Decision-making Mistakes Research Articles

Self-Supervised Learning for Near-Wild Cognitive Workload Estimation.

Feedback on cognitive workload may reduce decision-making mistakes. Machine learning-based models can produce feedback from physiological data such as electroencephalography (EEG) and electrocardiography (ECG). Supervised machine learning requires large training data sets that are (1) relevant and decontaminated and (2) carefully labeled for accurate approximation, a costly and tedious procedure. Commercial over-the-counter devices are low-cost resolutions for the real-time collection of physiological modalities. However, they produce significant artifacts when employed outside of laboratory settings, compromising machine learning accuracies. Additionally, the physiological modalities that most successfully machine-approximate cognitive workload in everyday settings are unknown. To address these challenges, a first-ever hybrid implementation of feature selection and self-supervised machine learning techniques is introduced. This model is employed on data collected outside controlled laboratory settings to (1) identify relevant physiological modalities to machine approximate six levels of cognitive-physical workloads from a seven-modality repository and (2) postulate limited labeling experiments and machine approximate mental-physical workloads using self-supervised learning techniques.

Effect of age on susceptibility to the attraction effect in sequential risky decision-making

Abstract Our study aims to contribute to the existing body of research on age-related changes in decision-making by investigating susceptibility to the attraction effect across adulthood. Prior studies have produced inconsistent conclusions regarding the decision-making abilities of older individuals, with some portraying them as easily manipulated and risk-averse, while others suggest the opposite. To address this issue, we conducted two experiments using a novel paradigm of the roulette task: (1) in an online environment with 357 participants and (2) in a laboratory setting with 173 participants. The results were consistent and demonstrated the robustness of the attraction effect. However, no age differences in susceptibility to the attraction effect as a common decision bias were found. As predicted, older adults were more likely to commit simple decision-making mistakes, especially in the preliminary trials, which could have serious financial or societal consequences. Additionally, older adults exhibited more risk-seeking behaviours. Furthermore, we observed that the dynamics of decision competence (as indicated by a decrease in the selection of erroneous decoy options and an increase in decision fluency) were similar for both younger and older adults, suggesting preservation of the ability to optimise decision-making while becoming familiar with new tasks. These findings provide insight into the cognitive functioning of older adults and indicate that decision-making abilities in late adulthood may be more complex than commonly assumed.

Industrial policy persistence and local economic performance: The role of subsidy allocation in China

The persistence of economic policies is crucial for their effectiveness and economic outcomes. However, debates on industrial policy effectiveness have primarily focused on policy tools and target sectors, with little attention given to policy persistence. This paper addresses this gap by evaluating how policy persistence during subsidy implementation affects policy effectiveness. We measure policy persistence using cosine similarity between vectors reflecting the cross-industry distribution of subsidies over consecutive years and instrument it with the occurrence of abrupt public safety incidents. Our results reveal a significantly positive effect of subsidy allocation persistence on local economic performance. This effect is stronger when local governments are influential or industries need consistent government support and weaker when policy changes are more predictable or local officials are less prone to decision-making mistakes. We further provide micro-level evidence showing that the persistence of industrial policies impacts local economic performance by influencing the activities of local businesses.

Pengaruh Manajemen Laba, Intellectual Capital dan Related Party Transaction terhadap Integritas Laporan Keuangan: Studi pada Perusahaan Sektor Manufaktur yang Terdaftar di Bursa Efek Indonesia Periode 2018-2021

In order for the information obtained by users of financial statements to be accounted for by the firm, financial statements and statements by corporations must be provided honestly, correctly, and without distortion or concealment. Users use financial reports as a decision-making tool since they provide an overview of the performance and growth of the organization. Conservativeness proxies may be used to evaluate the reliability of the financial accounts. To minimize fraud in financial reports and mistakes in decision-making, conservative accounting is the practice of presenting financial statements that are full of caution against important uncertainties and risks to a commercial business's situation. The goal of this research is to assess the financial reporting accuracy of manufacturing sector businesses listed on the Indonesia Stock Exchange (IDX) from 2018 to 2021 in the areas of intellectual property, related party transactions, and earnings management. This study uses the manufacturing sector of the IDX as its sample population for the years 2018 through 2021. Purposive sampling was employed, and data was collected from 408 samples representing 102 different firms over the course of four years. Panel data regression analysis using the Eviews 10 software is used for this in-depth examination of the data, which involves several rounds of testing. Financial statement accuracy was shown to be impacted by the presence of related party transactions, intellectual property, and earnings management. Earnings management reduces financial statement reliability. On the other hand, related party transactions and intellectual property have no bearing on how accurate the financial records are.

