laptop retail oligopoly: the unnoticed digital...
TRANSCRIPT
Laptop retail oligopoly:the unnoticed digital divide
Table of Contents
1 Executive summary ..................................................................................................................................3
2 Introduction................................................................................................................................................4
3 A relevant product....................................................................................................................................6
4 Evidence of a market anomaly...............................................................................................................7
5 The legal framework in the European Union...........................................................................................8
5.1 Rationale..............................................................................................................................................85.2 Dominance..........................................................................................................................................85.3 Abuse..................................................................................................................................................105.4 Effects on trade between Member States......................................................................................105.5 Brief discussion....................................................................................................................................11
6 Laptop retail market mechanics............................................................................................................12
7 Product perception, coalition and game theory................................................................................13
8 A simple negotiation process model.....................................................................................................16
9 Results........................................................................................................................................................17
10 Conclusions............................................................................................................................................21
11 Acknowledgements..............................................................................................................................22
ESOP 2012 2/23
1 Executive summary
Competitive markets expose consumers to a great variety of products. That is a direct consequence of low entrance barriers, no collusion, refusal to deal or other anticompetitive behaviors, nearly perfect information and a low occurrence of market coupling phenomena. Through continuous interaction, the exposure to a very large number of consumers enables an efficient selection of the fittest products and makes for strong competition. We will argue that the laptop computer market is bound to a configuration which is not efficient, i.e, a configuration that bears no benefit for the consumer. Furthermore, we will show that such configuration prevents innovative products from having a proper market tryout.
This situation differs from what is found in startup markets like smartphone and tablet computers. While the smartphone market has recently overcome a “generation gap”1 which makes it, in practical terms, a new market, tablets were not even widely known before Apple launched the iPad. Computer tablets were available before but the real breakthrough came from the appearance of a different operating system.
The laptop computer market features a certain degree of similarity to highly static markets such as food or fuel distribution but its potential for innovation is much higher. However, that innovation can not materialize and reach consumers under the current conditions.
The blockade originates in the retail channel – the connection between producers and consumers – where the small number of dominant players exhibits nonefficient, arguably “nonrational”, behavior.
The roots of this behavior are best described by statistics. Whenever a given retail product is heavily established in the market, every forthcoming competitor faces a low – though not zero – acceptance probability. A high number of consumers would translate such probability into a small but measurable market share that in time could grow according to the product value. However, the connection between producers and consumers is often cut by the small number of existing retail chains, who translate any initial acceptance probability into zero. As a result, competing products are filtered preventing consumer awareness, as well as, any adjustments on demand levels.
These facts can be described in terms of a statistical model based on simple assumptions and directly applied to the laptop retail market. We will show how small numbers of retailers and the coupling between their decisions affect the probability of product placement. By coupling we mean the interdependence that governs individual retailer decisions and tends to push the market towards homogenization.
In face of these facts, we will state that from the standpoint of consumers and suppliers the behavior of a small number of dominant retail chains is not significantly different from that of a single retailer, even in the absence of explicit joint action.
The most straightforward interpretation of the existing legal framework does not consider this scenario anticompetitive. Explicit joint action (also know as collusion) and single player dominance are indeed more obvious causes of market problems . But we will suggest that the coupling between retailers must be seen as a continuum of different degrees that, with or without explicit agreements, causes markets to malfunction. We will also show that the behavior pattern emerging from small numbers calls for an adequate interpretation of dominance and essential facilities.
1 From slow, buggy and limited to the fast, solid and very flexible devices available today.
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2 Introduction
Competitive markets expose consumers to a great variety of products. That is a direct consequence of low entrance barriers, no collusion, refusal to deal or other anticompetitive behaviors, nearly perfect information and a low occurrence of market coupling phenomena. Through repeated interaction, the exposure to a very large number of consumers enables an efficient selection of the fittest products and makes for strong competition. Real markets are often far from ideal. Ranging from natural monopolies to markets that need oversight and regulation, they exhibit different levels of inefficiency.
The laptop computer market features a combination of intrinsic properties that make it unique:
1. bundling of software and hardware with sales heavily dominated by the hardware retail channel
2. connection between suppliers and consumers through an oligopoly of retailers
3. complex products, imperfect information
4. strong influence of the consumer market on the business market
Although there are other important issues, namely those related to consumer rights, we will focus on the problems arising from property 2 which, supported by 3, is the source of effective shielding of consumers from competitive and innovative products. A market configuration diagram can be seen in Fig 1:
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Fig 1: Market configuration
In face of any market configuration, one should ask a few questions to test its efficiency. One of the most important questions is: “are products that, if otherwise brought to consumers might prove successful, being kept out of the market?”
Certainly, if the answer is yes, the Law of Supply and Demand doesn't apply to the connection between producers and consumers. That is, supply responds positively to demand except when set to zero by the middlemen. Whenever this is the case, the market has a problem.
That problem is indeed caused by the middlemen, due to their small number, but greatly reinforced by imperfect knowledge on the consumer side. The retailer behavior is rigid and the consumer, even if unsatisfied with the existing products, is incapable of demanding change. Together with a certain degree of cross retailer dependence the result emerges as an insurmountable barrier for potentially successful products, including locally developed ones.
