SUMMARY OF COURSE PRESENTATION
PRELIMINARY LESSONS
Course content
The aim of this preparatory course is to understand the main reasons for the failure of the market mechanism and to analyse the government interventions aimed at addressing this problem. More specifically, we will focus our analysis on issues such as externalities, public goods, non-competitive markets and asymmetric information.
Indicative syllabus distribution
- Introduction – Welfare Economics
- External effects
- Public goods
- Non-competitive markets
- Asymmetric information
Summary of Course Presentation
Learning Outcomes:
After successfully completing the course, students should:
- understand the reasons for the failure of the market mechanism,
- analyse government interventions aimed at correcting market failures.x
Course content
The purpose of the course is to present in a concise manner the basic mathematical techniques and statistical methods necessary for understanding the operation of business and competition.
During the course, students become familiar with the basic principles of mathematics and statistical methods and learn how to apply these techniques to practical problems in economics and business.
These mathematical techniques and statistical methods are critical for economic and business professionals, as they provide the tools to analyse and interpret data, predict trends and future developments, and support informed decision-making on economic activity and business performance.
Apart from the obvious independent value of the knowledge provided in the course, this knowledge creates a strong basis for an in-depth understanding of other courses in the Programme.
Overall, through this course, students acquire the necessary skills to become effective analysts and decision makers in the financial sector.
Learning Outcomes:
- Students should understand the basic concepts and methods of statistics, such as probability distribution, sampling, hypotheses, statistical tests and estimators.
- Students should be able to collect, organise, analyse and interpret data using appropriate statistical techniques.
- Students should be able to apply inference techniques to make data-driven decisions.
- Students should be able to formulate and test hypotheses using appropriate statistical tests.
- Students should be able to present the results of statistical analysis clearly and accurately, using tables, graphs and other visual representations.
- Students should understand and use mathematical tools, such as differential and integral calculus, to analyse economic problems.
- Students should be able to develop and analyse economic models that describe the behaviour of markets, consumers and firms.
- Students should be able to apply optimization techniques to solve economic problems, such as determining optimal consumption or production.
- Students should understand the basic principles of static and dynamic analysis and be able to apply them to economic models.
- Students should be able to analyse the equilibrium and stability of economic systems and understand the impact of changes in model parameters.
SUMMARY OF COURSE PRESENTATION
FIRST SEMESTER OF STUDIES
Course content
This course covers topics such as consumer theory, producer theory, game theory, analysis of market forms and behavioural economics. A significant portion of the course is devoted to the study of rational decision making and the modeling of related problems. It also analyzes how individual economic decisions interact in markets with varying degrees of competition, paying substantial attention to the comparative social welfare outcomes produced by different market forms.
Indicative syllabus distribution
1) The Market
2) Demand and Utility
3) Market Demand and Balance
4) Profit maximisation and Cost Curves
5) Offer
6) Monopoly Market
7) Oligopoly
8) Game Theory
9) Behavioural Economics
10) Exchange and Production
Learning Outcomes:
- After successfully completing the course, students should:
- understand the concept of utility,
- analyse the process of optimising consumer choice,
- explain the effect of substitution and income,
- analyse the concept of consumer surplus,
- understand the process of profit maximisation,
- understand the relationship between the long-term and short-term periods and the costs of the business,
- analyse the behaviour of a fully competitive firm,
- understand the process of maximising profits in a monopolistic market,
- analyse the process of oligopolistic pricing through the use of game theory tools
- understand the key elements of its economic prosperity.
