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Showing posts sorted by date for query pipeline. Sort by relevance Show all posts

Saturday, July 6, 2024

Do Home Broadband Speed Rankings Really Matter Much?

Ookla’s May 2024 report on mobile and home broadband shows Singapore and Hong Kong leading the list of countries with the fastest speeds, which is not surprising at all. 


You might not have expected Chile to rank third, the UAE and Iceland in spots four and five. The United States ranks sixth, which is sort of an anomaly. Over the past half century or so, it would not have been uncommon for U.S. metrics to rank anywhere from 12th to 20th on measures of tele-density or internet access bandwidth. 


We might reasonably ask how much importance such speed rankings actually mean. One might argue the rankings generally suggest that small city-states and small countries can produce good broadband infrastructure faster and better than any large country, simply because the physical facilities are smaller in coverage area, with higher density. And network size and population density directly affect the cost of such facilities. 


Hong Kong, Singapore and other such areas will always be able to create high-performance access infrastructure faster than any continent-sized country with low population density. 


Nor, looking only at city-states and small countries, might we see clear correlations between growth and home broadband speeds. Singapore and UAE might be strong performers in that regard. But other small countries might not show the same strong correlations. It might be the case that only rarely, if ever, are home broadband and economic growth rates uncorrelated. 


But the correlations are not consistent. So it is worth speculating about how important such rankings actually are, when it comes to applying the tools and wringing business or economic value out of them. 


To be sure, lots of studies suggest there is a correlation between economic growth (gross domestic product) and home broadband availability and speed, with perhaps greater correlations related to availability than speed. 


Study

Year

Key Findings

Ericsson, Arthur D. Little, and Chalmers University of Technology

2011

Doubling broadband speeds can add 0.3% to GDP growth

World Bank

2009

10% increase in broadband penetration associated with 1.38% increase in GDP growth for developing countries

OECD

2011

Positive but diminishing returns from increased broadband speeds on economic growth

ITU (International Telecommunication Union)

2012

Broadband has a statistically significant impact on GDP growth, but effect varies by region and level of development

Rohman and Bohlin

2012

Doubling broadband speed contributes 0.3% GDP growth in OECD countries


But it might also be worth noting that there are similar correlations between gross domestic product gains and educational attainment; rule of law; capital investment; income and wealth; or infrastructure density and availability. 


And correlation is not causation. 


In fact, “causality” might even be the reverse of what we might think. 


Keep in mind that economists generally economists might generally agree there is a  “causal” relationship between growth and:

  • Capital accumulation (both physical and human)  

  • Innovation and technological progress (research and development; creation of new ideas)

  • Macroeconomic stability helps (Low and stable inflation; sound fiscal policies)

  • Openness to trade

  • Quality Institutions (rule of law and low levels of corruption)

  • Financial markets well developed


So we might consider education an input to future capital; innovation or technology development. We might consider home broadband another form of capital. 


But it's often unclear whether some factors said to cause growth are themselves caused by growth. Does financial development, trade openness and political stability cause growth, or does growth cause financial development, trade and political stability? We cannot really say. 


Consider “good schools,” quality home broadband, medical care or other supposed platforms aiding growth. 


It might plausibly be the case that demand for good schools and fast internet access, for example. Are the product of demand from citizens who already have the resources to pay for such quality broadband, as well as the use cases. 


Likewise, if local schools are funded by property taxes, then “good schools” might be “caused” by affluent citizens who can afford expensive housing, which comes with high property values, leading to high tax revenues to fund schools. 


In fact, one might well argue that often, the prevalence of quality home broadband, transportation infrastructure or any number of other supposed producers of economic growth might instead be a result of pre-existing strong economic growth. 


Rather than robust economic growth being “created” by quality broadband; educational attainment and other drivers, it is equally plausible that pre-existing high growth creates wealth and resources that in turn lead to the other outcomes. 


You might suspect educational attainment, for example, is correlated with stronger economic growth, and studies support that notion. But a flywheel might be at work, where pre-existing high attainment leads to more attainment; high growth reinforcing more high growth. 


