Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
2016/2017
Belonging course: 
Course of Master's Degree Programme on METODI QUANTITATIVI PER LE DECISIONI AZIENDALI
Location: 
Napoli
Disciplinary sector: 
ECONOMIC STATISTICS (SECS-S/03)
Credits: 
6
Year of study: 
2
Teachers: 
Cycle: 
Second semester
Hours of front activity: 
48

Language

Italian

Course description

The course aims at developing expertise to:
- Be able to explore trends and relationships among business, market and context data
- Know how to use the methodology and tools that statistics provides to support decision-making and in the guidelines for geolocation choices
- Be able to interpret results from statistical methods and digital cartography tailored to the economic and marketing needs.

Expected learning outcomes:
Knowledge and understanding:
The student should be able to understand the main theories and models for the analysis of economic, business and market phenomena in a spatial framework. Moreover, he/she should know the main statistical tools for the territorial analysis of these topics as well as the main statistical sources of spatial microdata and metadata.
Applying knowledge and understanding:
The student should be able to know the spatial statistical tools and to implement them in specific statistical software. The student should be able to build the matrix of territorial data using information from external sources and to manage it using statistical software. He/she should be able to interpret correctly the output of spatial models obtained through statistical software.
Making judgements:
The student should be able to use the acquired knowledge in practical circumstances. Moreover, he/she should have the maturity and the ability to “think” autonomously a scientific work project and carry on in all its phases, from the definition of the subject to the data searching and to the implementation of statistical tools in the specific software.
Communication:
The student should be able to communicate clearly and with an adequate technical language the (individual and/or group) work projects to teacher and to the other colleagues of the Course. The student should be able to answer clearly and in-depth the questions of the oral examination.
Lifelong learning skills:
The student should be able to show a good learning ability and autonomy in investigating in-depth the matters of the Course using the references provided by the teacher.

Prerequisites

Basic knowledge of Statistics and Marketing

Syllabus

Geomarketing and statistics. Spatial data. Geocoding and Georeferencing. Representing spatial data: maps, cartography, Sit-Gis technology. Digital maps. Web maps and databases. Location decisions of enterprises. Territory and statistical information. Typologies and sources of spatial data. Territorial systems and classification. Territorial location and interaction of economic agents.
Territorial indicators. Methodology of composite indicators. Selection of basic indicators. Bivariate and multivariate association. Data transformation and normalisation. Weighting and aggregation systems. Sensitivity analysis. Study-cases on economic, business and market topics analysed using the methodology of composite indicators. Spatial lag. Spatial weigh matrix. Spatial autocorrelation. Multiple regression and spatial regression.

I module (24 hours):
Geomarketing and statistics. Spatial data. Geocoding and Georeferencing. Representing spatial data: maps, cartography, Sit-Gis technology. Digital maps. Web maps and databases. Location decisions of enterprises. Territory and statistical information. Typologies and sources of spatial data. Territorial systems and classification. Territorial location and interaction of economic agents.

II module (24 hours):
Territorial indicators. Methodology of composite indicators. Selection of basic indicators. Bivariate and multivariate association. Data transformation and normalisation. Weighting and aggregation systems. Sensitivity analysis. Study-cases on economic, business and market topics analysed using the methodology of composite indicators. Spatial lag. Spatial weigh matrix. Spatial autocorrelation. Multiple regression and spatial regression.

Teaching Methods

Traditional lectures. Exercises and pc-lab (SPSS, R, GeoDa, GeoDaSpace) and datawarehouse. Individual and group work projects.

Textbooks

- Amaduzzi S., Geomarketing. I sistemi informativi territoriali (Sit-Gis) a supporto delle aziende e della pubblica amministrazione. EPC editore.
- Gismondi R., Russo M.A. (2004), Definizione e calcolo di un indice territoriale di turisticità: un approccio statistico multivariato, Statistica, anno LXIV, n. 3
- OECD (2008), Handbook on constructing composite indicators – Methodology and user guide.
- Readings will be noted during classes (mainly papers)

Learning assessment

The learning assessment is on an ongoing basis during the Course. Students are continuously expected to take part into work projects using computer and statistical software. The discussion of the materials produced (R programs, elaborations with SPSS and Excel, GeoDa) and the presentation of their results to the teachers and to the other students are planned at the end of the Course using slides. This stage also includes an oral assessment of all the Course contents.

More information