Why Markets Make Mistakes

Many models of markets are based on assumptions of rationality, transparency, efficiency, and homogeneity in various combinations. They assume, at least implicitly, that decision makers understand the structure of the market and how it produces the dynamics which can be observed or might potentially occur. Are these models acceptable simplifications, or can they be seriously misleading? The research described in this article explains why markets routinely and repeatedly make 'mistakes' that are inconsistent with the simplifying assumptions. System Dynamics models are used to show how misestimating demand growth, allowing financial discipline to lapse, unrealistic business planning, and misperception of technology trajectories can produce disastrously wrong business decisions. The undesirable outcomes could include vicious cycles of investment and profitability, market bubbles, accelerated commoditization, excessive investment in dead-end technologies, giving up on a product that becomes a huge success, waiting too long to reinvent legacy companies, and changes in market leadership. The article illuminates the effects of bounded rationality, imperfect information, and fragmentation of decision making. Decision makers rely on simple mental models which have serious limitations. They become increasingly deficient as problems grow more complex, as the environment changes more rapidly, and as the number of decision makers increases. The amplification and tipping dynamics typical of highly coupled systems, for example, bandwagon, network, and lemming effects, are not anticipated. Examples are drawn from airlines, telecommunications, IT, aerospace, energy, and media. The key conclusions in this article are about the critical roles of behavioral factors in the evolution of markets

Workload fluctuation in management consulting firms.

Massachusetts Institute of Technology. Dept. of Industrial Management. Thesis. 1965. B.S.B.S

Taming the Business Cycles in Commercial Aviation: Trade-space analysis of strategic alternatives using simulation modeling

We investigate the effectiveness of strategic alternatives that are designed to dampen the cyclicality manifest in the commercial aviation related industries. The constituent enterprises of the commercial aviation system exhibit managerial and operational independence and have diverse value functions that often viewed the enterprises to view their competition as a zero-sum game. We argue that this need not always be the case; in the commercial aviation system both airline and airframe manufacturers constituents would benefit from a steadier influx of aircraft that counters the current situation that is characterized by relatively stable demand growth rate for air travel while airline profitability and aircraft ordering fluctuate intensely. In order to identify and evaluate the symbiotic potential, we use a system dynamics model of commercial aviation. After testing several individual strategic alternatives, we find that capacity management is key to cycle moderation for non-collusive strategies. Comparing faster aircraft deliveries to semi-fixed production schedules among other alternatives shows only the latter alternative to be Pareto efficient

Commoditization of technology-based products and services : a generic model of market dynamics

HD28 .M414 no.3887-96,

Business transformation : the key to long term survival and success

Includes bibliographical references (p. 11).HD28 .M414 no.3698-, 94,

1 The dynamics of technological substitutions

Technological substitution is the process by which disruptive technologies replace the dominant ones in an industry. The formulation of classical models of diffusion and substitution impose simplification constraints to reach analytical solvability. We use the system dynamics methodology to build upon existing models by integrating dynamic aspects derived from a broad theoretical framework and to explore the links between social dynamics, technological developments and substitution patterns. Our simulation model generates a substitutive drop in the life cycle which is not replicated by classical models but substantiated by empirical data from various industries. The more general theory embodied in the model allows to better understand the underlying dynamics of technological substitutions. The generic structure can generate the dynamics of a sailing ship effect and account for the non-uniformity of interpersonal communications

Commoditization of technology-based products and services : the base case scenarios for three industries

HD28 .M414 no.4013-98,