Emotional Paternalism
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Behavioral Biases on Investment Decision: a Case Study in Indonesia
Kartini KARTINI, Katiya NAHDA / Journal of Asian Finance, Economics and Business Vol 8 No 3 (2021) 1231–1240 1231 Print ISSN: 2288-4637 / Online ISSN 2288-4645 doi:10.13106/jafeb.2021.vol8.no3.1231 Behavioral Biases on Investment Decision: A Case Study in Indonesia Kartini KARTINI1, Katiya NAHDA2 Received: November 30, 2020 Revised: February 07, 2021 Accepted: February 16, 2021 Abstract A shift in perspective from standard finance to behavioral finance has taken place in the past two decades that explains how cognition and emotions are associated with financial decision making. This study aims to investigate the influence of various psychological factors on investment decision-making. The psychological factors that are investigated are differentiated into two aspects, cognitive and emotional aspects. From the cognitive aspect, we examine the influence of anchoring, representativeness, loss aversion, overconfidence, and optimism biases on investor decisions. Meanwhile, from the emotional aspect, the influence of herding behavior on investment decisions is analyzed. A quantitative approach is used based on a survey method and a snowball sampling that result in 165 questionnaires from individual investors in Yogyakarta. Further, we use the One-Sample t-test in testing all hypotheses. The research findings show that all of the variables, anchoring bias, representativeness bias, loss aversion bias, overconfidence bias, optimism bias, and herding behavior have a significant effect on investment decisions. This result emphasizes the influence of behavioral factors on investor’s decisions. It contributes to the existing literature in understanding the dynamics of investor’s behaviors and enhance the ability of investors in making more informed decision by reducing all potential biases. -
Cognitive and Emotional Bias in Real Estate Investment Pau Blasi
Cognitive and Emotional Bias in Real Estate Investment Pau Blasi To cite this version: Pau Blasi. Cognitive and Emotional Bias in Real Estate Investment. Business administration. Uni- versité Paris sciences et lettres, 2018. English. NNT : 2018PSLED041. tel-02064265 HAL Id: tel-02064265 https://tel.archives-ouvertes.fr/tel-02064265 Submitted on 11 Mar 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Cette thèse a été réalisée dans le cadre d’une Convention Industrielle de Formation par la Recherche (CIFRE) entre l’Université Paris Dauphine et la société BNP Paribas Real Estate. Les points de vue et opinions exprimés dans ce document sont ceux de l’auteur et ne reflètent pas nécessairement la position de l’Université Paris Dauphine et de BNP Paribas Real Estate. This thesis was carried out through an Industrial Agreements for Training through Research (CIFRE) between Paris Dauphine University and BNP Paribas Real Estate. The views and opinions expressed in this document are those of the author and do not necessarily reflect the position of Paris Dauphine University and BNP Paribas Real Estate. 1 2 Remerciements 3 Je tiens tout d’abord à remercier les professeurs Sofiane ABOURA, Alain COEN, Jaume ROIG HERNANDO, Fabrice LARCENEUX et Richard MALLE qui m’ont fait l’honneur de constituer le jury de thèse. -
Self-Compassion Is Associated with Less Stress and Depression and Greater Attention and Brain Response to Affective Stimuli in Women Managers Fernanda B
Pires et al. BMC Women's Health (2018) 18:195 https://doi.org/10.1186/s12905-018-0685-y RESEARCH ARTICLE Open Access Self-compassion is associated with less stress and depression and greater attention and brain response to affective stimuli in women managers Fernanda B. C. Pires1, Shirley S. Lacerda1* , Joana B. Balardin1, Bruna Portes1, Patrícia R. Tobo2, Carla R. C. Barrichello2, Edson Amaro Jr1 and Elisa H. Kozasa1 Abstract Background: Women have been assuming more responsibilities and higher positions in major companies, which exposes them to high levels of stress. Higher perceived work stress is related to higher emotional reactivity. Difficulties with emotional regulation can lead to anxiety and mood disorders, which are more prevalent in women than men. Indeed, women leaders are more likely to experience emotional fatigue than men due to excessive empathy. Our aim was to evaluate the associations between self-compassion (SC) scores to depression symptoms, perceived stress and mindfulness, as well as with brain responses to high-arousal unpleasant and pleasant pictures from the International Affective Picture System (IAPS), as measured through functional Magnetic Resonance Imaging (fMRI) in women managers. Methods: Forty-six participants were selected for the study. All participants filled the Self Compassion Scale (SCS), Beck Depression Inventory (BDI), Mindful Awareness Attention Scale (MAAS) and the Perceived Stress Scale (PSS). After that they were scanned during an fMRI affective response paradigm. Correlation analysis were performed among these variables. Results: Our data suggest that women with higher SC scores respond to affective stimuli with higher activation of the precuneus (a brain region related to self-referential processing), lower levels of stress and depression and show greater attention in everyday activities. -
