Intellectual Property for Business: Strategy and Analysis
A.Y. 2019/2020
Learning objectives
This module has been developed to connect cutting-edge techniques for data management and analysis in the field of management of intellectual property rights to teaching in the classroom. It aims to facilitate learning about key developments and applications in the intellectual property rights field. The module helps students to develop up-to-date empirical skills for the formulation of appropriate strategies in the area of intellectual property rights at the business level. It examines available data sources of intellectual property rights and equips students with up-to-date knowledge and thinking from experts in this area. This module aims to provide a dynamic platform for learning, which exploits the latest research and practice from experts (academics and practitioners) exploiting a hand-on approach.
Expected learning outcomes
During the module all learning outcomes below will be introduced, developed and assessed.
Knowledge and Understanding
Having successfully completed this module you will be able to demonstrate knowledge and understanding of:
1. The key and advanced dimensions of data management for intellectual property rights - Retrieval, Cleaning, Analysis, Choice and Implementation;
2. Diagnostic, practical and creative skills to analyse and evaluate a range of business solutions in relation to intellectual property rights;
3. Organisations' ability to implement chosen strategies and identify the areas requiring change.
Subject Specific Intellectual (Cognitive) skills
Having successfully completed this module you will be able to:
4. Develop skills in generating alternative solutions to complex issues surrounding intellectual property rights management at the business level, underpinning each with a supportive and well researched rationale in order to achieve critical success;
5. Evaluate these solutions, analysing the impact of potential outcomes on the various stakeholder groups;
6. Analyse alternative strategies for intellectual property development in differing operating contexts;
7. Assess the importance of data quality and design of indicators to effective intellectual property management;
Transferable (Key general) skills
Having successfully completed this module you will be able to:
8. Obtain, analyse and apply information from a variety of sources in the public and private domains;
9. Master new hard skills in relation to specialised software for the retrieval and analysis of intellectual property data;
10. Work collectively as an effective and efficient group member, including, where appropriate, organising, guiding and motivating others;
11. Plan and enact the successful completion of a personal workload;
12. Communicate both orally and in written form, using and justifying arguments within reports, presentations and debates.
Knowledge and Understanding
Having successfully completed this module you will be able to demonstrate knowledge and understanding of:
1. The key and advanced dimensions of data management for intellectual property rights - Retrieval, Cleaning, Analysis, Choice and Implementation;
2. Diagnostic, practical and creative skills to analyse and evaluate a range of business solutions in relation to intellectual property rights;
3. Organisations' ability to implement chosen strategies and identify the areas requiring change.
Subject Specific Intellectual (Cognitive) skills
Having successfully completed this module you will be able to:
4. Develop skills in generating alternative solutions to complex issues surrounding intellectual property rights management at the business level, underpinning each with a supportive and well researched rationale in order to achieve critical success;
5. Evaluate these solutions, analysing the impact of potential outcomes on the various stakeholder groups;
6. Analyse alternative strategies for intellectual property development in differing operating contexts;
7. Assess the importance of data quality and design of indicators to effective intellectual property management;
Transferable (Key general) skills
Having successfully completed this module you will be able to:
8. Obtain, analyse and apply information from a variety of sources in the public and private domains;
9. Master new hard skills in relation to specialised software for the retrieval and analysis of intellectual property data;
10. Work collectively as an effective and efficient group member, including, where appropriate, organising, guiding and motivating others;
11. Plan and enact the successful completion of a personal workload;
12. Communicate both orally and in written form, using and justifying arguments within reports, presentations and debates.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
Please find below a week-by-week schedule for this course module. Please note that there are sometimes unforeseen circumstances, such as staff illness and deeper coverage of some topics, that may necessitate some changes to this schedule (e.g. order and coverage of topics). To this end, the topics covered in week 9 will be kept as buffer (i.e. they may be covered or not). The lecturer will make every effort to communicate these changes to students in good time.
w1.Introduction
Introduction to the module
IP and strategy
w2. Foundations I
Intellectual capitalism and the appropriation of innovation
IPRS and the need for data
Which data from a patent document?