Study/Source

Correlation/Finding

Georgia Tech study 

0.75 correlation between years of education and GDP per capita. 1 year increase in education associated with 34.4% increase in GDP per capita.

Hanushek & Peterson analysis 

Raising US student test scores to Canadian levels estimated to add $77 trillion to US economy over 80 years.

International comparison 

Countries with top test scores (e.g. Singapore, Hong Kong) had ~2% higher annual GDP growth compared to average.

OECD countries analysis 

Positive correlation between education expenditure at all levels and GDP, stronger over 5-10 year periods.

Developing countries analysis 

Positive correlation between primary education spending and GDP growth. Negative correlation for secondary/higher education.

General finding 

Education is "intrinsically linked to economic growth", influencing both personal salaries and national GDP.


Likewise, studies of transportation infrastructure also tend to be correlated with gross domestic product, but sometimes only moderately. 


Transportation Mode/Metric

Correlation with GDP

Time Period

Source/Study

Civil aviation (freight)

0.907 (high)

1990-2007

IOP Science study 

Civil aviation (freight)

0.711 (strong)

2008-2017

IOP Science study 

Inland waterway (freight)

0.816 (strong)

1990-2007

IOP Science study 

Inland waterway (freight)

0.789 (strong)

2008-2017

IOP Science study 

Road transport (freight)

0.715 (strong)

1990-2007

IOP Science study 

Road transport (freight)

0.741 (strong)

2008-2017

IOP Science study 

Railway (freight)

0.668 (strong)

1990-2007

IOP Science study 

Railway (freight)

0.558 (moderate)

2008-2017

IOP Science study 

Water transportation (freight)

0.750 (strongest)

1989-2018

E3S Conferences study 

Highway (freight)

0.709 (strong)

1989-2018

E3S Conferences study 

Pipeline (freight)

0.700 (strong)

1989-2018

E3S Conferences study 

Railway (freight)

0.678 (strong)

1989-2018

E3S Conferences study 

Civil aviation (freight)

0.593 (moderate)

1989-2018

E3S Conferences study 


The point is that we cannot be very sure that faster home broadband is the result of growth or the cause of growth. Nor can we know very much about how the “quality” of broadband (speed and latency performance, for example) produces growth or is a reflection of growth. 


Sunday, January 21, 2024

How Might AI Reshape Business and Revenue Models?

If artificial intelligence develops as a general purpose technology (we cannot be sure, yet), it might have horizontal and vertical impact on businesses, reorganizing functions and reshaping core business models, as did the internet. 


As has been the trend for software, the internet had a horizontal impact, reorganizing value chains, functions, products, value creation and revenue models across industries. 


Horizontal Impact

Example

Disintermediation: Distribution functions are compressed or eliminated

Travel agents replaced by online booking platforms.

Friction reduced: knowledge and interaction barriers crumble

Open-source software, crowdfunding platforms. Wikipedia

Rise of new business models and industries: Entirely new ways of creating and delivering value emerge.

E-commerce, social media marketing, cloud computing.

Shift from physical to digital products and services: Tangible goods give way to virtual experiences and intangible offerings.

Streaming services replacing physical media, online education platforms.

Death of distance: Businesses can operate across borders almost as easily as within a single market or country

Global e-commerce, social media, messaging, content services, platforms


The vertical impacts affecting industries have been equally dramatic. Think of the emergence of ride sharing, lodging and other “sharing” or “platform” business models built on the internet’s existence. 


Sharing platforms (peer-to-peer networks) disrupt existing industry models because they are “asset light.” Hotels are capital intensive, as are taxi services. But the use of smartphones and private residences and autos to replicate “lodging” and “local transportation” services recasts the role of capital in any industry or business where a sharing platform is possible. 


The sharing network allows a direct peer-to-peer exchange between buyers and sellers. 


The internet also enabled multimedia communications at scale, thus creating the conditions for on-demand digital media to replace all prior forms of electronic and digital media, once broadband internet access was reasonably well available. So content consumption shifts from physical form such as newspapers, magazines and discs to streaming or web delivery. 


