17910 -
ECONOMIA COMPORTAMENTALE E TEORIA DEI CONSUMI
(objectives)
The course focuses on topics linked to consumer behavior which, in the light of the most recent analysis methodologies, is characterized by poor rationality, errors (bias) and a "heuristic" approach to solving problems. These behaviors together with the close relationship between emotion and purchase decision are used in the marketing sector to increase the purchase of products.
1. KNOWLEDGE AND UNDERSTANDING The course aims to provide basic theoretical and empirical knowledge in order to allow the student to independently understand consumer behavior and marketing strategies. This knowledge will be acquired mainly through lectures, reading targeted texts and participating in in-depth thematic seminars.
2. ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING The student must be able to apply the methodological and theoretical knowledge acquired in the interpretation of consumer behavior. These specific skills will be developed mainly through the study of case studies, the realization of the project work and the debate in the classroom.
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CACCHIARELLI Luca
( syllabus)
The course is divided into two parts. In the first part, our purpose is to study microeconomic theories related to demand (consumer preferences, revealed preferences and choice under uncertainty) and the most relevant topics of behavioural economics (paradoxes of rational choice theory, probability weighting, loss aversion, behavioural biases). In the second part, the course is devoted to focus on the main psychological models used to analyze consumer decision-making processes. Specifically, the role of cognitive and emotional factors affecting consumer choice. The last part of the course will cover relations between communication and consumer choice, the role of cognitive psychology in unfair trade practises analysis and the psychological bases of the context effects on consumer choice. The last short section of the course will cover the changes in the food consumption, in which consumers look for quality, food safety and environmental protection
( reference books)
1. Varian H. R. (2014). Intermediate Microeconomics (qualsiasi edizione). W. W. Norton & Company. I seguenti capitoli: Budget Constraint (Cap 2), Preferences (Cap 3), Utility (Cap 4), Choice (Capitolo 5 fino all’esempio di perfetti sostituti); Demand (Cap 6); Uncertainty (par. 12.2, 12.3 e 12.4); Consumers’ surplus (cap 14). 2. Guéguen, N. (2009). Psicologia del consumatore, Bologna: Il Mulino, 2010. 3. Bonini, N. & Hadjichristidis, C. (2009). Il sesto senso: Emozione e Ragione nella decisione, Il Sole24Ore: Milano. Cap 1, 2, 5 e 8
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8
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SECS-P/02
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48
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Core compulsory activities
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Optional group:
Gruppo di esami opzionali affini - (show)
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16
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119031 -
SOCIAL MEDIA MINING
(objectives)
In the age of digital transformation, an important part of information useful for organisations is available from unstructured data stored in office documents (word, power point, and pdf), on the web (web pages, blogs, and online communities) or social media. This information is crucial to understand environmental phenomena relevant for the lives of organisations. A major part of these pieces of information are stored in texts and are non structured. Moreover, this information shows many times all the characteristics of velocity, variety, and quantity of big data.
The course tackles the the technical challenges for organisations and the operational tools to identify, retrieve, extract, and analyse in an automatic manner data from non structured sources on the web and on social media. The course introduces to students the fundamentals organisational processes – sense making, decision making, and knowing – and the fundamentals of automatic analysis of textual data. The syllabus of the course includes also theoretical knowledge on the functioning of web technologies: web protocols, the HTML language, the data interchange formats (cvs and json), and the main APIs for accessing data on social media platforms.
Students attending the course will engage with data extraction, manipulation, and analysis from social media and web sites. The technical and operational knowledge acquired during the course can be used also for analysing other types of non structured data, such as reports, documents, or other data sources.
During the course the students will be engaged both in During the course the students will be engaged both in theoretical and practical learning, as individuals and in groups. The participation to the course will stimulate in students the following skills.
Knowledge and understanding Understand the opportunities and limits of big data, unstructured data, and automatic analysis of textual data. Know the fundamental organisational processes and the role that information plays in them. Know the theoretical foundations and the technical procedures for automatic data extraction and analysis of non structure data and textual data.
Applying knowledge and understanding Recognise the limitations and the potential domains of applications of the techniques for non structured data extraction, manipulation, and analysis. Recognise opportunities and risks in the use of information from non structured sources, from the web and from social media.
