Article
International Relations
Joshua D. Kertzer, Marcus Holmes, Brad L. LeVeck, Carly Wayne
Summary: This article examines how cognitive biases relevant to foreign policy decision making aggregate in groups. The results of three large-scale group experiments reveal that groups are as susceptible to biases as individuals, with decision-making structures neither attenuating the biases nor diverse groups performing differently than homogeneous ones. These findings have important implications for understanding foreign policy decision making, the role of group processes, and the behavioral revolution in international relations.
INTERNATIONAL ORGANIZATION
(2022)
Article
Business
Vidya S. Athota, Vijay Pereira, Zahid Hasan, Daicy Vaz, Benjamin Laker, Dimitrios Reppas
Summary: This study investigates cognitive biases among financial planners and explores how Artificial Intelligence can help overcome these biases. The findings suggest that financial planners exhibit cognitive biases while providing services and digital transformation using AI technologies may assist in addressing these biases, but should be combined with human intelligence.
JOURNAL OF BUSINESS RESEARCH
(2023)
Review
Psychology, Multidisciplinary
Vincent Berthet
Summary: The study suggests that individual differences in decision-making research on heuristics and cognitive biases have been overlooked, and reliable measures are needed. While there are currently reliable measures for some cognitive biases, improvements are needed for others, such as confirmation bias. Empirical work showed that adjustments can significantly improve some measures and confirmation bias can be reliably measured. Overall, the study highlights that measurement of individual differences in cognitive biases is still in its early stages, with a particular need for improved or developed contextualized measures.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Business
Jeremy L. Schoen, Justin A. DeSimone, Rustin D. Meyer, Katherine A. Schnure, James M. LeBreton
Summary: The research discusses the application of conditional reasoning technology in assessing implicit aspects of personality and emphasizes the importance of focusing on theoretical foundations rather than measurement issues for building more theoretically sound tests in future CR initiatives.
JOURNAL OF MANAGEMENT
(2021)
Article
Mathematics
Shahzad Faizi, Wojciech Salabun, Nisbha Shaheen, Atiq ur Rehman, Jaroslaw Watrobski
Summary: The paper introduces the hesitant 2-tuple linguistic set for handling uncertain data, along with operational laws and aggregation operators to merge information from decision makers. These operational laws and operators aid in dealing with complex choice situations and capturing diverse decision maker experiences.
Article
Materials Science, Multidisciplinary
Michael J. Kinsey, Max Kinateder, Steven M. Gwynne, Danny Hopkin
Summary: Fire engineering has become a mainstream discipline in building design process, involving complex fire codes and requiring engineers to possess a variety of knowledge and expertise. This study explores cognitive biases that may lead to errors in decision-making, suggesting measures to mitigate these biases, and emphasizing the importance of awareness among practicing fire engineers, building developers, fire code committees, and other stakeholders.
FIRE AND MATERIALS
(2021)
Review
Mathematical & Computational Biology
Ettore Cerracchio, Steven Miletic, Birte U. Forstmann
Summary: This article discusses the role of decision-making biases in the decision-making process and compares studies that used different models to investigate these biases. The results indicate that evidence accumulation models provide a more comprehensive explanation of decision-making phenomena by including response time behavior.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2023)
Review
Nursing
M. Lorraine Thirsk, T. Julia Panchuk, Sarah Stahlke, Reidar Hagtvedt
Summary: The biases in nurses' judgment and decision-making need to be addressed, and it is essential to identify and test debiasing strategies in real-world nursing settings.
INTERNATIONAL JOURNAL OF NURSING STUDIES
(2022)
Review
Psychology, Multidisciplinary
Vincent Berthet
Summary: The author reviewed research on the impact of cognitive biases on decision-making in management, finance, medicine, and law. The findings indicate that cognitive biases have an impact on professionals' decisions in these four areas, with overconfidence being the most common bias. The level of evidence supporting this claim varies across the different fields.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Multidisciplinary Sciences
Muhammad Akram, Xindong Peng, Aqsa Sattar
Summary: Aggregation operators are essential tools for consolidating data, and complex Pythagorean fuzzy models have extended existing models. This research investigates aggregation operators based on Yager t-norm and s-norm, discussing their properties and proposing an algorithm to advance multi-criteria decision-making strategies in a CPF environment. A fully developed numerical example is provided to demonstrate the significance of the proposed operators in decision-making environments, and the effectiveness of the operators is validated through tests.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Mathematics
Gerda Ana Melnik-Leroy, Gintautas Dzemyda
Summary: Multi-criteria decision-making methods aim to address limitations in human information processing, but cognitive biases such as framing and loss aversion may still influence decision outcomes. Different decisions can be made based on equivalent but differently framed descriptions of criteria, leading to variations in criteria weights and alternative rankings. Debiasing techniques and the influence of Prospect Theory on decision outcomes are discussed.
