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Journal articles on the topic 'Modeling decision making'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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1

Mohammadi, Anahita Malek, and Badaruddin Mohamed. "Convention Decision Making Modeling." International Journal of Trade, Economics and Finance 1, no. 1 (2010): 54–56. http://dx.doi.org/10.7763/ijtef.2010.v1.10.

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2

Sherif, Mona Mahmoud. "Modeling for Decision Making." Journal of Clinical Engineering 45, no. 1 (2020): 77–100. http://dx.doi.org/10.1097/jce.0000000000000346.

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3

Rothenberg, Lawrence S., and Mitchell S. Sanders. "Modeling Legislator Decision Making." American Politics Research 30, no. 3 (2002): 235–64. http://dx.doi.org/10.1177/1532673x02030003002.

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4

McShane, Marjorie, Sergei Nirenburg, and Bruce Jarrell. "Modeling decision-making biases." Biologically Inspired Cognitive Architectures 3 (January 2013): 39–50. http://dx.doi.org/10.1016/j.bica.2012.09.001.

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5

Silbert, Noah H. "Making decisions about modeling decision-making when analyzing speech perception data." Journal of the Acoustical Society of America 140, no. 4 (2016): 3163. http://dx.doi.org/10.1121/1.4969929.

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6

Krupa, Tadeusz, and Teresa Ostrowska. "Hierarchical Decision-Making Problems – Modeling and Solutions." Foundations of Management 8, no. 1 (2016): 311–24. http://dx.doi.org/10.1515/fman-2016-0024.

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Abstract Article illustrates the state of the work conducted at the Faculty of Management Warsaw University of Technology on the issue of modeling hierarchical decision-making problems in the context of administrative and infrastructural conditions of the various forms of public safety. The aim is to develop a universal methodology of conduct for the management needs of the public administration, whose powers are focused on maintaining the continuity of the critical infrastructure of the State. The key issues covered by the article are: modeling of hierarchical issues and decision-making proce

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7

Ganicheva, Antonina Valerianovna, and Alexey Valerianovich Ganichev. "Modeling of collective decision-making." Polythematic Online Scientific Journal of Kuban State Agrarian University, no. 174 (2021): 64–69. http://dx.doi.org/10.21515/1990-4665-174-007.

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8

Ziegel, Eric R. "Modeling in Medical Decision Making." Technometrics 44, no. 4 (2002): 409–10. http://dx.doi.org/10.1198/tech.2002.s99.

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9

Yager, R. R. "Modeling Prioritized Multicriteria Decision Making." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 34, no. 6 (2004): 2396–404. http://dx.doi.org/10.1109/tsmcb.2004.837348.

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10

Волочков, И. В. "Evolutionary modeling in decision making." Экономика и предпринимательство, no. 2(115) (May 6, 2020): 897–901. http://dx.doi.org/10.34925/eip.2020.115.2.181.

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Статья посвящена рассмотрению особенностей использования эволюционного моделирования в процессе принятия решений. Более детальное внимание уделено траблхакингу как прогрессивной методологии решения проблем в различных сферах общественной жизни. Отдельный акцент сделан на формулировке аргументов, систематизации фактов, которые позволяют обосновать значимость траблхакинга для моделирования и эволюции нетехнических систем. The article is devoted to the consideration of the specifics of using evolutionary modeling in decision making. The detailed attention is paid to troublehacking as a progressiv

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11

Bauer, Scott C., and Ira E. Bogotch. "Modeling site‐based decision making." Journal of Educational Administration 44, no. 5 (2006): 446–70. http://dx.doi.org/10.1108/09578230610683750.

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12

Cohen, Eliot A., and Wayne P. Hughes. "Military Modeling for Decision Making." Foreign Affairs 76, no. 6 (1997): 159. http://dx.doi.org/10.2307/20048303.

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13

Javor, Andrea J., Laurie D. R. Pearce, Alanna J. Thompson, and Ciara B. Moran. "Modeling Psychosocial Decision Making in Emergency Operations Centres." International Journal of Mass Emergencies & Disasters 32, no. 3 (2014): 484–507. http://dx.doi.org/10.1177/028072701403200304.

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The researchers compared the effectiveness of two decision models for modeling decision making in Emergency Operations Centers (EOCs): Klein's Recognition Primed Decision (RPD) model and Gladwin's Ethnographic Decision Tree Model (EDTM). The focus was on decisions that affect the psychological and social well-being of responders and community members. Communities of EOC personnel participated in a simulated emergency event, followed by an interview and/or focus group. Analysis of the decision-making processes during the simulation revealed that most operational decisions were made intuitively,

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14

Bloom, Laura A., and Bernard S. Bloom. "DECISION ANALYTIC MODELING IN HEALTH CARE DECISION MAKING." International Journal of Technology Assessment in Health Care 15, no. 2 (1999): 332–39. http://dx.doi.org/10.1017/s0266462399015251.