How all this works together will be explained in detail throughout this document. Sections 3 and 4 provide details on a specific product and its relation to the market. Section 5 reviews the competition Law in the European Union. Sections 69 derive a statistical model for a generic retail market and describe the results for this specific case.
It should be noted that this article does not intend to criticize the role of retailers. Retail is a necessity and, if working properly, an advantage to consumers. Fig 2 illustrates the role of retailers on the commoditization of laptop computers. As can be seen on Fig 2, it is not impossible to place consumer products in specialized channels, but critical mass (which is needed for scale gains) and even access to the price sensitive segment of the market is totally dependent on retail. If it doesn't work efficiently products are in practice blocked, except from a restricted niche of adopters which is not large enough to stimulate competition.
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Fig 2: The commoditization Scurve (taken from reference [23], inclusion and adaptation authorized by Rob Bearden)
3 A relevant product
The most wellknown Open Source operating system, Linux, is a natural candidate for integration on a laptop computer. Its high reliability, combined with a very low priceperunit, is in itself a reasonable justification for this statement. In fact, Linux comprises not only a modern operating system interface, but also a very mature set of applications capable of delivering stability and performance on many different scenarios [1][2][3][4]. Ubuntu Linux was described by PC World as “an easytouse Linux operating system that just works" [5]. It is also being deployed in large scale projects worldwide [6].
We should add another fact: the world wide Linux desktop market share, which includes both desktops and laptops, is nearly 1.5%, even though it is very impractical, if not impossible, to buy it preinstalled owing to the aforementioned properties 1 and 2. It was, however, tested on the Portuguese market via e.iniciativas, a Government project for the distribution of laptops to students, teachers and other citizens under state sponsored training. The project delivered around 600 000 computers from 5 manufacturers, via 4 network operators who agreed to handle the logistics while supplying 3g Internet connections. Only one laptop model, made available by a single operator, had Linux preinstalled. This somewhat low profile presence of Linux was an imposition from the Portuguese Government. Given the much lower price per unit of the software, the aforementioned model had better hardware than its competitors. Even though the computer was supplied by a local, relatively unknown assembler and the software was not, and still isn't, mainstream, the final market share of the Linuxbased solution on the project was 10%. It is reasonable to think that having a similar option on additional models might have resulted in a larger share.
This remarkable achievement provides strong empirical evidence of the relevance of Linux on laptop computers. We should also like to add the results of an economic impact study that objectively deems this product viable for the entire supply chain, up to the consumer. In fact, due to the difference in software costs, there may be as much as 70 EUR per unit for a mixture of customer savings, retail margin improvement and hardware upgrade. A healthier market would, therefore, have a positive impact on the local IT economy2 [7].
2 Undoubtfully. there are post market placement challenges to be dealt with, including support, network effects and communication issues. Those must not be overlooked if product vendors want to succeed. This document, however, is about the pre market placement difficulties whose root cause is often misunderstood. Details on post market issues are explored here: http://carlodaffara.conecta.it/fromtheorytopracticethehobbystdesktoplinuxexperiment .
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4 Evidence of a market anomaly
The assembler who supplied the successful local product for e.iniciativas has meanwhile been unable to place that product in any of the major local retailers, who claim that “consumers are not interested”. Furthermore, a visit to any of those retailers will show that almost every available laptop has a Microsoft operating system, whereas only one of them sells a few Apple products (which, nevertheless, are not their direct competitors because they belong to a different price range).
Thus, a wellperforming product for which there is both demand and adequate supply remains unavailable. While this affects millions of consumers, the decisionmaking process lies in the hands of a very small number of market players.
This kind “group boycott” is not necessarily intentional. In the following sections, we will show that there are different degrees of coupling between players within an oligopoly. We will also show that an apparent boycott is sometimes an intrinsic, undesired property of small numbers.
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5 The legal framework in the European Union
5.1 Rationale
In any wellfunctioning market economy, companies are encouraged to compete and develop the necessary efforts to be champions in their relevant markets, thus obtaining market power[8]. In a competitive market, the major incentive for economic operators is often considered to be profitability.
Art. 102 of TFEU – the Treaty on the Functioning of the European Union – takes this into account and forbids neither the mere existence of a dominant position, nor the creation or strengthening of that very position[9]. This provision targets the abusive exploitation of a dominant position, not dominance per se.
Together with Art. 101, Art. 102 pursues one of the key goals of the EU Competition policy established in Art. 3(1)(b) of TFEU: the establishment of the competition rules necessary for the functioning of the internal market.
It does so by regulating companies who hold positions of dominant market power, such as monopolies or near monopolies. It also regulates two or more companies acting jointly and achieving collective dominance. Its aim is not merely the prohibition of abusive pricing or output limitations, both traditional monopolist methods, it also deals with the use of market power to damage effective competition by preventing access to markets or driving out the existing competition.
