Formation of Economic and Social Networks

Last Updated: 19 February 2013

Site maintained by: Leigh Tesfatsion Department of Economics Iowa State University Ames, Iowa 50011-1070 http://www.econ.iastate.edu/tesfatsi/ tesfatsi AT iastate.edu Agent-Based Computational Economics (ACE) Website ACE Network Formation Research

Table of Contents: Introductory Readings Research Sites Software, Toolkits, and Computer Demos Books and Journals Some Early Individual Researchers

Introductory Readings

• Albert-László Barabási, "Network Overview" (pdf,3.3MB), 2006 Keynote Address.

  Professor Albert-László Barabási (Department of Physics, Notre Dame, Indiana) directs a research group focusing on the emergence and evolution of networks in various contexts (e.g., metabolic and genetic networks, actor networks, collaborative networks). This fun slide presentation provides a vivid visual summary of some of their key findings to date.

• Stephen P. Borgatti and Pacey C. Foster, "The Network Paradigm in Organizational Research: A Review and Typology", Journal of Management, Vol. 29(6), 2003, 991-1013. The published article is available from Science Direct.

  Abstract: This paper reviews and analyzes the emerging network paradigm in organizational research. It begins with a conventional review of recent research organized around recognized research streams. It then analyzes this research, developing a set of dimensions along which network studies vary, including: direction of causality; levels of analysis, explanatory goals, and explanatory mechanisms. The latter is used to construct a 2-by-2 table cross-classifying studies of network consequences into four canonical types. The paper concludes by noting the rising popularity of studies placing a greater stress on agency than was traditional in network research.

• Vincent Cheung and Kevin Cannon, Introduction to Neural Networks, (pdf,1.5M)

  Abstract: Superb introduction to artificial neural networks.

• Giorgio Fagiolo (Laboratory of Economics and Management, Sant'Anna School of Advanced studies, Pisa, Italy) has prepared a ppt presentation, titled Games on Networks: Rationality, Dynamics, and Interactions (pdf,1.5MB), that reviews recent research by himself and others on the endogenous formation of networks by strategically interacting players in a variety of application contexts.

• Bernd Fritzke, Growing Self-Organizing Networks - Why?" (pdf,550KB) In: M. Verleysen, (ed.), ESANN'96: European Symposium on Artificial Neural Networks, D-Facto Publishers, Brussels, 1996, 61-72 (invited paper).

  Abstract: "The reasons to use growing self-organizing networks are investigated. First an overview of several models of this kind is given are they are related to other approaches. Then two examples are pre- sented to illustrate the specic properties and advantages of incremental networks. In each case a non-incremental model is used for comparison purposes. The rst example is pattern classication and compares the supervised growing neural gas model to a conventional radial basis func- tion approach. The second example is data visualization and contrasts the growing grid model and the self-organizing feature map."

• Sanjeev Goyal (Faculty of Economics, Cambridge University, UKB), "Learning in Networks" (pdf,372KB), Working Paper, December 2003.

  Abstract: This paper surveys theoretical (analytical) research on learning, with a special focus on the interaction network between individual entities. The survey first examines the nature of learning about optimal actions for a given network architecture. It then discusses learning about optimal links and actions in an evolving network.

• Sanjeev Goyal, Connections: An Introduction to the Economics of Networks, Princeton University Press, Princeton and Oxford, 2007.

  Abstract: In (this booKB), Sanjeev Goyal puts contemporary thinking about networks and economic activity into context. He develops a general framework within which this body of research can be located. Topics covered include: network concepts and empirics; games on networks; coordination and cooperation; social learning; social networks in labor markets; strategic network formation; one-sided link formation; two-sided link formation; and research collaboration among firms.

• Matthew Jackson (Cal Tech, Pasadena), "A Survey of Models of Network Formation: Stability and Efficiency" (pdf,441KB), Working Paper, Revised May 2003.

  Abstract: This study is an extensive survey of the theoretical (analytical) literature on the formation of non-directed networks, i.e., networks in which links require mutual consent. Jackson notes in conclusion that many important and interesting open questions remain, many going well beyond what can currently be handled by analytical methods. He briefly mentions recent empirical research on network formation, as well as recent experimental research with human subjects and with computational agents.

• Michael Kosfeld (University of Zurich, Switzerland), "Network Experiments" (pdf,370KB), Working Paper, May 2003.