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The need to choose among alternatives instead of allowing the market to make choices has led health care professionals to rely on scientific information as an aid in decision making. Mathematical modeling is one of the increasingly common tools used over the past three decades to produce new information. But we have used almost exclusively noncomplex models to help analyze complex systems problems. The need to integrate the complexity of the interactions of clinical, quality of life, and economic attributes into such models can no longer be ignored. The opportunity is available to use existing

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15

Tatiana, Konovalenko Marina Gorbina Natalia Porozhnjak Alexandra Neverova. "COMMUNICATIVE MODELS OF MANAGEMENT DECISION MAKING." INDO AMERICAN JOURNAL OF PHARMACEUTICAL SCIENCES o6, no. 06 (2019): 11746–50. https://doi.org/10.5281/zenodo.3243560.

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<em>This article discusses the various modeling processes used to solve complex problems in management, to prevent significant difficulties and costs in conducting experiments in real life. The basis of the simulation is the need for relative simplification of the real life situation or event, however, this simplification should not violate the basic laws governing the functioning of the system under study. Improving the management decision-making process and, accordingly, improving the quality of decisions made is possible through the use of a scientific approach, models and decision-making m

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16

Martin, Nivetha, Florentin Smarandache, and Sudha S. "A Novel Method of Decision Making Based on Plithogenic Contradictions." Neutrosophic Systems with Applications 10 (October 1, 2023): 12–24. http://dx.doi.org/10.61356/j.nswa.2023.58.

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Plithogenic decision-making models are evolved integrating the Plithogenic modelling approach with various methods of multi-criteria decision-making (MCDM). The earlier Plithogenic based decision methods are primarily based on the degrees of appurtenance. This paper introduces a novel Plithogenic ranking genre of decision-making paradigm based on degrees of contradiction. The method of Decision Making on Plithogenic Contradictions (DMPC) developed in this research work is indigenous and unique as the modeling procedure doesn’t resemble any of the decision methods. This simple and logical appro

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17

Phoon, Kok-Kwang, Zi-Jun Cao, Jian Ji, et al. "Geotechnical uncertainty, modeling, and decision making." Soils and Foundations 62, no. 5 (2022): 101189. http://dx.doi.org/10.1016/j.sandf.2022.101189.

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18

Rosenfeld, Barry D., and Eric N. Turkheimer. "Modeling psychiatric patients' treatment decision making." Law and Human Behavior 19, no. 4 (1995): 389–405. http://dx.doi.org/10.1007/bf01499139.

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19

Bleiler-Baxter, Sarah K., D. Christopher Stephens, Wesley A. Baxter, and Angela T. Barlow. "Modeling as a Decision-Making Process." Teaching Children Mathematics 24, no. 1 (2017): 20–28. http://dx.doi.org/10.5951/teacchilmath.24.1.0020.

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Using simplification, relationship mapping, and situation analysis as a framework, we offer vignettes of student discussions about the Theme Park task to highlight their key choices as they model with mathematics.

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20

Orlob, G. T. "Water‐Quality Modeling for Decision Making." Journal of Water Resources Planning and Management 118, no. 3 (1992): 295–307. http://dx.doi.org/10.1061/(asce)0733-9496(1992)118:3(295).

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21

Huang, Zhimin, Feng Yang, Desheng D. Wu, Victor Shi, and Alireza Amirteimoori. "Decision-Making Modeling in Service Systems." Mathematical Problems in Engineering 2017 (2017): 1–3. http://dx.doi.org/10.1155/2017/6873951.

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22

Alarcón, Luis F., and David B. Ashley. "Modeling Project Performance for Decision Making." Journal of Construction Engineering and Management 122, no. 3 (1996): 265–73. http://dx.doi.org/10.1061/(asce)0733-9364(1996)122:3(265).

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23

McAndrew, Claire, Julie Gore, and Adrian Banks. "Convince Me: Modeling Naturalistic Decision Making." Journal of Cognitive Engineering and Decision Making 3, no. 2 (2009): 156–75. http://dx.doi.org/10.1518/155534309x441862.

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24

Kask, Susan, Carol Kline, and Kristin Lamoureux. "Modeling tourist and community decision making." Annals of Tourism Research 38, no. 4 (2011): 1387–409. http://dx.doi.org/10.1016/j.annals.2011.03.011.

