Tuesday, April 8, 2025

Outcomes, Not Intent, Will Drive Antitrust Against Meta, Alphabet

As U.S. regulators examine potential antitrust actions against Alphabet (Google) and Meta (Facebook) under the Clayton and Sherman Acts, they focus on several key behaviors and market outcomes that are believed to hinder competition. 


The question of intent or actions to reduce competition has been raised in that regard and the notion strikes me as quite complicated, given the obvious fact that digital goods markets (content, software, hardware, computing services) in particular often have a “winner take all” character. 


In other words, the result of robust competition is market concentration. That also seems to be the case for capital-intensive industries of most types as well. But “intent” is alleged to be at work.


Did Meta, for example, “buy” other promising firms to acquire engineering talent? Most of us would say that is a common practice in digital industries. Did Meta acquire some firms to build a position in related or adjacent industries? One might argue that also is true, but not illegal.


And the “winner take all” pattern we see in many digital industries or industry segments might likewise not be viewed as an outcome driven mostly by “intent” to prevent competition but to remain competitive in markets where innovation is constant. 


In U.S. antitrust law, the role of "intent" depends on the specific legal framework being applied, primarily under the Sherman Act (Sections 1 and 2) or the Clayton Act, some undoubtedly would note. 


Under Section 1 of the Sherman Act, which prohibits agreements "in restraint of trade" (cartels, price-fixing), intent is not a central element for proving a violation in cases of "per se" illegal conduct. If companies explicitly collude to fix prices or divide markets, the agreement itself and its effects on competition are what matter, irrespective of “intent.”


However, for "rule of reason" cases (where the conduct’s competitive effects are weighed), intent can play a supporting role. Evidence that firms aimed to suppress competition might bolster a case, but it’s not strictly required—empirical evidence of harm to consumers or market structure (e.g., higher prices, reduced output) is the core focus.


That noted, in “restraint of trade” cases, “intent” might strengthen a case for antitrust action. 


Under Section 2 of the Sherman Act, which addresses monopolization or attempts to monopolize, intent becomes more relevant. To prove monopolization, two elements are needed: (1) possession of monopoly power in a relevant market (an empirical question about market share, barriers to entry), and (2) "willful acquisition or maintenance" of that power through exclusionary conduct (not just superior efficiency). 


So “intent to exclude competitors” by buying them out can be part of the analysis, but it’s not sufficient on its own to prove antitrust violations. The issue remains the reality of market share, not “why did you do it” (intent) in a strict sense. 


The Clayton Act (Section 7 on mergers) is arguably even more empirical. Section 7 prohibits acquisitions where "the effect may be substantially to lessen competition or tend to create a monopoly." 


Intent to reduce competition isn’t strictly necessary. Regulators assess market concentration (Herfindahl-Hirschman Index) and competitive outcomes, irrespective of “intent.”


If a merger in a digital market (say, a dominant software firm buying a rival) risks entrenching market power, it can be challenged regardless of whether the firm explicitly aimed to squash competition or just wanted growth.


In cases like United States v. Microsoft (2001), the antitrust violation stemmed from specific exclusionary acts (tying Internet Explorer to Windows, restricting OEMs), not just its market dominance or intent to dominate.


In digital markets, where "winner-takes-most" dynamics are common, structural outcomes might always tend towards concentration. Are efforts to create customer  “stickiness” anticompetitive? Are ecosystems? Are bundles of value necessarily anticompetitive? 


And perhaps those will not prove decisive issues. Regulators will look for behavior: actions that harmed potential competitors. 


Under the Sherman Act (Section 2 dealing with monopolization), regulators will analyze whether the firms companies have:

  • Obtained or maintained monopoly power through anticompetitive conduct

  • Used exclusive dealing arrangements to foreclose competitors

  • Leveraged dominance in one market to gain advantage in adjacent markets


Under Section 1 (Restraint of Trade), regulators will be looking at actions that:

  • Restrict competition between platforms and third parties

  • Include potentially anticompetitive terms in advertising or services contracts


Under the Clayton Act, dealing with the anticompetitive effect of mergers and acquisitions, regulators will look at:

  • Acquisitions of potential competitors (Instagram, WhatsApp, YouTube, Waze)

  • Whether these deals substantially lessened competition or created monopolies

  • "Killer acquisitions" of nascent competitors


Also, under the Clayton Act’s Section 3 relating to “exclusive dealing,” regulators will look at:

  • Default placement agreements (Google as default search engine)

  • Distribution arrangements that exclude rivals


For Alphabet, that likely means looking for:

  • Self-preferencing in search results and advertising markets

  • Tying of Google services to Android

  • Control of digital advertising technology stack

  • Restrictive agreements with device manufacturers


In the case of  Meta, regulators will examine:

  • Network effects and data advantages creating barriers to entry

  • Acquisition strategy eliminating potential competitors

  • Interoperability restrictions

  • Data collection and privacy practices giving competitive advantages


“Intent” might not prove decisive, as the regulator focus might turn on empirical market outcomes almost exclusively. 