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud
Summary: Ranked hesitant fuzzy sets are a novel extension of hesitant fuzzy sets that require fewer demands and incorporate hierarchical knowledge about the evaluations submitted for each alternative. This approach provides a natural strategy for multi-criteria multi-agent decisions.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Orthopedics
Stein J. Janssen, Teun Teunis, David Ring, Robert C. Parisien
Summary: Cognitive biases have been shown to influence orthopaedic decision-making in hypothetical patient vignettes, with examples including base rate neglect, confirmation bias, anchoring heuristic, and framing effect. The study found variations in how orthopaedic surgeons display these biases, indicating a need for further research and development of debiasing strategies.
JOURNAL OF THE AMERICAN ACADEMY OF ORTHOPAEDIC SURGEONS
(2021)
Article
Clinical Neurology
Asuka Kaneko, Yui Asaoka, Young-A Lee, Yukiori Goto
Summary: The study found that anxiety and the cognitive realm of Theory of Mind (ToM) were associated with both social judgments and conformity, while social judgments and conformity remained independent processes. Social judgments were also linked to autistic traits and the affective realm of ToM, whereas social conformity was associated with negative affects other than anxiety and an intuitive decision-making style. These results suggest that Theory of Mind and negative affects may play important roles in social judgments and conformity, as well as the social biases implied in these social schemas.
INTERNATIONAL JOURNAL OF NEUROPSYCHOPHARMACOLOGY
(2021)
Review
Business
Chiara Acciarini, Federica Brunetta, Paolo Boccardelli
Summary: This paper investigates the potential interrelations among environmental transformations, cognitive biases, and strategic decisions, emphasizing the importance of cognitive biases on strategic decisions during times of environmental transformation. Decision-making is influenced by both internal (e.g. perception) and external factors (e.g. digitalization), and decision-makers are urged to manage cognitive biases to adapt to changing environments.
MANAGEMENT DECISION
(2021)
Article
Ecology
Maksym Polyakov, Fiona Dempster, Geoff Park, David J. Pannell
Summary: The primary causes of biodiversity decline worldwide are habitat destruction, alteration, and fragmentation resulting from human economic activities. Biodiversity conservation efforts in highly cleared and fragmented landscapes often involve restoring native habitat and ecosystems. Spatial targeting can improve restoration outcomes when it relies on voluntary landowner participation. Different targeting strategies, such as Aggregation, Connectivity, and Representativeness, perform differently depending on landscape characteristics, species characteristics, and restoration effort.
ECOLOGICAL ECONOMICS
(2023)
Article
Physics, Applied
Brenden W. W. Hamilton, Timothy C. C. Germann
Summary: Atomistic and continuum scale modeling have investigated the collapse of porosity under shock conditions in 1,3,5-trinitro-2,4,6-triaminobenzene (TATB). The collapse mechanisms and energy localization (hotspots) in TATB are not well-characterized. Simulation results show that weak shocks cause viscoplastic collapses perpendicular to the shock direction, while strong shocks cause hydrodynamic-like collapses without breaking TATB's strong hydrogen bonds. The resulting temperature fields of the hotspots differ significantly from other energetic materials, and their relative efficiency in energy localization is assessed based on normalized temperature values.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Multidisciplinary Sciences
Francois M. Castonguay, Julie C. Blackwood, Emily Howerton, Katriona Shea, Charles Sims, James N. Sanchirico
Summary: The COVAX initiative aims to ensure equitable access to COVID-19 vaccines, and countries receiving vaccines may distribute them based on their population size. Using economic-epidemiological modeling, the pro rata allocation rule is compared to an optimal one that minimizes economic damages, including social costs. The pro rata rule performs better with short immunity duration, population mixing, high vaccine supply, and minimal demographic heterogeneity. However, the optimal allocation generally outperforms the pro rata vaccine distribution rule despite uncertainties.
SCIENTIFIC REPORTS
(2023)
Article
Forestry
Murni Po, David J. Pannell, Iain Walker, Sorada Tapsuwan, Fiona Dempster, Daniel S. Mendham, Chris Beadle, Tran Lam Dong, Anh Hai Tran, Hanh Le Thi, Dang Thi Hai Ha
Summary: Acacia plantations are significant in the forestry industry in Viet Nam, mainly owned by smallholder farmers who have 1-5 hectares of land. Currently, most acacias are grown in short rotations for woodchip exports. The Vietnamese government aims to encourage farmers to convert to sawlog production on longer rotations. Farmers are willing to adopt longer rotations if they receive financial support and see others doing the same. A collaborative training approach leads to greater adoption of best practices.
