Howard E. Aldrich, Organizations Evolving, Sage Publications,
From the publisher: "Howard E. Aldrich charts the development of
organizational forms and assesses the impact on these of external innovations
such as changing technology and globalization. New theories of knowledge and
entrepreneurship are woven into the analysis, together with fresh
interpretations of data."
Howard E. Aldrich is Professor of Sociology at the University of North
Kenneth J. Arrow, The Limits of Organization, Norton, New York,
Jason Barr and Francesco Saraceno, "A Computational Theory of
the Firm,"Journal of Economic Behavior and Organization 49
Kathleen M. Carley, "A Comparison of Artificial and Human
Organizations,"Journal of Economic Behavior and Organization
31 (1996), 175-191.
Abstract: This paper presents results from an artificial organization project and demonstrates how contrasting models with each other and with empirical data can facilitate the development of more veridical organizational models. Specifically, this paper examines whether certain organizational models, differing only with respect to the cognitive limitations and adaptability or general intelligence of the agents, are better or worse predictors of the behavior of similar organizations composed of humans.
A. D. Chandler, "What is a Firm? A Historical Perspective,"European Economic Review 36 (1992), 483-494.
Joseph E. Harrington, Jr.,
"Agent-Based Models of Organizations",
pp. 1272-1337 in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland, Amsterdam,
the Netherlands, 2006.
The agent-based approach views an organization as a collection
of agents, interacting with one another in their pursuit of assigned
tasks. The performance of an organization in this framework is
determined by the formal and informal structures of interactions
among agents, which define the lines of communication, allocation of
information processing tasks, distribution of decision-making
authorities, and the provision of incentives. This chapter provides
a synthesis of various agent-based models of organizations and
surveys some of the new insights that are being delivered. The
ultimate goal is to introduce the agent-based approach to economists
in a methodological manner and provide a broader and less
idiosyncratic perspective to those who are already engaging in this
line of work. The chapter is organized around the set of research
questions that are common to this literature: 1) What are the
determinants of organizational behavior and performance? 2) How does
organizational structure influence performance? 3) How do the skills
and traits of agents matter and how do they interact with structure?
4) How do the characteristics of the environment -- including its
stability, complexity, and competitiveness -- influence the
appropriate allocation of authority and information? 5) How is the
behavior and performance influenced when an organization is
coevolving with other organizations from which it can learn? 6) Can
an organization evolve its way to a better structure?
Stephen Decanio, Catherine Dibble, and Keyvan Amir-Atefi, "The
Importance of Organizational Structure for the Adoption of
Innovations,"Management Science 46(10) (2000), 1285-1299.
Giovanni Dosi and F. Malerba (eds.), Organization and
Strategy in the Evolution of Enterprise, MacMillan Press,
Jacques Ferber, Olivier Gutknecht, and Fabien Michel, "From Agents to Organizations: An Organizational View of Multi-Agent Systems"(pdf,415KB),
pp. 214-230 in P. Giorgini, J. Mueller, and J. Odell (eds.), Agent-Oriented Sofware Engineering (AOSE) IV, Melbourne, Australia, 2004.
While multi-agent systems seem to provide a good basis for
building complex software systems, this paper points out some of the drawbacks of classical "agent-centered" multi-agent systems. To resolve these difficulties we claim that organization centered multi-agent system, or OCMAS for short, may be used. We propose a set of general principles from which true OCMAS may be designed. One of these principles is not to assume anything about the cognitive capabilities of agents. In order to show
how OCMAS models may be designed, we propose a very concise and minimal OCMAS model called AGR, for Agent/Group/Role. We propose a set of notations and a methodological framework to help the designer to build MAS using AGR. We then show that it is possible to design multi-agent systems using only OCMAS models."
Guido Fioretti, "Agent-Based Models of Industrial Clusters and
March 2005, published in Contemporary Issues in Urban and Regional Economics, edited by Frank Columbus, Nova Science Publishers.
Abstract: "Agent-based models, an instance of a wider
class of connectionist models, allow bottom-up simulations of organizations
constituted by a large number of interacting parts. Thus, geographical
clusters of competing or complementary firms constitute an obvious field of
application. This contribution explains what agent-based models are, reviews
applications in the field of industrial clusters, and focuses on a simulator
of infra- and inter-firm communication."
Nicolai J. Foss, "The Rhetorical Dimensions of Bounded Rationality:
Herbert A. Simon and Organizational Economics"(pdf preprint,140KB),
Working Paper No. 2002-07, Department of Industrial Economics and Strategy, Copenhagen Business School, Denmark, April 2002. Published in S. Rizzello (ed), Cognitive Paradigms in Economics, Routledge, 2002.
D. R. Ilgen and C. L. Hulin (eds.), Computational Modeling of Behavior
in Organizations: The Third Scientific Discipline, American Psychological
Association, Washington, DC, 2002.