Course content:
The course covers in depth the following topics, which are distributed according to the material taught on a weekly basis:
- Introduction to industrial organisation
- Price discrimination
- Product differentiation
- Advertising and information
- Market failure, competition policy and regulatory policy
- Price adjustment
- Relationships between undertakings in vertically related markets
- Entry regulation and access pricing in vertically related markets
- Regulatory policy in practice: Online markets
- Regulation from the regulators’ perspective
Learning outcomes:
Upon successful completion of the course, students will be able to know and apply the basic principles of industrial organisation to the conduct of public policy through competition policy and regulatory policy. More specifically, through descriptive, diagrammatic and mathematical presentation techniques, students will be able to:
- Understand the basic methodological tools of industrial organisation
- Apply advanced pricing techniques, such as price discrimination, as well as product differentiation strategies
- Understand the importance of advertising and information in strategic decision making
- They interpret the equilibrium in a market in terms of static efficiency (business profits, consumer surplus, social welfare, etc.)
- Identify the need for state intervention through competition policy and regulatory policy
- Understand the similarities and differences between competition policy and regulatory policy
- Identify the optimal regulatory policy in terms of pricing
- Identify the optimal regulatory policy in vertically related markets
- Introduction to competition policy, tools, methods, objective
- Efficiency and technical progress, monopoly versus competition, loss of welfare from monopoly
- Market definition, SSNIP test, quantitative techniques for defining relevant markets
- Oligopoly, collusion and antitrust, game theory, explicit collusion, implicit collusion, leniency programme, case studies
- Market structure and strategic competition, concentration, dominant firm theory, contestability
- Mergers, horizontal mergers, vertical mergers, mergers of groups of heterogeneous activities, anti-competitive effects, case studies
- Vertical relationships, exclusive dealing, resale price maintenance, exclusive geographic areas
- Natural monopoly theory, loss of welfare of monopoly, x-efficiency, regulatory tools (price cap regulation, rate of return regulation)
- Monopoly and price discrimination, measurement of monopoly power, intent to monopolize, “substantial facilitation doctrine”
- Commitment, clustering, network effects, switching costs, case studies
- Franchise offer, tender at the tender stage, contractual arrangements
- Presentation of case studies and discussion of selected applied topics. Final overview.
- What determines the extent of competition?
- What is the effect of the number of firms on prices, investment and product variety?
- Which industry conditions are conducive to the creation of cartels?
- Under what circumstances is an industry dominated by a firm?
Course content:
This course provides a thorough presentation of the quantitative methods used in economics to determine the behavior of many economic issues. Indeed, each economic issue consists of two main parts: a) the theoretical part and b) the empirical part. The theoretical part describes how the phenomenon is expected to behave, while the empirical part tries to verify its behaviour in practice using real data. Clearly, each part has its role and contribution to Economics, but without quantitative analysis, it is impossible to verify the validity of economic/financial theories. Thus, this course is very important because it will help students understand how quantitative analysis works in Economics in terms of analyzing data and estimating linear relationships between multiple variables. The tools that students will learn in this course will allow them to analyze data and draw policy conclusions.
Indicative syllabus distribution
- Introduction to Econometrics
- Statistics
Random Variable and Distributions
Statistical Reporting and Case Controls
3. Simple Linear Model
Correlation coefficient, properties and static control
Simple linear model assumptions
OLS estimation and Estimator Properties
Coefficient of determination
Statistical reporting and audits
Forecast
4. Multiple Linear Model
Model presentation and estimation
Presentation with matrix algebra and OLS estimation as well as MLE estimation
Determination Factor and Adjusted Determination Factor
Partial Correlation Coefficient
Statistical reference to the model parameters
Analysis of Variance
Simultaneous Statistical Checks
Forecast
Learning outcomes:
Upon successful completion of the course, the student should be able to analyse data, study the behaviour of phenomena, make predictions and take decisions.
SUMMARY OF COURSE PRESENTATION
SECOND SEMESTER OF STUDIES
Course content:
The course aims to provide students with the necessary knowledge to make strategic decisions in a rapidly evolving and changing international environment. The course includes the teaching of basic theories, tools and techniques in the corporate, competitive international setting. The backbone covers strategic analysis, strategy development, strategic decision making and strategy implementation. Students are encouraged to analyze and think critically as well as apply the concepts and tools taught.
