Disruptive strategy: Unlock assets in adjacent markets

Article

John Hagel, John Seely Brown, Maggie Wooll, Andrew de Maar

February 12, 2016

Overview

Unlock assets from adjacent markets

Cultivating opportunities on the edge

Def. Provide effective access to significant stockpiles of underutilized assets in adjacent markets.

Across diverse industries, a new breed of companies is turning to underused assets from adjacent markets to expand the range of prices and offerings in established markets. Many fast-scaling new entrants are becoming indispensable to customers by focusing on customer service and network value to meet diverse needs rather than on asset ownership. Without the capital burden of owning the assets in their networks, they can onboard incremental adjacent assets at minimal marginal cost and achieve critical mass quickly.

In the report Patterns of disruption: Anticipating disruptive strategies in a world of unicorns, black swans, and exponentials, we explored, from an established incumbent’s point of view, the factors that turn a new technology or new approach into something cataclysmic to the marketplace-and to incumbents’ businesses. In doing so, we identified nine distinct patterns of disruption: recognizable configurations of marketplace conditions and new entrants’ approaches that can pose a disruptive threat to incumbents. Here, we take a deep dive into one of these nine patterns of disruption: unlock assets from adjacent markets.

Twenty years ago, it would have been difficult to imagine that, relatively soon, the world’s largest for-hire vehicle company would own no vehicles, the largest accommodation company would own no hotels, and the world’s largest international phone company would own little infrastructure. Today, that is reality.1 Companies like Uber, Airbnb, and others using new models based on widespread connectivity have quickly created new customer value by deploying assets from adjacent markets to serve their customers.

Acting as network orchestrators,2 companies like these provide access to the assets of fragmented suppliers-assets that were not previously in the market-to better meet volatile demand and satisfy customer preferences. For example, a customer searching for accommodations on Airbnb over the weekend of the Super Bowl might be able to choose from $65/night guest bedrooms, $650/night apartments, and $6500/night homes, all in neighborhoods not served by hotels.

The effect of unlocking underused assets is to make supply more elastic. For customers, that often translates into better availability of the product or service, even in periods of high demand. Often, as has generally been the case with ridesharing and home-sharing networks, customers also experience greater choice, as the newly available adjacent supply tends to be fragmented and not standardized. The diversity of supply can also lead to offerings that span a wider price range, with potentially a large number of offerings with significant price advantages.

Products and services from unlocked assets tend to be more affordable because the network operators have fewer direct costs, and because new supply can be deployed with minimal incremental cost. For example, a new unit of lodging can be added to a home-share network for little more than the cost of a background check as compared to the cost (and large increment) of building a new hotel facility. By not owning assets, network orchestrators can focus resources on creating and operating a network that works to deliver more value to the customer-whether that means speed, choice, price, or convenience-than incumbents’ traditional, accepted offerings.

Mobilizing third-party resources rather than owning assets can also create significant economic value for the network operator. Relative to traditional asset builders-businesses that compete through controlling proprietary productive assets for scale advantage3-leveraging network resources to deliver customer value helps to reduce up-front capital costs, limits fixed asset investment, and diffuses risk among a larger pool of participants. Up-front investments in assets, from factories to taxi medallions to prime real estate, tend to share two common traits: delayed returns on investment and lower margins. In addition, owners incur the risk that the up-front investment in assets might not pay off as expected.4 Companies functioning as network orchestrators typically can deploy assets more quickly, shortening lead time to new revenue opportunities at significantly lower marginal cost.5 Network operators’ profit margins are estimated to be 60 percent higher than those of asset builders,6 and network operators tend to have higher market valuations; network operators average a price-to-revenue ratio of 8.2, more than four times that of asset builders.7

“Excess capacity is the low-cost fuel that makes the effort of platform-building worthwhile.” -Robin Chase, Peers, Inc.8

This pattern is powerful because, in addition to being able to create value for customers and network operators, it can also create value for the adjacent assets’ owners. To achieve the critical mass to be relevant, the network operator has to create enough value for the potentially non-commercial asset owners to participate in the network. Many ridesharing transportation network companies have experimented with variable fare models and car/driver requirements to entice drivers of private vehicles to participate in their networks. A critical mass of supply buffers against spikes in demand and offers customers more choice.

If participation in a network is exclusive for asset owners or customers, scaling quickly is critical in order to secure the network against competitors. Even when networks are not exclusive-for instance, many drivers participate in multiple rideshare companies’ networks-reaching critical mass quickly can lead to exponential growth; more supply attracts a larger number of diverse consumers, which can in turn entice new suppliers to on-board their assets to the network. To further support building critical mass, the network operator should aim to make participation as easy as possible, even if the participation of the asset owner is mostly passive, as is the case with adjacent energy or computing resources.

But where do these underutilized, affordable, yet relevant assets come from? The fundamental premise of this pattern is that there exists a stockpile of assets in an adjacent market that can be applied to meet a customer’s need, but that the asset has not yet been commercialized for that purpose. Perhaps the asset has not been deployed commercially because there was no way to economically connect the asset with a customer, or because there was no visibility into the unused capacity of the assets, or because the existing market was too narrowly defined around existing products rather than customer needs. Even identifying adjacent markets and the usable assets within those markets can be hard (see sidebar, “Identifying adjacent assets”).

