Chapter 17: Network Markets

Chapter 17: Network Markets Introduction Some products are popular with individual consumers precisely because each consumer places a value on others using the same good A telephone is only valuable if others have one, too Each user of Microsoft Windows benefits from having lots of other Windows users Users can run applications, e.g., Word on each other’s computers More applications are written for systems with many users Network Effects or network externalities reflect such situations in which each consumer’s willingness to pay for a product rises as more consumers buy it Strategic interaction in a market with network effects is complicated Chapter 17: Network Markets

Monopoly Provision of a Network Service An early model by Rohlfs (1974) illustrates many of the issues that surround markets with network effects Imagine some service, say a cable network, where consumers “hook” up to the system but the cost of providing them service after that is effectively zero Provider is a monopolist charging a “hook up” fee but no other payment The basic valuation of the product vi is uniformly distributed across consumers from 0 to $100. Consumer willingness to pay is fvi where f is the fraction of the consumer population that is served The ith’s consumer’s demand is: 0 if fvi < p 1 if fvi  p qiD = Chapter 17: Network Markets

Monopoly Provision of a Network 2 Consider the marginal consumer with basic valuation The firm will serve all consumers with valuations  With 100 consumers, solving for the fraction f of the market served we have: f = 1 - = 1 – p/100f So, the inverse demand function is: p = 100f(1 – f) Chapter 17: Network Markets

Monopoly Provision of a Network 3 The inverse demand curve has both upward and downward sloping parts. This means that there are two possible values for the fraction of the market served at any price p. $/unit = p 25 20 15 10 5 $22.22 0 0.2 0.4 0.6 0.8 1 f fL fH Chapter 17: Network Markets

Monopoly Provision of a Network 4 The Rohlfs model makes clear many of the potential problems that can arise in markets with network effects 1. The market may fail altogether Suppose the firm must set a fee over $30 perhaps to cover fixed costs Network will fail even though it is socially efficient When half the market is served, the customers hooking up have vi ‘s that range from $50 to $100 or fvi values that range from $25 to $50 Average value is then $37.50, well above $30 But as p rises to $30, f falls and so does average willingness to pay There is no price at which sufficient numbers of consumers sign on that yields an average willingness to pay of $30 Chapter 17: Network Markets

Monopoly Provision of a Network 5 2. There are multiple equilibria At p < $25, there is more than one equilibrium value of f At p = $22.22 both fL(p) = 1/3 and fH(p) = 2/3 are possible f values Lower fraction may be unstable (tipping) This group is comprised of consumer with top one-third of vi values The addition of one more consumer will raise willingness to pay sufficiently that consumers with the next highest third of vi values will be willing to pay and we will move to the fH equilibrium The loss of one consumer will lower the willingness to pay of that same top one-third and demand will fall to zero at p = $22.22 Chapter 17: Network Markets

Monopoly Provision of a Network 6 If the firm needs to serve more than one-third of consumers at a price of $22.22, fL is called a critical mass. Low or free introductory pricing Lease and guarantee that if critical mass is not reached, refund given Target large consumers with internal networks first Chapter 17: Network Markets

Networks, Complementary Services & Competition Rohlfs model is a monopoly model but has clear insights for oligopoly setting Market may fail Competition will be fierce—a firm that fails to reach a critical mass isn’t just smaller than its rival—it dies Multiple Equilibria are possible—Betamax versus VHS or Blu-Ray versus AOD DVD format—either system may win Winning system is not necessarily the best one Chapter 17: Network Markets

Price Competition and Network Effects Sometimes firms have separate networks instead of connecting consumers to the same network Banks/ATMS Facebook/Myspace Consider to firms at the ends of a Hotelling line A at zero, B at 1 Consumer valuation is V + k sA – tx – pA for firm A V + k sA – tx – pA for firm B Where si is the fraction of consumers buying from firm i Chapter 17: Network Markets

Price Competition and Network Effects 2 Sometimes firms have separate networks instead of connecting consumers to the same network Banks ATMS Facebook/Myspace Consider to firms at the ends of a Hotelling line A at zero, B at 1 Consumer valuation is V + k sA – tx – pA for firm A V + k sA – tx – pA for firm B Where si is the fraction of consumers buying from firm I sA = xm and sA = 1- xm where xm is the location of the marginal consumer Chapter 17: Network Markets

