Agent-Based IS

RA1: Complex Adaptive System Modeling, Emergent Behavior, and Strategic Simulation

- Theory Building: Understanding Fundamentals of Digital Business Transformation -

This section is dedicated to research on emergent behavior using agent-based IS and laboratory experiments following the tradition of laboratory empirical analysis established by Smith (1962).

Our projects in this research area, RA2, are focused on (1) theory building and (2) solving specific application problems using 'computational explanations' (Kimbrough 2003).

Merriam-Webster Dictionary defines emergence [i-'m&r-j&n(t)s; noun, 1704] as "the act of coming into being through evolution." Emergence has become an important concept in science. One reason is the ever-increasing pace of technological innovation.

Rapid advances in information technology (IT)--such as Moore's law, digital media formats, peer-to-peer architectures, and Web services computing--have become so rapid that certain uses have begun to increase uncertainty and even spark discontinuities or disruption. Often, a new order is seen emerging.

The study of emergent behavior is the subject of many disciplines, with examples that include physics, economics, and the management sciences.

Please listen into this taped discussion on "The Goals of Physics", which was aired on National Public Radio's Science Friday program on Friday, December 14, 2001 (www.npr.org). On this program, three scientists discuss different approaches to research in physics. They are:

Leon Lederman, Pritzker Professor of Science, Illinois Institute of Technology,
David Pines, Physics Professor at the University of Illinois at Urbana-Champaign and a Scientist at Los Alamos National Laboratory's Neutron Science Center Division, and
Chris Quigg, Senior Scientist at Fermi National Accelerator Laboratory in Batavia, Illinois.

Approximately 6 1/2 minutes into the discussion you can listen to a comprehensive description of the concept of "Emergent Behavior."

Across many industries strategies, structures, and business economics appear to be changing, again. This time change is enabled by the success of digital interactive technology such as the Internet protocols, the MP3 audio format, and Web services computing. In the pre-industrial age it was the arrival of the steam engine, the railroad, and the telegraph that changed the organization of economic activities.

In the pre-industrial age manufacturers made goods to order and sold them locally to the end user. The arrival of new manufacturing, transportation and communication systems challenged this integration of production and distribution under single ownership (Chandler 1990). The new technology allowed to reduce unit cost by sharply increasing output of homogenous products. Eager to offer products at low cost manufacturers increased output and had to rely on distributors in order to market and sell it. Hence, distribution emerged as a separate stage in the industry value system; or in other words, in response to new technology the industry had disaggregated into the two distinct stages of manufacturing and distribution.

Today, with digital media formats, peer-to-peer information systems architectures and Web services technology business executives are facing again deep structural changes in their industries (Schlueter-Langdon 2001).

What structure will emerge and how is not well understood yet. Therefore, implications for specific industries and firms are still fuzzy. "The fact that the New Economy is real, however, doesn't mean that we've understood it" says Joseph Stiglitz--a former chief economist of the World Bank, a former chairman of the Council of Economic Advisers, and Nobel laureate (2002, 88).

Historically, products have disappeared and entire industries have died. Schumpeter called this transformation process "creative destruction" to denote a "process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one. This process of creative destruction is the essential fact about capitalism" (1975, 83).

There are already some early victims of this transformation from analog systems to digital technology, and from narrowband to broadband communication links. Examples include Polaroid and The Encyclopedia Britannica.

One of the key strategic business decisions in digital business transformation are integration choices--or "make or buy" decisions: Should a company be focused (or specialized) or vertically integrated (for example into electronic distribution or channel systems)?

Economic theory and the information systems literature suggest that new information systems can be used to lower transaction cost, making market coordination less costly than when a bureaucracy or hierarchy is established and maintained (Coase 1937, Williamson 1975, Malone et al. 1987). Examples of such information technology include Web services (Hars and Schlueter-Langdon 2002), and electronic markets (Bakos 1991, Lee and Clark 1996), which have emerged in many industries (i.e., Bakos 1998, Choudhury et al. 1998). Firms have the opportunity to focus on the few business activities at which they excel and to outsource everything else to similarly focused specialists. The advantage of specialization strategy is also supported in the strategy literature. Prahalad and Hamel, for example, have emphasized specialization strategy as a focus on the corporation's core competence (1990).

However, success with specialization strategy depends not only on a firm's information systems (IS) strategy--or choice of information technology (IT) components--and its proper implementation, but also on the extent of industry-level integration. First, with regard to the "make or buy" question, there may be nothing to buy. Suppliers may not exist. In the economics literature, this is often referred to as a "closed" industry (Farrell et al. 1998). Second, even in an "open" system, defined as a "regime when firms add one stage of value and put the results back in the market, rather than controlling a longer segment of the value chain" (Farrell et al. 1998, 150), if there are too few suppliers, they could use their market power to make inputs prohibitively expensive or refuse to sell inputs at all. These coordination problems are known in the economics literature as the small numbers bargaining problem and market foreclosure, respectively (Whinston 1990, Ordover et al. 1990).