Cognitive Biases in Software Engineering: a Systematic Mapping Study
Cognitive Biases in Software Engineering: A Systematic Mapping Study Rahul Mohanani, Iflaah Salman, Burak Turhan, Member, IEEE, Pilar Rodriguez and Paul Ralph Abstract—One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained popularity in software engineering research. This paper therefore systematically maps, aggregates and synthesizes the literature on cognitive biases in software engineering to generate a comprehensive body of knowledge, understand state of the art research and provide guidelines for future research and practise. Focusing on bias antecedents, effects and mitigation techniques, we identified 65 articles (published between 1990 and 2016), which investigate 37 cognitive biases. Despite strong and increasing interest, the results reveal a scarcity of research on mitigation techniques and poor theoretical foundations in understanding and interpreting cognitive biases. Although bias-related research has generated many new insights in the software engineering community, specific bias mitigation techniques are still needed for software professionals to overcome the deleterious effects of cognitive biases on their work. Index Terms—Antecedents of cognitive bias. cognitive bias. debiasing, effects of cognitive bias. software engineering, systematic mapping. 1 INTRODUCTION OGNITIVE biases are systematic deviations from op- knowledge. No analogous review of SE research exists. The timal reasoning [1], [2]. In other words, they are re- purpose of this study is therefore as follows: curring errors in thinking, or patterns of bad judgment Purpose: to review, summarize and synthesize the current observable in different people and contexts. A well-known state of software engineering research involving cognitive example is confirmation bias—the tendency to pay more at- biases. -
COVID-19: Scientific Reasoning, Pragmatism and Emotional Bias
Gattinoni et al. Ann. Intensive Care (2020) 10:134 https://doi.org/10.1186/s13613-020-00756-7 LETTER TO THE EDITOR Open Access COVID-19: scientifc reasoning, pragmatism and emotional bias Luciano Gattinoni1*, John J. Marini2, Davide Chiumello3, Mattia Busana1 and Luigi Camporota4 Dear Editor, wide spectrum of opinions (as should be expected when the evidence is patchy and apparently inconsistent), none We thank Dr. Tobin et al. for their comments [1] in beside our own have received such an exacting response. response to our letter [2]. Leaving aside these refections, other considerations need At this time of uncertainty, clinicians turn to experts to be brought to the fore: the quibbling and partial nature and opinion leaders for advice on how to best manage of the objections raised. a patient aficted by a new and complex disease which When trying to piece together the pathophysiology of afects primarily—but not exclusively—the respiratory this unfamiliar entity, to this point we have had to rely system. Under the strains of pandemic practice, everyone on fragmentary evidence, logic and scientifc intuition. is trying hard; clinicians must strike a sensitive and dif- It is not difcult to imagine that to the ideas and exam- fcult balance in managing a relentless caseload with the ples we report in our manuscripts, Dr Tobin—or anyone limited (if not inadequate) resources at their disposal. else—will be able to fnd exceptions and contradicting In the midst of early applause by the general public evidence. Te scientifc literature is full of such examples. and intense scrutiny by healthcare systems and govern- Anyone can do the same—if they simply wish to abrogate ments—it is clear that there has been wide variability a point of view. -
Infographic I.10
The Digital Health Revolution: Leaving No One Behind The global AI in healthcare market is growing fast, with an expected increase from $4.9 billion in 2020 to $45.2 billion by 2026. There are new solutions introduced every day that address all areas: from clinical care and diagnosis, to remote patient monitoring to EHR support, and beyond. But, AI is still relatively new to the industry, and it can be difficult to determine which solutions can actually make a difference in care delivery and business operations. 59 Jan 2021 % of Americans believe returning Jan-June 2019 to pre-coronavirus life poses a risk to health and well being. 