Uberisation : quelques clés pour mieux comprendre

First published on IPdigIT.

Dans un article récent, le journal Le Monde explique comment Ben Becker et Elliot Glass, deux Américains actifs dans le monde de la publicité, ont habilement trompé leur monde en orchestrant une campagne de lancement pour une fausse application, prétendument destinée à devenir un Uber pour crottes de chien:

Pooper est l’une de ces start-up que nous connaissons bien, qui vous propose, moyennant modeste finance, de vous simplifier la vie. Design épuré et élégant, clip vidéo léché, présenté par un jeune archétype de l’entrepreneur branché (moins de 30 ans, lunettes et chemise à carreaux), le site Internet de Pooper (« poop » signifie « caca » en anglais) copie tous les codes des entreprises de l’économie collaborative, comme Airbnb ou Uber. Un seul détail devrait mettre la puce à l’oreille du lecteur averti : le logo, une petite crotte stylisée (blanche sur fond vert) avec un sourire en dessous.

pooper-logo

Au-delà du canular et du ‘happening’ artistique, Becker et Glass se sont livrés à une satire plutôt féroce d’une économie digitale peuplée de startups qui proposent des applications et des plateformes pour tout et, à leurs yeux, n’importe quoi. Newsweek utilise ces termes: “The target of Pooper’s satire is an innovation economy that prioritizes trivial “hacks” instead of addressing genuine societal ills.”

Qu’est-ce que l’uberisation?

Dans le monde francophone, on a créé le néologisme uberisation pour décrire ce phénomène. Comme le terme est récent, ses contours sont encore assez flous. Il est donc important de prendre un peu de recul pour tenter de répondre aux questions suivantes: Que faut-il exactement entendre par uberisation? Quels sont les facteurs qui favorisent ou freinent son développement? Quels en sont les impacts économiques pour le fonctionnement de l’économie?

C’est la mission que j’ai confiée à deux étudiants de la Louvain School of Management. Dans leur travail de fin d’études, intitulé “Uberisation : définition, impacts et perspectives” (que vous pouvez télécharger ici), Renan Lechien et Louis Tinel proposent d’abord leur propre définition de l’uberisation. Pour ce faire, ils ont compilé les éléments proposés par un large panel d’intervenants (consultants, acteurs de l’économie collaborative, scientifiques, journalistes, …), de manière à réunir différents points de vue. Selon eux,

L’uberisation d’une industrie peut être définie comme étant un phénomène présentant les deux caractéristiques suivantes : l’entrée d’une plateforme P2P [‘peer-to-peer’] dans une industrie existante, ainsi que le bouleversement des rapports de force entre les entreprises établies de cette industrie et la plateforme P2P. L’uberisation de l’économie correspond donc à l’émergence de ce phénomène dans de plus en plus de secteurs.

uberisation

Qui peut se faire ‘ubériser’?

En s’appuyant sur cette définition, les auteurs examinent ensuite les facteurs pouvant favoriser ou défavoriser l’uberisation. Il s’agit de répondre à la question suivante: pourquoi certains secteurs économiques sont-ils plus sujets que d’autres à l’uberisation? On peut mettre les facteurs suivants en évidence.

  • Le niveau de confiance que les ‘pairs’ doivent avoir les uns envers les autres pour qu’une transaction puisse se réaliser. Plus ce niveau est élevé, plus il sera couteux pour une plateforme virtuelle de mettre en place les mécanismes permettant de rassurer les parties prenantes quant à leur fiabilité respective (via des systèmes de réputation, de recommendation, etc).
  • La complexité des services échangés. L’uberisation repose sur des plateformes P2P, ce qui équivaut à dire que le service concerné doit pouvoir être offert par un large réservoir de ‘pairs’, c’est-à-dire des individus sans qualification particulière. La seule condition est que ces individus disposent de ressources inutilisées qu’ils sont prêts à mettre à disposition d’autres pairs (d’où l’idée d’une économie ‘collaborative’ ou ‘de partage’). Plus un service est complexe (ou plus il requiert de qualifications particulières), plus le nombre de ‘pairs’ pouvant l’offrir est réduit, ce qui met nécessairement à mal le modèle P2P.
  • Les caractéristiques des biens échangés. Selon leurs caractéristiques, certains biens seront plutôt échangés selon le schéma classique d’achat/vente, tandis que d’autres se prêteront à ces nouveaux modes d’échange basés sur le partage, le prêt ou la location. Ainsi, des biens que l’on utilise quasiment en permanence (des lunettes) ou que l’on peut devoir utiliser à n’importe quel moment (un générateur de secours) peuvent difficilement être prêtés ou partagés. A l’inverse, des biens relativement chers qu’on utilise peu souvent et de façon prévisible (une perceuse) peuvent, sans trop de dificulté, être mis à disposition d’autres utilisateurs quand on n’en a pas l’usage (pour autant, bien sûr, que les coûts de transport ne soient pas prohibitifs; pour plus de détails, voir Horton and Zeckhauser, 2016).

Sharing

Que faire si l’on est ‘uberisé’?

Dans la troisième partie de leur travail, Lechien et Tinel analysent les stratégies que peuvent déployer des entreprises installées quand elles se voient menacées par l’entrée de plateformes P2P. Les compagnies de taxi sont les premières à avoir été ‘uberisées’ (le terme prenant ici sa signification litérale); on pense aussi aux chaines hotelières et aux hotels indépendants qui doivent réagir face à l’entrée de Airbnb. Nous reprenons ici les recommandations que font Matzler, Veider et Kathan (2015) pour contrer l’entrée de plateformes P2P (ou en minimiser l’impact négatif) :

  • Vendre l’usage du produit plutôt que le produit lui-même (comme Daimler l’a fait avec son service de partage de voitures car2go);
  • Aider les clients à revendre leurs biens (à l’image de la plateforme de revente de meubles proposée par Ikea);
  • Exploiter les ressources et capacités inutilisées (par exemple, le partage de bureaux en collaborant avec une plateforme comme LiquidSpace);
  • Offrir un service de réparation et de maintenance (comme Best Buy l’a fait en rachetant Geek Squad, spécialisé dans la réparation d’ordinateurs);
  • Utiliser l’économie P2P pour cibler de nouveaux clients (à l’instar de Pepsi qui s’est allié avec la plateforme Task Rabbit pour lancer un nouveau soft drink);
  • Développer un nouveau modèle d’affaires via l’économie P2P (comme la plateforme Kuhleasing.ch créée par des fermiers suisses pour louer des vaches et des séjours à l’alpage, ou comme GM le fait via son acquisition de Sidecar).

Dans le reste de leur travail, Renan Lechien et Louis Tinel tentent de mesurer le pour et le contre de l’uberisation pour le fonctionnement de l’économie. Ils envisagent aussi les conséquences de l’uberisation pour la régulation. Ils terminent leur travail en appliquant leur analyse au cas de l’entrée d’Uber dans l’industrie du taxi.

Je vous invite vivement à consulter leur travail car il propose un cadre d’analyse pertinent pour comprendre les tenants et les aboutissants de l’uberisation. Un thème que nous ne manquerons pas de continuer à explorer sur IPdigIT!


Photo credit 1: eric.delcroix via VisualHunt / CC BY-NC-SA

Photo credit 2: Frits Ahlefeldt, Hiking.org via VisualHunt / CC BY-NC-ND

“Big Data in the Platform Economy” – A Digest of the Conference

On May 13, 2016, the editors of IPdigIT organized a one-day conference to study the growing importance of ‘Big data in the platform economy‘. To this end, they assembled a panel of experts from several disciplines: applied mathematics, engineering, economics, management, policy-making, and law. (You can find the general description of the conference here). The conference, held in the premises of the Microsoft Innovation Center in Brussels (whose efficient and kind support is gratefully acknowledged) was a real success, according to the feedback we received from numerous participants.

