RESEARCH METHODOLOGY FOR MARKETING
Instructional goals
The course will examine the specific issues involved in developing and
implementing marketing research to solve a managerial decision
problem. Students will obtain computer skills such as SPSS for Statistics.
Knowledge from this course can be also used for writing a master thesis.
Attention will be focused on the following points:
• Explaining and discussing
procedural and methodological factors that play a role when assessing
marketing research projects
• Discussing the various procedures used for
data collection
• Creating and explaining a questionnaire
• Explaining and discussing in detail the use and application of scales in marketing research
• Explaining the fundamentals of sampling in
marketing research
• Explaining the techniques to check and describe data
(e.g., frequency tables, cross-tabulations)
• Performing and interpreting parametric
and non-parametric tests
• Explaining the right multivariate technique for data analysis given a marketing research problem
• Understanding objectives,
use and interpretation of multivariate data-analysis techniques (e.g.,
regression, factor analysis, ANOVA)
• Understanding how to prepare a research report
Intended learning outcomes
• Knowledge and understanding: At the end of the course students will acquire knowledge on the statistical and analytical tools needed for solving specific marketing-related problems.
• Ability to apply knowledge and understanding: At the end of the course students will be able to design and manage the marketing research process, adopting data collection tools (Qualtrics) and software for statistical analysis (SPSS). Additionally, these capabilities will help students in developing their master thesis. They will be able to critically understand research papers and to propose their own research project.
• Independent judgment: At the end of the course, students will acquire the ability to analyze marketing problems and to identify the right insights for their solution. Specifically, critical thinking, problem solving, self-management, team-working, relationship and communication skills will be adequately developed, thus enhancing the disciplinary skills. These abilities will be acquired both through discussion during the lessons and through group work.
• Communication skills: At the end of the course students will acquire adequate skills and tools for data management and research reporting, both to specialists and non-specialists. These abilities will be acquired both through discussion during the lessons and through group work.
• Learning skills: The course mainly aims to develop methodological and analytical skills to develop a marketing research project on the basis of contextual needs. At the end of the course students will be able to autonomously deepen their knowledge. This ability will be acquired through the combination of the different teaching method.
Course Contents
The course will be divided into three main parts.
The first part discusses the marketing research process and the phases to write a marketing research report. In particular, the main issues associated with research design, data collection techniques, questionnaire and experimental design are discussed.
In the second part, an overview of basic statistics to use the SPSS software is provided. Key topics covered in this part include exploratory data analysis, univariate and bivariate hypothesis testing.
In the third part, frequent and relevant marketing research topics, including some predictive modelling, A/B testing, experimental analysis, and mediation/moderation approaches will be discussed.
Reference Books
Malhotra, N.K. (2019), “Marketing Research: An applied approach, Global Edition”, Seventh edition, Pearson Prentice Hall
(You can also study from previous editions)
Slides will be posted on the course website after each lecture
Suggested textbook: Field, A. (2017) “Discovering Statistics using IBM SPSS Statistics”, Sage
Teaching Methods
1. Conventional lectures
2. Lab sessions
3. Teamwork
Assessment Method
1. Written individual final exam: 30%
2. Two intermediate team assignments: 25%
3. Marketing research project (team project): 45%
Thesis assignment criteria
Students are required to prepare a preliminary research proposal that will be carefully evaluated by the teaching team. More details will be discussed at the end of the course.
Week 1 Contenuto sessioni on line e on campus
Course introduction
Introduction to Research Design: Survey & Experiment
Malhotra, Chapters 1-4
Week 2 Contenuto sessioni on line e on campus
Measurement and Scaling
Malhotra, Chapters 8-10
Week 3 Contenuto sessioni on line e on campus
Questionnaire Design
Malhotra, Chapters 13-15
Lab Session 1: Qualtrics - Preparing a survey
Week 4 Contenuto sessioni on line e on campus
Introduction to Descriptive Statistics and Exploratory Data Analysis: Data Preparation, Frequency Distribution, Cross-tabulation, summary statistics
Malhotra, Chapters 14,15
Lab Session 2: From Qualtrics to SPSS; Introduction to SPSS (open and save a file, checking/changing scale type, importing Qualtrics survey data into a SPSS file, syntax usage); Computing Descriptive Statistics on SPSS
Week 5 Contenuto sessioni on line e on campus
Scale Validity: Factor Analysis
Scale Reliability: Reliability Analysis
Malhotra, Chapter 9, 19
Lab Session 3: Factor and Reliability analyses
Week 6 Contenuto sessioni on line e on campus
Lab Session 4: Experiment Creation on Qualtrics, Creating Independent Variables on SPSS
The Experimental Design
Sampling Design and Procedures
Malhotra, Chapters 7, 11
Week 7 Contenuto sessioni on line e on campus
Introduction to Hypothesis; Testing differences between groups and relationship between variables (t-tests, chi-square)
Lab Session 5: t-tests, chi-square test
Malhotra, Chapter 15
Week 8 Contenuto sessioni on line e on campus
One-way Analysis of Variance (ANOVA); how to conduct a pre-test
Lab Session 6: one-way ANOVA
Malhotra, Chapter 16
Week 9 Contenuto sessioni on line e on campus
Two-way ANOVA and the Moderating Effect
Lab Session 7: Two-way ANOVA, Moderation Analysis with Categorical Moderator
Malhotra, Chapter 16
Week 10 Contenuto sessioni on line e on campus
Predictive Models: Regression and Correlation, Dummy Variables
Lab Session 8: Regression Analysis
Malhotra, Chapter 17
Week 11 Contenuto sessioni on line e on campus
Introduction to Mediation Analysis; Moderation and Mediation on PROCESS
Lab Session 9: Moderation Analysis with Continuous Moderator (PROCESS); Mediation Analysis (PROCESS)
Week 12 Contenuto sessioni on line e on campus
Course Recap – Q&A