The complication with the research problem at hand arises from the endogeneity of industry structure: Firms decide on an IS strategy and select IT in order to support their specialization strategy, the success of which depends, among other things, on the structure of the industry (Porter 1979, 1980). The industry structure, in turn, is the result of the behavior of individual firms and their adoption of information technology favoring specialization.

This complication is at the core of many other problems, such as standardization battles.

We have formalized this problem as a complex adaptive system because it allows us to model industry structure and transaction cost as endogenous variables. The behavior of firms and their interaction is based on micro-economic cost theory and the theory of non-cooperative games. Experiments have been conducted using discrete event simulation.

This approach follows the tradition of laboratory experiments as a tool in empirical economic analysis established by Smith. He pioneered tests of predictions from economic theory by way of laboratory experiments (Smith 1962; overview in Kagel and Roth 1995). Smith "initiated the use of the laboratory as a “wind tunnel” (a laboratory setup used to test prototypes for aircraft) in order to study the performance of proposed institutional mechanisms for deregulation, privatization, and the provision of public goods" (The Royal Swedish Academy of Sciences 2002, 9).

Please listen into Vernon Smith's Prize Lecture "Constructivist and Ecological Rationality in Economics," December 8, 2002, at Aula Magna, Stockholm University.

Bakos, Y. J. 1991. A strategic analysis of electronic marketplaces. MIS Quarterly 15(3) (September): 295-310.

Bakos, Y. J. 1998. The emerging role of electronic marketplaces on the Internet. Communications of the ACM 41(8) (August): 35-42.

Birch, D. J., and E. Burnett-Kant. 2001. Unbundling the Unbundled. The McKinsey Quarterly, Number 4 [electronic document] (accessed 11/24/01); available at http://www.mckinseyquarterly.com; Internet.

Chandler, A. D. 1990. Scale and Scope--The Dynamics of Industrial Capitalism. Belknap/Harvard University Press: Cambridge, MA.

Choudhury, V., K. S. Hartzel, and B. R. Konsynski. 1998. Uses and consequences of electronic markets: An empirical investigation in the aircraft parts industry. MIS Quarterly 22 (4): 471-507.

Farrell, J., H. K. Monroe, and G. Saloner. 1998. The vertical organization of industry: Systems competition versus component competition. Journal of Economics and Management Strategy 7(2) (Summer): 143-182.

Hars, A., and Schlueter-Langdon, C. 2002. Opportunities and risks of distributed systems architectures. Information Management and Consulting (5:3), pp. 13-20.

Kagel, J. H., and A. E. Roth (eds.). 1995. Handbook of Experimental Economics. Princeton
University Press: Princeton.

Kimbrough, S. O. 2003. Computational Modeling and Explanation. In: Bhargava, H. K., and N. Ye (eds.). Computational Modeling and Problem Solving in the Networked World. Kluwer Academic Publishers: Boston/London.

Lee, H. G., and T. H. Clark. 1996. Process reengineering through electronic market systems: Opportunities and challenges. Journal of Management Information Systems 13 (3) (Winter): 113-136.

Malone, T. W., J. Yates, and R. I. Benjamin. 1987. Electronic Markets and Electronic Hierarchies. Communications of the ACM 30(6) (June): 484–497.

Ordover, J., G. Saloner, and S. Salop. 1990. Equilibrium vertical foreclosure. American Economic Review 80: 127-142.

Porter, M. E. 1979. How competitive forces shape strategy. Harvard Business Review (March-April): 137-145.

Porter, M. E. 1980. Competitive Strategy: Techniques For Analyzing Industries and Competitors. The Free Press: New York, NY.

Pralahad, C. K., and G. Hamel. 1990. The core competence of the corporation. Harvard Business Review (May-June): 79-91.

The Royal Swedish Academy of Sciences. 2002. Foundations of Behavioral and Experimental Economics:
Daniel Kahneman and Vernon Smith. Advanced information on the Prize in Economic Sciences 2002 (December 17) [electronic document] (accessed 08/01/03); available at http://www.nobel.se/economics/laureates/2002/ecoadv02.pdf.

Schlueter Langdon, C. 2001. Elektronische Märkte und Netze ändern Industriestrukturen [Electronic Markets and Networks Change Industry Structures]. In: Schmidt, H. (eds.). Die Potentiale der Internet Ökonomie--Neue Regeln bestimmen die digitale Wirtschaft [The Potenital of the Internet Economy--The new rules of digital business]. Frankfurter Allgemeine Buch: Frankfurt, 63-68.

Smith, V. L. 1962. An experimental study of competitive market behavior. Journal of
Political Economy 70: 111-137.

Schumpeter, J. A. 1975. Capitalism, Socialism and Democracy. Harper: New York [orig. pub. 1942]

Whinston, M. 1990. Tying, foreclosure, and exclusion. American Economic Review 80: 837-859.

Williamson, O. E. 1975. Markets and Hierarchies: Analysis and Antitrust Implications. The Free Press: New York, NY.