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Journal articles on the topic 'Bounded rationality'

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Published: 4 June 2021
Last updated: 8 June 2024

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1

Ballester Pla, Coralio, and Penélope Hernández. "Bounded Rationality." Revista Internacional de Sociología 70, Extra_1 (February 14, 2012): 27–38. http://dx.doi.org/10.3989/ris.2011.10.20.

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2

Aumann, Robert J. "Rationality and Bounded Rationality." Games and Economic Behavior 21, no. 1-2 (October 1997): 2–14. http://dx.doi.org/10.1006/game.1997.0585.

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3

Grüne-Yanoff, Till. "Bounded Rationality." Philosophy Compass 2, no. 3 (May 2007): 534–63. http://dx.doi.org/10.1111/j.1747-9991.2007.00074.x.

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4

Jones, Bryan D. "BOUNDED RATIONALITY." Annual Review of Political Science 2, no. 1 (June 1999): 297–321. http://dx.doi.org/10.1146/annurev.polisci.2.1.297.

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5

Lilly, Gregory. "Bounded rationality." Journal of Economic Dynamics and Control 18, no. 1 (January 1994): 205–30. http://dx.doi.org/10.1016/0165-1889(94)90076-0.

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6

ZHENG, ZIYU. "FROM RATIONALITY TO BOUNDED RATIONALITY*." Australian Economic Papers 44, no. 4 (December 2005): 455–74. http://dx.doi.org/10.1111/j.1467-8454.2005.00270.x.

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7

Friedman, Daniel, and Ariel Rubinstein. "Modeling Bounded Rationality." Southern Economic Journal 65, no. 2 (October 1998): 366. http://dx.doi.org/10.2307/1060679.

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8

Correa, Romar. "Bounded Social Rationality." Journal of Interdisciplinary Economics 10, no. 3 (July 1999): 169–75. http://dx.doi.org/10.1177/02601079x99001000301.

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9

Broadbent, Donald E. "(Un)Bounded Rationality." Contemporary Psychology: A Journal of Reviews 30, no. 4 (April 1985): 263–65. http://dx.doi.org/10.1037/023691.

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10

Skidd, David R. A. "Revisiting Bounded Rationality." Journal of Management Inquiry 1, no. 4 (December 1992): 343–47. http://dx.doi.org/10.1177/105649269214011.

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11

Board, Raymond. "Polynomially Bounded Rationality." Journal of Economic Theory 63, no. 2 (August 1994): 246–70. http://dx.doi.org/10.1006/jeth.1994.1042.

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12

Sperry-Taylor, Ashton T. "Bounded Rationality in the Centipede Game." Episteme 8, no. 3 (October 2011): 262–80. http://dx.doi.org/10.3366/epi.2011.0021.

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AbstractNormative game theory unsatisfactorily explains rational behavior. Real people do not behave as predicted, and what is prescribed as rational behavior is normally unattainable in real-life. The problem is that current normative analysis does not account for people's cognitive limitations – their bounded rationality. However, this paper develops an account of bounded rationality that explains the rationality of more realistic behavior. I focus on the Centipede Game, in which boundedly rational players explore and test others' immediate behavior, until they can apply limited backward induction. The result is that the game has a solution in the form of a subjective Nash equilibrium, which boundedly rational players can possibly realize.
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13

MOGA, Horațiu, Andrei LUCHIAN, and Razvan BOBOC. "TOWARD A BOUNDED RATIONALITY APPROACH OF CYBERWARFARE." Review of the Air Force Academy 17, no. 1 (May 24, 2019): 19–28. http://dx.doi.org/10.19062/1842-9238.2019.17.1.3.

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14

Mills, Terence C., and T. J. Sargent. "Bounded Rationality in Macroeconomics." Journal of the Royal Statistical Society. Series A (Statistics in Society) 157, no. 3 (1994): 510. http://dx.doi.org/10.2307/2983545.