This strategy has become increasingly practicable as the world becomes more connected. It is made possible by advances in technologies such as location-aware devices, mobile payments, rich connectivity, and cloud computing power for matching and allocating algorithms. With powerful and affordable sensors and advanced real-time analytics, network operators can see asset usage and balance supply and price with demand at any given time. Aggregation platforms help overcome many of the challenges previously associated with connecting fragmented supply and demand, such as high search costs (in terms of both effort and time), transaction costs, and other risks. This type of strategy also becomes more feasible as companies develop competencies around network management and customer engagement. Further, as this model is tested in more markets, insurance products to underwrite new types of risk are likely to be introduced, making customers feel more comfortable with the quality and reliability of alternative supply, and helping asset owners to become more familiar with the model. Network effects serve to increase the incentive for owners to on-board their assets, as more markets with more offerings can attract a broader range of demand.

The regulatory environment plays a role in the disruptive potential for this pattern. Initially, as has been the case with cars and lodging, the new entrant and the owners of the adjacent asset supply tend not to be subject to the types of regulations faced by traditional incumbents. Complying with regulations can add time and expense to delivering offerings to consumers, often giving less-regulated network operators an advantage to scale more quickly and inexpensively. For example, municipalities regulate the price and number of permits issued for taxi medallions, while Uber’s growth is limited primarily by how quickly they can attract new drivers.

This pattern is difficult for incumbents to respond to when it makes existing assets obsolete or significantly devalued. The incumbent has likely made a significant investment in fixed assets to gain scale, while the new competition can gain scale without owning those assets. Further, the incumbent’s ability to monetize its investment is often impaired, because the new entrant, operating with a higher margin, can directly attack the incumbent’s core revenue streams with a lower-price offering. Even if the incumbent adapts by redeploying assets to create a new, lower-price offering that can compete with the new entrants’ leveraged models, such an offering would likely cannibalize the incumbent’s key revenue streams. Switching to a leveraged network model would challenge the incumbent’s core beliefs around what customers value and how value can be delivered-for example, that customers will accept a service delivered by amateurs rather than professionals. Adopting the new model would require repurposing or reconfiguring existing capital and infrastructure investments,9 and incumbents may not have the capabilities to cultivate and manage a network of fragmented suppliers.

The pattern of unlocking assets from adjacent markets can only occur in markets where two conditions exist: Customers’ needs must be able to be satisfied with an alternative asset, and that asset must be available-either because it is not being fully utilized or is being used for a lower-value purpose-in significant quantities to be deployed in that market. The mere existence of an adjacent asset will not necessarily be disruptive. For example, the books sitting on bookshelves in homes across the country are arguably underutilized and exist in significant quantity, yet they are unlikely to prove disruptive to booksellers, e-book purveyors, or libraries. The value of the item is small, demand is typically already met, and customers are able to satisfy their preferences for choice and affordability under current commercialization models.

On the other hand, deploying alternative assets to deliver a product or service will tend to be disruptive in markets with volatile demand or cyclical misalignment of supply and demand. Such misalignments occur either because supply is inelastic while demand is more volatile, or simply because adding additional supply capacity requires assets that are costly and require significant time to deploy. Assets need to be able to be used either simultaneously or in sequence without significantly losing value-thus, durable assets such as heavy equipment can be used repeatedly without per-use wear and tear impairing the value of the asset. Finally, markets with more diverse demand characteristics tend to be more vulnerable to disruption through this pattern: If every customer had standard preferences, such as for a $200 room with a queen-sized bed located downtown, they would be less interested in or willing to accept alternatives to that standard.

Unlocking adjacent assets is both powerful and challenging. Network effects typically confer a significant advantage to those who can identify and deploy adjacent assets first, yet both the underutilized adjacent assets (and the fundamental customer need they are meeting) are often obvious only after they’ve been deployed. When these models succeed in significantly improving the customer experience and also in creating significant new value for the asset owners, they can swiftly reshape an industry and surprise incumbents who ignore the world of possible alternatives for their customers.

Key stats

  • Uber delivered its one-billionth ride five-and-a-half years after launching.10
  • Uber covers 75 percent of the US population.11
  • The top 40 Airbnb hosts in New York have each grossed at least $400,000 over the past three years (from 2013).12
  • If its pace of growth continues, Airbnb’s supply could be larger than that of the top 10 hotel companies combined within two years.13
  • Airbnb lists properties in 97 percent of the world’s countries and has over 2 million listings.14

Identifying adjacent assets

Identifying potentially usable, undervalued, and underused assets is core to both executing this pattern and preparing for it. However, the valuable adjacent assets that can be leveraged to transform an industry tend to be, unfortunately, most obvious only once a competitor has deployed them.

Lower-tier customer needs that can be satisfied by alternative assets can further expand the market. For example, a customer may choose a Lyft car ride because they can choose the radio station, ride in the front seat, and chat with the driver in addition to getting affordable transportation.

Focusing on historical or predicted product use cases can limit opportunities for growth. Interestingly, incumbents might not notice that their market is expanding if they continue to define their market narrowly-for instance, if they see their business as providing telephone service rather than communication.

To help identify and unlock usable assets, incumbents should consider the following questions:

1. What is the fundamental need customers who choose your product are trying to satisfy?

2. What alternatives can satisfy that same need?

a. Are those alternative assets currently being used to their full capacity?

b. Can they be deployed to greater value?

c. Can you create a network of these assets that achieves critical mass?