In this post, we give you a short summary of the various presentations made during the day; we also give you access to the speakers’ slides.

Session 1. Big data, engineers, and analysts

The aim of the first session was to address the following questions: What is Big Data? What are the data analytics tools? What are the risks?

1. Gautier Krings (Chief Scientist at Real Impact Analytics and invited lecturer at UCLouvain) described the multiple facets of big data, from the technical challenges to the practical applications (Slides).

2. Rudy Van Hoe (Solution Sales Manager at Microsoft) presented Microsoft’s advanced analytics solutions, and told us that even cows can generate useful big data once they are properly connected! (Slides)

3. Julien Hendrickx (Assistant Professor and chair of the Department of Mathematical Engineering at UCLouvain) explained that even ‘safe-looking’ datasets may lead to privacy risks when they are combined. (Slides)

Session 1 speakers

 

Session 2. Big data, economists, and managers

In this second session, the speakers addressed the following questions: How, and to what purpose, do organizations exploit big data?

4. Pierre-Nicolas Schwab (Big Data / CRM manager at RTBF, researcher at Solvay Business School, and the founder of IntoTheMinds) described the trends and challenges of the big data business, with a focus on marketing applications. You can view his Prezi presentation here.

5. Wouter Vergote (Associate Professor in Economics at University Saint-Louis, Brussels) explained how big data can facilitate differential pricing and examined the pros and cons for consumers. (Slides)

6. Adeline Decuyper (Post-doctoral fellow in Geography at CORE, UCLouvain) showed how mobile phone data can support development programs; for instance, mobile phone data can help improve food security in Africa. (Slides)

Session 2 speakers

Session 3. Big data and competition lawyers

We started the afternoon with a session examining the role for personal data and big data in the regulation by competition law.

7. Cyril Ritter (Lawyer for the European Commission’s DG Competition) discussed the implications of big data for competition policy. He argued that the issue is not so much about data per se but about how data is used.

8. Inge Graef (PhD fellow at CITIP, KULeuven) pursued on the topic of data and competition law. She examined whether a ‘market for data’ should be defined and, if yes, how. (Slides)

9. Alexandre de Streel (Professor of European law at the University of Namur, and director of CRIDS and CERRE) argued that competition policy must be a complement, not a substitute, for consumer and privacy protection. (Slides)

Session 3 speakers

Session 4 – Big data and regulators

The final session aimed to address the following question: Is there a need to adjust intellectual property and data protection rules in the era of big Data?

10. Benoît Michaux (Partner with Hoyng Rokh Monegier, associate professor of IP law at the University of Namur and a Cepani arbitrator for domain-name disputes) made the connection between big data and copyright and database protection, talking about the scope of and the exceptions to these rights.

11. Christian D’Cunha (Assistant to the EDPS, European Data Protection Supervisor) presented and discussed the EU General Data Protection Regulation. (Slides)

Session 4 speakers

 

Incumbents and the sharing economy: the example of GM

First published on IPdigIT.

© Deloitte, 2015: The sharing economy.

It is safe to say that the automotive industry experiences some turmoil; cars themselves, as well as the way we are using them, are changing profoundly. Traditional, petrol-powered, cars are slowly being replaced by electric cars and potentially fully autonomous vehicles. On the consumer level, a shift in consumption patterns, away from ownership to usage, challenges the traditional car ownership model. As such, over the past years, we have seen the rise of on-demand transportation and car-sharing services. For some, companies such as Uber or Zipcar are convenient ways to outsource driving and make owning a car in itself unnecessary. For others, it makes owning a car worthwhile as it allows them to provide their services to the sharing economy.

Confronted with such disruptive changes, incumbents in the automotive industry are faced with the question of how to respond. To shed some light on the issue, I will have a look at the strategy of General Motors (GM). Why GM? Turns out, January has been a busy month for the Detroit-based carmaker. GM not only acquired Sidecar and teamed up with Lyft, two providers of on-demand transportation services, but also launched Maven, its own car-sharing service.

Partnering with Lyft

© Lyft

On January 4th, GM announced its strategic alliance with Lyft, the San-Francisco based provider of on-demand transportation services. In the United States, Lyft is the second largest and fastest growing provider of on-demand transportation services and provides 7 million rides a month, across more than 190 cities (I discuss Lyft and competition in the ride-sharing/-hailing industry here on IPdigIT).

In practical terms, the alliance implies that GM will invest $500 million in the start-up and Daniel Ammann, GM’s president, will join Lyft’s board of directors. But there is more to it. Key elements of the alliance further include the joint development of a car rental model for drivers as well as a network of on-demand autonomous cars.

  • A car rental model for Lyft drivers. GM and Lyft will set up a series of short-term car rental hubs in various cities across the United States. More specifically, people who want to work for Lyft, but do not own a car, can pick up a vehicle at these hubs and GM will be the preferred provider. For Lyft, the deal increases its supply of drivers (depending on the rental price and Lyft’s ability to ensure that the cars are only used for its own service). For GM, it represents an opportunity to set a foot in the ride-sharing/-hailing economy. Here the threat of a demand cannibalization for GM should be minimal as the focal point of its traditional owner-driver type of business is not in urban centers.

“The biggest part of GM’s business will continue to be the owner-driver model where someone buys a car and owns it, use it when they need to, and park it when it’s not in use,” he [Daniel Ammann] says. That model still works well, especially in the suburbs, where the company still makes most of its money, according to Ammann. Elsewhere, he says, it’s a different story. (Davey Alba, WIRED)

  • A network of on-demand autonomous cars. Setting up a series of car rental hubs is only an intermediate step, the long-run goal of the alliance is a network of on-demand autonomous cars. Over the past decade, companies such as Google, Tesla or Uber – only to name a few – joined the race towards a driverless future. And GM is no exception. Since it started collaborating with Carnegie Mellon University back in 2007, the carmaker devoted enormous resources to developing autonomous vehicle technology. “Why partner at all?” or “Why not team-up with Uber instead?”, some may wonder. Indeed, Uber recently made headlines by poaching 40 researchers and scientists from Carnegie Mellon University and launching its new research center for autonomous cars in Pittsburgh. However, also when it comes to autonomous cars, Uber sticks to its do-it-yourself mentality. Notice also that the race is not necessarily won by putting an autonomous car on the market. It is equally about getting consumers into them.

The Lyft-GM deal differs in one crucial way from any other effort. More than just getting the self-driving car built, the two companies working together offers the clearest picture yet of how those cars might actually be used. (Davey Alba, WIRED)

Exploring new technology: Mobileye and OnStar

© General Motors

Just one day later, on January the 5th, GM announced its plans to explore a new technology from Mobileye to build maps that support fully autonomous driving. GM started collaborating with Mobileye, a technology company that develops advanced collision avoidance systems, about ten years ago and uses its software on its car cameras.

The plan is the following. Mobileye’s technology is able to “detect vehicles, pedestrians, and other obstacles, as well as road markings, signs, and traffic lights“. With the right data, it is thus able to build highly detailed and constantly updated maps that bring autonomous driving one step closer to reality.

This is where GM’s OnStar system comes into play. OnStar is a GM subsidiary that grew out of a collaboration between GM, Electronic Data Systems and Hughes Electronics Corporation in 1995 (joined by Verizon Wireless in 2011). It combines different safety, connectivity and navigation features such as various security and emergency services, Wi-Fi service or remote access. Most important, it enables GM to obtain the precise, real-time data that is crucial for building high-definition maps. To give you an idea of the current state of research, today’s GPS systems have a margin of error of about 10 meters. Mobileye expects to reduce this margin to about 10 centimeters.

