Polarization and extremism emerge from rational choice: Estimation as a solution to biased sampling

Polarization is often described as the product of biased information search, motivated reasoning, or other psychological biases. However, polarization and extremism can still occur in the absence of any bias or irrational thinking. In this paper, we show that polarization occurs among groups of decision makers who are implementing rational choice strategies that maximize decision efficiency. This occurs because extreme information enables decision makers to make up their minds and stop considering new information, whereas moderate information is unlikely to trigger a decision and is thus under-represented in the information decision-makers collect. Furthermore, groups of decision makers will generate extremists -- individuals who hold strong views despite being uninformed and impulsive. In re-analyses of seven empirical studies spanning perceptual and preferential choice and a new study examining politically and affectively charged decisions, we show that both polarization and extremism manifest when decision makers gather information to make a choice. Polarization did not occur, however, when participants made an inference about the difference between two quantities as opposed to deciding which one is superior. Estimation therefore offers a theoretically-motivated intervention that can increase the amount of information people consider and reduce the degree of polarization and extremism among groups of individuals.

Using Intelligent Tools to Support Clinical Decision Making

Intelligent tools and collaborative systems can be used in healthcare contexts to support clinical decision making. Such an approach is concerned with identifying the way in which information is gathered and decisions are made along specific care pathways. This study develops a real-time collaborative system using an intelligent risk detection model (IRD) to improve decision efficiency in the clinical case of patients undergoing hip or knee arthroplasty. The benefits of adopting this improved clinical decision-making solution include increasing awareness, supporting communication, improving the decision making process for patients and caregivers while also improving information sharing between surgeons as key collaborative parties in the research case. This in turn leads to higher levels of patient and clinical satisfaction and better clinical outcomes.

Polarization and extremism emerge from rational choice

{Polarization is often thought to be the product of biased information search, motivated reasoning, or other psychological biases. However, polarization and extremism can still occur in the absence of any bias or irrational thinking. In this paper, we show that polarization occurs among groups of decision makers who are implementing rational choice strategies that maximize decision efficiency. This occurs because extreme information enables decision makers to make up their minds and stop considering new information, whereas moderate information is unlikely to trigger a decision. Furthermore, groups of decision makers will generate extremists -- individuals who hold strong views despite being uninformed and impulsive. In re-analyses of seven previous empirical studies on both perceptual and preferential choice, we show that both polarization and extremism manifest across a wide variety of choice paradigms. We conclude by offering theoretically-motivated interventions that could reduce polarization and extremism by altering the incentives people have when gathering information.

Should defense lawyers and prosecutors be appointed as judges?

This article analyses cases where independence between judges’ skills and states of nature affects decision efficiency in terms of the probability of making a correct collective decision, relative to the case where such independence does not exist. This article explains when it is advantageous to include either former defense lawyers who have expertise in obtaining an acquittal of defendants or former prosecutors who have expertise in obtaining a conviction, in a panel of judges.

Using Intelligent Tools to Support Clinical Decision Making

Intelligent tools and collaborative systems can be used in healthcare contexts to support clinical decision making. Such an approach is concerned with identifying the way in which information is gathered and decisions are made along specific care pathways. This study develops a real-time collaborative system using an intelligent risk detection model (IRD) to improve decision efficiency in the clinical case of patients undergoing hip or knee arthroplasty. The benefits of adopting this improved clinical decision-making solution include increasing awareness, supporting communication, improving the decision making process for patients and caregivers while also improving information sharing between surgeons as key collaborative parties in the research case. This in turn leads to higher levels of patient and clinical satisfaction and better clinical outcomes.

HOTEL SELECTION UTILIZING ONLINE REVIEWS: A NOVEL DECISION SUPPORT MODEL BASED ON SENTIMENT ANALYSIS AND DL-VIKOR METHOD

With the considerable development of tourism market, as well as the expansion of the e-commerce platform scale, increasing tourists often prefer to select tourism products such as services or hotels online. Thus, it needs to provide an efficient decision support model for tourists to select tourism products. Online reviews based on the user experience would help tourists improve decision efficiency on tourism products. Therefore, in this study, a quantitative method for hotel selection with online reviews is proposed. First, with respect this problem with online reviews, by analyzing sentiment words in online reviews, tourists’ sentiment preferences are transformed into the format of distribution linguistic with respect to sentiment levels. Second, from a theoretical perspective, we proposed a method to determine the ideal solution and nadir solution for distribution linguistic evaluations. Next, based on the frequency of words for evaluating hotel and the distribution linguistic evaluations, the weight vector of the evaluation features is determined. Further, a novel DL-VIKOR method is developed to rank and then to select hotels. Finally, a realistic case from TripAdvisor.com for selecting hotel is used to demonstrate practically and feasibility of the proposed model.

Profiles of human capital and strategic technological decisions on turbulence environment

<p>The objective of this article is to examine the absorptive capacity in the technology industry and aspires to recognize how firms can manage their strategic decisions in the turbulence contexts. In particular, we examine how organizations can strengthen their organizational contexts in order to absorb knowledge. From the knowledge management literature, this investigation extends our perception of the relationship between the human capital profiles (organization, research and development unit, and recent incorporations) and technological decision-making. Through the SEPI Foundation, a balanced panel of 1,220 Spanish industrial companies has used that answer to the Survey of Business Strategies (SBS) for a threeyear period, which signifies a total of 3,660 cases. The principal finding is the presence of high levels of human resources to understand a decision efficiency process. It also highlights its relationship to the firm’s technological committee. These contributions are notable for both researchers and practitioners. It could be stimulating to expand the study to the association between human capital profiles and other strategic technological decisions, as the preparation of an innovation plan or the measurement of innovation performance.</p>