3. Do the assets that address your primary value proposition also satisfy secondary customer needs?

4. Can the assets be made accessible and economically deployed to your customers?

“Scale makes big surpluses function differently from small ones.” -RClay Shirky, Cognitive Surplus

Digging deeper

Is deploying assets from adjacent markets the same thing as the sharing economy or collaborative consumption?

These concepts are related, but not all sharing models unlock underused assets. Companies that unlock adjacent assets operate networks of latent supply, building scale very quickly without investing as much capital as their asset-building counterparts. The supply already exists in the economy, and only needs to be identified and properly accessed for the market to take advantage.

Consider the difference between two common carsharing models. In each model, the company has built a digital platform that enables collaborative consumption of automobiles. In each case, members use an app to search for a convenient, available vehicle that they rent by the hour, picking it up from and returning it to its “home” garage. company A owns a fleet of cars that are garaged in fixed locations around the city. In contrast, company B merely connects customers who want to rent a vehicle with private owners of underutilized vehicles and facilitates the transaction (through automated unlocking, payment handling, and customer service). Building and maintaining company A’s fleet is more resource-intensive than recruiting the fleet of privately owned company B cars, although company A can typically deliver a more consistent experience.

The “unlocking assets from adjacent markets” pattern shares aspects of the model ZipCar founder Robin Chase defined as “Peers, Inc.” The model is predicated on three key elements: the existence of “excess capacity” in a market; the use of a platform to provide more efficient access to that capacity; and the collaborative, creative engagement of a group of peers who serve as suppliers and/or customers. However, the third element in particular is not necessary for disruption to occur (for example, Uber customers are not creatively collaborating with the company), although it is possible that deeper, collaborative engagement with suppliers or customers might prove useful in fending off copycat competition that could disrupt the disruptor. Be that as it may, the power of this pattern comes more from the ability to scale much more quickly and with less investment than is possible for more traditional businesses.

How is this pattern different than simply being more resourceful and leveraging waste?

There are many types of underutilized assets, one of which is waste. For example, a tire company might decide to turn the used tires returned by customers into rubberized flooring surfaces, creating a new product line with very low raw material cost and saving on waste disposal costs as well. While reducing waste or repurposing the byproducts of other processes to create a new product or service can be an opportunity for cost savings and new growth, it is not likely to be disruptive. These applications do not necessarily change the fundamental underlying value of existing assets because supply tends to be concentrated and a large amount of processing is typically required to repurpose the asset.

Case studies

Uber disrupts taxis in their local markets

Offering rides “e-hailed” directly from a smartphone app, Uber Technologies, Inc. and other ride services have shaken the taxi industry.18 The company capitalized on increasing customer trust of strangers and asset sharing as well as the connectivity enabled by widespread smartphone use to first deploy “for hire” town cars and then privately owned vehicles in the non-chartered ride marketplace.19 While Uber is often labeled “disruptive” due to its high $62.5 billion valuation,20 the data demonstrate that Uber and one of its competitors, Lyft, have collectively displaced incumbents and expanded the market, truly disrupting the industry.21 Of note, the disruptive impact of such private car networks will vary according to the local nature of taxi regulations,22 but the data suggest the taxi industry everywhere has cause for concern when the unlocking pattern appears on the horizon.

To appreciate how the industry has evolved, consider the US taxi market pre-Uber (2009-2010). The taxi industry was long characterized by heavy regulations23 and consumer dissatisfaction.24 Although regulations were managed locally, inefficiencies and reported problems were industry-wide. For example, a 1984 Federal Trade Commission report found that “there is no persuasive economic rationale for some of the most important regulations.”25 The report cites limits on the number of participating firms and vehicles, as well as minimum fares, as a waste of resources and a burden on the lower-income population.26 A more recent study by Princeton professor Henry Farber in October 2014 found that inadequate pricing incentives led to a scarcity of taxis under unpleasant or dangerous weather conditions, when taxis are most in demand.27

Local studies of the industry before rideshares showed high consumer dissatisfaction and inefficient service. In a 2006 study of the New York City taxi ecosystem, industry experts Schaller Consulting reported that consumers were dissatisfied with their ability to get a cab on demand, the value relative to cost, safety from accidents, drivers’ ability to navigate, and driver courtesy.”32 New York cabs wasted 39 percent of total mileage in 2005 cruising for passengers.33 In San Francisco, a 2007 dispatch survey found that the average time for a taxi to arrive after a request was around 16 minutes, and approximately 50 percent of the taxis dispatched never arrived. From the street, the average time to hail a taxi was approximately 8 minutes.34

Enter Uber: Uber identified idle town cars in the adjacent “for hire” market as viable substitutes to provide short-range transportation to dissatisfied taxi customers. Although regulations prohibited any car without a medallion from picking up street hails-“for hire vehicles” had to rely on call-ahead reservations35-the increasing use of location-aware smartphones made it possible to request and dispatch rides without street hails, allowing the town cars to compete directly with taxis. Ubiquitous connectivity, Uber’s efficient hailing and driver apps, and increasing familiarity with user-rating systems to establish trust enabled Uber to unlock and deploy these assets as a more expensive, but more dependable, alternative to taxi rides. The cars were driven by professional, courteous drivers and were clean and comfortable.36 With increased access to data from smartphones, Uber’s platform embedded an incentive structure to dynamically match supply with demand through “surge-pricing”-when demand was high, fares increased to entice more drivers on to the streets. Dynamic algorithms had finally addressed the “how to find a taxi in the rain” problem.37

Uber-disruptive or not? A response to Christensen

In a recent Harvard Business Review article, Harvard Business School Professor Clayton Christensen states that Uber is not disruptive based on his theory of disruptive innovation. “Uber’s financial and strategic achievements do not qualify the company as genuinely disruptive . . .” While debating whether or not Uber is disruptive is not the purpose of this research into patterns of disruption, given the nature of his recent article, it is worth proactively addressing any confusion about the difference of perspective.