Indicative syllabus distribution
- Necessity of strategy, strategic management concept
- Strategic positioning of the company: analysis of the internal and external environment, strategic mission and vision of a company
- Strategy at the business level – Strategy to develop competitive advantage
- Group-level strategy – Shrinkage, Stability and Growth strategies (diversification strategies, vertical and horizontal integration)
- Methods of implementation of strategic enterprises: acquisitions, mergers, franchising, management contracts, direct investments, strategic alliances, joint ventures.
- Putting the strategy into practice: Structures, processes, strategic change management
Learning outcomes:
Upon successful completion of the course, students are expected to have the knowledge to be able to:
- describe the basic concepts of strategy and the importance of strategy making for business
- describe the key strategic options for achieving a firm’s competitive advantage.
- describe the business strategies of enterprises.
- apply in practice the concepts and techniques taught in real business examples (case studies), through group work.
- distinguish and explain the alternative strategies for the development of a business and the methods of their implementation. Abilities to:
- analyse both the external and the internal environment of a business and apply the respective environmental analysis models to real business cases.
- develop a strategic plan for a business and propose strategic options in the context of business studies
Course content:
The course seeks to introduce participants to the concept of Economics for Managers. The purpose of the course is to enhance the knowledge base in economic theory and its interactions in the contemporary business environment. The teaching focuses on the level of analysis and in addition, extensive reference is made to practical issues of business decisions. The main objective of the course is for managers to be able to make decisions based on the economic environment (domestic, regional and global) using Power Business Intelligence (BI). In addition, this course aims to present:
- a) the interconnections between the main macroeconomic problems facing modern economies,
(b) the characteristics of state economic policy in the context of the regulation of the economic cycle; and
(c) the impact of all these on business.
Indicative syllabus distribution
- Economic concepts and the market ecosystem
- Financial decision making, key financials [Using Power BI]
- Market analysis and competitive conditions.
- Business environment
- consumer decisions, consumption, consumption, savings, demand, elasticity
- business decisions, cost forms, profit
- firms & basic market structures, perfect competition, monopoly, imperfect competition [Use Power BI]
- Financial decision management
- Analysis of consumer behaviour – examples of consumption
- Analysis of the investment behaviour of
Learning outcomes:
- Students should understand basic economic principles and theories such as supply and demand, market equilibrium, and elasticity.
- Students should be able to collect, analyse and interpret economic data to make management decisions.
- Students should be able to use economic models to make strategic decisions.
- Students should understand the concepts of resource management and the allocation of limited resources within a business.
- Students should be able to analyse markets and industries to identify opportunities and threats.
- Students should be able to interpret financial statements and perform financial analysis.
- Students should be able to identify and manage financial risks.
- Regulating the digital economy: Ecosystems, Competition Law and Regulation
- Theories of damage in digital ecosystems I
- Theories of Damage in Digital Ecosystems II
- Exploitation and exclusionary practices and non-price competition parameters (emphasis on data and privacy)
- Regulating the digital economy: The (self-)regulatory alternative(s) I
- Regulating the digital economy: The (self-)regulatory alternative(s) II
- The new frontiers of competition and regulation in digital ecosystems
- Competition problems in platform markets
- Definition of the market for platform markets
- Economic tools for the evaluation of damage theories in platform markets
- Understand the economic principles of competition enforcement
- Understand the specific characteristics of platform markets
- Evaluate the economic tools of the operation and market structure of platform markets.
Course content:
The course emphasizes the development of skills and knowledge for the analysis and exploitation of big data in digital environments. The course content covers basic and advanced data processing techniques such as data mining, machine learning algorithms and prediction techniques. Students learn to use modern data analysis tools and platforms, such as Hadoop, Spark and TensorFlow, to process and analyse big data at scale. In addition, the course covers topics related to data storage, management, and security, as well as their applications in various fields such as business analytics, healthcare, and social sciences. At the end of the course, students will be able to develop and implement data-driven strategies, providing valuable insights and predictive analytics for business decision making.