Naturally, this plan hinges on collecting a sufficient amount of data, and by this on a widespread use of GM’s OnStar system. It is now clear that there are additional benefits to being the preferred provider for Lyft’s short-term rental hubs (GM announced that “Lyft drivers and customers will have access to GM’s […] OnStar services“).

Acquiring Sidecar assets

© Sidecar

On January 19th, it became public that GM had acquired Sidecar, another player in the on-demand transportation industry. Founded in 2012, Sidecar has been around since the early days of the industry and contributed substantially to its success. Nevertheless, with competition toughening, it was quickly left behind by its rivals. In early 2015, the start-up shifted its focus on the delivery business, however, despite its efforts, decided to shut down its operations in December 2015.

At first glance, the move might seem a little odd, especially given GM’s alliance with Lyft. Surely, the acquisition is rumored to have been a rather attractive deal for GM (with an alleged acquisition price less than the $39 million raised by Sidecar). Also, Sidecar’s Chief Technology Officer and Co-founder Jahan Khanna, as well as twenty other employees will join the carmaker. For GM, the decisive factor, however, is something else. Paul Sunil, Co-founder and CEO of Sidecar (not joining GM), explains that a key component of the agreement is a license to Sidecar patents, notably “the US Patent #6356838 for “System and method for determining an efficient transportation route”“. Maulin Shah, managing attorney at Envision IP, comments on the importance of the deal:

Sidecar’s patent appears to be highly fundamental to this industry, and Sidecar is the only company among the group that owns an issued patent. The patent has 95 forward citations from later-filed patent applications owned by Microsoft, Research in Motion, Cisco, IBM, Sprint, General Motors, Honda Motor Co., Mitsubishi, Tom Tom, and Navteq.

There are speculations about what GM might do (or be able to do) with the license. Generally, this depends on a couple of factors, among others, whether GM is the exclusive licensee of the patent. Fact is also that in the past Sidecar never went to court. This leaves the strength of the patent untested. In any case, GM most likely prefers knowing the patent in its own IP portfolio, than in the ones of its competitors.

Introducing Maven

© General Motors

The final puzzle piece is the launch of Maven, GM’s own Personal Mobility Brand. Official news of Maven broke on January 21st, however, GM registered the trademark back in November 2015. Maven essentially combines several of GM’s initiatives in the car-sharing market.

  • A car-sharing service in Ann Arbor, Michigan, that, for now, focuses on serving faculty and students at the university of Michigan (there are plans to expand the service to other cities in the United States within the year). Further plans include the launch of a car-sharing service for apartment-building residents in Chicago as well as the expansion of a similar, already existing, program in New York City.
  • Existing global initiatives such as peer-to-peer car-sharing in Germany via CarUnity (according to GM, roughly 10,000 users in Frankfurt and Berlin joined the marketplace since mid-2015).
  • Diverse programs on campuses in the United States, Europe and China to test and refine Maven’s future service offerings.

Julia Steyn, Vice President at GM, emphasizes that a key element of Maven is customization; “We believe it’s important in the car sharing experience for the passenger and customer to feel like it’s your own vehicle“.

Maven customers will experience seamless smartphone and keyless integration with the vehicle. Maven customers use its app to search for and reserve a vehicle by location or car type and unlock the vehicle with their smartphone. The app also enables remote functions such as starting, heating or cooling and more. Customers can bring their digital lives into the vehicle through Apple CarPlay, Android Auto, OnStar, SiriusXM radio and 4GLTE wireless. Each vehicle will provide an ownership-like experience with the convenience of car-sharing. (GM, Press release)

Customization and convenience, together with an hourly rate as low as $6 (that is including insurance and gas) and no subscription fee (a clear distinction from competing services such as Zipcar or Car2Go) may convince consumers to give Maven a try.

Note also that GM’s OnStar system is once again part of the offer. This relates to another point. In itself, Maven should yield only little financial incentives for GM (compared to its other areas of business). The move mainly makes sense in light of GM’s efforts for building a network of self-driving cars. With Maven, GM lays the foundation for its own network of autonomous cars, reducing its dependence from Lyft in the long run.

Oh sure, there’s money to be made in car-sharing, as ZipCar and others have shown. But it’s small potatoes for a company like GM. It isn’t until you take the long view that this move makes sense. Maven can be the foundation for the self-driving car network GM wants to build. (Alex Davies, WIRED)


What are your thoughts on GM’s strategy? Can you think of other examples of how incumbents start joining the sharing economy?


Taking on Uber

First published on IPdigIT.

Over the past six years, Uber has become a synonym for on-demand transportation services. The San-Francisco based start-up pioneered the industry and continues to hold the pole position in the American market. According to a recent article on Bloomberg, Uber currently seeks to raise $2.1 billion in a financing round that would value the company at $62.5 billion.

Uber is actively focusing on expanding its success beyond the United States. Here the company has an eye on the Asian market, notably on India and China. As such, Uber announced earlier this year that it plans to invest $1 billion each in the Chinese and Indian markets.

Nevertheless, there might be a few bumps ahead. As such, earlier this month, Lyft, Uber’s main competitor in the United States, together with Didi Kuaidi, Ola and GrabTaxi, the three largest on-demand transportation services in respectively China, India and South-East Asia, announced their global partnership. By this Lyft and Didi Kuaidi expand their previously formed alliance that was announced in September 2015. According to a press release, the four companies together “cover nearly all of Southeast Asia, India, China and the United States, reaching nearly 50 percent of the world’s population”.

Who are Uber, Lyft, Didi Kuaidi, Ola and GrabTaxi?

With an estimated market valuation of $50 billion, Uber is the leading on-demand transportation provider in the United States. Founded in 2009, the company currently serves more than 300 cities across 68 countries. On the Chinese market, it is active in approximately 20 cities and further reports that about 30% of its rides take place in the country. In India, Uber claims to hold a 40% share and to provide 200 thousand rides a day (see here and here).

Current_Lyft_logoFounded in 2012, Lyft is the second largest and fastest growing provider of on-demand transportation services in the United States. The company is valued at an estimated $2.6 billion and reportedly seeking to raise $500 million at a market valuation of $4 billion. According to this press release, Lyft provides 7 million rides a month across more than 190 cities.

267255LOGODidi Kuaidi grew out of a merger between Didi Dache and Juaidi Dache, China’s two largest on-demand transportation services, in February 2015. Didi Kuaidi invests heavily in expanding its services on the Chinese market and currently provides “7 million rides per day across 360 Chinese cities”. The merged entity holds an 83% market share in the Chinese private car-hailing market and has an estimated valuation of $15 billion. Earlier this year, the company invested $100 million in Lyft and participated in a $350 million and $500 million round of funding for respectively GrabTaxi and Ola (see this article by Johana Bhuiyan).

Ola_Cabs_logoOla acquired its second largest competitor, TaxiForSure, in March 2015. With a self-reported 80% market share the company is leading the Indian ridesharing market and reaches an estimated valuation of $2.5 billion. According to this press release, it currently serves 102 cities and receives more than one million booking requests per day.

GrabTaxi_LogoGrabTaxi is present in six South-East Asian countries (Indonesia, Malaysia, Philippines, Singapore, Vietnam and Thailand) where it provides up to 1.5 million rides a day. The company holds a 95% percent market share in the third-party taxi hailing market and is currently valued at an estimated $1.5 billion.

If you want to know more about the different providers of on-demand transportation services all around the world (and how they compare to Uber), have a look at the map below.

0908_uber-map2_2000

What’s in it for Lyft, Didi Kuaidi and its recent partners?

