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Статті в журналах з теми "Bounded and Ecological Rationality"

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Автор: Grafiati

Опубліковано: 7 липня 2024

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1

Berg, Nathan. "The consistency and ecological rationality approaches to normative bounded rationality." Journal of Economic Methodology 21, no. 4 (October 2, 2014): 375–95. http://dx.doi.org/10.1080/1350178x.2014.969910.

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2

Lejarraga, José, and Maud Pindard-Lejarraga. "Bounded Rationality: Cognitive Limitations or Adaptation to the Environment? The Implications of Ecological Rationality for Management Learning." Academy of Management Learning & Education 19, no. 3 (September 2020): 289–306. http://dx.doi.org/10.5465/amle.2019.0189.

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3

Van der Merwe, Ragnar. "Rational Decision-Making in a Complex World." Logos & Episteme 13, no. 4 (2022): 381–404. http://dx.doi.org/10.5840/logos-episteme202213432.

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Prima facie, we make successful decisions as we act on and intervene in the world day-to-day. Epistemologists are often concerned with whether rationality is involved in such decision-making practices, and, if so, to what degree. Some, particularly in the post-structuralist tradition, argue that successful decision-making occurs via an existential leap into the unknown rather than via any determinant or criterion such as rationality. I call this view radical voluntarism (RV). Proponents of RV include those who subscribe to a view they call Critical Complexity (CC). In this paper, I argue that CC presents a false dichotomy when it conceives of rationality in Cartesian – i.e. ideal and transcendental – terms, and then concludes that RV is the proper alternative. I then outline a pragmatist rationality informed by recent work in psychology on bounded rationality, ecological rationality, and specifically embodied rationality. Such a pragmatist rationality seems to be compatible with the tenets of post-structuralism, and can therefore replace RV in CC.

4

Foxon, Tim. "Bounded rationality and hierarchical complexity: Two paths from Simon to ecological and evolutionary economics." Ecological Complexity 3, no. 4 (December 2006): 361–68. http://dx.doi.org/10.1016/j.ecocom.2007.02.010.

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5

Riva, Silvia, Paola Iannello, and Alessandro Antonietti. "Health comes first: Smart heuristics to stay healthy." RICERCHE DI PSICOLOGIA, no. 3 (December 2021): 1–14. http://dx.doi.org/10.3280/rip2021oa12717.

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In the classical "jacket-calculator" dilemma it is postulated decision is regulated by a mental topical accounting process which orients people to consider a discount price when purchasing items. We proposed an adapted version of the classical "jacket-calculator" task re-framing the choice in a medical context. Our results supported the view that simple minimal mental accounts influence evaluation and choice in the medical context where time, instead of price, represents a fundamental cue of the decision analysis. The decision process adopted by participants tended to be associated with a lexicographic decision mechanism where "time" appears the most effective cue of a "take-the-best" heuristic to predict people's behaviour accurately. These findings broaden the body of evidence indicating that bounded rationality in human decisions is intrinsically connected with the decisional context and different contexts may elicit different mental accounting strategies. In addition, the study stressed the need to enhance the dialogue between the more recent paradigm of the ecological rationality with the classical interpretations of bounded rationality because the two paradigms, not rarely opposed to each other, can provide hints to the interpretation of the decision process, with practical considerations for future interventions in health education and public health.

6

Stajkic, Bojana, and Kaja Damnjanovic. "The road to Nobel prize is paved with the conceptualisations of rationality from homo economicus to homo heuristicus." Theoria, Beograd 61, no. 2 (2018): 147–62. http://dx.doi.org/10.2298/theo1802147s.

