39 graduate courses in Waterloo’s course catalog for Fall 2023, from UW Open Data. uwloo can’t read that term’s Graduate Calendar, so this stands in for it; the calendar itself is in Waterloo’s archive.
MSCI 601Research Methods in the Management Sciences
This course focuses on methods used in empirical research in the management sciences. It encompasses: stages in the research process, theory building, problem definition, research strategies and designs, measurement issues, sampling, ethical concerns, data analysis, and the communication of research results. These issues will be examined in published research and student proposals. Priority may be given to Management Sciences students.
MSCI 602Strategic Management of Technological Innovation
This course includes: integrating technology and business strategy; design and evolution of technology strategy; development of the firm's innovative capabilities; creating and implementing systems for innovation; innovation challenges in established firms. In addition to a textbook, cases are used to add realism and context to this course. Priority may be given to Management Sciences students.
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.
Introduction to the concepts of learning, person perception, attitudes, and motivation in an organization. Consideration of communication, roles, norms, and decision making within a group. Discussion of power, control, leadership, and management in light of the above concepts. 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.
This course will examine economic concepts that are useful to management, from decisions about proposed investments in process changes or product modifications, to strategic considerations for the firm. Topics will include: techniques for financial evaluation of proposed investments; incorporating risk into evaluations; basic concepts from game theory; theory of demand; production functions; cost functions; competitive markets; other market structures. Priority may be given to Management Sciences students.
MSCI 609Quantitative Data Analysis for Management Sciences
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 research seminar concentrates on a macro view of organizations as dynamic systems. It emphasizes the principles of effective management of organizations and technology. Further, the course examines the conceptual foundations of organizational theory and design. Priority may be given to Management Sciences students.
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.
This course concentrates on the theoretical and practical issues related to the design of the human-computer interfaces. Aspects of human perception, cognition and various models of task analysis are discussed. Further, the course examines the principles of interface design and the related empirical evidence. Priority may be given to Management Sciences students
MSCI 631Probabilistic Models in Operations Research
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.
This course provides an introduction to Discrete Event Simulation. Topics covered include applications of discrete event simulation, simulation languages, data collection and input analysis, random number generation, validation, output analysis for a single system, comparison of several systems, variance reduction techniques and experimental design. Through a project, students will acquire the skills necessary to define a problem, develop and validate a conceptual and computer model, analyse the problem, and make recommendations. 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.
MSCI 634Deterministic Models in Operations Research
The objective of this course is to provide students with an in-depth understanding of the theory and algorithms in deterministic optimization. Specifically, it covers advanced topics in linear optimization including simplex method, duality, sensitivity analysis, and interior point methods. Then, topics in integer optimization including polyhedral theory, branch-and-bound, and cutting plane algorithm are discussed. Other topics such as nonlinear optimization and dynamic programming may be covered.
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.
With the rapid growth of unstructured natural language data, such as web pages, blogs, product reviews, news articles and enterprise data, there is an increasing need for systems that would retrieve relevant documents, extract specific information from them, mine opinions, summarize and categorize texts. This course provides students with an understanding of the major methods for retrieving, mining and analyzing textual data, with the emphasis on algorithms, techniques and their evaluation.
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.
This course will provide students with an understanding of Project Management Fundamentals while allowing them to gain practical experience of International Project Management and Development in a live practical project. Topics covered include: Project Management Methodologies, Project Manager's Role, Managing Project Stakeholders, Scope, Quality and teams; Project Risk Management, Procurement, Leadership, and Ethics.
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.
The course focuses on the modeling and solution of practical optimization problems. It covers formulations based on integer and nonlinear optimization, solution approaches based on large-scale optimization, and algorithmic design and implementation. Topics include set covering formulations, Lagrangean relaxation, Benders decomposition, column generation, branch-and-price, nonlinear programming, and metaheuristics. Possible applications areas include bin packing, routing, scheduling, and logistics planning. 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 course goal is to understand, model and improve decision making under uncertainty and complexity. Bayesian principles and expected utility theory are combined, their underlying assumptions critically reviewed, and alternative theories surveyed. Other issues addressed include decision with multiple attributes. 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.
This course covers predictive analytics that provides techniques to model the relationships between inputs and outcomes, and construct predictions about future outcomes, and prescriptive analytics that provides tools to optimize actions against a complex set of objectives to find best practices and design best policies under all circumstances. The theoretical techniques will be applied to such chains, service industries, healthcare systems, revenue management, inventory management, and sports.
Introduction to game theory including symmetric and asymmetric games, as well as static and dynamic games. Topics include game rules and information, mixed and continuous strategies, moral hazard, adverse selection, and introductory mechanism design. Applications such as: sustainability in supply chains, prediction markets, and contract design, are reviewed in this course.
MSCI 731Matrix-Analytic Methods in Stochastic Models
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.
This course treats the broad subject of network models. Network flow problems form a special class of linear programming that arise in a wide variety of applications including transportation, telecommunications, logistics and supply chain management. The purpose is to study the properties of network flow models, to discuss extensions and various solutions approaches, and to survey some applications.
This is an applied course in industrial organization economics. It deals with productivity, the relationship between productivity and technological change, the determinants to firms' investments in research, development and innovation, the diffusion of innovations, entrepreneurship, and technology policy. 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.
This course introduces graduate students to theories, ideas, and findings in behavioural decision-making research. Although normative theories of judgment and decision-making will be discussed, the main focus of this course will be descriptive theories. The readings are selected to introduce students to a variety of issues dealing with judgment and decision-making in psychology and economics as well as other business disciplines such as marketing, finance, organizational behaviour and operations management. Possible topics will include decision-making under risk and ambiguity, emotions and decision-making, intuition vs. deliberation, and intertemporal choice.Priority may be given to Management Sciences students.
MSCI 753Entrepreneurship and Intrapreneurship: Managing New Technology-based Firms
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.