Hmmm, Amazon #1; Facebook #2; Google #3…
The Evil List of Technology Companies
Hmmm, Amazon #1; Facebook #2; Google #3…
The Evil List of Technology Companies
The Information Age is different in many ways. This is why digital formats have roiled physical formats across all the creative industries. We need to think outside the box.
Interesting article from an academic expert (my annotations in red):
a digital platform is either large or dead.
One of the biggest concerns about today’s tech giants is their market power. At least outside China, Google, Facebook, and Amazon dominate online search, social media, and online retail, respectively. And yet economists have largely failed to address these concerns in a coherent way. To help governments and regulators as they struggle to address this market concentration, we must make economics itself more relevant to the digital age.
Digital markets often become highly concentrated, with one dominant firm, because larger players enjoy significant returns to scale. For example, digital platforms incur large upfront development costs but benefit from low marginal costs once the software is written. They gain from network effects, whereby the more users a platform has, the more all users benefit. And data generation plays a self-reinforcing role: more data improves the service, which brings in more users, which generates more data. To put it bluntly, a digital platform is either large or dead.
As several recent reports (including one to which I contributed) have pointed out, the digital economy poses a problem for competition policy. Competition is vital for boosting productivity and long-term growth because it drives out inefficient producers and stimulates innovation. Yet how can this happen when there are such dominant players?
Today’s digital behemoths provide services that people want: one recent study estimated that consumers value online search alone at a level equivalent to about half of US median income. Economists, therefore, need to update their toolkit. Rather than assessing likely short-term trends in specific digital markets, they need to be able to estimate the potential long-term costs implied by the inability of a new rival with better technology or service to unseat the incumbent platform.
This is no easy task because there is no standard methodology for estimating uncertain, non-linear futures. Economists even disagree on how to measure static consumer valuations of free digital goods such as online search and social media. And although the idea that competition operates dynamically through firms entering and exiting the market dates back at least to Joseph Schumpeter, the standard approach is still to look at competition among similar companies producing similar goods at a point in time.
The characteristics of digital technology pose a fundamental challenge to the entire discipline. As I pointed out more than 20 years ago, the digital economy is “weightless.” Moreover, many digital goods are non-rival “public goods”: you can use software code without stopping others from doing so, whereas only one person can wear the same pair of shoes. And they require a substantial degree of trust to have any value: we need to experience them to know whether they work, and social influence is often crucial to their diffusion.
Yet standard economics generally assumes none of these things. Economists will bridle at this statement, rightly pointing to models that accommodate some features of the digital economy. But economists’ benchmark mental world – particularly their instinctive framework for thinking about public policy questions – is one where competition is static, preferences are fixed and individual, rival goods are the norm, and so on.
Starting from there leads inexorably to presuming the “free market” paradigm. As any applied economist knows, this paradigm is named for a mythical entity. But this knowledge somehow does not give rise to an alternative presumption, say, that governments should supply certain products.
This instinct may be changing. One straw in the wind is the call by Jim O’Neill, a former Goldman Sachs economist who now heads the Royal Institute of International Affairs (Chatham House), for public research and production of new antibiotics. Having led a review of the spread of anti-microbial resistance – which will kill millions of people if new drugs are not discovered – O’Neill is dismayed by the lack of progress made by private pharmaceutical companies.
Drug discovery is an information industry, and information is a non-rival public good which the private sector, not surprisingly, is under-supplying. [Yes – this is what intellectual property rights/copyrights/patents is all about. The problem is attributing the value created by the sharing of information. We may be able to solve that with blockchain ledgers.] That conclusion is not remotely outlandish in terms of economic analysis. And yet the idea of nationalizing part of the pharmaceutical industry is outlandish from the perspective of the prevailing economic-policy paradigm.
Or consider the issue of data, which has lately greatly exercised policymakers. Should data collection by digital firms be further regulated? Should individuals be paid for providing personal data? [Yes, they should. Personal data is as proprietary as personal labor and personal ideas. Making sure users get paid for their data changes the business models of these natural monopolies.] And if a sensor in smart-city environment records that I walk past it, is that my data, too? The standard economic framework of individual choices made independently of one another, with no externalities, and monetary exchange for the transfer of private property, offers no help in answering these questions. [Yes, because we don’t yet assign value to shared information. We rely on the property rights of tangible assets.]
Economic researchers are not blameless when it comes to inadequate policy decisions. We teach economics to people who go out into the world of policy and business, and our research shapes the broader intellectual climate. The onus now is on academics to establish a benchmark approach to the digital economy and to create a set of applied methods and tools that legislators, competition authorities, and other regulators can use.
