 5: Applications: Spam filtering, recommender systems, and others. [6L]
References Text Books:
1. Understanding Machine Learning. Shai Shalev-Shwartz and Shai Ben-David. Cambridge University Press. 2017.
2. The Elements of Statistical Learning. Trevor Hastie, Robert Tibshirani and Jerome Friedman. Second Edition. 2009.
References:
1. Foundations of Data Science. Avrim Blum, John Hopcroft and Ravindran Kannan. January 2017.
2. Pattern Recognition and Machine Learning. Christopher Bishop. Springer. 2006.
Course: Quality Management
Course Objectives: The field of quality management keeps advancing in both depth and breadth with the scope of application in manufacturing and services. Quality issues are now the
concern of all organizations, including public and service sectors. The purpose of this course is to put quality management into perspective, and to highlight its critical importance, as well
as to present in-depth ideas on different methodologies, tools and techniques proposed for product and process improvement.
Learning Outcomes: To understand the importance of quality management in manufacturing as well as in service industries.
To get familiar with the various process and product quality improvement and using them with the help of some application software like SYSTAT, MINITAB etc. (3) To understand the
various Quality Management Systems adopted in many industries.

New Course
Name Quality Management
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction to Quality Management: Evolution, Concept of Product and Service Quality; Contributions of Juran, Deming, and Crossby; Quality Costs [4L] Unit II: Process Quality Improvement Tools and techniques: Graphical and statistical techniques; Seven Quality Control tools; Hypothesis Testing; Regression; Control charts; Process capability analysis; Measurement system analysis. [12L]
Unit III: Acceptance sampling plan [4L]
Unit IV: Design and Analysis of Experiment (DOE) [8L]
Unit V: Product Quality Improvement: Quality Function Deployment; Introduction to Robust Design and Taguchi Method; Design Failure Mode & Effect Analysis; Introduction to Product Reliability Analysis [6L]
Unit VI: Quality System (QS) in organizations: Quality Auditing concepts: Introduction to ISO 9000 and 14000 standards; TQM; Six Sigma concepts; Lean and JIT Quality Philosophy; Benchmarking [6L]
References Text Books:
1. Introduction to Statistical Quality Control, D. C. Montgomery,, John Wiley & Sons.
2. Fundamentals of Quality Control and Improvement, Mitra A.,, PHI.
References:
1. The Management and Control of Quality, J Evans and W Linsay,, Thomson.
2. Total Quality Management, Besterfield, D H et al.,, Pearson Education.
3. Design and Analysis of Experiments, D. C. Montgomery,, John Wiley & Sons.
Course: Service Operations Management
Course Objectives: The intent of the service operations management course is to provide students with an understanding of the analysis, decision making and implementation issues of
managing the operational aspects of a service. The intent of the course is to provide students with the concepts and tools necessary to effectively manage a service operation.
Learning Outcomes: -The students will able to understand the basic theories regarding service industry.
- After completing the course the student can manage the service industry efficiently.

New Course
Name Service Operations Management
Code
L T P 3-0-0
Status Specialization Elective
Course Content Unit I: Introduction to service operations management and nature of services. Formulating Strategy for managing services. [8 L] Unit II: Strategic Positioning and Service Strategy; Application of technologies in Services. Managing Service Experiences [12 L] Unit III: Concept of Service Quality and measurement tools; Matching Supply and Demand for service industry [8L]
Unit IV: Inventory Management in Services; Tools for Managing Services; Site Selection for Services. Case studies. [12 L]
References Text book
1. Service Management: Operations, Strategy, Information Technology by James A. Fitzsimmons and Mona J. Fitzsimmons, 2005, McGraw Hill, 8th Edition
Reference book
1. Successful Service Operations Management - by Metters, King-Metters, by Pullman & Walton, Cengage Learning., 2nd Edition
Course: Project Management
Course Objectives: The objectives of this course are (a) to understand the fundamental principles of Project management. (b) to familiar with the different methods and techniques
used in project management. (c) To help an efficient decision making.
Learning Outcomes: -Improving knowledge and understanding of project management principles
─ Identifying and proactively managing project pitfalls
─ Learning how to plan and structure a project
─ Examining some tools and techniques to help manage projects