Cross-app service

One of the key aspects of the partnership is a cross-app service that will become available from 2016 onward. With this service clients of Lyft, Didi Kuaidi, Ola or GrabTaxi will be able to use their local apps when traveling to countries that are covered by the partnership (i.e., the United States, China, India and the six South-East Asian countries currently covered by GrabTaxi). For international clients, this cross-app service effectively eliminates any switching costs: they can continue to use their trusted local apps, in their language and currency. Take the case of Lyft users in the United States. When traveling to China (or any other country in the network) those users no longer have to switch to a local, i.e., Chinese, provider (and set-up and familiarize themselves with a new app, that may or may not be available in their language and/or currency). Instead they can continue to use their Lyft app to haul rides. In a nutshell, the cross-app service allows consumers to multi-home, i.e., to access the services of several (international) providers, at no cost.

Through this global partnership, […] international travelers can seamlessly access local on-demand rides by using the same application they use at home. Each company will handle mapping, routing and payments through a secure API, providing the best global experience for the millions of travelers that cross between the U.S., Southeast Asia, India and China every year. (PRNewswire)

Everything else being equal, the partnership thus increases the attractiveness of the apps offered by Lyft, Didi Kuaidi, Ola or GrabTaxi, relative to the ones by other (local) competitors that are not active in the countries covered by the partnership. As a corollary, the four companies may be able to attract new clients, especially among those that frequently travel between the countries in question.

This continuity in consumer experience that follows from the cross-app service has further implications. First, companies gain access to new international consumers, without having to adapt their offer (e.g., the language or interface of the app). This allows them to save resources by leveraging on the strength of their partners in their respective markets. Second, companies do not lose track of their clients when they travel to other countries. This gives companies access to new data and ultimately additional insights into consumer preferences. The increased information allows companies to increase the quality of their services and set themselves apart from their (local) competitors.

If you can’t beat them, join them

Uber and Co are two-sided platform businesses (more on this topic here on IPdigIT). As such, consumers are only one part of the equation. To grow successfully, it is equally important to attract a sufficient number of drivers for one’s service. And this is where Uber appears to be struggling. One of the main reasons seems to be that drivers do not sign exclusive contracts with transportation service providers and as such may be active on several platforms (nevertheless, at any given point in time, drivers obviously can only work for one provider). This brings with it that drivers are highly susceptible to financial incentives, such as subsidies or sign-up bonuses, and frequently switch between platforms. With a limited supply of (quality) drivers, it thus comes hardly as a surprise that continuously attracting drivers has become an expensive sport for Uber and its competitors.

The race for dominance in the Chinese transportation market is costing Didi Kuaidi and Uber, the two largest ride-hailing companies in the country, more than $1bn a year as they lavish money on incentives for drivers and passengers. (Leslie Hook and Charles Clover, Financial Times)

In that sense, the partnership is a smart move for its members. It allows them to gain a presence in international markets without having to fight incumbents. Notice that companies are taking active measures to increase driver loyalty (and the supply of drivers). For instance, Ola introduced a car leasing model and, more recently, a private loan program (similarly, Uber offers its Xchange leasing program). To be eligible for the loan program, drivers have to have been working for Ola for a minimum of six months and pay at least eight installments towards their car under the leasing model.

Another related advantage of the partnership, that is emphasized by its members, is its potential for sharing ideas and best practices, “from product innovations to driver support, technology developments, winning on the regulatory front, and approaches for managing local operations in a rapidly scaling organization” (Anthony Tan, CEO and co-founder of GrabTaxi). This point is of particular importance in the given context as the markets concerned are characterized by their distinct cultural norms, preferences, infrastructure and regulatory environments.

For Lyft, which is scrambling to catch up to Uber’s inexorable, global advance — and for Didi Kuaidi, Ola, or GrabTaxi, which are bracing themselves for it — allying with local players in international markets is a savvy move that will expand addressable market and the sharing of valuable competitive knowledge. (Johana Bhuiyan, BuzzFeed)

Finally, the partnership, at least in the short run, may relax competition between its members and allow them to focus on their own (local) markets, without having to fend off international competitors. Here I want to stress the “in the short run”. First, all partners show an interest in expanding their operations internationally. Second, I am wondering how sustainable the partnership is in the long run, particularly given the apparent difference between its members in terms of their current market positions and potential for (international) growth.

Entering international markets: to fight or not to fight?

Uber and Lyft are pursuing two very different expansion strategies. Whereas Uber is investing heavily in its own infrastructure in order to gain a foothold in international markets, Lyft is partnering up with incumbents. In a recent The New York Times article Farhad Manjoo reflects on both strategies and outlines two possible scenarios.

I can see the logic in this [the global partnership], and I even think there’s a pretty good chance it could work. Lots of American tech companies have tried to conquer China and India, and almost all have failed. Uber could squander lots of money trying. And maybe, just maybe, Lyft could emerge as a strong No. 2 here. In a market valued at hundreds of billions or possibly more than a trillion dollars, that’s not a bad play.

But it’s a very optimistic scenario. Here’s what could happen instead: Uber creates a near-monopoly in the United States, gets a foothold in other markets, and slowly expands that position to become dominant everywhere. So, sure, it’s risky and expensive, but if it works, there’s a big reward. And that gets to Uber’s big advantage: Operationally, so far, Uber has proved to be masterful. So while I think Lyft’s defense is smart, I would bet on Uber continuing to win.


I am interested in your opinion on this matter. In your eyes, does the alliance pose a threat to Uber’s expansion strategy in the Asian market or even its position on the American market? And what about other countries such as Latin America or Europe? Could Lyft adopt a similar strategy? And if so, would it be successful?


 

La e-réputation des entreprises: lente à construire, rapide à détruire?

First published on IPdigIT.

La réputation des entreprises est un actif incorporel important, quoiqu’invisible dans la comptabilité, ce serait même selon certains “l’actif stratégique le plus important sur le plan de la création de valeur. Elle procure à la firme un avantage compétitif unique qui lui permet de se différencier de ses concurrents.” (M. Graziani, La réputation de la grande entreprise est-elle un actif spécifique?, 2014). Aujourd’hui, la différentiation nécessaire dans la concurrence ne peut pas toujours s’appuyer sur la domination des coûts et la pratique de prix inférieurs, elle passe souvent par la différenciation des produits et services. A son tour, cette différenciation requiert de créer et entretenir une image de marque. L’image de marque se construit, elle ne se réduit bien entendu pas à la stratégie de dépôt et de préservation d’une marque. L’image de marque résulte de choix entourant le produit, que l’on va par exemple rapprocher du secteur du luxe, ce que pratique Apple, notamment avec son iWatch, pour justifier des prix élevés. Le produit ou service peut aussi être adoubé par des personnalités en vue qui ont leurs “followers”, notamment en ligne, ou supporté par une large communauté de fans, qui vont par exemple anticiper le lancement d’un nouveau modèle. Au-delà, la réputation est associée à l’entreprise elle-même. C’est pourquoi les entreprises vont s’efforcer d’apparaître comme des “citoyens responsables” et promouvoir des programmes en matière de responsabilité sociétale.

Les stratégies sont multiples, mais la réputation s’acquiert par une série d’actions et décisions qui s’inscrivent dans la durée. Peut-elle se perdre très rapidement, comme l’estime Warren Buffet?

Extrait de izquotes.com

La question peut se poser à l’heure où l’image de Volkswagen est sérieusement écornée suite au scandale des logiciels espions intégrés dans les moteurs diesel de nombreux modèles de la marque allemande.