Mainstream economics has largely failed to keep up with the rapid pace of digital transformation, and it is struggling to find practical ways to address the growing power of dominant tech companies. If the discipline wants to remain relevant, then it must rethink some of its basic assumptions.
The following article caught my attention. It seems to suggest that millennials and Gen Zers have just become more willing than earlier generations to seek out therapy for mental health issues. But 50-75% quit their jobs due to mental health? That seems more like an epidemic than social enlightenment and the fact that it strikes deepest among certain age cohorts is a red flag. I would suggest that other research studies into happiness, fulfillment, and health have come up with different factors. (My book The Ultimate Killer App: How Technology Succeeds presents most of this research with citation references.)
First, most normal (i.e, non-medical) psychological depressive states can be traced to a disconnect between expectations and reality. We all experience this as disappointment, but an over-emphasis on relative status with our peers can be a strong catalyst for psychological distress. Certainly social media has made this relative status more salient in our daily lives: “Gee, our friends on Facebook seem to be living much more exciting and rewarding lives!!!” We’ve even coined this distress as FOMO (fear of missing out). In pre-mass media days few people knew they were missing out on the Vanderbilt or Rockefeller lifestyle; these were more like Hollywood fantasies. But social media has brought such status comparisons into our daily lives with real people we know. How can a young worker flipping burgers as a career job stepping stone last more than a month of this humiliation when his friends are playing ping-pong at Google? Apparently not many.
An older generation would reply that work is not supposed to be fun, that’s why it’s called work. But I think the future offers us better solutions if we are cognizant enough of the problem to seek them out. First, healthy humans at some point realize that relative status matters not a whit; nobody really cares about how great your life is, except you and perhaps your mom.
The second point that psychological research reveals is that money and wealth offer a very poor representation of true status and self-actualization. Instead we should be looking to our creative and social instincts. This is the major thesis of The Ultimate Killer App: what we truly desire to be happy and fulfilled is to explore our creativity and share it with like-minded others to establish robust social connections. Having a child and a family helps satisfy these most primal needs. It really comes down to Maslow’s Hierarchy of Needs and this is the foundational idea of tuka, a creativity sharing social network platform.
by Megan Henney
Young people are spearheading mental health awareness at the workplace.
About half of millennials and 75 percent of Gen Zers have quit their jobs for mental health reasons, according to a new study conducted by Mind Shares Partners, SAP and Quatrics. It was published in Harvard Business Review.
That’s compared to just 20 percent of respondents overall who said they’ve voluntarily left a job in order to prioritize their mental health — emblematic of a “shift in generational awareness,” the authors of the report, Kelly Greenwood, Vivek Bapat and Mike Maughan, wrote. For baby boomers, the number was the lowest, with less than 10 percent quitting a job for mental-health purposes.
It should come as no surprise that younger generations are paving the way for the de-stigmatization of mental health. A Wall Street Journal article published in March labeled millennials the “therapy generation,” as todays 20- and 30-somethings are more likely to turn to therapy, and with fewer reservations, than young people in previous eras did.
A 2017 report from the Center for Collegiate Mental Health at Penn State University found that, based on data from 147 colleges and universities, the number of students seeking mental-health help increased at five times the rate of new students starting college from 2011 to 2016. And a Blue Cross Blue Shield study published in 2018 revealed that major depression diagnoses surged by 44 percent among millennials from 2013 to 2016.
Increasingly, employees (about 86 percent) want their company to prioritize mental health. Despite that — and the fact that mental health conditions result in a $16.8 billion loss in employee productivity — the report found that companies are still not doing enough to break down the stigma, resulting in a lack of identification in workers who may have a mental health condition. Up to 80 percent of individuals will manage a mental health condition at one point in their lifetime, according to the study.
Of course, sometimes employees are unaware of the different resources offered at their organizations, or are afraid of retribution if they elect to use them. In the study, millennials, ages 23 to 38, were 63 percent more likely than baby boomers, 55 to 73, to know the proper procedure for seeking mental health support from the company.
The study was based on responses collected from 1,500 U.S. adults.
Below I include a recent article from Barron’s Magazine, presenting the financial challenges to Spotify, the dominant music streaming service. Here’s why I believe it’s dead:
Spotify [is] a “pure play on a loss-leader category.”