The general framework contained in Art. 102 provides that:
Any abuse by one or more undertakings of a dominant position within the internal market or in a substantial part of it shall be prohibited as incompatible with the internal market insofar as it may affect trade between Member States.
It then goes on to present a nonexhaustive list of four examples of abuse.
So, according to Art. 102, three cumulative elements determine whether a given behavior falls into the scope of this article:
• a company (or companies in joint action) must be dominant;
• the dominant position of that company (or collective dominance of a group of companies) is expressed through an abusive conduct;
• trade between MemberStates is affected by that abuse.
In the following sections, any references to the dominance of a single company may be generalized to the collective dominance of a group of companies in joint action.
5.2 Dominance
The determination of the relevant market
Before dwelling upon the matter of dominance in a particular market, one should define the relevant market, both in terms of its cluster of products and geographical reach.
This exercise starts by examining the product, whether goods or services, from the company alleged to have committed abuse, and investigating whether other products are interchangeable or substitutible by that product. Close enough substitutes can act as competitive restraints and influence the capacity of a company to price freely[10].
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The European Commission's Notice on the Definition of the Relevant Market[11] states that it uses an economic approach to define the relevant market. Paragraph 7 states that
a relevant product market comprises all those products and/or services which are regarded as interchangeable or substitutable by the consumer, by reason of the products' characteristics, their price and their intended use.
When determining the relevant market, the geographic market also has to be considered. Paragraph 8 of the Commission Notice defines it in the following manner:
"The relevant geographic market comprises the area in which the undertakings concerned are involved in the supply and demand of products or services, in which the conditions of competition are sufficiently homogeneous and which can be distinguished from neighboring areas because the conditions of competition are appreciably different in those areas".
The investigation of the geographic market is similar to that of the product market. The question is this: in the presence of a hypothetical, small, but permanent increase in price, will consumers find alternative products in other geographic areas? If the answer is yes, there is a very good chance that the areas in question are part of the same geographic market.
Determining dominance
Once the relevant market is identified, it can serve as the basis to calculate the market share and degree of dominance of the company alleged to have committed an abuse. These calculations are made by analyzing the market share of the company in question, as well a number of other important elements.
The wording of TFEU fails to provide a clear definition of dominance. It was up to the Commission and the ECJ to provide guidance concerning the interpretation of this concept. In United Brands, the Court defined dominant position as
the position of economic strength enjoyed by an undertaking which enables it to prevent effective competition being maintained on the relevant market by affording it the power to behave to an appreciable extent independently of its competitors, customers and ultimately of its consumers.[12]
It defined the concept with further precision in HoffmanLa Roche, adding that
such a position does not preclude some competition which it does where there is a monopoly or quasi-monopoly but enables the undertaking which profits by it, if not to determine, at least to have an appreciable influence on the conditions under which that competition will develop[13].
Bearing these considerations in mind, the starting point to establish dominance is the estimation of the market share of the product. Even though they only create a presumption of market power, it is common understanding that large market shares are, indeed, a strong indicator of dominance.
Other factors are also considered, namely access to capital, the existence of economies of scale, vertical integration, product differentiation, opportunity costs, the degree of interdependence between undertakings, the conduct of firms, overall size and strength, as well as the existence of IPRs[14].
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5.3 Abuse
Determination of Abuse
Once a company achieves a position of dominance, it has a special responsibility not to allow its conduct to impair genuine undistorted competition on the common market[15]. Any literal reading of the abuses listed in Art. 102 of TFEU suggests that these responsibilities consist firstly in a duty not to unduly exploit its customers (and consumers in general) by pursuing a high price policy or contract on unreasonable terms.
In HoffmanLa Roche, the ECJ defines abuse as
an objective concept relating to the behavior of an undertaking in a dominant position which is such as to influence the structure of the market where, as the result of the very presence of the undertaking in question, the degree of competition is weakened and which, through recourse to methods different from those which condition normal competition in products and services on the basis of the transactions of commercial operators, has the effect of hindering the maintenance of the degree of competition still existing in the market or the growth of that competition[16].
From this interpretation of Art. 102 of TFEU and the concept of abuse, one can say that this notion is twofold: it not only includes exploitative abuses, but also exclusionary ones. On the one hand, exploitative abuses harm consumers and customers directly through the exertion of the company's economic strength. On the other hand, exclusionary abuses have their effects "primarily on the structure of the market [...] by weakening competitors through raising their costs, refusing to deal with them or denying access to essential facilities"[17]. In other words, exclusionary abuses weaken actual or potential competition with anticompetitive performances (e.g. predatory pricing, fidelity inducing abuses and refusal to supply).
Essential Facilities Doctrine
The denial of access to essential facilities is an exclusionary abuse. A refusal to grant access to an essential facility may be a breach of competition rules.
The first time the Commission uses the expression "essential facility" was in its Sealink/B&I Holyhead decision, in 1992. In the mentioned decision, the Commission identified this principle in the following terms:
An undertaking which occupies a dominant position in the provision of an essential facility and itself uses that facility (i.e. a facility or infrastructure, without access to which competitors cannot provide services to their customers), and which refuses other companies access to that facility without objective justification or grants access to competitors only on terms less favourable than those which it gives its own services, infringes Article 82 [Art. 102 TFEU] if the other conditions of Article 82 [Art. 102 TFEU] are met [18].