L’immédiateté du scandale affecte en tout cas l’image en ligne de l’entreprise. Si l’on fait aujourd’hui une recherche sur ‘tromperie et diesel’, la sanction de la marque VW est claire:

Recherche sur Google le 25 sept. 2015

Recherche sur Google le 25 sept. 2015

Une marque aussi réputée que VW continuera très vraisemblablement à rayonner. La forte image construite au fil du temps est dans certains cas la meilleure ancre qui permette de résister à la tempête d’image. La crise sera sans doute plus durable dans le récent cas Volkswagen que dans le cas par exemple de Findus (2013). La société Findus s’était retrouvée au coeur du scandale de la viande de cheval insérée dans les lasagnes, mais c’était la société Spanghero qui avait substitué la viande de cheval à la viande de boeuf à l’insu de Findus. En revanche, Volswagen a sciemment intégré dans les véhicules un dispositif visant à contourner les normes de contrôle des émissions polluantes.

Dans certains cas, l’entreprise en situation de crise de réputation risque de prendre des décisions qui pourraient être contre-productives.

viande-de-cheval-findus-lasagne_1328647

Ainsi, Findus a essayé “de “nettoyer” le web (dont Wikipédia) pour faire disparaître les traces de “l’affaire Findus” en payant des sociétés spécialisées en e-réputation” mais la presse a mis en lumière cette tentative de réécrire l’histoire sur le web (La Tribune, 18 février 2013, cité dans l’article “Findus” sur Wikipedia). Pour redorer le blason de Findus, l’agence de e-réputation va tenter de supprimer les associations entre Findus et l’escroquerie à la viande de cheval. Demander à un moteur de recherche la suppression des liens n’est du reste pas possible car il n’existe pas de droit à l’oubli au profit des personnes morales. L’affaire Findus va aussi donner lieu à une série de détournements sur le web.

cheval-detournement-6_1500718Relayant ces bons mots sur le web, une agence de communication dénommée “Rosbeef” (ce n’est pas une blague! voir ici) a lancé, sans l’accord de Findus, une campagne qui utilisera des affiches reprenant la marque avec le slogan:

PUB-FINDUS-large

D’abord dérangée par cette initiative, Findus va, devant le bon accueil du web, changer d’avis et faire appel à l’agence pour poursuivre la campagne. La recherche de la e-réputation peut donc prendre des tours plutôt étonnants et tordus. A quoi s’attendre comme suite en ligne de l’affaire VW?

 

Les composantes de la réputation sont multiples. Pour étudier ces facettes, Anne Cantéro (consultante en droit des technologies) et moi-même avons mis sur pied, avec la collaboration de la Fédération des Entreprises de Belgique (FEB-VBO), un cycle de conférences consacrées à la e-réputation des entreprises.

La première séance (25 sept. 2015) comportait la présentation de Gabriel Goldberg (Semetis) sur les techniques d’optimisation de l’e-réputation que proposent les firmes spécialisées en référencement web ou SEO (Search Engine Optimization). Gauthier Broze (Thurso et Legally Brand) a montré quelles techniques utiliser pour faire du “power branding ” en ligne (et hors ligne). Le développement d’une communauté en ligne (en l’espèce la Thurso Nation) permettant aux fans de s’identifier à une tribu est une clé pour le démarrage d’une e-réputation positive. Stephanie Misotten (Solvay) a passé en revue les outils de veille et de contrôle juridique de la e-réputation.
Presentation by Gabriel Goldberg, Semetis
Legally Brand, Business by Power Branding. Case study: THURSO by Gauthier Broze
E-reputation, Solvay policy and strategy by Stephanie Missotten

Une seconde séance (23 octobre 2015) est consacrée à l’e-marketing, qui pose notamment des problèmes de vie privée.

Une troisième séance (27 novembre 2015) aborde les risques e-réputation liés aux relations de travail, en particulier l’usage des réseaux sociaux par les employés.

Pour le programme et les informations pratiques, voyez ici.

How do comparison shopping sites make a living? An update

First published on IPdigIT.

comparsion

Comparison shopping sites, also known as shopping robots or shopbots, have been around for about two decades. Sites such as Shopping.com, Shopper.com, PriceGrabber, Shopzilla, Vergelijk or Kelkoo help us find goods or services that are sold online by providing us with loads of information (products sold, price charged, quality, delivery and payment methods, etc.). As they present the information in an accessible way and display links to the vendors’ websites, shopbots significantly reduce our costs of searching for the best deal.

The most common business model for shopbots is to charge sellers for displaying their information while letting users access the site for free. Fees can be computed in different ways, as explained by Moraga and Wildenbeest (2011, p. 4):

Initially, most comparison sites charged firms a flat fee for the right to be listed. More recently, this fee usually takes the form of a cost-per-click and is paid every time a consumer is referred to the seller’s website from the comparison site. Most traditional shopbots, like for instance PriceGrabber.com, and Shopping.com operate in this way. Fees typically depend on product category—current rates at PriceGrabber range from $0.25 per click for clothing to $1.05 per click for plasma televisions. Alternatively, the fee can be based on the execution of a transaction. This is the case of Pricefight.com, which operates according to a cost-per-acquisition model. This model implies that sellers only pay a fee if a consumer buys the product. Other fees may exist for additional services. For example, sellers are often given the possibility to obtain priority positioning in the list after paying an extra fee.

How can such a business model be economically viable? To answer this question, we need to understand how shopbots create value for both retailers and consumers, so as to outperform their outside option, i.e., the possibility for them to find each other and conduct transactions outside the platform?

A quick journey through a number of landmark contributions to the theory of imperfect competition will help us understand the importance of price transparency and search costs. To use a simple setting, think of a number of firms offering exactly the same product, which they produce at exactly the same constant unit cost. They face a large number of consumers. If firms compete by setting the price of their product, Joseph Bertrand has shown in 1883 that the only reasonable prediction of this competition is that firms will set a price equal to the unit cost of production. This result is sometimes called the ‘Bertrand Paradox’ as the competitive price is reached although there may be no more than two firms in the industry.

One important assumption behind this result is that there is full transparency of prices: all consumers are able to observe the prices of all firms without incurring any cost. As the firms offer products that are exactly the same, consumers only care about the price and (absent capacity constraint), they all buy from the cheapest seller, which generates this cutthroat competition.

What happens if it is assumed instead that consumers face a positive search cost if they want to observe and compare prices? Peter Diamond (Nobel Prize in economics, 2010) show in his 1971 paper that the exact opposite result obtains: all firms will price at the monopoly level and no consumer will search. This result, known as the ‘Diamond Paradox’, holds even if consumers have infinitesimal search costs. Belleflamme and Peitz (2010, p. 164) explain the intuition:

In this equilibrium, consumers expect firms to set the monopoly price. A firm which deviates by setting a lower price certainly makes those consumers happier that learnt about it in the first place, but since the other consumers do not learn about it, this will not attract additional consumers. Given their beliefs, consumers have an incentive to abstain from costly search, so that a deviation by a firm is not rewarded by consumers.

The next question that naturally arises is what happens between the previous two extremes. What if consumers have different search costs. In their “bargains and ripoffs” paper of 1977, Steven Salop and Joseph Stiglitz (Nobel Prize in economics, 2001) suppose that there are two kinds of consumers: the “informed” consumers can observe all prices for free, whereas the “uninformed” consumers know nothing about the distribution of prices. Under this assumption, they show that spatial price dispersion can prevail at equilibrium: some stores sell at the competitive price (and attract informed consumers) while other stores sell at a higher price (selling only to uninformed consumers).