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In this paper we present the main psychological conceptions of rationality: unbounded rationality, bounded rationality, optimization under constraints, and ecological rationality. We show how these concepts directed the research questions, and how they shaped psychological models of complex cognitive processes. In its symbolic tradition, for more than a century, the psychology, as a fundamental cognitive science, has been focused on the question of how the environment is represented in the cognitive system, how the cognitive system operates with those information, and, ultimately, what are the outcomes of these processes. The basis on which the research efforts focusing on complex cognitive processes, such as judgment, decision-making, and reasoning - are rooted in is the stance of authors, and psychological models regarding rationality. The conceptualizations of rationality are, at the beginning of the psychological research, implicit, because they are taken from a normative approach, and the research focus is on the outcome of cognitive processes, while the functions and the processes themselves are neglected. Later, as the research diverge from the normative approach, the psychological conceptualization of rationality becomes more explicit and subjective, and more nested in the environment, and the empirical studies aim to describe the structure and dynamics of complex cognitive processes.

7

Prußeit, Tabitha. "Intuiciones y racionalidad ecológica." Revista de Humanidades de Valparaíso, no. 24 (February 29, 2024): 145–62. http://dx.doi.org/10.22370/rhv2024iss24pp145-162.

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Through an ecological approach, it can be said that a person tries to identify the optimal action for him- or herself by a set of different possible actions through intuition. The debate about the ‘dual process theories’ takes up this idea and postulates two different ways to evaluate decision possibilities: A logical-analytical path and an intuitive (Magrabi and Bach, 2013). Predominantly, it is assumed that the logical-analytical path is related to rationality and therefore the path to strive for in rational decision-making. However, in science it has been shown that bounded rationality is to be assumed. Therefore, the question of the extent to which emotions or feelings, and in this context also intuitions, are rational has come to the fore (De Sousa, 1987; Evans and Cruse, 2004). In this paper, intuitions are considered as a feeling with intentionality: Intuitions always refer to an appropriate environment and are directed toward a decision that results in an action. With Damásio (1994, 2013) it can be shown that an intuition is a feeling that excels in acting as a cue or signal. With the assumption of an ecological rationality (Gigerenzer, Todd and ABC Research Group, 1999; Todd and Gigerenzer, 2012; Todd and Brighton, 2016), it can be shown that intuitive decisions are based on experiential knowledge and implicit structure recognition (Magrabi and Bach, 2013). Accordingly, with the approach of an ecological rationality it can be shown that an intuitive decision is rational in the sense that a person interacts quickly and energy-efficiently successfully adapted with his or her environment and thereby identifies the individual optimal action for him- or herself. This may then be recognized as a ‘gut feeling’ or ‘intuition’. Two challenges will be outlined explained in this paper: The influence of a negative environment on intuitive decisions, and the confusion of an intuition with an emotion or other feeling.

8

Farias, Hilder André Bezerra, Sérgio Luiz de Medeiros Rivero, and Márcia Jucá Teixeira Diniz. "Negative incentives and sustainability in the amazonian logging industry." Nova Economia 27, no. 3 (December 2017): 363–91. http://dx.doi.org/10.1590/0103-6351/2735.

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Abstract: This paper investigates the existence of lock-in of low technology and high environmental impact on Brazilian Amazon logging industry. The research employed evolutionary economics as a theoretical basis, especially the concept of technological trajectories. The duality of decisions involving logging - conventional logging (CL) versus reduced-impact logging (RIL) - was studied. An agent-based simulation model - in which decision-making under bounded rationality is based on a genetic algorithm - was implemented in Java programming language. Results demonstrate the existence of lock-in, producers aversion to risks, greater operational efficiency of sustainable logging, and benefits derived from a policy of environmental bonuses, both in economic and ecological terms.

9

Choudhury, Avishek. "Toward an Ecologically Valid Conceptual Framework for the Use of Artificial Intelligence in Clinical Settings: Need for Systems Thinking, Accountability, Decision-making, Trust, and Patient Safety Considerations in Safeguarding the Technology and Clinicians." JMIR Human Factors 9, no. 2 (June 21, 2022): e35421. http://dx.doi.org/10.2196/35421.