This doctrine is adopted by the ECJ in the Bronner case[19], but within strict limits. According the Court's ruling, this doctrine is only appropriate whenever a dominant company's monopoly over a product or facility leads to a permanent exclusion of competition in a related market.
5.4 Effects on trade between Member States
The classic assertion on how abuse may be considered to affect trade between Member States was issued in Commercial Solvents. The ECJ held that this condition was to be interpreted and applied in the light of Art. 3(1)(b), which states that competition in the Internal Market is not to be distorted. The Court said that
When an undertaking in a dominant position within the Common Market exploits its position in such a way that a competitor in the Common Market is likely to be eliminated, it does not matter whether the conduct relates to the latter’s exports or its trade within the Common Market, once it has been established that the elimination will have repercussion on the competitive structure within the Common Market [20].
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5.5 Brief discussion
It is clear that, due to their relevance in the laptop sales [7], retailers form an essential facility for this market (see section 5.3). But it is unproven that such facility is abused by dominant suppliers to distort competition. Until otherwise proven, any detected malfunction must be regarded as a market imperfection. In this case, the set of undertakings that form the essential facility doesn't work efficiently. But the way essential facilities are described in Law seems to focus on situations where a market player owns an infrastructure that is needed by its competitors, which essentially means market control in the hands of a single entity. Obviously, there are ways for an essential facility to malfunction other than being directly owned by a market participant. We could describe this as a problem of crosstier dominance: there is no single player dominating the market but there is a strong imbalance between production and distribution, due to excessive power concentration in the distribution tier.
Another difficulty of applying the existing framework to retail market oligopolies is centered around the concept of joint action (section 5.1). Beyond the obvious scenario of explicit joint action, where competing companies sit around a table to take decisions that harms consumers, there are more subtle ways of decreasing competition. In the case of retail markets implicit joint action may be a consequence of reciprocal monitoring by the market players. There may also be a common bias between players as a consequence of a shared culture in a small group. A given distortion of competition may possibly be the consequence of different types of “joint action”.
How regulators interpret “joint action”, “dominance” and “essential facilities” is critical to whether or not the current legal framework is applicable to existing retail markets of predictable and verifiable malfunction. Analyzing in detail the root causes of such malfunction is the purpose of the following sections.
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6 Laptop retail market mechanics
Despite the limitations on the existing legal framework, the depicted market configuration is recognizably pathological. In order to fully understand that, we need to examine the logic behind purchase decisions. The key concept is the perceived advantage of each product and related services.
When consumers choose to buy a certain laptop, they act upon a number of different decisions. They have to decide when to buy, how much to spend, favorite brands/models and preferred retail store3. This means that any service provided by the retailer is an important factor for the purchase. The individual advantages of each store are perceived in many different and complex ways. Marketing strategies, brand alliances, product campaigns and customer support contribute to create a final image in the minds of consumers where a specific brand and its products are related to different features.
However, in the case of large retailers, certain features of the provided service are not determinant. Customer support, return policies, safety requirements, taxes and consumer rights in general are tightly regulated and leave no room for diversified strategies. The difficulties of micromanagement prevent large retailers from giving individual attention to customers. As a consequence, the added value of the service provided by large retailers is often uniform across different chains and not directly used as a marketing factor. In these cases, retailers depend heavily on cobranding. The perceived advantages of a product are related to the purchase decision and thus to its purchase probability. Under cobranding this probability both depends on and influences the retailers' image and their marketing strategies.
It's reasonable to think that technical specifications should play a key role in the purchasing process, since laptop computers are technical items. However on large retailers, there is a very high level of uniformity across specifications as well: there is only one available operating system and for each price class the hardware features are very similar.
In fact, from a retailer's point of view, the marketing power of a given product supplier can prove more important than the technical specifications of a given product, thus exerting significant influence on the available options. In the end, the retailer's brand is at stake and depends critically on the image of the supplier brands sold by that chain. This can lead to markets that are mainly driven by branding strategies instead of product merit, at the expense of a large share of consumers who would welcome the best products on objective grounds such as price/quality and technical specifications.
Moreover, in a market configuration where cobranding between retail brands and product brands is the determinant factor, the placement of a new product by a single retailer is more likely to be perceived as a risk than as an opportunity. This may betrue even if the product has obvious advantages. In fact, the opportunity for differentiation through the careful choice of the best set of products including products from new brands is undervalued in this market configuration.
That can, in certain cases, induce retailers to behave approximately like a single uniform distribution channel instead of a competitive market with a focus on providing the best products to the final consumers. This coalitionlike behavior will be described in the next section.
3 This is described in detail by standard consumer behavior models.
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7 Product perception, coalition and game theory
With resort to game theory analysis, let us consider the decision matrix connecting retailer R and supplier S while negotiating the introduction of a new product in the retail channel.