  Abstract: This paper surveys (human-subject) experimental research on social and economic networks. The experiments consider networks of coordination and cooperation, buyer-seller networks, and network formation.

• David G. Rand, Samuel Arbesman, and Nicholas A. Christakis, "Dynamic Social Networks Promote Cooperation in Experiments with Humans (pdf,361KB), Proceedings of the National Academy of Sciences, Early Edition, 2011.

  Abstract:The authors conduct human-subject experiments to explore large-scale cooperation, where subjects' cooperative actions are equally beneficial to all those with whom they interact. Their experimental findings confirm the predictions of a set of evolutionary game theoretic models and demonstrate the important role that dynamic social networks can play in supporting large-scale human cooperation.

• Leigh Tesfatsion and Kenneth L. Judd, Eds., Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam, the Netherlands, Spring 2006.

  Abstract: This handbook includes two chapters on the agent-based computational modeling of networks, one chapter (by Allen Wilhite) focusing on economic activities conducted on fixed-node networks and a second chapter (by Nicolaas Vriend) focusing on the endogenous formation of economic relational networks. The preface and table of contents of this handbook can be viewed here.

• F. Schweitzer, G. Fagiolo, D. Sornette, F. Vega-Redondo, A. Vespignani, and D. R. White, "Economic Networks: The New Challenges" (pdf,1.1MB), Science, 24 July 2009, Vol. 325, No. 5939, pp. 422-425.

  Abstract: "The current economic crisis illustrates a critical need for new and fundamental understanding of the structure and dynamics of economic networks. Economic systems are increasingly built on interdependencies, implemented through trans-national credit and investment networks, trade relations, or supply chains that have proven difficult to predict and control. We need, therefore, an approach that stresses the systemic complexity of economic networks and that can be used to revise and extend established paradigms in economic theory. This will facilitate the design of policies that reduce conflicts between individual interests and global efficiency, as well as reduce the risk of global failure by making economic networks more robust."

• Randall Verbrugge (BLS, Washington D.C.), "Interactive Agent Economies: An Elucidative Framework and Survey of Results", Macroeconomic Dynamics 7(3), 2003, 424-472.

  Abstract: The author presents an analytical framework for exploring the implications of economic interaction. The initial sections of the paper include a survey of previous work on interacting agent economies with a stress on analytical studies.

• Anna Nagurney (John F. Smith Memorial Professor, Isenberg School of Management, University of Massachusetts, Amherst) is the Editor of a book series titled New Dimensions in Networks, to be published by Edward Elgar Publishing Company. This series is designed to publish original manuscripts and edited volumes that push the development of the theory and application of networks to new dimensions. It is interdisciplinary andinternational in its coverage, and aims to connect existing areas, unveil new applications, and extend existing conceptual frameworks as well as methodologies. For information regarding manuscript submission policy and procedures, visit here.

Research Sites

• Agent-Based Computational Research on the Evolution of Interaction Networks (Tesfatsion)

  Leigh Tesfatsion (Iowa State University, Ames) maintains a resource site for researchers interested in taking an agent-based computational economics (ACE) approach to studying the Evolution of Interaction Networks. ACE is the computational study of economies modeled as dynamic systems of interacting agents. The site provides annotated pointers to readings, software, individual researchers, and research groups.

• CASOS: Center for Computational Analysis of Social and Organizational Systems

  CASOS (Center for Computational Analysis of Social and Organizational Systems) at Carnegie Mellon University brings together computer science, dynamic network analysis, and the empirical study of complex socio-technical systems. Computational and social network techniques are combined to develop a better understanding of the fundamental principles of organizing, coordinating, managing, and destabilizing systems of intelligent adaptive agents (human and artificial) engaged in real tasks at the team, organizational, or social level. CASOS is a university-wide center drawing on faculty, students, and programming staff in multiple departments at Carnegie Mellon.

• Coalition Theory Network

  The Coalition Theory Network (CTN) is an association of high-level scientific institutions whose aim is the advancement and diffusion of research in the area of coalition formation. The CTN, founded in 1995, sponsors annual meetings and summer school activities.

• Complex Systems and Random Networks (Mendes)

  J. F. F. Mendes (University of Aveiro, Portugal) maintains a resource site titled Complex Systems and Random Networks that provides pointers to publications, discussion papers, and links related to this topic area.