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15

Novikov, D. A. "Bounded Rationality and Control." Automation and Remote Control 83, no. 6 (June 2022): 990–1009. http://dx.doi.org/10.1134/s0005117922060145.

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16

Sheffrin, Steven M., and Thomas J. Sargent. "Bounded Rationality in Macroeconomics." Economica 62, no. 245 (February 1995): 134. http://dx.doi.org/10.2307/2554781.

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17

Vaughan, Mark D., and Thomas Sargent. "Bounded Rationality in Macroeconomics." Southern Economic Journal 62, no. 1 (July 1995): 298. http://dx.doi.org/10.2307/1061418.

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18

Cristofaro, Matteo. "Herbert Simon’s bounded rationality." Journal of Management History 23, no. 2 (April 10, 2017): 170–90. http://dx.doi.org/10.1108/jmh-11-2016-0060.

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Purpose The purpose of this paper is to investigate the historical advancements attained on the bounded rationality concept in management research, considering the key influencing discoveries in related fields. Understanding the cross-fertilization that has occurred is the first step to go beyond the current knowledge on bounded rationality and to face its challenges. Design/methodology/approach The adopted method is historical. This research approach helps to explain the evolution of a widespread concept in a scientific field and, particularly, to identify the parallel influencing advancements made in related domains. Findings Investigation of the irrational forces of human reasoning is at the centre of today’s research agenda on rationality in organizations, claiming to be an extension of the original bounded rationality concept. In this regard, scholars should commit themselves to build a more holistic approach to the investigation of human rationality, conjointly applying socio-biological and behavioural perspectives to explain the real behaviour of people in organizations and society. This reconnection will also help to overcome the inner limits of some “fashion of the month” streams that have yet to demonstrate their contribution. Originality/value This is the first study that offers an overall historical evolution of the bounded rationality concept which considers both management research and developments in related fields. The historically educed lessons learned are at the basis of the concluding recommendations for future research.
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19

Williamson, Paul. "Learning and Bounded Rationality." Journal of Economic Surveys 11, no. 2 (December 16, 2002): 221–30. http://dx.doi.org/10.1111/1467-6419.00031.

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20

Abrahamian, Andray. "North Korea's Bounded Rationality." Survival 61, no. 1 (January 2, 2019): 141–60. http://dx.doi.org/10.1080/00396338.2019.1568048.

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21

Grabiszewski, Konrad. "Rationalizing epistemic bounded rationality." Theory and Decision 78, no. 4 (June 24, 2014): 629–37. http://dx.doi.org/10.1007/s11238-014-9455-y.

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22

Nyarko, Yaw, Michael Woodford, and Nicholas C. Yannelis. "Bounded rationality and learning." Economic Theory 4, no. 6 (November 1994): 811–20. http://dx.doi.org/10.1007/bf01213813.

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23

Evans, Jonathan St B. T. "Reasoning with Bounded Rationality." Theory & Psychology 2, no. 2 (May 1992): 237–42. http://dx.doi.org/10.1177/0959354392022011.

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24

De Vany, Arthur. "Bounded rationality in macroeconomics." Journal of Economic Dynamics and Control 20, no. 5 (May 1996): 811–17. http://dx.doi.org/10.1016/0165-1889(95)00876-4.

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25

Новиков, Дмитрий Александрович, and Dmitriy Novikov. "Bounded Rationality and Control." Mathematical Game Theory and Applications 14, no. 1 (January 18, 2023): 49–84. http://dx.doi.org/10.17076/mgta_2022_1_44.