Retailer R has a decision to make regarding the product supplied by S and considers three possible outcomes:
1. accepts to resell the product in its retail chain if exclusivity is granted
2. accepts to resell the product nonexclusively
3. does not accept to resell the product.
Supplier S must also consider three possible outcomes:
1. supplies the product exclusively through retail chain R
2. supplies the product nonexclusively through retail chain R
3. does not supply the product through retail chain R
A decision matrix that combines the various possibilities, as used in game theory [21], can be seen in Fig 3.
* while possible, this outcome represents a “breach of contract” by S.
This matrix displays the evaluation of possible outcomes from a retailer's point of view, where X ij is the score for each situation. As can been seen by examining the combinations of the outcomes listed above, the highlighted 2x2 submatrix represents the situations where an agreement is reached.
Competition between retailers to resell the product supplied by S occurs whenever the advantages of reselling exclusively are seen as greater than those of selling nonexclusively and than those of not reselling at all, i.e, X11 > X12 > X33. This leads to a high probability of acceptance on a series of independent decisions by different retailers.
On the other hand, whenever the market mindset is such that X12 > X11, the retailer will have an incentive to negotiate in ways that push him towards coalition, with possible disadvantages for the consumers. But the higher value of X12 may be unrelated to an objective evaluation of the product and its potential success among consumers. It may be, instead, a question of retailer perception. We will argue that this situation occurs in the laptop retail market and analyze it in more detail.
In this situation, what in fact happens is that throughout negotiations S must face a barrier that
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Fig 3: Product acceptance decision matrix
R outcome 1 R outcome 2 R outcome 3
S outcome 1 X11 X12
S outcome 2 X21* X22
S outcome 3 X33
inhibits the acceptance of products independent of their merit. This barrier is only lowered once the first retail chain accepts to resell. Only then will other retailers perceive it as more advantageous to resell the product supplied by S than to risk having to tell their customers they don't have it.
During the negotiations, the product acceptance hypothesis is given two different assessments. Before the first retailer accepts to resell, the probability of success is p. Once the first retailer accepts to resell, a new probability of success (p') is defined for subsequent negotiations. This means the perceived value of the product varies as a function of the coupling between retailer decisions, which we will call the coalition factor, c.
In any case, whenever X12 > X11 we will have p < p', i.e., the probability of a successful negotiation between supplier S and retailer R is higher if R knows that S is selling the product through other retailers.
By plotting the probability of success in negotiations between S and R for the same product as a function of increased coalition between retailers, one can clearly acknowledge how the barrier S faces affects negotiations.
We adopted linear functions to model the dependence of probabilities on the coalition factor, as can be seen in Fig 4. While different functions can certainly be applied, we will stick to this choice as it is the simplest assumption illustrating the interdependence between retailer decisions.
That dependence can be expressed as
p '=p01− p0cp= p0−p0 c
(1)
In the case of a market where perfect coalition occurs, p' will be equal to 1. That means that after the first retailer accepts to resell the product, all other retailers follow the same decision and the market behaves exactly as if only one retail chain controlled 100% of market share. In a more realistic situation, if c is near 1 retailers will be practically acting as single chain and negotiations for new products or brands would need to be conducted jointly and simultaneously between all interested parties. On the other hand, the absence of any coupling between retailer decisions
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Fig 4: Market barrier as a function of coalition
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
p'p
no coalition increased coalition
pro
babi
lity
of s
ucc
ess
negotiaton barrier for new products
(c=0) implies that the probability of acceptance (p0) is constant throughout any series of negotiations. In between, there is room for different situations, as will be described in the following sections.
It should be noted that the depicted dependence between retailer decisions is not necessarily a form of collusion or market manipulation. The simple fact that each retailer is able to monitor the products offered by all the others, as long as “all” is a small number, is a trivial dependence enabler. The existence of a nonzero coalition factor is a natural market property and does not in itself imply any kind of intentionally harmful behavior.
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8 A simple negotiation process model
Using the barrier model shown above, one can estimate the probability the product supplied by S has of entering the market. The expected share of retailers that will be persuaded to resell throughout the negotiations can also be estimated.
In order to obtain these estimates, one has to make some assumptions regarding the negotiation process. For a market of N retailers we will assume the following:
1. Supplier S negotiates with all retailers only once if the product is not accepted. This series of negotiations can be modeled as a set of N Bernoulli trials of probability p.
2. Each retailer has no information about the negotiations with other retailers.
3. If the product is accepted at a certain stage in the negotiation trials, S will negotiate again with all the remaining retailers using the previous success as a new negotiation factor. This can be modeled as set of N1 Bernoulli trials, now of probability p'.
4. All retailers perceive the product with equal value. The probability of success in each negotiation assumes only two different values: p if the product has not yet entered the market and p' otherwise.