The differences are primarily definitional. Here, we refer to disruption as an outcome that can result from different strategies, including the “enter low and work up market” strategy, while Professor Christensen’s disruptive innovation is defined by the entry point and the process itself. The reasons Christensen provides for why Uber is not disruptive are that it 1) did not originate in the low end of the market or in a new market, either of which is required by his definition, and 2) did not start with an inferior product.

As we describe in the case study, Uber (and its competitor Lyft) both took significant market share from the incumbent taxi companies and expanded the market for on-demand mobility. Therefore, Uber and other ridesharing companies can be considered disruptive to the taxi industry.

“In the collaborative economy, growth doesn’t require us to expand production and consumption of physical goods. Instead, growth occurs when each individual peer joins a platform and contributes.” -Robin Chase, Peers, Inc.

Airbnb challenges the affordable hotel market

As a network orchestrator, Airbnb competes on a different basis than major hotel chain incumbents, whose expertise is in forecasting, management, and design and development of properties. One differentiator for Airbnb is its ability to rapidly scale; Airbnb can grow as quickly as it can attract owners to list their spare rooms or properties. In 2015, that pace exceeded 2,700 new listings per day.59 In comparison, three hotel brands (Hilton, Marriott, and InterContinental Hotels Group) added between 80 and 200 rooms per day on average,60 and took an average of two to three years to fully develop a project in the pipeline.61 In addition, because it commercializes existing properties rather than developing its own, Airbnb’s incremental costs to add listings to the platform (for example, professional listing photos) are nominal.

While Airbnb’s platform provided a convenient marketplace to connect hosts and guests, its rapid growth was also due to its use of signaling mechanisms to build trust and maximize the likelihood of successful bookings. An online reputation system lets participants-both guests and hosts-rate and review each stay, and hosts and landlords are covered by an insurance policy of up to $1 million.66 These mechanisms reinforce transparency, encourage participatory quality control, and build trust in the privately owned assets, helping to create value for all participants.

Major hotel chains maintain a pricing scheme that matches consumer demand for varying standards of quality and covers their high fixed costs. Airbnb hosts, on the other hand, are typically not hotel professionals and set prices they deem appropriate. Barclays found that in many cases, prospective consumers find that Airbnb offers a less expensive alternative to hotels, with some studies showing a 20-50 percent discount.69

The distributed locations, combined with the lack of standardization or regulated quality, tends to deter the business traveler whom mid-scale hotels serve-only 10 percent of Airbnb guests are estimated to be business travelers versus 60 percent of hotel guests. Airbnb also caters to certain types of customers, like those whose stay exceeds 30 days or large groups renting entire properties, who could not otherwise stay at hotels-in New York City, almost a quarter of Airbnb stays would not be possible in hotels.72

Short story

On-site energy storage

The sun and the wind. Not assets in the traditional sense, but arguably the energy contained in the sun’s rays beating down on the roof of a food processing plant or the winds whipping off the suburban hills is underutilized. And where wind turbines and solar panels are installed, their power-generating capacity often doesn’t align with demand at any given point in time. Development of wind and solar has been hampered, in part, by the wide variability in output throughout the day and year. Solar panels on a home or business might provide adequate energy for the customer while the sun is shining, but when the sun goes down, the customer still needs power. When demand is low, the value of wind and solar assets exceeds the demand for power only as a result of net metering programs that require utility companies to buy the excess energy from customers at retail rates.79 In fact, even traditional sources of power generation often represent excess capacity at different times throughout the day when the generating capacity is greater than customer demand.

Today, however, advances in energy storage technologies (for example, batteries, flywheels) are enabling more widespread, distributed energy storage, enabling customers to have greater control over their use of energy from the grid and removing one barrier to the use of renewables.82 This could prove disruptive to utility-owned generation. Whether or not it is disruptive to the incumbent providers of power-the utility companies-will depend on who owns the storage, its size, where it is located, and the level of connectedness (to the grid or to other users).

Customer-sited batteries, whether for the home or for a commercial user (for example, a food processing plant), have the potential to disrupt in two ways. One, they allow a user to store the excess energy generated by the on-site solar unit, wind turbine, or other energy generation source for use when demand is higher or generation is lower, potentially eliminating dependence on power from the utility provider. Two, customer-sited storage enables large commercial customers to store energy from the grid during off-peak times and consume electricity from storage during peak times without shutting down machinery or losing productivity. In doing so, the commercial customer avoids the “demand charges” utilities typically levy on commercial customers to offset the expensive peak power, eliminating a major revenue stream for utilities. These batteries could disrupt in another way as well: via microgrids that connect small-scale power generators (for example, individuals or businesses that have on-site generating assets) to other users-this would disrupt through the “connect peers” pattern and is also more subject to regulatory conditions in local markets.

Are there other products or services, not yet commercialized, that can deliver the same basic function to consumers?

Is my market vulnerable?

Is demand for my product or service volatile and the supply inelastic?

