Teaching

Marketing, consumer behaviour, digital marketing, advertising and research methods, taught in English from bachelor’s to doctoral level

Course portfolio of Bruno Schivinski: marketing, consumer behaviour, digital and international marketing, advertising, research methods, applied statistics and structural equation modelling, taught in Poland, Australia, Vietnam, Ghana and the UK. Open to visiting teaching.

I teach marketing, consumer behaviour, digital and international marketing, advertising and research methods, in English, from first-year undergraduates to doctoral candidates, at universities in Poland, Australia, Vietnam, Ghana and the United Kingdom. Every course pairs a leading international textbook with teaching materials I develop myself (lecture notes, datasets, case studies, exercises and assessments) drawn from my own research and current practice. Courses are built around real market problems: students write complete marketing plans, design digital marketing strategies, run their own surveys and in-depth interviews and, at doctoral level, estimate and test structural equation models with their own data.

Course portfolio

Marketing

Undergraduate

Advertising

Course coordinator and instructor

How advertising works and how it is managed: the theories behind persuasive messages, the work of agencies and creative teams, traditional and digital media, audiences and their values, regulation, and how to measure whether an advertisement worked.

Course outline
  1. Advertising as a message from the brand
  2. Theories behind the message
  3. Advertising agencies and how they work
  4. Creative elements of advertisements
  5. Traditional media
  6. Digital and emerging media
  7. Advertising and audience values
  8. Offensive advertising and regulation
  9. Evaluating advertising effectiveness
  10. The future of advertising

Taught at

  • Gdańsk Tech · 2012–2015

Core textbook

Cover of Introduction to advertising: Understanding and managing the advertising process
Mogaji, E. (2021). Introduction to advertising: Understanding and managing the advertising process. Routledge.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

Consumer Behaviour

Course coordinator and instructor

Why people buy, use and dispose of products, and how culture, identity and social groups shape those choices. Students apply psychological and sociological models to real brands and international markets.

Course outline
  1. Buying, having and being: introduction to consumer behaviour
  2. Consumer ethics, the marketplace and the planet
  3. Perception and meaning
  4. Learning, memory and knowledge
  5. Motivation and values
  6. Attitudes and how to change them
  7. Decision making
  8. Buying, using and disposing
  9. Identity and the self
  10. Personality, lifestyles and values
  11. Social and cultural identity
  12. Groups and social influence
  13. Social class and status
  14. Culture and consumption

Taught at

  • Gdańsk Tech as “International Consumer Behaviour” · Management (International Business Management) · 2025–present
  • FTU as “Consumer Behavior in Services” · Advanced Program in International Business Management (bachelor's, taught in English) · 2025
  • NTU as “The Customer Experience” · MSc Marketing suite · 2015–2017

Core textbooks

Cover of Consumer behavior: Buying, having, and being
Solomon, M. R., & Russell, C. A. (2024). Consumer behavior: Buying, having, and being (14th ed., global ed.). Pearson.
Cover of Consumer behaviour
Sethna, Z., & Blythe, J. (2019). Consumer behaviour (4th ed.). Sage.

Plus my own lecture notes, datasets, case studies and exercises.

Undergraduate

Digital Marketing

Course coordinator and instructor

How to plan, run and measure digital marketing: online consumer behaviour, digital research, segmentation and positioning, the online marketing mix, and owned, paid and earned media. Students build a complete digital marketing plan for a new website or app.

Course outline
  1. Digital marketing: past, present and future
  2. Strategic digital marketing and performance metrics
  3. The digital marketing plan
  4. Global digital marketing
  5. Ethical and legal issues
  6. Digital marketing research
  7. Consumer behaviour online
  8. Segmentation, targeting, differentiation and positioning
  9. Product and price online
  10. The internet for distribution
  11. Owned media
  12. Paid media
  13. Earned media
  14. Customer relationship management

Taught at

  • Gdańsk Tech as “E-marketing and Trend Analysis” · Data Engineering (Big Data in Business Management) · 2025–present
  • FTU · Advanced Program in International Business Management (bachelor's, taught in English) · 2025

Core textbooks

Cover of eMarketing: Digital marketing strategy
Frost, R., Fox, A. K., & Daugherty, T. (2023). eMarketing: Digital marketing strategy (9th ed.). Routledge.
Cover of Marketing communications
Eagle, L., Dahl, S., Czarnecka, B., & Lloyd, J. (2015). Marketing communications. Routledge.

Plus my own lecture notes, datasets, case studies and exercises.