New Course
Name Project Management
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction to Project Management and the basic concepts. Concept of life cycle of project. Concept of idea generation in the context of project Management. Project idea generation & screening using SWOT, PEST, Porter’s Model. [6L]
Unit II: Project evaluation: Market and demand Analysis, Technical Analysis, Financial analysis (NPV, IRR, Payback Time, Profitability Index, Tax, Depreciation, Inflation) Project selection under risk: Project selection under probabilistic condition. Application of simulation technique for project selection. Modeling Technique: Application of mathematical programming techniques for project selection. [14 L]
Unit III: Project Planning and Scheduling: Planning Time Scales, Project Planning using Network techniques (PERT & CPM), GANTT chart development, Crashing of
project, Resource leveling concepts [14 L]
Unit IV: Project organizational structures. Concept of project management information system. [6 L]
References Text Books
1. Projects – Prasanna Chandra- Mcgrawhill Publication., 8th Edition
2. Contemporary project Management – Timothy J. Kloppenborg, Cengage Publication, 3rd Edition
Reference books
1. Project Management – Panneerselvam and Senthilkumar , PHI, 2009
2. Project Manageent: A Systems Approach to Planning, Scheduling, and Controlling, 10th ed, Harold Kerzner, Wiley India, 11th Edition
Course: Materials Management
Course Objectives: The objectives of this course are: (a) to impart functional knowledge of Materials Management, Materials Procurement, Inventory Control as well as Warehousing for
both service as well as manufacturing sectors; (b) to provide theoretical and practical exposure for application of such concepts
Learning Outcomes: -The course helps to understand fundamentals of Materials Management.
-At end of this course, students would be able to make decisions regarding practical aspects of Materials Management like purchasing, inventory management and warehouse
management.

New Course
Name Materials Management
Code
L T P 3-0-0
Status Departmental Elective
Course Content Unit I: Functions & Objectives, Purchasing policy and sourcing strategies, Case studies. [8 L]
Unit II: Concept of Supplier Rating, Various models for selection and Development, Stores Management Principles and Practices, Case studies. [8 L]
Unit III: Concept of inventory management. Classification of inventories. Inventory management models and extensions. Case studies. [14L] Unit IV: Concept of MRP I, MRP II and extension. Application of ERP for materials management. JIT and Lean systems. Case studies. [10 L]
References Text Books
1. Materials Management : an integrated Approach, by Prem Vrat, Springer Publication, 1st Edition
2. Material Management: An Integrated Approach, Gopalkrishnan & Sundarsan: Prentice Hall of India Private Limited, New Delhi, 2003
Reference Books
1. Materials Management : an Executive's Supply Chain Guide by Stan C McDonald, Wiley, 1st Edition
2. Introduction to Materials Management, Steve Chapman, Ann K. Gatewood, Tony K. Arnold, Lloyd Clive, Pearson, 8th edition, 2016
3. Materials Management: Procedures, Text and Cases, by A. K. Dutta, Prentice Hall of India Private Limited, New Delhi, 2nd edition, 2009
Course: Corporate Finance
Course Objectives: This course will help students to understand the significance of financial management and the role of finance manager in the organization. The students will be
equipped with all tools and techniques for efficient financial management in the organization.
Learning Outcomes:
1. To understand the concept of financial management in decision making process.
2. To develop understanding about the various tools and techniques used for efficient financial management.
3. To understand the role of finance manager in the corporate sector.



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New Course
Name Corporate Finance
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I: Introduction to Financial Management, Objectives, Agency Problem; Concept of Time Value of Money, Capital Markets, Sources of Capital, Cost of Capital [12L]
Unit II: Basics of Capital budgeting: Principles and Techniques [8L]
Unit III: Leverage: Operating, Financial and Combined Leverage, Introduction to Optimal Capital Structure, Designing capital structure Management of
Working Capital: Determinants, computation & working capital financing, Introduction to Dividend Decisions: factors, Bonus Shares & Stock Splits 19L]
References Text Books
1. Financial Management (11th Edition)- By I.M.Pandey – Vikas Publishing
2. Financial Management – Texts, Problem & Cases (7th Edition) – By Khan & Jain – Tata McGraw Hill
References:
1. Financial Management (9th Edition) – By Prasanna Chanadra – Tata McGraw Hill
2. Handbook of ICAI
3. Case Studies - to be provided by the instructor
Course: Organizational Behavior
Course Objectives: The course aims to provide the participants insights into Human Behavior in general and in the context of organization in particular, so that they are able to develop an understanding of human nature and are able to get along with them more effectively resulting in better managerial action. Some changes have been made keeping in view the advances in human behavior and organizational dynamics.
Course Outcome: The students after completing this course will be able to understand the dynamics of human interactions in organizational settings and develop sophistication to work
with and through people.

