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Обычная версия сайта
07
Апрель

Consumer Behaviour

2023/2024
Учебный год
ENG
Обучение ведется на английском языке
4
Кредиты
Статус:
Курс обязательный
Когда читается:
4-й курс, 1 модуль

Преподаватели

Course Syllabus

Abstract

The course explores the conceptual foundations of consumer behavior. Students develop deep theoretical knowledge about the influence of various types of factors on consumer behavior, motives and models for making purchasing decisions; as well as practical skills in applying the theory of consumer behavior to solving practical problems of marketing strategic planning, market segmentation, positioning of the company and its brands, implementation of advertising campaigns.
Learning Objectives

Learning Objectives

  • Learning Objectives: - deep understanding the motivations, needs and preferences of the target audients - model consumer behavior and purchase decision making process based on consumer typology - form marketing strategies based on consumer behavior research.
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to collect, analyze, store data in accordance with common scientific and ethical standards
  • be able to follow ethical norms and standards in professional field
  • Analyses an impact of external factors on customer experience strategy
  • A student knows the history of the discipline and subfields
  • Student will be able to measure, critique and interpret consumer behavior based on the knowledge of the internal Influences on consumer behavior.
  • Understanding differences in consumer behavior
  • To identify and predict consumer preferences based on consumer typology.
  • be able to identify and structure the factors that influence consumer behavior
  • A student know the main conceptuals approaches in the study of consumer behavior
Course Contents

Course Contents

  • Lecture 1. Consumer Behavior and Marketing.
  • Lecture 2. Motivation of consumers
  • Lecture 3. Trends.
  • Model of the consumer's decision-making process. Application.
  • Marketing research methods. Qualitative research methods. Customer Journey Map.
  • Quantitative assessment methods. Consumer behavior in the Internet Marketing.
  • Quantitative research methods. RFM analysis. Segmentation. The targeted strategy development.
  • Motivation of consumers. Essay.
    This work has a weight of 0.25 in the total final grade.
  • Marketing research. Project work.
    The grade for this work has a weight of 0.25 in the overall final grade
  • Final testing.
  • Literature and notes
  • Grading System
  • Seminar 1.
  • Seminar 2
    Case study : Film Academy segmentation
  • Seminar 3.
  • Seminar 4.
  • Seminar 5
    Work in class: elaborating CJM for clients from different branches in groups. Stages: 1. Map out all the steps through which customers go in working with you. 2.Keep the focus on the customer, delivering a better experience and improving efficiency 3.Find the right balance between digital and human interactions. 4.Design exceptional journeys for their customers by answering three fail-safe questions : 1) can we make it easier; 2)can we make it faster? 3) can we make it more personalized? Present results.
  • Seminar 6
  • Seminar 7
Assessment Elements

Assessment Elements

  • non-blocking Motivation of consumers. Essay.
    During the entire course the 10-point grade scale is used. The essay must respond to the requirements of the assignment, contain high-quality information and author's opinion, demonstrate the student's awareness and ability to work, research, and achieve results. the text should be at least 5,000 characters long.
  • non-blocking Provide marketing research using the field or remote methods.
    1.Determine the objectives and target audience of the research . 2.Develop a questionnaire form. 3.Process the results of the research 4. Present the results.
  • non-blocking Final Testing
  • non-blocking Class participation
Interim Assessment

Interim Assessment

  • 2023/2024 1st module
    0.25 * Motivation of consumers. Essay. + 0.2 * Class participation + 0.3 * Final Testing + 0.25 * Provide marketing research using the field or remote methods.
Bibliography

