Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
Belonging course: 
Course of Master's Degree Programme on FASHION, ART AND FOOD MANAGEMENT
Disciplinary sector: 
Year of study: 
Second semester
Hours of front activity: 



Course description

In the data-driven era, providing value means being able to translate data rapidly into value-add information.
The aim of the course is to provide a specific set of  techniques, competencies and procedures to perform exploration, iteration, and investigation of business data, for the purposes of obtaining better insights about a business that can lead to improved decision-making.
The learning objectives of the course can be declined as follows:
Knowledge and understanding:
Data analysis for business requires high technical expertise, which is one of the reasons why it is so in demand
In today's fast growly and highly complex world, executives and managers should have at least some basic skills in business data analysis.
the student must be able to identify the techniques useful for finding information, must be able to use the data sources already available and to process qualitative and quantitative data by interpreting the results. It must also be able to formulate a marketing problem, defining its resolution objectives and strategies, adequately choosing the quantitative tools available to correctly analyze the different types of information.
Ability to apply knowledge and understanding:
Business data analysis includes all the activities to help managers cope with strategic decisions, achieve major goals and solve complex problems, by collecting, analyzing and reporting the most relevant information. Information could be about the causes of the current situation, the most likely trends to occur, and what should be done as a result. At the end of the course, the student will have the main quantitative methods aimed at understanding, measuring and analyzing the evolution of the markets, studying the social and cultural environment, the economic and psychological factors to be which originates consumer behavior (need, perception and satisfaction). He will be able to plan a market research, identify the most suitable quantitative analysis technique to solve a certain marketing problem, elaborate and interpret the results obtained.
Autonomy of judgment:
Statistical methods are an essential support to the choice of target markets, especially, in the formulation and planning of marketing strategies, in the measure of the effectiveness of marketing tools, in the forecast of the real and financial aggregates. In this perspective, the course aims to provide an operational tool to investigate and process information, which originate in the markets, useful to cope with demand variability by means of appropriate statistical techniques. the student will be able to identify limits and advantages of each market analysis technique, within those studied, interpret quantitative results by providing concrete support to those who make strategic managerial decisions in the marketing area. Above all, he will be able to develop a specific analysis methodology for each marketing problem encountered.
Communication skills:
the student will have the opportunity to present a project work (ppt or precious) to the reference teacher, to the students and other interested teachers and to external interlocutors (companies involved) in seminars organized during the course. Above all, students will have to present results in a clear and appropriate form, with a technical-scientific language.
Learning skills:
the student will have to deepen his knowledge by consulting recommended articles and texts and participating in seminars relating to the topics of the course.


Basic knowledge of mathematics and statistics


The objective of this course consists in enabling students to develop the ability to process data, to use analytical and logical reasoning to gain information from the data. The main purpose is to find meaning in data so that the derived knowledge can be used to make informed decisions.
Activities can include identifying and verifying potential strategies and solutions, and testing the feasibility of the selected solutions. Analysis is based, as much as possible, on relevant, accurate and reliable information, often involving interactive and automated statistical analysis.
Students will manage quantitative tools aimed to the comprehension, the measure and the analysis of market evolution, as well as to the study of social and cultural environment, of economic and psychological factors where the consumer behavior originates (needs, perceptions and customer satisfaction). The course provides an iterative process of guided teaching and learning, including discussions, case studies, exercises and skills development activities.
It can be divided into five blocks, as follows:
I block (6 hours)
Planning a Research: how to collect data, eventually how to conduct a survey, how to analize, interpret and report results.
II block (12 hours)
Analysis of market potential and customer behaviour: multiple linear regression and logistic regression.
III block (8 hours)
Market segmentation techniques: Cluster analysis.
IV block (8 hours)
Positioning Techniques: MultiDimensional Scaling (MDS).
V block (6 hours)
Text Mining
VI block (8 hours)
Project work

The course provides an iterative process of guided teaching and learning, including discussions, case studies, exercises and skills development activities.
Students will deal with the following topics:
Planning a Research and analyze results by means of multiple regression models, factor analysis, cluster analysis and MultiDimensional Scaling (MDS) models.

Teaching Methods

The course will be organised in standard lessons and in computer lab. During the course, the implementation of quantitative techniques will be illustrated with the aid of main statistical softwares. A project work will address a problem solving analysis, which can be a strategic decision making support.


– Grover R., Vriens M. (2006), The Handbook of Marketing Research. Uses, Misuses, and Future Advances, Sage Pubblications
– Janssens W., Pelsmacker P., Van Kenhove P., Wijnen K. (2008), Marketing research with SPSS, Pearson Education
–Other material provided by teacher
SPSS manual

Learning assessment

For attendants a project work and software examination in computer classroom are expected. The project work will have a score to add to the final result of the test. The final multiple choice test will take place on moodle platform at link elearning.uniparthenope.it

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