Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
2015/2016
Belonging course: 
Course of Master's Degree Programme on METODI QUANTITATIVI PER LE DECISIONI AZIENDALI
Location: 
Napoli
Disciplinary sector: 
MANAGEMENT (SECS-P/08)
Credits: 
3
Year of study: 
2
Teachers: 
Prof. POPOLI Paolo
Cycle: 
Second semester
Hours of front activity: 
24

Language

Course description

Objectives of the course
The course aims to provide basic knowledge on the concept of the performance, and on measurement principles and methods, for the purpose of strategic and operational control of the company. The study program will allow the student to know the principles and the basic criteria of the measurement and analysis of performance, observed in their multidimensionality: competitive performance, social performance, performance of internal processes, innovation and learning, and financial performance.

Expected learning outcomes
Knowledge and understanding skills. The course intends to give the instruments required to analyse statistical models for performance evaluation. The student will be able to analyse several online data warehouses, by using appropriate statistical methods, and observing both Italian and European scenario from an original point of view.
Applying knowledge and understanding. The course aims to analyse several models for evaluation, also by using the appropriate statistical packages, in order to evaluate the main features of implications of the different statistical approaches .
Making judgements. The student will be able to understand simple and complex phenomena, by using indicators built on the available information. In more detail, the student will be able to:
• study the relationships in a multidimensional scenario;
• apply several statistical methodologies;
• perform analysis thorough statistical software.
The presentation of several “case studies” could help in a better understanding of different statistical tools.
Communicative Skills. At the end of the course, the student will be able to explain the results of the model through an appropriate vocabulary. The presentation by powerpoint slides will help student pass the final exam.
Lifelong learning skills. Learning skills will be stimulated through power point presentations and discussions among the students in the classroom. Several presentations connected to previous researchers and the analysis of some scientific articles (or essays) will increase the student’s background.

Prerequisites

General knowledge and reasoning ability. Prerequisite skills are the basic knowledge of descriptive and inferential statistics. Students who lack the prerequisites for this course can refer to the professor who will supply a bibliography or supplementary content.

Syllabus

The course is organised as follows: Section 1 reviews statistical methods for assessing business performance (8 hours; 1 credit). Section 2 combines efficiency and productivity (8 hours; 1 credits). Section 3 considers the efficiency measures and the nonparametric approach to estimating technical efficiency (Data Envelopment Analysis - DEA). The parametric approach (16 hours; 2 credits) Section 4 concerns the productive activity structure and the recent features related to the multivariate statistical analysis of financial ratios (8 hours; 1 credits). Section 5 deals with several data warehouses for the quantitative analysis of economic phenomena, by using relevant statistical packages (8 hours; 1 credit).

Course organization: traditional teaching.

During the lessons the issues mentioned in the study program will be discussed and presented, together with applications by using statistical software. Slides and supplementary material can be downloaded from the Moodle platform.

Teaching Methods

Textbooks

Textbooks and supplementary suggested readings
Bracalente B., Cossignani M., Mulas A. (2009), Statistica aziendale, McGraw Hill.
Giovannini E. (2008), Understanding Economic Statistics: an OECD Perspective, OECD
Zhu J. (2015), Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, 2nd edition, Springer.

Slides and supplementary material.

Learning assessment

More information