Master's

International Advertising

Course coordinator and instructor

How culture shapes advertising and global brand communication. Students analyse cultural values and communication styles across markets, examine the international business and media environment, and design and evaluate advertising strategies for brands competing internationally.

Course outline
  1. The paradoxes of global marketing communications
  2. Global branding
  3. Values and culture
  4. Dimensions of national culture
  5. Culture and consumer behaviour
  6. Researching and applying cultural values
  7. Culture and communication
  8. Culture and the media
  9. Culture and advertising appeals
  10. Culture and executional style
  11. From value paradox to international advertising strategy

Taught at

  • RMIT · Master's, School of Media and Communication · 2024, 2025

Core textbook

Cover of Global marketing and advertising: Understanding cultural paradoxes
de Mooij, M. (2021). Global marketing and advertising: Understanding cultural paradoxes (6th ed.). Sage.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

International Marketing

Course coordinator and instructor

How firms take their products to foreign markets. Students weigh culture, language, political and legal systems, economic systems and technology, choose countries and entry modes, and adapt the marketing mix (product, price, distribution and promotion) for international customers.

Course outline
  1. Introduction to international marketing
  2. Culture and cross-cultural marketing
  3. Global trade and integration
  4. Country selection and entry strategies
  5. International marketing planning, organisation and control
  6. Markets and segmentation in an international context
  7. International positioning
  8. Market research in the international environment
  9. International product and brand marketing
  10. Standardisation and adaptation
  11. International pricing and finance
  12. International channels, exporting and retailing
  13. Globally integrated marketing communications
  14. International sales promotion and public relations

Taught at

  • Gdańsk Tech · Master's · 2012–2015
  • FTU as “Multinational Marketing Strategy” · Advanced Program in International Business Management (bachelor's, taught in English) · 2025

Core textbook

Cover of International marketing
Baack, D. W., Czarnecka, B., & Baack, D. E. (2018). International marketing (2nd ed.). Sage.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

Marketing Planning and Strategy

Course coordinator and instructor

How to analyse a market and turn the analysis into a marketing plan that can be defended to senior managers: internal and external analysis, objectives, strategy, the marketing programme, budgets and metrics. Students write a full marketing plan for a real brand.

Course outline
  1. What marketing planning is and why it matters
  2. The front end of the plan
  3. Internal analysis
  4. The global and market environment
  5. Bringing the analyses together
  6. Objectives and assumptions
  7. Marketing strategy
  8. The marketing programme
  9. Budgets
  10. Metrics and market research
  11. Scenarios
  12. Ethics in marketing planning
  13. Strategy models and empirical generalisations

Taught at

  • FTU · Advanced Program in International Business Management (bachelor's, taught in English) · 2025
  • NTU as “Strategic Marketing and the Global Environment” · MSc Marketing suite · 2015–2017

Core textbook

Cover of Marketing planning & strategy: A practical introduction
Dawes, J. (2021). Marketing planning & strategy: A practical introduction. Sage.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

Principles of Marketing

Course coordinator and instructor

The foundations of marketing: creating customer value and engagement, understanding markets and buyers, and designing the marketing mix. Students work in teams to write and present a complete marketing plan for a real company and a new product.

Course outline
  1. Creating customer value and engagement
  2. Company and marketing strategy
  3. The marketing environment
  4. Marketing information and customer insights
  5. Consumer and business buyer behaviour
  6. Segmentation, targeting and positioning
  7. Products, services and brands
  8. New products and the product life cycle
  9. Pricing
  10. Marketing channels, retailing and wholesaling
  11. Advertising and public relations
  12. Personal selling and sales promotion
  13. Digital marketing
  14. The global marketplace
  15. Sustainable marketing, social responsibility and ethics

Taught at

  • Gdańsk Tech as “Essentials of Marketing” · Management (bachelor's) · 2025–present
  • Gdańsk Tech as “Marketing” · Management (master's) · 2025–present
  • Gdańsk Tech as “Marketing” · Data Engineering (bachelor's) · 2025–present
  • NTU · MSc Marketing suite · 2015–2017

Core textbooks

Cover of Marketing: An introduction
Armstrong, G., Kotler, P., & Balasubramanian, S. (2025). Marketing: An introduction (16th ed., global ed.). Pearson.
Cover of Principles of marketing
Kotler, P., Armstrong, G., & Balasubramanian, S. (2026). Principles of marketing (20th ed.). Pearson.

Plus my own lecture notes, datasets, case studies and exercises.

