Digital Competition Economics Training Course

 Digital Competition Economics Training Course 

Introduction 

Digital Competition Economics examines how digital platforms, data-driven business models, algorithms, network effects, artificial intelligence, and online ecosystems are transforming competition and market power. Digital Competition Economics Training Course develops practical expertise in digital markets, competition economics, platform economics, market definition, pricing strategies, mergers and acquisitions, algorithmic competition, data economics, and digital antitrust. Participants will explore how technology companies create, maintain, and leverage market power while developing economically rigorous approaches for assessing competitive harm, innovation, consumer welfare, and market efficiency. 

The course provides a practical and globally relevant understanding of digital competition policy, combining economic theory, empirical analysis, regulatory frameworks, and real-world case studies. Participants will examine competition issues involving major technology platforms, online marketplaces, digital advertising, app stores, cloud computing, artificial intelligence, and data-intensive businesses. Through applied exercises and international case studies, learners will strengthen their ability to conduct market analysis, evaluate competitive effects, interpret digital evidence, and develop effective competition-policy recommendations for rapidly evolving digital economies. 

Course Objectives 

1. Analyze digital market structures and competitive dynamics.
2. Evaluate market power in technology-driven markets.
3. Apply advanced digital competition economics techniques.
4. Assess network effects and platform economics.
5. Analyze data-driven sources of competitive advantage.
6. Evaluate digital pricing and algorithmic strategies.
7. Conduct digital market definition and concentration analysis.
8. Assess mergers involving technology companies.
9. Identify anticompetitive conduct in digital ecosystems.
10. Apply empirical and quantitative competition analysis.
11. Evaluate innovation, consumer welfare, and dynamic competition.
12. Interpret emerging AI and algorithmic competition risks.
13. Develop evidence-based digital competition policy recommendations.

Organizational Benefits
 

1. Strengthens digital competition policy capabilities.
2. Improves technology-market risk assessment.
3. Supports evidence-based regulatory decisions.
4. Enhances merger and acquisition analysis.
5. Improves understanding of platform market power.
6. Strengthens economic and regulatory compliance.
7. Supports digital-market investigations.
8. Enhances strategic competition intelligence.
9. Improves assessment of innovation and consumer welfare.
10. Builds advanced institutional economic expertise.

Target Audiences
 

1. Competition economists and antitrust professionals.
2. Government regulators and policy analysts.
3. Economists and economic consultants.
4. Competition-law and corporate lawyers.
5. Technology and digital-market executives.
6. Researchers and university professionals.
7. M&A and investment professionals.
8. Compliance and regulatory specialists.

Course Duration: 5 days
 
Course Modules

Module 1: Foundations of Digital Competition Economics
 

• Evolution of digital economies and competition.
• Characteristics of digital markets and ecosystems.
• Market power in technology industries.
• Competition, innovation, and consumer welfare.
• Global case study: European digital-platform competition.
• Practical exercise: Mapping a digital market ecosystem.

Module 2: Platform Economics and Network Effects
 

• Two-sided and multi-sided platform markets.
• Direct and indirect network effects.
• Platform governance and ecosystem competition.
• Switching costs, lock-in, and interoperability.
• Global case study: Online marketplace competition.
• Practical exercise: Assessing platform network effects.

Module 3: Data, Algorithms, and Digital Market Power
 

• Economic value of data and data accumulation.
• Big data as a competitive advantage.
• Algorithmic pricing and competitive interaction.
• Artificial intelligence and market power.
• Global case study: Algorithmic competition in digital advertising.
• Practical exercise: Evaluating data-driven competitive advantages.

Module 4: Market Definition and Concentration Analysis
 

• Defining relevant digital product markets.
• Geographic market definition in digital services.
• Substitution, zero-price services, and quality dimensions.
• Market shares and concentration indicators.
• Global case study: Digital search and online advertising.
• Practical exercise: Conducting a digital market assessment.

Module 5: Anticompetitive Conduct in Digital Markets
 

• Abuse of dominance in technology markets.
• Exclusive dealing and self-preferencing.
• Predatory pricing and tying strategies.
• Access restrictions and interoperability concerns.
• Global case study: App-store competition investigations.
• Practical exercise: Identifying potential exclusionary conduct.

Module 6: Digital Mergers and Acquisitions
 

• Economic analysis of digital mergers.
• Acquisitions of emerging technology firms.
• Killer acquisitions and nascent competition.
• Vertical and conglomerate effects.
• Global case study: Major technology-sector merger reviews.
• Practical exercise: Evaluating digital merger effects.

Module 7: Empirical and Quantitative Digital Competition Analysis
 

• Econometric approaches to digital competition.
• Pricing, demand, and consumer behavior analysis.
• Market concentration and competitive-effects testing.
• Experimental and observational digital-market data.
• Global case study: Quantitative analysis of platform competition.
• Practical exercise: Developing a competition-analysis framework.

Module 8: Future Digital Competition Policy
 

• AI, generative AI, and emerging competition risks.
• Regulation of digital platforms and ecosystems.
• Innovation and dynamic competition.
• International digital competition-policy developments.
• Global case study: Comparative digital antitrust approaches.
• Capstone exercise: Developing a digital competition policy recommendation.

Training Methodology
 

• Instructor-led presentations and interactive lectures.
• Practical digital-market analysis and economic exercises.
• International case studies and regulatory examples.
• Group discussions, simulations, and problem-solving activities.
• Quantitative and evidence-based competition assessment.
• Capstone projects and participant presentations.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.
 
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
 
c. Course duration is flexible and the contents can be modified to fit any number of days.
 
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
 
e. One-year post-training support Consultation and Coaching provided after the course.
 
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.