• Economics of Networks (Economides)

  The Internet Site for the Economics of Networks, maintained by Nicholas Economides (New York University), provides a collection of information on economic issues of networks, such as the telephone and fax communications networks, the internet, financial exchange and credit card networks, and "virtual networks" such as the virtual network of all Windows or all Mac computers.

• Economics of Networks Links (WebEc)

  WebEc maintains a list of annotated pointers focusing on the Economics of Networks.

• Emergence (Resnick and Silverman)

  Mitchel Resnick and Brian Silverman (Epistemology and Learning Group, MIT Media Laboratory) maintain an "active essay" that explores the idea of emergence of global regularities arising from simple interactions. Visitors with a Java-enabled browser can activate animations that illustrate the concepts under discussion. The site can be accessed here.

• e-Social Science Project

  A group of researchers at the University of Manchester, managed by Gillian Sinclair, is conducting research on e-Social Science, the application of grid technologies to social science research, including economics. They have funded several projects in qualitative data and one of special interest to economists entitled FINGRID. This group is also hosting the First International Conference on e-Social Science at Manchester this summer. For more information, visit the here

• Graph Theory and Network Analysis (Batagelj)

  Vladimir Batagelj maintains a list of pointers to graph theory and network analysis resources (e.g., programs, algorithms, graph formats, data, and visualization tools).

• International Network for Social Network Analysis (INSNA)

  The International Network for Social Network Analysis (INSNA) contains information about INSNA and related subjects, including reference sources, links to related sites, and network software.

• Network Dynamics Bibliography (Crutchfield and Watts)

  The Network Dynamics Bibliography is an on-line bibliography maintained by Jim Crutchfield and Duncan Watts at the Santa Fe Institute that lists pointers to Web sites, books, papers, and reviews related to networks and network dynamics.

• Network Economics (Varian)

  Network Economics is a site maintained by Hal Varian at the University of Berkeley. It provides a briefly annotated list of pointers to Web sites focusing on network issues such: as the impact of the Internet on people, firms, and markets; new economic forces at work in the ever more networked global economy; telecommunications issues (including the Microsoft anti-trust case); network externalities; and technical specs and services.

• Networks and Social Dynamics

  The Social Dynamics Laboratory Group at Cornell University studies the effects of network topology on the dynamics of social interaction.

• Network Effects and Lock-In (Liebowitz)

  The Network Effects maintained by Stanley J. Liebowitz (University of Texas at Dallas) is devoted to network effects, path dependence, and lock-in. In particular, the site provides reviews, commentary, and resources related to a book by Leibowitz et al. titled Winners, Losers, and Microsoft (Independent Institute, March 2001). In the latter, the authors provide a detailed empirical critique of the network effects, path-dependence and lock-in purported to have occurred in the software industry as well as in other often-cited cases (e.g., the triumph of the QWERTY configuration over the Dvorak configuration for typewriter keyboards, and the triumph of the VHS format over the Beta format for videocassette recorders).

• Scale-Free Networks and Small World Networks (INSNA)

  The International Network for Social Network Analysis (INSNA) maintains links to papers and other research resources related to scale-free (power law) networks and small world networks.

• Self-Organized Networks (Barabási)

  Professor Albert-László Barabási (Department of Physics, Notre Dame, Indiana) conducts research focusing on the emergence and evolution of networks in various contexts (e.g., metabolic and genetic networks, actor networks, collaborative networks). For more information about his research, visit here.

• Self-Organizing Innovation Networks (Gilbert)

  Nigel Gilbert (University of Surrey, UK) conducts research on self-organizing innovation networks. For more information, visit here. A key paper on this topic is Nigel Gilbert (University of Surrey, UKB), Andreas Pyka (University of Augsburg, Germany), and Petra Ahrweiler (University of Hamburg, Germany), "Innovation Networks -- A Simulation Approach" (html), Journal of Artificial Societies and Social Simulation, Volume 4, No. 3, 2001.

• Social Network Analysis (Snijders)

  A Social Network Analysis Page is maintained by Tom A. B. Snijders (Department of Sociology, University of Groningen, the Netherlands). The site provides annotated pointers to a variety of downloadable programs for social network analysis developed by Snijders and his collaborators, together with pointers to related articles.

• Social Network Links (White)

  Doug White (Anthropology and Social Science, UC Irvine, Irvine, CA) maintains a listing of Social Network Web Sites that includes galleries, projects, vitae, home pages, articles, journals, associations, newsletters, listservers, and classes related to social network research.

