An examination of the history of the practice within modern retailing in the United Kingdom, the United States and Canada reveals a difference in the legal approach by the govern* ments concerned. The more common arguments advanced in support of resÊleoprlce maintenance fail in their objective when exam ined in relation to the benefits accruing to the consumer. The most prevalent aspect of these arguments, ^loss-leader" competition, appears as an indeterminate concept because of the inability of both economists and businessmen to arrive at an acceptable definition. Nevertheless these sane arguments give some Insight into the motives of retailers, wholesalers and manufacturers for desiring the use of resaleprice mainten ance. These motives evolve from the desire to either increase or protect present profits. Retailers who support the practice
Resaleprice maintenance (RPM) is any of a variety of practices through which manufacturers restrict resellers in the prices that they may charge for the manufacturer’s products. RPM can be imposed explicitly as a manufacturer’s suggested retail price (MSRP or list price) or as a price floor (minimum RPM), or the price can be set implicitly by, for example, fixing the retailer margin, see European Commission (2010). The legal status and use of RPM has been controversial for over a century, and evidence suggests that both the scale of RPM use and the effects on the economy are underestimated. Overstreet (1983) provides an extensive review of RPM use for the period when this practice was per se legal. In 1988, when RPM was illegal in the USA, the Supreme Court adopted a wide use of the Colgate doctrine according to which a manufacturer may refuse to deal with a retailer if it does not comply with the manufacturer’s price policy. Butz (1996) quoted antitrust authorities arguing that RPM became “ubiquitous” and “endemic”, “but based upon ‘winks and nods’ rather than written agreements that could be used in court.”
The prominent Babies R Us decision (McDonough et al., v. Toys R US, Inc., 2009) was the first to explore the economic consequences of resaleprice maintenance after the Supreme Court’s Leegin Decision. Previously, litigation concerned the presence or absence of an agreement; but that changed with the new jurisprudence which instead emphasized the restraint’s direct anti-competitive effects. While the district court’s decision in the Babies R Us case rested on the factual circumstances of the case, it did not have before it an economic model through which those facts could be integrated. This paper offers such a mode, the predicates of which are drawn from the case. The
Abstract: Legal studies usually treat a policy of a manufacturer or retailer as socially harmful if it reduces product output and increases the price. We consider a two-period model where the first-period price is fixed by resaleprice maintenance (RPM) and resellers endogenously decide to use another “collusion suspect,” meet-the-competition clause with a most-favored-customer clause (MFC), to counteract strategic customer behavior. As a result of MFC, second-period (reduced) price increases, and resellers’ inventories decrease. However, customer surplus may increase and aggregate welfare increases in the majority of market situations. MFC can not only decrease the losses in welfare and resellers’ profits due to strategic customers but, under reseller competition, may even lead to higher levels of these values than with myopic customers, i.e., to gains from increased strategic behavior. MFC may create “MFC-traps” for resellers, where one of possible market outcomes yields a gain from increased strategic behavior while another results in a reseller profit less than the worst profit in any stable outcome without MFC. With growing competition, benefits or losses from MFC can be higher than losses from strategic customer behavior.
discussed below, from an economic perspective RPM sits rather awkwardly on the spectrum in the figure above. Yes, for sure, it can be anticompetitive. But it can also give rise to important efficiency benefits, and in some cases will be indispensable for achieving those efficiency benefits. Many economists would agree that RPM is, if anything, slightly closer to the left hand side of the above figure than the right hand side. 24 But we believe that most economists would agree that its precise position in any given case will depend on market circumstances, and certainly that it is not squarely on the left hand side, holding hands with naked price fixing or dancing around with bid rigging.
Despite the fact that the ‘traditional approach’ to RPM was ultimately applied, this was the first time for the Polish Supreme Court to take a broad and detailed note of pro-competitive effects of fixed resale prices. These mentioned effects reflect, in fact, the pro-competitive justifications articulated by the European Commission in its Guidelines on Vertical Restrains of 2010. These are, first, easier market entry for certain producers – entrance of a new market player will always be pro-competitive because other market players will react by cutting their prices, or in any other way desired by consumers. Second, the Supreme Court recognized the economic concept of the free-riding effects, that is, the protection of a distributor who is providing a broad-scope of services against sellers not doing so (but charging lower prices). Yet the Polish Supreme Court stated that the free-rider effect is not working on all types of markets and that it does not have to effectively lead to better services of distributors since it is not requiring them directly to do so. Conclusively, in the Court’s opinion, avoiding the free-rider effect may justify the use of RPM only in exceptional circumstances. Third, it was noted in the judgment that RPM might have pro-competitive effects as they may lead to a uniform image and character of the sales network as well as effective advertising campaigns charging lower prices.