Indicative syllabus distribution
- Introduction to data analysis and Big Data: characteristics and importance of big data in economics.
- Architectures for collecting, analyzing and storing big data, including SQL and NoSQL databases, data warehouses and data lakes.
- Data cleaning and pre-processing methods, such as missing data management, outlier detection, normalisation and data transformation.
- Exploratory Data Analysis (EDA) techniques, pattern and trend identification.
- Data visualisation techniques and tools. Data analysis and statistical methods using Python.
- Introduction to big data tools and technologies such as Hadoop and Spark.
- Applications of big data in competition and market regulation: price analysis techniques, correlation identification and detection of unfair practices.
Learning outcomes:
Upon successful completion of the course, students will be able to:
- Understand the characteristics and importance of big data in economics.
- They have a broad knowledge of various architectures for collecting, analysing and storing big data.
- Select and apply appropriate methods of data cleaning and pre-processing.
- They use exploratory data analysis (EDA) techniques.
- Apply methods of visual data analysis.
- Select and apply appropriate statistical analysis techniques using the Python language.
- Have knowledge of big data tools such as Hadoop and Spark
- Apply specialised data analysis techniques for competition and market regulation.
Course content:
In the context of the course, students will be introduced to machine learning techniques and artificial intelligence methods, while they will be informed about their use in economic activity. In addition, in the context of the course students will be introduced to the innovation development process (development of new products/services) and the digital transformation process (development of new processes using digital technology) through in-depth analysis of available data.
Specifically, in the context of the course students will be taught
- how to identify and combine multiple data sources,
- what machine learning is,
- what is artificial intelligence,
- what are the most important machine learning techniques,
- how machine learning is used in the context of decision-making,
- what is multidimensional data, geographic data, and big data,
- how to visualise data and how to analyse multidimensional data and big data,
- how to apply machine learning techniques for pattern recognition,
- what neural networks are and how they are used,
- how to create innovation and how to develop new products/services through in-depth analysis of available data, etc.
The emphasis of the course will be on machine learning and artificial intelligence techniques with case studies. Specifically, students will be introduced to these techniques through case studies in the following areas of economic activity: Insurance, Healthcare, Banking, Manufacturing, etc.
Indicative syllabus distribution
- Introduction to machine learning and artificial intelligence
- Main machine learning tools
- Main artificial intelligence tools
- Applications
Learning outcomes:
After completing the course, students will be able to:
- understand the concepts of machine learning and artificial intelligence.
- understand the changes that machine learning and artificial intelligence are bringing to business and the economy.
- Understand the value of data for decision-making.
- select the most appropriate machine learning tools to analyse data.
use machine learning techniques to create data-driven innovation and innovative applications of artificial intelligence.
Course content:
The aim of the course is to deepen the understanding of basic concepts of EU competition law, such as: the understanding of the extraterritorial application of EU competition rules, the prohibition of Article 101 par. 1 TFEU, abuse of dominant position: theoretical basis and object of protection under Article 102 TFEU, control of “concentration of undertakings”
Indicative syllabus distribution
- The object of protection of free competition law – Protection of economic freedom
- The pursuit of economic efficiency
- The European Union’s competition law and policy objectives
- The extraterritorial application of EU competition rules
- From Council Regulation 17/62 to the modernisation of EU competition law
- Regulation 1/2003 and the relationship between national and EU competition law
- Fundamental rights and competition law
- Regulating the relationship between national and EU competition rules
- Directive 2019/1 (ECN+) – Strengthening the powers of competition authorities
- The prohibition in Article 101(1)(a) of the EC Treaty. 1 TFEU
- The statutory exception of article 101 par. 3 TFEU
- Exemption regulations by category
- Decisions of the European Commission and the General Court and Court of Justice of the EU
- Vertical agreements
- Abuse of a dominant position: theoretical basis and scope of protection under Article 102 TFEU
- The Commission’s Priority Notice for the examination of Article 102 TFEU
- The case law of the Court of Justice of the EU and the practice of the European Commission
- The importance of Article 106 TFEU – YΓΟΣ
- Control of “Concentration of undertakings” (Mergers – Acquisitions – Joint ventures) Regulation (EC) 139/2004
- Judicial review of European Commission decisions (Regulation 139/2004)
- Directive 2014/104/EU on damages actions
- The application of EU competition law by the European Commission (Fines, leniency, settlement)
- Judicial review of the CJEU and the CJEU – Case law
- Article 107 TFEU State aid
Learning outcomes:
- Students will understand the basic principles and sources of EU competition law.