In his model of sales of 1980, Hal Varian (now chief economist at Google) establishes the possibility of temporal price dispersion. In his model, the equilibrium conduct for firms is to randomize over prices (to put it roughly, it is as if they were rolling a dice to determine which price to set). As a consequence, at any given period of time, firms set different prices for the same product; also, any given firm changes its prices from one period to the next. This is why price dispersion is said to be temporal.

comparison shopping

Let us now terminate our journey by introducing shopbots into the picture. In the previous models, firms didn’t have to incur any cost to convey price information to consumers. It was consumers who had to search for the information, with some consumers incurring a larger search cost than others for some unknown reason. By adding a new player to the model, namely a shopbot, Michael Baye and John Morgan propose, in their 2001 paper, a more realistic model where the above assumptions are relaxed. In their model, a profit-maximizing intermediary runs a shopbot that mediates the information acquisition and diffusion process. This intermediary can charge both sides of the market for its services; that is, firms may have to pay the intermediary to advertise their price and consumers may have to pay to gain access to the list of prices posted on the shopbot. After observing the fees set by the intermediary, sellers decide whether or not to post their price on the shopbot and if so, which price, while consumers decide whether or not to visit the shopbot and learn the prices (if any) that are posted there.

Baye and Morgan show that price dispersion persists in this environment. This is because the intermediary optimally chooses to make sellers pay for advertising their price on the shopbot, while letting all consumers access the shopbot for free. This means that all consumers are ‘fully informed’ in the sense that they buy from the cheapest firm on the shopbot. Despite this fact, firms earn positive profits at equilibrium (this is due to the fact that they post randomized prices on the shopbot, as was the case in Varian’s model of sales).

The predictions of this model square quite well with the business model that most shopbots have adopted and with the common observation that prices listed on shopbots are dispersed (even though the advertized products are very similar). So, the quick journey that we have made allows us, I believe, to understand better how shopbots can enter the market and survive in the long run.

Important remaining questions are whether shopbots increase the competitiveness of product markets and enhance market efficiency. In this regard, a recent contribution by David Ronayne suggests that “price comparison websites may do customers a disservice”. He explains the intuition in this blog post:

Price comparison websites impose two opposing forces on the markets in which they operate. On one hand, they increase competition between firms, which pushes prices down. But on the other, comparison websites make substantial profits, which they glean in a large part from fees charged to firms for referring customers to them. As explained on Money Supermarket’s website: “Our main income is derived from customers clicking through from results pages and buying a product.” In 2013, the company experienced turnover of £225m (up 10% on 2012), with post-tax profits standing at £35m (up 40% on 2012). This has a knock-on effect on firms. It adds to their costs and therefore affects their pricing decisions, so can lead to them upping their prices.

I would like you to do some research about the effects of price comparison websites on the well-being of consumers. You can also give your opinion referring to your own experience.

(This post updates a previous post published in March 2014.)

The multisidedness of crowdfunding platforms

First published on IPdigIT.

Source: triplepundit.com

Source: triplepundit.com

A number of posts on this blog have already dealt with multisided platforms (see here) and with crowdfunding (see here). My aim with this post is to link the two topics and show that crowdfunding platforms are a prime example of multisided platforms. Crowdfunding platforms (CFPs) facilitate the interaction between entrepreneurs trying to raise funds and consumers/investors willing to participate in the financing of new projects. Why can they be seen as multisided platforms? As Evans (2011) explains it, a business opportunity emerges for a multisided platform when three conditions are met:

  1. There are distinct groups of customers.
  2. A member of one group benefits from having his demand coordinated with one or more members of another group; in the jargon of the economics literature, it is said that each group exerts indirect, or cross-side, network effects on the other groups.
  3. An intermediary can facilitate that coordination more efficiently than bilateral relationships between the members of the groups.

As I now show, CFPs meet these three conditions.

1. Distinct groups of customers

CFPs link at least two distinct groups: entrepreneurs (fundraisers) on one side and contributors (funders) on the other side. Some platforms have brought an additional side on board, namely sophisticated investors (such as venture capitalists, business angels, and institutional investors). For instance, two Belgian platforms have chosen this route: MyMicroInvest allows projects to be funded by the crowd together with a professional venture capitalist; Angel.me has established a partnership with the bank Belfius. The objective is clear: the participation of sophisticated investors is meant to reassure individual contributors; because these investors have much larger capacities and experience to investigate the reliability and success probability of proposed projects, crowdfunders can infer useful information from the choices that these investors make. Note that the opposite may be true as well: sophisticated investors may use the “wisdom of the crowd” as an indicator of the potential success of a new product (something that they may have a hard time to evaluate otherwise). In the same vein, Indiegogo (a CFP popular with hardware projects) has added some celebrity investors (such as Virgin Group founder Sir Richard Branson, or Pay Pal Founder Max Levchin) to its $40 million round in new funds from investors.

2. Presence of externalities

Each group’s valuation of the platform depends on the participation of the other group(s). As far as contributors are concerned, there are two reasons for which they are likely to prefer platforms with a larger number of entrepreneurs: such platforms provide them with a wider set of campaigns that they can choose to support and, in the reward-based model, such platforms also increase the probability that contributors will obtain rewards that fit their tastes. Yet, another force may play in the opposite direction: the chances that any given campaign will be successful (i.e., will reach the required threshold) are inversely related to the number of campaigns that the platform hosts; for that reason, contributors may prefer platforms with a smaller number of entrepreneurs. We may conjecture that the former effects outweigh the latter (in particular if contributors can find some way to coordinate on projects that are more likely to be successful). It is thus reasonable to say that entrepreneurs exert positive indirect network effects on contributors. The same obviously applies in the opposite direction: contributors exert positive indirect network effects on entrepreneurs: entrepreneurs value platforms that are able to attract larger crowds of contributors as they increase their chances to raise the targeted funds; platforms that attract a larger number of contributors are also more interesting because they allow entrepreneurs to showcase their products and to “test the waters” on a larger scale. It is important to note that agents on both sides also care about what the members of their own group do; that is, within-side external effects are also present. Such effects are likely to be negative among entrepreneurs as they compete for the funds that the crowdfunders are willing to contribute: the more campaigns the platform hosts, the tougher the competition. In contrast, positive within-group effects exist among contributors: the project that a particular contributor has chosen to support is more likely to reach the required threshold the larger is the number of contributors who may choose to back this project too. All these effects are summarized in the next figure:

Externalities on a crowdfunding platform

Externalities on a crowdfunding platform

3. High transaction costs

As for the third condition, even though entrepreneurs may be able to connect with the crowd by their own means (here is an example), CFPs undoubtedly offer them both higher prospects of success and lower costs. In particular, CFPs are able to mitigate the problems raised by information asymmetries much more efficiently than any individual fundraiser could do on his/her own (on this topic, see Agrawal et al., 2013). In sum, it seems clear that CFPs belong to the broad class of multisided platforms. If you want to dig deeper, you may want to examine how CFPs differ from well-known multisided platforms such as dating sites, real-estate platforms, or videogame consoles.

Mind. your own. business school – a case study of a multi-sided platform

First published on IPdigIT. This blog post is based on the comments of Master students to an article posted by Paul Belleflamme on IPdigIT in April 2014.

source: mybs.eu

A large part of today’s most successful and fastest growing business ventures is in fact multi-sided. Meaning they enable and derive value from the interaction between at least two distinct groups of participants. The example of mind your own business school (MYBS) illustrates that business opportunities for such multi-sided platforms (MSPs) may also arise in the academic world. As the following quote explains, MYBS serves as a platform that assists future Master students in finding the perfect business school.

After several years of studying, you have a clear idea where your interests lie and what exactly is your cup of tea. Searching this preference in the extensive offer currently existing is like searching a needle in a haystack. We help you by adding specific and relevant search criteria and help you to easily access all the necessary information. (source: MYBS)

This post builds on the example of MYBS to illustrate the concept and challenges of MSPs.