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New Course
Name Organizational Behavior
Code
L T P 3-0-0
Status Departmental Core
Course Content Unit I : People as the competitive advantage - OB for understanding human behaviour. OB as a contrived discipline, An overview of OB [5L]
Unit II : Personality and individual differences, role of nature and nurture in shaping personality [6L]
Unit III : Foundations of Individual Behavior - Learning, Perception, Values, Attitudes, Job Satisfaction, Motivation: Contributions of Maslow, Herzberg and Vroom
[8L]
Unit IV Group Processes in Organizations, Group dynamics [6L]
Unit V : Leadership- theories, concept and practice; Emotional Intelligence and Managerial Effectiveness [6L]
Unit VI : Conflict and Negotiation, Culture, concept and meaning, Organizational culture, Stress and behaviour, Behaviour modification at the work place [8L]
References Text Books
1. Organizational Behaviour by Stephen P Robbins, 16th Edition, Pearson
2. Organizational Behaviour by Fred Luthans, 12th Edition, McGraw Hill
References:
1. Managing for responsibility by Sharma et. al 1st edition, Business expert press
2. Organizations and behaviours- Work book, VIVA publications.
Course: Software Lab
Course Objectives: The course introduces a novel approach to studying the core concepts in decision making, which is one important part in business management. The course aims to
1. Understand the steps of modeling process from a general management perspective. 2. Learn tools, analytical frameworks and general principles for decision making. 3. Interpret the
results to help the decisions of the manager.
Learning Outcomes: -1. The students can define business problems in logistics, supply chain management and finance with specific objectives and constraints
2. The students can analyze different optimizing problems by using excel spreadsheet
3. The course will help to interpret the optimal solutions given by computer from the management perspective

New Course
Name Software Lab
Code
L T P 0-0-3
Status Departmental Core
Course Content Unit I: Operations Research Models: Basic Linear programming problem formulation and solving, Example of mixed integer problem, integer problem, Binary problems and Sensitivity analysis. Product Mix problem, assignment problem, Binary project selection problem. [8P]
Unit II: Operations Management Problems: Application of excel based command for forecasting problems and calculation of errors. Capacitated facility location model (Single and multi-period model), Capacitated supplier selection problem. [8P ]
Unit III: Financial Modeling: Capital budgeting problems using spreadsheet, Calculation of NPV, IRR, Payback time. Problems considering TAX, Depreciation, and Inflation. Probabilistic capital budgeting models. [4P]
Unit IV: Multi-criteria Decision making tools: AHP, TOPSIS, and goal programming for various management problems. [4P]
-Use of application package like Lingo, SPSS.
Case studies.
References Text Books
1. Optimization Modeling with LINGO by Linus Schrage., 5th Edition
2. Data, Models and Decision making by Albright, Winston and Zappe, Cengage Publication, 4th Edition
Reference books
1. Financial Management by P.K. Jain and M.Y. Khan, McGrawhill, 8th Edition
2. Operations Research by J.K. Sharma, Trinity Publication, 6th Edition
Course Objectives: Course:Simulation Modelling & Analysis Lab
Simulation is an important tool available to those responsible for the design and operation of complex processes or systems. The objective of this course is to
introduce students to important features of ARENA software and teach them to build valid, credible, and appropriately detailed simulation models.
 Learning Outcomes: On completion of this course, students shall be able to use simulation as a tool to plan, design, and control complex systems.

Old Couse New Course
Name N.A Simulation Modeling & Analysis Lab
Code

L T P N.A 0-0-2
Status

Course
Content
N.A UNIT I: Selecting Input Probability Distribution [2P] UNIT II: Random-Number Generators [2P]
UNIT III: Generating Random Variates [2P]
UNIY IV: Output Data Analysis for a Single System [2P] UNIT V: Comparing Alternate System Configurations [4P] UNIT VI: Variance-Reduction Techniques [4P]
UNIT VII: Simulating a Single-Server Queuing System [2P] UNIT VIII: Simulating a Multi-Server Queuing System [2P] UNIT IX: Simulating an Inventory System [2P]
UNIT X: Simulating of Manufacturing Systems [2P]
References N.A Text Book:
Law, A. M., Kelton, W. D., & Kelton, W. D. (1991). Simulation modeling and analysis (Vol. 2). New York: McGraw-Hill.
Kelton, W. D. (2002). Simulation with ARENA. McGraw-hill.
Course: Operations Analytics
Course Objectives: : Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. The course on
operations analytics focuses on how the data can be used to profitably match supply with demand in various business settings.
Learning Outcomes: In this course, students will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk.