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25

Filipkovska, L., and O. Matviienko. "Managerial Decision Support Making in Economic Systems Based on Cognitive Modeling." International Journal of Engineering & Technology 7, no. 4.3 (2018): 588. http://dx.doi.org/10.14419/ijet.v7i4.3.19962.

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The research is devoted to the search for the technologies to support managerial decisions in the transport industry economic systems. The problems of the complex economic systems modelling have been identified. Cognitive modelling is considered as a tool of supporting intelligent decision making in economic systems. The modelling is based on methods of pattern recognition theory. The results of the scientific research are presented with structural-analytical models of decision support systems. Such models represent the knowledge processing to formulate recommendations for making managerial de

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26

Filippov, E. V. "MODELING IRRATIONAL MANAGERIAL DECISION-MAKING IN THE IT PROJECTS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 243 (September 2024): 52–60. https://doi.org/10.14489/vkit.2024.09.pp.052-060.

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The problems of irrational managerial decision-making by IT professionals who have moved to managerial positions and the problem of modeling these decisions are studied. It is noted that unpredictability is the main undesirable property of such decisions. The problem to find steps reducing the unpredictability of irrational decisions is being solved. This also required solving the problems of identifying factors specific to IT professionals, modeling decision-making with these factors in mind. Surveys and mapping project practices to known patterns of irrational behavior was all done to identi

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27

Korem, Nachshon, Or Duek, Ruonan Jia, et al. "Modeling decision-making under uncertainty with qualitative outcomes." PLOS Computational Biology 21, no. 3 (2025): e1012440. https://doi.org/10.1371/journal.pcbi.1012440.

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Modeling decision-making under uncertainty typically relies on quantitative outcomes. Many decisions, however, are qualitative in nature, posing problems for traditional models. Here, we aimed to model uncertainty attitudes in decisions with qualitative outcomes. Participants made choices between certain outcomes and the chance for more favorable outcomes in quantitative (monetary) and qualitative (medical) modalities. Using computational modeling, we estimated the values participants assigned to qualitative outcomes and compared uncertainty attitudes across domains. Our model provided a good

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28

Handel, Oliver. "Modeling Dynamic Decision-Making of Virtual Humans." Systems 4, no. 1 (2016): 4. http://dx.doi.org/10.3390/systems4010004.

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29

II, Yoichi. "Quantitative Decision Making Using Modeling and Simulation." Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics 41, no. 5 (2010): 205–10. http://dx.doi.org/10.3999/jscpt.41.205.

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30

Saisubramanian, Sandhya. "Adaptive Modeling for Risk-Aware Decision Making." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9896–97. http://dx.doi.org/10.1609/aaai.v33i01.33019896.

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This thesis aims to provide a foundation for risk-aware decision making. Decision making under uncertainty is a core capability of an autonomous agent. A cornerstone for with long-term autonomy and safety is risk-aware decision making. A risk-aware model fully accounts for a known set of risks in the environment, with respect to the problem under consideration, and the process of decision making using such a model is risk-aware decision making. Formulating risk-aware models is critical for robust reasoning under uncertainty, since the impact of using less accurate models may be catastrophic in

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31

Marques, Cláudia Brazil, Fabrício Moraes de Almeida, Carlos Alberto Paraguassú-Chaves, et al. "Modeling and Decision Making Applied to Agriculture." International Journal of Advanced Engineering Research and Science 8, no. 8 (2021): 070–81. http://dx.doi.org/10.22161/ijaers.88.9.

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32

Cardil, Adrián, Santiago Monedero, Gavin Schag, et al. "Fire behavior modeling for operational decision-making." Current Opinion in Environmental Science & Health 23 (October 2021): 100291. http://dx.doi.org/10.1016/j.coesh.2021.100291.

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33

Attonaty, Jean-Marie, Marie-Hélène Chatelin, and Frédérick Garcia. "Interactive simulation modeling in farm decision-making." Computers and Electronics in Agriculture 22, no. 2-3 (1999): 157–70. http://dx.doi.org/10.1016/s0168-1699(99)00015-0.

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34

Vadali, Monika, Gurumurthy Ramachandran, and John Mulhausen. "Exposure Modeling in Occupational Hygiene Decision Making." Journal of Occupational and Environmental Hygiene 6, no. 6 (2009): 353–62. http://dx.doi.org/10.1080/15459620902855161.

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35

Klein, Robert W., Robert S. Dittus, Stephen D. Roberts, and James R. Wilson. "Simulation Modeling and Health-care Decision Making." Medical Decision Making 13, no. 4 (1993): 347–54. http://dx.doi.org/10.1177/0272989x9301300411.