Price Competition and Network Effects 3 Assume t>k > 0 The marginal consumer is defined by V +k sA – txm – pA = V + k sB – t(1 – xm) – pB. Using rational expectations we have (sA-sB=1+2xm) Chapter 17: Network Markets

Price Competition and Network Effects 4 Which gives demand and profits Chapter 17: Network Markets

Price Competition and Network Effects 5 And best responses So in equilibrium pA = pB = t – k So stronger network effects (higher k) intensifies price competition Chapter 17: Network Markets

Systems and Standards Competition Competition between networks does not always lead to one survivor Each network may have its own system Compatibility issues What is gained and lost when consumers cannot use their brand of the product on other systems? Competition to be the Industry Standard Firms may compete to have their system adopted as the industry standard What are the implications of standards competition? Chapter 17: Network Markets

Competition and Technical Compatibility Fear of being incompatible can lead to the inferior Nash Equilibrium— neither firm switches because it thinks the other won’t switch Both switching to the new technology is a superior Nash Equilibrium Competition and Technical Compatibility Both staying with the old technology is a Nash Equilibrium The fight over compatibility can lead to poor technical choices overall Two possible problems: Excess Inertia and Excess Momentum Excess Inertia Firm 2 Old Technology New Technology Old Technology (5,4) (2, 2) Firm 1 New Technology (1, 5) (6,7) Chapter 17: Network Markets

Technical Compatibility 2 Both switching to the new technology is a Nash Equilibrium Both staying with the old technology is a superior Nash Equilibrium Again, fear of being incompatible can lead to the inferior Nash Equilibrium Technical Compatibility 2 In the case of excess inertia, each firm wants to adopt the same technology as its rival but, fearful that the rival won’t switch to the new technology, each wrongly stays with the old It is also possible that there is Excess Momentum and each wrongly switches to the New Technology Excess Momentum Firm 2 Old Technology New Technology Old Technology (6,7) (2, 2) Firm 1 New Technology (1, 5) (5,4) Chapter 17: Network Markets

Technical Compatibility 3 The Excess Inertia and Excess Momentum cases apply to market settings where the network gains from compatibility and “connectedness” are large both firms want to adopt a common technology Difficulty in agreeing which technology both should use Sometimes firms will not have a preference to make their technology the common standard or not to have a common technology at all Different technologies loses compatibility But different technologies differentiates each product and softens price competition, e.g., PlayStation 3 vs. Wii vs. X-Box Chapter 17: Network Markets

Technical Compatibility 4 Firm 1 choosing technology 1 and Firm 2 choosing technology 1 is the Nash Equilibrium preferred by Firm 1 STRATEGIES: build an early lead by establishing a large installed base; and 2) convince the suppliers of complements to adopt your preferred technology Firm 1 choosing technology 2 and Firm 2 choosing technology 2 is the Nash Equilibrium preferred by Firm 2 Technical Compatibility 4 Assume there are two technologies, Firm 1’s technology 1 and Firm 2’s technology 2 In Battle of the Sexes firms still agree that there should be a common standard but each wants its own technology to be the standard Battle of the Sexes Firm 2 Technology 1 Technology 2 (10,7) (6,5) Technology 1 Firm 1 (5,4) (8,12) Technology 2 Chapter 17: Network Markets

Technical Compatibility 5 STRATEGIES similar to before. build a large installed base of the preferred technology with your name on it; and make sure that you have lined up suppliers of complements so that you are the one who gets to adopt that technology Firm 1 choosing technology 1 and Firm 2 choosing technology 2 is the Nash Equilibrium preferred by Firm 1 Technical Compatibility 5 Firm 1 choosing technology 2 and Firm 2 choosing technology 1 is the Nash Equilibrium preferred by Firm 2 Again, assume there are two technologies, technology 1 and technology 2, but technology 1 is probably better In Tweedledum and Tweedledee, the firms want to differentiate their products by choosing different strategies but each wants to be the one with the superior technology 1 Tweedledum and Tweedledee Firm 2 Technology 1 Technology 2 (3,3) (8,5) Technology 1 Firm 1 (6,7) (2,2) Technology 2 Chapter 17: Network Markets

