scholarly journals Investors’ Short Term Decision Making and Review of the Hindsight Bias Effect

Author(s):  
Tchai Tavor
Author(s):  
Stefan Scherbaum ◽  
Simon Frisch ◽  
Maja Dshemuchadse

Abstract. Folk wisdom tells us that additional time to make a decision helps us to refrain from the first impulse to take the bird in the hand. However, the question why the time to decide plays an important role is still unanswered. Here we distinguish two explanations, one based on a bias in value accumulation that has to be overcome with time, the other based on cognitive control processes that need time to set in. In an intertemporal decision task, we use mouse tracking to study participants’ responses to options’ values and delays which were presented sequentially. We find that the information about options’ delays does indeed lead to an immediate bias that is controlled afterwards, matching the prediction of control processes needed to counter initial impulses. Hence, by using a dynamic measure, we provide insight into the processes underlying short-term oriented choices in intertemporal decision making.


2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.


2020 ◽  
Vol 21 (2) ◽  
pp. 136-142 ◽  
Author(s):  
Tessie W. October ◽  
Amy H. Jones ◽  
Hannah Greenlick Michals ◽  
Lauren M. Hebert ◽  
Jiji Jiang ◽  
...  

2021 ◽  
Vol 13 (13) ◽  
pp. 7007
Author(s):  
Habtamu Nebere ◽  
Degefa Tolossa ◽  
Amare Bantider

In Ethiopia, the practice of land management started three decades ago in order to address the problem of land degradation and to further boost agricultural production. However, the impact of land management practices in curbing land degradation problems and improving the productivity of the agricultural sector is insignificant. Various empirical works have previously identified the determinants of the adoption rate of land management practices. However, the sustainability of land management practices after adoption, and the various factors that control the sustainability of implemented land management practices, are not well addressed. This study analyzed the factors affecting the sustainability of land management practices after implementation in Mecha Woreda, northwestern Ethiopia. The study used 378 sample respondents, selected by a systematic random sampling technique. Binary logistic regression was used to analyze the quantitative data, while the qualitative data were qualitatively and concurrently analyzed with the quantitative data. The sustained supply of fodder from the implemented land management practices, as well as improved cattle breed, increases the sustainability of the implemented land management practices. While lack of agreement in the community, lack of enforcing community bylaws, open cattle grazing, lack of benefits of implemented land management practices, acting as barrier for farming practices, poor participation of household heads during planning and decision-making processes, as well as the lack of short-term benefits, reduce the sustainability of the implemented land management practices. Thus, it is better to allow for the full participation of household heads in planning and decision-making processes to bring practical and visible results in land management practices. In addition, recognizing short-term benefits to compensate the land lost in constructing land management structures must be the strategy in land management practices. Finally, reducing the number of cattle and practicing stall feeding is helpful both for the sustainability of land management practices and the productivity of cattle. In line with this, fast-growing fodder grass species have to be introduced for household heads to grow on land management structures and communal grazing fields for stall feeding.


2021 ◽  
Author(s):  
Lars Dorren ◽  
Wouter Van Dooren

AbstractUsing ex ante analysis to predict policy outcomes is common practice in the world of infrastructure planning. However, accounts of its uses and merits vary widely. Advisory agencies and government think tanks advocate this practice to prevent cost overruns, short-term decision-making and suboptimal choices. Academic studies on knowledge use, on the other hand, are critical of how knowledge can be used in decision making. Research has found that analyses often have no impact at all on decision outcomes or are mainly conducted to provide decision makers with the confidence to decide rather than with objective facts. In this paper, we use an ethnographic research design to understand how it is possible that the use of ex ante analysis can be depicted in such contradictory ways. We suggest that the substantive content of ex ante analysis plays a limited role in understanding its depictions and uses. Instead, it is the process of conducting an ex ante analysis itself that unfolds in such a manner that the analysis can be interpreted and used in many different and seemingly contradictory ways. In policy processes, ex ante analysis is like a chameleon, figuratively changing its appearance based on its environment.


2021 ◽  
Author(s):  
Shir Dekel ◽  
Micah Goldwater ◽  
Dan Lovallo ◽  
Bruce Burns

Previous research found that anecdotes are more persuasive than statistical data—the anecdotal bias effect. Separate research found that anecdotes that are similar to a target problem are more influential on decision-making than dissimilar anecdotes. Further, previous investigations on anecdotal bias primarily focused on medical decision-making with very little focus on business decision-making. Therefore, we investigated the effect of anecdote similarity on anecdotal bias in capital allocation decisions. Participants were asked to allocate a hypothetical budget between two business projects. One of the projects (the target project) was clearly superior in terms of the provided statistical measures, but some of the participants also saw a description of a project with a conflicting outcome (the anecdotal project). This anecdotal project was always from the same industry as the target project. The anecdote description, however, either contained substantive connections to the target or not. Further, the anecdote conflicted with the statistical measures because it was either successful (positive anecdote) or unsuccessful (negative anecdote). The results showed that participants’ decisions were influenced by anecdotes only when they believed that they were actually relevant to the target project. Further, they still incorporated the statistical measures into their decision. This was found for both positive and negative anecdotes. Further, participants were given information about the way that the anecdotes were sampled that suggested that the statistical information should have been used in all cases. Participants did not use this information in their decisions and still showed an anecdotal bias effect. Therefore, people seem to appropriately use anecdotes based on their relevance, but do not understand the implications of certain statistical concepts.


Author(s):  
Kamal Pandey ◽  
Bhaskar Basu ◽  
Sandipan Karmakar

“Smart cities” start with “Smart Buildings” that improve the quality of urban services while ensuring sustainability. The current scenario in India reveals that the corporate and residential building structures are incorporating various self-sustainable techniques. Out of the multiple factors governing the comfort of smart buildings, indoor room temperature is an important one, since it drives the need of cooling or heating through controlling systems. Around one-third of total energy consumption of commercial buildings in India is attributed to Heating, Ventilation and Air Conditioning (HVAC) systems. Accurate prediction of indoor room temperature helps in creating an efficient equilibrium between energy consumption and comfort level of the building, thus providing opportunities for efficient decision making for energy optimization. Considering Indian climatic and geographical conditions, this paper proposes an efficient decision making approach using Bayesian Dynamic Models (BDM) for short-term indoor room temperature forecasting of a corporate building structure. The results obtained from Bayesian Dynamic linear model, using Expectation Maximization (EM) algorithm, have been compared to standard Auto Regressive Integrated Moving Average (ARIMA) model, and have been found to be more accurate. Forecasting of indoor room temperature is a highly nonlinear phenomenon, so to further improve the accuracy of the linear models, a hybrid modeling approach has been proposed. The inclusion of state-of-the-art nonlinear models such as Artificial Neural Networks (ANNs) and Support Vector Regression (SVR) improves the forecasting accuracy of the linear models significantly. Results show that the hybrid model obtained using BDM and ANN is the best fit model.


Sign in / Sign up

Export Citation Format

Share Document