Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
2021/2022
Belonging course: 
Course of Master's Degree Programme on AMMINISTRAZIONE, FINANZA E CONSULENZA AZIENDALE
Disciplinary sector: 
BUSINESS ADMINISTRATION AND MANAGEMENT (SECS-P/07)
Language: 
Italian
Credits: 
6
Year of study: 
2
Teachers: 
LARDO ALESSANDRA
Cycle: 
First Semester
Hours of front activity: 
48

Language

Italian

Course description

The course is designed to introduce students to the typical models and tools for analysing, evaluating and controlling company performance, with particular reference to developments linked to digital transformation.
The aim is to provide fundamental knowledge on the main and most advanced performance measurement models. In addition, the course will also focus on performance forecasting and analysis through the use of advanced software, tools that are changing the internal processes of organisations following the paradigm shift imposed by Industry 4.0 and artificial intelligence. Finally, the last part of the course will focus on the analysis of complex strategies for the management of knowledge and intellectual property in companies operating in the Fashion, Art and Food sectors in the digital era, also through the analysis of companies' case studies.

Prerequisites

Accounting; Financial and Managerial accounting; Management control.

Syllabus

The course content can be divided into several lecture modules, the duration of which depends on the students' level of preparation and their familiarity with the basic concepts of business economics, accounting, budget analysis, planning and control. In theory, the course is structured as follows:
I Module (1 CFU): Introduction to the concepts of digitisation of business performance, analysis of the main smart technologies and business intelligence tools. Introduction to performance measurement starting from financial statement analysis.
II Module (2 CFU): Modern performance measurement systems; insights on small and medium enterprises: the Cube model.
Module III (2 CFU): The impact of digital transformation on performance measurement and the development of forecasting and performance analysis models based on the use of smart technologies; in-depth study on Public Administrations; in-depth study on performance measurement in terms of sustainability (social, environmental, economic): non-financial reporting.
Module IV (1 CFU): Analysis of performance measurement models and tools to be applied to companies operating in the Fashion, Art and Food sectors. Managing and measuring the value of intellectual property for FAF companies in the digital era.

Management information systems: basic concepts. From the financial statements analysis to the modern performance measurement systems: the Tableau de Bord, the Prism performance, the Intangible asset monitor, the BSC, the Smart Pyramid. Insights on small and medium enterprises: the Cube model. In-depth information on Public Administrations. In-depth analysis of performance measurement in terms of sustainability (social, environmental): non-financial reporting. The use of spreadsheets for the construction of forecasting and performance analysis tools through the use of advanced software that meets the needs of top management to make strategic decisions in a context of increasing uncertainty and complexity.

Teaching Methods

Lezioni frontali, studio e discussione di casi, esercitazioni in laboratorio informatico.

Textbooks

N. Castellano (2012), La misurazione delle performance per le piccole imprese. Strumenti di misurazione e processi di controllo, Giappichelli.
Galeotti, M., & Garzella, S. (Eds.). (2013). Governo strategico dell'azienda. G Giappichelli Editore
Liebowitz, J. (2006). Strategic intelligence: business intelligence, competitive intelligence, and knowledge management. CRC Press.
Trequattrini, R., & Lardo, A. (2019). Il governo delle aziende copyright-based nell'era digitale: Profili teorici e dinamiche evolutive nella prospettiva economico-aziendale. FrancoAngeli (Chapters 2 and 5).
The lecturer will supplement the recommended texts with some articles, cases, notes that will be distributed during the course and made available on the University's e-learning platform.
Other useful reference texts are:
Van Rijmenam, M. (2019). The Organisation of Tomorrow: How AI, blockchain and analytics turn your business into a data organisation. Routledge.

Learning assessment

The assessment of expected learning outcomes will be done in different ways and at different times. Specifically, in itinere the learning outcomes will be ascertained through training tests based on: structured tests, aimed at ascertaining the acquisition of knowledge; the use of business cases, aimed at ascertaining the acquisition of skills. At the end of the course, instead, the expected learning outcomes will be ascertained through a written test. The test consists of multiple-choice questions, two open-ended questions and the performance of exercises.
The assessment criteria and scores are determined according to the following scale:
- less than 18/30 - insufficient level: you will not achieve any of the learning outcomes listed under 'knowledge and understanding';
- 18-20/30 - sufficient level: the candidate achieves, in particular, the learning outcomes expected under 'knowledge and understanding';
- 21-23/30 - fully sufficient level: the candidate achieves, in particular, the learning outcomes foreseen under 'knowledge and understanding' and 'applied knowledge and understanding';
- 24-26/30 - good level: the candidate achieves, in particular, the expected learning outcomes under 'knowledge and understanding', 'applied knowledge and understanding' and 'independent judgement';
- 27-29/30 - very good level: the candidate achieves, in particular, the learning outcomes listed under 'knowledge and understanding', 'applied knowledge and understanding', 'applied autonomy of judgement' and 'communication skills';
- 30-30 cum laude - excellent level: the candidate fully achieves the expected learning outcomes under 'knowledge and understanding'; 'applied knowledge and understanding'; 'independent judgement'; 'communicative skills' and 'learning ability'.

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