Mechanisms Underlying Economic Choice

This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple measurement of cognitive uncertainty generates novel insights about what people find complex and how they respond to it.

Research in perceptual decision making is dominated by paradigms that tap the visual system, such as the random-dot motion (RDM) paradigm. In this study, we investigated whether the behavioral signature of perceptual decisions in the auditory domain is similar to those observed in the visual domain. We developed an auditory version of the RDM task, in which tones correspond to dots and pitch corresponds to motion (the random-tone pitch task, RTP). In this task, participants have to decide quickly whether the pitch of a “sound cloud” of tones is moving up or down. Stimulus strength and speed–accuracy trade-off were manipulated. To describe the relationship between stimulus strength and performance, we fitted the proportional-rate diffusion model to the data. The results showed a close coupling between stimulus strength and the speed and accuracy of perceptual decisions in both tasks. Additionally, we fitted the full drift diffusion model (DDM) to the data and showed that three of the four participants had similar speed–accuracy trade-offs in both tasks. However, for the RTP task, drift rates were larger and nondecision times slower, suggesting that some DDM parameters might be dependent on stimulus modality (drift rate and nondecision time), whereas others might not be (decision bound). The results illustrate that the RTP task is suitable for investigating the dynamics of auditory perceptual choices. Future studies using the task might help to investigate modality-specific effects on decision making at both the behavioral and neuronal levels.Electronic supplementary materialThe online version of this article (doi:10.3758/s13414-013-0447-8) contains supplementary material, which is available to authorized users.

To explore how group effect generates and how it influences individual’s economic decision-making from the two levels of psychological cognition and behavior choice, as well as the prerequisites for differentiating into two different effects, this study compares the individual different acceptance degree of fair/unfair offer from inside and outside the group in making economic decision through designing the model of ultimatum bargaining game based on decision-making neuroscience. What’s more, the study attempts to explore the preconditions of the two completely different phenomena of in-group preference and black sheep effect and uses ERP technology to find the cranial nerve basis of this effect so as to reveal the brain’s thinking process.

This computerized system, which collects, processes, and stores data on and analyzes and reports the performance of production equipment and operations, is one step closer to the optimum profitability of producing properties. It is designed primarily to be used by the production man properties. It is designed primarily to be used by the production man directly responsible for day-to-day economic decisions. Introduction In any attempt at optimizing operations by means, for example, of a failure-control program, basic information is required for defining the nature and magnitude of the problems involved and for estimating the economic stakes. The information determines whether or not one should try to solve a particular problem; and if more than one solution is possible, it aids in deciding on the most profitable one. In short, the basic information makes it possible to set economic priorities to the solution of problems. Methods of obtaining basic information related to equipment performance have been the subject of much work. Many oil-producing companies have created and now operate data gathering and processing systems, all of which have two things in common: they obtain accurate and timely information and process and condense it into an easily usable and process and condense it into an easily usable and digestible form; and they use computers to process and report data. Atlantic Richfield has created a system for data gathering and handling that has been in use throughout its Continental U. S. and Canadian operations since late 1969. This system, known as the Equipment Performance Reporting System, relies heavily on the use of computers. It was developed as a cooperative effort with field personnel to the point that it is now part of the Company procedures. By late 1971 the system had more than 34,000 records in its data banks. Since its inception, the original concept of a data gathering and processing system for use by production personnel has been expanded according to needs production personnel has been expanded according to needs discovered as a result of using the system. These needs are: (1) to set better specifications for subsurface and surface equipment, (2) to predict future performance of equipment, and (3) to follow closely performance of equipment, and (3) to follow closely the economic impact of remedial action such as area-wide corrosion treating programs. The Equipment Performance Report System-Part One The Equipment Performance Report System consists of four parts. The following discussion will be limited to Part One, which is concerned with subsurface failures, and to Part Three, which handles well inhibition. Parts Two and Four will be described later. As early as 1964, Fincher and Nunn defined a usable data gathering and processing system as one that contains1. A simple report form,2. Complete data about each reported event,3. Computer processing for rapid data handling, and4. Output in the form of orderly and concise data summaries for easy review. JPT p. 185

This dissertation explores the early modern English stage as a significant site for producing, exploring, and meditating on psychological uncertainty, specifically through encounters between human characters and representations of the supernatural. I argue that the psychological disturbance these encounters engender allows for a re-evaluation of the process and nature of belief formation. Rather than dismiss dramatic supernatural representations as I would like to start off by thanking the wonderful faculty, staff and students of the Department of English, who have all contributed to creating such a warm, communal and collegial environment. I feel very lucky to have been part of this department for the last five years, as it has taught me so much about what it means to be a colleague, a teacher, a mentor, and an involved member of an academic community. I would like to extend thanks particularly to Dr.