Research methods

Doctoral

Applied Statistics

Course coordinator and instructor

A doctoral grounding in the statistics behind business research: exploring and screening data, testing hypotheses and reporting effect sizes, regression, comparing groups and modelling categorical outcomes. Every analysis is run hands-on in IBM SPSS Statistics and R.

Course outline
  1. Why statistics: the research process
  2. Statistical models, estimation and the standard error
  3. Hypothesis testing, effect sizes and statistical power
  4. Working in IBM SPSS Statistics and R
  5. Exploring and visualising data
  6. Bias, outliers and assumptions
  7. Non-parametric tests
  8. Correlation
  9. The linear model: multiple regression
  10. Comparing two means
  11. Moderation and mediation
  12. ANOVA, ANCOVA and factorial designs
  13. Repeated-measures and mixed designs
  14. Categorical outcomes: chi-square and logistic regression

Taught at

  • UPSA · PhD programmes · 2019–2021

Core textbooks

Cover of Discovering statistics using IBM SPSS Statistics
Field, A. (2024). Discovering statistics using IBM SPSS Statistics (6th ed.). Sage.
Cover of Discovering statistics using R
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

Marketing Research

Course coordinator and instructor

How to plan and carry out a marketing research project from problem to report. Students test a new product concept with their own survey: they design the questionnaire, choose the sample, collect and code the data, analyse it and write up the results.

Course outline
  1. The nature and types of marketing research
  2. The research process and research design
  3. Measurement and levels of measurement
  4. Questionnaire design
  5. Measuring attitudes
  6. Sampling
  7. Data editing, coding and preparation
  8. Descriptive and bivariate analysis
  9. Multivariate analysis, including cluster analysis
  10. Qualitative interviews and projective techniques
  11. Netnography and online qualitative research
  12. Observation and survey procedures
  13. Research ethics and the research report

Taught at

  • Gdańsk Tech · Bachelor's programmes
  • NTU as “Customer Insight through Marketing Research” · MSc Marketing suite · 2015–2017

Core textbooks

Iacobucci, D., & Churchill, G. A. (2015). Marketing research: Methodological foundations (11th ed.). Earlie Lite Books.
Cover of The practice of social research
Babbie, E. R. (2021). The practice of social research (15th ed.). Cengage.
Cover of Netnography: The essential guide to qualitative social media research
Kozinets, R. V. (2020). Netnography: The essential guide to qualitative social media research (3rd ed.). Sage.

Plus my own lecture notes, datasets, case studies and exercises.

Doctoral

Multivariate Research Methods

Course coordinator and instructor

Doctoral training in the multivariate techniques most used in social-science and business research, from data screening to factor analysis, regression-based models and an introduction to structural equation modelling.

Course outline
  1. Overview of multivariate methods
  2. Examining your data: missing values, outliers and assumptions
  3. Exploratory factor analysis
  4. Cluster analysis
  5. Multiple regression
  6. MANOVA
  7. Discriminant analysis and logistic regression
  8. Introduction to structural equation modelling
  9. Confirmatory factor analysis

Taught at

  • Gdańsk Tech · Doctoral School, years 1–2 · 2025

Core textbooks

Cover of Multivariate data analysis
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage.
Cover of Principles and practice of structural equation modeling
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.

Plus my own lecture notes, datasets, case studies and exercises.

Doctoral

Quantitative Research Methods

Course coordinator and instructor

How to design, run and publish quantitative research at doctoral level: turning theory into hypotheses, designing surveys and experiments, building valid measures, and testing models with regression, factor analysis and structural equation modelling.

Course outline
  1. The logic of quantitative research
  2. From theory to hypotheses and conceptual models
  3. Research design: surveys and experiments
  4. Measurement and questionnaire design
  5. Sampling and data collection
  6. Data screening and preparation
  7. Reliability and validity
  8. Regression and group comparisons
  9. Exploratory and confirmatory factor analysis
  10. Structural equation modelling
  11. Mediation and moderation
  12. Reporting quantitative research for publication

Taught at

  • UPSA · PhD programmes · 2019–2024

Core textbooks

Cover of Discovering statistics using IBM SPSS Statistics
Field, A. (2024). Discovering statistics using IBM SPSS Statistics (6th ed.). Sage.
Cover of Principles and practice of structural equation modeling
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
Cover of Multivariate data analysis
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage.

Plus my own lecture notes, datasets, case studies and exercises.

