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Course Syllabus

Bachelor 2023/2024

Marketing Research

Type: Elective course (International Program 'International Relations and Global Studies')
Area of studies: Public Policy and Social Sciences
Delivered by: Faculty of World Economy and International Affairs
Where: Faculty of World Economy and International Affairs
When: 3 year, 3, 4 module
Mode of studies: offline
Open to: students of one campus
Language: English
ECTS credits: 3
Contact hours: 44

Course Syllabus

Full Syllabus

Abstract

The course is aimed at obtaining applied knowledge and skills in the field of marketing research, which will be in demand both in business and in the academic environment. Students will become familiar with relevant aspects of marketing research, such as formulating a business problem, designing, using mixed methods, sampling, data analysis, and visualization and application of results in practice. Considerable attention is paid to the use of AI to solve applied marketing problems.
Learning Objectives

Learning Objectives

  • To introduce students to the general principles of marketing research, to understand the possibilities and limitations of different methods of conducting marketing research
  • To equip students with a reasonable choice of marketing research, necessary and sufficient in a particular market situation
  • To give students practical skills in conducting marketing research
  • To introduce the opportunities that AI offers to solve marketing problems
Expected Learning Outcomes

Expected Learning Outcomes

  • Define marketing research
  • Describe a framework for coducting marketing research
  • Explain how AI works for marketing purposes
  • Define research design
  • Compare and contrast the basic research designs: exploratory, descriptive, and causal.
  • Understand the various forms of qualitative research
  • Discuss and classify survey methods
  • Identify the criteria for evaluating survey methods
  • Intruduce the concepts of measurement and scaling
  • Explain the chacterisitics od description, order, distance, and origin.
  • Understand the concepts of the sampling distribution, statistical inference, and standard error.
  • Discuss the statistical approach to determining sample size based on simple random sampling and the construction of confidence intervals
  • Discuss the nature and scope of data preparation
  • Explain questionnaire chacking and editing, treatment of unsatisfactory responses by returning to the field, assigning missing values, and discarding unsatisfactory responses
  • Familiar with the basics of how advanced research methods in marketing work
Course Contents

Course Contents

  • Introduction to modern Maketing Research. The use of AI in marketing.
  • Research Design
  • Qualitative Research
  • Quantitative research
  • Measurement & Scaling
  • Sampling
  • Data Preparation
  • Advanced research methods
Assessment Elements

Assessment Elements

  • non-blocking Group presentation analysing a report on trends in marketing
    The lecturer provides a marketing report prepared by a research team from the business. A group of students, having chosen a report from the proposed list, independently study its contents, analyse and present the results at the seminar session in the form of a group presentation.
  • non-blocking Individual review of classmates' analysis of the report
    The student chooses a presentation prepared by fellow students, which he/she reads in advance and prepares a written review, which he/she also reads in the seminar class.
  • non-blocking Individual interim Test 1
    Test with closed-ended questions
  • non-blocking Individual interim Test 2
    Test with closed-ended questions
  • non-blocking Group homework 1
    Design of the research questionnaire
  • non-blocking Group homework 2
    Analysis of quantitative data and interpretation of results
  • blocking The exam
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.15 * Group homework 1 + 0.15 * Group homework 2 + 0.2 * Group presentation analysing a report on trends in marketing + 0.05 * Individual interim Test 1 + 0.05 * Individual interim Test 2 + 0.1 * Individual review of classmates' analysis of the report + 0.3 * The exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0
  • Malhotra, Naresh. Marketing Research: an Applied Orientation, Global Edition, Pearson Education, Limited, 2019. ProQuest Ebook Central, Retrieved from https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5640382.
  • Marketing research : an applied orientation, Malhotra, N. K., 2020

Recommended Additional Bibliography

  • Carter, L. L. (2019). Equivalence and Research Design Optimization for International Market Segmentation. Journal of Marketing Development & Competitiveness, 13(3), 10–24. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=138601389
  • Doing qualitative research, Silverman, D., 2017
  • Doing statistical analysis : a student's guide to quantitative research, Thrane, C., 2023
  • Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., Kumar, V., Rahman, M. M., Raman, R., Rauschnabel, P. A., Rowley, J., Salo, J., Tran, G. A., & Wang, Y. (2020). Setting the future of digital and social media marketing research: Perspectives and research propositions.
  • Fallon, M. (2016). Writing up quantitative research in the social and behavioral sciences. Brill.
  • Hackett, P. (2019). Quantitative Research Methods in Consumer Psychology : Contemporary and Data Driven Approaches. New York, NY: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1853813
  • Inter-university Consortium for Political and Social Research. (2012). Guide to Social Science Data Preparation and Archiving: Best Practice Throughout the Data Life Cycle. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.AA22F59E
  • Introduction to survey sampling, Kalton, G., 2021
  • Keith McNulty. (2021). Handbook of Regression Modeling in People Analytics : With Examples in R and Python. Chapman and Hall/CRC.
  • Osondu, O. (2021). A First Course in Artificial Intelligence. Bentham Science Publishers Ltd.
  • Patricia Leavy. (2020). The Oxford Handbook of Qualitative Research: Vol. Second edition. Oxford University Press.
  • Rebecca Bryant, Brian Lavoie, & Constance Malpas. (2018). Realities of Research Data Management. Part Four. Sourcing and Scaling University RDM Services. https://doi.org/10.25333/C3QW7M
  • Research design : qualitative, quantitative and mixed methods approaches, Creswell, J. W., 2018
  • Seidman, I. (2019). Interviewing As Qualitative Research : A Guide for Researchers in Education and the Social Sciences (Vol. Fifth edition). New York, NY: Teachers College Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2168597
  • Sharan B. Merriam, & Robin S. Grenier. (2019). Qualitative Research in Practice : Examples for Discussion and Analysis: Vol. Second edition. Jossey-Bass.
  • Sharon L. Lohr. (2019). Sampling : Design and Analysis: Vol. Second edition. Chapman and Hall/CRC.