You have two tools to facilitate your resale decisions. The …rst is chat, located at the bottom right hand side of the screen. Messages can be sent to the other participant in this box. Please type a message now, for example, “hello” and press enter. You will see that your message has popped up and is identi…able by the label, “YOU.” If your practice partner has also sent a message, that message should have popped-up in the box and is identi…able by their role of either BUYER or SELLER. Make sure that you hit enter after you have typed a message for it to be sent. We also ask that throughout the experiment you do not provide identi…able information about yourself to the other participant. In addition to chat, you will also have access to the scrollbar seen on the left side of the screen. You can use the scrollbar to determine your payo¤ for a given o¤er. The minimum possible resale o¤er is 10, and the maximum is 50. You can choose any resaleprice between these two values by sliding the scrollbar, or clicking on the right and left arrows, which will increase and decrease the resaleprice. Please move the scrollbar now. You should now see that information has appeared below the scrollbar, which will be automatically updated as you move the scrollbar. The resale o¤er is given directly below the scrollbar. Below the o¤er, you are given your resale pro…t for that given o¤er. Directly below your pro…t, you are given the probability that the other participant’s resale pro…t will be positive for that particular o¤er. If you would like to exit resale, there is a button at the bottom left of the screen that you can click to choose to exit the resale stage at any time. You will have 180 seconds (3 minutes) to agree to an o¤er with the other participant. The time will be indicated in the middle of the right side of the screen, above chat. If an o¤er is not accepted either by you or the other participant before time expires, no resale will occur. Please press Exit Resale to continue.
At the conclusion of the auction, the …nal use values were randomly drawn by the computer software. A bidder who won the item earned the di¤erence between his …nal value and the auction price. In the default penalty treatments, if the winning bidder was making losses he would automatically default if the penalty payment under default, which was a percentage of the auction price, was less than the loss from not defaulting. In the resale treatment, (regardless of whether he was making losses) a winning bidder who did not have the highest value automatically traded the item at a resaleprice equal to the highest realized value. The winning bidder would then earn the di¤erence between the resaleprice and the auction price. While alternative, non- automated, bargaining mechanisms for resale could have been used (e.g., free-form bargaining), our design allowed us to keep experimental control over the resale market. 17
The above examples show that many realistic situations could be best analyzed through a model that incorporates resale possibilities into all-pay auctions. It remains open to char- acterize players’ behaviors in all-pay auctions with resale. Intuitively existence of resale possibilities exhibits influence on bidders’ bidding behaviors in the first stage. The aftermar- ket buyers usually have access to information revealed by the initial seller, such as submitted bids. If the submitted bids reveal private information of primary bidders, resaleprice will be responsive to those bids and a bidder’s resale profit can depend on the bid he makes in the primary auction. Therefore, resale possibilities introduce an endogenous element to bidders’ valuations upon winning the auction and creates an incentive for primary bidders to signal their private information to aftermarket buyers. This information connection between resaleprice and submitted bids is our primary focus.
Abstract—Supply chain of Indonesian Automotive Industry can be described from the component product industry as a supplier to consumer. Single Agent Brand in the supply chain automotive industry is a tier that has a dominant effect on supply chain automotive activities, so the wrong strategy selection in this tier can deliver a fatal effect on the majority tier of the supply chain automotive industry. This strategy can result in a violation of Indonesian law regulation. One of strategy that is likely to conflict with law regulation in Indonesia is a vertical restraint. This article discussed the evaluation of supply chain business strategy related to the indication of vertical restraint based on dealer and customer point of views. The result of this research proves that there are vertical restraints based on evaluation of resaleprice maintenance, territorial restriction, tying, and exclusive dealing.