Assessing the impact of chart design and time intervals on the usability of time series data visualization: A Case Study on Cryptocurrency Data

Based on Google Trends, searches related to cryptocurrency have significantly increased in the last couple of years. One crucial aid for cryptocurrency traders or investors is the graphical visualization, which shows the time series data of the cryptocurrency prices. However, problems may occur in data visualization, such as visual noise and information loss, which cause perceptual and cognitive errors in data reading. Therefore, good visualization is needed to avoid decision-making mistakes, particularly in the cryptocurrency trade and investment activities. This study aims to investigate the effect of chart design and time interval on the usability of data visualization. The experiments are conducted in two scenarios, i.e., with and without time pressure. The participants recruited in this study were non-experienced and experienced people classified based on their familiarity with cryptocurrency investment/trading. Objective usability testing is performed by eye tracking, while subjective assessment employs the System Usability Scale (SUS) questionnaire. There are four quantitative dependent variables: response time, number of errors, number of fixations, and time to first fixation. The results show that time interval and time pressure significantly affect usability for both groups of respondents. Although chart design does not substantially affect the dependent variables, a candle chart is generally better than a line chart. By comparing all the combinations of chart design and time intervals, this study concluded that combining candle charts with 1-hour or 4-hour time intervals gives the best results for both respondent groups.

Stakeholders’ positioning in the projects’ implementation

Today, most people are talking about project activities and their effectiveness. Among the aspects considered in project management, there is no management of stakeholders, although their influence and participation determine the success of the project. Positioning is an important stage in project management, because it is the correct distribution of stakeholders into groups that makes it possible to build the right strategy for interacting with t stakeholders and minimize their negative impact on the project. There are several approaches to stakeholder positioning in the scientific literature, but they are not always used in practice. This decision is due to distrust of the positioning stakeholders’ process, possible mistakes in decision-making and the lack of a program to help the project manager. The article presents a way to improve the process of positioning stakeholders by creating a desktop application. Such application was developed by the authors of the article through one of the most popular programming languages Python and the well-known PyQt5 framework. As a result of using the application, the project manager receives a completed matrix where stakeholders are located on the basis of the completed information, and the opportunity to get the most out of working with stakeholders.

Design and Performance Study of Improved Fuzzy System with Genetic Algorithm

Technical trading relies heavily on analysis, most of which is statistical in nature. When the data to be modeled is nonlinear, imprecise, or complicated, fuzzy inference systems (FISs) are used in conjunction with computational, mathematical, and statistical modeling methodologies to simulate technical trading. Fuzzy logic may be modeled using linear, nonlinear, geometric, dynamic, and integer programming. These techniques, when combined with fuzzy logic, help the decision-maker arrive at a better solution while still facing some degree of ambiguity or uncertainty. The moving average method is a useful metric that may give trade recommendations to aid investors further. While trading signals inform investors of when to purchase and sell, a simple moving average provides no such information. In this research, we suggest a fuzzy moving average approach in which the intensity of trading signals, measured in terms of trading volume, is determined by using the fuzzy logic rule. In this research, we propose using fuzzy logic technical trading rules, which are more resistant to decision-making mistakes, to mitigate the trading uncertainty inherent in the conventional technical indicators method.

Hiscovid for visualizing and identifying when policymakers made mistakes against COVID-19.

There are two types of policy outcome analysis tools: snapshot tool and time-series tool. hiscovid is a time-series policy outcome scoring tool of COVID-19 policies by country where the daily cumulative population mortality is used for scoring the outcomes of COVID-19 country policies to visualize and identify when policymakers made mistakes. hiscovid allows policymakers to observe the progress and transition of scores over time to learn lessons from the past decision-making mistakes for correcting the current policies to reduce unnecessary deaths. The lower the score, the better the policy. hiscovid attracted 1480 users worldwide.

