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Why Some Platforms Thrive and Others Don’t
Feng Zhu
MBA Class of 1958 Professor of Business Administration
Feb 6, 2019 Disney’s soon-to-
launch streaming service and
Netflix competitor, known as
Disney+, will include non-
Disney programming at
launch, Disney CEO Bob Iger
confirmed in a call with investors
following Disney’s earnings on
Tuesday.
Performance Heterogeneity Among Platforms
• Airbnb: $48 Billion (12/2020) => $68 Billion (yesterday)
• Uber: $92 Billion (12/2020) => $55 Billion (yesterday)
• TaskRabbit: $120 Million, acquired by IKEA (2017)
• Groupon: $13 Billion at IPO (2011), $278 M (yesterday)
A few network properties can have strong influences on
market competitiveness and platform performance
1. Strength of Network Effects
2. Vulnerability to Multihoming
3. Degree of Network Clustering
4. Risk of Disintermediation
5. Opportunities for Network Bridging
1. Strength of Network Effects
To what degree utility of a user depends on the participation of other users
Cross-Side (indirect) Network Effects
YouTube, Uber, Android/iOS, etc.
Data Network Effects
Search engines, recommendation systems, etc.
Same-Side (Direct) Network Effects
Facebook, WeChat, etc.
Network effects can transform competitive dynamics
X =
Highly competitive market
Technologies that generate
network effects Amazon Echo with > 50% share
X =
Network effects can be limited
2. Vulnerability to Multihoming
App developers/
Service providers
Consumers
Platform A Platform B
“Seesaw Effect”
Low multihoming on one side leads to high multihoming on the other side.
A platform could reduce multihoming on both sides to defend
market position
Consumers: Prime
Third-Party Sellers: Fulfillment Centers
3. Degree of Network Clustering
Uber Airbnb
3. Degree of Network Clustering
Uber Airbnb
Groupon
UberEats
Instacart
Booking
Expedia
4. Risk of Disintermediation
Consumers
Service
Providers
Platform
5. Opportunities for Network Bridging
• Build and connect multiple networks to one another and exploit synergies.
• The installed bases and data on their interactions are valuable in multiple
scenarios and markets.
Understand 1) the impact of network properties on market
competitiveness and platform performance and 2) the impact of
platform strategy on network properties
Network Effects
Multihoming
Network Clustering
Disintermediation
Network Bridging
Market
Competitiveness
&
Platform
Performance
Platform
Strategy
Feng Zhu and Marco Iansiti, “Why Some Platforms Thrive and Others Don’t.” January-February 2019.
Harvard Business Review 97(1): 118–125.
Academic Publications and Business Cases
• Feng Zhu, Xinxin Li, Ehsan Valavi, and Marco Iansiti, “Network
Interconnectivity and Entry into Platform Markets.” 2021.
Information Systems Research 32(3): 1009–1024.
• Hui Li and Feng Zhu, “Information Transparency, Multihoming,
and Platform Competition: A Natural Experiment in the Daily
Deals Market.” 2021. Management Science 67(7): 4384–4407.
• K. Francis Park, Robert Seamans, and Feng Zhu, “Homing and
Platform Responses to Entry: Historical Evidence from the U.S.
Newspaper Industry.” 2021. Strategic Management Journal 42(4):
684–709.
• Grace Gu and Feng Zhu, “Trust and Disintermediation:
Evidence from an Online Freelance Marketplace.” 2021.
Management Science 67(2): 794–807.
• Feng Zhu and Marco Iansiti, “Entry into Platform-Based
Markets.” 2012. Strategic Management Journal 33(1): 88–106.
• Michael Zhang and Feng Zhu, “Group Size and Incentives to
Contribute: A Natural Experiment at Chinese Wikipedia.” 2011.
American Economic Review 101(4): 1601–1615.
• Chiara Farronato, Michael W. Toffel, and Feng Zhu. “Digital
Platforms: An Introduction.” Harvard Business School Technical
Note 621-016 (2020).
• Krishna G. Palepu, Feng Zhu, Susie L. Ma, and Kerry Herman.
“Ant Group (A).” Harvard Business School Case 122-003 (2021).
• Feng Zhu, Weiru Chen, and Shirley Sun, “ZBJ: Building a Global
Outsourcing Platform for Knowledge Workers (A).” Harvard
Business School Case 618-044 (2018) (Revised 2019).
• Feng Zhu, Krishna G. Palepu, Bonnie Yining Cao, and Dawn H.
Lau, “Pinduoduo.” Harvard Business School Case 620-040
(2019).
• Feng Zhu and Angela Acocella, “Fasten: Challenging Uber and
Lyft with a New Business Model.” Harvard Business School
Case 616-062 (2016) (Revised 2018, 2020).
