Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Quality planning and analysis: strategy for definition, importance, and measurement of quality, improvement by graphical and statistical methods, and total quality chain.

An overview of the objectives, policies and self-imposed restrictions that together describe how organizations propose to develop and direct all the resources invested in operations so as to best fulfil, and possibly redefine, their missions. Coordination of marketing, operations, and finance functions within a framework designed to meet the competitive requirements of the marketplace. Interface issues between corporate strategy and the management of the operations function.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

This course is designed to provide students with an understanding of the behavior of individuals and groups in organizations. Students will identify and develop the skills needed to make an effective contribution to organization, to manage others, and to maintain a high quality of work life. Topics covered include: motivation, communication, conflict negotiation, group dynamics, leadership, organizational&job design, and change management

Basic functions of Human Resource Management from a generalist perspective for all managers; job design, recruitment, selection, training and career development, compensation and benefits, performance appraisal and discipline in organizations; current developments in HRM abroad and in Türkiye.

Statistical techniques in business data analysis; decision making under uncertainty. Concept of loss functions, decision trees, Bayes' Rule; correlation analysis, simple and multiple regression analysis (variable selection, model building, residual analysis); exponential smoothing methods; autoregressive (AR), moving average (MA), and ARMA models; introduction to intervention analysis, outlier-level shift-variance change detection procedures , and autoregressive conditional heteroscedasticity models. Extensive use of computer-based computational tools and business applications.

Fundamental quantitative methods for business decision making: problem formulation, analysis, and use of management science tools, such as linear and integer programming, decision analysis and Monte Carlo simulation with spreadsheets. Extensive use of business applications.

Computer simulation as a means of evaluating designs and operating procedures for complex systems; systems analysis, modeling, use of simulation languages/software, experimental design and statistical analysis.

Business Value Creation with Big Data. Data sources. Data mining tasks and supervised/ unsupervised learning. Evaluation criteria. Generalizing from data versus overfitting. Data mining process. Data collection strategy. Security, privacy and ethical considerations. Case studies.