Research Methods in Management

2020/2021

Academic Year

ENG

Instruction in English

4

ECTS credits

Delivered at:

Department of Business Informatics

Course type:

Compulsory course

When:

1 year, 1 module

Instructors

Veselova, Anna

Gladkova, Margarita

Course Syllabus

Abstract

The Course ‘Research Methods in Management’ is a part of a cycle of Courses providing Master’s Program ‘Master in International Management (MIM). This Course establishes a range of requirements for students’ skills and knowledge and determines content and the forms of educational activities and reporting. It is recommended to have a preliminary knowledge in the following disciplines prior attending this course: • Management • Introduction to Economic Theory. The course introduces the process of formal inquiry and helps students to develop analytical skills needed to collect research relevant information, process and analyze the data using established quantitative or qualitative research methods and to make conclusions on the basis of research results. It makes students familiar with the development of structured questions to guide their inquiry, bibliographic research to set their inquiry in the context of the work of other scholars, research design and the selection of research methods. Upon the completion of the course students will identify proper research topic and formulate research problem, determine the information sources necessary for addressing the research question, identify different types of data that may be used for empirical analysis, develop a research design, select different research methods, conduct empirical research, and formulate conclusions.

Learning Objectives

• introduce methods of quantitative and qualitative analysis useful in their professional business and management activities.
• identify which method to use depending on the research objective
• introduce how to prepare and evaluate research report

Expected Learning Outcomes

• Understand the specific nature of the different type of data, be acquainted with its basic concepts and models used to its analysis
• Be able to conduct primary analysis of quantitative data - descriptive statistics and graphs
• Be able to formulate statistical hypothesis based on the research assumptions and test them using statistical criteria
• Be able to understand and estimate the simple and multiple linear regression models, test the specification of the estimated models, interpret the estimation results, and make the predictions;
• Gain a general understanding of basic configurational methods, such as factor analysis and cluster analysis.
• Be able to conduct case study analysis and be familiar with its procedure
• Be able to present results of research analysis

Course Contents

• Data gathering and sampling
  Where and how the data for research can be collected?
• Data description
  Describing data: metrics, tables, graphs
• Hypothesis testing
  General procedure of hypothesis testing. Application and examples.
• Topic 7. Quantitative methods for dependence analysis
  Correlation analysis. Simple linear regression. Multiple correlation and multiple regression. Mediation and moderation.
• Topic 8. Advanced quantitative methods of analysis.
  Multivariate methods such as factor and cluster analysis. Interconnections within dataset.
• Case study analysis
  Qualitative data analysis: case study analysis. Methodology and applications.
• Fuzzy set
  Qualitative research: fuzzy set
• Reporting of research results
  How to report results of conducted research?

Assessment Elements

• Exam
• Essay
• Home assignments
• Quizzes

Interim Assessment

• Interim assessment (1 module)
  0.15 * Essay + 0.5 * Exam + 0.2 * Home assignments + 0.15 * Quizzes

Bibliography

Recommended Core Bibliography

• Discovering statistics using IBM SPSS statistics, Field, A., 2018
• Saunders, M., Lewis, P., & Thornhill, A. (2015). Research Methods for Business Students (Vol. Seventh edition). New York: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1419381

Recommended Additional Bibliography

• Jeffrey M Wooldridge. (2010). Econometric Analysis of Cross Section and Panel Data. The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.mtp.titles.0262232588