Thank you!
z@hbs.edu

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Media Mergers – Feng Zhu – September 2022 OECD Discussion

  • 1. Why Some Platforms Thrive and Others Don’t Feng Zhu MBA Class of 1958 Professor of Business Administration
  • 2.
  • 3. Feb 6, 2019 Disney’s soon-to- launch streaming service and Netflix competitor, known as Disney+, will include non- Disney programming at launch, Disney CEO Bob Iger confirmed in a call with investors following Disney’s earnings on Tuesday.
  • 4. Performance Heterogeneity Among Platforms • Airbnb: $48 Billion (12/2020) => $68 Billion (yesterday) • Uber: $92 Billion (12/2020) => $55 Billion (yesterday) • TaskRabbit: $120 Million, acquired by IKEA (2017) • Groupon: $13 Billion at IPO (2011), $278 M (yesterday)
  • 5. A few network properties can have strong influences on market competitiveness and platform performance 1. Strength of Network Effects 2. Vulnerability to Multihoming 3. Degree of Network Clustering 4. Risk of Disintermediation 5. Opportunities for Network Bridging
  • 6. 1. Strength of Network Effects To what degree utility of a user depends on the participation of other users Cross-Side (indirect) Network Effects YouTube, Uber, Android/iOS, etc. Data Network Effects Search engines, recommendation systems, etc. Same-Side (Direct) Network Effects Facebook, WeChat, etc.
  • 7. Network effects can transform competitive dynamics X = Highly competitive market Technologies that generate network effects Amazon Echo with > 50% share X =
  • 8. Network effects can be limited
  • 9. 2. Vulnerability to Multihoming App developers/ Service providers Consumers Platform A Platform B
  • 10. “Seesaw Effect” Low multihoming on one side leads to high multihoming on the other side.
  • 11. A platform could reduce multihoming on both sides to defend market position Consumers: Prime Third-Party Sellers: Fulfillment Centers
  • 12. 3. Degree of Network Clustering Uber Airbnb
  • 13. 3. Degree of Network Clustering Uber Airbnb Groupon UberEats Instacart Booking Expedia
  • 14. 4. Risk of Disintermediation Consumers Service Providers Platform
  • 15. 5. Opportunities for Network Bridging • Build and connect multiple networks to one another and exploit synergies. • The installed bases and data on their interactions are valuable in multiple scenarios and markets.
  • 16.
  • 17. Understand 1) the impact of network properties on market competitiveness and platform performance and 2) the impact of platform strategy on network properties Network Effects Multihoming Network Clustering Disintermediation Network Bridging Market Competitiveness & Platform Performance Platform Strategy
  • 18. Feng Zhu and Marco Iansiti, “Why Some Platforms Thrive and Others Don’t.” January-February 2019. Harvard Business Review 97(1): 118–125.
  • 19. Academic Publications and Business Cases • Feng Zhu, Xinxin Li, Ehsan Valavi, and Marco Iansiti, “Network Interconnectivity and Entry into Platform Markets.” 2021. Information Systems Research 32(3): 1009–1024. • Hui Li and Feng Zhu, “Information Transparency, Multihoming, and Platform Competition: A Natural Experiment in the Daily Deals Market.” 2021. Management Science 67(7): 4384–4407. • K. Francis Park, Robert Seamans, and Feng Zhu, “Homing and Platform Responses to Entry: Historical Evidence from the U.S. Newspaper Industry.” 2021. Strategic Management Journal 42(4): 684–709. • Grace Gu and Feng Zhu, “Trust and Disintermediation: Evidence from an Online Freelance Marketplace.” 2021. Management Science 67(2): 794–807. • Feng Zhu and Marco Iansiti, “Entry into Platform-Based Markets.” 2012. Strategic Management Journal 33(1): 88–106. • Michael Zhang and Feng Zhu, “Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia.” 2011. American Economic Review 101(4): 1601–1615. • Chiara Farronato, Michael W. Toffel, and Feng Zhu. “Digital Platforms: An Introduction.” Harvard Business School Technical Note 621-016 (2020). • Krishna G. Palepu, Feng Zhu, Susie L. Ma, and Kerry Herman. “Ant Group (A).” Harvard Business School Case 122-003 (2021). • Feng Zhu, Weiru Chen, and Shirley Sun, “ZBJ: Building a Global Outsourcing Platform for Knowledge Workers (A).” Harvard Business School Case 618-044 (2018) (Revised 2019). • Feng Zhu, Krishna G. Palepu, Bonnie Yining Cao, and Dawn H. Lau, “Pinduoduo.” Harvard Business School Case 620-040 (2019). • Feng Zhu and Angela Acocella, “Fasten: Challenging Uber and Lyft with a New Business Model.” Harvard Business School Case 616-062 (2016) (Revised 2018, 2020).