5. The probabilities p and p' agree with the barrier model shown in Fig 4 and depend on a coalition factor c which can vary from 0 to 1
6. The coalition factor does not change with N4
Under these assumptions, we find the random variable that measures the number of successful negotiations, Xs , to be described by the following distribution:
P X s=k =1− pN k=0
[1−1− pN ]N−1k−1 p ' k−1
1− p ' N−k 0k≤N (2)
This is a modified Binomial distribution which we will call the Retail Filter distribution, or simply RF distribution. For more details please refer to Annex A. The expected value of (2) is given by:
< X s>=[1−1−p N][1N−1 p ' ] (3)
By combining (1) with (2) and (3) both the probability of a given product entering the market and the expected number of persuaded retailers can be easily calculated.
In the present analysis, the product in question faces both an oligopoly of retailers and a very high dominance of a competing product. Thus, we must be conservative in estimating the probability of acceptance p0 which is the basis of our numeric results. For consumers, the probability of acceptance was measured at around 0.1 (10% market share in the project mentioned in section 3) but that doesn't imply the value for retailers is the same. The likelihood of acceptance by retailers could be lower if their stance is more conservative or higher otherwise. It is tempting to picture retailers as more conservative than consumers due to the cobranding constraints mentioned in section 5. Since it wouldn't be easy to agree on a value from theoretical arguments and there aren't enough retailers to form a reasonable sample, we will assume 0.1 is an adequate value to start with. In fact, it will be clear that small changes in p0 do not affect the nature of the results. We will see that even an optimistic retailer value of 0.1 is not enough for this market to work properly.
4 It is natural to think that for large numbers of N mutual retailer monitoring becomes harder, which consequently reduces mutual dependence. Since we are mostly focused on small numbers of N, that refinement is not included in the model.
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9 Results
Bearing in mind what was shown in the previous section, we can easily calculate the probability of product placement from the first branch of expression (2). Since that branch measures the probability of nonplacement, the calculation is trivial. For instance, in a market of 4 retailers with an intermediate coalition factor of 0.5, the probability of product placement is 0.19.
The plot in Fig 5 shows the probability of placement as a function of the coalition factor c for different numbers of retailers. It becomes clear that the probability of placement decreases sharply with c and that for any value of c it increases with the number of retailers. Fig 5 also depicts the current threshold for legal action under the framework discussed in section 5. In the absence of proven cartel, legal action can occur if there is a single controlling player5. In that case, for the present market situation, the probability of placement that triggers legal action is 0.1. The dashed line is slightly displaced up for readability.
In Fig 6 we can see how the probability of product placement varies as a function of the number of retailers for different values of c. It is clear from Fig 6 that the probability of product placement increases sharply as a function of N for small values of the coalition factor. However, as c becomes larger the increase becomes much slower. For the limiting case c=1 there is no increase, as could already be seen on the previous plot. Thus, the stronger the coupling between retailer decisions occurs, the more retailers are needed for successful product placement.
The previous results describe the likelihood of having a product available in at least one supply chain. However, it is also of great importance to estimate how far this placement can be achieved. In order to do that, we must calculate the expected market share. In this case, “market share” is simply the number of retailers who agree to resell the product divided by N, and can be
5 This is the most straightforward interpretation of competition Law, as discussed in section 5.5. It does not exclude other possible interpretations.
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Fig 5: Product placement probabilities for different numbers of retailers
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.2
0.4
0.6
0.8
1
1.2
N=1N=2N=3N=4N=10N=20N=50current legalthreshold
coalition factor
pro
babi
lity
obtained directly from expression (3):
M=< X s>
N (4)
Interestingly, despite the monotonous decrease of the placement probability with c, there is a value of cM that maximizes the expected market share. This happens due to a combination of opposing factors: the probability of achieving a first success decreases with c, but the expected number of consecutive successes following the first one increases. For c=cM , the possibility of ending up with zero successes is optimally compensated by the increased likelihood of success in the trials that follow a potentially successful one. In Fig 7, we can see the expected market share for different numbers of players as a function of c. As the number of players in the market increases, the coupling effect becomes more and more noticeable.
However, the plot shown in Fig 7 doesn't take into account a key fact that applies only to small values of N: real market shares must be calculated by rounding <Xs> to the nearest integer which, in this case, is often zero. That is, an effective expected market share is defined as:
M eff=|| < X s> ||
N (5)
The corresponding plot shown in Fig 8 is radically different from the one in Fig 7 for small numbers of N.
In fact, it is clear from Fig 8 that for N<=4 the effective market share is in practice zero, except in a very narrow window of c where, for N=4, one success is expected. The reason is simple: for a small number of retailers, the expected value for the number of successes obtained from (3) is nearly zero. In line with what would be expected, as N tends to infinity, the difference between M and Meff becomes irrelevant.
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Fig 6: Product placement probabilities for different values of the coalition factor
0 10 20 30 40 50 60 70 80 90 100
0
0.2
0.4
0.6
0.8
1
1.2
c=0 c=0.5 c=0 .9
number of retailers
pro
babi
lity
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Fig 7: Expected share of retailers (without rounding)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
N=1N=2N=3N=4N=10N=20N=50current legalthreshold
coalition factor
exp
ect
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sh
are
of r
eta
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Fig 8: Effective expected share of retailers
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.1
0.2
0.3
0.4
0.5
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0.7
N=1N=2N=3N=4N=10N=20N=50current legalthreshold
coalition factor
effe
ctiv
e s
ha
re o
f re
taile
rs
However, and this is a less trivial outcome, for a reasonably small number of players (ex: N=10) the differences are small enough to be neglected. This means that, for a product with an initial acceptance probability of 0.1, a market of only 10 or more players would seem likely to work well enough.
