Competing in the Huge Digital Economies of China and India

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The global digital economy crossed an important milestone recently: the number of internet users in two countries — China, with just over 800 million users, and India, with 500 million users  – surpassed the aggregate number of internet users across 37 OECD countries combined. In both countries, users spend more time on the internet than the worldwide average of 5.9 hours per day. They also have room to grow; China has just under 60% of its population online, while India, with one of the lowest rates of internet penetration in the world, has under 25% of its population online.

While it’s tempting to group China and India together as a block of emerging digital markets, they offer several important distinctions, especially for international entities and countries looking to invest. In our Digital Evolution Index (DEI), we place them in the “digital south” which means the full

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The Tightrope Google Has to Walk in China

HBR Staff

With over 1.3 billion people, the Chinese consumer market is a tempting target for Western technology companies. Of course, it’s also a risky place to do business. The recent news that Google is considering a re-entry into China further highlights a troubling balancing act faced by technology companies looking to do business there. The company last entered China in 2006 with a censored search engine, but pulled the plug on the operation four years later after it discovered that human-rights activists’ Gmail accounts had been hacked. While the economic opportunity in re-entering China could be massive for the firm, there are very real dangers for Google or any internet firm in underestimating the threat posed by Chinese meddling.

Any internet platform company doing business in China has to negotiate a major business and ethical dilemma: The Chinese government enforces overbearing regulations that censor speech in the name

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The Virtual Work Skills You Need — Even If You Never Work Remotely

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Maintaining strong, productive relationships with clients and co-workers can be challenging when you never see the person you’re working with. Yet, it is common to have ongoing work relationships – sometimes lasting years — with people you’ve never met in person.

We often think of “virtual work” as working with someone located outside an office, or in another city or country. This type of work is on the rise: a 2017 Gallup report found 43% of American employees work remotely; in another survey, 48% of respondents reported that a majority of their virtual teamwork involved members from other cultures.

However, virtual work also encompasses how we are turning to technology to conduct business with nearby colleagues, sometimes within the same building or campus. At a large consumer-products firm where we’ve been conducting research, an HR director recounted the changes she witnessed in employees located in two

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How to Use Facebook’s Settings to Have More-Productive Conversations

HBR Staff

The past year has served as a wake-up call for many Facebook users. Between the Cambridge Analytica scandal, Mark Zuckerberg’s congressional testimony and the advent of Europe’s General Data Protection Regulation (GDPR), we have fresh insight into how much Facebook knows about us—knowledge that has inspired many people to re-think what they share on Facebook, how they manage their Facebook settings, or even whether they want to use social media at all.

While Facebook’s algorithm uses our data to show us content and ads that it thinks is more likely to be of interest to us, it can also distort our view of the world by limiting our view to the people and perspectives we find most appealing or otherwise engaging. That algorithm is also the reason that some Facebook threads unfold as civil, respectful (but perhaps insufficiently representative) conversations among like-minded souls, while others turn into all-out

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A Study Shows the Best Times of Day to Post to Social Media

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U.S. companies are expected to spend more than $37 billion dollars on social media promotion annually each year by 2020, representing 24% of the economy’s total digital advertising spend. It’s an astounding number, given that the vast majority of social media managers charged with getting customers to click on posts and through to their websites operate with little strategy beyond what we call “spray and pray,” an approach that litters social media with firm generated content in the hopes that one or more of those posts draw in customers.

There is a better way. Our research on circadian rhythms suggests that content platforms like CNN, ESPN, National Geographic, and others can enhance their profit payoffs by at least 8% simply by posting content following the biological responses of their audience’s sleep-wake cycles and targeting content types to when the audience is most naturally receptive to it.

On

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Why Google Fiber Is High-Speed Internet’s Most Successful Failure

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In 2010, Google rocked the $60 billion broadband industry by announcing plans to deploy fiber-based home internet service, offering connections up to a gigabit per second — 100 times faster than average speeds at the time. Google Fiber, as the effort was named, entered the access market intending to prove the business case for ultra-high-speed internet. After deploying to six metro areas in six years, however, company management announced in late 2016 that it was “pausing” future deployments.

In the Big Bang Disruption model, where innovations take off suddenly when markets are ready for them, Google Fiber could be seen as a failed early market experiment in gigabit internet access. But what if the company’s goal was never to unleash the disrupter itself so much as to encourage incumbent broadband providers to do so, helping Google’s expansion in adjacent markets such as video and emerging markets including

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Why Western Digital Firms Have Failed in China

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Many leading American digital firms, including Google, Amazon, eBay, and Uber, have successfully expanded internationally by introducing their products, services, and platforms in other countries. However, they have all failed in China, the world’s largest digital market.