- They will recognise the purposes and importance of competition law for the functioning of the internal market.
- Students will be able to analyse and interpret the main legislative acts and relevant case law in the field of competition law.
- Students will develop skills in analysing decisions of the European Commission and the Court of Justice of the European Union.
- Students will learn to apply the principles of competition law to real-life cases and business practices.
- Students will develop skills in solving practical problems and preparing legal documents and opinions.
- Students will cultivate their critical thinking and learn to evaluate the impact of business practices on the market.
- Students will improve their skills in oral and written communication of legal issues.
- Students will understand the relationship between competition law and EU economic policy.
- Students will be able to analyse the economic impact of competition decisions and regulatory interventions.
Course content:
This course examines the incentives and effects of mergers and acquisitions (M&A) from the perspective of Competition Policy.
The analysis will be done through the use of microeconomic and industrial organisation tools as well as through the presentation of a series of case studies.
Indicative syllabus distribution
- Introduction
- Horizontal S&E
- Vertical S&E
- Diagonal S&E
- R&D in Digital Markets
Learning outcomes:
- Familiarity with the economic analysis of Mergers & Acquisitions Acquisitions (M&A) and their treatment by Competition Policy.
- Develop theoretical knowledge and practical skills related to the understanding of these issues.
- The course covers both theoretical issues related to business practices and the practical components between the economic and legal approaches to S&E.
Course content:
This course will allow students to understand the fundamental principles of digital markets in order to analyse them from the perspective of static and dynamic efficiency in an attempt to formulate optimal regulatory policy.
Indicative syllabus distribution
- Introduction to digital markets
- The multiple sides of a digital market
- The digital market as a network market
- Competition and prosperity in the digital economy
- Competition law and regulation in digital markets
- Data protection and data portability
- Net neutrality and fair allocation initiative
- The European Commission’s Digital Market Act (DMA)
- Impact of the DMA on consumers and businesses
- The future of digital markets and their regulation
Learning outcomes:
Upon successful completion of the course, students will be able to:
- Identify and understand the fundamental principles of digital markets
- Recognise the reasons why digital markets need to be considered and analysed within a specific context
- Examine digital markets through multi-platform analysis models
- Assess the situations that make the digital market fail, thus justifying regulatory policy
- Understand important issues related to digital markets, such as data protection, fair share and net neutrality
- Interpret the legislative framework of digital markets, with particular emphasis on that of the European Union
Course content:
Modern businesses are called upon to operate in a highly competitive and internationalised environment, with high acquisition costs and the required resources, rapid social, economic and technological changes, applying management practices in the context of social corporate responsibility. In this context, effective management is a primary factor in the realisation of the objectives of modern enterprises.
The course is the basic introductory course in the concepts of business organization and management. The primary objective of the course is to familiarize the student with the principles of management.
The purpose of the course is the analytical examination of the functions of Management, through the provision of specific theoretical knowledge, so that the future manager will have made the concept of Management his/her own, knowing at all times what actions he/she should take in order to effectively manage the company he/she is in charge of.