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36

Papamichael, K., H. Chauvet, J. LaPorta, and R. Dandridge. "Product modeling for computer-aided decision-making." Automation in Construction 8, no. 3 (1999): 339–50. http://dx.doi.org/10.1016/s0926-5805(98)00081-8.

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37

Chen, Kaung-Hwa, and Hsin-Hui Lin. "Interactive group decision-making: Modeling and application." Socio-Economic Planning Sciences 32, no. 2 (1998): 113–21. http://dx.doi.org/10.1016/s0038-0121(97)00008-6.

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38

Bala, MV, and GA Zarkin. "WMM3: MODELING SEQUENTIAL DECISION-MAKING IN PHARMACOECONOMICS." Value in Health 2, no. 3 (1999): 233. http://dx.doi.org/10.1016/s1098-3015(11)71092-0.

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39

Michael Chung, H., Paul E. Johnson, and Peter A. Todd. "Introduction: expertise and modeling expert decision making." Decision Support Systems 21, no. 2 (1997): 49–50. http://dx.doi.org/10.1016/s0167-9236(97)00016-x.

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40

Duckstein, Lucien, and Steven A. Nobe. "Q-analysis for modeling and decision making." European Journal of Operational Research 103, no. 3 (1997): 411–25. http://dx.doi.org/10.1016/s0377-2217(97)00308-1.

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41

Krishnan, Viswanathan. "Modeling ordered decision making in product development." European Journal of Operational Research 111, no. 2 (1998): 351–68. http://dx.doi.org/10.1016/s0377-2217(97)00328-7.

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42

Spector, Alexander A., and Warren L. Grayson. "Stem Cell Fate Decision Making: Modeling Approaches." ACS Biomaterials Science & Engineering 3, no. 11 (2017): 2702–11. http://dx.doi.org/10.1021/acsbiomaterials.6b00606.

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43

Johnson, Joseph G. "Cognitive modeling of decision making in sports." Psychology of Sport and Exercise 7, no. 6 (2006): 631–52. http://dx.doi.org/10.1016/j.psychsport.2006.03.009.

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44

Sasou, Kunihide, Ken'ichi Takano, and Seiichi Yoshimura. "Modeling of a team's decision-making process." Safety Science 24, no. 1 (1996): 13–33. http://dx.doi.org/10.1016/s0925-7535(96)00029-x.

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45

Collura, Thomas F. "Modeling the Frontal Emotional Decision-Making Process." International Journal of Psychophysiology 108 (October 2016): 65. http://dx.doi.org/10.1016/j.ijpsycho.2016.07.216.

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46

Heikkila, Tanya, and Kimberley Roussin Isett. "Modeling Operational Decision Making in Public Organizations." American Review of Public Administration 34, no. 1 (2004): 3–19. http://dx.doi.org/10.1177/0275074003260911.

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47

Purcell, Braden A., Richard P. Heitz, Jeremiah Y. Cohen, Jeffrey D. Schall, Gordon D. Logan, and Thomas J. Palmeri. "Neurally constrained modeling of perceptual decision making." Psychological Review 117, no. 4 (2010): 1113–43. http://dx.doi.org/10.1037/a0020311.

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48

Kim, Choong Nyoung, Kyung Hoon Yang, and Jaekyung Kim. "Human decision-making behavior and modeling effects." Decision Support Systems 45, no. 3 (2008): 517–27. http://dx.doi.org/10.1016/j.dss.2007.06.011.

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49

Lee, Jane HyoJin, and Eunhye Flavin. "GPS: AI Decision Making and Statistical Modeling." Mathematics Teacher: Learning and Teaching PK-12 118, no. 6 (2025): 464–67. https://doi.org/10.5951/mtlt.2024.0217.

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Growing Problem Solvers provides four original, related, classroom-ready mathematical tasks, one for each grade band. Together, these tasks illustrate the trajectory of learners’ growth as problem solvers across their years of school mathematics.

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50

Власов, Дмитрий, and Dmitriy Vlasov. "Game-Theoretic Modeling in Practice of Decision-Making." Scientific Research and Development. Economics 6, no. 6 (2019): 59–63. http://dx.doi.org/10.12737/article_5c1b6bff770bb7.44461594.

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In recent years application of game-theoretic modeling for decisionmaking in various fields of economic activity became very popular. However not enough researches are conducted for the purpose of determination of adequacy and efficiency of such use, questions of orientation of various game models on the solution of specific objectives of the theory of decision-making are not fully described. The relevance of a subject of article is caused by increase of interests in game theory and game modeling as to the tool of the solution of various problems of decision-making in the conditions of risk an

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