• Virtual Center for Supernetworks (Nagurney)

  A supernetwork is a network consisting of nodes, links (virtual or physical), and flows that is over and above a collection of existing networks. Examples include teleshopping and telecommuting networks. The Virtual Center for Supernetworks at the University of Massachusetts, Amherst, is directed by Anna Nagurney (John F. Smith Memorial Professor, Isenberg School of Management). The primary objective of this interdisciplinary center is to foster the study and application of supernetworks and to serve as a resource to academia, industry, and government on such networks. Resources available at this site include project descriptions, a compilation of software tools, and pointers to related links. For more information, visit here.

• Visualization of Networks

  The Visual Complexity Site provides an astonishing array of network visualizations created by complexity researchers. Types of visualized networks include art, business, computer systems, food webs, the Internet, knowledge networks, music, pattern recognition, political networks, social networks, transportation networks, and the World Wide Web.

Software, Toolkits, and Computer Demos

• Boids - Flocking Creatures (Reynolds)

  Craig Reynolds (Sony, Research and Development Group) maintains a web site titled Boids featuring his simulations of flocking creatures called "boids." His basic flocking model consists of three simple steering behaviors possessed by each individual boid that govern how each boid maneuvers itself based on the positions and velocities of its nearby flockmates. As illustrated by the Java applets at this site, the model results in amazingly life-like collective flocking dynamics. Also available at this site is a link to work by Reynolds on an interactive system permitting user interaction with large groups of autonomous characters. The characters respond in real time to the user's interaction as well as to each other and their environment.

• Computational Laboratories and Demonstration Software (Tesfatsion)

  Leigh Tesfatsion (Economics Department, Iowa State University, Ames) maintains a list of annotated pointers to ACE/CAS Computational Laboratories and Demonstration Software. Included are many demos of possible interest for the agent-based computational modeling of networks (e.g., demos for several distinct versions of the Schelling Segregation Model, a Trade Network Game demo, demos of cellular automata, and demos of flocking behavior).

• Multiple-Agent Modeling Software and Toolkits (Tesfatsion)

  Leigh Tesfatsion (Economics Department, Iowa State University, Ames) maintains an extensive site here providing annotated pointers to general software and toolkits designed specifically for the modeling of systems with multiple interacting agents. Several of the toolkits, for example Repast, provide specific capabilities for the representation and visualization of interaction networks.

• Network Analysis Software (Benta)

  Marius Benta (University College, Cork, Ireland) has developed free application software called Agna for social network analysis, sociometry, and sequential analysis. The purpose of the software is to assist in the study of group communication relations, kinship relations, the structure of animal behavior, and organizational psychology. For more information, visit here.

• Network Visualization (Kempel)

  Lothar Kempel (MPI für Gesellschaftsforschung, Köln, Germany) maintains NetVis: A Gallery of Social Structures. This network visualization site documents work in progress regarding efforts to visualize social structures using a combination of automatic procedures and aesthetics.

• Network Visualization for Real-World Systems

  Visualcomplexity.com maintains an intriguing site devoted to the visual exploration of real-world complex networks.

• Neural Network Toolbox (Mathworks)

  The Mathworks, Inc., has released version 4.0.1 of its Neural Network Toolbox (NNT) for the design and use of artificial neural networks in various practical application settings (e.g., banking and finance, business, credit card activity checking, defense, engineering, electronics, entertainment, industrial, insurance, manufacturing, medical, oil and gas, robotics, speech, securities, telecommunications, and transportation). A printable version of the NNT user's guide is available online in pdf format that provides an introduction to neural networks, help with NNT installation, a discussion of NNT capabilities, and sample applications. For more information, visit here.

• ORA: Social Network Analysis Tool (CASOS)

  ORA is a social network analysis tool that enables the user to simultaneously reason about multiple networks connecting people, knowledge, resources, and tasks (or events). Both traditional and dynamic network measures are included. ORA can be used for risk assessment to locate individuals that are potential risks to the group or organization given one or more of the following types of relational or network information: social; knowledge; resource; and task/event. The GUI is used to set up organization(s) and perform two broad functions: run risk measures on the organization(s); and optimize the organizational structure. ORA is supported by CASOS, the Center for Computational Analysis of Social and Organizational Systems at Carnegie Mellon University. For more information, visit here.