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The rationality constraint condition is formulated, which states that when solving control, computing and communication problems ($C^3$) together, real-time requirements may not make it possible to find the optimal solution (control action), forcing the use of almost optimal solutions (the best found with the existing restrictions on the search procedure). This condition connects and demonstrates the unity and deep interconnection of such concepts common in management and optimization as: necessary diversity, limited rationality, analytical complexity, heuristics, records in real-time optimization. In relation to the problem of institutional management of organizational and technical systems, a number of examples of solving problems of minimizing error or complexity, as well as searching for: critical bandwidth of the communication channel, critical computing rate and the maximum number of controlled subsystems are given.
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26

Milov, O., O. Korol, and V. Khvostenko. "DEVELOPMENT OF THE CLASSIFICATION OF THE CYBER SECURITY AGENTS BOUNDED RATIONALITY." Системи управління, навігації та зв’язку. Збірник наукових праць 4, no. 56 (September 11, 2019): 82–90. http://dx.doi.org/10.26906/sunz.2019.4.082.

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The subject are the bounded rationality agents of cyber security system. The purpose of this work is is to build a classification system for agents of a cybersecurity system with limited rationality. The tasks: consideration of the decisionmaking process by agents in cybersecurity systems, analysis of various manifestations of bounded rationality of agents of the cybersecurity system, introduction of classification features of bounded rationality, formal presentation of bounded rationality of various types, combining agents with various types of bounded rationality into a whole classification system. Results. Presents approaches to the classification of the concept of rationality in relation to cybersecurity systems. Such types of rationality are considered as strong, semi-strong, weak. Further classification of types of rationality is carried out on the basis of the place of manifestation of rationality. For this, the decision-making process in the cybersecurity system has been considered, formal relations have been introduced, which characterize its various stages. Such types of bounded rationality as informational, methodological, predictive, evaluative and conditional are considered. The ratio of the considered types of rationality is presented. Conclusion: A comparison of various types of bounded rationality, based primarily on its place in the decision-making process, made it possible to propose a classification scheme of bounded rationality characteristic of agents of the cybersecurity system. The result of the formalization of the description of bounded rationality is presented, which can be used as the basis for the development of models of behavior of interacting agents of cybersecurity systems.
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27

Spiegler, Ran. "‘BUT CAN'T WE GET THE SAME THING WITH A STANDARD MODEL?’ RATIONALIZING BOUNDED-RATIONALITY MODELS." Economics and Philosophy 27, no. 1 (January 18, 2011): 23–43. http://dx.doi.org/10.1017/s0266267110000453.

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This paper discusses a common criticism of economic models that depart from the standard rational-choice paradigm - namely, that the phenomena addressed by such models can be ‘rationalized’ by some standard model. I criticize this criterion for evaluating bounded-rationality models. Using a market model with boundedly rational consumers due to Spiegler (2006a) as a test case, I show that even when it initially appears that a bounded-rationality model can be rationalized by a standard model, rationalizing models tend to come with unwarranted ‘extra baggage’. I conclude that we should impose a greater burden of proof on rationalizations that are offered in refutation of bounded-rationality models.
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28

Gal, Michal S. "Is Bounded Rationality in Entry Decisions Necessarily Bad for Social Welfare?" Antitrust Bulletin 61, no. 4 (November 17, 2016): 541–45. http://dx.doi.org/10.1177/0003603x16676141.

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In the article Boundedly Rational Entrepreneurs and Antitrust, Professor Tor provides an excellent overview of the effects of bounded rationality on the behavior of entrepreneurs in the marketplace. In this short note, I offer some observations on the article. In particular, it suggests several additional parameters that might be worth exploring before we can reach a conclusion about the role that bounded rationality plays in economically irrational entry decisions. It also suggests some factors that should be weighed before determining whether irrational entry is socially harmful. Finally, the note provides several observations with regard to regulation, including the effects of algorithmic applications on bounded rationality decisions by entrepreneurs.
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29

Schilirò, Daniele. "Economic Decisions and Simon’s Notion of Bounded Rationality." International Business Research 11, no. 7 (June 15, 2018): 64. http://dx.doi.org/10.5539/ibr.v11n7p64.

