1. Welcome Strategies of Network Companies Jonathan D. Wareham wareham@acm.org

2. Agenda  Pricing  Standards  Auctions  Bundling

3. Assumption that electronic markets have less friction than comparable markets. Search costs lower Competition increases Average prices should fall, converging on market level Study of prices of books and CDs and software sold on internet: Higher prices & greater variance in electronic channel !!!!! Price Levels

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6. 1.Superior disc. pricing techniques: lower registration and menu costs 2.Heterogeneity: wine in store or restaurant Versioning 3.Temporal preference: consumer behavior and types 4.Imperfect information: bait and switch 5.Neural real estate: 5% sites/75% traffic 6.Market immaturity: eMarkets too young Possible Causes

7. P Q $1.00 1 Coke Fixed Prices

8. Consumers Surplus Dead Weight Loss MC

9. Get a little more revenue

10. 2nd Degree Price Discrimination “product line pricing”, “market segmentation”, “versioning” Gold Club, Platinum Club, Titanium Club, Synthetic Polymer Club First Class, Business Class, World Traveler Class Professional Version, Home Office

11. 3rd Degree Price Discrimination  The practice of charging different groups of consumers different prices for the same product  Examples include student discounts, senior citizen’s discounts, regional & international pricing, coupons

12. Maximize the Revenue ! Perfect (1 st degree) Price Disc.

13. Perfect Price Discrimination Price $ Quantity D 10 8 6 4 2 1 2 3 4 5 Profits:.5(4-0)(10 - 2) = $16 Total Cost MC

14. Prefect Price Discrimination  Practice of charging each consumer the maximum amount he or she will pay for each incremental unit  Permits a firm to extract all surplus from consumers  Difficult: airlines, professionals and car dealers come closest

15. Caveats:  In practice, transactions costs and information constraints make this is difficult to implement perfectly (but car dealers and some professionals come close).  Price discrimination won’t work if you cannot control three things: Preference profiles Personalized billing; (anonymous transactions lesson seller’s discriminatory power over consumers) Consumer arbitrage

16. What is different about this site?

17. 1.Internet double edged sword: Consumers enjoy lower search costs, but… eMarketers have superior tools to register your consumption patterns and price sensitivity 2.The end of fixed pricing??? Fixed pricing as an institution only 100 years old!! Developed in response to large scale economies/production models….with standard products !!!! Conclusions

18. But lets mix things up a bit more.. Product heterogeneity, Make the products different!!!! Available from different locations and time periods (wine served in store or restaurant) Levels of customer service, “Mass Customization” Search engines, product reviews, samples may create stickiness - charge price premium. Outstanding product information or compelling web design. Colors, wall paper, or exposure cycles may also influence buying behavior.

19. Customer Info and Economic Effects  Personalized product => highest price charged. Price comparison is impossible. Sellers may be in a better position to bargain.  All consumers’ needs are met. Some configurations of industrial goods may not be feasible.  All consumers may be served efficiently.

20. Market Segmentation through Quality Differentiation  Different classes of service (1 st class, 2 nd class)  Basic, expanded basic and premium cable services  Economy, family and luxury automobiles  Standard, professional subscription plans  Educational, professional, enterprise versions of software The key consideration is how to charge high-income group more without making them switch to lower-class goods

21. Differentiated Products  Homogeneous products in the industrial age  Competition through differentiation Horizontal differentiation (brand proliferation) Vertical differentiation (quality)  Reasons for differentiation Reduce substitutability Segment the market Entry into the market “price control” Market power

22. Horizontal Differentiation  The game of location (proximity to customer’s tastes) Alice Bob 1/2 Alice Bob

23. Vertical Differentiation Price Quality High Low

24. 1.Versions 2.Timing and delays 3.Ease of use 4.Pathways into site 5.Segregation of markets and users 6.Analysis of click stream and previous purchasing history How???

25. Making Self-Selection Work  May need to cut price of high end  May need to cut quality at low end  Value-subtracted versions May cost more to produce the low- quality version.  In design, make sure you can turn features off!

