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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
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Equilibria in NetworksSimulation ModelResults and Further Research
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Equilibria in NetworksSimulation ModelResults and Further Research
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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)
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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)?
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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
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equilibria game has two Nash equilibria: (s11,s21) and (s12,s22) both are Pareto-efficient only (s12,s22) is Kaldor-Hicks efficient
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Equilibria in NetworksResults and Further ResearchSimulation Model
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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
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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
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Individual benefits E i (ex post) Individual benefits E i (ex ante) Network-wide (centralized) savings Centralized solution simulation model
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individual consequences (mostly no side payments necessary)
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individual consequences (magnified)
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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
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Equilibria in NetworksResults and Further ResearchSimulation Model
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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
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details
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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
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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
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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
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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
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Die Standardisierungslücke (einfaches Modell)
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Fehlentscheidungen
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Fehlentscheidungen
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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.
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