Network Formation: General Resources

Last Updated: 11 June 2024

Site Developed By: Leigh Tesfatsion Professor Emerita of Economics Courtesy Research Professor of     Electrical & Computer Engineering Heady Hall 260 Iowa State University Ames, Iowa 50011-1054 https://www2.econ.iastate.edu/tesfatsi/ tesfatsi AT iastate.edu Agent-Based Computational Economics (ACE) Website ACE/ABM Network Formation Research

Table of Contents: Introductory Readings ACE/ABM Network Formation Research Software, Toolkits, and Computer Demos Some Early Individual Researchers

Important Disclaimer: Many excellent network formation resources originally posted at this site have had to be removed due to broken links. Below are annotated links to still-available resources that visitors might find useful and/or of historical interest.

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,1.5MB)

  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 presented to illustrate the specification properties and advantages of incremental networks. In each case a non-incremental model is used for comparison purposes. The first example is pattern classification and compares the supervised growing neural gas model to a conventional radial basis function 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 book), 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, "Networks in the Understanding of Economic Behaviors" (pdf,4.2MB), Journal of Economic Perspectives 28(4), Fall 2014, 3-22.

  Abstract: This study provides an overview of theoretical (analytical) and empirical work on network formation. It does not cover the now-extensive literature on the computational modeling of network formation (html).

• 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.

• Frank Schweitzer, Giorgio Fagiolo, Didier Sornette, Fernando Vega-Redondo, Alessandro Vespignani, and Douglas R. White, "Economic Networks: The New Challenges" (pdf,1.1MB), Science Vol. 325, July 24, 2009, 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."

ACE/ABM Network Formation Research

• 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 open-ended dynamic systems of interacting agents. The site provides annotated pointers to readings, software, individual researchers, and research groups.

• Journal of Economic Interaction and Coordination

Software, Toolkits, and Computer Demos

• Boids - Flocking Creatures (Reynolds)

  Craig Reynolds (Sony, Research and Development Group) developed now-famous simulations of flocking creatures he 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.

• 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.

Some Early Individual Researchers

Important Disclaimer: Research on social network formation is now so extensive it is impossible to maintain an up-to-date list of participants. Below is a listing (circa 2009) of some early individual 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 Analysis, 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 York): 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 York): 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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