Research on Psychological Deviation of Young Investors Based on Questionnaire

With the continuous development of China's securities market, many market effects have been widespread for a long time. However, the rapid development of behaviour finance precisely integrates people's psychological factors and behaviour science into finance and conducts in-depth research on the behavioural and psychological deviation affecting economic decisions. Due to the late start of the research on the securities market in China, the relevant theoretical basis is not perfect. If investors lack an empirical basis, they will often be affected by various cognitive and psychological biases, leading to investment decision-making mistakes. Given this, this paper focuses on young investors in China and uses a questionnaire to test this group for cognitive, psychological, and behavioural biases. Based on the results of the test, this paper proposes coping strategies how to avoid or reduce bias and thus improve the accuracy of investment decisions.

Anticipatory foresight and adaptive decision-making as a crucial characteristic for business continuity, crisis and emergency leadership

This paper reviews some of the common challenges to high-quality decision-making at the leadership level, such as limiting decision shortcuts, analytical blind spots, failure to consider multiple perspectives or options, and reluctance to adjust decisions that are not working well. The paper also reviews some of the pertinent literature and scholarship on decision-making approaches to build a summative decision-making model of anticipatory foresight and adaptation to overcome dysfunctional decision-making mistakes. The paper proposes a new framework that focuses on the internal decision-making processes that leaders should adopt — an approach to decision-making that combines the concepts of anticipatory foresight, predictive vision, creative imagination, adaptive skill sets and adaptive flexibility. It is essential to incorporate these dimensions in how we prepare leaders, equip and train them, create processes and protocols, and ultimately how we evaluate and assess leadership performance.

Systematic review of health policy and behavioral economics: A neglected point in health promotion.

Health policymakers use a variety of policy tools. These policies are either based on external factors or are based on paternal considerations; people may need to have help in the selection of items that may be regretted about them in the future. However, recent research on behavioral economics shows that major decision-making mistakes are not only limited to vulnerable groups but also are ubiquitous and systematic. The purpose of this study was on health policy making with a behavioral economics approach in health promotion. The eligible studies were obtained from Medline (PubMed), Web of Science, and Scopus databases. The search strategy uses a combination of keywords in the titles. The keywords of behavioral economics along with the keyword of health have been used to find related articles. After deleting duplicate articles, a total of 38 articles were identified. After reviewing the title and abstract, 13 studies were omitted because they did not meet the inclusion criteria. Ten articles were removed from the found articles due to the unavailability of the full text and four articles were excluded because their method was quantitative. Finally, a total of 11 articles were eligible for including this review study. Recent research on behavioral economics shows that decision-making errors are not limited to vulnerable groups but are ubiquitous and systematic. Forgotten income or negligible income is very high and is reasonably explained by transaction costs. Educational interventions often have little effect and do not benefit from basic cost-benefit tests. In addition, the seemingly insignificant aspects of choice-frameworks and assumptions-often have a profound effect on behavior.

Съезды московского общества сельского хозяйства: система развития аграрных преобразований. XIX – начало XX в.

In the proposed article, on the basis of the materials of the Moscow Society of Agriculture identified in the fund of the Central Scientific Agricultural Library. With the involvement of the developments of researchers on the history of agrarian thought in Russia in the 19th and early 20th centuries, forms of communication between the scientific and professional communities are determined for the modernization of the agricultural sector of agriculture after the peasant reform of 1861 of the year. The publication highlights the main forms of communication: the publishing activity of the Society, the organization of exhibitions and congresses. To assess the large-scale activities of the Moscow Society of Agriculture for 110 years, a brief overview of its practical work is presented, and the role in the agrarian rationalization of agriculture in Russian historiography is revealed. Members of the Moscow Society have made a significant contribution to the study of the state of agriculture, ways of evolution and methods of increasing its productivity. On the example of materials from three All-Russian congresses on agronomic assistance to the population, the organizational aspects of resolving issues of agricultural management in the regions of Russia. The role and significance of the public initiative is especially valuable today, when the problems of innovative renewal and modernization of the agricultural sector are becoming a national task. For its successful solution, the documents of the congresses can be useful, since they make it possible to trace the genesis of the processes of agricultural development in various thematic areas and economic zones in historical terms and to avoid possible mistakes in decision-making.

Doing the right thing or doing things right: what is better for a successful manufacturing reshoring?