To start with, we need to clarify why MYBS can be described as an MSP. MSPs are intermediaries, such as technologies, products or services, that connect two or more customer groups (Hagiu (2013)). Further, according to Evans (2011) (see also here), a business opportunity for an MSP may arise when three necessary conditions are met: (1) there are at least two distinct participant groups, (2) the platform features indirect, or cross-side, network effects and (3) there are potential efficiency gains from the intermediary role played by the platform. Let us now check whether those three conditions are met for MYBS.

Identifying the different participant groups of MYBS is not entirely straightforward. Clearly, one is readily identified; namely, the group of future Master students, who use MYBS in order to search and compare various Master programs. A second group is made up of the business schools, which offer the different Master programs featured on MYBS. Business schools are typically represented by at least one alumnus. Alumni may thus be seen as a third participant group. Next, there is the group of advertisers, or partners of MYBS. This, potentially fourth, group includes a small subset of the business schools as well as other companies (OTM foods, BeanZ, forGrass) or institutions such as student associations or Deloitte student academy. Finally, MYBS features the Financial Times ranking of Europe’s top 70 business schools. Ranking providers may therefore be a fifth participant group. Be it as it may, condition (1) is satisfied as MYBS connects at least two distinct participant groups: prospective Master students and business schools.

A key element of MSPs is the presence of indirect, or cross-side, network effects. Meaning the presence of participants on one side of the platform generates value for participants on other side(s). For MYBS this is clearly the case. To give an example, a larger number of participating business schools provides future students with information on a larger set of Master programs and by this may enable them to find a better match. In turn, a larger number of prospective Master students, who use MYBS, may increase a school’s chances of attracting the strongest, or most motivated, students.

Finally, interacting with participants from an other side of the platform is more efficient when done via the platform (compared to outside the platform). We will discuss this point in detail later on.

Despite the large number of successful multi-sided business ventures, managing a multi-sided platform is a complex task and, as Hagiu (2013) points out, successful MSPs are the exception rather than the rule. That is why, in the following I will address four fundamental challenges of MSPs and analyse how MYBS deals with them.

How many sides to bring on board?

A first and obvious question to ask when building an MSP business is how many sides to include. Advantages from bringing a further participant group on board may include stronger cross-side network effects, a larger scale of operation as well as an additional source of revenue. Nevertheless, increasing platform complexity may lead to potential conflicts of interest between the different sides and may significantly constrain the platform providers’ (future) strategy.

I discussed previously that MYBS brings between two and five different sides on board: future Master students, business schools and their representatives as well as advertisers and ranking providers. Let us now have a closer look at their relationship to one another.

  • As mentioned before, prospective students and business schools strongly benefit from the presence of one another. Moreover, prospective Master students most likely value the presence of alumni. Here a key challenge of MYBS is keeping the group of alumni motivated as the latter derive no direct benefit from their participation (although they may very well derive indirect benefits from guiding prospective students, representing their Alma Mater, and so on). In this context, MYBS could extend its offer by adding current Master students as contact persons or by including testimonials of current and/or former Master students.
  • The amount of advertising on MYBS is limited. What is more, it is informational and mainly provides more visibility to certain schools. By clicking on the logo of an advertising business school, one obtains an overview of its different Master programs; the logos from other MYBS partners are collected on a separate page. Regarding the question of whether or not to extend the amount of advertising, e.g. by adding further business schools, companies or other education providers (study abroad programs, language classes, etc.), MYBS faces a conflict. Naturally, more advertising partners imply larger advertising revenues. At the same time, however, an increased amount of advertisement may not be welcome by the prospective Master students (disturbance, lowers perceived quality of MYBS and the information provided on it) and/or the business schools (increased competition, advertisement not in line with reputation/image). MYBS carefully needs to balance this trade-off when deciding about its future (advertisement) strategy.

One side that so far is not featured on MYBS are companies in their role as the prospective students’ potential employers (unless the former opt for an academic career). Companies, which are for example partners of certain business schools or employ one or several of their alumni, may provide feedback on the Master programs offered by those schools. Such a service is very likely to be valued by the prospective Master students; nevertheless, a conflict of interest with the business schools is equally likely to arise. Business schools and companies, to a certain degree, compete with one another for prospective students. For instance, depending on the offer, students may decide to postpone their Master studies and first work for a couple of years. Also, a company may be put in an awkward situation if it employs alumni from different business schools.

Features and functionalities

MYBS’ main purpose is to enable students to search, select and compare different Master programs offered by highly reputed European business schools. As such it features a variety of search and comparison tools. Prospective students may search for Master programs via a geographical map, by viewing the top 20 Masters as ranked by the Financial Times, by discovering Master programs in a certain field of study or more structured by means of a search engine with different search criteria such as field of study, study fees or language and duration of the program. Alternatively, students may obtain an overview of the different programs offered by a specific business school by clicking on its logo (provided, of course, the business school opted for advertising on MYBS). For each specific Master program, MYBS then provides a summary sheet with the program’s most important characteristics (study fees, language and duration of the program, country), links to the business schools’ websites (application procedure, funding possibilities), an indicator of the associated living costs (provided by numbeo) as well as, in most cases, the possibility to contact one or more alumni. The last point has to be seen as the key feature of MYBS which sets it apart from competing platforms.

[…] we think it’s essential to not only be guided by cold numbers. The strength of our offer lies in our network. We try to have a contact person for all the masters. (source: MYBS)

For the group of prospective Master students, MYBS yields a significant reduction in search costs and further benefits from one-stop shopping as information from diverse sources is aggregated in one place. Moreover, as pointed out previously, for the majority of business schools MYBS provides the possibility of contacting one or several alumni. Finding such contact persons, who are further willing to share their experience, on one’s own should be rather difficult and time consuming. For the groups of business schools and advertisers, MYBS offers visibility and the possibility to promote their Master programs or other offers to a large and targeted audience. To summarise, there are clear benefits for all participants from interacting via MYBS.

Pricing structure

In theory, MSPs have access to multiple and diversified revenue sources as they include several distinct participant groups (Hagiu (2013)). In reality, however, most MSPs offer their services for free, or at a subsidised price, to at least one side of the platform and derive their profits from the remaining sides.

This is also what one can observe on MYBS. Prospective Master students are the participant group with the highest price sensitivity. Also, information aggregated on MYBS can be found for free elsewhere, although, undeniably, with some effort. As a result, students may access MYBS for free and represent therefore the subsidised side. Advertisers, i.e., business schools and other partners of MYBS, are the money side and pay a fee in order to have their logo featured on the website.

Rules and regulations

MYBS mainly creates value by aggregating information from diversified sources. Its main focus should thus be on ensuring that sufficient and high quality information is provided. To put it differently, as the quality of the information on MYBS is directly linked to the information provided by its participant groups, some type of entry regulation is necessary to ensure a certain quality standard of the platform. How does MYBS put this into practice?

  • First off, to be included on MYBS, a business school has to be featured in the Financial Times ranking of the top 70 European business schools. This focus on a restricted set of highly reputed business schools has several important implications. First, for MYBS it is easier to guarantee that the information provided on their website is accurate and up-to-date when the number of business schools is limited. Second, competition between business schools is restricted. However, it is at the same time restricted to some of the strongest schools. This may provide the featured institutions with additional incentive to provide current and accurate information on their respective websites. Third, MYBS may be particularly interesting for prospective Master students with a strong academic and professional background. The reason is that those students are more likely to fulfil the entry requirements of the featured business schools. Thus, the focus on a restricted set of highly reputed business schools may also feature a positive feedback effect for the group of business schools in terms of the quality, or motivation, of their applicants.
  • Regarding the group of prospective Master students, any prospective student, or more generally anybody, can browse MYBS. In order to contact an alumni or to keep track of one’s favourite Master programs, however, one is required to log in via facebook or linkedin. MYBS hence outsources any identity verification and relies on the controls of the two networking sites. For the prospective Master students this brings with it that there is limited anonymity when contacting an alumnus. The contact details or the identity of the alumnus in turn are not revealed (at least for the first contact) as an alumnus may only be contacted via MYBS.

