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Adoption and Deployment of New Network Technologies: An Economic Perspective

This research focuses on assessing the technical and economic viability of new network technologies and provides analytical frameworks for decision-making. It explores topics such as technology adoption, network infrastructure choice, and trade-offs between functionality-rich and minimalist designs.

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Adoption and Deployment of New Network Technologies: An Economic Perspective

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  1. Soumya Sen Dept. of Electrical & Systems Engineering University of Pennsylvania ssoumya@seas.upenn.edu www.seas.upenn.edu/~ssoumya Joint Work with: R. Guerin, K. Hosanagar, Y. Jin On the Adoption and Deployment of New Network Technologies: An Economic Perspective 22nd November, 2010. Georgia Institute of Technology.

  2. Networked Systems have a ubiquitous presence e.g., Internet, Power grid, Facilities Management networks, Distributed databases Success of new network technologies depends on: Technical advantage Economic factors (e.g. price, costs, demand) Shortcomings: Many technologies have failed to get adopted e.g., IPv6 migration, QoS solutions Ad-hoc decisions for deployment e.g. Cloud Computing, U-Verse versus. FiOS How to assess (design) new network technologies (architectures) for technicaland economicviability? Analytical frameworks Multi-disciplinary approach Research Motivation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 2

  3. On Developing Analytical Models: What are the key economic aspects? What factors are specific to network technologies? (e.g. externality, gateways) What are the ‘qualitative’ insights from the model? Are the results robust to changes in the underlying model? Some Dimensions for Assessing Network Technologies: Topic 1: Network Technology Adoption/ Migration How can a provider help its technology (service) to succeed? Topic 2: Network Infrastructure Choice What infrastructure should the new technology (service) be deployed on? Understanding Trade-offs between Shared and Dedicated networks Topic 3: Trade-offs between Functionality-rich versus Minimalist Designs Research Approach S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 3

  4. Two competing and incompatible network technologies (e.g., IPv4 IPv6) Different qualities and price Different installed base Users individually (dis)adopt the technology that gives them the highest positive utility Depends on technology’s intrinsic value and price Depends on number of other users reachable (externality) Gateways offer a migration path Overcome chicken-and-egg problem of first users Independently developed by each technology Effectiveness depends on gateways (converters) characteristics/ performance Duplex vs. Simplex (independent in each direction or coupled) Asymmetric vs. Symmetric (performance/ functionality wise) Constrained vs. Unconstrained (performance/functionality wise) Problem Formulation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 4

  5. A Basic User Model Technology 1: U1(,x1,x2) =  q1+(x1+α1β x2) – p1 Technology 2: U2(,x1,x2) =  q2+(βx2+α2x1) – p2 • Users evaluate relative benefits of each technology • Intrinsic value of the technology ( q1) • Tech. 2 better than Tech.1 (q2>q1) •  denotes user valuation (captures heterogeneity), • Externalities: linear in no. of users (0≤x1+x2≤1) - Metcalfe’s Law • Possibly different across technologies (captured through β) • αi, 0αi1, i = 1,2, captures gateway’s performance • Cost (recurrent) for each technology (pi) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 5

  6. Low-def. video (Tech.1) High-def video (Tech. 2) • Technology 1: U1(,x1,x2) =  q1+(x1+α1β x2) – p1 • Technology 2: U2(,x1,x2) =  q2+(βx2+α2x1) – p2 • User sensitivity to technology quality ( ) • Private information for each user, but known distribution • Low-def & High def video-conferencing service • Low-def has a lower price (p1< p2)but lower quality (q1< q2) • Video is an asymmetric technology • HQ users get higher externality from each other (β>1) • Encoding is hard, decoding is easy • Low-def subscribers could display high-def signals but not generate them • Converter characteristics • Simplex, asymmetric, unconstrained (α1β>1) • High/Low-def user can decode Low/High-def video signal • αi, 0αi1, i = 1,2, captures gateways’ performance S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 7

