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Marketing Science


Subject to changes

Admission requirements

Master students


Marketing Science is a multidisciplinary subject. The course addresses core concepts and fundamental principles of marketing and discusses state-of-the-art topics and research methods in the ever-changing field of marketing, such as neuromarketing and artificial intelligence in marketing, etc. This course will link academic and practical insights to highlight how to adaptively apply marketing tools in managing business practices in this digital age.

Course objectives

By the end of the course, the student should be able to:

  • apply segmentation, targeting, and positioning to develop marketing strategies

  • apply marketing tools to guide business practices

  • develop marketing research and draw managerial conclusions

  • apply AI-driven marketing tools (e.g., AI-driven customer segmentation, and data-driven predictive modeling)

  • understand the importance of applying neuroimaging in marketing research and business practices


Check MyTimetable and use your ULCN account to login.

You will find the timetables for all the courses and degree programme in MyTimetable. This enables you to create a personal timetable. Any teaching activities that you have registered for in uSis will automatically be displayed in your timetable. Any timetables that you add will be saved and automatically displayed the next time you sign in.

Mode of instruction


Assessment method

The final grade will be composed of the following three parts:
50% closed-book written examination
20% assignment – marketing plan
30% participation & interaction

A week after the final grades are known an announcement will put on Brightspace with the date, time and location where students can review the exam and standard answers.

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

  1. Armstrong, G.M., Kotler, P., Harker, M.J. and Brennan, R., 2019. Marketing: an introduction. Pearson UK.
  2. Edelson, M., Sharot, T., Dolan, R.J. and Dudai, Y., 2011. Following the crowd: brain substrates of long-term memory conformity. science, 333(6038), pp.108-111.
  3. Tom, S.M., Fox, C.R., Trepel, C. and Poldrack, R.A., 2007. The neural basis of loss aversion in decision-making under risk. Science, 315(5811), pp.515-518.
  4. Marteau, T.M., Hollands, G.J. and Fletcher, P.C., 2012. Changing human behavior to prevent disease: the importance of targeting automatic processes. science, 337(6101), pp.1492-1495.
  5. Lee, N., Broderick, A.J. and Chamberlain, L., 2007. What is ‘neuromarketing’? A discussion and agenda for future research. International journal of psychophysiology, 63(2), pp.199-204.
  6. Fisher, C.E., Chin, L. and Klitzman, R., 2010. Defining neuromarketing: Practices and professional challenges. Harvard review of psychiatry, 18(4), pp.230-237.
  7. Morin, C., 2011. Neuromarketing: the new science of consumer behavior. Society, 48(2), pp.131-135.
  8. Campbell, C., Sands, S., Ferraro, C., Tsao, H.Y.J. and Mavrommatis, A., 2020. From data to action: How marketers can leverage AI. Business Horizons, 63(2), pp.227-243.
  9. Luo, X., Tong, S., Fang, Z. and Qu, Z., 2019. Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), pp.937-947.
  10. Rai, A., 2020. Explainable AI: From black box to glass box. Journal of the Academy of Marketing Science, 48(1), pp.137-141.
  11. Paschen, J., Kietzmann, J. and Kietzmann, T.C., 2019. Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing.
  12. Salah, K., Rehman, M.H.U., Nizamuddin, N. and Al-Fuqaha, A., 2019. Blockchain for AI: Review and open research challenges. IEEE Access, 7, pp.10127-10149.
  13. Micu, A., Micu, A.E., Geru, M. and Lixandroiu, R.C., 2017. Analyzing user sentiment in social media: Implications for online marketing strategy. Psychology & Marketing, 34(12), pp.1094-1100.
  14. Seo, E.J. and Park, J.W., 2018. A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. Journal of Air Transport Management, 66, pp.36-41.
  15. Rita, P., Oliveira, T. and Farisa, A., 2019. The impact of e-service quality and customer satisfaction on customer behavior in online shopping. Heliyon, 5(10), p.e02690.


Students have to register for the course in uSis (lectures and exam). The registration in uSis will open two months before the start of the academic year. Click here for instructions.

There is limited capacity for external students. Please contact the programme coordinator.

More information on the different types of registration can be found here.


For all questions you can contact

Note: If you are an ICTiBPS student, you can contact the programme coordinator of ICTiBPS for any questions about your program.


  • Students are responsible for enrolling/unenrolling themselves for (partial) exams/retakes.

  • Students are responsible for enrolling themselves for (partial) exams/retakes.

  • The deadline for enrolling for an exam/retake is 14 calendar days before the exam/retake takes place (exam date - 14 = deadline enrolling date).

  • Students who do not enroll themselves for an exam/retake by the deadline are not allowed to take the exam/retake.

  • Students fail the course if any of the partial components (except the exam) that make up the final mark of the course is assessed below 4.0.

  • Students fail the course if the grade for the (final) exam is assessed below 5.0.

  • The final grade is expressed as a whole or half number between 1.0 and 10.0, including both limits. The result is not to be expressed as a number between 5.0 and 6.0.

  • If one of the components of the final mark constitutes a component that assesses attendance or class participation, students cannot take a retake for this component. Therefore, students fail the course if their mark for this component is less than 4.0.

  • Partial grades, inclusive the exam grade will not be rounded. If partial grades will be communicated, it is possible partial grades are rounded, but unrounded partial grades will be used in the calculation of the final grade. The final grade will be rounded at 0.5 (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).

  • It is not possible to do retakes for group assignments. Therefore, if students fail the group assignment component, they fail the course.

  • Students pass the course if the final mark is 6.0 or higher (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).

  • For courses, for which class participation is an assessment component, students may not be penalised for an absence if the student has a legitimate justification for this absence. The student must notify the program coordinator via email ( of such an absence BEFORE the lecture, describing the reason for missing the lecture. If the student does not notify the program coordinator before the lecture, the student will be penalised. Students may be required to provide further documentation to substantiate their case, and class attendance requirements are only waived under exceptional circumstances such as illness.

  • Students who are entitled to more exam/retake time must report to 10 days before the exam/retake takes place.