11 41 % % ...expect it will take at least 6 The pandemic has greatly increased the 65 months before things get number of US adults reporting depression % back to normal (updated April and/or anxiety.5 2021).4 Up to of consumers now interested in telehealth going forward. $250B 76 57% of providers view telehealth more of current US healthcare spend % favorably than they did before COVID-19.7 could potentially be virtualized.6 The dramatic increase in of Medicare primary care visits the conducted through 90% $3.5T telehealth has shown longevity, with rates in annual U.S. health expenditures are for people with chronic and mental health conditions. since April 2020 0.1 43.5 leveling off % % Most of these can be prevented by simple around 30%.8 lifestyle changes and regular health screenings9 Feb. 2020 Apr. 2020 OCCAM’S RAZOR • CONJUNCTION FALLACY • DELMORE EFFECT • LAW OF TRIVIALITY • COGNITIVE FLUENCY • BELIEF BIAS • INFORMATION BIAS Digital health ecosystems are transforming• AMBIGUITY BIAS • STATUS medicineQUO BIAS • SOCIAL COMPARISONfrom BIASa rea• DECOYctive EFFECT • REACTANCEdiscipline, • REVERSE PSYCHOLOGY • SYSTEM JUSTIFICATION • BACKFIRE EFFECT • ENDOWMENT EFFECT • PROCESSING DIFFICULTY EFFECT • PSEUDOCERTAINTY EFFECT • DISPOSITION becoming precise, preventive,EFFECT • ZERO-RISK personalized, BIAS • UNIT BIAS • IKEA EFFECT and • LOSS AVERSION participatory. -
A Motivational Account of the Impact Bias DISSERTATION Presented In
A Motivational Account of the Impact Bias DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Gina M. Hoover, M.A. Graduate Program in Psychology The Ohio State University 2011 Committee: Dr. Gifford Weary, Advisor Dr. Kentaro Fujita Dr. Jennifer Crocker Copyrighted by Gina M. Hoover 2011 Abstract The impact bias is the tendency for people to overestimate the intensity and duration of their feelings in response to some future outcome (Gilbert, Driver-Linn, & Wilson, 2002; Wilson & Gilbert, 2003; Wilson & Gilbert, 2005). Most explanations for the bias conceptualize it as an undesirable side effect of how the cognitive system goes about making predictions. Yet, perhaps such mispredictions can serve an important self- regulatory function, helping people achieve their goals. This research argued for a motivated impact bias. That is, there are times when people may be driven to predict feelings more extreme than they actually will experience. By overestimating one’s feelings to some future outcome, the stakes of succeeding or failing at gaining that outcome are raised. As such, this may energize people to pursue their goals to achieve the desired outcomes. The more one wants to gain (or avoid) some outcome, the more likely s/he will be to exhibit such an impact bias. To investigate this question, participants were asked to predict their feelings in response to the outcome of a performance task (visual responsiveness task in studies 1-3, creativity task in study 4, and verbal test in study 5) they would complete. -
Does CEO Emotional Bias Affect Performance?
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Souissi, Yasmine; Jarboui, Anis Article Does CEO emotional bias affect performance? Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Souissi, Yasmine; Jarboui, Anis (2018) : Does CEO emotional bias affect performance?, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 6, Iss. 1, pp. 1-21, http://dx.doi.org/10.1080/23322039.2018.1453452 This Version is available at: http://hdl.handle.net/10419/194777 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), -
Integrating Temporal Biases the Interplay of Focal Thoughts and Accessibility Experiences Lawrence J
PSYCHOLOGICAL SCIENCE Research Article Integrating Temporal Biases The Interplay of Focal Thoughts and Accessibility Experiences Lawrence J. Sanna1 and Norbert Schwarz2 1University of North Carolina at Chapel Hill and 2University of Michigan ABSTRACT—We provide an integrative account of temporal bi- come to mind. This interaction drives the emergence of these biases, ases (confidence changes, planning fallacy, impact bias, and as well as debiasing. hindsight bias). Students listed either 3 or 12 thoughts about success or failure before an upcoming real-life exam or im- TEMPORAL BIASES mediately after learning their grades. Previous explanations had focused on how thought content alone (what comes to mind) Figure 1 illustrates the time course of the four temporal biases that are influences temporal biases. We found, however, an interaction our focus here. between thought content and accessibility experiences (how eas- ily or difficultly thoughts come to mind). Thinking about 3 ways to succeed (success was easy to bring to mind) was equivalent to Confidence Changes thinking about 12 ways to fail (failure was difficult to bring to People are less confident in success when events draw near than they mind), and conversely, thinking about 3 ways to fail was are at a more distant time. For example, participants taking an im- equivalent to thinking about 12 ways to succeed. In no case was mediate test were less confident than those taking a test in 4 weeks thought content alone sufficient to predict the biases. These re- (Nisan, 1972; see also Gilovich, Kerr, & Medvec, 1993). Similarly, sults have implications for debiasing strategies and other judg- college seniors were more muted in estimating their first-job salaries ments over time. -
John Collins, President, Forensic Foundations Group
