53 research outputs found
sj-pdf-1-qjp-10.1177_17470218211052037 – Supplemental material for Lay, professional, and artificial intelligence perspectives on risky medical decisions and COVID-19: How does the number of lives matter in clinical trials framed as gains versus losses?
No full textSupplemental material, sj-pdf-1-qjp-10.1177_17470218211052037 for Lay, professional, and artificial intelligence perspectives on risky medical decisions and COVID-19: How does the number of lives matter in clinical trials framed as gains versus losses? by Sumitava Mukherjee and Divya Reji in Quarterly Journal of Experimental Psychology</p
Goalkeeper Behavior and decision making during penalty kicks in Men’s World Cup
No full textData and analysis of FIFA World Cup Penalty Shootout data from 1982 to 2022
Registered in 2023 by Rishav Singh ([[email protected]]) and Dr. Sumitava Mukherjee ([[email protected]]).
Dataset contains author contributions (Pablo L. Landeiros- Kaggle dataset URL: ([https://www.kaggle.com/datasets/pablollanderos33/world-cup-penalty-shootouts])
The analysis is done on data from the dataset mentioned above (containing data from FIFA (TM) Men's World Cups from 1982 to 2018) augmented with data from FIFA (TM) World Cup 2022 (manually coded by two researchers from freely available YouTube (TM) videos- links provided in the "Videos.txt" file). The dataset contains information for each kick in the following columns:
1. Game_id (numeric): Match number
2. Team (String): The team that took the kick
3. Zone (Categorical): Zone to which the ball was kicked (Indicated in accompanying file- Goal Zone.jpg)
4. Foot (Categorical): Which foot was used to kick the ball
5. Keeper (Categorical): Keeper jump direction for each kick
6. OnTarget (Boolean- 0 or 1): Whether the kick was on target or not.
7. Goal (Boolean- 0 or 1): whether the kick resulted in a goal or not.
8. Penalty_Number (Numeric): Kick number of the current kick in the shootout
9. Elimination (Boolean- 0 or 1): Whether the kick resulted in an elimination for one of the teams or not.
The full dataset is provided in the "WorldCupShootoutsRECENT.csv" file.
Code for analysis is provided in the "WorldCupAnalysis.R" file (RScript format)
Affective Valuations of Gains and Losses: Role of Current Affect and Magnitude
No full textBrief introduction and background:
This research study aims to investigate how people affectively value potential gains and losses. It seeks to test the hypothesis forwarded by Mellers et al. (2021) that current affect plays a vital role in judgments about gains and losses. The paper proposes that one can find evidence for loss aversion (predicted emotional impact of losses exceeds those of gains) when the reference point is positive and not when the reference point is negative.
The authors suggest that previous research may have failed to find loss aversion in bipolar response scales due to the absence of a measured reference point. For instance, McGraw et al. (2010) suggest that bipolar scales cannot capture loss aversion since there is no direct comparison of gains and losses. Mellers et al. (2021) report a study from Berman & Mellers (2014) where the current affect of participants is conceptualized as the reference point (Figure 2), and suggest that this can consolidate conflicts in the literature.
However, Mellers et al. (2021) do not tackle the crucial issue of magnitude or stake size of the potential outcomes. For example, Mukherjee et al. (2017) suggest that loss aversion is magnitude-dependent. They report, through a series of studies, that loss aversion may appear or not appear depending on the magnitude of the stakes used in the judgment tasks.
The present study is motivated by these gaps in the literature. Given that the judgment of gains and losses can be influenced by two distinct factors – the reference point (current affect) and the magnitude of the stake – we intend to empirically investigate them.
[Note: Berman and Mellers (2014) discovered that participants' current affective state is not at zero but slightly positive. When changes in affective state are calculated from this reference point, results are consistent with loss aversion.]
Methods:
We will conduct two experiments to test magnitude-dependent loss aversion (Mukherjee et al., 2017) and reference-dependent loss aversion (Mellers et al., 2021).
Experiment 1: This experiment will measure participants' affective predictions regarding a potential outcome through judgments of gains and losses. The magnitude of this potential outcome will be manipulated between subjects (low vs. high).
Experiment 2: This will additionally measure participants' current affect along with their affective predictions about the same potential outcomes. The current affect will be operationalized as a reference point to test the suggestions made by Mellers and colleagues
Role of Magnitude in Loss Aversion
No full textLoss aversion has been a widely recognized phenomenon (Kahneman & Tversky, 1979), which posits that losses loom larger than gains when measured from the same reference point for both risky and riskless choices. However, several studies have challenged the empirical validity of loss aversion (Ert & Erev, 2013; Gal & Rucker, 2018; Harinck et al., 2007; Mellers et al., 1997; Yechiam, 2019), suggesting that loss aversion may not hold for small losses (Mukherjee et al., 2017; Mukherjee & Srinivasan, 2021). This raises questions about the generalizability of loss aversion (Gal & Rucker, 2018) and has led to two theoretical positions: the classic view, which asserts that loss aversion is consistent across all magnitudes, and a magnitude-dependent perspective, which suggests that loss aversion is present for large magnitudes but not for small ones.
In this project, we investigate magnitude-dependent loss aversion across two between-group conditions: low magnitude and high magnitude. Participants (n = 208) played a sequence of 200 gambles involving gains and losses of varying magnitudes. Our findings reveal significant differences in median loss aversion coefficients between the two magnitude groups, with higher loss aversion observed for high magnitudes and lower loss aversion for low magnitudes. These results confirm the existence of magnitude-dependent loss aversion and underscore the critical role of magnitude in shaping our understanding of this phenomenon.
we also look at previous datasets that used a similar paradigm - Zhao et al. 2020 and Sheng et al. 2021 both have also been uploaded
Concerns with attempts by neuroeconomics to answer the philosophical question ‘Is it rational to donate money for charity?’
No full textExploring Cybercriminal Activities, Behaviors, and Profiles
No full textWhile modern society benefits from a range of technological advancements, it also is exposed to an ever-increasing set of cybersecurity threats. These affect all areas of life including business, government, and individuals. To complement technology solutions to this problem, it is crucial to understand more about cybercriminal perpetrators themselves, their use of technology, psychological aspects, and profiles. This is a topic that has received little socio-technical research emphasis in the technology community, has few concrete research findings, and is thus a prime area for development. The aim of this article is to explore cybercriminal activities and behavior from a psychology and human aspects perspective, through a series of notable case studies. We examine motivations, psychological and other interdisciplinary concepts as they may impact/influence cybercriminal activities. We expect this paper to be of value and particularly insightful for those studying technology, psychology, and criminology, with a focus on cybersecurity and cybercrime
money in the mental lives of the poor: Sample from indian urban working-class population
No full textThe project explores the psychological dimensions of poverty among the Indian working-class population, focusing on the impact of economic scarcity on thoughts related to money and financial stress. The literature review reveals how poverty influences the decision-making, risk behaviour, and cognitive functioning of the individuals dealing with it. The study aims to provide a nuanced understanding of the diverse thought patterns shaped by different material conditions within the poor population.
The methodology involves a conceptual replication of a study conducted by Shah et al. (2018), presenting two vignettes to participants representing real-life scenarios. Two scenarios include Study 1, “a visit to the doctor.”, and Study 2, “festival celebration.” After presenting one scenario per participant, they were asked to respond with three prominent thoughts that would arise if they were in that situation. We surveyed 240 participants in two categories: 1. those who get their wages on monthly wages and 2: those who get their wages on daily wages
- …