The article concerns the revision of earlier decisions to offshore production activities (so called “relocation of second degree”); more specifically it is focused on the “reshoring” (also referred as “relocation to the home country”, “back-reshoring” or “back-shoring”). The research aims are to investigate what types of mistakes occur along the decision-making and implementation process and how they affect the outcome, in terms of success or failure, of a relocation strategy. A multiple case study involving four companies in the fashion industry from Portugal and Italy was conducted. The cross-case analysis allowed to differentiate decision-making mistakes from implementation ones and to assess differences and similarities among the cases in terms of content of the relocation, drivers and outcomes. The research contributes to previous literature on reshoring by bringing evidence of different types of mistakes to be considered, thus requiring further conceptualization of the reshoring process. Managers and entrepreneurs should consider the importance of doing the things right also during the implementation, too often underestimated. The present article is the first one in the reshoring literature bringing evidence of cases of failure in the relocation decisions and discriminating among different kinds of mistakes.

Estimating the outcome of an active phase in the military conflict on Eastern Ukraine based on the Sugeno fuzzy integral

A military conflict (especially its active phase) is a time of maximum exertion of all the powers of the state and society, a time that requires quick and correct decisions from state bodies. The quality of these decisions is largely determined by the estimation adequacy of the current situation. As the analysis shows, modern military conflicts start suddenly and develop rapidly. The official informing system turns out to be ineffective, what leads to numerous mistakes in decision-making. In addition, modern military conflicts are of a hybrid nature. The outcome of such military conflicts depends on many factors of a non-military nature, for example, the quality of governance, support from the population, international assistance. These factors are often formulated qualitatively (linguistically), and the conditions of the active phase of a military conflict do not give time to check the adequacy of quantitative data. Therefore, it is necessary that the method for estimating the outcome of the active phase takes into account the data uncertainty and ensures a generalization of the partial characteristics of the current situation. Based on the analysis of known approaches to the description and processing of uncertainty, the authors proposed using the methods of fuzzy integral calculus to describe partial characteristics and calculate a generalized characteristic, which is an estimation of the success of the outcome of an active phase. The authors have solved the following subproblems: identification of structure and parameters of standard for estimating; choice of the observation channel of the characteristics of the current situation; constructing the algorithm for estimations generalization. The authors demonstrated the work of the proposed algorithm by the example of estimating the results of hostilities in eastern Ukraine in July 2014.

Emotional Turmoil and Time Constraints Decrease the Ability of Team Members to Communicate Effectively and Make Decisions

Emotional Turmoil and Time Constraints Decrease the Ability of Team Members to Communicate Effectively and Make Decisions

Charles Davenant on the objectives and principles of “political arithmetic” as an instrument of public administration

In the late XVII century in England has establishes the school of “political arithmetic”, which goal consisted in the analysis of social phenomena on the basis of quantitative indicators. Its main representatives became William Petty, John Graunt and Charles Davenant (1656-1714). The latter left a mark in the history of England as a philosopher, politician and publicist, who made a significant contribution to the development and implementation of the methods of “political arithmetic”. The object of this research is the views of the English thinker, reflected in his pamphlets and treatises of the 1690’s. The subject is the Davenant’s views on the principles and tasks of “political arithmetic” in the context of his political theory. Special attention is given to correlation between Davenant’s views on the development of “political arithmetic’ and his concept of public administration. The scientific novelty lies in the comprehensive examination of the political and economic views of Charles Davenant within the framework of his attitude on the method of “political arithmetic”. The author delivers a thesis on the importance of the political and epistemological context, which formed Davenant’s views on the quantitative indicators. Grasp of quantitative data Davenant correlated directly with the practice of administration. According to the philosopher, a public official having the capacity for “evaluation” and proper interpretation of data could avoid many mistakes in decision-making and reliance on “bad” advices. The thinker suggested that possession of quantitative data and their competent interpretation could increase the efficiency of administration.

Site selection framework of fishing photovoltaic hybrid project under interval-valued intuitionistic fuzzy environment

Abstract The main objective of this paper is to propose a decision-making framework for FPHP to evaluate and select the optimal site to achieve the win-win situation. In order to achieve this goal, this study proposed a decision index system which consist of 5 attributes, 12 criteria and 29 sub-criteria. The novelty of this decision index system is that it not only considers the site selection requirements of SPPS, but also consider those of fish farm. It avoids the problem that too much attention is paid to SPPS, which makes the fish farm unsustainable. The proposed decision model was established based on the IVIFN and fuzzy measure. Its novelty is that it can handle with the problems, such as the diversity of data forms, the inability to reflect the professionalism in the fuzzy measure and the inability to satisfy the independence assumption in reality, which the FPHP must face in the process of site selection but the common used decision models cannot deal with. Then, the proposed site selection framework of FPHP was used in a case to show its applicability. The sensitivity analysis is performed to verify the robustness of the proposed site selection framework, meanwhile, the comparative analysis is performed to show the fact that if the site selection requirement of fish farm and the problems in the FPHP site selection are not considered, it will lead to decision-making mistakes.

