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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”, http://repository.upenn.edu/ese_papers/496/. Acknowledgements.

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Dynamics of Network Technology Competition The Role of Gateways

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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”, http://repository.upenn.edu/ese_papers/496/

New York Computer Science & Economics Day, Nov 9, 2009


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 Day


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 Day


    Model

    • Users individually continuously evaluate their technology choice

    • Decision based on technology utility

      Technology 1: U1(,x1,x2) =  q1+(x1+α1β x2) – p1

      Technology 2: U2(,x1,x2) =  q2+(βx2+α2x1) – p2

    • User decisions are rational (but myopic – based on current adoption)

      • No technology if U1< 0, U2<0

      • Technology 1 if U1>0, U1> U2

      • Technology 2 if U2>0, U1< U2

    • 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 Day


    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 Day


    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 Day


    Example 1: “Boom & bust Cycles”(From Stable to Unstable- Asymmetric Gateways)

    x1: Fraction of Technology 1 adopters, x2: Fraction of Technology 2 adopters

    • 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

    New York Computer Science & Economics Day


    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


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