But we must bear in mind that an expected value can approximately match a real situation only over a statistical number of independent observations. It takes repetition for an expected value to materialize. Since there is only one set of retailers, each of which having memory, it may be difficult to perform a large number of independent negotiation sequences in an acceptable time frame. It is likely that only one or a small number of negotiation sequences will take place.
Whenever only a single observation of a random variable is possible, the mode of its probability distribution may be a better bet than the expected value, since it represents the most likely outcome6. In Fig 9 the mode of (4) is shown as a function of the coalition factor, for different numbers of retailers.
Just as the expected value, the mode has a maximum for a certain value of c. However the outcome suggested by the mode is much more pessimistic. The most probable outcome for a number of retailers under 10 and p0=0.1 is achieving zero successes.
What this means is that even a situation with a statistically meaningful N (eg N=10, N=20) may not be good enough if repetition is not possible on a reasonable time frame.
6 If instead, a small number of observations is possible both indicators should be looked at.
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Fig 9: Retailer share mode
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Retailer share mode
1234102050100
coalition factor
mo
da
l sh
are
10 Conclusions
New products always face a low initial acceptance probability. It takes time for a product to build the much needed reputation that increases this probability. The rate at which it happens depends upon many factors, and sometimes on small adjustments of a single factor [22].
This article examined the challenge of getting trough the firewall of dominant retailers. That is a necessary condition in many markets for a product to become visible. It is through exposure to a very large amount consumers that an innovative product can grow to its natural market share.
We argued that both the number of existing retailers and the coupling between their decisions are determinant to the probability of new products entering the market.
The coalition factor that describes the crossretailer coupling lowers the probability of placement as it increases, but has distinct effects on the expected market share depending on the number of existing retailers. We suggested that this coalitionlike behavior can be explained by a disproportionate importance of branding and marketing among retailers, which may prevent suppliers from delivering the best products at the lowest price. This leads to heavy constraints in consumer choice.
We have shown that for N<=4 the anomalous effect introduced by small numbers dominates over the coalitionlike behavior regarding the effective expected market share. This was entirely expectable, since small numbers can never reflect statistic variables acceptably. We have also pointed out that if only one or very few negotiation sequences are possible the mode might be a better indicator than the expected value, deeming the result even less favorable.
We conclude that retail oligopolies are very prone to filtering new products independently of the likelihood of their acceptance by consumers when the new products compete with heavily established ones.
The previous statements are true in general and particularly easy to observe in the laptop retail market. The facts presented in sections 14 fit the model developed in sections 69.
During early reviews of this document we have been repeatedly asked how these filtering anomalies could affect Linux laptops while Android – which is Linux based – is the most successful smartphone operating system and a strong competitor in the tablet market. We had already explained, in section 1, the fundamental difference between those markets. At this point, we are able to look at that difference from another perspective: for markets where a certain supplier brand hasn't reached overdominance the initial acceptance probabilities for new products are much higher among retailers. Because of that, applying the same model would lead to different results.
The Linux on laptops combination became viable relatively late, in terms of Microsoft presence. But having been technically possible and economically interesting for many years, it is still kept out of the market by the retail anomalies described in this article. That happens even in the presence of interested consumers and suppliers.
We therefore question the effectiveness of the existing legal framework (section 5) with the following statement: from the standpoint of consumers and suppliers, the behavior of a small number of dominant retail chains is not significantly different from that of a single retailer.
Regulators should evaluate the direct and indirect losses caused by this situation [7] and put corrective measures in place.
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11 Acknowledgements
We are grateful to Paul Meller, Paulo Vilela and Open Forum Academy for the review of this document. We wish to thank Carlo Daffara for the precise and detailed input provided to us and Robert Bearden for the permission to reuse the Scurve plot.
