Bachelor in Business Intelligence and Data Analytics

Bachelor in Business Intelligence and Data Analytics

Become an expert in data analysis and business decision making in a technological ecosystem and with great networking opportunities

Digital economy principles

Description: 

The digital economy is expanding quickly, particularly through digital business models. In fact, the six most valuable businesses (by market cap) are all significant participants in the digital economy. Knowing the economics of digital goods and services is critical to understanding how the global economy functions. This includes innovations such as social media, apps, cloud computing, mass storage, data mining, cryptocurrencies or sharing services, among others. The corporate landscape of today has been highly affected by these changes.

Type Subject
Primer - Obligatoria
Semester
Second
Course
1
Credits
6.00

Titular Professors

Previous Knowledge: 

Principles of Business Management

Objectives: 

This cross-disciplinary course will let students learn and put into practice the basics of today's economy, considering the key elements of digital technologies. Along with this, it will offer theoretical and practical insights for the students to be applied for the investigation of actual business and economic markets.

Contents: 

1.         Introduction and course overview

2.         Competitive advantage, analytics, and platforms

3.         Managing ecosystems

4.         Data strategy

5.         Innovation and platforms

6.         AI and cognitive biases

7.         Introduction to crypto and blockchain

8.         Metaverse

9.         Business models

Methodology: 

Students are expected to come to class prepared, having completed a first approximation to each topic. Lecture slides will be available to download, and casual online videos will also be referenced for class preparation and review. Good preparation will generate more time for interactive class sessions and a project work. This project will need to be submitted and presented before the end of each semester. In addition to group task, weekly activities will also be assigned to assess students' understanding of the material covered in class. This should help students develop study routines for the subject and face exams with confidence.

The main methodologies used for this course are:

MD.0     Master class

MD.1     Problem-oriented classes and exercises

MD.4     Seminars

MD.6     Project-based learning

Evaluation: 

This course consists of the following evaluation activities:

Homework Completion and class participation (moderately significant assessment activity) / 25% of the final grade. This activity not only assesses that the exercises, readings, case studies, etc., are being completed but also that at the end the knowledge explained in the classroom is understood and allows the student to advance positively throughout the course. Homework assignments will consist of quizzes (multiple choice questions), required readings, and practical cases. Finally, the student's participation in class will also be considered.

Semester group project (highly significant evaluation activity) / 20% of the final grade. Students will work on a project that must be completed in group and submitted through a scheduled task on the eStudy platform. The project will be presented in class before the final exam.

Midterm exam (highly significant evaluation activity) / 25%of the final grade. The midterm exam will consist of a part with multiple-choice questions and another part with long-answer questions where students will have to answer on topics and/or issues worked throughout the course. The examwill not allow students to consult class materials or notes.

Final evaluation (highly significant evaluation activity) / 30% of the final grade. The final exam will also consist of a part with multiple-choice questions and another part with long-answer questions where students will have to answer topics and/or issues worked on throughout the course. This exam will evaluate the students on any topic worked on during the course, and therefore may question the students again on issues worked on and asked in the partial exam. This exam does not allow students to consult class materials or notes either.

 

To pass the subject, the overall score must be higher than 5.

There is no retake exam for this course. Students who fail will have to re-register for the course next year.

Evaluation Criteria: 

To pass the subject, the overall score must be higher than 5.

There is no retake exam for this course. Students who fail will have to re-register for the course next year.

Basic Bibliography: 

Øverby, H., & Audestad, J. A. (2021). Introduction to Digital Economics: Foundations, Business Models and Case Studies. Springer Nature.

Additional Material: 

Acemoglu, D., & Robinson, J. A. (2013). Why Nations Fail. Currency. Begg, D., Dornbush, R. & Fisher, S., ECONOMICS, Ed. Mc Graw Hill.

Brunton, F. Digital Cash (2019). The unknown history of the anarchists, utopians, and technologists who created cryptocurrency. Princeton University Press, 2019.

Holroyd, C.; Coates, Ken S. (2015). The Global Digital Economy: A Comparative Policy Analysis-Student Edition. Cambridge Press.

Hu, Tung-Hui. (2015). A Prehistory of the Cloud. MIT press.

Huws, U.(2014). Labor in the global digital economy: The cybertariat comes of age. NYU Press.

Jab?o?ski, A.; Jab?o?ski, M. (2020). Social Business Models in the Digital Economy. Palgrave Macmillan, 2020. Jordan, T.; The Digital Economy. Polity Press.

Mankiw, G., Taylor, M. (2015). ECONOMICS, Cengage Learning EMEA, 3rd Edition.