Delayed Evacuation after a Disaster Because of Irrational Prediction of the Future Cumulative Precipitation Time Series under Asymmetry of Information

This study investigated biased prediction of cumulative precipitation, using a variety of patterns of histories of cumulative precipitation, to explore how such biased prediction could delay evacuation or evacuation orders. The irrationality in predicting the future of cumulative precipitation was examined to obtain insights into the causes of delayed evacuation or evacuation orders using a simulated prediction of future cumulative precipitation based on the cumulative precipitation history. Anchoring and adjustment, or availability bias stemming from asymmetry of information, was observed in the prediction of cumulative precipitation, and found to delay evacuation or evacuation orders.

A Study on Changing Role of Investor Behaviour towards Digital Investments – Pre and During COVID-19 Scenarios

World markets are facing anxiety and vulnerability due to global pandemic of COVID-19.Investors are becoming cautious while selecting their investment avenues and hence theirfocus is shifting to more secure forms of investments. Cryptocurrencies are one of therenowned form of digital investments and has drawn attention of many investors since itsorigination. Since 2013 it has been attracting and shifting eye balls of many financial and ITresearchers with its excellent returns and use of advanced technology. The present study hasexplored the impact of COVID-19 on the investor behaviour towards digital currencies. Forthe very same purpose researchers have considered pre and during COVID phases andcompared the shift in volatility of five selected cryptocurrencies. The study has also explored few of the most prominent investor biases which influences investor behaviour and how these biases have shifted during global pandemic of COVID-19. Some of the prominent biases such as, availability bias, regret, mental accounting and herding have been recognized in the study to understand investor behaviour.

Cognitive Biases Among Millennial Indian Investors: Do Personality and Demographic Factors Matter?

This study examines the influence of financial literacy, gender, annual family income and neuroticism personality trait on the probability of millennial equity investors to suffer from selected cognitive biases (availability bias, representative bias, mental accounting bias and anchoring and adjustment bias). Binary logistic regression method is applied to conduct the analysis. Results of the current study indicate that selected demographic factors and investor personality are significant in predicting the probability of millennial Indian investor to suffer from the biases under consideration. For availability bias, financial literacy; for representative bias, financial literacy, neuroticism and gender; for mental accounting bias, neuroticism, gender and annual family income; and for anchoring and adjustment bias, financial literacy, neuroticism, gender and annual family income are found as significant predictors.

Perilaku Investor Dalam Transaksi Saham di Pasar Modal

This study aims to analyzing the behavior of Palembang investors through cognitive biases and emotional biases that impacting investor’s decision making on stock transaction in the capital market. This decision making proxied by cognitive biases, there are overconfidence bias, represtentativeness bias, anchoring and adjustment bias, availability bias, illusion of control bias, and conservatism bias, also proxied by emotional biases there are self-control bias, optimism bias, loss aversion bias, dan status quo bias. The population of the study are investors whom became partners of securities, those listed in Indonesian Stock Exchange and the securities which stand only in Palembang region. There are 50 investors as sample of this study with purposive sampling as sampling method. The type data of this study is qualitative and the resources of data in this study is primary data with distributing questionnaire. Analyzing method in this study using multivariate analysis Structural Equation Model (SEM) and the result of this study shows that availability bias, conservatism bias, and loss aversion bias have significance effect to Palembang investor’s decision making in 2020. For future research could be able to take other samples from another big cities, as well as conducted research on the relationship between behavioral biases and financing or behavioral biases and health that including demographics and etc.

Snap Judgements and Availability Bias in Travel Decisions

Past research has explored how travelers make economic decisions, but only a small number of papers look at financial nudges and price anchoring—how they might cause travelers to make snap judgements about value that undermine rational economic principles. This research explores the behavioral response to different kinds of incentives. It finds that, consistent with theory, when presented with two numbers certain individuals will anchor to a higher number and be willing to pay more. Likewise, it finds that certain consumers are not able to quickly make judgements about the cost of travel. When the survey participants were offered daily or monthly payment plans, payments each day were valued almost twice as much as a single payment each month. This offers important policy considerations for public agencies seeking to reduce driving, particularly as new disruptive platforms emerge and new technology allows for more dynamic and curated data to be used to nudge travel behavior.