The widely touted reasons for these failures include censorship by the Chinese government and cultural differences between China and the West. While these factors undoubtedly have played a role, such explanations are overly simplistic. Google, for example, has succeeded in dominating many foreign markets that have radically different political systems and cultures (including Indonesia, Thailand, and Saudi Arabia). And these factors have not stopped Western multinationals from succeeding in China in car manufacturing, fast-moving consumer goods, and even sectors where culture plays a key role, such as beer, coffee shops, fast food, and the film industry. There are deeper reasons behind the systematic failure of Western digital firms in

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The Productivity Booster You Have in Your Pocket, But Probably Don’t Use

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HBR Staff

The world’s 230 million knowledge workers are frazzled. Modern life is an interminable cacophony of emails, notifications, messages, alerts, feeds, data and information. 70% of us look at our phones within 30 minutes of waking up. All this causes stress. With multiple notifications on multiple apps on multiple pages of our devices, where do we start? Who will help us?

Fortunately, almost all of us already have a personal assistant. It’s a piece of software on a device you own: the intelligent assistant (IA). We carry IAs around on our laptops (Microsoft’s Cortana), phones (Google Assistant, Apple’s Siri, Samsung’s Bixby) and smart speakers (Amazon’s Alexa, Baidu’s Little Fish). You probably have more than one. There are an estimated one billion IA-enabled devices in the world today. With smartphone penetration in the UK and US approaching 70%, it’s easy to believe that there will be as many intelligent assistants as

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Why Network Effects Matter Less Than They Used To

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When we teach strategy to MBA students, they want magic bullets, things they can do to make their companies thrive forever. For a long time we emphasized “network effects” as a potential secret sauce for business models. Economists use “network effects” to describe contexts where a good or service offers increasing benefits the more users it has. Network effects can be direct: for example, Slack becomes more useful as other people also use Slack. Network effects can also be indirect, meaning that one set of users benefits as more of another type of users joins a platform. For example, AirBnB would not be useful for travelers if there were no apartment-owners using the platform. Similarly, home-owners would not want to use AirBnB if travelers weren’t using it to find a place to stay.

We have long taught that network effects can provide market power and sustained or even

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The AT&T Ruling Shows That U.S. Regulators Don’t Understand Media’s Present — or Future

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This week’s decision by U.S. District Judge Richard Leon to allow AT&T and Time Warner to complete their merger will bring to a close a deal that has been pending for almost two years.

In his blistering, 172-page decision, Judge Leon did much more than simply reject the government’s claim that combining two companies that do not compete with each other would harm consumers. He also made clear, as a matter of federal law, that the U.S. Justice Department’s view of a static media landscape is dead and buried.

“If there ever were an antitrust case where the parties had a dramatically different assessment of the current state of the relevant market and a fundamentally different vision of its future development,” Judge Leon began his decision, “this is the one.”

The judge was faced from the outset with a stark choice: Was the relevant

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How to Give a Webinar Presentation

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As more and more companies cultivate a global workforce and international client base, it’s increasingly necessary to present remotely. For years, teleconferencing was the best option, but in the past five years internet speeds and web conferencing technologies have become sufficiently robust to support a shift to live video streaming. But presenting in a webinar — when you often don’t have access to visual cues about how the audience is responding — can sometimes feel disconcerting or awkward.

In the course of promoting my books, delivering client trainings, and teaching executive education programs, I’ve conducted several hundred webinars over the past few years. Here are the strategies I’ve found to be most effective in engaging executive audiences.

First, make use of the camera. It’s shocking to me how many professionals still consider it acceptable to host webinars with no video, merely providing voiceover as they click through a series of

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Research: Watching an Expert Do Something Makes You Think You Can Do It Too

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You can find just about any skill you want to learn on the internet. Steve Jobs’s captivating presentation style, Steph Curry’s jumper, Michael Jackson’s moonwalk — all of these are easily accessible. Clearly, instructional videos, how-to guides, and online tutorials have changed the way we learn.

Or have they? Watching expert performances might make you feel that you could perform similar skills. But new evidence suggests that learning by observation may, at times, be illusory. Observers come away feeling confident that they’re well prepared to try the task out themselves, but when they do, often they’re not better than they were before.