26. How Many Versions?  One is too few  Ten is (probably) too many  Two things to do Analyze market Analyze product

27. Analyze Your Market  Does it naturally subdivide into different categories? AND  Are their behaviors sufficiently different?  Example: Airlines Tourists v. Business travelers

28. Analyze Your Product  Dimensions to version  High and low end for each dimension  Design for high end, reduce quality for low end  Low end advertises for high end in service industries – Cheap rates  High end – Flagship products - advertises for low end in many products.

29. Goldilocks Pricing  Mass market software (word, spreadsheets) Network effects User confusion  Default choice: 3 versions  Extremeness aversion  Small/large v. small/large/jumbo

30. Extremes Aversion  Bargain basement at $109, midrange at $179 Midrange chosen 45% of time  High-end at $199 added Mid-range chosen 60% of time  Wines Second-lowest price  “Framing effects”-example

31. Cross-Subsidies  Prices charged for one product are subsidized by the sale of another product  May be profitable when there are significant demand complementarities effects  Examples Browser and server software Drinks and meals at restaurants Long distance and local access Auto spare parts Razor & Blades Burger, fries, drinks Auto financing

32. Lessons  Version your product  Delay, interface, resolution, speed, etc.  Add value to online information  Use natural segments  Otherwise use 3  Control the browser, access, comparisons, etc.  Bundling & cross subsidies may reduce dispersion

33. Down & Dirty  First degree (perfect) price discrimination “market of one”  Second degree price discrimination “product line pricing”, “market segmentation”, “versioning”  Third degree price discrimination “different prices to different groups” Other definitions in literature…

34. Standards: Examples  RR gauges  Edison v. Westinghouse  NBC v. CBS in color TV  3Com v. Rockwell/Lucent  Qwerty  What is going on now in wireless???

35. Examples  Rival evolution Video machines  Rival revolutions DVD-A v. SACD  Evolution v. Revolution

36. Recent Standards Wars  AM stereo Auto industry invested, radio didn’t  Digital wireless phones Europe: GSM US: GSM, TDMA (cousin of GSM), CDMA  TDMA: 5 million  CDMA: 2.5 million  GSM: 1 million

37. Standards Wars  Ericsson (TDMA) has AT&T, SBC, Bellsouth  Qualcom (CDMA) has Bell Atlantic, US West, etc Performance play strategy  How big are the network externalities? Geographic scope Investment is sunk, systems interconnect

38. Key Assets  Control over an installed base  Intellectual property rights  Ability to innovate  First-mover advantages  Manufacturing  Strength in complements  Reputation and brand name

39. Network Externalities  Direct Network Effects X n The value of a product is a direct function of the number of others that own the product Telephones, Fax machines  Indirect Network Effects Your DVD player is not interdependent with my DVD player. However, more people who demand DVD players will increase the number of DVDs available.

40. Demand & Supply for a Network Good

41. Diffusion and Price

42. What is an auction ?  A method for allocating scarce resources based on competition  Bidding mechanism: the seller (auctioneer) defines the auction rules:  how the winner is determined  how much he must pay each buyer chooses a bidding strategy  The auction rules define a game among buyers should use game-theoretic concepts to analyze auctions

43. Examples  Ancient cases: 500BC: Herodotus mentions about auctions in Babylon Ancient Rome: commercial trading, selling war booty  193 A.D.: auction for the entire empire  More recent cases: auctions for rare collective items in wholesale markets of fish, flowers, etc. for public contracts in stock market  Very recent cases: auctions over Internet (E-bay, ONSALE, etc.) for bandwidth (Interxion, RateX, etc.), spectrum

44. Auctions and resource allocation  An auction is a market mechanism that allocates resources (goods) to buyers  generates value for the consumers generates revenue for the seller  generates revenue for the producer  Is used where traditional market mechanisms (e.g. fixed price) can not be used can serve as an internal mechanism Seller value revenue buyers

45.  When choosing an auction design, a variety of assessment criteria and measures may be used: social efficiency (maximize the total value to buyers: Vickrey) revenue (seller profit) bidder profit time, complexity, susceptibility to collusion  Why is it hard to design? Due to lack of information! seller  Auction: incentive mechanism buyer: maximizes expected profit seller: maximizes performance measure Performance Measures

46.  Valuation private values common values correlation  Risk assessment risk neutral risk averse  Symmetry symmetric asymmetric Bidder and seller characteristics i Buyer i

47. Auctions  Uses  Major types of Auction English First-price, sealed-bid Second-price, sealed-bid (Vickrey) Dutch

48. English Auction  An ascending sequential bid auction.  Bidders observe the bids of others and decide whether or not to increase the bid.  The item is sold to the highest bidder.

