1. An Individual View on Cooperation Networks Institute of Information Systems J. W. Goethe University, Frankfurt http://www.is-frankfurt.de Tim Weitzel, Daniel Beimborn, Wolfgang König

2. Equilibria in NetworksSimulation ModelResults and Further Research

3. Equilibria in NetworksSimulation ModelResults and Further Research

4. Equilibria in Networks network benefits  synergies, network effects …  example: EDI but…  coordination problems (multiple equilibria)  example: EDI equilibrium analysis  existence and efficiency of equilibria (where, and how to get there?)  evaluation of solution mechanisms (centralized, decentralized)

5. theoretical foundation and literature Coordination problems (network effects as externality):  multiple equilibria, path dependencies [Arthur 1983; 1989; 1996] [David 1985] [Liebowitz/Margolis 1998]  market failure (discrepancy private and collective gains) [Kindleberger 1983; Farrell/Saloner 1986]  excess inertia [Katz/Shapiro 1985; 1986]  tippy networks, monopoly [Besen/Farrell 1994] [Shapiro/Varian 1998] increasing returns  multiple equilibria  which one will and should be achieved  as individual agent?  as entire network (owner or other aggregate entity)?

6. Equilibrium concepts Pareto efficiency:  an equilibrium is called Pareto-efficient if no one can be made better off without at least someone being worse off  in neo-classical economics, markets move towards Pareto efficiency Kaldor-Hicks efficiency:  in networks, there are multiple Pareto-efficient equilibria. The Kaldor-Hicks criterion describes a preference order for Pareto- efficient equilibria  an equilibrium is called Kaldor-Hicks-efficient when changing towards it from the present state, the gainers could compensate the losers and still be better off

7. equilibria  game has two Nash equilibria: (s11,s21) and (s12,s22)  both are Pareto-efficient  only (s12,s22) is Kaldor-Hicks efficient

8. Equilibria in NetworksResults and Further ResearchSimulation Model

9. Model network participation as trade-off between  network participation costs (technology adoption, customizing, converters, etc.)  and benefits (direct network effects, cost savings due to a deeper integration with business partners, reduced friction costs)  Example: EDI network, electronic marketplace, iMode services

10. Model Idealistic network engineering by centralized coordination  omniscient central planner seeks overall optimum  no agency costs  “monolithic” decisions, collective objective function vs. realistic networks by decentralized coordination  autonomous agents embedded in individual network neighborhood  opportunistic behavior  individual information sets

11. Individual benefits E i (ex post) Individual benefits E i (ex ante) Network-wide (centralized) savings Centralized solution simulation model

12. individual consequences (mostly no side payments necessary)

13. individual consequences (magnified)

14. findings  efficiency gap  centralized control: scarce cases of agents that are forced to participate against their will (or that would require compensations ex post in a decentralized context)  not only the whole network but also the vast majority of individuals are better off getting the optimal solution from a central principal  consequence: substantial number of “win-win” situations: if there are no E i (z) < 0 centralized solution is Pareto-superior to decentralized

15. Equilibria in NetworksResults and Further ResearchSimulation Model

16. Main results two cases of network inefficiency: 1.either agents wrongly anticipated their environments' actions  reducing uncertainty is in principal sufficient, i.e. designs aimed at enhancing the "information quality" (i.e. to solve the renowned start-up problem). 2.or some agents that should join a network from a central perspective are individually worse off doing so  some form of redistribution needs to be established  substantial fraction of first case promising concerning “severity” of network coordination problems: cheap talk (information intermediation) often does it! future extensions:  network topology, density  negative effects and other dependencies

17. details

18. appendix Externality  an externality is considered to be present whenever the utility function Ui(.) of some economic agent i includes real variables whose values are chosen by another economic agent j without particular attention to the welfare effect on i’s utility Pareto efficiency:  an equilibrium is called Pareto-efficient if no one can be made better off without at least someone being worse off.  formally: an allocation x is considered to be Pareto-optimal if and only if no other allocation y exists which is weakly preferred over x by all individuals and strongly preferred by at least one individual

19. Standardisierungsmodell (Grundlagen)  Agent i (i  {1,...,n}) entscheidet über Nutzung des Standards q  Standardisierungskosten K iq vs. Standardisierungserlöse c ij  methodischer Vergleichsrahmen für institutionelle Mechanismen: Zentrale (globale) vs. dezentrale (lokale) Koordination

20.  default network consists of 35 agents corresponding to 630 variables and 2,415 restrictions  normally distributed costs and network effects  analogous results for other network sizes (e.g. n = 1,000) and distributions  50 repetitions per parameter constellation  figure results from 4,500 simulation runs expected individ. utility (ex ante)network-wide savings individual benefits (ex post) centralized objective function

21. Einige Ergebnisse Netzwerksimulationen  Standardisierungsnutzen (Netzeffekte)  (C) = 1000  (C) = 200  Standardisierungskosten  (K) = 1000  (K) = var.  Netzgröße n = 35  Zeithorizont T = 35  Netzdichte V = var.  Netztopologie = var.  Installed Base B = var.  Anzahl Standards Q = 4

22. Die Standardisierungslücke (einfaches Modell)

23. Fehlentscheidungen

24. Fehlentscheidungen

25. Model  challenge: synchronize individual and aggregate objective functions  classic solution: profit sharing or a network ROI guaranteeing each participating agent “fair” returns on their participation costs  rests upon the assumption that 1.there are sufficient network gains to be redistributed 2.redistribution design can actually be developed to ensure e.g. positive ROI  In economic equilibrium analysis 1) implies that eventual allocation is Kaldor-Hicks-superior to the former and 2) that it is Pareto- superior.