New York Computer Science & Economics Day, Nov 9, Dynamics of Network Technology Competition The Role of Gateways Soumya Sen Dept. Elec. & Sys. Eng University of Pennsylvania Technical Report: “Modeling the dynamics of network technology adoption and the role of converters”,

New York Computer Science & Economics Day2 Acknowledgements Joint work with: Youngmi Jin (Penn, ESE) Roch Guerin (Penn, ESE) Kartik Hosanagar (Penn, Wharton) In collaboration with: Andrew Odlyzko (U. Minn) Zhi-Li Zhang (U. Minn)

New York Computer Science & Economics Day3 One (out of many) Motivating Example Two competing video-conf service offerings Incumbent: Low-def video (has low quality, low price) Entrant: High-def (has high quality, high price) Technology characteristics User value depends on who they can reach –Higher externality benefits for High-def than for Low-def Gateways/converters can allow inter-operability with some limitations –Simplex, asymmetric, unconstrained »Asymmetric: encoding is hard, decoding is easy »Low-def subscribers can display high-def signals but not generate them Modeling the evolution and outcome of technology competition

New York Computer Science & Economics Day4 Model Users individually continuously evaluate their technology choice Decision based on technology utility Technology 1: U 1 ( ,x 1,x 2 ) =  q 1 +(x 1 +α 1 β x 2 ) – p 1 Technology 2: U 2 ( ,x 1,x 2 ) =  q 2 +(βx 2 +α 2 x 1 ) – p 2 User decisions are rational (but myopic – based on current adoption) –No technology if U 1 < 0, U 2 < 0 –Technology 1 if U 1 > 0, U 1 > U 2 –Technology 2 if U 2 > 0, U 1 < U 2 Adoption dynamics can be captured with a standard diffusion model –Main complexity is keeping track of combinations of decision regions

New York Computer Science & Economics Day5 What can this model achieve? Identify feasible combinations of possible equilibria Characterize diffusion trajectories Insight into possible adoption patterns can be extracted from the solution

New York Computer Science & Economics Day6 Key Findings Gateways can introduce instabilities (“boom and bust” cycles) Impossible without gateways Gateways create unpredictable outcomes Allow inferior technologies to persist Can hurt or help the incumbent Can hurt or help overall market penetration

New York Computer Science & Economics Day7 Example 1: “Boom & bust Cycles” (From Stable to Unstable- Asymmetric Gateways) As the efficiency of Tech. 1 gateway increases, system goes from dominance of Tech. 2 to a system with no stable state –No stable equilibrium for  1 =1 and  2 =0 x 1 : Fraction of Technology 1 adopters, x 2 : Fraction of Technology 2 adopters

New York Computer Science & Economics Day8 Example 2: Hurting Overall Market (Asymmetric Gateways – Entrant) Tech. 2 fails to gain market share without gateways Tech. 2 introduces gateways of increasing efficiency –Tech. 2 gains market share, but at the cost of a lower overall market penetration

New York Computer Science & Economics Day 9 Results Robustness Most/all results hold for a wide range of model variations –No closed-form solutions, but numerical investigations are possible Model variations –Heterogeneity in user decisions ( θ ) Non-uniform distributions –Positively and negatively skewed Beta-distributions Extended to externality benefits –Other externality models Non-linear externalities –Sub-linear: x α, 0<α<1 –Super-linear: x α, α>1 –Logarithmic: log(x+1) –Switching Costs –Learning Costs –Contract-breaking Costs –‘Lock-in’ costs –Future Directions: Dynamic Pricing Strategy

New York Computer Science & Economics Day 10 Anchoring the Model 1.IPv4  IPv6 –Duplex, asymmetric, constrained gateways 2.Low def. video conf.  High def. video conf. –Simplex, asymmetric, unconstrained converters

New York Computer Science & Economics Day 11 IPv4 (Tech. 1)  IPv6 (Tech. 2) IPv4: U 1 ( ,x 1,x 2 ) =  q 1 +(x 1 +α 1 β x 2 ) – p 1 IPv6: U 2 ( ,x 1,x 2 ) =  q 2 +(βx 2 +α 2 x 1 ) – p 2 Setting –We are (eventually) running out of IPv4 addresses Providers will need to start assigning IPv6 only addresses to new subscribers (p IPv4 =p 1 >p 2 =p IPv6 ) –IPv4 and IPv6 similar as “technologies” ( q 1  q 2 and  =1 ) Mandatory IPv6 IPv4 gateways for transition to happen –Most content is not yet available on IPv6 Little in way of incentives for content providers to do it –Duplex, asymmetric, constrained converters Users technology choice –Function of price and accessible content

New York Computer Science & Economics Day 12 Low-def. video  High-def. video Low-def: U 1 ( ,x 1,x 2 ) =  q 1 +(x 1 +α 1 β x 2 ) – p 1 High-def: U 2 ( ,x 1,x 2 ) =  q 2 +(βx 2 +α 2 x 1 ) – p 2 Setting –Two video-conf service offerings: Low-def & High-def Low-def has lower price ( p 1 <p 2 ), but lower quality (q 1 <q 2 ) –Video as an asymmetric technology Encoding is hard, decoding is easy –Low-def subscribers could display high-def signals but not generate them Externality benefits of High-def are higher than those of Low-def (  >1 ) Converters characteristics –High/Low-def user can decode Low/High-def video signal –Simplex, asymmetric, unconstrained Users technology choice –Best price/quality offering –Low-def has lower price but can enjoy High-def quality (if others use it…)