If your product or service has a potential substitute in an adjacent market, you are vulnerable to this pattern. The potential substitute must have a similar function. There are many reasons the substitute might not yet be commercialized: Regulatory restrictions might prevent it from entering the marketplace or an entrepreneur has yet to see it for its full value. See the sidebar above on “Identifying adjacent assets” for more on recognizing substitute products or services in adjacent markets.

Does your industry face stringent taxes or regulations that limit supply or increase cost?

Volatile demand and inelastic supply create a market disequilibrium that can make goods too expensive or unavailable. Companies that commercialize and orchestrate networks of fragmented supply can respond more flexibly to these situations.

Assets unlocked from adjacent industries are usually not subject to the same regulations as those already commercialized, and can therefore be deployed at a lower cost.

Acknowledgements

This research would not have been possible without generous contributions and valuable feedback from numerous individuals. The authors would like to thank: Philippe Beaudette, Andrew Blau, Peter Fusheng Chen, Jack Corsello, Larry Keeley, Eamonn Kelly, Vas Kodali, Jon Pittman, Janet Renteria, Suzanna Sanborn, Peter Schwartz, Dan Simpson, Vivian Tan, Lawrence Wilkinson, Andrew Ysursa, Blythe Aronowitz, Jodi Gray, Carrie Howell, Junko Kaji, Duleesha Kulasooriya, and Kevin Weier.

