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Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Basic Statistical Analysis Teacher (Name, first letter of one parent’s name, last name): Bošković T. Olgica, Dragutinović Mitrović S. Radmila, Rajić M. Vesna Subject status: Compulsory Number of ECTS: 10 Prerequisite: Subject objective The aim of this subject is to make students familiar with some basic methods of statistical inference, assumptions, advantages and constraints of their application, as well as with the logic of statistical (inductive-probabilistic) way of thinking in general. Since almost every economic analysis is based on the use of statistical methods, the additional aim of this subject is to gain a practical knowledge, i.e., the application of theoretical models within the domain of the empirical data. Subject outcome The acquired theoretical knowledge enables the students to apply statistical methods in practice, i.e. to independently conduct simple statistical analyses of empirical data. This includes the following: the choice of the appropriate statistical method depending on the given subject and the aim of the empirical research, the descriptive statistical analysis of economic phenomena and quantifying economic interdependence, as well as the correct interpretation of the results and the process of drawing the appropriate economic conclusions. Subject content The structure of the subject comprises several areas of the statistical analysis. The following are taken into consideration: the basic statistical indicators within the descriptive statistical analysis, the main terms in probability theory, random variable and probability distributions, sample and sample statistics, methods of statistical estimation, parametric hypothesis tests based on one and two samples, analysis of variance, nonparametric hypothesis tests, chi-square test, simple and multiple linear correlation and regression, index numbers and time series analysis. Literature 1. Prem S. Mann (2009) Introductory statistics, John Wiley&Sons, Inc., 6th ed. 2. Bowerman, B. L. and O’Connell , R. T. (2010) Business Statistics in Practice, McGraw-Hill/Irwin. Number of active teaching lessons Other

lessons: 0 Lectures: 4

Practice classes:4

Other forms of teaching: 0

Study research work: 0

Teaching methods The course includes lectures and practice classes which are in line with the subject structure and include the process of acquainting the students with the appropriate statistical packages. Lectures cover approximately 80% of theory (methods, definitions, concepts) and about 20% of illustrative examples. Practice classes include the following methods: explaining the theoretical parts of the subject matter, solving statistical problems individually and in small groups, illustrations through practical work. Active participation in the process of solving problems and discussion presupposes that students have already acquired basic theoretical knowledge about the topics discussed during the lectures.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Colloquium/a 30.00 Written exam

30.00

Oral exam 40.00

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies:, Undergraduate academic studies Subject title: Basics of Econometrics Teacher (Name, first letter of one parent’s name, last name): Pavle D. Petrović, Zorica L.Mladenović, Aleksandra Č. Nojković Subject status: Compulsory Number of ECTS: 10 Prerequisite: None Subject objective The objective of this course is to introduce students with the basic econometric methods and prepare them for empirical work in economics. In particular, topics will include specification and estimation of econometric models, testing, and forecasting. The course gives students the opportunity to use actual economic data to test economic theories. In addition, by analyzing specific empirical studies students will be provided with the economic implications of the specific econometric results. Subject outcome Students have adopted the principles of econometric modelling within the Classical Linear Regression Model framework. Students are trained to estimate and predict from simple econometric models. Students learn to interpret the results of the econometric analysis. Students are trained to solve econometric problems based on concrete economic data. Students are introduced to basic use of statistical software packages (EViews or equivalent econometrics program).

Subject content Theory lessons Simple regression. Population, sample and linear regression line. The ordinary least squares (OLS) method of estimation. The correlation. The coefficient of determination. Non-linear relationships. Application in economic analysis. Small and large sample properties of the estimators. The Classical Linear Regression Model (CLRM): Simple and Multiple Regressions. The Assumptions, OLS method of estimation, properties of the OLS estimator, hypothesis testing, and prediction. Multicollinearity. Dummy variables. Testing linear restrictions. Autocorrelation and heteroskedasticity: definition, consequences, detecting and resolving. Model specification. Misspecification errors. Alternative approaches in choosing an appropriate model. Time series analysis. Stationarity. Presents of a unit root: economic and statistical implications. Testing for a unit root. Cointegration. Example of applied cointegration analysis: Modelling inflation in Serbia. Simultaneous Equations Models. Structural and reduced form equations. The identification problem. Estimation methods (OLS, Method of Indirect Least Squares (ILS), Method of Instrumental Variables (IV) and Two-stage least squares (TSLS) method). Applied econometric analysis. Klein’s macroeconomic model of the U.S. economy (prediction, the final form of the model and the estimation of the effectiveness of the economic policies in a system of simultaneous equations) and, the Rotterdam model.

Practice lessons: practice classes, other forms of teaching, study research work

In practice class students are solving econometric problems (numerically or by using econometrics software). Literature 1. Verbeek, M. A Guide to Modern Econometrics, 4th ed., Wiley, 2012 2. Wooldridge, J.M. Introductory Econometrics: A Modern Approach, 5th ed., Cengage Learning, 2012 3. Asteriou, D. and Hall, S.H., Applied Econometrics, Palgrave, 2011 Number of active teaching lessons Other lessons

0 Lectures: 60

Practice classes: 60



Teaching methods Teaching is realised through lectures and practice classes. Lectures include presentation of the theoretical framework and empirical applications of presented methodology. In practice class students are solving numerically concrete tasks. One part of the practice classes are held in the computer lab in order to familiarize students with the use of statistical software in solving econometric problems.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Activities during lectures 5 Written exam

30

Practice lessons

5 Oral exam 30

Colloquium/a 30 .......... Semester papers

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Business Informatics Teacher (Name, first letter of one parent’s name, last name): Rade M. Stankić Subject status: Compulsory Number of ECTS: 7 Prerequisite: Subject objective The objective of this course is to make students well-acquainted with contemporary theoretical and practical aspects of business informatics and to enable them to master the knowledge and techniques of computer applications in business, which involves the use of software and selected methodological tools such as programming languages, database management systems, e-business models, operating systems, Internet technologies, etc.. Subject outcome With the acquired theoretical and practical knowledge, students will be able to use information technology, system software, programming languages, application software and database management systems in developing applications to solve specific business problems. Knowledge of specific software tools enable students to efficiently use the information and communication technologies in the creation of business applications. Subject content Theory lessons Basic Concepts of Computer Science; Information Theory; Presenting Information; History of Computers; Computer Architecture; Algorithms; Software, Programming and Programming Languages; Applications Software; Systems Software; Database Management Systems; Information Technologies and Information Systems; Business Information Systems; Development of Information Systems; Management Information Systems; Decision Support Systems; Expert Systems; Electronic Data Interchange (EDI); Business Information Systems and Standardization; Protecting Business Information Systems; Internet; Economic potential of the Internet; World-Wide Web; E-Business; Electronic Banking; E-Commerce; Electronic Marketing; Computer Networks; ERP software. Practice lessons: practice classes, other forms of teaching, study research work: Creating a Web site; Working with the relational database management system; Using programming languages. Literature Tucker A., Computer Science, CRC Press, 2004., Turban E., Volonino L., Information Technology Management, Wiley, 2012. Number of active teaching lessons Other lessons Lectures: 60