A. Lomi and E. R. Larsen (eds.), Dynamics of Organizations:
Computational Modeling and Organizational Theories, AAAI Press, New York,
Thomas A. Marschak and Roy Radner, Economic Theory of
Teams, Yale University Press, New Haven, 1972.
John A. Mathews, "Strategizing vs. Economizing: Theorizing Dynamic Competitive Behavior in
Disequilibrium," Working Paper 17-11-02, Aarhus School of Business,
Denmark, November 2002.
Abstract: "This paper is addressed to the fundamentals of what
is meant by the competitive behavior of firms. The problem is that much of
the interesting work in strategy that documents behavior by firms at the
frontiers of biotechnology, ICTs, and other knowledge-intensive sectors, both
individually and in networks and clusters, seems to escape the frameworks of
traditional strategizing discourse. An approach is proposed, and explored,
which involves formulating all strategizing behavior as taking place in
disequilibrium, where positive entrepreneurial profits can be earned, and
contrasting this with economizing behavior, seen as revolving around perfectly
competitive equilibrium (PCE), where by definition all entrepreneurial
profits are zero. ... The paper closes by contrasting this approach, which
is Schumpeterian (Joseph Schumpeter), Knightian (Frank Knight), and Penrosian
(Edith Penrose) in inspiration, with the language of strategizing based on
Bart Nooteboom, Learning and Innovation in Organizations and
Economies, Oxford University Press, 2000, 343 pages, ISBN:
From the Author: "This book seeks to develop a heuristic of
discovery. How does novelty arise, and how can it arise in such a way that
exploitation and exploration can be combined? An attempt is also made to
connect the levels of individual learning, organizational learning, and
innovation in industries or `innovation systems.' Building blocks for this
endeavor are sought in economics, sociology, and cognitive science."
Barte Nooteboom is with the Rotterdam School of Management at the
Erasmus University Rotterdam.
Elinor Ostrom, "Collective Action and the Evolution of Social
Norms,"Journal of Economic Perspectives 14 (2000), 137-158.
Michael J. Prietula, Kathleen M. Carley, and Les Gasser, Simulating
Organizations: Computational Models of Institutions and Groups,
The MIT Press, Cambridge, MA, 1998.
S. T. Seitz, C. L. Hulin, and K. A. Hanish, Simulating Withdrawal
Behaviors in Work Organizations: An Example of a Virtual Society,
Nonlinear Dynamics, Psychology, and Life Sciences 4 (2000), 33-65.
Herbert Simon, The Sciences of the Artificial, Second
Edition, The MIT Press, Cambridge, MA, 1982.
Timothy Van Zandt, "Organizations with an Endogenous Number of
Information Processing Agents," pp. 239-305 in M. Majumdar (ed.),
Organizations with Incomplete Information, Cambridge
University Press, Cambridge, UK, 1998.
Oliver E. Williamson and Sidney G. Winter (eds.), The Nature
of the Firm: Origins, Evolution, and Development, Oxford
University Press, New York, 1993.
Esben S. Andersen
(Business Studies, Aalborg University, Denmark): Economic organization
(knowledge creation, specialisation, and networks); Evolutionary modelling
and simulation; History of economic analysis, with a focus on Schumpeterian
(Institute for Software Research, Carnegie Mellon University,
Pittsburg, PA): Computational organizational theory; Social organizational
knowledge and information networks; How social networks, knowledge networks,
and informational networks interact to influence the emergence of groups.
(Department of Economics, Cleveland State University, Ohio):
Industrial organization; Computational organization theory; Multi-agent
adaptive systems; Applied game theory.
(Library and Information Science, University of Illinois at
Urbana-Champaign): Technical and social aspects of organization-scale
information processing; Intelligent multi-agent systems; Enterprise
integration for continuously-learning agile firms.
(Department of Economics, Johns Hopkins University, Baltimore):
Industrial organization; Political economy; Evolutionary economics; Game
(Algorithmics Group, Department of Software Technology, Delft University of Technology, the Netherlands): Computational economic organization; Governance and matching; Market design.
J. Peter Murmann
(Australian School of Business, University of New South Wales, Australia):
Evolutionary theory in management and organization theory; Evolutionary
theories in the social sciences.
(Rotterdam School of Management, Erasmus University, Rotterdam, The
Netherlands): Organizational dynamics; Agent-based transaction cost
economics; New institutional economics.
Elinor Ostrom (died 6/12/2012), long-time Professor of Political Science, Workshop in Political Theory and Policy
Analysis at Indiana University, Bloomington, IN: Common pool resource usage; Collective decision-making.
(Department of Political Science, University of Chicago, Illinois, U.S.A.):
Emergent organization; Rise of the Medici, 1400-1434; Plea bargaining;
Federal budget process.
Michael J. Prietula
(Department of Information Analysis, Goizueta Business School, Emory University, Atlanta, Georgia): Computational organizational
theory; Information systems; Cognitive science/human expertise.
(School of Computer Science, The University of Nottingham, UK): Application of agent-based modeling and simulation to study human-centric complex adaptive systems.