  7. User Adoption Process • Decision threshold associated with indifference points for each technology choice: 10(x), 20(x), 21(x),wherex=(x1, x2) • U1(, x) = 0 → =10(x)- Indifferent to Tech. 1 • U2(, x) = 0 → =20(x) - Indifferent to Tech. 2 • U2(, x) =U1(, x) → =21(x) - Indifferent between Tech. 2 and Tech. 1 • Users rationally choose • None if U1< 0, U2<0 • Technology 1 if U1>0, U1> U2 • Technology 2 if U2>0, U1< U2 • Decisions change as x evolves over time (myopic) • ≥10(x) : U1(, x) > 0- Tech. 1 becomes attractive • ≥20(x) : U2(, x) > 0 - Tech. 2 becomes attractive • ≥21(x) : U2(, x) > U1(, x)- Tech. 2 over Tech. 1 x1 x2 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 8

  8. Diffusion Model • Assume a given level of technology penetration x(t)=(x1(t), x2(t)) at time t • Hi(x(t)) is the number of users for whom it is rational to adopt technology i at time t (users can change their mind) • Adoption dynamics: • Users differ in learning and reacting to adoption information • Diffusion process with constant rate γ< 1 • At equilibrium, Hi(x*) = xi*, i {1,2} • DetermineHi(x(t)) from user utility function H1( x(t)) H1( x(t)) H2( x(t)) H1( x(t))= 20(x) -10(x) H2( x(t))=1- 21(x) H1( x(t))=1- 10(x) H2( x(t))=0 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 9

  9. Solution Methodology • Delineate each region in the (x1,x2) plane, where Hi(x)has a different expression • There are 9 such regions, i.e., R1,…, R9 • Regions can intersect the feasibility region S x2 x2=1 R1 Each ‘region’ has different pairs of expressions of H1(x) and H2(x) R4 P Tech. 2 adoption level R2 S R5 R6 R3 x1 0 0 x1=1 R7 Q Tech. 1 adoption level R8 R9 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 10

  10. Computing Equilibria & Trajectories • Solve Hi(x*) = xi*, i {1,2} in each region • Identify “candidate” equilibrium for each Region Rk • Candidates are valid onlyif they lie in their region • Equilibria can be stable or unstable • Trajectories: • λ1and λ2can be positive, negative, or even complex S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 11

  11. What are possible adoption outcomes? Combinations of equilibria Stable/ Unstable Adoption trajectories? Monotonic vs. chaotic (cyclic) What is the role of gateways? Do they help and how much? Key Questions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 12

  12. Theorem 1: There can be multiple stable equilibria (at most two) Coexistence of technologies is possible even in absence of gateways Final outcome is hard to predict simply from observing the initial adoption trends Results (1): A Typical Outcome S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 13

  13. Theorem 2:Gateways can help a technology alter market equilibrium from a scenario where it has been eliminated to one where it coexists with the other technology, or even succeeds in nearly eliminating it. Gateways need not be useful to entrant always! No gateways: Tech. 2 wipes out Tech.1 Perfect gateways: Tech. 1 nearly wipes out Tech. 2 Results (2): Gateways may help Incumbents Tech. 2 adoption level Tech. 2 adoption level Tech. 1 adoption level Tech. 1 adoption level S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 14

  14. Theorem 3:Incumbent can hurt its market penetration by introducing a gateway and/or improving its efficiency if entrant offers higher externality benefits (β>1) and users of incumbent are able to access these benefits (α1β>1) Theorem 4: Both technologies can hurt overall market penetration through better gateways. Entrant can have such an effect only when (α1β<1). Conversely, Incumbent demonstrates this behavior only when (α1β>1) Takeaway: Gateways can be harmful at times. They can lower market share for an individual technology or even both. Results (3): More Harmful Gateway Behaviors Tech. 2 adoption level Tech. 2 adoption level Tech. 1 adoption level Tech. 1 adoption level S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 15