Other forms of teaching:

Study research work:

Teaching methods For each teaching unit adequate presentations are prepared, and some of the units include the use of the Internet. Active participation of students is planned in the form of presentations which are individually or team prepared as a complement to the topic. At the end of each topic a discussion is held. The exercises take place at the Centre for Information Technology.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Presentation 10 Written exam 30 Colloquium/a 10 Oral exam 30 Practice lessons 20

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Business Information Systems Teacher (Name, first letter of one parent’s name, last name): Jasna, Đ. Soldić-Aleksić Subject status: Compulsory Number of ECTS: 5 Prerequisite: none Subject objective The subject objective is to provide students with knowledge regarding the basic structure, functioning and the concept of contemporary business information systems (BIS). The main topics concerning the ICT (Information Communication Technology) applications in business information systems will be presented to students. In the first place, it applies to the issue of the role and importance of information system for functioning of business organisation. Also, the following topics will be covered: different classes of business information systems; communication systems; electronic commerce; acquiring IT applications and infrastructure; managing information resources; the impacts of information communication technology on individuals, organisations and society. Subject outcome The main subject outcome concerns to the students’ ability to acquire the knowledge on contemporary Information Communication Technologies - ICT, in particular the importance and potential application of these technologies in business information systems. It is expected that students will get necessary knowledge regarding the importance and role of information systems in achieving the crucial strategic goals of business organization, which is the basic mission of BIS functioning. Subject content The content of the BIS subject is organized as follows: ICT – the concept, management and development trends; ICT and information systems; the place and the role of information system in business organization; information infrastructure and architecture; classification of information systems: functional information systems, transaction processing systems, operative, management and strategic information systems, Web-based systems; development changes and information systems management; information, management and decision making; Decision Support Systems; Data, data organization and management; Intelligent decision support systems; Electronic business; Electronic commerce, banking and marketing; Information systems building; Managing information resources and security; the impacts of information technology on individuals, organizations and society; Literature Information Technology for Management, E. Turban, L. Volonino, 7th edition, John Wiley & Sons, Inc. 2010.

Lecturing presentations, J. Soldic-Aleksic, 2013.

Number of active teaching lessons Other lessons: 0 Lectures:

2

Practice classes: 2



Teaching methods Lecturing classes will be organized in the computer laboratory; also practical students’ work in computer laboratory: students’ presentations – individual and/or group work on some specific topic from the subject content; case studies - presentations; seminar works; organization of test during the course or at the end of

semester.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Activities during lectures Written exam

Practice lessons

Oral exam 60


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Commodity science Teacher (Name, first letter of one parent’s name, last name): Dušanka V. Ušćumlić, Jasna B. Babić Subject status: optional from compulsory group consisting of 2 subjects Number of ECTS: 5 Prerequisite: - Subject objective: Mastering of knowledge and skills in quality, in quality of material products, as well as in quality of some groups of products most important for national conditions. Overview of resources (material and energy) essential for obtaining of specific groups of products (primary and secondary). Subject outcome: Knowledge of quality level and quality characteristics of material products; preservation of quality level; base for standardization; classification of products; raw material for specific groups of products; possible assortment of products based on specific resources. Subject content

Theory lessons: А. General part: 1. Product (classifications); 2. Quality of products (quality characteristics of material products, standardization); 3.Transposition of products (storage, packaging); B. Specific commodities: 1. Mineral resources; 2. Energy sources (conventional and alternative); 3. Metal materials (ferrous, coppers); 4. Non-metal products; 5. Chemical products (basic nonorganic and organic, polymers), 6. Food products

Literature Hoyle D.: Quality Management Essentials, Butterworth-Heinemann, 2007 Eversheim W.: Innovation Management for Technical Products, Springer-Verlag Berlin Heidelberg, 2009 Number of active teaching lessons Other

lessons 0 Lectures: 30




Teaching methods Lectures: Oral presentation, discussion with students, presentation of students papers (individual and teams), checking of how the students understand presented material. Practice classes: Explanation of unclear facts and concepts from the lectures; establishing of materials, discussions between students and individual and groups presentation of specific themes.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Activities during lectures 10,0 Written exam

-

Practice lessons

0 Oral exam 60,0


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Data Analysis Teacher (Name, first letter of one parent’s name, last name): Jasna, Đ. Soldić-Aleksić Subject status: Compulsory Number of ECTS: 8 Prerequisite: none Subject objective The subject objective is to provide students with the necessary theoretical knowledge and practical skills how to use software packages for data analysis. Main topics are statistical software package IBM SPSS (Statistical Package for Social Sciences) and electronic spreadsheet programs, as well as the combined usage of these programs and their connections with data base software. Subject outcome It is expected that students at the end of semester, after the period of their regular attendance and active participation in the subject course, will acquire the necessary theoretical knowledge of the software tools for business data analysis, and also be capable to carry out the concrete data analysis assignments. We believe that in this way students will be able to conduct practical analytical jobs in various business domains, which is based on the synthesis of basic theoretical knowledge, practical skills and the ability to interpret generated results. Subject content The content of the subject is organized in the following way: basics of the electronic spreadsheet programs, main procedures and functions of the program – group functions and specifics of the particular functions; an advanced techniques for formula creations; internal data bases (i.e. lists) and the relevant operations: data sorting, filtering and work with D-functions; work with external data bases – importing data from data base software programs; pivot tables; “What-If” analysis – program tools for this analysis; business modeling and simulations in electronic spreadsheet programs; data exchange with other program applications; the basics of the work in the IBM SPSS program environment; work with IBM SPSS data files; data transformation; ranking, sorting and filtering of data; data exchange with other program environments; work with chosen statistical procedures in IBM SPSS package. Literature

1. Applied Data Analysis, J. Soldic-Aleksic, Publication Center at the Faculty of Economics, Belgrade, 2011.

2. Discovering Statistics Using SPSS, A. Field, 3rd edition, SAGE Publications, Ltd. London, 2009. 3. Microsoft Excel Data Analysis and Business Modeling, W.L Winston, Microsoft Press,

Washington, 2004, 4. 4. Data Analysis & Decision Making with Microsoft Excel, Albright, S.C., Winston, W.L.,

Zappe, C.J., South-Western Cengage Learning, 2009. Number of active teaching lessons Other lessons

0 Lectures: 4

Practice classes: 3



Teaching methods Lectures and practice classes are conducted in the computer laboratory applying the basic principle – “one student work at one computer”. Apart from classical lecturing, it would be applied case analysis and discussions with students; individual and/or group students work on concrete analysis; tests; seminar works etc.


