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Models of Bounded Rationality: Empirically Grounded Economic Reason
Abstract
Offering alternative models based on such concepts as satisficing (acceptance of viable choices that may not be the undiscoverable optimum) and bounded rationality (the limited extent to which rational calculation can direct human behavior), Simon shows concretely why more empirical research based on experiments and direct observation, rather than just statistical analysis of economic aggregates, is needed.Throughout Herbert Simon's wide-ranging career—in public administration, business administration, economics, cognitive psychology, philosophy, artificial intelligence, and computer science—his central aim has been to explain the nature of the thought processes that people use in making decisions.The third volume of Simon's collected papers continues this theme, bringing together work on this and other economics-related topics that have occupied his attention in the 1980s and 1990s: how to represent causal ordering formally in dynamic systems, the implications for society of new electronic information systems, employee and managerial motivation in the business firm (specifically the implications for economics of the propensity of human beings to identify with the goals of organizations), and the state of economics itself.Offering alternative models based on such concepts as satisficing (acceptance of viable choices that may not be the undiscoverable optimum) and bounded rationality (the limited extent to which rational calculation can direct human behavior), Simon shows concretely why more empirical research based on experiments and direct observation, rather than just statistical analysis of economic aggregates, is needed.The twenty-seven articles, in five sections, each with an introduction by the author, examine the modeling of economic systems, technological change: information technology, motivation and the theory of the firm, and behavioral economics and bounded rationality.
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“AI's data-centric approach often clashes with human decision-making, which relies on personal understanding, logic, heuristics, and creativity [31, 36, 46, 110, 111].”
From Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making (2025) · cites this paper as [111]
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Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.
Tversky, A., & Kahneman, D. (1983) · Psychological Review · doi:10.1037/0033-295x.90.4.293 · Cited by 3,991
Reasoning the fast and frugal way: Models of bounded rationality.
Gigerenzer, G., & Goldstein, D. G. (1996) · Psychological Review · doi:10.1037/0033-295x.103.4.650 · Cited by 3,504
Representativeness revisited: Attribute substitution in intuitive judgment.
Kahneman, D., & Frederick, S. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.004 · Cited by 3,476
Being there: putting brain, body, and world together again
(1997) · Choice Reviews Online · doi:10.5860/choice.34-6204 · Cited by 2,631
Slovic, P., Finucane, M., Peters, E., & MacGregor, D. G. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.025 · Cited by 2,349
Metadata
- Authors
- Simon, H. A.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 1997
- OpenAlex
- W1510672157
- Cited by
- 4,205
- References
- 0
- FWCI
- 30.86
- Type
- book
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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