Analisis Pengaruh Behavioural Finance Terhadap Pengambilan Keputusan Investasi Investor di Kepulauan Riau

Perkembangan ekonomi global yang semakin maju dan cepat akibat adanya perkembangan teknologi menyebabkan kegiatan berinvestasi semakin dipermudah. Hal tersebut membuat minat investasi di Indonesia selama empat tahun terakhir berkembang sangat pesat. Akan tetapi, peningkatan jumlah investor dan banyaknya keuntungan yang ditawarkan tidak menggambarkan secara nyata kinerja investasi para investor itu sendiri. Kinerja investasi yang baik juga memiliki korelasi kuat dengan pengambilan keputusan investasi yang baik dan rasional. Seorang investor yang baik biasanya akan membuat suatu keputusan investasi yang rasional, tetapi nyatanya para investor sering kali membuat keputusan investasi yang buruk akibat pengaruh faktor psikologis dalam diri mereka sendiri. Sebagai contohnya, pada masa pandemi COVID-19 ini, IHSG Indonesia bahkan seluruh negara mengalami penurunan drastis akibat kepanikan para investor. Dari contoh tersebut dapat kita ketahui bahwa peran faktor psikologis sangatlah penting. Penelitian ini dibuat dengan tujuan untuk mencari tahu dan menguji faktor-faktor behavioural finance yang memiliki pengaruh kepada para investor di Kepulauan Riau dalam proses pengambilan keputusan investasi. Faktor-faktor behavioural finance yang diuji pada penelitian ini adalah representativeness bias, availability bias, overconfidence bias, loss aversion bias, dan anchoring and adjustment bias. Sampel yang digunakan sebagai bahan pengujian berjumlah 133 responden yang merupakan investor aktif di Kepulauan Riau. Hasil pengujian menunjukkan bahwa, variabel loss aversion dan anchoring & adjustment bias berpengaruh positif terhadap proses pengambilan keputusan investasi para investor di Kepulauan Riau, sedangkan variabel representativeness bias, overconfidence, dan availability bias tidak memiliki pengaruh yang signifikan.

The relationship between time to diagnose and diagnostic accuracy among internal medicine residents: a randomized experiment

Background Diagnostic errors have been attributed to cognitive biases (reasoning shortcuts), which are thought to result from fast reasoning. Suggested solutions include slowing down the reasoning process. However, slower reasoning is not necessarily more accurate than faster reasoning. In this study, we studied the relationship between time to diagnose and diagnostic accuracy. Methods We conducted a multi-center within-subjects experiment where we prospectively induced availability bias (using Mamede et al.’s methodology) in 117 internal medicine residents. Subsequently, residents diagnosed cases that resembled those bias cases but had another correct diagnosis. We determined whether residents were correct, incorrect due to bias (i.e. they provided the diagnosis induced by availability bias) or due to other causes (i.e. they provided another incorrect diagnosis) and compared time to diagnose. Results We did not successfully induce bias: no significant effect of availability bias was found. Therefore, we compared correct diagnoses to all incorrect diagnoses. Residents reached correct diagnoses faster than incorrect diagnoses (115 s vs. 129 s, p < .001). Exploratory analyses of cases where bias was induced showed a trend of time to diagnose for bias diagnoses to be more similar to correct diagnoses (115 s vs 115 s, p = .971) than to other errors (115 s vs 136 s, p = .082). Conclusions We showed that correct diagnoses were made faster than incorrect diagnoses, even within subjects. Errors due to availability bias may be different: exploratory analyses suggest a trend that biased cases were diagnosed faster than incorrect diagnoses. The hypothesis that fast reasoning leads to diagnostic errors should be revisited, but more research into the characteristics of cognitive biases is important because they may be different from other causes of diagnostic errors.