Learning outcomes:
Upon successful completion of the course, students will be able to:
- describe the functions of management, the roles and required competencies of the manager.
- describe and distinguish the forces of the internal and external environment that affect the operation and effectiveness of modern businesses.
- identify and evaluate characteristics and decision-making stages for good group and individual decisions.
- describe the types and process of business action planning for effective implementation of business strategy.
- describe the ways of organising, how the organisational structure is created, how roles and responsibilities are assigned to the members of the enterprise/organisation.
- identify and describe the sources of power of the leader-manager, what constitutes the nature of leadership and describe and evaluate the appropriateness of applying traditional and contemporary theories of leadership.
- describe what and how motivates human behaviour in the workplace, how effective employee groups are created and how individual and intergroup relationships are managed and what are the obstacles/difficulties and the process and means for effective interpersonal and organisational communication.
- recognise, evaluate and describe the necessity and feasibility of establishing control systems and how they operate to optimise the use of production factors, systems and processes.
ΣΥΝΟΠΤΙΚΗ ΠΑΡΟΥΣΙΑΣΗ ΜΑΘΗΜΑΤΩΝ
THIRD SEMESTER OF STUDIES
Course content:
The course will describe the different market structures in terms of real competition in relation to economic efficiency. Particular attention will be paid to structural and behavioral strategies that can impede effective competition and cause market failure. Understanding the causes of market failure helps to inform policy aimed at addressing the problems that exist in different markets. To facilitate an in-depth understanding of the course, it is necessary to refer to real case studies both nationally and internationally (Google/Android, GDF/Suez, Deutsche Telecom, EURIBOR, etc.).
Indicative syllabus distribution
- Introductory concepts, introduction to competition policy.
- The concept and characteristics of networks and markets
- Electronic communications and networks
- Competition policy and the digital economy
- Collusive behaviour and abuse of dominant position in new economy markets
- Concentration control (horizontal, vertical and diagonal concentrations).
- Economic models of merger control (ex ante and ex post)
- Case studies in markets with network effects (energy, electronic communications, IT, transport).
- State Aid control (State Aid control)
Learning outcomes:
In modern economies, the nature of competition and the organisation of firms in markets are key factors influencing prices, quality and innovation.
In many cases, increased competition produces desirable results, but in some cases increased competition can lead to inefficiencies and this requires appropriate policy aimed at managing competition and, in some cases, direct regulation.
This course will allow students to consolidate the theory of industrial organisation in a practical context while having the opportunity to analyse policy issues arising in different sectors.
Course content:
The course focuses on how Leadership in a business or organization can cope with today’s changing international environment in which competition is constantly intensifying. In this light, the course addresses the dimensions of the contemporary competitive environment, which include human resources, access to finance, competition for raw materials, competition for CSR, etc. Further, it examines the main components of leadership, based on the principle that leadership is dynamic and not static. Thus, it discusses the relationship between leader, followers and circumstances, and emphasizes the characteristics and values of leaders, charismatic leadership, and the problems faced by contemporary leaders and how they respond to them. Special emphasis is also placed on the role of emotional intelligence in solving these problems and on ‘leader survival’.
Indicative syllabus distribution
- International and domestic competition
- Forms of competition
- Concept and role of leadership
- Systems Approach to Leadership
- Leaders and Managers
- Leadership and effectiveness
- Leader Characteristics
6.Leadership Development
- Participatory Leadership
- Leadership Roles
- Charismatic and Transformational Leadership
- Leadership, organisational learning and change
- Leadership in teams
Learning outcomes:
Upon successful completion of the course, the student should:
– He understands the importance of the key role of Leadership in the successful operation of businesses and organizations in today’s demanding, competitive and volatile environment.
– Distinguish the difference between management and leadership and as a future executive to enrich their thinking on inspiring trust and motivating individuals and teams.