Monday, April 7, 2025

Most People Probably Pay Less for Home Broadband Than We Think

It always is difficult to ascertain what “most” consumers actually are paying for home broadband service, partly because people choose a range of plans (faster speeds cost more); partly because many buy service only in a bundle, so there is not actual discrete and identifiable cost. 


In the U.S.  market that is a pronounced issue, as an estimated 70 percent of home broadband services are purchased as part of a bundle. So most of the market arguably buys home broadband in a way that obscures the actual cost. Only about 30 percent of buyers choose a service with a clear recurring price. 


Platform

Typical Speeds

Data Allowance

Monthly Price Range

Common Characteristics

Satellite

~25–30 Mbps download

~3–5 Mbps upload

10–20 GB/month (with some unlimited options at higher prices)

~$75–$85

Mainly chosen in rural or remote areas; higher latency and data caps are common; plans often come with extra fees for overage.

Cable TV

~100 Mbps (often scalable to 200+ Mbps in some markets)

Unlimited data (with occasional fair-use policies)

~$55–$65

The most popular option in urban/suburban areas; offers a good balance of speed and cost; bundle options with TV/phone are common.

Telco (Fiber/DSL)

~100–200 Mbps (fiber often delivers symmetrical speeds)

Typically unlimited or very high data limits

~$60–$70

Fiber plans (e.g., Verizon Fios, AT&T Fiber) are prized for reliability and speed; DSL remains common where fiber isn’t available.

Independent ISP

~50–150 Mbps

Varies, but often unlimited or high caps

~$50–$60

Smaller regional providers often offer competitive pricing and personalized service; plan details can be more tailored.

Fixed Wireless

~25–50 Mbps

Often moderate data caps (e.g., 250 GB/month) or unlimited with speed throttling

~$50–$60

Frequently used in rural or underserved areas; installation can be simpler and faster; speeds may vary with weather and line-of-sight conditions.

Mobile Broadband

Varies (commonly 10–30 Mbps when used as a home hotspot)

Often included as part of an unlimited smartphone plan or separate data allotment

~$55–$65

Purchased as a hotspot or integrated into a mobile plan; flexibility for on-the-go usage, but performance depends on network congestion and coverage.


And estimates vary dramatically when bundled service costs are considered. Where the estimated cost of a cable TV stand-alone service might be between $55 and $65 a month for 100 Mbps service, that same service might “cost” only about $30 to $40 a month when purchased as part of a bundle. 


Platform

Estimated Broadband Cost Portion

Notes

Cable TV

~$30–$40/month

Cable bundles often offer broadband at a discounted rate compared to standalone options, as the service is cross-subsidized by TV/phone components.

Telco (Fiber/DSL)

~$35–$45/month

Fiber bundles tend to emphasize higher speeds and reliability; the broadband portion may carry a slight premium compared to cable but still remains competitively priced in a bundle.

Fixed Wireless

~$30–$40/month

Often offered in rural or underserved regions, these bundles provide broadband at rates similar to cable bundles, though speed and data policies can vary.

Mobile Broadband

~$30–$40/month

When integrated into smartphone or home hotspot bundles, the effective broadband cost is often reduced as part of multi-line or data-centric deals.


Sunday, April 6, 2025

Fast Food Restaurants Might be Among the Few Firms Able to Measure AI Revenue Upside

Move over, “digital transformation.” Now we have "AI transformation," which  refers to the integration of artificial intelligence into business processes to improve efficiency, decision-making, and innovation.


As a practical matter, AI transformation is likely to be hard to measure and might not happen “rapidly,” as whole business processes might have to be redesigned. On the other hand, it might be easier to illustrate how “AI transformation” can affect some processes in a measurable way. 


McDonald's wanted to improve its drive-thru experience, boost sales through personalized recommendations, and optimize restaurant operations.


CompanyAI ImplementationResults/ImpactYear
McDonald'sDynamic Yield acquisition1-2% increase in average check size in test locations2019-2020
StarbucksDeep Brew3% increase in same-store sales2020-2021
KFCFace-scanning kiosks (China) recognize cusotmers, suggest ordersUp to 27% increased average transaction average transaction size for repeat customers2019
Domino'sDOM AI ordering assistant20% higher conversion rates with personalization2021
ChipotleChippy AI system15% increase in add-on items2022
Sonic Drive-InAI-powered digital menu5.9% increase in promoted-item sales2021
Wendy'sAI-powered drive through6% increase in average check size2022-2023
Burger KingGuest Track AI1.5-3% increase in average check size2021
Taco BellDigital kiosks with AI20% higher average order value2022
Dunkin' Mobile appuses AI7.4% increase in app order value2022-2023
Pizza HutHot Spots3.5% increase in add-on items2021
Panera BreadAI-powered loyalty program8% increase in frequency2022
WingstopDigital platform with AI13.5% higher average transaction2023
Shake ShackAI-powered kiosks18% higher average check2022

McDonald's in 2019 began using Dynamic Yield, an AI-powered personalization platform owned by Mastercard. McDonalds then used it to change digital drive-through menus based on weather, time of day, popular items, and current restaurant traffic.