Now that we have analysed the business strategy of MYBS, how well do you think it is adapted to its competitive environment? On a more general note, in your eyes, what are the prospects for MYBS? Do you have any suggestions in terms of its future strategy? In particular, should MYBS include employers as an additional side? What is more, should the platform expand its offer to non-European business schools, different degrees (Bachelor, PhD) or different fields of study? Or is its focus on a restricted set of reputed business schools and their Master programs its key asset?

A ‘multisourced’ case-study of a multisided platform

First published on IPdigIT.

MYBS

To paraphrase a famous Belgian surrealist artist: “This post is not a post“. More precisely, it is not a post yet, but it should become one once all your comments will be pieced together. My goal, in a very lazy educational way, is to build a case study of a specific multisided platform through crowdsourcing (which is, according to Wikipedia, “the practice of obtaining needed services, ideas, or content by soliciting contributions from a large group of people“).

crowdsourcing

Source: cooltownstudios.com

The platform that I would like you to study could be of some interest for you if you plan further studies. Its name is MYBS, which stands for Mind Your Own Business School. Its purpose is to help you “find your perfect business school among 1023 masters in 185 cities“.

Here is a list of questions that you can choose to address in your comment (depending on the available information).

  • Why can MYBS be described as a multisided platform (for a definition, see here)?
  • Which sides has MYBS brought on board?
  • Are there other sides that MYBS could bring on board?
  • If yes, what are the pros and cons of such strategy?
  • What is the price structure chosen by MYBS?
  • What are the main functionalities and features of the platform?
  • How do they facilitate the interaction among the members of the various sides?
  • What are the governance rules (regulating access and interactions) put in place by MYBS?
  • How do these rules affect the members of the various sides?
  • In your view, did MYBS choose its functionalities and rules in an optimal way?
  • Are there similar (online or offline) platforms competing with MYBS?
  • Do these competitors share the same business model as MYBS (in terms of number and identity of sides, price structure, features and functionalities, governance rules)?
  • What are the prospects for a platform such as MYBS?

As background readings, refer to the various posts on multisided platforms already published on this blog. Two other useful references are Hagiu (2014) and Eisenmann, Parker and Van Alstyne (2006).

What drives self-regulation in the nascent P2P “ride-sharing” industry?

First published on IPdigIT.

uber The American company Uber has been all over the news in Belgium over the last three weeks. Uber connects passengers with drivers of vehicles for ride-sharing services; it appears therefore as a typical two-sided platform. As Evans (2011) explains it, a business opportunity emerges for a two-sided (or multi-sided) platform when three conditions are met:

  1. There are distinct groups of customers.
  2. A member of one group benefits from having his demand coordinated with one or more members of another group (i.e., there are indirect, or cross-side, network effects).
  3. An intermediary can facilitate that coordination more efficiently than bilateral relationships between the members of the groups.

Uber meets the three conditions. First, the two groups are passengers and drivers. Second, indirect network effects are clearly present; as one can read on Uber website:

By seamlessly connecting riders to drivers through our apps, we make cities more accessible, opening up more possibilities for riders and more business for drivers.

Finally, drivers and passengers would have a hard time to find each other if they could not use the Uber app on their smartphone. Uber made the headlines in Belgium recently because it first launched its service (UberPOP) in Brussels, then was requested to stop this service by the Brussels authorities, and finally counterattacked by modifying its offering and by making it freely accessible for one week. To justify its decision, the Brussels government invoked the fact that Uber service is illegal because it violates several regulations (the drivers do not pass any exam, they do not follow the tariffs and vehicles do not exhibit the required marks). Brussels is by far not the only city in the world where Uber is in conflict with the regulators (Seattle just added its name to the list today); and the same goes for similar peer-to-peer transport platforms such as Lyft, Sidecar, or Turo. One can easily understand that taxi drivers feel threatened by these new business models, which make it possible for you and me to compete with them. It is thus logical that they lobby their local authorities to have these services shut down. One can also understand that regulators take sides with taxi drivers, not only because a taxi strike is a nuisance that any reasonable city council is glad to avoid, but more importantly because these platforms are relatively new and it is therefore not clear whether they correctly protect the interests of all the parties involved (passengers and drivers). In an excellent piece recently published in the Economix column of the New York Times, Arun Sundararajan explains that the current misalignment between newer peer-to-peer business models and older regulations is dangerous because it may impede economic growth.

This is unfortunate, because the emerging peer-to-peer, collaborative “sharing economy” will be a significant segment of the country’s future economic activity, stimulating new consumption, raising productivity and catalyzing individual innovation and entrepreneurship.

In the face of this “regulatory conundrum”, Arun Sundararajan recommends a combination of self-regulatory measures taken by the platforms themselves and some redesigned government oversight:

The solution is to delegate more regulatory responsibility to the marketplaces and platforms while preserving some government oversight, by creating new self-regulatory organizations like those that have succeeded in other markets and industries. (…) the government should recognize that the new peer-to-peer marketplaces have sophisticated controls naturally built in. (…) The platforms have voluntarily adopted additional nondigital safeguards. (…) Self-policing isn’t a universal panacea. We’ll still need government mandates to prevent effects like congestion, or for, say, providing accessible vehicles and ensuring disaster preparedness — things that markets don’t easily self-provide.

I fully subscribe to this view (and, apparently, so does the State of California as it is the first State that made peer-to-peer transport services legal under a dedicated regulatory framework). As noted above, Uber and the other peer-to-peer transport services are typical examples of two-sided platforms. I have already explained in a previous post that

On such platforms, intermediaries have to design various strategies to induce agents on both sides to participate. This might be tricky because of the “chicken-and-egg” problem that pesters all these platforms: to attract one group, you need to attract the other one, but were should you start?

A first role of these platforms as intermediaries is thus to act as platform operators by providing a platform where passengers and drivers are able to interact. Yet, a precondition for having both sides on board is that they can trust each other, which is far from obvious in the presence of asymmetric information. Hence, the intermediaries must also play the role of trusted third-parties; that is, Uber, Lyft, Sidecar and the likes must act as certification agents, mainly by revealing information about the drivers’ reliability or quality. They do so through reputation systems and active supplier screening; another cooperative initiative in this direction is the Peer-to-Peer Rideshare Insurance Coalition, which aims “to build a foundation of insurance best practices, policies and information for P2P Ridesharing.”

trust

Source: creatinemarketing.com

If they want to be considered as trusted intermediaries, platforms have to become bearers of reputation and effectively certify the quality and reliability of the drivers that they take on board. It is indeed in the platforms’ best interest to screen drivers carefully so as to keep only the high-quality ones. Why? Because a driver selected by the platform is believed to be of high quality by a passenger unless she previously experienced low quality of some other driver contacted through the platform. Hence, to avoid any stain on its reputation, the platform will directly discontinue the operation of low quality drivers. Understanding that, drivers do not find it profitable to provide a low quality service, implying that only high quality services are eventually provided on the platform. In a nutshell, the platform can be trusted simply because it suffices to have one rotten apple in the bag to spoil the rest of them in no time, something that a two-sided platform simply cannot afford. As many Internet-based platforms share this problem of establishing trust, I would like you to find and discuss some specific mechanisms that they put in place in order to achieve this goal.