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Decision making in economics has been always intertwined with the concept of rationality. However, neoclassical economic literature has been dominated by a specific notion of rationality, namely, perfect rationality, characterized by the assumption of consistency and by the maximization hypothesis. Herbert Simon, in his long research activity, questioned this concept of perfect or global rationality, suggesting a different vision, based on empirical evidence and regarding an individual’s choices. He challenged the neoclassical theory of global rationality, suggesting his notion of bounded rationality, a satisficing (instead of optimizing) behavior, and the relevance of procedural rationality to understand the process of thought of decision makers.Thus, this paper focuses on Simon’s notion of bounded rationality, since bounded rationality remains the hallmark of his theoretical contribution. First, the paper examines the economic decision process in the neoclassical theory and Simon’s notion of bounded rationality. Then, it analyzes in depth Simon’s behavioral model of rational choice, underlining the relevance of satisficing behavior and procedural rationality. Finally, it suggests an assessment of the concept of bounded rationality.
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30

Malone, David. "Workload Distribution Within An Extensive Case Pedagogy: A Competitive Bidding Strategy." College Teaching Methods & Styles Journal (CTMS) 1, no. 3 (July 22, 2011): 13. http://dx.doi.org/10.19030/ctms.v1i3.5235.

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This paper presents a bidding strategy that may be incorporated into case-intensive courses. The purpose of the bidding process is to equitably distribute credit when students are assigned cases of differing degrees of difficulty. The paper also collects data to help answer a basic research question regarding this device: Is there evidence of bounded rationality among students in executing their bidding strategies? While there does appear to be evidence of some bounded rationality, the bidding mechanism appears to distribute workload and credit rationally.
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31

Zhang, Peilin. "Changes in Modern Urban Planning Teaching and Theory." Open House International 44, no. 3 (September 1, 2019): 40–43. http://dx.doi.org/10.1108/ohi-03-2019-b0011.

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In order to further optimize the methods of modern urban planning, the philosophical basis, planning theory, planning measures and practice are analyzed, and some discussions are made in connection with China's planning practice. The research results show that the core of modern urban planning is constructed by traditional rationalism with classical physics as its core. Urban planning is both a technology and a social science. Whether it is traditional or modern urban planning, it has been closely linked with the legal system since its birth. It is an important direction to promote the development of urban planning discipline. The most influential rational ideas of city planning are instrumental rationality, bounded rationality and communicative rationality. Instrumental rationality derives from rational comprehensive planning, systematic planning and procedural planning; the separation-gradualism and hybrid inspection model are developed under the influence of bounded rationality and are amendments to instrumental rationality; communication planning, collaborative planning and consultative planning are developed on the basis of communicative rationality, which is one of the important development directions at present.
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32

DeMoor, Michael J. "Societal Rationality: Bounded or Embedded?" Philosophia Reformata 84, no. 2 (November 11, 2019): 171–93. http://dx.doi.org/10.1163/23528230-08402001.

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This paper offers a characterization and critique of the idea of bounded rationality and its consequences for public policy. It offers an alternative way of accounting for the crucial features of human rationality that bounded rationality sees, using categories inspired by the Reformational philosophy of Herman Dooyeweerd and others, and then shows how this alternative account of the “bounds” of human rationality points toward an alternative orientation toward public policy-making.
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33

Huang, Tingliang, Zhe Yin, and Ying-Ju Chen. "Managing Posterior Price Matching: The Role of Customer Boundedly Rational Expectations." Manufacturing & Service Operations Management 19, no. 3 (July 2017): 385–402. http://dx.doi.org/10.1287/msom.2016.0612.