To work effectively for commercial companies in different sectors of the economy, it is of interest to business owners, investors, management, employees, the state and society as a whole. The efficiency of commercial companies is crucial for the process of financial and economic decision-making. In Latvia, there have been neither in-depth research studies on the efficiency of financial activity, nor studies on the efficiency of certain sectors of the economy. The aim of the research is to summarize and analyse data on factors influencing the operational efficiency of commercial companies working in the national economy sectors: number of employees in the sectors, number of enterprises, value of exports and imports, personnel costs and number of employees in enterprises of a given sector, gross investments in material matters, land, machinery, equipment, non-financial investments in intangible assets and fixed assets, turnover, indicators of financial performance of enterprises, which provide aggregated information on liquidity, profitability and solvency of enterprises. The data processing used ibm spss statistics v21 method. The result of the research study is to group the factors that have a significant impact on the efficiency of the economic sector.

At present, the question of choosing the right approach to hydrodynamic studies and the subsequent processing of the data obtained is highly relevant. The quality of the research and, accordingly, data processing is influenced by various factors, such as the lithological composition of the rocks, their density, mechanical stresses in the rock, the hydrodynamic effect of cracks, the filtration motion of liquids, the distribution of pressure and temperature in the formation. Deposits of Yamashneft OGPD are at a late stage of development, most wells are stripped. All of the above mentioned factors can affect the results of the treatment of the pressure buildup curve (PBC), which often differ from the actual values of the bottomhole zone parameters of the formation, which indicates an incorrect approach to research (recovery time) and selection of the treatment method. The issues of obtaining reliable information at a late stage of development are of particular importance, since it is on their basis such important technological and economic decisions are taken as the disconnection of the waterlogged reservoirs and stripped wells, and technological measures for increasing the oil recovery factor are planned and implemented. When carrying out hydrodynamic studies of wells and interpreting the obtained data, it is necessary to take into account the structure of the investigated formation, the features of the pore space, the geological and physical characteristics, which will allow a correct calculation of the porosity and permeability properties. So, the geological and physical data of operational objects were generalized, the dependence of the influence of the properties of the developed formation and the physico-chemical parameters of the extracted products on the shape of the PBC was made, the application of the adapted methods of interpreting the curves depending on the given development conditions was proposed, a method of studying wells allowing to combine the process of swabbing with the study was presented.

Identifying what mechanisms are exactly used by individuals in economic decisions is one core objective of different disciplinary fields, ranging from economics, psychology, cognitive science, and neuroscience. Although significant progress has been made among the different fields over the last decades, the identification of different choice mechanisms is not trivial, and research still faces a number of challenges, such as inappropriate reverse inferences (Krajbich et al., 2015). In the current thesis, I provide insights into the understanding and measurement of economic choice mechanisms. My research questions are based on the analysis of data properties that are specific to a mixture of different strategies and are not susceptible to reverse inference problems, as well as the development of carefully designed experimental tasks and setups to mitigate those problems. In Chapter 2 and 3, specifically, I tackle the application of the fixed-point property (FP) and its ability to identify the presence of a mixture of cognitive processes in experimental data. The FP is a particularly useful property of mixture distributions (Falmagne, 1968). Consider an experiment where two processes jointly account for the final behavior (e.g., RTs) and the relative contribution—i.e., mixture proportion— of each process for the final behavior changes, depending on the experimental conditions. The FP entails that, under such experiment, the observed distributions of a dependent variable for the different experimental conditions all cross at the same point (Falmagne, 1968). Leveraging this method, some researchers have already identified mixture distributions in their experimental data (Couto et al., 2020; Grange, 2016; Maanen et al., 2014; Poboka et al., 2014). However, some performance metrics are still missing for researchers aiming to apply the FP. In Chapter 2 and 3, I provide such performance metrics. In Chapter 4 and 5, I systematically investigate and dissociate different choice mechanisms with the use of carefully designed experimental tasks and setups. To investigate multiple choice mechanisms experimentally, researchers have leveraged the presumed difference in processing speed between different types of processes and assumed that slow(er) decisions represent one type of process and fast(er) decisions other type (Rubinstein, 2007). Likewise, researchers have used time pressure as a manipulation to make inferences about the nature of the processes (Kocher et al., 2018). This reasoning has been applied in behavioral economics to investigate whether individuals are naturally inclined to be e.g., risk-averse or risk-seeking under time pressure (Kirchler et al., 2017; Kocher & Sutter, 2006). However, the effects of time pressure are still inconsistent between studies (Kocher et al., 2018), showing that there is not always a correlation between measured RTs (i.e., faster decisions) and risk behavior (i.e., safer decisions). It is therefore crucial that multiple choice mechanisms are investigated and interpreted comparatively and relative to specific experimental factors (i.e., in addition to time pressure) and/or through the analysis of both behavioral and neural signatures (i.e., in addition to measured RTs and/or risk behavior). The research I conduct in Chapter 4 and 5 is based on these research objectives.