40

Practice lessons

Oral exam 20


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Databases Teacher (Name, first letter of one parent’s name, last name): Aleksandra T. Zečević Subject status: Compulsory Number of ECTS: 5 Prerequisite: Subject objective The aim of this course is to acquaint students to modern database management systems, as well as specific technologies for data processing and data models, and specific theories which to determine and design a particular database. Special attention is given to the design of databases and the development of business applications. Subject outcome With the acquired theoretical and practical knowledge, the students will be able to design and administer a database for different needs in business information systems. Subject content Theory lessons 1. Basic concepts. Database architecture; 2. Types of databases. Structure of relational databases. Relational operations. The relational algebra; 3. SQL. Structure of SQL queries. SQL data definition; 4. Database management systems (DBMS). Creating databases, tables, indexes. Inserting, deleting and updating data. Using queries; 5. Aggregate functions. Database administration; 6. Constraints. Database integrity and security. Entity integrity: keys; 7. Normalization process. Normal forms. Normal forms of keys and domains; 8. Decision- support systems. Data warehousing. OLAP (Online Analytical Processing); 9. Web databases. Practice lessons: practice classes Exercises of practical examples will follow the lectures in the area of databases, in particular database system. Using the programming language in conjunction with HTML, to access and manipulate data in web databases. Literature 1. Thomas Connoly, Carolyn Begg: Database Systems: A Practical Approach to Design, Implementation and Management, Addison-Wesley, 2009. Number of active teaching lessons Other lessons Lectures: 30




Teaching methods Lectures. Each teaching unit followed by a presentation and each is an introduction to the work to be performed in the exercises. Exercise. Performed in IT Center. Also, the exercises are performed by the system of one student - one computer. The aim of the exercises is to enable students to create and administer databases.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Project development 10 Written exam

60

Colloquium/a 30

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Decision Theory Teacher (Name, first letter of one parent’s name, last name): Dragan, B. Azdejković, Zoran Z. Popović Subject status: Compulsory Number of ECTS: 7 Prerequisite: - Subject objective: The aim of this course is to inform students about the results of normative decision theory. They will learn to set various problems, identify and analyse all elements relevant for proper decision making. They will also get acquainted with the methods of decision making under conditions of certainty, risk and uncertainty, sequential decision making, decision in a group and bargaining. Results of behavioural theory will help students to recognize systematic mistakes done in decision making and its causes, so that they can avoid cognitive traps. Subject outcome: Students will be able to: properly formulate and present a variety of business problems, apply normative methods in solving the above-mentioned problems and use results as support to decision, determine economic feasibility of collecting additional information and adjust the risk (to reliability of the information), mitigate or completely avoid negative effects of intuitive decision making, learn how to prepare for negotiations and how to implement them successfully. Subject content Normative decision theory: Process of decision making, Decision maker and his preferences, Model of decision making (table and tree of decision making), Methods of decision making under conditions of uncertainty (Maximax, Maximin, Hurvic, Savage, Laplace), Decision making under conditions of risk (maximum expected value), Additional information and its price (Bayes’ theorem), Sequential decision making, Multi attribute decision making, Basics of game theory, Group decision making (theories of Arrow and Sen and analysis of voting rules). Behavioral decision theory, Unlimited and limited rationality (Simon theory, Kahneman and Tversky theory), Defining objectives (hierarchy and interrelationships), Generating alternatives, Group as decision maker, Choice of solutions and analysis of the results. Literature Goodwin, P., and G. Wright, Decision Analysis for Management Judgment, Jon Wiley and Sons, Chichester, 2004. Martin J. Osborne, An introduction to game theory, Oxford University Press, August 2003. Number of active teaching lessons Other lessons

0 Lectures: 4 Practice classes: 2



Teaching methods Lectures, exercises, presentation, colloquium.


30

Practice lessons

8 Oral exam 30

Colloquium/a 16 Semester papers 8

http://www.oup-usa.org/

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Econometric Time-series Analysis Teachers: Zorica L. Mladenović, Aleksandra Č. Nojković Subject status: Compulsory Number of ECTS: 8 Prerequisite: Subject objective The course is designed to introduce time-series econometric tools and to gain understanding of the characteristics of macroeconomic and financial time series. The course emphasises the application of statistical and econometric methods in order to analyse real economic data by using EVIEWS software. Subject outcome Students have adopted theoretical principles of econometric time-series modelling. Students have acquired theoretical and practical knowledge of modelling specific features of economic time series. Students are trained to apply econometric time-series models to quarterly and monthly data in order to adequately describe time-series dynamics and derive properly economic conclusions.

Subject content Descriptive methods. Basic concepts: stationarity, autocovariance and autocorrelation functions. Linear process. Univariate stationary time-series models: autoregressive models, moving average models and autoregressive moving average models. Univariate nonstationary time-series models. Random walk. Autoregressive integrated moving average models. Unit-root tests. The Box-Jenkins modeling approach: identification, parameter estimation and adequacy testing. The parameter estimation methods (method of moments, non-linear least squares method and method of maximum likelihood). Seasonal time series. Structural break. Multivariate stationary time-series models. Vector autoregressive model. Causality testing. Cointegration. The Engle-Granger two-step approach. Literature 1. Enders, W. (2009), Applied Econometric Time Series, Wiley, 3rd ed. 2.Mills, T.C. and R.N. Markellos (2008), The Econometric Modeling of Financial Time Series, Cambridge University Press, 3rd ed. 3.. Tsay, R.S. (2010), Analysis of Financial Time Series, Wiley, 3rd ed. Number of active teaching lessons Other lessons Lectures: 60




Teaching methods Theoretical classes are devoted to presentation of theoretical models and their application in various economic researches. Practical classes take place in computer room with the purpose of modelling real macroeconomic and financial time series by using EVIEWS software.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Activities during lectures 5 Practical part of the exam

10

Practice lessons

5 Theoretical part of the exam 50

Colloquium/a 30 ..........

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies:, Undergraduate academic studies Subject title: Econometrics Teacher (Name, first letter of one parent’s name, last name): Aleksandra Č. Nojković Subject status: Compulsory Number of ECTS: 10 Prerequisite: None Subject objective The objective of this course is to make students well-acquainted with the basic econometric methods and prepare them for empirical work in economics. In particular, topics will include specification and estimation of econometric models, testing, and forecasting. The course gives students the opportunity to use actual economic data to test economic theories. Subject outcome Students have adopted the principles of econometric modeling within the Classical Linear Regression Model framework. Students are trained to estimate and predict from simple econometric models. Students learn to interpret the results of the econometric analysis. Students are trained to solve econometric problems based on concrete economic data. Students are introduced to basic use of statistical software packages (EViews or equivalent econometrics program). Students are trained to apply the econometrics in state administration, finance, or other analytical work

Subject content Theory lessons Introduction. The Classical Linear Regression Model (CLRM): Simple and Multiple Regressions. The Assumptions, methods of estimation, small and large sample properties of the estimators. Hypothesis testing and prediction. Testing linear restrictions. Dummy variables. Multicollinearity. Misspecification errors. Stochastic repressors and Instrumental variable estimation. Heteroskedasticity and autocorrelation. Generalized Least Squares (GLS). Simultaneous Equation Models. Fundamental Issues in Simultaneous Equation Models. The problem of identification. Methods of estimation.