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The health care management and the medical practitioner literature lack a descriptive conceptual framework for understanding the dynamic and complex interactions between clinicians and artificial intelligence (AI) systems. As most of the existing literature has been investigating AI’s performance and effectiveness from a statistical (analytical) standpoint, there is a lack of studies ensuring AI’s ecological validity. In this study, we derived a framework that focuses explicitly on the interaction between AI and clinicians. The proposed framework builds upon well-established human factors models such as the technology acceptance model and expectancy theory. The framework can be used to perform quantitative and qualitative analyses (mixed methods) to capture how clinician-AI interactions may vary based on human factors such as expectancy, workload, trust, cognitive variables related to absorptive capacity and bounded rationality, and concerns for patient safety. If leveraged, the proposed framework can help to identify factors influencing clinicians’ intention to use AI and, consequently, improve AI acceptance and address the lack of AI accountability while safeguarding the patients, clinicians, and AI technology. Overall, this paper discusses the concepts, propositions, and assumptions of the multidisciplinary decision-making literature, constituting a sociocognitive approach that extends the theories of distributed cognition and, thus, will account for the ecological validity of AI.

10

Mainzer, Klaus. "Challenges of Complexity in the 21st Century. An Interdisciplinary Introduction." European Review 17, no. 2 (May 2009): 219–36. http://dx.doi.org/10.1017/s1062798709000714.

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The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. Modern evolutionary economics can be modelled in the framework of complex systems and nonlinear dynamics. Historically, evolutionary economics was inspired by Schumpeterian concepts of business cycles and innovation dynamics. What are the laws of sociodynamics? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the complexity in firms, institutions and organizations? The world-wide crisis of financial markets and economies is a challenge for complexity research. Misleading concepts of linear thinking and mild randomness (e.g. Gaussian distributions of Brownian motion) must be overcome by new approaches of nonlinear mathematics (e.g. non-Gaussian distribution), modelling the wild randomness of turbulence at the stock markets. Systemic crises need systemic answers. Nevertheless, human cognitive capabilities are often overwhelmed by the complexity of nonlinear systems they are forced to manage. Traditional mathematical decision theory assumed perfect rationality of economic agents (homo oeconomicus). Herbert Simon, Nobel Prize laureate of economics and one of the leading pioneers of systems science and cognitive science, introduced the principle of bounded rationality. Therefore, we need new insights into the factual microeconomic behaviour of economic agents by methods of humanities, cognitive and social sciences, which are sometimes called ‘experimental economics’. Social and economic dynamics are interdisciplinary challenges of modern complexity research.

11

Gambarotto, Francesca, Marco Rangone, and Stefano Solari. "Moral and Institutional Foundations of Sustainable Technological Entrepreneurship." Sustainability 15, no. 18 (September 15, 2023): 13796. http://dx.doi.org/10.3390/su151813796.

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In this essay, we reflect on the conditions that allow firms to play a leading role in the ecological transition process. The essay starts with an analysis of the technological and economic features of eco-efficient technologies. We argue that they are weak levers for the ecological transition. As eco-efficiency is based on profit-maximising goals, the pace of the transition is unlikely to peak quickly. In fact, this profit motive restrains firms from fully embedding ecological principles in their choices. Some behavioural concerns arise, as rationally bounded firms are likely to pursue uncomplicated and effortless pathways so as to safeguard profits. For instance, firms may pretend to be sustainable, while chasing opportunistic practices such as greenwashing, wokening, and cost shifting. Hence, they cannot lead the ecological transition process. A few consequences derive. First, new moral values must become pivotal criteria in firms’ decision-making processes. Second, such a big challenge must become shared and widely accepted in social discourse, so as to involve all economic actors and trigger a general process of institutional change. These are necessary conditions for the ensuing economic and social provisioning to take care of the limits of the Earth. Finally, we suggest that the teaching of economics must also be concerned with making such a change in mindset successful.