So product formats change. So do value propositions. With the emergence of streaming and web access to music, revenue generation in the music business shifted from “selling prer-ecorded copies of music” to “live performance.” Revenue now mostly is earned by performances, not units of pre-recorded music or streaming content purchases. Value now is created by live performance. 


The internet also allowed for customization and individualized experiences, either of form or timing. Users could access “what they want, when they want it.” That is true for mass-produced content such as movies or TV shows or songs as well as for the custom, personal networks of social network “friends” and “following” topics. 


The internet also enabled firms to operate across far-larger markets, both for physical goods and intangible products as well. So distribution networks could be reshaped to support online fulfillment and logistics networks rather than in-store retailing: Amazon instead of shopping at a local retail location. 


Similarly, marketing efforts could be reshaped to use virtual mechanisms rather than physical, targeted and customized based on user search and social media behavior, rather than demographics or psychographics. 


Platform business models are perhaps the clearest example of how an industry can be reimagined. Throughout history, most businesses have operated on a “pipeline” model, where a given product is created, sold and distributed by the owner of that product.


The internet enabled “platforms” where the value is the exchange that matches buyers with sellers, the exchange itself often owning neither the assets sold nor the customer relationships with buyers. 


The revenue model is a fee for arranging the match of buyer and seller. Once the platform reaches sufficient size, other revenue sources, such as subscriptions or advertising, also become feasible. 


Ecosystems often become more important as well. The whole idea behind a “platform” is that it provides increasing value (for tenants, data center operators and retail customers) as more partners, suppliers and features are enabled on the platform. Consider data centers. 


These days, “software” or “digital services” are purchased directly from, or fulfilled by, a cloud-connected data center. 


These days, much of the value of any data center is the other networks, software suppliers, content and application providers that can be connected within any single data center. Some of the value comes from the ability to more easily (cross connect) or quickly (direct peering) exchange data between partners, such as a video streaming network reaching the backbone and local distribution providers of internet access. 


In other cases, proximity makes it easier for suppliers to bundle each others’ services in a more-transparent and simple way for customers who are buying “computing, storage or apps  as a service” from a data center. 


Convenience is another attraction of the ecosystem, as when a single customer is able to purchase multiple large language model, security or enterprise software services at a single location, or from a single computing as a service supplier. 


The point is that AI could have a similar impact, whether it becomes a GPT or not. AI could change the horizontal functions any business or process requires. AI also could reshape particular industries by changing value propositions. Advertising, content, sales, banking and finance are among the obvious areas where AI could add value in the same way that prior data mining has had. 


Consider the many new industries, roles, capabilities and products enabled by the internet, from e-commerce to cloud computing. In fact, some would argue AI itself is enabled by the internet. 


New Industry

Description

E-commerce: Online retail platforms for buying and selling goods and services

Amazon, Etsy, Shopify, Alibaba

Social media: Platforms for creating and sharing user-generated content and building online communities

Facebook, Instagram, Twitter, TikTok

Streaming services: On-demand access to audio and video content

Netflix, Spotify, Hulu, Disney+

Content creation: Blogging, online publishing, influencer marketing

YouTube, Twitch, Substack, Patreon

Cybersecurity: Services and solutions to protect data and systems from cyber attacks

Crowdstrike, Palo Alto Networks, McAfee

Cloud computing: On-demand access to computing resources like servers, storage, and databases

Amazon Web Services, Microsoft Azure, Google Cloud Platform

Fintech: Financial technology services delivered through digital platforms

PayPal, Square, Robinhood, Chime

Gig economy: Online platforms connecting temporary workers with businesses

Uber, Lyft, Airbnb, Deliveroo

E-learning: Online education and training platforms

Coursera, Udemy, Khan Academy, Edmodo

Online gaming: Multiplayer online games and virtual worlds

World of Warcraft, League of Legends, Fortnite, Roblox

Data analytics: Collecting, analyzing, and interpreting data to gain insights

Google Analytics, Tableau, Power BI, Amazon Redshift

Artificial intelligence: Developing and implementing AI models for various applications

Machine learning, natural language processing, computer vision, robotics

DIY and Licensed GenAI Patterns Will Continue

As always with software, firms are going to opt for a mix of "do it yourself" owned technology and licensed third party offerings....