Investigating the effect of personality on left-turn behaviors in various scenarios to understand the dynamics of driving styles

Objectives: To explore whether the driving style is static or dynamic, the purpose of this study was to investigate the effects of drivers’ personality traits and driving scenarios on left-turn behaviors. We also evaluated drivers’ perceptions in different situations to understand the occurrence of unreasonable driving behaviors.Methods: Two self-administered questionnaires were used to calculate participants’ personality dimensions and driving style scores, respectively. Two experimental tasks were conducted by driving simulator with different weather, light, and speed of the opposing through vehicles.Results: Results showed that personality was significantly related to driving style. Neither the left-turn response process nor gap acceptance maneuvers were directly influenced by light conditions. In the test area, the average speed and the minimum speed of the left-turning vehicle, as well as the distance of the vehicle from the collision point when the speed is the smallest were significantly related to the weather, interaction type, and velocity difference, and the time to collision during which first brake or release gas pedal occurs was significantly related to velocity difference. Three out of the four driving conditions (except for light conditions) exhibited a statistically significant effect on the judgment of the arrival time of autonomous vehicles and their risk assessment, and personality was significantly related to risk assessment. Moreover, dangerous driving behavior was found to be significantly associated with drivers’ driving personality.Conclusions: The driving style is dynamic and influenced by personality and driving conditions. Not only the wrong assessment of driving scenarios may lead to danger, but also the driver’s personality characteristics such as self-interest, impulsively, and lack of self-confidence will lead to decision-making mistakes even when the judgment of driving scenarios is correct.

Hunting white elephants on the road. A practical procedure to detect harmful projects of transport infrastructure

The white elephant concept is used to qualify public investments representing a severe misallocation of society's resources or expenditures that can be deemed to reduce the wellbeing of its future members. In the transport sector, white elephants (WEs) are particularly relevant due to the vast amount of resources involved in large-scale infrastructure projects and to their long lifecycle. In most articles on the subject, WEs are major projects showing a certain political or even economic short-term appeal but that are essentially inefficient. In this paper, the definition includes, beyond those that are inefficient, projects that are financially unsustainable and/or very unfair to future generations when properly analysed over their project lifecycle. An early identification as WEs of those efficient projects from the socioeconomic point of view that are bound to entice the failure of a main stakeholder or are unfair to future generations, facilitates reconsidering their financial structuring in order to make them acceptable and avoid the WE label.The authors propose a new approach to detect WEs that goes beyond the traditional detection through standard techniques, such as cost-benefit analysis (CBA), and involves the incorporation in decision-making of new indicators. Those of the Intergenerational Redistributive Effects Model (IREM) show the importance of the long-term impacts arising from major investment in transport infrastructure. Using the annuities of the socioeconomic CBA and financial analyses, the IREM indicators allow a look beyond the future impact of the project on society's welfare –measured through conventional CBA– and its capacity of being financed, and produce a good assessment of its intergenerational effects. In this paper, the authors present the results of applying IREM to a set of transport projects in the European Union and, with more detail, to several Spanish motorway projects with private financing. The IREM's outputs indicate that most of the projects in the sample will be fair to future generations. Some of the analysed investments could, however, be considered as WEs when applying the intergenerational perspective. IREM appears therefore to be a useful tool to avoid decision-making mistakes in major infrastructure projects.

Tilting at windmills: The flawed U.S. policy toward the 1971 Indo-Pakistani war

ABSTRACTThis article examines decision-making mistakes made by U.S. President Nixon and national security advisor Kissinger during the 1971 India-Pakistan crisis and war. It shows that Nixon and Kissinger routinely demonstrated psychological biases that led them to overestimate the likelihood of West Pakistani victory against Bengali rebels as well as the importance of the crisis to broader U.S. policy. The evidence fails to support Nixon and Kissinger’s own framing of the 1971 crisis as a contest between cool-headed realpolitik and idealistic humanitarianism, and instead shows that Kissinger and Nixon’s policy decisions harmed their stated goals because of repeated decision-making errors.