Practice lessons: practice classes, other forms of teaching, study research work In practice class students are solving econometric problems (numerically or by using econometrics software). Literature 1. Verbeek, M. A Guide to Modern Econometrics, 4th ed., Wiley, 2012 2. Wooldridge, J.M. Introductory Econometrics: A Modern Approach, 5th ed., Cengage Learning, 2012 3. Asteriou, D. and Hall, S.H., Applied Econometrics, Palgrave, 2011 Number of active teaching lessons Other lessons

0 Lectures: 60




Teaching methods

Teaching is realized through lectures and practice classes. Lectures include presentation of the theoretical framework and empirical applications of presented methodology. In practice class students are solving numerically concrete tasks. One part of the practice classes are held in the computer lab in order to familiarize students with the use of statistical software in solving econometric problems.


30

Practice lessons

5 Oral exam 40


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Economic Statistics Teacher (Name, first letter of one parent’s name, last name): Gorana P. Krstić, Dejan B. Šoškić Subject status: Compulsory Number of ECTS: 7 Prerequisite: None Subject objective The goal of the Economic Statistics course is to introduce students to data collection methodology, show how indicators are calculated, and present the advantages and drawbacks of the methodologies and indicators used. Economic Statistics aims at enabling students to gain greater knowledge of statistical data and better understand indicators they will encounter and use in their work. Subject outcome Students who complete this course should become able to use national and international sources of data; use available statistical data in economic analysis, in a critical fashion; apply suitable methods to calculate statistical indicators, taking into account the advantages and limitations of the methods (methodologies) chosen, and appropriately interpret the results obtained. Subject content The content of the Economic Statistics is based on general principals of economic theory and statistics. It covers the following main areas: Economic activity (System of National Accounts, Productivity, Short-term Economic Indicators), Public Finance, Prices, Labour Market, Living Standard, External Macroeconomic Position, Financial Sector. Literature 1. United Nations, System of National Accounts 2008, 2009. 2. Government Finance Statistics Manual, 2001. 3. Borjas, G. Labor Economics, Sixth Edition , McGraw-Hill Higher Education, 2012. 4. Edward N. Wolf, Poverty and Income Distribution, Second Edition, Wiley-Blackwell, 2009. 5. DeFusco, R.A., Dennis W. McLeavey, Jerald E. Pinto and David E. Runkle, Quantitative Methods for Investment Analyses, 2nd edition, CFA Institute, 2004. 6. IMF, Monetary and Financial Statistics Compilation Guide, IMF, 2008. Number of active teaching lessons Other

lessons 0

Lectures: 4

Practice classes: 2



Teaching methods Teaching takes the form of lectures and practical classes aligned with the structure of the course. The lectures will explain methodology and concepts in each field, using practical examples in discussion with the students. The practical classes will focus on examples and practical problems that clarify issues covered in the lectures, and will involve discussions and independent presentations by students. Particular attention will be devoted to calculating indicators for Serbia using the latest available data published by the Republican Statistical Office (RSO). Students will also be able to investigate selected areas in greater detail by writing study research papers.

Grading (maximum number of points 100)

Pre-examination obligations Points Final exam Points Activities during lectures 4 Written exam

60

Practice lessons

4 Oral exam

Colloquium/a 30 .......... Semester papers 2

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Economic-Mathematical Methods and Models Teacher (Name, first letter of one parent’s name, last name): Backović M. Marko, Popović Ž. Zoran, Prica Z. Ivana, Stamenković S. Mladen Subject status:Compulsory Number of ECTS: 10 Prerequisite: Subject objective The goal of the subject is applying and development of different quantitative analysis models used for a successful business management. These models should provide a decision maker exact information in order to select optimal solution of various business problems. Subject outcome Students should be able to apply and develop different quantitative methods in decision making process of various business situations in order to get exact information used for the optimal solution of business problem. Subject content Theory lessons Subject is divided into nine parts focused on studying various method and models for optimal management of a decision maker. Subject is organized as follows: 1. Economic-mathematical functions, 2. Queuing theory, 3. Inventory models, 4. Linear programming, 5. Transportation problem, 6. Game theory, 7. Network models and project management, 8. Dynamical programming, 9. Markov models. Practice lessons: practice classes, other forms of teaching, study research work Practice lessons are implemented through solving numeric examples of economic problems, most frequently based as business decision problems of a company. Literature

1. Hillier F.S., Lieberman G.J. (2001), Introduction to Operations Research, McGraw-Hill. Number of active teaching lessons Other lessons Lectures: 4

Practice classes: 4



Teaching methods The basic form of the lectures, which are (mostly) run through the proper presentation and numerical examples. Students are encouraged to ask questions the teacher for an explanation. Exercises are performed by solving numerically the set and hypothetical economic problems associated with most of the business decisions of companies.


35

Practice lessons

Oral exam 35


Title of the curriculum/curricula: (E00) Economy, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: International Marketing Teacher (Name, first letter of one parent’s name, last name): Rakita M. Branko, Mitić J. Sanja i Marković Z. Dušan Subject status: The subject is compulsory at the modules Marketing, Management, Trade Management and Marketing and International Economics and Foreign Trade, and optional at the module Tourism and Hotel Industry Number of ECTS: 7 Prerequisite: No prerequisite Subject objective The goal of the subject is to introduce students to basic concepts, principles, strategies and skills necessary to succeed in international market. Subject outcome Students are enabled to understand the scope of international marketing, to obtain information on international markets, to do advance marketing activities planning and international markets targeting, to manage international marketing mix instruments and business operations in international markets. Subject content Theory lessons Basic concepts of international marketing and the following thematic areas are studied first: international marketing research, international market targeting, international market entry strategies. Specific international marketing activities and marketing mix instruments through which companies penetrate into targeted international markets are then analysed. At the end of the course students are introduced to: management of international competitiveness, international brand management, international sales management, and internet marketing. Practice lessons: practice classes, other forms of teaching, study research work The goal of practice lessons is to assess students’ understanding of lectured units, solve theoretical and practical questions, analyse case studies, organize debate teams, prepare presentations, organize roll play activities, homework and essays presentations etc. Literature

• Terpstra V., Foley J., Sarathy R, 2012, International Marketing, Naper Publishing • Keegan W. J., 2011, Global Marketing Management, Prentice Hall

Number of active teaching lessons Other lessons: 0 Lectures: 4

Practice classes: 2



Teaching methods Ex cathedra, interactive lessons, case study analysis, roll play activities, research work, creative workshop, home work presentations, teamwork presentations