• Schelling Segregation Model (Cook)

  Chris Cook (Computer Science Department, Iowa State University, Ames) has developed an interactive computer demo for an extended version of the Schelling Segregation Model (SSMB), due to Thomas Schelling (Micromotives and Macrobehavior, Norton, 1978). Agents are located on a chess board with 64 locations. The user determines the population mix from among three agent types (red, green, and blue), or chooses from among various default settings. The user can also specify a "happiness rule" for each agent type or select a default setting. The happiness rule determines when an agent is happy with his current board location, taking into account both the number and the types of his neighbors. If unhappy, the agent either attempts to move to a more desirable board location or exits the board altogether.

  Chris Cook has released his SSM demo as freeware under the GNU Public License. Automatic installation software for his SSM demo can be obtained at The Schelling Segregation Model: Demonstration Software Also available at this site is a more detailed description of the SSM, a description of the SSM demo's capabilities, instructions for using the automatic installation software, a link for accessing the SSM demo source code (C#), and copyright information.

• Trade Network Game Lab (Tesfatsion)

  The Trade Network Game Laboratory (TNG Lab) is a computational laboratory for exploring the evolution of trade networks among strategically interacting buyers, sellers, and dealers. The TNG Lab is targeted for the Microsoft Windows desktop and is both modular and extensible. It permits visualization of the formation and evolution of trade networks by means of run-time animations, run-time charts, and run-time data displays. A clear, easily operated graphical user interface permits testing of key parameters pertaining to learning, payoffs, types and numbers of agents, and the physics controlling network displays. Automatic installation software for the TNG Lab, together with tutorials and research articles, can be obtained at the TNG Home Page.

Books and Journals

Books and Monographs on Economic and Social Network Formation

Journal of Economic Interaction and Coordination

Netnomics: Economic Research and Electronic Networking

Networks

Review of Network Economics

Social Networks

Some Early Individual Researchers

Important Disclaimer: Research on social network formation is now so extensive it is impossible to keep the links below either current or complete. These links were last thoroughly updated in 2009 and can be viewed as an historical record of some early researchers in this area.

A

John E. Abraham, (Civil Engineering, University of Calgary, Calgary, Canada): Microsimulation of urban economic and transportation systems for transportation planning, urban planning and policy analysis. Part of a team of Canadian researchers focusing on locational decisions of firms and households and the related decisions of land developers, and how these are influenced by the economic flows/trips that occur among given locations.

Howard E. Aldrich (Sociology, University of North Carolina, Chapel Hill, U.S.A.): Entrepreneurship; Origins of new organizational populations; Organizational evolution.

Holly Arrow (Psychology, University of Oregon, Eugene): Human-subject experiments with endogenous formation of socioeconomic networks; Social psychology

B

Venkatesh Bala (Economics, McGill University, Montreal, Canada): Noncooperative theory of network formation; learning from neighbors; a strategic model of network reliability

Albert-László Barabási (Physics, University of Notre Dame, Indiana): Networks; Internet; Cellular Networks; Parasitic computing.

Jennifer L. Berdahl (Rotman School of Management, University of Toronto): The dynamics of composition and socialization in small groups -- insights gained from a computational model; A theory of groups as complex systems; Dynamics of diversity in work groups

Phillip Bonacich (Professor Emeritus, Sociology, University of California, Los Angeles): Social networks; Evolution of exchange networks.

Steve Borgatti (Organization Studies, Boston College, Massachusetts): Social networks; Knowledge flows in organizations; Network methodology.

Yann Bramoulle (Department of Economics, University of Laval, Quebec, Canada): Interdependent utilities and social networks.

C

Antoni Calvó-Armengol (Economics, ICREA, Universitat Autonoma de Barcelona and CEPR): Bargaining networks; Referral networks; Formation of socioeconomic networks.

Kathleen M. Carley (School of Computer Science, Carnegie Mellon University, Pittsburgh, PA): Computational and social and organization theory; dynamic social networks; multi-agent network models; group, organizational, and social adaptation and evolution; statistical models for dynamic network analysis and evolution; computational text analysis; and the impact of telecommunication technologies on communication and information diffusion within and among groups.

Alessandra Casella (Economics, Columbia University, N.Y.): Trade networks

Dean Corbae (Economics, University of Texas, Austin): Directed matching and monetary exchange; Endogenous market participation.