Streaming music has been priced as a loss leader, in other words the costs of streaming music exceed what platforms receive from subscribers in revenue. This is not atypical for networking platforms as the platforms hope to monetize the data these networks create through their users. Of course, a network does not really become valuable until it is of dominant size and able to maintain continued user engagement. Facebook is the one we are most familiar with. And Facebook did not become profitable until it had been in operation for 6 years and experienced phenomenal user growth. Also, FB has an ad revenue model (more on this later).
The problem with Spotify is that its major product line loses money, a lot of money. Streaming unlimited music costs a lot more than $10/month per subscriber. But raising the price merely loses subscribers, and customer acquisition costs (CAC) on the margin often increase over time. So, the desperate strategy is to find a way to generate revenue from the data sharing network.
But Spotify faces some serious competition: Apple, Amazon, and Google. All three of these tech titans can afford to lose money on streaming for a long time, much longer than Spotify can stay solvent or keep the support of its investors. Spotify is a dead man walking. Its subscriber base will be auctioned off before it depreciates to zero. Or not.
For example, how does Spotify compete with this?
I expect the revenue squeeze will also hit Facebook’s main advertising model. Digital advertising is dominated by Google and Facebook. Google monetizes search routines it gathers every time you invoke its search algorithms. Facebook monetizes social sharing and likes. Each then sell access to this data to third-party advertisers. Now, search is a more robust indicator of interest than likes, so Google’s ad reach and keyword auctions offer greater value than FB “likes.” FB tries to increase its value through social network dynamics, but there is so much noise there that there’s a real question how much that is really worth in terms of advertising conversions.
But both platforms need to look at the big shadow hovering just over their shoulders and bearing down on their ad models. Amazon knows what people buy on its platform, which reveals a far more robust indicator for what people will buy again. Access to Amazon’s data will be worth that much more than FB and even Google. I expect FB has the weakest attention model and thus Amazon and Google will continue to eat into its ad revenues. I’m sure FB is working overtime trying to figure out how to pivot and leverage its massive user base. Libra Coin is a clear indicator of that. FB is hoping to use crypto tokenization to monetize peer-to-peer finance and banking. Unfortunately it faces some serious regulatory opponents in the central banks and the commercial payments industry. But I suppose FB has much cash to burn trying to find its next lily pad.
The real problem with the scramble for data real estate is that there are only so many hours in a day. On top of that, users and consumers are becoming cognizant of the value of their personal data and will be less inclined to give it away for free. This blows up most of the “mobile app” bubbles vying for attention in the digital economy. The future, if one is to believe in technological progress, is a far more decentralized digital universe where users reap much more value from the data they create and share, and successful platforms will need to deliver much more value than a free app for their users.
The question for us all is who will eat whom on the way to this future? (If we believe Elizabeth Warren, she will be eating them all. Politics is always a wild card.)
By Avi Salzman
Barron’s October 5, 2019
A miserable few months have made Spotify’s stock as dull as elevator music. Now, some analysts think the stock is beaten down enough that a rally is coming, and Wall Street is ready to groove on the remix.
Spotify Technology (SPOT) has fallen 17% since Barron’s wrote a skeptical cover article on the company (“Spotify Stock Is Risky Because the Music Industry Isn’t Changing Fast Enough,” April 19). Short interest on the stock, which was below 3% for much of the year, is now above 5%.
Yet two formerly bearish analysts have recently shifted to a more neutral stance, on the theory that the bad news is already in the stock’s price.
Spotify is the global leader in streaming music, and it passed 100 million paying users this year. Still, doubts have grown on Wall Street about the company’s ability to sustain subscriber growth.
In August, Spotify started giving new premium users three free months of service, up from one month, which “has supported fears of negative subscriber trends,” writes Credit Suisse analyst Brian Russo, one of the analysts who has become incrementally more positive about the shares. The company has launched other offers, too, including six free months of Spotify for people who buy an Xbox Game Pass.
Investors will have to wait until Oct. 28, when Spotify reports third-quarter earnings, to find out whether the generous offers are cutting into its margins. For now, the stock still seems stretched. Its market cap is $21 billion, more than the $19.1 billion that the music industry took in worldwide in 2018—and most of that money goes to labels and artists.
Spotify, meanwhile, is expected to lose $1.92 a share this year; in April, the loss had been projected to be $1.48. Kevin Rippey, an Evercore ISI analyst, calls Spotify a “pure play on a loss-leader category.”