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References[1] Ubuntu 10.04 LTS: Lucid Lynx Benchmarked And Reviewed Tom's Hardware http://www.tomshardware.com/reviews/ubuntu10.04lucidlynx,2634.html [2] Lucid dream: Ars reviews Ubuntu 10.04 ARS Technica http://arstechnica.com/opensource/reviews/2010/05/luciddreamarsreviewsubuntu1004.ars [3] Review: Ubuntu "Lucid Lynx" 10.04 LTS OS News http://www.osnews.com/story/23261/Review_Ubuntu_Lucid_Lynx_10_04_LTS [4] Ubuntu 10.04 LTS Lucid Lynux operating system PC World http://www.pcworld.idg.com.au/review/software_and_services/ubuntu/10_04_lts_lucid_lynx/346594 [5] http://www.pcworld.com/product/547998/canonical_ltd_ubuntu_1004_lucid_lynx.html [6] http://www.ubuntu.com/products/casestudies/frenchnationalpoliceforcesaves2millionyearubuntu [7] Market introduction of locallyassembled laptop computers with preinstalled Open Source software; ESOP; http://esop.pt/retail [8] CRAIG & de BÚRCA; EU Law, text, cases and materials; Oxford; 2003; p. 992; [9] BAEL & BELLIS; Competition Law of the European Community; Kluwer Law International; 2005; p. 903; [10] Case 85/76; HoffmanLa Roche v. Commission [1979] ECR 461; par. 39;[11] Commission Notice on the definition of the relevant market for the purpose of Community Competition Law [1997]; OJ C372/5;[12] Case 27/76; United Brands Co. and United Brands Continental BV v. Commission [1978] ECR 207; par. 65;[13] Case 85/76; HoffmanLa Roche v. Commission [1979] ECR 461; par. 4;[14] WHISH, R.; Competition Law; Butterworths; 2003; pg. 183; [15] Case 322/81; NV Nederlandsche BanderIndustrie Michelin v. Commission [1983] ECR 3461; par. 57;[16] Case 85/76; HoffmanLa Roche v. Commission [1979] ECR 461;[17] GOYDER; EC Competition Law; Oxford University Press; 2003; p. 283; [18] Commission Decision Sealink/B&I Holyhead: Interim Measures [1992] CMLR 255; recital 41;[19] Case C7/97; Oscar Bronner GmbH & Co. KG v. Mediaprint Zeitungs und Zeitschriftenverlag GmbH & Co. KG; 1998 E.C.R. I7791; [1999] 4 C.M.L.R. 112;[20] Joined Cases 6 and 7/73; Istituto Chemioterapico Italiano S.p.A. and Commercial Solvents Corporation v Commission of the European Communities [1973]; par. 33;[21] http://en.wikipedia.org/wiki/Game_theory#Normal_form [22] The Tipping Point: How Little Things Can Make a Big Difference; Little Brown; 2000.(23) Rob Bearden, Tayloring an Open Source Business Model, http://www.infoworld.com/event/osbc/08/osbc_agenda.html
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Annex AThe RF distribution
Annex A The RF distribution
Deriving the RF distribution
Consider the negotiation process defined in the main text. Let Xs be the main variable, that measures the total number of successes in the sequence. Let X's be an auxiliary variable that measures the number of successes after a first success took place.
The probability of zero successes being achieved follows trivially from considering a sequence of N unsuccessful Bernoulli trials:
P X s=0=1− pN (A.1)
To obtain an expression for a nonzero number of successes we must consider a generic number of failed trials, say j1, followed by a success at the jth trial (j <= N) and a sequence of Nj + (j1) = N1 new trials with success probability p'.
Therefore, we may write for the auxiliary variable X's
P X ' s=k |X s≠0=N−1k p ' k
1−p ' N−1−k 0≤k≤N−1 (A.2)
On the other hand we know that
P X s=k1=P X ' s=k∩X s≠0 (A.3)
which is equivalent to
P X s=k1=P X ' s=k |X s≠0P X s≠0 (A.4)
From (A.1) we have
P X s≠0=1−1−pN (A.5)
Combining (A.2), (A.4) and (A.5) we arrive at the expression
P X s=k1=[1−1− pN]N −1
k p ' k1− p ' N−1−k 0≤k≤N−1 (A.6)
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Process diagram
By rearranging the index k on both sides of the previous expression we find:
P X s=k =[1−1−pN]N −1
k−1 p ' k−11− p ' N−k 1≤k≤N (A.7)
Expected value
The expected value is calculated using (A.1) and (A.7)
< X s >=∑k=0
N
k P X s=k =0⋅1−p N[1−1− pN]∑
k=1
N
k N −1k−1 p ' k−1
1− p ' N−k (A.8)
By rearranging the index k, the previous expression can be rewritten as
< X s>=[1−1−p N][∑
k=0
N−1
k1N−1k p ' k
1− p ' N−k1 ] (A.9)
It can then be expanded to
< X s>=[1−1−p N][∑
k=0
N−1
k N−1k p ' k
1−p ' N−k1∑
k=0
N−1
N−1k p ' k
1−p ' N−k1] (A.10)
or
< X s>=[1−1− p N ][∑k=0
N−1
k N−1k p ' k
1−p ' N−1− k∑
k=0
N−1
N −1k p ' k
1− p ' N−1−k] (A.11)
We then note that both sums in the previous expression are related to the binomial distribution of parameters N1 and p', to obtain
< X s>=[1−1−p N][N −1 p '1] (A.12)
Mode
To calculate the mode we first note that for k>0
P X s=k1
P X s=k =
N−kk
p '1− p '
(A.13)
Thus, for k>0 the probability values increase with k when
kNp' (A.14)
From this fact the mode can then be found for different situations
m X s=Np' and Np'1 Np '∈ℕfloor Np ' Np'∉ℕ
(A.15)
The probability for k=0 has to be compared to the probability of the modal values in the previous expression so that the overall mode of the RF distribution can be obtained. Plots of the overall mode using the smallest value for the first branch of (A.15), as a function of the coalition factor, are included in the next page.
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