First published on IPdigIT.

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.

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.)

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?

First published on IPdigIT.

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.”

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.