Senator Elizabeth Warren proposes breaking up key tech titans such as Facebook, Apple, Microsoft, Google, and Amazon (FAMGA).

Becky Berkman

2019-03-21 12:33:00 Thu ET

Senator Elizabeth Warren proposes breaking up key tech titans such as Facebook, Apple, Microsoft, Google, and Amazon (FAMGA). These tech titans have become too dominant and thus tend to leverage their market power to squelch competition to the detriment of consumers. In addition to bulldozing market competition, these tech titans use private user information for profits, tilt the playing field against small-to-medium enterprises, and stifle R&D innovation as their M&A deals encapsulate niche competitors.

For better scale economies and network effects, several strategic M&A examples include the recent acquisitions of Instagram, Whatsapp, and Oculus (by Facebook), DoubleClick, Waze, and Nest (by Google), Whole Foods and Zappos (by Amazon), and Shazam, Texture, InVisage, Regaind, and Lattice Data (by Apple).

Warren further proposes to bar these prime platform orchestrators (FAMGA) from sharing private user data with third parties. Under the Warren proposal, small tech startups would have a fair shot to sell their products on Amazon without the fear of facing fierce competition from Amazon and its affiliates; Google could not smother competitors by demoting their products and services on the Internet search engine; and Facebook would face real pressure from Instagram and WhatsApp to improve the user experience with better privacy protection.

 


If any of our AYA Analytica financial health memos (FHM), blog posts, ebooks, newsletters, and notifications etc, or any other form of online content curation, involves potential copyright concerns, please feel free to contact us at service@ayafintech.network so that we can remove relevant content in response to any such request within a reasonable time frame.

Blog+More

Donald Trump defies the odds to become the new U.S. president.

John Fourier

2016-11-08 00:00:00 Tuesday ET

Donald Trump defies the odds to become the new U.S. president.

Donald Trump defies the odds to become the new U.S. president. He wants to make America great again. He seeks to repeal Obamacare. He has zero tole

+See More

The U.S. Treasury yield curve inverts for the first time since the Global Financial Crisis.

Apple Boston

2019-04-09 11:29:00 Tuesday ET

The U.S. Treasury yield curve inverts for the first time since the Global Financial Crisis.

The U.S. Treasury yield curve inverts for the first time since the Global Financial Crisis. The key term spread between the 10-year and 3-month U.S. Treasur

+See More

The Economist suggests that the world has learned few lessons of the global financial crisis from 2008 to 2009.

Becky Berkman

2018-09-07 07:33:00 Friday ET

The Economist suggests that the world has learned few lessons of the global financial crisis from 2008 to 2009.

The Economist re-evaluates the realistic scenario that the world has learned few lessons of the global financial crisis from 2008 to 2009 over the past deca

+See More

Our proprietary alpha investment model outperforms most stock market indices from 2017 to 2021.

Apple Boston

2021-02-02 14:24:00 Tuesday ET

Our proprietary alpha investment model outperforms most stock market indices from 2017 to 2021.

Our proprietary alpha investment model outperforms the major stock market benchmarks such as S&P 500, MSCI, Dow Jones, and Nasdaq. We implement

+See More

Peter Schuck analyzes U.S. government failures and structural problems in light of both institutions and incentives.

Dan Rochefort

2023-04-28 16:38:00 Friday ET

Peter Schuck analyzes U.S. government failures and structural problems in light of both institutions and incentives.

Peter Schuck analyzes U.S. government failures and structural problems in light of both institutions and incentives. Peter Schuck (2015)   Why

+See More

Most artificial intelligence applications cannot figure out the intricate nuances of natural language and facial recognition.

Fiona Sydney

2019-09-01 10:31:00 Sunday ET

Most artificial intelligence applications cannot figure out the intricate nuances of natural language and facial recognition.

Most artificial intelligence applications cannot figure out the intricate nuances of natural language and facial recognition. These intricate nuances repres

+See More