Margarida Corominas-Bosch (Economics, Universitat Pompeau Fabra, Barcelona): Bilateral trading networks modelled as bargaining models under rigid communication

D

Catherine Dibble (Geography, University of Maryland, College Park): Agent-based simulation; Computational laboratories in economic geography; Formation and effects of socio-economic networks in spatial landscapes; Small-world networks.

Elenna Dugundji (Faculty of Social and Behavioural Sciences, University of Amsterdam, the Netherlands): Land use transportation planning and policy; Long-term effects of multi-modal transportation infrastructure planning and pricing policy in relation to the residential choice behavior of households; Agent-based simulation within the framework of the AMADEUS research program.

Bhaskar Dutta (Economics, Warwick University, UKB): Endogenous formation of networks; Analyzing conflict between stability and efficiency in networks.

E

Victor M. Eguiluz (IMEDEA, Universitat de les Illes Balears, Palma de Mallorca, Spain): Dynamical models of socio-economical network formation and evolution.

F

Marcel Fafchamps (Center for the Study of African Economies, Oxford University, UK): Networks, communities, and markets in Subsahara Africa; Risk sharing in networks in rural Philippines; Market emergence, trust, and reputation.

Giorgio Fagiolo (St. Anna School of Advanced Studies, Pisa, Italy): ACE Labor market dynamics; Local interaction models; Evolution of social and economic networks; Learning; Endogenous interactions; Economics of innovation and technical change.

Linton C. Freeman (Sociology and Institute for Mathematical Behavioral Sciences, University of California at Irvine): Social network analysis; Visualizing social networks; Uncovering organizational hierarchies.

G

Nigel Gilbert (Department of Sociology, University of Surry, UK): Innovation networks; Simulation in the social sciences; Sociology of the environment and science policy.

Sanjeev Goyal (Department of Economics, University of Essex, Colchester, UK): Noncooperative theory of network formation; learning from neighbors; Collaboration and competition in networks; Strategic analysis of network reliability

Amy Greenwald (Computer Science, Brown University, Providence, RI): Learning in network contexts; Automated buyer search on electronic markets; Strategic dynamic pricing by software agents; Game theory.

H

Nobuyuki Hanaki (GREQAM, Aix-Marseille University, France): Co-evolution of individual behaviors and interaction structures; Networks and markets; Dynamics of collaboration networks

Joseph E. Harrington, Jr. (Economics, The Johns Hopkins University, Baltimore, Maryland, U.S.A.): Endogenous networks; Centralization versus decentralization in multi-unit organizations; Progressive ambition, electoral selection, and the creation of ideologues.

Dirk Helbing (Institute for Economics and Traffic, Dresden University of Technology, Germany): Concepts from physics applied to the study of supply networks and business cycles; Pedestrian and vehicle traffic; Sociodynamics and game theory; Econophysics.

Midori Hirokawa (Faculty of Economics, Hosei University, Tokyo): Formation of communities by natives and newcomers; Network design

I

J

Matthew O. Jackson (Economics, Stanford University, CA): Strategic models of social and economic networks; Evolution of social and economic networks; Coalition and Party Formation in legislative voting games; Reputation versus social learning.

K

Raja Kali (Economics, Sam M. Walton College of Business, University of Arkansas, Fayettesville): Institutional foundations of industrial organization; Endogenous business networks as a response to inadequate legal and financial institutions; The role of business networks in the process of economic development; Financial interlinkage and assortative matching.

Maureen Kilkenny (Resource Economics, University of Nevada-Reno): Spatial economics; Computable general equilibrium modelling

Alan Kirman (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix Marseille, France): Market organization and trading relationships; Trade network structures; Endogenous interactions.

Rachel Kranton (Economics, University of Maryland, College Park): A theory of buyer-seller networks; Vertical integration, networks, and markets.

Valdis Krebs (Organizational Consultant, Organizational Network Anaysis, DotCom): Building adaptive organizations in the networked knowledge economy; Organizational network mapping; Terrorist networks.

L

M

Michael W. Macy (Sociology, Cornell University, Ithaca, N.Y.): Informal social control in on-line trading communities; Coalition formation in exchange networks; Trust and cooperation in the U.S. and Japan; Management fads; Collective action; Evolutionary game theory; Deviance and social control; Social psychology; Social Exchange theory; Rational choice.

Filippo Menczer (School of Informatics and Department of Computer Science, Indiana University, Bloomington): Evolutionary agents to model societies and organizations; Referral networks in labor markets; Management networks in organizations.