50

Practice lessons 5

Oral exam 10


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Management Information Systems Teacher (Name, first letter of one parent’s name, last name): Rade M. Stankić Subject status: Optional Number of ECTS: 7 Prerequisite: Subject objective The objective of this course is to introduce students to contemporary theoretical and practical aspects of management information systems. By gradually introducing students to contemporary tools for creating business applications the goal is to train students to use new information technology for making business decisions. Subject outcome With the acquired theoretical and practical knowledge, students will be able to use information technology, information systems, applications software and database management systems in developing applications to solve specific problems in management. Knowledge of specific software tools enables students’ efficient use of information and communication technologies in business decision making. Subject content Theory lessons Information Technologies and Informatiоn Systems; Business Information Systems; Systems Software; Applications Software; Database Mаnagement Systems; Development of Information Systems; Management Information Systems; Decision Support Systems; Expert Systems; Electronic Data Interchange (EDI); Business Information Systems and Standardization; Business Information Systems Protection; Internet; Economic potential of the Internet; World-Wide Web; E-Business; Electronic Banking; E-Commerce; Electronic Marketing; Computer Networks; ERP software. Information Technology for Management. Practice lessons: practice classes, other forms of teaching, study research work: Creating a Web site; Working with a spreadsheet; Working with the relational database management system. Literature Laudon K., Laudon J., Management Information Systems, (12th Edition), Prentice Hall, 2011. Number of active teaching lessons Other lessons Lectures: 60




Teaching methods For each teaching unit adequate presentations are prepared, and some of the units include the use of the Internet. Active participation of students is planned in the form of presentations which are individually or team prepared as a complement to the topic. At the end of each topic a discussion is held. The exercises take place at the Center for Information Technology.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Presentation 10 Written exam 30 Colloquium/a 10 Oral exam 30 Practice lessons 20

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Marketing Research (MR) Teacher (Name, first letter of one parent’s name, last name): Prof. dr Srđan M. Bogosavljević, Dr Ivana Z. Prica, Dr Biljana Ž. Chroneos Krasavac, , Marina P. Petrović, Lazar A. Čolić Subject status: It is compulsory for the following curricula: Marketing (III); Trade Management and Marketing (III); Finance, Banking and Insurance (IV); Tourism and Hotel Industry (IV). For the rest of curriculum (mentioned above) this subject is optional. Number of ECTS: 7 Prerequisite: Student should be familiar with the basics of Elementary Statistics. Subject objective Getting familiar with the process and practical aspects of MR, from research design to interpretation and implementation of the results obtained using the Marketing Information Systems. Understanding the role of MR in the contemporary business environment and its importance for efficient business decision-making and maximization of the business results. Subject outcome By the end of this course students should be able to individually and critically approach the MR problems in real life business environment and to work in teams that are either performing or utilizing MR. Subject content Lectures Process and Role of MR; Design and Implementation of MR; Data Collection; Secondary and Standardized sources; Explorative Research: Qualitative Research and Observational Methods; Descriptive Research: Attitude Measurement and Questionnaire Design; Causal Research; Sampling and Sample Size; Data Analysis Techniques and Application: Regression Analysis; Discriminant and Canonical Analysis; Factor and Cluster Analysis; Multidimensional Scaling and Conjoint Analysis. Practice classes Analysing theoretical concepts of MR through empirical examples. Implementation of data analysis through the empirical examples using SPSS software. Literature Aaker, David A., Vineet Kumar, and George S. Day. Marketing research. John Wiley & Sons, 2008. Number of active teaching lessons: 90 Other lessons Lectures: 60




Teaching methods Teaching is realised through lectures and practice classes. Lectures deal with the theoretical framework and empirical applications of the presented methodology. In practice classes students are solving concrete empirical tasks.


30

Practice lessons Oral exam 30 Colloquium/a 40 Semester papers

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Nonparametric Statistical Methods Teacher (Name, first letter of one parent’s name, last name): Vladimir R. Vasić Subject status: Optional Number of ECTS: 7 Prerequisite: no Subject objective The goals of course are statistical methods that are not based on standard (usually unfulfilled) assumptions of classical statistical procedures of normality and homogeneity of variances population. In the case of disturbance of these assumptions it is more efficient to use one of the non-parametric procedures based on ranked observations or methods based on repeated patterns. Subject outcome After completing this course, students will be able, in analysing the complex variable phenomena in economics and in business, to choose efficient statistical methods independently and with the help of the chosen software application,. Students will be able to analyse in detail the preconditions on real data and to understand the logic of most nonparametric methods in the case of one, two or more samples. Subject content Parametric and nonparametric statistical methods. The basic principles of the nonparametric methods of conclusion. Randomization method of Ronald Fisher. Statistical tests based on ranked observations. Testing locations in the case of one and two dependent samples. Testing locations in the case of two independent samples. The problem of dispersion in the case of two samples. Examination of the general difference of two populations. Testing the equality of proportions of the two sets. Non-parametric tests in the case of three or more samples. Linear statistics of ranked observations. Asymptotically distribution of statistics based on ranks. Asymptotic power of the test and Pitman asymptotic relative efficiency. Nonparametric methods of estimation: estimate and confidence interval for the median, confidence interval for quantiles of distribution. Nonparametric regression and correlation analysis. Statistical methods based on repeated samples. Empirical distribution functions and plug-in principle. The bootstrap method. Jackknife estimate. Literature Lovric, M. Nonparametric methods of statistical inference. Faculty of Economics, Belgrade 2006. Sprent, P. and N. Smeeton. Applied Nonparametric Statistical Methods, 4 ed. Chapman & Hall 2007 Hollander, M. and D. Wolfe. Nonparametric Statistical Methods, 2 ed. John Wiley & Sons, New York 1999. Number of active teaching lessons Other lessons Lectures: 60




Teaching methods Lectures are based on explaining the logic, concepts and principles of non-parametric statistical methods. During practice lessons attention is paid to solving real examples from the business environment and where modeling is done in the PC center using adequate statistical software. The group-interactive work is implied, including: group solving tasks, multimedia software tools, the use of Internet resources with Java applets and simulations.


20

Practice lessons

Oral exam 40

Colloquium/a 20 .......... Semester papers 10

Title of the curriculum/curricula: Economics, Business Management, and Statistics Type and level of studies: Undergraduate academic studies Subject title: Operations Research Teacher (Name, first letter of one parent’s name, last name): Branko V. Urošević Subject status: Compulsory Number of ECTS: 10 Prerequisite: None Subject objective The main objective of this course is to teach students some basic static and dynamic optimization methods, and implementing them in quantitative investment analysis and other areas of finance and economics. The focus is on practical relevance of methods. Students are taught how to think and work indepedently and recognize and solve relevant problems. Background in finance and mathematical finance is not assumed. Acquired knowledge in quantitative methods of investments presents very solid foundation for studying finance and economics at the top graduate level. Subject outcome Participants are trained to independently formulate and solve several important classes of optimization problems that appear in investment science. Among others, they learn methods of nonlinear and dynamic programming that appear directly in investment practice. They learn also basics of stochastic calculus. For participants without prior knowledge in finance and investments, this course provides an excellent opportunity to learn basic concepts of security valuation, portfolio analysis, and option theory. This makes participants well qualified for jobs in finacial institutions. Subject content Theory lessons The course consists of three parts. The first part serves as a refresher of linear algebra, theory of convex sets and functions and static optimization with and without additional constraints. In the second part participants learn how to apply optimization methods to value and select optimal portfolios of fixed income (bonds) and variable income (stocks) assets. In the third part options are studied. Valuation methods in discrete and continuous time and carefully developed and applied for pracing American and European put and call options as well as exotic options. Dynamic programming and rudiments of theory of stochastic differential equations are discussed in the context of option pricing.