TREES FORESTS AND PEOPLE
(2023)
Article
Ecology
Claire A. Doll, Michael P. Burton, David J. Pannell, Curtis L. Rollins
Summary: With climate change, water-limited cities face difficulties in maintaining historic watering levels in urban parks, leading park managers to consider changes to park designs. Public preferences for different park designs in Perth, Australia were assessed using a choice experiment, revealing acceptance of both irrigated and non-irrigated alternatives. Incorporating at least 40% native vegetation groundcover can increase the utility derived from parks and conserve water, while park managers have flexibility in designing parks that still provide near-optimal benefits to communities.
ECOLOGICAL ECONOMICS
(2023)
Article
Agricultural Economics & Policy
Yuan Chai, David J. Pannell, Philip G. Pardey
Summary: Nitrogen from agricultural fertilizers is a significant contributor to water pollution. Excessive nitrogen usage by farmers and their misconceptions about nitrogen fertilizer are identified as factors that contribute to nitrogen pollution. Utilizing insights from behavioral science, along with new market instruments and technological innovations, can help generate more efficient policy options.
Article
Biology
Emily Howerton, Kyle Dahlin, Christina J. Edholm, Lindsey Fox, Margaret Reynolds, Brandon Hollingsworth, George Lytle, Melody Walker, Julie Blackwood, Suzanne Lenhart
Summary: Infectious diseases pose a significant threat to global public health, and the governance structure plays a crucial role in managing disease outbreaks. Research findings show that both uniform and non-uniform governance structures impact resource allocation and burden of cases, with minimal difference in total costs.
JOURNAL OF MATHEMATICAL BIOLOGY
(2023)
Article
Health Care Sciences & Services
Rebecca K. Borchering, Luke C. Mullany, Emily Howerton, Matteo Chinazzi, Claire P. Smith, Michelle Qin, Nicholas G. Reich, Lucie Contamin, John Levander, Jessica Kerr, J. Espino, Harry Hochheiser, Kaitlin Lovett, Matt Kinsey, Kate Tallaksen, Shelby Wilson, Lauren Shin, Joseph C. Lemaitre, Juan Dent Hulse, Joshua Kaminsky, Elizabeth C. Lee, Alison L. Hill, Jessica T. Davis, Kunpeng Mu, Xinyue Xiong, Ana Pastore Y. Piontti, Alessandro Vespignani, Ajitesh Srivastava, Przemyslaw Porebski, Srini Venkatramanan, Aniruddha Adiga, Bryan Lewis, Brian Klahn, Joseph Outten, Benjamin Hurt, Jiangzhuo Chen, Henning Mortveit, Amanda Wilson, Madhav Marathe, Stefan Hoops, Parantapa Bhattacharya, Dustin Machi, Shi Chen, Rajib Paul, Daniel Janies, Jean-Claude Thill, Marta Galanti, Teresa Yamana, Sen Pei, Jeffrey Shaman, Guido Espana, Sean Cavany, Sean Moore, Alex Perkins, Jessica M. Healy, Rachel B. Slayton, Michael A. Johansson, Matthew Biggerstaff, Katriona Shea, Shaun A. Truelove, Michael C. Runge, Cecile Viboud, Justin Lessler
Summary: This study examined the impact of expanding COVID-19 vaccination to children aged 5-11 years on disease burden and resilience against variant strains. The results showed that vaccinating children can significantly reduce cases, hospitalizations, and deaths, with greater benefits for children in particular.
LANCET REGIONAL HEALTH-AMERICAS
(2023)
Article
Multidisciplinary Sciences
Emily Howerton, Michael C. Runge, Tiffany L. Bogich, Rebecca K. Borchering, Hidetoshi Inamine, Justin Lessler, Luke C. Mullany, William J. M. Probert, Claire P. Smith, Shaun Truelove, Cecile Viboud, Katriona Shea
Summary: Probabilistic predictions are crucial for public health planning and decision making during infectious disease emergencies. Aggregating predictions from multiple models can improve the robustness and uncertainty estimation of the outcomes. However, selecting an appropriate aggregation method is challenging when empirical validation is not feasible. This paper summarizes the literature on aggregating probabilistic predictions, provides simulation examples of different methods, and offers a strategy for choosing an aggregation method in the absence of empirical validation. The work focuses on the linear opinion pool (LOP) and Vincent average, which make different assumptions about between-prediction uncertainty and provide an R package for implementation.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2023)