Spotify is looking at new revenue opportunities. The company has branched out into podcasting, with plans to spend as much as $500 million this year on acquisitions in the space. But there is no obvious payoff from those purchases; the podcast ad market in the U.S. is still below $1 billion. Spotify didn’t respond to requests to hear the company’s case from top executives.
Spotify leads rivals like Amazon.com (AMZN) and Apple (AAPL) among young customers, but it will probably need to find older fans in developed markets to hit Wall Street targets, Russo argues. That could be tough. Amazon’s smart speakers have helped it sell music packages to older customers and will make it difficult for Spotify to expand in that market, Russo says.
And Spotify’s rivals are increasing their offerings. Google-owned YouTube Music is promoting personalized playlists to help users find new music, an area that has been one of Spotify’s biggest strengths. Amazon has released a high-quality music service that costs $12.99 for Prime users—a small premium to Spotify’s $9.99—offering listeners CD-quality sound, or better. Unlike Spotify, those companies don’t depend on music to make money.
Because of the competition, Russo expects Spotify to grow disproportionately in emerging markets, “where disposable income is lower and monetization, both in terms of subscription and advertising, is more challenging.”
Spotify stock may well rise when the company reports third-quarter numbers, given the bearish setup in the market. But for it to become an attractive longer-term investment, it needs a clearer path to profitability.
They don’t. They just don’t hear it enough in the right context!
This is the problem tuka is trying to solve: to recreate that music sharing network you had when you were in high school and college!
Why do old people hate new music?
by Frank T. McAndrew
When I was a teenager, my dad wasn’t terribly interested in the music I liked. To him, it just sounded like “a lot of noise,” while he regularly referred to the music he listened to as “beautiful.”
This attitude persisted throughout his life. Even when he was in his 80s, he once turned to me during a TV commercial featuring a 50-year-old Beatles tune and said, “You know, I just don’t like today’s music.”
It turns out that my father isn’t alone.
As I’ve grown older, I’ll often hear people my age say things like “they just don’t make good music like they used to.”
Why does this happen?
Luckily, my background as a psychologist has given me some insights into this puzzle.
We know that musical tastes begin to crystallize as early as age 13 or 14. By the time we’re in our early 20s, these tastes get locked into place pretty firmly.
In fact, studies have found that by the time we turn 33, most of us have stopped listening to new music. Meanwhile, popular songs released when you’re in your early teens are likely to remain quite popular among your age group for the rest of your life.
There could be a biological explanation for this. There’s evidence that the brain’s ability to make subtle distinctions between different chords, rhythms and melodies gets worse with age. So to older people, newer, less familiar songs might all “sound the same.”
But I believe there are some simpler reasons for older people’s aversion to newer music. One of the most researched laws of social psychology is something called the “mere exposure effect.” In a nutshell, it means that the more we’re exposed to something, the more we tend to like it.
This happens with people we know, the advertisements we see and, yes, the songs we listen to.
When you’re in your early teens, you probably spend a fair amount of time listening to music or watching music videos. Your favorite songs and artists become familiar, comforting parts of your routine.
For many people over 30, job and family obligations increase, so there’s less time to spend discovering new music. Instead, many will simply listen to old, familiar favorites from that period of their lives when they had more free time.
Of course, those teen years weren’t necessarily carefree. They’re famously confusing, which is why so many TV shows and movies – from “Glee” to “Love, Simon” to “Eighth Grade” – revolve around the high school turmoil.
Psychology research has shown that the emotions that we experience as teens seem more intense than those that comes later. We also know that intense emotions are associated with stronger memories and preferences. All of this might explain why the songs we listen to during this period become so memorable and beloved.
So there’s nothing wrong with your parents because they don’t like your music. In a way, it’s all part of the natural order of things.
At the same time, I can say from personal experience that I developed a fondness for the music I heard my own children play when they were teenagers. So it’s certainly not impossible to get your parents on board with Billie Eilish and Lil Nas X.
by Matt Stoller
The Guardian, Mon 9 Sep 2019
Google and Facebook are the subject of large antitrust investigations. This is good news for our democracy and a free press
The most important input for an advertiser is knowing who is watching the ad. If you know who is seeing an ad slot, you can charge a lot of money to tailor it for that person’s specific interest. If you don’t know who is seeing an ad slot, you can’t charge very much at all. Google and Facebook know who is looking at ad slots everywhere and what they are interested in, so they can sell anything any marketer needs.
Unfortunately, this is what digital media has delivered so far.
The inherent weaknesses of data-driven analytics and algorithms. Especially when it comes to aesthetic content.