N

Kai Nagel (Computer Science, TU Berlin): Large-scale agent-based microsimulations for transportation planning; Simulation of the economic decision-making that leads to demand for transportation; General micro-simulation of socio-economic systems.

Matthew G. Nagler (Economics, Lehman College, City University of New YorKB): Network effects of sport utility vehicles; Negative externalities that breed network externalities (i.e. "stick networks" as opposed to "carrot networks"); Consumer behavior.

Anna Nagurney (Finance and Operations Management, University of Massachusetts, Amherst, Massachusetts): Network models of large-scale financial, transportation, and regional economic systems; Algorithms on serial and parallel computer architectures to predict flows of funds, people, goods, and services.

O

John M. Orbell (Professor Emeritus, Political Science, University of Oregon, Eugene): Evolution of cooperation and trust; Coordination issues and social chess; Intersection of evolutionary theory, cognitive science, and the study of human social relations; Evolutionary psychology.

David O'Sullivan (Geography, Penn State University, University Park): Cellular automata and graph based models applied to urban spatial phenomena; Internet geography; Geocomputation and agent-based modelling.

P

Denis Phan (Center for Research in Economics and Management, University of Rennes, France): Global and local effects of interaction structures; Network externalities; Small-world networks, phase transitions, and avalanches in ACE frameworks; Moduleco (an agent-based computational laboratory); Cognitive economics; Generic properties of complex adaptive systems.

Margaret M. Polski (Institute for Development Strategies, Indiana University, Bloomington, and A. T. Kearney, New YorKB): Agent-based modelling; Economic development and institutional change; Innovation and growth in the new economy; Institutional evolution and change in U.S. commercial banking; Legislative games.

Q

R

James E. Rauch (Economics, University of California at San Diego, La Jolla, California): Impact of bureaucratic structure on bureaucratic and economic performance; Incomplete information and networks in international trade; Networks and markets.

S

Giora Slutzki (Computer Science, Iowa State University, Ames): Graph theory; networks and game theory.

Tom A. B. Snijders (Department of Sociology, University of Groningen, the Netherlands): Evolution of social networks; Statistical methods; Simulation models; Random utility; Markov chain Monte Carlo; Simulation-based estimation.

Raphael Suire (Center for Research in Economics and Management, University of Rennes, France): Local interaction models; Social capital; Social networks; Spatial dynamics.

T

Leigh Tesfatsion (Economics, Iowa State University, Ames, Iowa): Agent-based computational economics; The design of restructured wholesale power markets; A computational laboratory for visualizing and analyzing the formation of buyer-seller trade networks under alternative market structures; Market power, hysteresis, and excess earnings heterogeneity in labor markets arising from network and behavioral effects.

Ted Temzelides (Economics, University of Pittsburgh, PA): Directed matching and monetary exchange; Search equilibrium; Learning in market games.

U

Brian Uzzi (Kellogg Graduate School of Management, Northwestern University, Evanston): How professionals, entrepreneurs, and firms develop and use social networks to make markets and manage transactions.

V

Anne van de Nouweland (Economics, University of Oregon, Eugene): Link formation in cooperative situations

Fernando Vega-Redondo (Facultad de Económicas, Universidad de Alicante, Spain): Learning in games; Evolution; Networks; Complex dynamics.

Balázs Vedres (Sociology and Social Anthropology, Central European University): Social and economic transformation from a network perspective; The analysis of the sequences of network events; Inter-organizational and intra-organizational networks; Conceptual and discourse networks.

Nick Vriend (Economics, Queen Mary and Westfield College, University of London): Dynamics of interactive market processes; Emergent properties of evolving market structures and outcomes.

W

Douglas White (Anthropology and Social Science, UC Irvine, Irvine, CA): Social networks and sociocultural complexity; longitudinal fieldsite and network ethnography; cross-cultural comparisons.

Allen Wilhite (Economics, University of Alabama in Huntsville): Small-world networks; Decision making when agents are influenced by the decisions of others.

Ian F. Wilkinson (Marketing, University of Sydney, Australia): Evolution of institutional and network structures; Structural dynamics of industrial networks; the Kauffman NK model.

Randall D. Wright III (Economics, University of Pennsylvania, Philadelphia): Dynamic matching in monetary exchange; Pricing and matching with frictions; Search equilibria.

X

Y

Z

Martin G. Zimmermann (Department of Physics, University of Buenos Aires): Dynamical models of socio-economic network formation and evolution.

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