INTRODUCTION: Quantum computing technology has become a center of attention in various scientific disciplines, including economic analysis. The adoption of quantum computing in economic analysis offers tremendous potential to improve the processing of complex economic data and provide deep insights. However, the use of quantum technology in the context of distributed information systems also raises several challenges, including data security and the limitations of quantum technology. OBJECTIVE: This research aims to investigate the implications of adopting quantum computing in economic analysis, with a focus on distributed information systems. METHODS: This research was carried out using a descriptive qualitative approach, with data derived from the results of relevant research and previous studies. The collected data will be processed and analyzed to gain a deeper understanding of the adoption of quantum computing in economic analysis in distributed information systems. RESULTS: This research then finds that the adoption of quantum computing in economic analysis has the potential to increase efficiency, accuracy, and depth of economic insight. However, limitations of current quantum technologies, including quantum errors, limited scale of operations, and data security issues, limit their applications. In the long term, research and development will be key to overcoming these obstacles and maximizing the potential of this technology in economic analysis. CONCLUSION: The long-term implications include increased economic competitiveness and significant changes in the way economic decision-making is carried out, assuming that ethical and regulatory issues are also carefully considered.

Research on IS success and IT adoption has shown that object-based beliefs about IT systems have a profound impact on subsequent IT usage. However, we still lack knowledge on and need to identify antecedents and determinants of object-based beliefs in order to understand how the belief formation process works and how it can be influenced. Our research builds on and extends Markus and Silver's (2008) concepts of functional affordance and symbolic expression to examine how IT-related factors influence the formation of beliefs. To test our research model, we surveyed 183 users of a student information system. The proposed model was supported, offering evidence that values, meaning, and functional affordances provided by an IT system positively affect information quality and system quality.

Do humans make good decisions?

Since 1981, James Fowler’s stage model of faith development has provided researchers with a framework for understanding the ways in which people develop belief systems over the course of their lives. Despite its helpfulness, there are several notable areas of critique that can be levelled against the model, including its lack of parsimony, heavy reliance on structural-developmental design, and lack of responsiveness to diversity. This article revises Fowler’s stage model into a process model, reducing the seven stages of his original design into four process steps that occur during belief formation and re-evaluation. These four steps – religious socialisation, early questioning, exploration and engagement, and refinement – can offer researchers a meaningful and parsimonious path for understanding the process of belief formation, transition, and maintenance. Implications and future directions are discussed.

Coordination games often have multiple equilibria. The selection of equilibrium raises the question of belief formation: how do players generate beliefs about the behavior of other players? This article takes the view that the answer lies in history, that is, in the outcomes of similar coordination games played in the past, possibly by other players. We analyze a simple model in which a large population plays a game that exhibits strategic complementarities. We assume a dynamic process that faces different populations with such games for randomly selected values of a parameter. We introduce a belief formation process that takes into account the history of similar games played in the past, not necessarily by the same population. We show that when history serves as a coordination device, the limit behavior depends on the way history unfolds, and cannot be determined from a-priori considerations.

A decision maker is asked to express her beliefs by assigning probabilities to certain possible states. We focus on the relationship between her database and her beliefs. We show that if beliefs given a union of two databases are a convex combination of beliefs given each of the databases, the belief formation process follows a simple formula: beliefs are a similarity-weighted average of the beliefs induced by each past case.

The article is devoted to big data investments for economic decisions. The work reflects some aspects of the use of big data in various fields of economic activity, especially forecasting market trends of the company's activities, economic feasibility of investments, investment management and making investment decisions through optimization and risk management. It is about the methodology of data processing and analysis, as well as machine learning and artificial intelligence technologies, provides a valuable presentation of information. Also considered are the difficulties of implementing big data, such as privacy issues, ethical issues and data reliability issues. The author's conclusion is that the use of big data to a large extent allows to highlight the accuracy and efficiency of solving economic issues, but requires appropriate skills and technologies for the implementation of data. Keywords: big data, economic decision making, forecasting, business process optimization, machine learning, artificial intelligence, risk management, data analysis.