12

Santos, Bruno Maciel. "Poder, incerteza e heurísticas: contribuições da psicologia cognitiva para o estudo da tomada de decisões nas Relações Internacionais." Brazilian Journal of International Relations 8, no. 2 (August 28, 2019): 353–84. http://dx.doi.org/10.36311/2237-7743.2019.v8n2.07.p353.

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A falta de consenso sobre uma definição de poder e sobre como lidar com a incerteza nas Relações Internacionais são problemas antigos nessa disciplina. Este artigo apresenta algumas contribuições da psicologia cognitiva relacionadas ao uso de heurísticas decisórias para as discussões acerca do conceito de poder e relacionadas à incerteza no campo das Relações Internacionais. Para tanto, realiza-se uma revisão das visões divergentes acerca do conceito do poder e da incerteza entre os três paradigmas mais influentes nas Relações Internacionais, apresentando como cada um deles define esses dois conceitos e quais as implicações teóricas dessas visões. Apesar de várias definições operacionais, é possível que o conceito formal de poder apresentado por Dahl (1957) seja utilizado como referência para as quatro faces do poder apresentadas. No entanto, essa definição implica necessariamente algum grau de incerteza nas relações de poder, relacionadas à informação, seja pela sua disponibilidade, pela sua confiabilidade, pela ambiguidade ou pela sua subjetividade. Sendo assim, apresenta-se as heurísticas decisórias como forma de lidar com a tomada de decisão em situações de incerteza envolvendo relações de poder, a partir de uma racionalidade circunscrita e ecológica. Essa abordagem é uma, dentre várias possíveis, e não busca impor termos absolutos para a discussão, nem negar as várias contribuições teóricas feitas pelas demais abordagens discutidas, mas sim destacar alguns pontos negligenciados e apresentar novas possibilidades de análise no campo das Relações Internacionais. Abstract: The lack of agreement about a definition of power and how to deal with uncertainty in the International Relations are long known problems of the discipline. This article presents some contributions from cognitive psychology related to the use of decision heuristics to the discussions about the concept of power and related to uncertainty in the field of International Relations. For this, it revises the different visions about the concept of power and uncertainty among the three most influential paradigms in International Relations, presenting how each one of them defines these two concepts and what are the theoretical implications for these visions. Despite the many operational definitions, it is possible that the formal concept provided by Dahl (1957) be taken as a reference for the four faces of power presented here. Nonetheless, this definition necessarily embeds some degree of uncertainty in power relations as a matter of information, be it because of its availability, its reliability, its ambiguity or its subjectivity. In this sense, decision heuristics are presented as a way to deal with decision-making under uncertainty related to power relationships, from a bounded and ecological rationality perspective. This approach is just one, among many, and does not seek to impose absolute terms to the discussion, nor denies the many theoretical contributions made by the other approaches discussed here, but points out new possibilities for analysis and shed light to neglected terms for debate in the field of International Relations. Keywords: Power; Uncertainty; Decision-Making; Bounded Rationality; International Relations Theories. Recebido em: outubro/2018. Aprovado em: junho/2019.

13

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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14

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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15

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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16

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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17

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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18

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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19

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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20

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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21

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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22

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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23

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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24

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.

25

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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26

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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27

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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28

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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29

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.

30

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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31

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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32

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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33

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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34

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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35

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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36

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.

37

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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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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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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Wu, Xinlin, and Yong Zhao. "Research on Bounded Rationality of Fuzzy Choice Functions." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/928279.

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The rationality of a fuzzy choice function is a hot research topic in the study of fuzzy choice functions. In this paper, two common fuzzy sets are studied and analyzed in the framework of the Banerjee choice function. The complete rationality and bounded rationality of fuzzy choice functions are defined based on the two fuzzy sets. An assumption is presented to study the fuzzy choice function, and especially the fuzzy choice function with bounded rationality is studied combined with some rationality conditions. Results show that the fuzzy choice function with bounded rationality also satisfies some important rationality conditions, but not vice versa. The research gives supplements to the investigation in the framework of the Banerjee choice function.

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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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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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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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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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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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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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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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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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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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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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