49.  ascending bid, open-outcry  item is sold at least at the reserve price  best strategy for bidder bid a small amount more than the previous high bid until bidder’s valuation is reached, then stop  auctioneer has great influence  most emotional and competitive of auctions  much information regarding demand is revealed English Auction

50. First-Price, Sealed-bid  An auction whereby bidders simultaneously submit bids on pieces of paper.  The item goes to the highest bidder.  Bidders do not know the bids of other players.

51.  first price wins  sealed (each bidder is ignorant of other bids)  usually each participant is allowed one bid  two parts bidding period resolution (winner determination) phase  bidder’s strategy: shade bids to generate positive profit to avoid winner’s curse (for common value)  little information on demand is revealed First price, sealed-bid

52. Second Price, Sealed-bid  The same bidding process as a first price auction.  However, the high bidder pays the amount bid by the 2nd highest bidder.

53. Developed for Social Efficiency: Vickrey auction  second price wins, sealed the item is awarded to the highest bidder at a price equal to the second highest bid  dominant strategy: submit a bid equal to true valuation  incentive compatibility less fear of winner’s curse (for common value)

54. Why???? Asymmetric Cases  Different distributions for bidders’ valuations  Revenue equivalence does not apply  First price auctions not socially optimal  Public authorities should use second price auctions for efficiency purposes otherwise, possibility for inefficiency u

55. Intuition 1.Aggressive bidders receive sure and certain awards but pay a price closer to market consensus. 2.The price that winning bidder pays is determined by competitors' bids alone and does not depend upon any action the bidder undertakes 3.Hence, closer to real market valuation and socially optimal 4.Less bid shading or collusion occurs because people don't fear winner's curse. 5.Hence, they may adjust bid upwards. 6.Bidders are less inclined to compare notes before an auction.

56. Dutch Auction  A descending price auction.  The auctioneer begins with a high asking price.  The bid decreases until one bidder is willing to pay the quoted price.  Strategically equivalent to a first-price auction

57.  descending price (often by “Dutch clock”), open-outcry  first price wins  auctioneer usually has no influence  little information on demand is revealed Dutch Auction price

58. Information Structures  Independent private values Bidders know their own valuation of the item, but not other bidders’ valuations Bidders’ valuations do not depend on those of other bidders  Affiliated (or correlated) value estimates Bidders do not know their own valuation of the item or the valuations of others Bidders use their own information to form a value estimate Value estimates are affiliated: the higher a bidder’s estimate, the more likely it is that other bidders also have high value estimates. Common values is the special case in which the true (but unknown) value of the item is the same for all bidders

59. Optimal Bidding Strategy in an English Auction  With independent private valuations, the optimal strategy is to remain active until the price exceeds your own valuation of the object.

60. Optimal Bidding Strategy in a First-Price, Sealed- Bid Auction  If there are n bidders who all perceive valuations to be evenly (or uniformly) distributed between a lowest possible valuation of L and a highest possible valuation of H, then the optimal bid for a risk-neutral player whose own valuation is v is

61. Example  Two bidders with independent private valuations (n = 2)  Lowest perceived valuation is unity (L = 1)  Optimal bid for a player whose valuation is two (v = 2) is given by

62. Optimal Bidding Strategy in a Second-Price Sealed-Bid Auction  The optimal strategy is to bid your own valuation of the item.  This is a dominant strategy. You don’t pay your own bid, so bidding less than your value only increases the chance that you don’t win. If you bid more than your valuation, you risk buying the item for more than it is worth to you.

