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Emerging Trends in the Sports Industry

Code: 44834 ECTS Credits: 9
2024/2025
Degree Type Year
4316022 Sport Management OT 0

Contact

Name:
Ricard Esparza Masana
Email:
ricard.esparza@uab.cat

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

There are no prerequisits.


Objectives and Contextualisation

- Gain insight into the evolving landscape of the sports industry, including its legal and governance aspects, digital and green transformation, and the role of data science.

- Learn essential management tools, digital transition strategies, and the impact of social networks, Big Data, and AI in sports organizations.

- Explore the unique data challenges and opportunities in sports, from fan engagement and performance analysis to IoT, AI, and blockchain applications, while building practical analytics skills.


Learning Outcomes

  1. CA15 (Competence) Apply new technologies, especially digitisation, to decision-making, especially in (intra)entrepreneurial projects.
  2. CA16 (Competence) Compare and contrast different ways (traditional and new) to offer products and services in the sports market and identify the potential market.
  3. CA17 (Competence) Question the different possibilities of business models whilst taking into consideration the aspects related to Industry 4.0 and environmental sustainability.
  4. KA21 (Knowledge) Recognise new market trends in the sports industry.
  5. KA22 (Knowledge) Identify the main current technological solutions that can be applied to the sports industry, as well as those that will be possible in the near future.
  6. SA33 (Skill) Implement activities using new technologies available for existing products and services in the sports industry in order to strengthen competitiveness.
  7. SA34 (Skill) Come up with proposals for new business opportunities based on new trends in the sports industry.

Content

1. Current governance trends in the sports business

2. Digital transformation in the sports industry

3. Green and sustainable transition in the sports industry


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Participatory theoretical session 45 1.8
Problem solving, exercises in the ordinary classroom 15 0.6
Type: Supervised      
Study cases 15 0.6
Supervision of group work and class discussions 15 0.6
Type: Autonomous      
Problem solving, exercises 30 1.2
Studying hours 90 3.6

Online modality


In the case of the online modality, the methodology will be adjusted in order students can achieve all the learning outcomes specified in this guide and at the same time develop the skills and abilities of the subject.

To this end, the resources available in the modle classrooms will be optimized to maximize student involvement and motivation (forums, debates, simulation games, case studies, online presentations, etc ...)

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Applied activities to be solved and submitted 40% 5 0.2 CA15, CA16, CA17, KA21, SA33, SA34
Exam 30% 2 0.08 KA21, KA22, SA33, SA34
Individual theoretical and practical activities 30% 8 0.32 CA15, CA16, CA17, KA21, KA22, SA33, SA34

Theoretical-practical tests/tasks: Submission of tasks; Presentation and defence of the exercises and works carried out (they can be individual and/or in group).

Individual theoretical and practical works: Delivery of exercises and works, as well as participation in forums and debates.

The teaching team will detail the specific activities at the beginning of the module.


Bibliography

Complementary readings:

- "Sports Law and Regulation: Cases, Materials, and Problems" by Matthew J. Mitten, Timothy Davis, Rodney K. Smith, and Robert C. Berry.

- "Sports Analytics and Data Science: Winning the Game with Methods and Models" by Thomas W. Miller.

- "Sport Business Analytics: Using Data to Increase Revenue and Improve Operational Efficiency" by C. Keith Harrison and Scott Bukstein.

- "Sports Data Analytics: Using Data to Improve Performance and Win More Games" by Daniel A. Y. Fort.


Software

N/A


Language list

Name Group Language Semester Turn
(TE) Theory 1 Spanish annual afternoon
(TE) Theory 5 English annual morning-mixed
(TE) Theory 10 Spanish annual morning-mixed