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The posterior price-matching policy, whereby a firm promises to reimburse the price difference to a customer who purchases a product before the firm marks it down, has been used in practice. The extensive literature has offered the following explanations for why posterior price matching is adopted: to reduce inventory, to soften competition, to price discriminate consumers, and to eliminate consumer strategic waiting incentives. In this paper, we provide a novel explanation and investigate the role of consumer bounded rationality in the sense of anecdotal reasoning. We adopt a simple model that allows us to isolate the role of customer bounded rationality on using posterior price matching. We demonstrate that while it is never optimal to adopt posterior price matching when consumers have rational expectations, it can be optimal when they have boundedly rational expectations. We show when and how a seller can intentionally mark down with some probability and adopt price matching to make a profit. Ignoring customer bounded rationality can result in a significant profit loss. Then, we build a dynamic programming model to investigate how the firm should dynamically manage its markdowns over the long run. We show that a cyclic policy switching between a high and low markdown probability is typically optimal for exploiting customer bounded rationality. We characterize the nature of the cyclic policy and the range in which it is optimal. Our findings underscore the importance of consumer bounded rationality and provide managerial and practical guidelines on how to manage price matching when customers are boundedly rational. The online supplement is available at https://doi.org/10.1287/msom.2016.0612 .
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34

Long, Xueqin, Liancai Zhang, Yuejiao Wang, and Hongzhi Guan. "Dynamic Evolution of Traveler’s Bounded-Rational Route Choice Behavior." Journal of Advanced Transportation 2018 (December 4, 2018): 1–12. http://dx.doi.org/10.1155/2018/4378364.

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Travelers’ route choice shows bounded-rationality because of different perceptions of route attributes. Based on the bounded-rationality, the paper proposes the dynamic evolution rules and route choice model, and simulation method is applied to study the evolution process and results. The model includes three parameters reflecting the bounded-rationality of travelers. First, simulation results show that the bounded-rationality affects the evolution process. The switching threshold or the perception deviance is larger, convergence rate is faster, and shorter time is needed to reach equilibrium state. Also, fewer perfect rational travelers will lead to similar results. Second, the system can reach equilibrium and the final equilibrium volume of every route is almost unaffected by bounded-rationality. The equilibrium volume of every route is an approximately fixed value under all simulation scenes. At last, it is found that equilibrium volume of every route obeys normal distribution. That is, bounded-rationality affects the equilibrium convergence rate, but volume equilibrium results will not be influenced.
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35

Fiedler, Ingo. "Bounded Rationality in Compulsive Consumption." Journal of Business Theory and Practice 9, no. 1 (January 30, 2021): p30. http://dx.doi.org/10.22158/jbtp.v9n1p30.

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The standard microeconomic assumption is that consumers’ choices maximize consumers’ utility. This theoretical article challenges this assumption by presenting a framework of an extreme case: compulsive consumption. Backed by a wide range of existing empirical evidence it is shown by the example of pathological gamblers that some consumers (1) have inconsistent preferences, (2) underestimate the time horizon and the frequency of consumption, and (3) underestimate the costs and overestimate the benefits of consumption. The results do not necessarily violate rational choice theory if interpreted as intra-personal externalities. By applying the perspective of picoeconomics, it is possible to reconcile fully rational but competing agents within an individual with inconsistent aggregate decisions. Yet, from a welfare perspective, the results imply that bounded rationality can be interpreted as a source of inefficiency and can thus constitute a rationale for regulatory intervention.
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36

Arunachalam, V. S., and R. Bhaskar. "Bounded Rationality and Materials Selection." MRS Bulletin 24, no. 10 (October 1999): 57–61. http://dx.doi.org/10.1557/s0883769400053264.

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The vulnerabilities inherent in choosing an innovative material for a design can make for technological catastrophe. The points of weakness are not dependent on the technical nature of the innovation, but instead are intrinsic to human problem-solving and decision-making. We present a computational approach for managing and containing this fallibility using ideas from cognitive science and artificial intelligence, in particular, understanding how the boundedly rational behavior of humans and organizations leads to specific kinds of errors that affect the choice and use of materials.Materials choice in an industrial setting is often the result of a long chain or network of circumstances whose origins lie in many domains—from traditional engineering practice to the very latest innovation, from the commercial to the technical. In turn, every materials-selection decision has a long chain of consequences that are difficult to compute. This lengthy chain of consequences of a single decision gives rise to numerous points of error. What is particularly troublesome about these errors is not that they arise because of incomplete scientific engineering knowledge, but rather that they occur in spite of the fact that all (or at least, almost all) of the technically relevant information is available and sometimes even known to the technical personnel on the project. We will illustrate this approach by using a historical example of a major materials failure. Advances in database-systems design present an opportunity for integrating the ontology of material attributes with properties data. This may enable the design of more appropriate validation procedures required in proving a material for an artifact.
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37