Endnotes

    1. This is not to say that companies following this model don’t own any assets, nor is it a question of leasing versus owning. The point is that they do not own or control the assets traditionally associated with providing a type of service to the customer. View in article
    2. The terms “network orchestrator” and “asset builder” were defined in a joint research study from Deloitte and OpenMatters in conjunction with Wharton to describe two of the four business models that have been used in the past 40 years. Barry Libert, Yoram (Jerry) Wind, and Megan Beck Fenley, “What Airbnb, Uber, and Alibaba have in common,” Harvard Business Review, November 20, 2014, https://hbr.org/2014/11/what-airbnb-uber-and-alibaba-have-in-common, accessed December 17, 2015. View in article
    3. Ibid. View in article
    4. Ibid. View in article
    5. Edge Perspectives with John Hagel, “Exploring new forms of economic leverage,” http://edgeperspectives.typepad.com/edge_perspectives/2008/10/exploring-new-f.html, accessed December 17, 2015. View in article
    6. Barry, et al. “What Airbnb, Uber, and Alibaba have in common.” The study estimated that network orchestrators operated at a 24 percent margin versus 15 percent for asset builders, on average. View in article
    7. Ibid. View in article
    8. Robin Chase, Peers, Inc.: How People and Platforms Are Reinventing the Collaborative Economy and Reinventing Capitalism, (New York, NY: PublicAffairs, 2015), p. 35. View in article
    9. This unlocking of assets is closely related to the model of a collaborative economy which thrives on sharing, openness, and connectedness outlined by Robin Chase in her book, Peers, Inc. As familiarity and acceptance of the sharing economy model grows among producers and consumers, the potential for asset substitutes and unlocking in adjacent markets will only increase. View in article
    10. Katie Roof, “Uber hits one billionth ride, gifts free year,” TechCrunch, December 30, 2015, http://techcrunch.com/2015/12/30/uber-hits-one-billionth-ride-gifts-free-year-of-rides/#.mryx5d:mnNv, accessed January 1, 2016. View in article
    11. Andrew J. Hawkins, “Uber covers 75 percent of the US, but getting to 100 will be really hard,” Verge, http://www.theverge.com/2015/10/23/9603324/uber-coverage-rural-areas-dominance-plan, accessed January 1, 2016. View in article
    12. Elizabeth A. Harris, “The Airbnb economy in New York: Lucrative but often illegal,” November 4, 2013, http://www.nytimes.com/2013/11/05/nyregion/the-airbnb-economy-in-new-york-lucrative-but-often-unlawful.html?smid=tw-share&_r=0, accessed December 17, 2015. View in article
    13. Vicki Stern, Patrick Coffey, Richard Taylor, James Rowland Clark, Flecia R. Hendrix, and Anthony F. Powell, Hotels: Is Airbnb a game-changer?, Barclays, January 16, 2015, p. 11, accessed December 2015. View in article
    14. Airbnb corporate website, “About,” https://www.airbnb.com/about/about-us/, accessed January 21, 2016. View in article
    15. Clayton M. Christensen and Michael E. Raynor, “Creating a killer product,” Forbes, October 13, 2003. View in article
    16. Clayton M. Christensen, Scott D. Anthony, Gerald Berstell, and Denise Nitterhouse, “Finding the right job for your product,” MIT Sloan Management Review, April 1, 2007. View in article
    17. Clay Shirky, Cognitive Surplus: How Technology Makes Consumers into Collaborators, (New York: Penguin Books, 2010), p. 24. View in article
    18. John Patrick Pullen, “Everything you need to know about Uber,” Time, November 4, 2014, http://time.com/3556741/uber/, accessed January 1, 2016. View in article
    19. Julian Chokkattu and Jordan Crook, “A brief history of Uber,” TechCrunch, August 14, 2014, http://techcrunch.com/gallery/a-brief-history-of-uber/slide/8/, accessed December 15, 2015; Charles J. Johnson, “Timeline: The history of Uber,” Chicago Tribune, March 11, 2015, http://www.chicagotribune.com/bluesky/technology/chi-timeline-ubers-controversial-rise-20150205-htmlstory.html, accessed December 12, 2015. View in article
    20. Eric Newcomer, “Uber raises funding at $62.5 billion valuation,” Bloomberg Business, December 3, 2015, http://www.bloomberg.com/news/articles/2015-12-03/uber-raises-funding-at-62-5-valuation, accessed December 4, 2015. View in article
    21. Karen Weise, “These four charts show how Uber steals turf from cabs and spreads throughout a city,” Bloomberg Business, October 19, 2015, http://www.bloomberg.com/news/articles/2015-10-19/these-four-charts-show-how-uber-steals-turf-from-cabs-and-spreads-throughout-a-city, accessed December 4, 2015. View in article
    22. Karen Weise, “This is how Uber takes over a city,” Bloomberg Business, June 23, 2015, http://www.bloomberg.com/news/features/2015-06-23/this-is-how-uber-takes-over-a-city, accessed December 4, 2015. View in article
    23. Mark W. Frankena and Paul A. Pautler, An economic analysis of taxicab regulation, Federal Trade Commission, May 1984, https://www.ftc.gov/sites/default/files/documents/reports/economic-analysis-taxicab-regulation/233832.pdf, accessed December 2015. View in article
    24. City and Country of San Francisco Taxi Commission, “Public convenience and necessity report,” February 13, 2007, http://www.medallionholders.com/docs/pcn-07-report.pdf, accessed December 2015; Schaller Consulting, The New York City taxicab fact book, March 2006, http://www.schallerconsult.com/taxi/taxifb.pdf, accessed December 2015. View in article
    25. Mark W. Frankena and Paul A. Pautler, An economic analysis of taxicab regulation, Federal Trade Commission, May 1984, https://www.ftc.gov/sites/default/files/documents/reports/economic-analysis-taxicab-regulation/233832.pdf, accessed December 2015. View in article
    26. Ibid. View in article
    27. Henry S. Farber, Why you can’t find a taxi in the rain and other labor supply lessons from cab drivers, Princeton University, October 2014, http://www.parisschoolofeconomics.eu/IMG/pdf/taxi65_farber-2.pdf, accessed December 2015. View in article
    28. Lawrence Van Gelder, “Medallion limits stem from the 30’s,” New York Times, May 11, 1996, http://www.nytimes.com/1996/05/11/nyregion/medallion-limits-stem-from-the-30-s.html, accessed December 12, 2015. View in article