Making judgements Understand if and which data from non structure sources (web and social media) could satisfy the information need of people and organisations. Understand how to integrate structured and unstructured sources of data to answer to the information need of people and organisations. Be able to assess the information contained – and the potential biases – in unstructured data. Be able to interpret in an objective manner the information obtained from the automatic analysis of textual data.
Communication skills During the course the students will train the skills of presenting, arguing, and debating in public the results of their analysis and their interpretations.
Learning skills Be able to learn in an autonomous and self-managed way.
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BRACCINI Alessio maria
( syllabus)
The course syllabus is divided in a theoretical and a practical part. In the theoretical part the students will deepen the sense making, decision, making and knowing organisational processes. They will deepen the technical problems, and the application potential, of automatic analysis of non structured data and of textual analysis. They will also deepen other theoretical pieces of knowledge related to web technologies and social media.
In the practical part the students will deepen a set of practical competences related to the use of tools to collect, manipulate and analyse data for improving the information needs of organisations. In the practical part the students will focus on the following aspects: - Web scraping and social media mining - Data manipulation: cleaning, de-coding, re-coding, and transformation - Basic operations of text mining: creation of text corpora, extraction of tokens, lexicons, roots, stems, n-grams, and dtm/tdm matrices
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Margherita Emanuele Gabriel
( syllabus)
The course program is divided into a theoretical part and an application / practical part. In the theoretical part, students will deepen the organizational processes of sense making, decision making, and knowledge. They will investigate the technical problems and the potential of unstructured data analysis and automatic text analysis. They will also deepen theoretical knowledge related to the functioning of web technologies and social media. In the application / practical part, students will deepen a series of practical skills concerning the use of tools for collecting, manipulating and analyzing data functional to increase the information needs of organizations. In the application / practical part the following aspects will be addressed: - Web scapring and social media mining - Data manipulation: cleaning, coding, and transformation of data - Basic operations of text mining: creation of corpus, extraction of tokens, lexicons, roots, lemmas, n-gram, tdm / dtm matrices; - Advanced operations: semantic annotation, topic extraction, sentiment, emotion from the text, classifications
( reference books)
Simon Munzert, Christian Rubba, Peter Meißner, and Dominic Nyhuis Automated data collection with R: A practical guide to web scraping and text mining. John Wiley & Sons, 2014
ISBN 978-1118834817
Bing Liu Sentiment analysis: Mining opinions, sentiments, and emotions Cambridge University Press, 2015
ISBN 978-1107017894
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8
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SECS-P/10
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48
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Related or supplementary learning activities
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119036 -
ECONOMIA E MARKETING DEI PRODOTTI AGROALIMENTARI
(objectives)
The course aims to provide the theoretical and methodological tools: (i) to understand the structure of the economic system, with particular reference to the agri-food sector; (ii) to identify the characteristics of the production and consumption processes of agri-food products and their implications on the environmental and social dimension; (iii) to analyse the determinants of food consumers' choices and how these choices can drive the marketing strategies.
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FRANCO Silvio
( syllabus)
Part 1 - The paradigm 1.1 - Introduction to the course 1.2 - Environment and society in the history of economic thought 1.3 - Relations between environment and economy 1.4 - Discussion on the topics Part 2 - Economic processes: the case of the agri-food sector 2.1 - The nature of the economic process and its environmental and social implications 2.2 - The structure of agri-food production processes 2.3 - The structure of food consumption processes 2.4 - Discussion on the topics Part 3 - Sustainability in the agri-food sector 3.1 - The concepts of weak sustainability and strong sustainability 3.2 - Examples of assessment of the sustainability in the agri-food systems 3.3 - Discussion on the topics Part 4 - Consumers' behaviour and agri-food marketing 4.1 - The decision-making process of the consumer of agri-food products 4.2 - Perception of the quality and value of food 4.3 - The implications on agro-food marketing (evidences and examples) 4.4 - The implications on territorial marketing (evidences and examples) 4.5 - Discussion on the topics
( reference books)
- Silvio Franco, "Appunti dalle Lezioni di Economia e Marketing del Prodotti Agroalimentari", 2019
- Supplementary readings and insights
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8
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AGR/01
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48
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17911 -
MARKETING AND BIG DATA ANALITYCS
(objectives)