Bibliography

Recommended Core Bibliography

  • Andrew Smith. (2020). Consumer Behaviour and Analytics : Data Driven Decision Making. Routledge.
  • Blundell, R. (1988). Consumer Behaviour: Theory and Empirical Evidence——a Survey. Economic Journal, (389), 16. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.ecj.econjl.v98y1988i389p16.65
  • Consumer behaviour in a changing world : food, culture and society. 2016. Ed. by Fabio Verneau and Christopher Griffith Emerald Group Publishing Limited https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=4514345.
  • Emerald Group Publishing Limited. (2015). A Focus on Consumer Behaviours and Experiences in an Online Shopping Environment. Emerald Group Publishing Limited.
  • GUSHTEROV, N. (2018). Modelling Consumer Behaviour on the Energy Market. Economics 21 / Ikonomika 21, (2), 25–43. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=130846852
  • Kateřina Matušínská, & Šárka Zapletalová. (2021). Rational and Emotional Aspects of Consumer Behaviour. Forum Scientiae Oeconomia, 9(2), 95–110. https://doi.org/10.23762/FSO_VOL9_NO2_5
  • Kumra, R. Consumer Behaviour. Mumbai, Global Media, 2006. – URL: https://ebookcentral.proquest.com/lib/hselibrary-ebooks/reader.action?docID=3011355&ppg=1&query=consumer%20behaviour
  • Nair, S. R. (2009). Consumer Behaviour and Marketing Research : (text and Cases) (Vol. Rev. ed). Mumbai [India]: Himalaya Publishing House. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=332241
  • Roberts-Lombard, M., & Parumasur, S. B. (2017). Consumer Behaviour (Vol. Fourth edition). Cape Town: Juta and Company [Pty] Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1647446
  • Solomon, M. R. (2016). Consumer Behaviour : A European Perspective. [N.p.]: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1419690
  • Агаларова, Е. Г. Исследование поведения потребителей : учебник / Е. Г. Агаларова, И. Ю. Антонова, Е. А. Косинова. — Ставрополь : СтГАУ, 2018. — 136 с. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/141595 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
  • Агаларова, Е. Г. Исследование поведения потребителей : учебник / Е. Г. Агаларова, И. Ю. Антонова. — Ставрополь : СтГАУ, 2020. — 153 с. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/245852 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
  • Дубровин, И. А. Поведение потребителей : учебное пособие / И. А. Дубровин. — 4-е изд. — Москва : Дашков и К, 2020. — 310 с. — ISBN 978-5-394-01475-8. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/229634 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
  • Поведение потребителей, Блэкуэлл, Р., 2010
  • Поведение потребителей, Энджел, Дж. Ф., 1999
  • Поведение потребителей, Энджел, Дж. Ф., 2000
  • Скляр, Е. Н. Маркетинговые исследования: Практикум : учебное пособие / Е. Н. Скляр, Г. И. Авдеенко, В. А. Алексунин. — Москва : Дашков и К, 2021. — 216 с. — ISBN 978-5-394-04349-9. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/229460 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

  • Ambler, T., Kokkinaki, F., & Puntoni, S. (2004). Assessing Marketing Performance: Reasons for Metrics Selection. Journal of Marketing Management, 20(3–4), 475–498. https://doi.org/10.1362/026725704323080506
  • Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining. (2012). https://doi.org/10.1057/dbm.2012.17
  • David Martín-Ruiz, Carmen Barroso-Castro, & Isabel Mª Rosa-Díaz. (2012). Creating customer value through service experiences: an empirical study in the hotel industry. Tourism and Hospitality Management, (1), 37. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.tho.journl.v18y2012n1p37.53
  • Davis, J. (2017). Measuring Marketing : The 100+ Essential Metrics Every Marketer Needs, Third Edition (Vol. Third edition). Berlin: De Gruyter. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1670242
  • Derya Birant. (2011). Data Mining Using RFM Analysis. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B99B7782
  • Infiniti Research. (9 C.E., Winter 2019). Why Customer Journey Mapping is Important for Retailers | Read Infiniti Research’s Latest Success Story to Gather Detailed Insights. Business Wire (English).
  • Jeffery, M. Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know [Электронный ресурс] / Mark Jeffery; БД ebrary. – John Wiley & Sons, Incorporated, 2010. – 323 p. – ISBN 9780470504543. – Режим доступа: https://ebookcentral.proquest.com/lib/hselibrary-ebooks/reader.action?docID=485632&query=Data-Driven+Marketing. – Загл. с экрана.
  • Mario D’Arco, Letizia Lo Presti, Vittoria Marino, & Riccardo Resciniti. (2019). Embracing AI and Big Data in customer journey mapping: from literature review to a theoretical framework. https://doi.org/10.21511/im.15(4).2019.09
  • MCKNIGHT, C. (2017). Customer Journey Maps: A Path to Innovation and Increased Profits. EContent, 40(6), 20.
  • Mintz, O., & Currim, I. S. (2013). What Drives Managerial Use of Marketing and Financial Metrics and Does Metric Use Affect Performance of Marketing-Mix Activities? Journal of Marketing, 77(2), 17–40. https://doi.org/10.1509/jm.11.0463
  • Moon, H., Han, S. H., Chun, J., & Hong, S. W. (2016). A Design Process for a Customer Journey Map: A Case Study on Mobile Services. Human Factors & Ergonomics in Manufacturing & Service Industries, 26(4), 501–514. https://doi.org/10.1002/hfm.20673
  • Pradeep A. K., Appel A., Sthanunathan S. AI for Marketing and Product Innovation: Powerful New Tools for Predicting Trends, Connecting with Customers, and Closing Sales. - John Wiley & Sons, 2019.