– Has developed knowledge of change management
Course content:
The course explores the application of game theory to the analysis of oligopoly markets. It covers fundamental concepts of game theory and examines the strategic interaction between firms in an oligopoly environment. Students will learn how firms make decisions about pricing, output, and other strategic variables, taking into account the actions and reactions of their competitors. The course also includes applications in competition policy to interpret theoretical concepts.
Indicative syllabus distribution
- Introduction to Game Theory
- Static Information Static Games
- Dynamic Padded Information Games
- Static Imperfect Information Games
- Advanced Topics in Oligopoly Theory
- Introduction to Auctions
- Topics in Auction Theory
- Cooperative Games
- Oligopoly games
- Special Topics in Oligopoly Games
Learning outcomes:
Upon successful completion of the course, students will be able to:
- Understand the basic principles of game theory and their application to economics.
- Analyse strategic interactions between firms in oligopolistic markets.
- Explore different models of oligopoly.
- Apply the concepts of game theory to real market scenarios.
- Develop critical thinking and problem-solving skills in the context of strategic decision-making.
Course content:
In this course we will examine the criteria and conditions for controlling state aid at national and European level, the effects of such measures on the market, as well as case studies.
Indicative syllabus distribution
- The concept of State aid
- Typical classification of State aid measures
- The distortion of free competition by State aid measures
- State aid control by the European Commission
- The role of national authorities and courts
Learning outcomes:
Upon successful completion of the course, students will be able to:
- They understand the control of state aid from the point of view of free competition law.
Understand the legal theory, the articles of the Treaty on the Functioning of the European Union, the case law of the European Court of Justice and the practical application through case studies
Course content:
The course will introduce students to basic statistical and econometric techniques to equip them with the necessary knowledge and skills to tackle real-world problems requiring data processing. In addition, students will be trained in empirical applications using statistical software.
Indicative syllabus distribution
- How to write a paper/thesis
- Introduction to basic concepts in econometrics and statistics
- Descriptive statistics in R
- Estimation of linear regression in R. Interpretation of results.
- Estimation of panel data in R. Fixed Effects, Random Effects. Interpretation of results.
- Estimation of probit and ordered probit models. Interpretation of results
Learning outcomes:
Upon completion of the course, students will be able to identify and explain the use of modern econometric methods in the context of economics. In addition, students will be able to apply econometric tools to data sets to examine and interpret relationships between economic variables. Finally, students will be able to understand third-party empirical reports on economic issues.
Course content:
During the third semester of their studies, postgraduate students who choose to write a thesis must decide on the topic of their thesis in collaboration with their supervisor(s).
The main task of the thesis is to:
- a) the student’s specialisation in the field of research,
- b) deepening the thought process and methodology of research
- c) application of the knowledge acquired during the courses of the MSc.
Upon completion of the thesis, postgraduate students will be able to conduct both basic and applied research on competition policy and market regulation, while developing and advancing knowledge in fields related to the subject matter of the programme of study.
Stages of a thesis:
- Choice of Subject
- Literature review
- Drafting a Research Topic (Proposal)
- Preparation of Diploma Thesis
- Submission and Presentation
- Submission of Copies of Diploma Thesis
Learning outcomes:
Upon successful completion of the thesis, the student will be able to:
- Design and implement a well-structured research study, choosing appropriate methods and tools for data collection and analysis.
- Analyze quantitative and qualitative data accurately and interpret the results based on existing literature and theoretical approaches to the subject.
- Write a complete, coherent and scientifically documented thesis, following academic standards and reference rules
- Present clearly and professionally the results of their research to academic or professional audiences, and support the findings of their work with documentation.
- Apply and combine the knowledge and skills acquired during the course to solve practical or theoretical problems in the field of their research.
- Critically evaluate existing literature, identify gaps and areas for investigation, and contribute to the advancement of knowledge in their field.
- Manage time and resources effectively during the research process, demonstrating autonomy and organisational skills.