Many Skills Are Easier Seen Than Done

In six experiments, recently published in Psychological Science, we tested the hypothesis that people overestimate how much their abilities improve after extensively watching others perform. In one experiment, 193 University of Chicago students visited our lab for a dart-throwing

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How Nextdoor Addressed Racial Profiling on Its Platform

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On March 3, 2015, hyperlocal social network Nextdoor announced that it had raised $110 million in venture capital. The deal valued the company at more than $1 billion—revered, unicorn status. It had to be a giddy moment for CEO Nirav Tolia and co-founders David Wiesen, Prakash Janakiraman, and Sarah Leary. But just three weeks later, all of that celebrating must have seemed like a distant memory.

The news site Fusion ran an article explaining how Nextdoor “is becoming a home for racial profiling.” Reporter Pendarvis Harshaw detailed how presumably white members were using Nextdoor’s crime and safety forum to report “suspicious” activities by African Americans and Latinos. Jennifer Medina of The New York Times followed up, reporting that “as Nextdoor has grown, users have complained that it has become a magnet for racial profiling, leading African-American and Latino residents to be seen as suspects in their own neighborhoods.”

Facebook is Exxon of the Internet

“…the utopian view of social networking connecting everyone for good is coming to end across the political spectrum. Now it’s seen less as a hopeful tool and more as a weapon that everyone thinks is in the wrong hands. In many ways, Facebook is like the Exxon of our time — an indispensable tool that everyone despises — Exxon, maybe Comcast, and now Facebook; there’s not a lot of brands like that. After enough oil spills, we started investing in solar and battery technology … now we need to find our digital solar and batteries to invest in.”

Moxie Marlinspike, a security researcher & former head of security at Twitter. Via

The Thing I Love Most About Uber

In spite of all the ink that journalists, analysts, and pundits have spilled on Uber over the years, no mainstream article has focused on what I consider to be the most elegant feature of this now ubiquitous, high growth global service — no driver-partner is ever told where or when to work. This is quite remarkable — an entire global network miraculously “level loads” on its own. Driver-partners unilaterally decide when they want to work and where they want to work. The flip side is also true — they have unlimited freedom to choose when they do NOT want to work. Despite the complete lack of a “driver-partner schedule” this system delivers pick-up times that are less than 5 minutes (in most US cities (with populations over 25K) and in 412 cities in 55 other countries. The Uber network, along with Mr. Smith’s invisible hand, is able to elegantly match supply and demand, without the “schedules” and “shifts” that are the norm in most every other industry.

Some have raised questions and concerns about the “gig” economy and the rise of these new independent and autonomous work types. Detractors frequently highlight that these work types lack some of the structured benefits that are frequently attached to traditional full time job offerings. However, what they fail to consider is that there is one critical and fundamental feature of the “gig” economy that is completely absent from traditional job types. That feature — worker autonomy of both time and place — simply does not exist in other industries. One cannot show up for work at Starbucks on a Monday and then decide not to work at all on Tuesday, and for only 2 hours on Wednesday. Oh yeah, and then on Thursday let’s just “play it by ear.” One cannot get a job at Walmart or McDonalds or ironically even as a taxi cab driver without agreeing to some sort of shift or schedule. It is unheard of for an employee to say “I want to work 3 hours this week, 45 the next, and then take 2 weeks off.” This autonomy and freedom of the “gig” work type, which is highly valued by millions and millions of people, would be impossible to implement for the overwhelming majority of companies.

In November of 2014, the Morgan Stanley sell-side research team that focuses on the auto industry, headed by Adam Jonas, made a trip to Detroit to visit the big three automakers. In their own words, “the highlight of the trip, however, was three Uber trips we took between meetings.” They chronicled these three trips in a report they published titled, Confessions of an Uber Driver: Rollin in the ‘D.

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The Thing I Love Most About Uber

In spite of all the ink that journalists, analysts, and pundits have spilled on Uber over the years, no mainstream article has focused on what I consider to be the most elegant feature of this now ubiquitous, high growth global service — no driver-partner is ever told where or when to work. This is quite remarkable — an entire global network miraculously “level loads” on its own. Driver-partners unilaterally decide when they want to work and where they want to work. The flip side is also true — they have unlimited freedom to choose when they do NOT want to work. Despite the complete lack of a “driver-partner schedule” this system delivers pick-up times that are less than 5 minutes (in most US cities (with populations over 25K) and in 412 cities in 55 other countries. The Uber network, along with Mr. Smith’s invisible hand, is able to elegantly match supply and demand, without the “schedules” and “shifts” that are the norm in most every other industry.