The logic behind this symmetrization result is that although the resaleprice is endoge- nously determined together with the bidding strategies in the auction, but from the point of view of the relevant "marginal types" it is exogenous and common to the two bidders. Therefore, the relevant types are price takers at the margin, and they face a common price, so the resale market behaves as if it were frictionless at the margin. To gain intuition, suppose that one of the bidders is weaker in the sense that he is more likely to have a low valuation. Such a weak bidder bids more aggressively than the strong bidder and thus may win the object even if his valuation is lower than that of his rival. Therefore, he has a prof- itable resale opportunity at the resale stage. If he wins the auction by a small margin, then his take it or leave it resale o¤er r will be accepted by the strong bidder with probability 1, and his utility is equal to r. 2 Therefore, his gain from winning at the margin, his e¤ective
A speculator who wins a unit in the auction can resell it to the bidder in a resale market. We assume that resale takes place through a generic (and un-modelled) bargaining mechanism between players. Let r be the actual resaleprice at which a speculator and the bidder trade as a result of post-auction bargaining with one-sided incomplete information, where the seller has value 0 and the buyer is privately informed about his value, which is uniformly distributed on [50; 100]. 7 To make the model interesting, we assume that the expected resaleprice is E [r] > c, otherwise a speculator does not enter the auction even if he expects to win an object at price 0. There is demand reduction if the bidder bids less than his valuation for the second unit and bids more for the …rst unit than for the second unit (see, e.g., Wilson, 1979, and Ausubel and Cramton, 1998), while there is speculation if a speculator bids a positive price for a unit. Auction with 1 Speculator First suppose that only one speculator enters the auction, so that there are two players in total in the auction. We describe a possible equilibrium in which the speculator manages to obtain strictly positive pro…t, despite competing with a bidder who has a higher valuation. 8
110. See id. The Court went on to list pro-competitive effects of vertical price restraints. One of these benefits is the elimination of free riding. The Court stated that when a retailer provides auxiliary services such as decorated showrooms and first-hand demonstrations, the manufacturer may experience the benefit through promotion of its product. However, the retailer that provides these auxiliary services often incurs higher costs and thus has to raise the price of the product. This opens the door for a discount retailer to come in and undercut the auxiliary provider’s price. The free riding problem arises when consumers go to the auxiliary provider to enjoy the demonstrations and gather information, but ultimately buy the product from the discount retailer. A resaleprice maintenance scheme can eliminate free riding by setting a price floor so that the discounters cannot undercut and prices can auxiliary providers can effectively provide the extra services.
Representing 43% of the total sample, the pragmatics score high on the pragmatic and generative dimensions. Characterized by their strong propensity to resell furniture online (26.5%) and to earn medium level of earnings online (46.3% between CAD 250 and CAD 750 versus 35.7% for the whole sample), these consumers reflect moderate scores on almost all variables, appearing therefore as medium online resellers. Basically, they refer to those consumers who mostly perceive the web as a fast and easy way to dispose of goods (Lemaitre and de Barnier, 2015), and who are mostly interested in the pragmatic and generative aspects inherent to online resale. Finally, the online aficionados (30% of total sample) score higher on virtually all dimensions, especially generative, pragmatic, and social. They resell more often online, more and all kinds of products, and earn therefore more money than sporadic experiencers and pragmatics. Basically, they are more likely to be or to become professional resellers (Chu and Liao, 2007) who use the Internet as an outlet to resell recurrently several units of identical products or buy products in order to resell them online.
To our knowledge there exist only two other experimental studies of auctions with resale: Georganas (2003) looks at symmetric English auctions where resale opportunities arise out of small deviations from equilibrium bidding that become magnified once resale opportunities are present. Lange, List and Price (2004) study symmetric first price auc- tions where opportunities for resale result from bidder uncertainty regarding the value of the item. Results from neither of these studies is directly applicable to our environment. More relevant is the growing literature on asymmetric private value auctions, in particular the Guth, Ivanova-Stenzel, and Wolfstetter (2005) experiment which employs supports similar to ours.
Figure 22 presents the output of the ANN analysis. The sum of squares error (SSE) values represent the cross-entropy error, considerably lower for the Testing set. As we mentioned earlier, the camera data set had a multi-collinearity problem with the independent variable, Max.resolution. Collinearity impacts the model performance by increasing the difficulty of identifying the true relationships between response and predictor. [15, 16] So, we removed Max.resolution from the model, and the SSE for the Training set reduced from about 115 to a bit below 66. Multiple online articles and data mining blogs touch on the problem of multicollinearity while fitting ANN. The relative error for the Training set registered 0.184, while for the Testing set it registered 0.170. A value closer to 0 indicates that the model has a lower random-error component, thus serving as a more useful fit for prediction. Figure 23 displays a predicted-by-observed value for each data value. It almost seems as if some of the cheaper cameras might have a negative price in the future, which, in a strange way, makes conceptual, if not actual, sense. Some of the cameras released in the 1990s can today be bought, used, on eBay for $30 or less. Cameras in the $1000–$2000 range vary in their predicted prices, from nearly $0 up to about $3000. The majority of cameras fall in the range of $0–$2000; yet several cameras fall in the $4000–$6000 range, and a few cameras approach $8000. Notably, and as expected, as observed camera prices increased, on average the predicted value of a camera also increased, with one clear exception being an observed value of $5000 for which the predicted value dropped to below $2000. Figure 24 displays a residual-by-predicted value for each scale- dependent data value.