Practice lessons: practice classes, other forms of teaching, study research work Participants are expected to work through numerous exercises as well as to perform empirical studies on real financial data.

Literature 1. David Luenberger, Investment Science, Oxford University Press, 1997 2. Fundamental Methods of Mathematical Economics, 4th Edition, McGraw-Hill, 2006 Number of active teaching lessons Other

lessons 0

Lectures: 4

Practice classes: 4

Other forms of teaching:0

Study research work:0

Teaching methods Lectures: Ex-catedra Practice lessons: problem solving sessions, computer exercises, two empirical projects


60 100

Practice lessons

Oral exam


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Programming Languages Teacher (Name, first letter of one parent’s name, last name): Aleksandra T. Zečević Subject status: Compulsory Number of ECTS: 5 Prerequisite: Subject objective The aim of this course is to introduce students to modern programming languages. Special attention is given to their use for the development of business applications and web applications. Subject outcome With the acquired theoretical and practical knowledge, the students will be able to solve and programming various types of problems and tasks. Subject content Theory lessons Object-oriented programming – An overview of Java (declaring objects, statements, class fundamentals, subclasses); Programs, data types, variables; Control statements and logical operators; Arrays; Classes and methods. The Applet class; Graphics – AWT classes; Introducing Swing; Database connectivity – JDBC; Script language – PHP, language basics; Data types; Operators and expressions; Decisions and loops; Arrays; Creating and accessing strings; Functions; Handling HTML forms with PHP; Supporting web databases. Practice lessons: practice classes Development of practical examples to follow lectures in the Java programming language, and then the scripting language PHP, which is especially important for web applications and databases. Literature 1. Herbert Schildt: Java, The complete reference, Oracle Press, 2011. 2. Steven Holzner: PHP5: The Complete reference, McGraw-Hill Osborne Media, 2007. Number of active teaching lessons Other lessons Lectures: 30




Teaching methods Lectures and exercises will be held in the premises of IT Center. Preparation and presentation of business applications (solving real problems), is the basis for the realization of the educational process.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Project development 10 Written exam

40

Colloquium/a 30 Oral exam 20

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Quality management Teacher (Name, first letter of one parent’s name, last name): Dušanka V. Ušćumlić, Jasna B. Babić Subject status: Compulsory from a group of 2subjects Number of ECTS: 7 Prerequisite: - Subject objective: Mastering of: knowledge and skills in theory of quality in general and in quality of products, in standardization; basic principles of quality management (TQM, processes, quality management systems); seven basic tools of quality. Subject outcome: Knowledge of: quality level and quality characteristics of material products; preservation of quality level; base for standardisation (ISO 9000, 14000, 22000 etc); principles and tasks of quality management. Knowledge and application of the assortment of seven basic tools of quality (flow chart, histogram, Pareto diagram, check sheets, Ishikawa diagram, control chart, scatter diagram). Subject content

Theory lessons: 1. Quality; 2. Quality of products (quality characteristics, integral quality, degree of quality); 3. Standardization; 4. Quality management (TQM, Process management); 5. Quality management systems (ISO 9000, ISO 14000 etc.); 6. Tasks of quality management (planning, control, assurance, improving); 7. Quality management tools (seven “basic tools“); 8. Costs of quality

Literature Hoyle D.: Quality Management Essentials, Butterworth-Heinemann, 2007 Number of active teaching lessons Other

lessons 0 Lectures: 60




Teaching methods Lectures: Oral presentation, discussion with students, presentation of students papers (individual and teams), checking of how the students understand lectured material. Practice classes: Explanation of unclear facts and concepts from the lectures; establishing of materials, discussions between students as well as individual and group presentation of specific themes.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Activities during lectures 10,0 Written exam

-

Practice lessons

0 Oral exam 60,0


Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Quantitative Finance Teacher (Name, first letter of one parent’s name, last name): Miloš Č. Božović Subject status: O Number of ECTS: 6 Prerequisite: none Subject objective The course studes quantitative methods of financial economics applied to corporate finance and other related areas. These methods allow us to understand thoroughly the important issues that arise in making financial decisions in companies, including optimal capital structure, optimal ownership structure, valuation of risky projects and companies as a whole, as well as pricing of financial instruments used by companies to finance their operations. Subject outcome At the end of the course the student should master the basic concepts and quantitative methods used in corporate finance, and be able to apply them in theory and practice. Subject content Theory lessons Introduction – quantitative methods in corporate finance Capital Asset Pricing Model (CAPM) – basic definitions; capital market line and security

market line; empirical studies of CAPM; extensions of CAPM - factor models Valuation of risky projects – criteria for selection of investments (net present value, internal

rate of return); valuation of securities; risks related to investments in securities Theory of dynamically complete markets – Arow-Debreu securities and risk-neutral

probabilities; complete markets; Arow-Debreu securities in the market with many time periods Options – basic concepts and institutional aspects; binomial trees; Black-Scholes formula; put-

call parity Capital structure – the structure and cost of capital; First Modigliani-Miller theorem, Second

Modigliani-Miller theorem; risky debt; First Modigliani-Miller theorem in the case of a risky debt; Second Modigliani-Miller theorem in the case of a risky debt; First and Second Modigliani-Miller theorems: summary and criticism; corporate income tax; Third Modigliani-Miller theorem; bankruptcy costs; personal income tax; Miller theorem; Meckling and Jensen (1976) theory; Myers (1977) theory; Myers and Majluff (1984) theory

Models ownership structure –static model of moral hazard and optimal ownership structure; dynamic model of moral hazard and the evolution of ownership structure

Methods of company valuation – methods based on the balance sheet; methods based on the income statement; methods based on discounted cash flows; other methods

Corporate bonds Warrants and convertible bonds

Practice lessons: practice classes, other forms of teaching, study research work Practice classes with exercises and examples Literature

1. Jonathan Berk & Peter DeMarzo, Corporate Finance, Pearson (2010) Number of active teaching lessons Other lessons

0 Lectures: 3

Practice classes: 2



Teaching methods The course consists of lectures and exercises according to the course content. Lectures will be dedicated to theoretical concepts, which will be illustrated through examples in the practice classes.