    29. Bruce Schaller, The New York City for-hire vehicle fact book, New York City Taxi and Limousine Commission, February 1993, http://www.schallerconsult.com/taxi/fhv_fb.htm, accessed December 2015; Emily Badger, “Taxi medallions have been the best investment in America for years. Now Uber may be changing that,” Washington Post, June 20, 2014, https://www.washingtonpost.com/news/wonk/wp/2014/06/20/taxi-medallions-have-been-the-best-investment-in-america-for-years-now-uber-may-be-changing-that/, accessed December 12, 2015. View in article
    30. Ibid. View in article
    31. Carolyn Said, “In the days of Uber, Lyft, some still buy S.F. taxi medallions,” SF Gate, January 25, 2015, http://www.sfgate.com/business/article/In-the-days-of-Uber-Lyft-some-still-buy-S-F-6038188.php, accessed December 4, 2015. View in article
    32. Schaller Consulting, The New York City taxicab fact book. View in article
    33. Ibid. View in article
    34. City and Country of San Francisco Taxi Commission, “Public convenience and necessity report,” February 13, 2007, http://www.medallionholders.com/docs/pcn-07-report.pdf, accessed December 2015. View in article
    35. Schaller, The New York City for-hire vehicle fact book. View in article
    36. Pullen, “Everything you need to know about Uber.” View in article
    37. Ibid. View in article
    38. Uber.com Newsroom, “Drive with Uber-Earn cash with your car! (full-time),” https://newsroom.uber.com/drive-with-uber-earn-cash-with-your-car-6/, March 28, 2014. View in article
    39. Lisa Rayle, Susan Shaheen, Nelson Chan, Danielle Dai, and Robert Cervero, App-based, on-demand ride services: Comparing taxi and ridesourcing trips and user characteristics in San Francisco, University of California Transportation Center, November 2014, http://www.its.dot.gov/itspac/Dec2014/RidesourcingWhitePaper_Nov2014.pdf, accessed December 2015. View in article
    40. Some of Uber’s scale was achieved through financing rather than leverage-the company’s policy to finance new vehicles for its drivers entering the market, rather than unlocking. By 2015, only approximately 12.5 percent of drivers in the United States became Uber drivers in this manner. The majority of the impact was from unlocking vehicles previously prevented from entering or competing in the taxi market. View in article
    41. Uber.com Newsroom, “The new UberX: Better, faster, and cheaper than a taxi,” https://newsroom.uber.com/sf/uberx-cheaper-than-a-taxi/, June 11, 2013. View in article
    42. Weise, “These four charts show how Uber steals turf from cabs and spreads throughout a city.” View in article
    43. Weise, “This is how Uber takes over a city.” View in article
    44. Amelia Templeton, “3 big takeaways from Portland’s data on Uber and taxis,” Oregon Public Broadcasting, July 20, 2015, http://www.opb.org/news/article/three-big-takeaways-from-portlands-data-on-uber-and-taxis/, accessed December 4, 2015. View in article
    45. Karen Weise, “These four charts show how Uber steals turf from cabs and spreads throughout a city.” View in article
    46. Megan Garber, “After Uber, San Francisco has seen a 65% decline in cab use,” Atlantic, September 17, 2014, http://www.theatlantic.com/technology/archive/2014/09/what-uber-is-doing-to-cabs-in-san-francisco-in-1-crazy-chart/380378/, accessed December 15, 2015. View in article
    47. Anita Balakrishnan, “Uber more popular than taxis for biz travelers,” CNBC, October 15 2015, http://www.cnbc.com/2015/10/14/the-business-travel-taxi-market-getting-dominated-by-uber-lyft-and-airbnb.html, accessed December 15, 2015. Business travelers make up approximately 25 percent of the market for taxis and limousine services. View in article
    48. Josh Barro, “New York City taxi medallion prices keep falling, now down about 25 percent,” New York Times, January 7, 2015, http://www.nytimes.com/2015/01/08/upshot/new-york-city-taxi-medallion-prices-keep-falling-now-down-about-25-percent.html?_r=0, accessed December 12, 2015. View in article
    49. Jonathan Hall and Alan Krueger, An analysis of the labor market for Uber’s driver-partners in the United States, January 22, 2015, https://s3.amazonaws.com/uber-static/comms/PDF/Uber_Driver-Partners_Hall_Kreuger_2015.pdf, accessed December 2015. View in article
    50. Uber.com Newsroom, “The new UberX.” View in article
    51. San Francisco Municipal Transportation Agency, “Taxi rates,” https://www.sfmta.com/getting-around/taxi/taxi-rates, accessed December 17, 2015. View in article
    52. Aamer Madhani, “Once a sure bet, taxi medallions becoming unsellable,” USA Today, May 18, 2015, http://www.usatoday.com/story/news/2015/05/17/taxi-medallion-values-decline-uber-rideshare/27314735/, accessed December 15, 2015. View in article
    53. JP Mangalindan, “San Francisco cab drivers are Uber’s latest pickup,” Fortune, January 15, 2014, http://fortune.com/2014/01/15/san-francisco-cab-drivers-are-ubers-latest-pickup/, accessed December 15, 2015. View in article
    54. Ibid, p. 256. View in article
    55. Jessica Salter, “Airbnb: The story behind the $1.3bn room-letting website,” Telegraph, September 7, 2010, http://www.telegraph.co.uk/technology/news/9525267/Airbnb-The-story-behind-the-1.3bn-room-letting-website.html, accessed December 4, 2015. View in article
    56. Airbnb, “About us,” https://www.airbnb.com/about/about-us/, accessed December 7, 2015. View in article
    57. Rolfe Winkley, “Airbnb raises over $100 million as it touts strong growth,” Wall Street Journal, November 20, 2015, http://www.wsj.com/articles/airbnb-raises-over-100-million-as-it-touts-strong-growth-1448049815, accessed December 4, 2015. View in article
    58. Current market valuations for: Hilton: $21.5 billion; Marriott: $17.2 billion; IHG: $9.0 billion; Google Finance. View in article
    59. Airbnb, “About us,” https://www.airbnb.com/about/about-us/, accessed December 7, 2015. View in article
    60. Number of rooms accurate as of June 2015. Room numbers sourced as follows: Hilton Worldwide-Statista Dossier, Statista, accessed December 2015; InterContinental Hotels Group-Statista Dossier, Statista, accessed December 2015; Marriott International-Statista Dossier, Statista, accessed December 2015. View in article
    61. Vicki Stern, Patrick Coffey, Richard Taylor, James Rowland Clark, Flecia R. Hendrix, and Anthony F. Powell, Hotels: Is Airbnb a game-changer?, Barclays, January 16, 2015, page 11, accessed December 2015. View in article