  15. Theorem 5: Gateways can create “boom-and-bust” cycles in adoption process. This arises only when entrant exhibits higher externality benefits (β>1) than incumbent and the users of the incumbent are unconstrained in their ability to access these benefits (α1β>1) Corollary: This cannot happen without gateways, i.e., in the absence of gateways, technology adoption always converges Takeaway: Gateways can create perpetual cycles of adoption/ disadoption P.S: Behavioral Results were tested for robustness across wide range of modeling changes Results (4): More Harmful Gateway Behaviors Tech. 2 adoption level Tech. 1 adoption level Tech. 1 adoption level Tech. 1 adoption level S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 16

  16. Limit Cycles: An Intuitive Explanation α1β>1 Technology 1 Technology 2 Full-circle! Technology 1: U1(,x1,x2) =  q1+(x1+α1β x2) – p1 Technology 2: U2(,x1,x2) =  q2+(βx2+α2x1) – p2 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 17

  17. Gateways can be useful to: Promote coexistence & improve market penetration Help lessen price sensitivity But, Gateways can be harmful too: Hurt an individual technology Lower Overall Market Introduce Market Instabilities Analytical model is useful in: Identifying scenarios for policy intervention developing long-term strategic vision Qualitative results are robust to: Different User Preference (θ) Non-uniform distribution (positively & negatively skewed β-distribution) Extended to externality benefits (i.e. θβx instead of θq+βx) Alternative Externality Models Non-linear externalities (Sublinear: xα, 0 < α < 1, Superlinear: xα, α > 1, Logarithmic: log(x+1)) Presence of Switching costs, Learning costs Conclusions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 18

  18. Network Infrastructure Choice:Shared Versus Dedicated Networks 1. Problem Formulation 2. Model & Solution Methodology 3. Key Findings & Examples 4. Conclusions Part 2: Outline S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 20

  19. Emergence of new services require: Network provider has to decide between: Common (shared) Network Infrastructure Separate (dedicated) Network Infrastructure Examples: Facilities Management services & IT e.g. IT & HVAC systems Video and Data services e.g. Internet & IPTV services Cloud Computing e.g. Private (dedicated) cloud Vs Shared cloud Broadband over Power lines Lack of Framework to evaluate choices: Ad-hoc decisions (AT&T U-Verse versus Verizon FiOS) Manufacturing Systems Literature: Plant-product allocation, optimal resource allocation Motivation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 21

  20. Two network services (technologies) One existing (mature) service One new service with demand uncertainty Sharing can create economies or diseconomies of scope in costs New service has demand uncertainty Needs capacity provisioning beforedemand gets realized Dynamic resource “reprovisioning” But some penalty will be incurred (portion of excess demand is lost) Technology advances allow Reprovisioning (e.g., using virtualization) How critical is reprovisioning ability in choosing network design? Compare networks based on profits Problem Formulation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 23

  21. Model Formulation • Basic Model: • A Two-Service Model • Service 1 (existing service) • Service 2 (new service with uncertain demand) • Three-stage sequential decision process • Compare Infrastructure choices based on expected profits Infrastructure Choice Stage Capacity Allocation Stage Solve backwards Reprovisioning Stage S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 24

  22. Model Variables • Provider’s profit depends on: • Costs: • Fixed costs • Variable costs • - grows with the number of subscribers (e.g. access equipment, billing) • Capacity costs • - incurred irrespective of how many users join (e.g. provisioning, operational) Gross Profit Margin = pi - ai , i={s2, d2} Return on capacity = pi /ai S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 25