Křečková, J., and H. Brožová. "Agricultural Insurance and Bounded Rationality." Agris on-line Papers in Economics and Informatics 09, no. 01 (March 30, 2017): 91–97. http://dx.doi.org/10.7160/aol.2017.090108.

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38

TAKAHASHI, Nobuo. "Where is Bounded Rationality From?" Annals of Business Administrative Science 14, no. 2 (2015): 67–82. http://dx.doi.org/10.7880/abas.14.67.

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39

Evans, David, George W. Evans, and Bruce McGough. "Bounded rationality and unemployment dynamics." Economics Letters 210 (January 2022): 110150. http://dx.doi.org/10.1016/j.econlet.2021.110150.

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40

Hernandez, Jose G. Vargas, and Ricardo Perez Ortega. "Bounded rationality in decision–making." MOJ Current Research & Reviews 2, no. 1 (January 22, 2019): 1–8. http://dx.doi.org/10.15406/mojcrr.2019.02.00047.

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41

Hernandez, Jose G. Vargas, and Ricardo Perez Ortega. "Bounded rationality in decision–making." MOJ Current Research & Reviews 2, no. 1 (January 22, 2019): 1–8. http://dx.doi.org/10.15406/10.15406/mojcrr.2019.02.00047.

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42

Hernández M.B.A., José G. Vargas, and Ricardo Pérez Ortega. "Bounded Rationality in Decision-Making." Journal of Business Management and Economic Research 1, no. 2 (December 28, 2018): 34–46. http://dx.doi.org/10.29226/tr1001.2018.91.

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43

Sciubba, Emanuela. "Bounded Rationality: The Adaptive Toolbox." Economic Journal 113, no. 485 (February 1, 2003): F189—F190. http://dx.doi.org/10.1111/1468-0297.t01-7-00105.

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44

FUKUDA, Shuichi. "K12100 Bounded Rationality and Engineering." Proceedings of Mechanical Engineering Congress, Japan 2014 (2014): _K12100–1_—_K12100–3_. http://dx.doi.org/10.1299/jsmemecj.2014._k12100-1_.

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45

Dequech, David. "Bounded Rationality, Institutions, and Uncertainty." Journal of Economic Issues 35, no. 4 (December 2001): 911–29. http://dx.doi.org/10.1080/00213624.2001.11506420.

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46

Sent, Esther-Mirjam. "Bounded Rationality: The Adaptive Toolbox." Journal of Economic Issues 36, no. 1 (March 2002): 232–34. http://dx.doi.org/10.1080/00213624.2002.11506464.

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47

SCHULTE, PAUL. "Universal vision or bounded rationality?" International Affairs 83, no. 3 (May 2007): 501–10. http://dx.doi.org/10.1111/j.1468-2346.2007.00634.x.

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48

Su, Xuanming. "Bounded Rationality in Newsvendor Models." Manufacturing & Service Operations Management 10, no. 4 (October 2008): 566–89. http://dx.doi.org/10.1287/msom.1070.0200.

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49

Huang, Tingliang, Gad Allon, and Achal Bassamboo. "Bounded Rationality in Service Systems." Manufacturing & Service Operations Management 15, no. 2 (May 2013): 263–79. http://dx.doi.org/10.1287/msom.1120.0417.

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50

Russell, Stuart J. "An architecture for bounded rationality." ACM SIGART Bulletin 2, no. 4 (July 1991): 146–50. http://dx.doi.org/10.1145/122344.122374.

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