Grading (maximum number of points 100) Pre-examination obligations Points Final exam Points Homework assignments 40.00 Written exam 60.00

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Sampling Theory and Planning of Experiments Teacher (Name, first letter of one parent’s name, last name): Ljiljana M. Petrović Subject status: Compulsory Number of ECTS: 7 Prerequisite: Subject objective The main objective of this course is to prompt students to learn the classical theory of the samples (for the finite population) and the method of experiment. The sampling theory shows different ways of selecting samples, evaluation on selected samples and methods of analysis of the collected data. It presents the basic models of planning experiments that apply for minimizing of the experimental error. The sampling theory evaluates various characteristics of the population based on the observation of one part of the population with no change in the population, and in planning experiments we act on one part of the population in order to evaluate the effect of that action on the entire population. Subject outcome Students learn about different methods of sample selection, the evaluation of the selected samples, the application of different models of planning experiments in order to evaluate the effect of activity of various factors on the observed population and the methods of analysis of the collected data. Sampling theory and planning of experiments are widely used in various scientific disciplines. Subject content Theory lessons The course consists of two parts. The first part is sampling theory with standard sampling: simple random sampling, unequal probability sampling, stratified random sampling, systematic sampling, cluster sampling, multistage design, double sampling and treats the use of auxiliary data with ratio and regression estimation. The second part is is devoted to analysis of variance and different experimental plans: randomized-block designs, Latin-square design, factorial experiments and designs for factorial experiments. Literature 1. Cochran, W. G. , Sampling Techniques, 3rd edition, Wiley, New York, 1977. (selected chapters) 2. Montgomery, D.C., Design and Analysis of Experiments, 6th edition, John Wiley & Sons, 2005. (selected chapters) Number of active teaching lessons Other lessons Lectures: 4

Practice classes: 2



Teaching methods In lecture classes the theoretical elements of the subject matter are discussed, with many illustrative examples, while examples of tasks dominate on practice lessons. The practice lessons are primarily interactive. Active engagement can help a student be exempt from taking a part of the preliminary exam (colloquium). The colloquium comprises material covered in lectures and practice lessons from the beginning of the school year to the day of the tests.


20

Practice lessons

40 Oral exam 40

Colloquium/a .......... Semester papers

Таble 5.2 Course specification Study program/Study programs: Economy, business management and statistics Type and level of studies: Undergraduate academic studies Course title: Technology Policy and Development Lecturer (Name, Middle name, Surname): Ljubodrag B. Savic, Milorad C. Filipovic Status of the course: required ЕСTS number: 7 Requirement: Aim of the course: To provide students with knowledge about theoretical and methodological aspects of courses of action, factors and indicators of measuring technological development. Students will be able to recognise the importance of knowledge, innovation and technology transfer to strengthening the competitive position of the company and the national economy. Result of the course : Mastering the teaching students will be able to actively and effectively participate in solving complex problems related to the company's development strategy and macroeconomic policy of the country, especially in finding solutions and measures to encourage innovation, technology transfer and the overall technological development. Сourse content Lectures: The concept and the importance of knowledge, innovation, technology development and technology transfer; Factors of technological development; Indicators, methods of measurement and prediction of the technology development; Scientific research systems, strategies and policies of technological development; Innovation and enterprise development strategies; Concept and types of technology transfer; Technological development policies of individual countries; Analysis and Technological Development of Serbia. Practical teaching: In practice classes students are expected to participate interactively throughout the preparation and presentation on certain issues and discussions. The practice classes are a combination of topics from lectures, presentations of matter that is not covered in the book, but witch is related to the syllabus, the analysis of specific case studies and work presentations of student groups on specific issues relevant to the course. Literature 1. Fulvio Castellacci, Stine Grodal, Sandro Mendonca, Mona Wibe, , Advances and challenges in innovation studies, Journal of Economic Issues, 2005.

2. N. David, Weil Economic Growth, Pearson Addison Wesley, 2005.

3. Vernon W. Ruttan, Technology, Growth, and Development: An Induced Innovation Perspective, Oxford University Press, 2000.

4.A.Thirwall: Growth and Development, Macmillan press, 2004.

1

Number of lessons in active teaching Other lessons Lectures:

4 Practical lessons: 2

Other types of lessons:

Research work:

Teaching mеthods: Lectures, practical teaching, case studies, processing, preliminary exams, presentation of individual and team work of students, questions, discussions and visits to individual institutions.

Evaluation of knowledge (maximum number of points: 100) Pre-exam requirements points Final exam points Аctivity in class 4 Written exam Practical lessons 8 Oral exam 60 Preliminary exams 16 .......... Seminars 12 Knowledge evaluation methods can be different. This table contains only a number of options: (written exams, oral exams, project presentation, seminars etc.) Маximum length of one А4 page.

2

Title of the curriculum/curricula: Economics, Business Administration and Statistics Type and level of studies: Undergraduate academic studies Subject title: Theory and Models of Decision Making Teacher (Name, first letter of one parent’s name, last name): Dragan, B. Azdejković, Zoran Z. Popović Subject status: Obligatory / Elective Number of ECTS: 5 Prerequisite: - Subject objective: The aim of this course is to inform students about the results of normative decision theory. They will learn to set various problems, identify and analyse all elements relevant for proper decision making. They will also be introduced with methods of decision making under conditions of certainty, risk and uncertainty, sequential decision making, decision in a group and bargaining. Methods are critically analyzed through explaining their weaknesses as well as the advantages of formal compared to the intuitive decision making. Subject outcome: Students will be able to: properly formulate and present a variety of business problems, apply normative methods in solving above mentioned problems and use results as support to decision, determine economic feasibility of collecting additional information and adjust the risk (to reliability of the information), formally present the choice between actions to be implemented over a longer period of time, recognize different negotiating situations and accordingly choose the appropriate strategy. Subject content Normative decision theory: Process of decision making, Decision maker and his preferences, Model of decision making (preference relations and terms of rationality), Methods of decision making under conditions of uncertainty (Maximax, Maximin, Hurvic, Savage, Laplace), Decision making under conditions of risk (maximum expected value), Decision making under conditions of risk – use of cardinal utility by von Neumann and Morgenstern, Additional information and its price (Bayes’ theorem), Sequential decision making, Multi attribute decision making, Basics of game theory (games with zero and non-zero sum, bargaining games) Basics of social choice theory. Descriptive decision theory: Main results of behavioral decision theory (Theory of Herbert Simon and Theory of Daniel Kahneman and Amos Tversky) Literature Goodwin, P., and G. Wright, Decision Analysis for Management Judgment, Jon Wiley and Sons, Chichester, 2004. Martin J. Osborne, An introduction to game theory, Oxford University Press, August 2003. D.E. Bell, H. Raiffa and A. Tversky (eds.), Decision making: Descriptive, normative, and prescriptive interactions, Cambridge University Press, Cambridge, 1988. Number of active teaching lessons Other lessons

0 Lectures: 2 Practice classes: 2



Teaching methods Lectures, exercises, presentations, colloquium.