UndergraduateMaster's

Research Methods

Course coordinator and instructor

How to design and carry out a business research project with both numbers and words. Students analyse survey data hands-on in IBM SPSS Statistics and R, plan, conduct, transcribe and analyse their own in-depth interviews, and study online communities through netnography.

Course outline
  1. Research questions, design and ethics
  2. The logic of statistics: samples, estimation and significance
  3. Data entry, visualisation and screening in SPSS and R
  4. Correlation and regression
  5. Comparing means: t-tests and ANOVA
  6. Categorical data and chi-square
  7. Scales, factor analysis and reliability
  8. Designing an interview study
  9. Conducting in-depth interviews
  10. Transcribing interviews
  11. Analysing interview data: coding and meaning
  12. Netnography: qualitative research on social media
  13. Validity, generalisation and reporting

Taught at

  • Birkbeck as “Research Methods in Management” · Bachelor's and master's (marketing and management) · 2017–2019
  • Regent's as “Marketing Research” · BA (Hons) Global Management, year 2 · 2018–2019

Core textbooks

Cover of Discovering statistics using IBM SPSS Statistics
Field, A. (2024). Discovering statistics using IBM SPSS Statistics (6th ed.). Sage.
Cover of Discovering statistics using R
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.
Cover of InterViews: Learning the craft of qualitative research interviewing
Brinkmann, S., & Kvale, S. (2015). InterViews: Learning the craft of qualitative research interviewing (3rd ed.). Sage.
Cover of Netnography: The essential guide to qualitative social media research
Kozinets, R. V. (2020). Netnography: The essential guide to qualitative social media research (3rd ed.). Sage.

Plus my own lecture notes, datasets, case studies and exercises.

Master's

Research Methods in Media and Communication

Course coordinator and instructor

How to design and carry out a research project in media and communication, from research question and proposal to data analysis. Students learn quantitative analysis hands-on in both IBM SPSS Statistics and R, and finish with a research plan for their capstone project.

Course outline
  1. Research problems, questions and proposals
  2. Finding and evaluating the literature
  3. Research design and the logic of statistics
  4. Data, variables and visualisation in SPSS and R
  5. Bias, assumptions and data screening
  6. Correlation
  7. Linear regression
  8. Comparing two means
  9. Moderation and mediation
  10. Comparing several means: ANOVA, ANCOVA and factorial designs
  11. Exploratory factor analysis and reliability
  12. Categorical outcomes: chi-square and logistic regression
  13. Writing the research plan

Taught at

  • RMIT · Master's, School of Media and Communication · 2021, 2024, 2025

Core textbooks

Cover of Discovering statistics using IBM SPSS Statistics
Field, A. (2024). Discovering statistics using IBM SPSS Statistics (6th ed.). Sage.
Cover of Discovering statistics using R
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.

Plus my own lecture notes, datasets, case studies and exercises.

Doctoral

Structural Equation Modelling

Course coordinator and instructor

A doctoral course on specifying, estimating, testing and reporting structural equation models: measurement models, structural paths, model fit, group comparisons and measurement invariance, and mediation and moderation.

Course outline
  1. SEM: promise, problems and reporting standards
  2. Data preparation and software
  3. Causal models and path analysis
  4. Estimation, model testing and fit
  5. Comparing models and groups
  6. Confirmatory factor analysis
  7. Structural regression models
  8. Mediation and moderation
  9. Moderated mediation and mediated moderation
  10. Measurement invariance
  11. Best practices in SEM

Taught at

  • Gdańsk Tech · Doctoral School, years 1–2 · 2026

Core textbooks

Cover of Principles and practice of structural equation modeling
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
Cover of Structural equation modeling with AMOS: Basic concepts, applications, and programming
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
Cover of Structural equation modeling with Mplus: Basic concepts, applications, and programming
Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge.
Cover of Multivariate data analysis
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage.
Cover of Doing statistical mediation and moderation
Jose, P. E. (2013). Doing statistical mediation and moderation. Guilford Press.

Plus my own lecture notes, datasets, case studies and exercises.

Where I have taught

Birkbeck, University of London

London, United Kingdom

  • Lecturer in Marketing (B)2017–2019

Department of Management (now Birkbeck Business School)

Courses: Research Methods

Regent's University London

London, United Kingdom

  • Lecturer in Marketing2018–2019

Courses: Research Methods

Visiting teaching and guest lectures

I welcome invitations to teach as a visiting professor, run intensive courses, give guest lectures, and lead doctoral workshops on structural equation modelling and survey research methods.

Contact me on LinkedIn