Management Science (MGS)
Covers statistical topics with practical applications in management science, including multiple regression and correlation, sampling theory and methods, analysis of variance and covariance, factor analysis, cluster analysis and discriminant analysis. Analyzes real databases with the aid of the computer.
Provides a methodology for the planning and control of management systems. Covers the methods for defining the elements and activities of business and related systems and for designing and testing improved systems. The methodology of computer simulation is used in conjunction with flow charting and other tools of systems analysis to plan, evaluate and improve the system's performance.
Focuses on formulating and solving decision problems under conditions of certainty. The models and methods covered have wide applicability in the practice of management science. Beginning with advanced linear programming topics including sensitivity analysis and duality, treats integer, nonlinear, and goal programming models and applications, and selected network and classical optimization methods. Additional topics include reliability theory and queuing theory. Cases and problems from service, manufacturing, and transportation organizations will be covered. The computer is extensively used to develop flexibility in model building and analysis.
Covers a variety of modeling approaches that incorporate inherent uncertainty about the consequences of alternative actions. Includes decision analysis, Markovian decision processes and applications, queuing theory, reliability models, stochastic programming and game theory. Develops a sensitivity to the applicability and limitations of these stochastic models and to the value of the computer in their analysis.
Introduces students to the more advanced statistical techniques used in operations planning and analysis. Focuses on sampling methods, data mining, forcasting methods, statistical methods for quality control, non-parametric statistics, index numbers and advanced statistical inference. Uses cases from service, manufacturing, and transportation organizations. SAS and EXCEL are used.
Introduces the student to the different perspectives on digital enterprises and digital networks. Places the emphasis on digital structures and design, and the role of operations management and models in digital markets, ethics, and trust and security matters relating to cyberspace. Views these and other digital issues from a strategic perspective with the aim of giving the student the necessary tools to effectively manage a digital enterprise.
The function of supply chain management is to design and manage the flow of materials and information starting from the raw materials through production and distribution until the finished goals or services reach the customer. Builds an understanding of the individual components of supply chains with emphasis on coordination across multiple functions and organizations. Develops the analytical and problem solving skills necessary to solve supply chain management and design problems. Develops the ability to design and formulate integrated supply chain strategy, so that all components are internally synchronized and tuned to fit corporate strategy, competitive realities and market needs. Topics include: quality and productivity issues, manufacturing and service operations planning, reengineering, strategic use of information technology, management of technology, purchasing decisions, inventory reduction, global operations strategy, mass customization, logistics, and optimization of the entire supply chain.
Covers advanced topics of interest to operations managers. Broadens the student's exposure to managing operations in manufacturing and service industries. Topics include productivity analysis, quality control, physical distribution, purchasing, maintenance and facilities planning. Case analysis and computer applications are used.
Discusses the implications of the Internet from technology integration and operations management strategies and organizational behaviors for eBusiness in a variety of high and low technology environmentsl compares new firms and firms established before the advent of the Internet. Applies various business management and organizational behavior models in diverse industrial settings.
This course will introduce concepts and techniques of data mining. Emphasis of this course is on applications rather than theory. This course will include applications of data mining to banking, retailing, health care, and telecoms. The purpose of this course is to: Provides a structured approach to understanding the elements of data mining. Presents a generic data mining methodology to translate business issues into data mining problems. Teaches mathematical and statistical techniques of data mining. Discusses applications in banking, retailing, healthcare, and telecoms. Develops evaluation criteria to choose data mining software, and introduces implementation strategies for data mining applications.
Focuses on the design and management of quality for manufacturing, service and public sectors to achieve global competitiveness. Emphasizes new techniques for managing quality. Topics include statistical quality control, total quality management, concurrent engineering, Taguchi designs, bench marking, ISO 9000, quality function deployment, quality philosophies of Deming, Juran, Crosby, Taguchi, Ishikawa and others, environmental quality, reliability, availability and maintainability, Malcolm Baldrige Quality Award and Deming Prize.
Focuses on planning issues relating to transportation problems such as congestion and traffic control. Exposes students to methods for transportation demand forecasts, management of transportation problems using techniques such as linear programming, network models including probabilistic generalized networks, and simulation. Issues, such as planning with limited resources and project planning with a focus on budget control and constraints, are discussed. Application of heuristic models in multi-project scheduling and resource leveling will also be developed. Capacity panning and expansion issues are discussed.
Discusses problems in developing transportation policies and will evaluate the social and political issues involved. Such issues include environmental, community, and legal constraints. Explores the role of transportation managers in determining and achieving operating objectives and formulating and implementing transportation strategy in urban, suburban and global environments. Covers studies of the policies, regulations and controls established by all levels of government that currently impact the transportation industyr.
Corporations are now recognizing the strategic role of the operation function in satisfying customer needs. A systemic approach that takes a cradle-to-grave approach of a product or process is now being taken by corporations in order to meet these needs. Such approach requires tracking the operation process from raw material acquisition to fabrication, assembly, customer delivery, and waste disposal. All these can only be achieved through integrated information systems. Enterprise Resource Planning (ERP) enables the corporation not only to track the product or process but also to coordinate and manage the activities that are involved in the operations process. It is an integrated process that shares common database for all the functional units of an organization. Through ERP, a comprehensive management of the financial, manufacturing, marketing and distribution, and human resources issues across the enterprise could be better coordinated for the efficient running of the organization. ERP therefore, helps the enterprise to become more competitive by improving the performance and quality of the entire supply chain. Today's managers therefore, must learn how to manage processes in an ERP environment. Enterprise resource planning is applicable to any sector of the economy. Manufacturing, service and public enterprises face the same common problems of how to coordinate or manage their operations function. Thus, this is a topic of great interest to every organization. ERP is about achieving a fully integrated information system through the supply chain or value chain. This enhances the quality of business decisions that are made. The demands on organizations are constantly changing. Integrated information is the key to competitiveness. It is no longer enough to provide high quality, low cost products or services to customers. Without integrated information system, the organization will be unable to respond rapidly to changes in the market place and will in fact, not optimize its services.
This is a capstone course in the graduate program in e-business operations. The major objective of the course is to integrate materials that the student has learned in his/her program of study and apply that knowledge to e-Business strategic issues facing the enterprise. The e-business theme is deeply integrated throughout the course of study. The courses learning objectives are achieved through the use of standard lecture, online instruction, experiential exercises, e-Business case studies and a management simulation.
Under the supervision of a faculty advisor, the student prepares a research document which includes the following: definition of a business problem, appropriate information and data, analysis and evaluation of the data, presentation of findings, conclusions, and recommendations.