63. Optimal Bidding Strategies with Affiliated Value Estimates  Difficult to describe because Bidders do not know their own valuations of the item, let alone the valuations others. The auction process itself may reveal information about how much the other bidders value the object.  Optimal bidding requires that players use any information gained during the auction to update their own value estimates.

64. The Winner’s Curse  In a common-values auction, the winner is the bidder who is the most optimistic about the true value of the item.  To avoid the winner's curse, a bidder should revise downward his or her private estimate of the value to account for this fact.  The winner’s curse is most pronounced in sealed-bid auctions.

65. Common value auctions  Value of bidder is not fixed before the auction True value of item is not known ex-ante, although defined Value to bidder i depends on other bidder’s values examples: sealed box with coins, oil-lease  Complex strategies, no general results  Winner’s curse: the winner discovers that he overestimated the value of the item  Strategic approach: shade the bid to account for the adverse selection bias

66. Expected Revenues in Auctions with Risk Neutral Bidders  Independent Private Values English = Second Price = First Price = Dutch  Affiliated Value Estimates English > Second Price > First Price = Dutch Bids are more closely linked to other players information, which mitigates players’ concerns about the winner’s curse.

67. Collusion  Bidders make collusive agreements to get the item at a lower price: they select their designated winner (the one with the highest valuation) others promise to follow a specific strategy (abstain from bidding)  Which auctions are more collusive than others ? Enforcement issue: incentives for non-winners to keep their promise

68. Collusion (cont.)  First price sealed bid and Dutch auctions: not self-enforcing! no possibility for punishment In FP: winner places bid = other bidders may abstain or break the ring by bidding slightly higher In Dutch: one of the others may shout “mine” and win!  English and Second price auctions: self- enforcing! In English: if one of the others bids higher than promised, then the winner may overbid again In SP: winner’s bid = valuation of others’ bid

69. What would you pay for all this stuff?

70. Desired Revenue 3.5 = 35

71. Your Valuation 2 3 43 3 4 46 3 3 = 35 But If Price = 3.5 Revenue = 14

72. Solution: Bundle it!!! = 35 Revenue = 35 Someway, somehow, you will find a combination of products equal to 35 2 3 43 3 4 46 3 3

73. Why Bundle?  Technological complementarities in production, distribution, and consumption  Sunday newspaper A bundle of articles – we do not read them all, but which ones?? Economies of scale in production and distribution

74. Why Bundle?  Price discrimination Intuition different Price discrimination based on ability to identify and segregate customers But we can’t always do that – hence 2 nd degree price discrimination But when marginal costs are low – bundling may be better!

75. Bundling  Price discrimination Increases the menu of prices to better match heterogeneous distribution of consumers Bundling reduces the effective heterogeneity of consumers’ willingness to pay. Someway, somehow – out of these 10 goods, you will find some combination that you will value at 20$ - we just do not know which ones.

76. Key Variables  Production Costs: cost of producing additional units for the bundle  Distribution Costs: Costs of distributing a bundle  Transaction Costs: Costs of administrating the transaction – arranging for payment  Binding Costs: cost of binding components together as a bundle  Menu Costs: Costs of administering multiple prices of bundle

77. Production Costs When production costs – specifically marginal costs are low – bundle. The inclusion of an additional product does not cost much, so why not do it anyway and increase your chances of addressing consumers valuation profile. Software, magazines, cable packages Hi marginal costs: un-bundle

78. Distribution Costs When distribution costs are high - bundle. Newspapers Low distribution costs: un-bundle Pay per view TV Buying single articles on internet

79. Transaction Costs If cost of administering small payments is sufficiently low – use micro- payments Pay per view Buying single articles on internet If cost of administering payments is high- use long term payment/subscriptions Magazines, Cable TV

80. Binding and Menu Costs  If binding costs are high – don’t bundle  High menu costs may make discriminatory pricing difficult and may favor bundling by default – Neither of these are as determinative as the others.

81. To Bundle or to Un-Bundle?  It depends on a combination of all factors  Marginal cost most important  Distribution costs secondary  Transaction costs: are micro payments feasible?  Binding and Menu costs peripheral but an issue.