Course subject: Management Sciences (MSCI)

This course surveys a spectrum of models and techniques in Operations Research, with emphasis on applications. It focuses on the development of modeling skills, the interpretation of results, sensitivity analysis and computer implementations of decision support systems. Topics include linear, integer and network optimization models. Simulation analysis and other topics in stochastic processes may also be covered. The use of quantitative models in different levels of the decision making hierarchy are illustrated through case studies and readings from the Management Sciences literature. Priority may be given to Management Sciences students.

The course provides a comprehensive background in the management principles needed to effectively enhance interpersonal skills, evaluate organizational performance and apply organizational functioning. The subject areas that make up this course, in order to provide this broad background, include: Financial Accounting, Management Accounting, Organizational Behaviour, Management, Information Systems, Production and Operations Management, and Marketing. Key objectives of the course include (1) to enable confident interactions with functional specialists, (2) to provide tools for the evaluation of organizational performance, and (3) to enhance appreciation for the contributions, and applications of management theories to organizations. Priority may be given to Management Sciences students.

Descriptive statistics and probability concepts; discrete and continuous probability distributions; sampling methods and the central limit theorem; estimation and confidence intervals; inference and hypothesis testing; linear regression and correlation; multiple regression and model building.

This course focuses on methods and algorithms for turning very large collections of data into actionable insight. Topics may include data profiling, transformation and cleaning, data mining, data warehousing and cloud computing. Applications will be drawn from various areas such as smart grid analytics and ubiquitous computing. Students will read and present papers and complete a research project. Priority may be given to Management Sciences students. Previous studies in programming, algorithms, statistics and database management are necessary background topics for those taking this course.

The goal of this course is to enable students to think probabilistically. The modelling and analysis of uncertain systems in operations research is emphasized. Tools include renewal theory, Markov processes and queuing analysis, while application areas include production and inventory control, health-management, transportation, and other problems in probabilistic operations research. Priority may be given to Management Sciences students.

The course emphasizes inventory control models with deterministic and stochastic demand, and supply chain management. Other areas which might be addressed are aggregate planning, machine scheduling, material requirements planning, and multi-echelon production and distribution systems. Priority may be given to Management Sciences students.

This course presents the foundations which underlie the development of management information systems. Emphasis is placed on the concepts, strategies, techniques and tools for identifying and specifying information systems requirements, and developing designs. Students are expected to complete an analysis and design project. Priority may be given to Management Sciences students.

The course is concerned with the design, management and use of databases. The course combines theoretical foundations of database organization and database design methodologies with the practical aspects of developing, implementing and managing databases. Some topics include: relational database design, entity modelling, SQL, and comparison of different types of databases.

Companies today confront an increasing array of choices regarding markets, locations for key activities, organizational structures, and processes for managing across borders. This course provides students with the conceptual tools necessary to understand and work effectively in today's interconnected world by developing strategic perspectives that link the global environment and the capabilities and position of the firm. Topics include Globalization, International Strategy Development, Mode of Entry and Alliance Structures, Organizational Design, Structure and Control, Human Resources Management, Cross-cultural Issues, Ethics in International Business, International Marketing and Branding, International Operations, Exporting and Importing, and Global Corporate Sustainability.

Introduction to selected applications of LP. The simplex method. Duality and sensitivity analysis. Computer solutions to LP. Network flow problems with applications and algorithms. Special topics such as revised simplex method, primal-dual method, decomposition principle, generalized upperbounding and ellipsoid methods. Priority may be given to Management Sciences students.

Modern supply chain management encompasses the logistics of inventory and transportation flows, whether within a given organization or between that firm and other companies (suppliers, customers) that are part of its business. This course thus deal with models and analyses of the inbound transportation of raw materials, manufactured components and sub-assemblies. Another emphasis is the (outbound) physical distribution of finished goods from factory to consumer: freight transportation (various modes, customer service, multi-location inventory management and distribution-centre site selection. Specialized topics (for term projects) may be chosen from among Logistics Information Systems; Global Supply Chain Management; Vehicle Routing; or the Logistics of e-Commerce. Priority may be given to Management Sciences students.

The objective of this course is to develop skills with a range of procedures and programs for multivariate data analysis. The focus will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, menu-driven and syntax programming, interpreting output, and presenting results of a complex nature.

Priority may be given to Management Sciences students.

This course introduces matrix-analytic methods and shows their applications in queuing theory, inventory theory, supply chain management, telecommunications networks, reliability, finance mathematics, and risk and insurance analysis. In the first half of the course, the basic theory on phase-type distributions, Markovian arrival processes, and matrix-geometric solutions is introduced. In the second half of the course, applications of matrix-analytic methods in stochastic modeling (queuing, reliability, inventory, supply chain, etc.) are examined. Previous study of stochastic models is required, such as MSCI 631.

Priority may be given to Management Sciences students.

Science and Technology are increasingly viewed as important tools to promote the social, economic, and political goals of modern economies. Accordingly, science and technology (S&T) policy issues have assumed prominence in contemporary policy discourse. Firms are often operated under different policy environments and their strategies should be formulated under the various environments. This course provides students with the background and tools needed to critically evaluate issues in S&T policy debates. After reviewing the basics of science and technology policy, we will discuss a few instruments of S&T policy, e.g., intellectual property rights, tax and subsidy, public funding for research, and prizes. Throughout the course, we will integrate the theoretical discussions with cases of contemporary S&T policy issues. Previous study of economics is required, such as MSCI 607.

This course is designed to provide the student with up-to-date understanding of the developments, issues and current research in the topics associated with knowledge as an asset in organizations. Topics include: knowledge and economic growth and change: the global knowledge-based economy; consequences of the increasing role of the knowledge worker; strategic and organizational roles of intellectual capital; monitoring, and valuing and reporting intellectual capital. Priority may be given to Management Sciences students.

An overview of the process of initiating startups, spin-outs or new ventures within an existing company. Ventures based on new technologies are a focus. Topics include extrpreneurship and organizational culture, opportunity identification and assessment, business plans and new venture diagnostics, protecting intellectual property, finance, marketing and the entrpreneurial team.