30

Practice lessons

5 Oral exam 30

Colloquium/a 25 Semester papers 5

http://www.oup-usa.org/

Title of the curriculum/curricula: (E00) Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Theory and Policy of Financial Statements Teacher: Kata I. Škarić Jovanović Subject status: Compulsory Number of ECTS: 10 Prerequisite: No Subject objectives: Starting from the knowledge which has been gained trough studying Financial Accounting and other subjects dealing with the operating, financial and investment activities of an enterprise, students should acquire the knowledge of how to identify the information needs of users of financial statements. They should also learn that the financial reporting is an activity which is characterised by a high degree of public accountability; and that reliability of the financial information presented in financial statements is a necessary prerequisite for the development of financial markets, as well as the economy as a whole. Subject outcome After mastering the teaching units the student is expected to be able to: understand the requirements underlying the assumptions of financial reporting and the proper balancing principles which are the basis of International Financial Reporting Standards; understand the objectives and content of General Purpose Financial Statements of enterprises and banks; assess the implications of individual business activities and apply proper requirements for their presentation in Balance Sheet and Income Statements according to the International Financial Reporting Standards and Framework; define the financial reporting policies objectives and instruments through which implementation of these goals can be realized. Subject content The subject’s content is divided into three parts: In the first part, after the introductory lecture which is dedicated to the concepts, types and tasks of the Balance Sheet and Income Statement, the principles of proper bookkeeping are presented, including the principles of proper inventory, the proper accounting principles in the strict sense and the principles of proper balancing. In the second part, having defined the qualitative characteristics of financial statements as well as elements of financial statements in accordance with the conceptual framework, the content of Balance Sheet and Income Statement and rules which can been used for valuation of items presented in these two financial statements. Besides that, in this part have been presented objectives and contents of other three financial statements Cash Flow Statement, Statement of Changes in Equity and Notes. Special attention is dedicated to politics of balances and latent reserves. Third part is devoted to special characteristics of financial reporting in banks and other financial institutions. In this part the content of the financial statements of banks and other financial institutions are presented. Literature: Rivsine, Collins, Johnson; Financial Reporting & Analysis, second edition, Prentice Hall, Upple Saddle River, New Jersey Number of active teaching lessons Other

lessons:-

Lectures: 60 Practice classes: 60 Other forms of teaching: - Study research work: -

Teaching methods During lectures material will be presented by using Power Point presentations and by elaborating numerous examples from business practice. In practice classes examples from business practice will be used to illustrate problems of recognition and evaluation of the elements which define financial position and profitability of the enterprises and the banks.

Grading (maximum number of points 100) Pre-examination obligationsy

Points Final exam Points

Colloquium/a 40 Oral exam 60

Title of the curriculum/curricula: Economics, Business Management and Statistics Type and level of studies: Undergraduate academic studies Subject title: Trade Management Teacher (Name, first letter of one parent’s name, last name): Stipe M. Lovreta, Goran K. Petković, Zoran P. Bogetić, Dragan Ž. Stojković Subject status: Compulsory Number of ECTS: 7 Prerequisite: none Subject objective The educational objective of this subject it to provide students with knowledge and skills, as well as to enable them to adopt the methods (tools) which managers of global, regional and local companies in the purchase, sale, trade (retail and wholesale) and logistics are required to have. Along with strategic components of trade management, additional objective is to provide students with basic knowledge of operative commercial management, including the managing of operations sector in global trading companies. Subject outcome Learning outcome (knowledge gained) is the ability of students to understand the essence of running a modern trading company, especially considering strategic options and tactical implementation on business functions level. Student should obtain the following knowledge after taking this subject: purchasing, logistics, selling, organizational knowledge, financial management of trade enterprises balanced with marketing efforts. Subject content The subject covers all areas of applied management in trade sector: strategic planning in trading goods and services, financial planning and control, organization and human resources management, implementation and development of the system. The course is structured in three main areas. The first area relates to strategic planning in commercial companies with respect to key global trends in trade, intermediary services, logistics and related industries. The second area covers the financial planning and analysis, performance monitoring, and measures that can be taken to improve performance of the trade companies. The third area relates to the organization of trade and intermediary companies and human resource management in these companies. Literature Berman, Barry and Evans, Joel (2012) Retail Management: A Strategic Approach (12th Edition), Pearson Education Number of active teaching lessons Other

lessons Lectures: 4

Practice classes: 2



Teaching methods The approach to teaching is interactive. It includes: teaching ex cathedra lectures (ppt presentation), as well as lectures in the computer center using appropriate simulation models of real situations in trade management; collective presentation - lecture that is guided by a short student presentation of examples from local and international practices as introduction to thorough interpretation of concepts by teacher. Practice classes include case studies, simulations, discussions, including guests from well known companies, leaders of national and European trade practices.


Practice lessons

5 Oral exam 60

Colloquium/a 30 .......... Presentation

Study program/Study programs: (E00) Economics, business management and statistics, Undergraduate studies Type and level of studies: Undergraduate academic studies Course title: Energy Economics Lecturer (Name, Middle name, Surname): Gojko M. Rikalovic Status of the course: Optional ЕСTS number: 7 Requirement: - Aim of the course Introducing students with theoretical and methodological basics of the economic study of energetics, the role of energetics in the economic development, basic characteristics of this infrastructural economy field, modern energy market functioning, ecological aspects of energetics, and in particular with Serbia’s energy policies and strategy with a view on European integrations. Result of the course Mastering this course will enable the students to understand the influence of energetics on the economic and overall development, to realize the specificities of energy investments, as well as to acquire key methodological knowledge for determining the efficiency of natural resources use. Apart from that, they will also be able to engage in energy policies and strategy, energy price forming and energy parities, to gain an insight into experiences of other countries in this field, models of restructuring the energy operators, as well as in the implementation of Common energy policy instruments in our country. Сourse content Еnergy economics and the subject of its study; The role and importance of energetics and energy; Energy basics and energy balance; Energy sources and investments in the development of capacities; Energy development financing; International energy market, energy imports and exports; Energy policies and economic development; Economics of energy production and use; Economic characteristics of energy sector; Energy efficiency and energy security; The degree of energy dependency and fossil fuels; Renewable energy sources and sustainable energy; Energy and environment; Serbia’s long-term energy development strategy and policies; The Energy Community of South East Europe and the process of European integration of energy sector; The road towards global energetics. Literature Subhes C. Bhattacharyya. 2011. Energy Economics: Concepts, Issues, Markets and Governance. Springer Number of lessons in active teaching Other

lessons

Lectures: 4

Practical lessons: 2

Other types of lessons:

Research work:

1

Teaching mеthods: Lectures; Analysis of examples from practice; Presentation of students’ essays and seminar papers; Visits to EPS and NIS companies;

Evaluation of knowledge (maximum number of points: 100) Pre-exam requirements points Final exam points Activity in class 20 Case study analysis, essays and seminar papers

20 Oral exam 60

.......... Knowledge evaluation methods can be different. This table contains only a number of options: (written exams, oral exams, project presentation, seminars etc.) Маximum length of one А4 page.

2

title of the curriculum/c urricula type and level of ... · mitrović s. radmila, rajić m. vesna...

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