On Bias in Forensic Science National Commission on Forensic Science – May 12, 2014 56-year-old Vatsala Thakkar was a doctor in India but took a job as a convenience store cashier to help pay family expenses. She was stabbed to death outside her store trying to thwart a theft in November 2008. Bloody Footwear Impression Bloody Tire Impression What was the threat? 1. We failed to ask ourselves if this was a footwear impression. 2. The appearance of the impression combined with the investigator’s interpretation created prejudice. The accuracy of our analysis became threatened by our prejudice. Types of Cognitive Bias Available at: http://en.wikipedia.org/wiki/List_of_cognitive_biases | Accessed on April 14, 2014 Anchoring or focalism Hindsight bias Pseudocertainty effect Illusory superiority Levels-of-processing effect Attentional bias Hostile media effect Reactance Ingroup bias List-length effect Availability heuristic Hot-hand fallacy Reactive devaluation Just-world phenomenon Misinformation effect Availability cascade Hyperbolic discounting Recency illusion Moral luck Modality effect Backfire effect Identifiable victim effect Restraint bias Naive cynicism Mood-congruent memory bias Bandwagon effect Illusion of control Rhyme as reason effect Naïve realism Next-in-line effect Base rate fallacy or base rate neglect Illusion of validity Risk compensation / Peltzman effect Outgroup homogeneity bias Part-list cueing effect Belief bias Illusory correlation Selective perception Projection bias Peak-end rule Bias blind spot Impact bias Semmelweis -
Negative and Positive Bias for Emotional Faces: Evidence from the Attention and Working Memory Paradigms
Literature Review Negative and Positive Bias for Emotional Faces: Evidence from the Attention and Working Memory Paradigms Qianru Xu1,2, Chaoxiong Ye1,2*, Simeng Gu1,3, Zhonghua Hu1, Yi Lei1, Xueyan Li4, Lihui Huang5, Qiang Liu1 1Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China; 2Department of Psychology, University of Jyvaskyla, Jyväskylä, Finland; 3Department of Medical Psychology, Jiangsu University Medical School, Zhenjiang, China; 4School of Foreign Languages, Dalian University of Technology, Dalian, China; 5Faculty of Education, Sichuan Normal University, Chengdu, China; Running-head: Negative and positive bias for emotional faces Author Note This work was supported by grants from the National Natural Science Foundation of China (no. 31700948 and no. 31970989), and the Academy of Finland (no. 333649). All the authors had full independence from the funding sources. We would like to thank Dr. Weizhen Xie for the helpful discussion. Correspondence should be addressed to Dr. Chaoxiong Ye, Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, 610000, China, Email: [email protected]. 1 ABSTRACT Visual attention and visual working memory (VWM) are two major cognitive functions in humans, and they have much in common. A growing body of research has investigated the effect of emotional information on visual attention and VWM. Interestingly, contradictory findings have supported both a negative bias and a positive bias toward emotional faces (e.g., angry faces or happy faces) in the attention and VWM fields. We found that the classical paradigms—that is, the visual search paradigm in attention and the change detection paradigm in VWM—are considerably similar. The settings of these paradigms could therefore be responsible for the contradictory results. -
Evidence for Animal Grief?
Ristau, Carolyn (2016) Evidence for animal grief?. Animal Sentience 4(8) DOI: 10.51291/2377-7478.1014 This article has appeared in the journal Animal Sentience, a peer-reviewed journal on animal cognition and feeling. It has been made open access, free for all, by WellBeing International and deposited in the WBI Studies Repository. For more information, please contact [email protected]. Animal Sentience 2016.046: Commentary on King on Animal Grief Evidence for animal grief? Commentary on King on Animal Grief Carolyn Ristau Little Neck, New York Abstract: The nature of evidence appropriate to the study of animal emotion (and cognition) is discussed in this review with reference to Barbara King’s book. How Animals Grieve is beautifully written, but it intermixes examples meeting King’s criteria for evidence of grief with other poignant but far less convincing examples. Yet, as noted earlier by Griffin (1958/1974), “Excessive caution can sometimes lead one as far astray as rash enthusiasm.” King cites strong evidence from long-term scientific field studies, often involving known individuals; from videotapes; from convergent evidence in neurophysiological studies; and, notwithstanding possible emotional bias, from animals living closely with humans. She makes salient points about data from one-time occurrences and variability, distinguishing experience from expression, and cautioning about over-emphasis on statistics without adequate contextual description. She is persuasive, with both caveats and recognition of the need to be open to the likelihood of animal emotional experience. Such possibilities have a great impact on our treatment of animals, individually and as a society. Carolyn A.