Some have raised questions and concerns about the “gig” economy and the rise of these new independent and autonomous work types. Detractors frequently highlight that these work types lack some of the structured benefits that are frequently attached to traditional full time job offerings. However, what they fail to consider is that there is one critical and fundamental feature of the “gig” economy that is completely absent from traditional job types. That feature — worker autonomy of both time and place — simply does not exist in other industries. One cannot show up for work at Starbucks on a Monday and then decide not to work at all on Tuesday, and for only 2 hours on Wednesday. Oh yeah, and then on Thursday let’s just “play it by ear.” One cannot get a job at Walmart or McDonalds or ironically even as a taxi cab driver without agreeing to some sort of shift or schedule. It is unheard of for an employee to say “I want to work 3 hours this week, 45 the next, and then take 2 weeks off.” This autonomy and freedom of the “gig” work type, which is highly valued by millions and millions of people, would be impossible to implement for the overwhelming majority of companies.

In November of 2014, the Morgan Stanley sell-side research team that focuses on the auto industry, headed by Adam Jonas, made a trip to Detroit to visit the big three automakers. In their own words, “the highlight of the trip, however, was three Uber trips we took between meetings.” They chronicled these three trips in a report they published titled, Confessions of an Uber Driver: Rollin in the ‘D.

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Facebook Is Changing How Marketers Can Target Ads. What Does That Mean for Data Brokers?

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Last month, Facebook announced in a brief statement that it will be shutting down Partner Categories, a feature that allows marketers to target ads on the company’s universe of platforms by using third-party data provided by data brokers. The move, which comes during a period of intense scrutiny over the social media giant’s privacy and security practices following the Cambridge Analytica revelations, marks a first-of-its-kind pivot among internet companies. This development could have major repercussions for internet companies and the broader digital advertising ecosystem if the firms at the center of this industry follow suit, collectively distancing themselves from data brokers and increasing transparency into their practices with personal data.

Traditionally, marketers on Facebook — and on most major platforms that allow targeted ads — have had three types of data streams they could leverage for targeting. First, they could use data they have collected themselves,

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How to Think for Yourself When Algorithms Control What You Read

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With the flick of a switch, a handful of tech giants can change the nature and extent of mankind’s ingestion of information. In 2013, Google took a step towards understanding the intent of their users with the Hummingbird algorithm. Twitter replaced most-recent with most-important tweets when they introduced their algorithmic timeline in 2016. Facebook claimed they’ll be replacing clickbait with more meaningful interactions on their feeds earlier this year.  These changes are almost always met with public uproar for a few weeks, soon after which humanity acquiesces. The ability for an elite to instantly alter the thoughts and behavior of billions of people is unprecedented.

This is all possible because of algorithms. The personalized, curated news, information and learning feeds we consume several times a day have all been through a process of collaborative filtering. This is the principle that if I like X, and you and

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Online Reviews Are Biased. Here’s How to Fix Them

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In the age of the internet, reputations are almost never a blank slate. Consumers are surrounded by online reviews thanks to other consumers who’ve gone to the trouble of posting opinions about products and services online.

But online reviews are a dual-edged sword. On the one hand, they’re a blessing if they help consumers to make more informed decisions. On the other hand, there is a systematic problem with many online reviews — they tend to over-represent the most extreme views.

To see why, consider the last time you purchased a product. Perhaps you were asked to provide a review afterward. Did you do it? If so, our research suggests you most likely really loved the product, or absolutely hated it. If instead you had a moderate view, you’re likely to have left no review at all, finding it not worth the time and effort.

That problem generalizes

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The 4 Dimensions of Digital Trust, Charted Across 42 Countries

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The year 2018 is barely underway and, already, digital trust initiatives have captured headlines. Facebook’s Mark Zuckerberg has said his platform will de-prioritize third-party publisher content to keep users focused on more “meaningful” posts from family and friends. Google has led off the new year by blocking websites that mask their country of origin from showing up on Google News. And the European Union’s upcoming General Data Protection Regulation (GDPR) will affect every organization around the world that handles personal data for EU residents. The regulations will also, no doubt, inform data protection laws and corporate trust-building strategies elsewhere.

Even China’s opaque behemoths have started the year with unprecedented acknowledgements of the need to address trust concerns: Tencent had to publicly deny that it collects user WeChat history after it was openly challenged; Alibaba’s Ant Financial apologized to users of its mobile-payment service for automatically enrolling them in

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