On a hot day, the menu might prioritize cold drinks; during the morning rush, breakfast combos might be featured. 


In the kitchen, McDonald’s added AI models and sensors (to monitor equipment health)  predict demand for food items, optimize kitchen prep times, reduce waste and limit equipment downtime


The firm also adopted AI-driven forecasting, to  help improve inventory management, reduce food shortages and overstocking.


Other fast food restaurants are doing likewise. Still, “transformation” is more a goal and a process, rather than an easily-quantifiable outcome. 


Saturday, April 5, 2025

Embodied AI (Robots) Likely Key to Some Onshoring of U.S. Manufacturing

It is hard to avoid the conclusion that artificial intelligence, in the the form of embodied robots, will be an important part of the business case if manufacturing facilities return to the United States as part of restoring policies and firm responses, jobs will indeed be created, but not at the scale of the pre-offshoring era, it is reasonable to predict. 

Automation, particularly robots using artificial intelligence, likely will handle much of the repetitive, labor-intensive work. 


Study/Source

Estimated Job Creation

Role of Automation

Key Insights

Forbes (2025)

Hyundai's $20 billion investment expected to create 1,500 jobs in Louisiana

Automation is a major factor in reducing traditional manufacturing jobs.

Manufacturing production is high, but job creation is modest due to automation replacing manual labor.

Davron (2024)

Reshoring creates advanced manufacturing jobs requiring higher skills and wages

Advanced manufacturing relies heavily on technology, reducing reliance on manual labor.

Reshoring fosters innovation but requires a skilled workforce trained for automated processes.

Business Insider (2024)

Reshoring could add $10 trillion to the economy over the next decade

High-tech sectors benefit most, integrating automation for efficiency.

Automation is central to reshoring efforts, enhancing productivity but limiting traditional job growth.

Christian Science Monitor (2025)

AI-driven factories may add slightly more jobs than they destroy

Factories integrate AI and robotics to increase efficiency and resilience.

Human roles shift toward managing robots and AI rather than performing manual tasks.

Shoplogix (2023)

Robotics create new roles like technicians and engineers but displace manual labor jobs

Robots perform repetitive tasks faster and more accurately than humans.

Upskilling is essential as traditional roles are replaced by tech-focused positions.

LinkedIn (2025)

Manufacturing output increased 15% since 2020, employment rose only 3%

Automation reduces factory jobs while creating opportunities in high-tech roles.

Reshoring with automation boosts productivity but limits job creation in traditional sectors.



Where an existing garment factory presently operating in Southeast Asia employs X workers, a repatriated operation in the United States might require perhaps 10 percent to 20 percent of those workers. Recall that the reason such facilities moved from U.S. domestic locations to off shore is precisely lower labor rates. 


Assuming higher U.S. wage rates, the only way the economics would work is if far fewer workers were required. 


Study/Analysis

Source

Key Findings on Job Increases

Automation Consideration

Date

Reshoring Initiative Report

Reshoring Initiative

Estimated 1.6 million jobs reshored from 2010-2022, with potential for more if trends continue.

Notes automation reduces job counts; 2022 data shows 364,000 jobs added, but robotics limits scale vs. past.

2022

Oxford Economics:  How Robots Change the World

Oxford Economics

Robots could displace 20 million global manufacturing jobs by 2030, but reshoring may add some back.

Predicts automation will cap U.S. job gains; historical 1.6 jobs lost per robot suggests fewer net gains.

2019

MIT: Robots and Jobs

Acemoglu and Restrepo (NBER)

Between 1990-2007, 1 robot per 1,000 workers reduced employment by 6 workers locally.

Automation in reshored facilities could mean 50-70% fewer jobs than offshored totals due to robot density.

2017

Ball State University:  Manufacturing Study

Center for Business and Economic Research

U.S. lost 5.8 million manufacturing jobs (1980-2016), mostly to productivity automation, not trade.

Suggests reshoring creates high-skill jobs (e.g., technicians), but far fewer than original low-skill positions.

2017

McKinsey Global Institute: Future of Work

McKinsey

Automation could displace 16-20 million U.S. jobs by 2030, but reshoring may offset some losses.

Highlights that returning facilities will lean on robots/AI, creating 10-20% of original job numbers.

2017

ITIF: Robotics and Production

Information Technology and Innovation Foundation

Robotics boosts productivity, potentially adding manufacturing jobs in developed nations.

Job growth tied to engineers/tech roles; traditional labor replaced by robots, reducing total job count.

2019

Brookings: Automation and Jobs

Brookings Institution

Automation offsets job losses from trade, but reshoring impact limited by tech adoption.

Estimates 100-150 jobs per large reshored factory, vs. 500-1,000 historically, due to automated processes.

2015, 2022


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