Technical Compatibility 6 There is no Nash Equilibrium (in pure strategies)—Firm 2 may frequently change or update its technology to lose its “little brother” If Firm 1 chooses technology 2 then Firm 2 wants to adopt technology 2, too If Firm 1 chooses technology 1 then Firm 2 wants to use technology 1, as well Technical Compatibility 6 In Tweedledum and Tweedledee each firm wants superior technology but really care about differentiating their products by choosing different technologies In Pesky Little Brother, Firm 1 is the dominant firm (big brother) that wants to limit competition from Firm 2 (little brother) by adopting a different technology. Firm 2 always wants compatibility Pesky Little Brother Firm 2 Technology 1 Technology 2 (12,4) (16,2) Technology 1 Firm 1 (15,2) (10,5) Technology 2 Chapter 17: Network Markets

Public Policy and Systems/Standards Competition Public policy in the presence of strong network externalities is complicated Low introductory pricing and bundling of complements may look like anticompetitive practices but are really just necessary to survive Decreeing a common standard forces government to choose the winning standard. Governments are not necessarily good at picking winners Should governments try to coordinate technology choices or, instead, “let a thousand flowers bloom” Chapter 17: Network Markets

Chapter 17: Network Markets Empirical Application: Network Effects in Software—The Case of Spreadsheets Computer software is probably among those products with important network features, e.g., the more people that use Excel or PowerPoint the more usable and valuable they are to any one consumer Can we identify network features empirically? A relatively early attempt is Gandal’s (1994) investigation of spreadsheet program pricing Chapter 17: Network Markets

Empirical Application: Network Effects in Spreadsheet Programs 2 A spreadsheet is a long-established business planning tool Originally a pencil-and-paper operation with sheets organized into many rows and columns that could be summed either vertically or horizontally to trace the impact of individual factors Computerized versions began to appear in 1980 By the mid-1980’s there were eight or more different spreadsheet programs on the market The dominant product was Lotus 1-2-3 Each product had different features, e.g., Graphing Ability to link entries in one spreadsheet to those in another Lotus compatibility Chapter 17: Network Markets

Empirical Application: Network Effects in Spreadsheet Programs 3 A hedonic regression is a model of price determination that explains a product price as a result of its key features rather than explicitly model supply and demand Gandal (1994) estimates an hedonic regression for spreadsheet programs over the years 1986 to 1991 Postulates key characteristics that should affect spreadsheet price Identifies which characteristics are network features Explicitly considers the role of time and technical progress so that a spreadsheet price index may be constructed Chapter 17: Network Markets

Empirical Application: Network Effects in Spreadsheet Programs 4 · Basic Features LMINRC = a measure of sheer computing power LOTUS = a 1,0 variable equal to 1 if it has the Lotus brand GRAPHS = a 1,0 variable equal to 1 if it has graphing ability WINDOW = number of windows program handles simultaneously LINKING = a 1,0 variable equal to 1 if it links spreadsheet entries Network Features LOCOMP = a 1,0 variable equal to 1 if program is Lotus compatible EXTDAT = a 1,0 variable equal to 1 if it can import external data LANCOM = a 1,0 variable equal to 1 if it can link to a local network Time Dummies one for each year to pick up the pure effect of time (technology improvement) on spreadsheet prices Chapter 17: Network Markets

Empirical Application: Network Effects in Spreadsheet Programs 5 Network features raise value of spreadsheet program Variable: Coefficient t-statistic LMINRC 0.11 ( 1.59) LOTUS 0.56 ( 4.36) GRAPHS 0.46 ( 3.51) WINDOW 0.17 ( 2.14) LINKING 0.21 ( 1.91) LOCOMP 0.72 ( 4.28) EXTDAT 0.55 ( 4.05) LANCOM 0.21 ( 1.65) CONSTANT 3.76 (12.31) 1987 – 0.06 (–0.38) 1988 – 0.44 (–2.67) 1989 – 0.70 (–4.20) 1990 – 0.79 (–4.90) 1991 – 0.85 (–5.30) Technical progress lowers spreadsheet prices over time Chapter 17: Network Markets

Empirical Application: Network Effects in Spreadsheet Programs 6 Gandal’s Results Demonstrate importance of network features for spreadsheet programs Allow construction of a spreadsheet price index that controls for quality, i.e., that reflects the pure passage of time Since dependent variable is ln Price, Hedonic Price Index is: Implied Spreadsheet Price Index (1986 = 1.00) Year 1986 1987 1988 1989 1990 1991 Index 1.00 0.94 0.64 0.49 0.45 0.42 Chapter 17: Network Markets