Main data sources for patent
Individual presentations
Hand-on activities
w3-w4. Foundations II
Student competition launch
Patent indicators
Hand-on tutorials on data retrieval, patent databases and software for analysis
w5-w7. Capturing value: profiting from innovation and the market for ideas
Mentoring session
Managing IPRs
Implications of IPRs in a global environment
Complementary assets
The influence of standards
Organising to capture value
Individual presentations
w7-w9. Analysis of competition and cooperation
Mentoring sessions
Patent intermediaries
Patent transactions
Citations, Co-inventions and Co-applications
Patenting strategic groups
Technological evolutions
Individual presentations
w10. Wrap-up
Final workshop
w1.Introduction
Introduction to the module
IP and strategy
w2. Foundations I
Intellectual capitalism and the appropriation of innovation
IPRS and the need for data
Which data from a patent document?
Main data sources for patent
Individual presentations
Hand-on activities
w3-w4. Foundations II
Student competition launch
Patent indicators
Hand-on tutorials on data retrieval, patent databases and software for analysis
w5-w7. Capturing value: profiting from innovation and the market for ideas
Mentoring session
Managing IPRs
Implications of IPRs in a global environment
Complementary assets
The influence of standards
Organising to capture value
Individual presentations
w7-w9. Analysis of competition and cooperation
Mentoring sessions
Patent intermediaries
Patent transactions
Citations, Co-inventions and Co-applications
Patenting strategic groups
Technological evolutions
Individual presentations
w10. Wrap-up
Final workshop
Prerequisites for admission
Prerequisites refer to core topics in the following areas: Industrial Organisation, Economics and Management of Innovation and Quantitative Methods
Teaching methods
A number of teaching methods will be used in lectures in order to cater to a variety of learning styles and address the learning needs of the diverse student population. Please find a non-exhaustive list of the teaching/learning methods that might be employed during classes:
Face-to-face lectures
Guest speaker's talks (in class or in distance)
Exercises (exercises, database, software etc.)
Case studies
Individual assignments
Group assignments
Interactive class activities (role playing, business game, simulation, online forum, instant polls)
Class sessions will be interactive. A number of the classes will be devoted to case discussions where the task of analysing the issues in the case will be undertaken by the class as a whole or in small groups. In other classes, students are expected to contribute their ideas on the issues being discussed and examples drawn from their personal experiences and from reading the business/academic press. These classes will involve a discussion of academic articles or other in-class activities.
Face-to-face lectures
Guest speaker's talks (in class or in distance)
Exercises (exercises, database, software etc.)
Case studies
Individual assignments
Group assignments
Interactive class activities (role playing, business game, simulation, online forum, instant polls)
Class sessions will be interactive. A number of the classes will be devoted to case discussions where the task of analysing the issues in the case will be undertaken by the class as a whole or in small groups. In other classes, students are expected to contribute their ideas on the issues being discussed and examples drawn from their personal experiences and from reading the business/academic press. These classes will involve a discussion of academic articles or other in-class activities.
Teaching Resources
There is no core textbook that students should read in preparation for this course. As this is an advanced course, the core of the preparation comes from a variety of material (slides, cases, academic and professional readings, exercises, hands-on tutorials etc.). Details on all the material (including slides for each class) can be found on Ariel. Most of them are available in the library as a printed or an electronic copy or available on Ariel or external repositories.
Assessment methods and Criteria
Assessment methods - attending students
Note that this course does not have a final exam for attending students and the evaluation will be based on a combination of class participation (20%), Individual paper presentation and write-ups (40%) and final group presentation (40%).
Class participation - 20%
Class participation reflects the assessment of students' contribution to class learning:
Does the student interact with fellow students and the professor regularly?
Are his/her comments and questions well informed, reflecting careful analysis?
Do student's comments and questions add to the understanding of the situation and show creativity?
Does the student ask questions to other students? Do his/her comments link previous contributions and follow the overall direction of the discussion?
Individual paper presentation and write-ups - 40%
Students will be asked to prepare and deliver at least two presentations and hand in two brief memos related to two academic/professional papers (the exact number will depend on the number of attending students). During the first week, the students will be randomly assigned to the papers. The presentations and write-ups are individually prepared.
Final group presentation - 40%
Students are expected to deliver and hand in a presentation aimed at analysing an important strategic issue at a firm using the concepts and frameworks from class.
Assessment methods - non-attending students
Non-attending students will be evaluated through a nal exam that covers all the material discussed in class (e.g., cases, readings, relevant theoretical framework, exercises, hands-on tutorials, etc.). All the material (including slides for each class) can be found on Ariel. The nal exam will consist of a combination of multiple-choice and short questions and will be up to 2 hours long.