    62. Deloitte analysis. Data sources: Hilton Worldwide Holdings Inc., “Form 10Q, September 2015; Marriott International, Inc., “Form 10Q,” September 2015;” Hilton Worldwide-Statista Dossier, Statista, accessed December 2015; InterContinental Hotels Group-Statista Dossier, Statista, accessed December 2015; Marriott International-Statista Dossier, Statista, accessed December 2015; Airbnb, “About us,” https://www.airbnb.com/about/about-us/, accessed December 7, 2015; Zainab Mundallal, “Airbnb will soon be booking more rooms than the world’s largest hotel chains,” Quartz, January 20, 2015, http://qz.com/329735/airbnb-will-soon-be-booking-more-rooms-than-the-worlds-largest-hotel-chains/, accessed December 15, 2015; Carole Cadwalladr, “Airbnb: The travel revolution in our spare rooms,” Guardian, September 16, 2013, http://www.theguardian.com/travel/2013/sep/16/airbnb-travel-revolution, accessed December 15, 2015; Nina Mandell, “Airbnb doubled number of listings in 2012,” Fast Company, February 7, 2013, http://www.fastcompany.com/3005629/where-are-they-now/airbnb-doubled-number-listings-2012, accessed December 15, 2015. View in article
    63. Deloitte analysis. Data sources: Marriott International, “Marriott facts,” http://www.marriott.com/careers/business-facts.mi, accessed December 2015; Hilton Worldwide, “About,” http://www.hiltonworldwide.com/about/, accessed December 2015; InterContinental Hotels Group, “Overview,” http://www.ihgplc.com/index.asp?pageid=16, accessed January 2016; Austin Carr, “Inside Airbnb’s grand hotel plans,” Fast Company, March 17, 2014, http://www.fastcompany.com/3027107/punk-meet-rock-airbnb-brian-chesky-chip-conley, accessed December 15, 2015. View in article
    64. Ibid. View in article
    65. Ibid. View in article
    66. Georgios Zervas and Davide Prosperio, The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry, Boston University, May 7, 2015, http://people.bu.edu/zg/publications/airbnb.pdf, accessed December 2015; Airbnb, “Host protection insurance,” https://www.airbnb.com/host-protection-insurance, accessed January 1, 2016. View in article
    67. Platform Thinking, “The Lepore-Christensen debate: A repeatable pattern for platforms and disruptive innovation,” http://platformed.info/lepore-christensen-disruptive-innovation-airbnb/, accessed December 17, 2015. View in article
    68. Colin Strong, “Airbnb and hotels: What to do about the sharing economy?,” Wired, November 2014, http://www.wired.com/insights/2014/11/hotels-sharing-economy/, accessed December 15, 2015. View in article
    69. Priceonomics, “Airbnb vs hotels: A price comparison,” http://priceonomics.com/hotels/, June 17, 2013. View in article
    70. Stern et al., Barclays. View in article
    71. Ibid. View in article
    72. Ibid. View in article
    73. Ibid. View in article
    74. Ibid. View in article
    75. Airbnb, “Business travel,” https://www.airbnb.com/business-travel, accessed December 2015. View in article
    76. Deloitte analysis. Data from the following sources: Marriott International, Statista Dossier, “Statista,” accessed December 2015; Hilton Worldwide, Statista Dossier, “Statista,” accessed December 2015; InterContinental Hotels Group, Statista Dossier, “Statista,” accessed December 2015; Marriott International, Inc., “Form 10Q,” September 2015; Hilton Worldwide, Inc., “Form 10Q,” September 2015; Owen Thomas, “Airbnb could soon do $1 billion a year in revenues,” Business Insider, January 24, 2013, http://www.businessinsider.com/airbnb-billion-revenues-2013-1, accessed December 15, 2015; Rafat Ali, “Airbnb’s revenues will cross half billion mark in 2015, analysts estimate,” March 25, 2015, http://skift.com/2015/03/25/airbnbs-revenues-will-cross-half-billion-mark-in-2015-analysts-estimate/, accessed December 8, 2015; Heather Somerville, “Exclusive: Airbnb to double bookings to 80 million this year-investors,” Reuters, September 28, 2015, http://www.reuters.com/article/us-airbnb-growth-idUSKCN0RS2QK20150928, accessed on December 12, 2015; Janet Snyder, In focus: Intercontinental Hotels Group, HVS, April 2014, http://www.hvs.com/jump/article/download.aspx?id=6865, accessed December 2015; Airbnb, “About us,” https://www.airbnb.com/about/about-us/, accessed December 7, 2015; “Airbnb will soon be booking more rooms than the world’s largest hotel chains,” Quartz, http://qz.com/329735/airbnb-will-soon-be-booking-more-rooms-than-the-worlds-largest-hotel-chains/; Carole Cadwalladr, “Airbnb: The travel revolution in our spare rooms,” Guardian, September 16, 2013, http://www.theguardian.com/travel/2013/sep/16/airbnb-travel-revolution, accessed December 15, 2015; Nina Mandell, “Airbnb doubled number of listings in 2012,” Fast Company, February 7, 2013, http://www.fastcompany.com/3005629/where-are-they-now/airbnb-doubled-number-listings-2012, accessed December 15, 2015; Statista, “Number of Hilton worldwide hotel rooms,” Statista, http://www.statista.com/statistics/247301/number-of-hilton-worldwide-hotel-rooms/, accessed December 2015. View in article
    77. Stern et al., Barclays. View in article
    78. VRBO, “Home,” http://www.vrbo.com/, accessed December 2015. VRBO is part of the HomeAway network. In total, the network has more than a million listings, although a listing may be duplicated across HomeAway, VRBO, and Airbnb. View in article
    79. Marlene Motyka and Suzanna Sanborn, “US solar power growth through 2040: exponential or inconsequential?” Deloitte Center for Energy Solutions, September 2015, http://www2.deloitte.com/us/en/pages/energy-and-resources/articles/us-solar-power-growth-through-2040.html View in article
    80. Jeff St. John, “Dueling charts of the day: Peaker plants vs. green power,” Greentech Media, January 17, 2014, http://www.greentechmedia.com/articles/read/dueling-charts-of-the-day-peaker-plants-vs.-green-power. View in article
    81. Greencharge networks, company website, “Solutions,” http://www.greencharge.net/, accessed 1/27/2016. View in article
    82. Gregory Aliff, “The new math: Solving the equation for disruption to the US electric power industry,” Deloitte Center for Energy Solutions, 2014, https://www2.deloitte.com/content/dam/Deloitte/us/Documents/energy-resources/us-energyandresources-the-new-math.pdf. View in article
    83. Chris Mooney, “Why Tesla’s announcement is such a big deal,” Washington Post, May 1, 2015, https://www.washingtonpost.com/news/energy-environment/wp/2015/04/30/why-teslas-announcement-could-be-such-a-big-deal/. View in article
    84. Solar Energy Industries Association, “Solar industry data: Q2 2015 solar market insight fact sheet,” http://www.seia.org/research-resources/solar-industry-data. View in article

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