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New Course
Name Operations Analytics
Code
L T P 3-0-0
Status Specialization Elective
Course Content Unit I: Introduction to Operations analytics
Understanding and defining operations analytics, What involves in operations analytics, Decision Domains in operations analytics, Importance of analytics in Operations
& Supply Chain Management, Key issues in operations analytics [6L]
Unit II: Descriptive & Predictive analytics
Basic concepts of random variable, descriptive statistics, common forecasting tools, and quality of forecast [6L] Unit III: Prescriptive Analytics, Low uncertainty
Solve operations problems in settings with low uncertainty using optimization models. [9L] Unit IV: Predictive Analytics, Risk
Evaluate and compare operations decisions when their impact is uncertain using simulation to estimate some common measures of risk and reward. [9L]
Unit V: Prescriptive Analytics, High uncertainty
Solve complex operations problems with high degrees of uncertainty using optimization, simulation, and decision trees together. [9L]
References Text Books:
1. Albright, S., & Winston, W. (2014). Business analytics: Data analysis & decision making. Nelson Education.
2. Law, A. M., Kelton, W. D., & Kelton, W. D. (1991). Simulation modeling and analysis (Vol. 2). New York: McGraw-Hill.
Reference Book:
1. Chopra, S., & Meindl, P. (2016). Supply chain management: Strategy, planning, and operation. Pearson Publication
2. Heizer, J. H., & Render, B. (2008). Operations management(Vol. 1). Pearson Education India.
Course Objectives: The course is designed to New Course: Financial Econometrics
 Provide knowledge of modern econometric techniques commonly employed in the finance literature.
 Develop an understating of statistical tools in the area of finance.
 Introduces financial modelling for research oriented students in finance
Learning Outcomes: Understand the essential foundations of time series models.
Construct and evaluate forecast models using financial time-series. Explain and apply models of volatility using financial time-series.
Understand and estimate the long run relationship between variables using financial time- series.
Understand, construct and estimate panel data models. Understand and estimate the limited dependent variable models.

New Course
Name Financial Econometrics
Code
L T P (3-0-0)
Status Departmental Elective
Course Content Unit I: Overview of the classical linear regression model (CLRM)- Recent development and analysis of the CLRM, CLRM assumptions and diagnostic tests, Univariate time series modelling and forecasting- Moving average processes, Autoregressive processes, ARMA processes, Building ARMA models: the Box--Jenkins approach. [10L] Unit II: Multivariate models- Vector autoregressive models, Impulse responses and variance decompositions. Modelling long-run relationships in finance- Stationarity and unit root testing, Cointegration, Equilibrium correction or error correction models, Testing for and estimating cointegrating systems using the Johansen technique based on VARs. [10 L]
Unit III: Modelling volatility and correlation- Autoregressive volatility models, Autoregressive conditionally heteroscedastic (ARCH) models, Generalised ARCH (GARCH) models. [10 L]
Unit IV: Panel data models-The fixed effects model, Time-fixed effects model, The random effects model. Limited dependent variable models- The linear probability model, The logit and probit models, Multinomial linear dependent variables. [10 L]
References Text Books
1. Introductory Econometrics for Finance, 2nd Edition, Chris Brooks, Cambridge University Press (2014)
2. Introduction to Econometrics, 4th Edition, Christopher Dougherty, Oxford University Press (2011).
Course: Supply Chain Management
Course Objectives: A supply chain is comprised of all the parties involved in fulfilling a customer request. The integrated management of this network is a critical determinant of success
in today’s competitive environment. This objective of this course is to provide students with a strong understanding of supply chain management concepts.
Learning Outcomes: Learning the key concepts and techniques will allow students to analyse, manage and improve supply chain processes, assess supply chain performance and make
recommendations to increase supply chain competitiveness.

New Course
Name Supply Chain Management
Code
L T P 3-0-0
Status Specialization Elective
Course Content Unit I: Introduction : Definition of supply chain, Emergence of SCM, Realization of SCM, Decision phases in supply chain [6L]
Unit II: Achieving strategic fit and scope : Supply chain performance, Supply chain drivers and obstacles [6L] Unit III: Strategic decisions : Role of distribution in supply chain, Network design in a supply chain [6L]
Unit IV: Aggregate level decisions : Demand forecasting in supply chain, Aggregate planning, and Managing predictable variability. [6L]
Unit V: Sourcing and Transportation decisions [6L]
Unit VI: Supply chain coordination, Information Technology in Supply chain [6L] Unit VII: E-Business [3L]
References Text Book:
1. Supply chain management: Strategy, planning, and operation, Chopra, S., & Meindl, P. (2016.) Pearson Publication
References:
1. Fundamentals of supply chain management: twelve drivers of competitive advantage, Mentzer, J. T. (2004), Sage.
2. Supply chain logistics management, Donald, J. B., Closs, D., & Cooper, M. B. (2002), The McGraw-Hill Companies, Inc.