1) Conoscere i Big Data, cosa sono e come possono essere utilizzati dalle aziende in chiave strategica e in ottica di customer experience 2) Conoscere e Comprendere l’utilizzo dei Big Data, le fonti da cui provengono e le analisi che si possono attivare 3) Conoscere e Comprendere l’utilizzo delle principali tecniche di analisi dei Big Data 4) Conoscere e Comprendere l’utilizzo delle principali tecnologie per le fonti dei Big Data 5) Conoscere la normativa italiana ed europea in termini di privacy e di utilizzo dei Big Data 6) Conoscere e saper interpretare i dati derivanti dalle varie analytics dei Big Data e come possono essere utilizzati per definire la strategia di marketing customer oriented
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IANDIORIO Elisa
( syllabus)
OBJECTIVES AND DESCRIPTION OF THE COURSE
This training allows the students to acquire the competences and the knowledge necessary for the evaluation in business of the Big Data: what they are, how they are analysed and used in order to increase the business performances. Today the purchase of a good or service doesn't exclusively depend on the relation quality / price or price / performances, the customer experience has become an object of fundamental analysis for every type of enterprise. Today a firm can increase the sales and the billing thanks to the ability to offer its own products or services at the right moment, in the right place, to a specific person, by using the right channel. The attention has moved from the product to the consumer: all rotates around him and for this reason it is necessary to have an analysis of his needs but, above all, of his expectations, with the purpose to build an offer ad hoc to maximize the probabilities of purchase. The digital era and the Internet of Things provide the firms with all the necessary tools to supervise each phase of the Customer Journey getting great amounts of data useful to improve the Customer Experience, to direct the business strategy and to get valid economic return. At the end of this training the student will have acquired the necessary knowledge to develop a business strategy using the Big Data in order to analyse the consumer and his purchase behaviour. In short the training will allow the student to:
- evaluate the impact of the Big Data at technological and managerial level, including the level of analysis of the consumer behaviour
- understand the opportunities offered by the Big Data and their costs
- structure a business strategy according to the customer experience
INTRODUCTION ON THE METHODOLOGY OF PLANNING AND MANAGEMENT
The proposed training has been projected in order to balance frontal lessons with an interactive didactics, including the analysis and the theoretical explanation along with the exercises and case history
MAIN TOPICS
• The Big Data: what the Big Data are and why they are so important for the firms
• The way the Big Data changed the firms
• The Customer Experience: what it is and why it is important for the firms
• Internet of Things: what it is and how it revolutionizedd the way of analysing the consumer
• Technologies for the Big Data: the current tools to analyse the Big Data
• Developing a business strategy by using the Big Data
• Case History
( reference books)
"Big Data - Cosa sono, come analizzarli e utilizzarli per fare marketing" Autore: Elisa Iandiorio - Casa Editrice: Dario Flaccovio - Codice ISBN 9788857909257"
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8
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SECS-P/08
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48
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119032 -
INNOVAZIONE E CERTIFICAZIONE DEI PRODOTTI
(objectives)
1) Know the principles of technological innovation and related reference models. 2) Learning the principles to understand the dynamics of innovation and product certification for the competitiveness of companies, with particular reference to international markets. 3) Ability to communicate the principles of technological innovation and the requirements of product certification. 4) Ability to analyze data and the context of the reference markets for the correct implementation of technological innovation and to promote competitiveness. 5) Knowledge of product certification tools and production chains.
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RUGGIERI Alessandro
( syllabus)
1. Technological innovation: process and product innovation; the concept of 'innovative product'; sources of innovation; matching between research and innovation; startups and spinoffs. 2. Types of process and product: intermediate and final products; consumer products and industrial products; machinery and equipment; the international context; production chains: plastic materials; chemical industry; pharmaceutical; fashion system (clothing, textile industry, footwear), steel products; mechanic industry; automotive; agribusiness; digital and consumer electronics industry. 3. Impact of innovation on products and processes: digitization and automation (industry 4.0); new factory and production models; 'digital' products; new materials: green chemistry materials, bioplastics and biosensors; biotechnology; use of innovative processes and materials for 'traditional' products. 4. Product certification: types of certification; product certification; environmental product certification; the CE marking; production chain specifications; sector and supply chain certifications; the international framework; certification and export of products in non-EU markets.
( reference books)
Lecture notes and teaching materials provided by the professor
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8
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SECS-P/13
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48
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