  23. Solution (1): Reprovisioning Stage • Service 2 revenue: (i={s2, d2} for Shared and Dedicated respectively) • when D2 ≤ Ki: Ri (D2 ≤ Ki) = pi D2 – aiKi • when D2>Ki: • Reprovisioning Ability: • A fraction “α” of the excess demand can be accommodated User contribution Capacity cost • Ri (D2 > Ki) = (pi – ai )(Ki + α(D2 - Ki)) • A word about reprovisioning ability, α • Independent of the magnitude of excess demand • Captures feasibility of and latency in securing additional resources • So what do α =0 and α =1mean? S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 26

  24. Solution (2): Capacity Allocation Stage • Expected Revenue, E(Ri|Ki), for a given provisioned level Ki: • Optimal Provisioning Capacity: • For demand distribution ~U[0, D2max]: S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 27

  25. Solution (3): Infrastructure Choice Stage • Dedicated Networks: • Service 1 revenue: • Service 2 revenue under optimal provisioning: • Total profit: • Shared Network: • Infrastructure Choice: • Common if , else separate Profit from Service 2 Profit from Service 1 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 28

  26. Choice of Infrastructure • Impact of system parameters: • Varying cost parameters affect the choice of infrastructure • Shared to Dedicated (or Dedicated to Shared) • Single threshold for switching n/w choice • Surprisingly, ad-hoc “reprovisioning” ability also impacts in even more interesting ways! • Common is preferred over separate when Depends on provisioningdecision Independent of provisioning decision h(α)= Diff. in optimal capacity cost Function of pi, ai, α, i={s2,d2} S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 29

  27. Analyzing the effect of αon h(α) • Proposition 1: Increase in α benefits both shared and dedicated networks. • (i) if increases in α benefits shared (dedicated) n/w more than dedicated (shared) • (ii) if increases in α benefits shared (dedicated) more at low α and dedicated (shared) more at high α • The value of h'(0) and h'(1) fully characterize the shape of h(α) Return on Capacity Gross Profit Margin S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 30

  28. Results: Impact of Reprovisioning GPMded(pd2-ad2) is sufficiently lower than GPMshr(ps2-as2) GPMded> GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded<ROCshr i.e. (pd2/ad2) <(ps2/as2) GPMded> GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded>ROCshr i.e. (pd2/ad2) >(ps2/as2) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 31

  29. Developed a generic model that captures economies and diseconomies of scope between shared and dedicated networks Reprovisioning can affect the outcome in non-intuitive ways Validates the need for models to incorporate this feature Yields guidelines on how reprovisioning affects choice of architecture Identified key operational metrics to consider Provides decision guideline Robustness: Non-uniform demand distribution (positively & negatively skewed β-distribution) Economies and diseconomies of scale Different reprovisioning abilities for shared and dedicated networks (α1, α2 ≠α) Conclusions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 32

  30. Network Technology Adoption: S. Sen, Y. Jin, R. Guerin and K. Hosanagar. Modeling the Dynamics of Network Technology Adoption and the Role of Converters. IEEE/ACM Transactions on Networking. 2010 S. Sen, Y. Jin, R. Guerin and K. Hosanagar. Technical Report: Modeling the Dynamics of Network Technology Adoption and the Role of Converters. Technical Report. June, 2009. Available at http://repository.upenn.edu/ese papers/496/. Y. Jin, S. Sen, R. Guerin, K. Hosanagar and Zhi-Li Zhang. Dynamics of competition between incumbent and emerging network technologies. In Proc. Of ACM NetEcon'08, pp.49-54, Seattle, WA, 2008. Network Infrastructure Choice: (4) S. Sen, R. Guerin and K. Hosanagar. Shared Versus Separate Networks - The Impact of Reprovisioning. In Proc. ACM ReArch'09, Rome, Italy, December 2009. S. Sen, K. Yamauchi, R. Guerin and K. Hosanagar. The Impact of Reprovisioning on the Choice of Shared versus Dedicated Networks, Proc. of Ninth Workshop on E-business, WEB, St. Louis, MO, December 2010. Bibliography Thank You! S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 33

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