Assessment Details [DSE STUDENTS ONLY]
Students from the MSc programme in Data Science and Economics are expected to earn 6 ECTS credits instead of 9. Information about the assessment for attending and non-attending students is provided below:
Assessment methods - DSE attending students
DSE attending students should attend classes for a total of 40 contact hours. They are free to pick the hours they prefer but their attendance will be checked through appropriate means. Provisions for attendance are similar to the ones for non-DSE attending students. Assessment will be similar to the one for non-DSE students (please refer to section above) as per the following:
20% - Their mark on class participation will be referred to the reduced number of total contact hours (40 contact hours).
40% - They are expected to prepare and deliver fewer paper presentations (the exact number will depend on overall number of attending students)
40% - They will conduct the group work together with the students from the assigned group and participate to mentoring sessions
Assessment methods - DSE non-attending students
DSE non-attending students will be evaluated through a nal exam that covers all the material discussed in class (e.g., cases, readings, relevant theoretical framework, exercises, hand-on tutorials, etc.) expect for the material for weeks 7, 8 and 9 (see the section with the schedule). All the material (including slides for each class) can be found on Ariel. The nal exam will consist of a combination of multiple choice and short questions and will be up to 2 hours long.
Note that this course does not have a final exam for attending students and the evaluation will be based on a combination of class participation (20%), Individual paper presentation and write-ups (40%) and final group presentation (40%).
Class participation - 20%
Class participation reflects the assessment of students' contribution to class learning:
Does the student interact with fellow students and the professor regularly?
Are his/her comments and questions well informed, reflecting careful analysis?
Do student's comments and questions add to the understanding of the situation and show creativity?
Does the student ask questions to other students? Do his/her comments link previous contributions and follow the overall direction of the discussion?
Individual paper presentation and write-ups - 40%
Students will be asked to prepare and deliver at least two presentations and hand in two brief memos related to two academic/professional papers (the exact number will depend on the number of attending students). During the first week, the students will be randomly assigned to the papers. The presentations and write-ups are individually prepared.
Final group presentation - 40%
Students are expected to deliver and hand in a presentation aimed at analysing an important strategic issue at a firm using the concepts and frameworks from class.
Assessment methods - non-attending students
Non-attending students will be evaluated through a nal exam that covers all the material discussed in class (e.g., cases, readings, relevant theoretical framework, exercises, hands-on tutorials, etc.). All the material (including slides for each class) can be found on Ariel. The nal exam will consist of a combination of multiple-choice and short questions and will be up to 2 hours long.
Assessment Details [DSE STUDENTS ONLY]
Students from the MSc programme in Data Science and Economics are expected to earn 6 ECTS credits instead of 9. Information about the assessment for attending and non-attending students is provided below:
Assessment methods - DSE attending students
DSE attending students should attend classes for a total of 40 contact hours. They are free to pick the hours they prefer but their attendance will be checked through appropriate means. Provisions for attendance are similar to the ones for non-DSE attending students. Assessment will be similar to the one for non-DSE students (please refer to section above) as per the following:
20% - Their mark on class participation will be referred to the reduced number of total contact hours (40 contact hours).
40% - They are expected to prepare and deliver fewer paper presentations (the exact number will depend on overall number of attending students)
40% - They will conduct the group work together with the students from the assigned group and participate to mentoring sessions
Assessment methods - DSE non-attending students
DSE non-attending students will be evaluated through a nal exam that covers all the material discussed in class (e.g., cases, readings, relevant theoretical framework, exercises, hand-on tutorials, etc.) expect for the material for weeks 7, 8 and 9 (see the section with the schedule). All the material (including slides for each class) can be found on Ariel. The nal exam will consist of a combination of multiple choice and short questions and will be up to 2 hours long.
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT - University credits: 6
Lessons: 40 hours
Professor:
Rentocchini Francesco
Shifts:
-
Professor:
Rentocchini FrancescoProfessor(s)
Reception:
Find a free slot that fits your schedule at the link below and book it (at least 24h ahead). For remote office hours, use Microsoft Teams (use code "zbyxyzp" to enter the channel at first connection)
DEMM Office 17 / Microsoft Teams