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This review presents an approach to modeling decision making under misspecified subjective models. The approach is based on the idea that decision makers impose subjective causal interpretations on observed correlations, and it borrows basic concepts and tools from the statistics and artificial intelligence literatures on Bayesian networks. While these background literatures used Bayesian networks as a platform for normative and computational analysis of probabilistic and causal inference, in the framework proposed here graphical models represent causal misperceptions and help analyze their behavioral implications. I show how this approach sheds light on earlier equilibrium models with nonrational expectations and demonstrate its scope of economic applications.

Purpose Recent literature in the field of knowledge management (e.g. Nonaka and Takeuchi, 2021) asks for new, future-oriented approaches to strategy that allow us to deal with an increasingly complex world. Thus, this paper aims to build an approach to exploit aesthetics (human’s sensory perceptions and their felt meanings) to sense an organizations purpose and realize it by means of organizational strategy. Design/methodology/approach Conceptual paper, providing a new perspective on the perception of Organizational Purpose. The abductive argument follows Weick’s notion of Disciplined Imagination (Weick, 1989). Findings The main argument of this paper is that aesthetics contribute to the identification of organizational purpose. Thus, aesthetic perceptions can inform strategy to implement a stakeholders’ sense of purpose into strategy. Research limitations/implications The argument presented is grounded in recent literature on the concepts of purpose and aesthetics and abductive in nature. Thus, empirical research to validate the argument would be beneficial and worthwhile to be undertaken. Practical implications The paper presents the idea to integrate the sense of organizational purpose into a corporate strategy to address stakeholders’ value expectations and build more sustainable organizations. By emphasizing aesthetics, the study takes a stand for the inclusion of nonrational knowledge in organizational decision-making. Originality/value As far as the author’s knowledge goes, the concepts of aesthetics and organizational purpose have not theoretically been connected to each other. However, due to the implicit nature of purpose, aesthetics may serve as the matching knowledge tool to work with organizational purpose.

Does media bias affect voting? We analyze the entry of Fox News in cable markets and its impact on voting. Between October 1996 and November 2000, the conservative Fox News Channel was introduced in the cable programming of 20 percent of U. S. towns. Fox News availability in 2000 appears to be largely idiosyncratic, conditional on a set of controls. Using a data set of voting data for 9,256 towns, we investigate if Republicans gained vote share in towns where Fox News entered the cable market by the year 2000. We find a significant effect of the introduction of Fox News on the vote share in Presidential elections between 1996 and 2000. Republicans gained 0.4 to 0.7 percentage points in the towns that broadcast Fox News. Fox News also affected voter turnout and the Republican vote share in the Senate. Our estimates imply that Fox News convinced 3 to 28 percent of its viewers to vote Republican, depending on the audience measure. The Fox News effect could be a temporary learning effect for rational voters, or a permanent effect for nonrational voters subject to persuasion.

We offer an institutional explanation for the contemporary expansion of formal organization—in numbers, internal complexity, social domains, and national contexts. Much expansion lies in areas far beyond the traditional foci on technical production or political power, such as protecting the environment, promoting marginalized groups, or behaving with transparency. We argue that expansion is supported by widespread cultural rationalization in a stateless and liberal global society, characterized by scientism, rights and empowerment discourses, and an explosion of education. These cultural changes are transmitted through legal, accounting, and professionalization principles, driving the creation of new organizations and the elaboration of existing ones. The resulting organizations are constructed to be proper social actors as much as functionally effective entities. They are painted as autonomous and integrated but depend heavily on external definitions to sustain this depiction. So expansion creates organizations that are, whatever their actual effectiveness, structurally nonrational. We advance institutional theories of social organization in three main ways. First, we give an account of the expansive rise of \"organization\" rooted in rapid worldwide cultural rationalization. Second, we explain the construction of contemporary organizations as purposive actors, rather than passive bureaucracies. Third, we show how the expanded actorhood of the contemporary organization, and the associated interpnetration with the environment, dialectically generate structures far removed from instrumental rationality.

Genetically modified foods (GMFs) have met with strong opposition for most of their existence. According to one account—the consequence-based perspective (CP)—lay people oppose GMFs because they deem them unsafe as well as of dubious value. The CP is backed by the data and offers a clear solution for easing GMF opposition. However, several scholars have claimed that the CP is faulty, that lay opposition derives from largely nonrational factors and is consequence blind. One recent statement of this, the moral-absolutism perspective (MAP), contends that GMFs’ opponents are principled “moral absolutists” who think that GMFs should be banned no matter their value or risk. Herein we critically weigh key arguments for this proposal. We also present five new studies that probed the clearest data that seem to favor the MAP—opponents affirming the statement that GMFs should be “prohibited,” no matter their value or risk. These studies jointly show that (a) most presumed absolutists do not understand the key question and/or (b) cannot validly answer it. We show that taking due steps in clarifying the question and screening for those participants who cannot validly answer it cuts down absolutism to near zero. Finally, we demonstrate that helping GMFs’opponents imagine a world wherein GMFs are safe and constructive makes the majority willing to welcome GMFs in this context.

Evaluating precision oncology outcomes requires access to real-world and clinical trial data. Access is based on consent, and consent is based on patients' informed preferences when deciding to share their data. Decision-making is often modeled using utility theory, but a complex decision context calls for a consideration of how heuristic, intuitive thought processes interact with rational utility maximization. Data-sharing decision-making has been studied using heuristic theory, but almost no heuristic research exists in the health data context. This study explores this evidence gap, applying a qualitative approach to probe for evidence of heuristic mechanisms behind the health data-sharing preferences of those who have experienced cancer. Exploring qualitative decision-making reveals the types of heuristics used and how they are related to the process of decision-making to better understand whether consent mechanisms should consider nonrational processes to better serve patient decision-making. This study aimed to explore how patients with cancer use heuristics when deciding whether to share their data for research. The researchers conducted a focus group study of Canadians who have experienced cancer. We recruited participants through an online advertisement, screening individuals based on their ability to increase demographic diversity in the sample. We reviewed the literature on data-sharing platforms to develop a semistructured topic guide on concerns about data sharing, incentives to share, and consent and control. Focus group facilitators led the open-ended discussions about data-sharing preferences that revealed underlying heuristics. Two qualitative analysts coded transcripts using a heuristic framework developed from a review of the literature. Transcripts were analyzed for heuristic instances which were grouped according to sociocultural categories. Using thematic analysis, the analysts generated reflexive themes through norming sessions and consultations. A total of 3 focus groups were held with 19 participants in total. The analysis identified 12 heuristics underlying intentions to share data. From the thematic analysis, we identified how the heuristics of social norms and community building were expressed through altruism; the recognition, reputation, and authority heuristics led to (dis)trust in certain institutions; the need for security prompted the illusion of control and transparency heuristics; and the availability and affect heuristics influenced attitudes around risk and benefit. These thematic relationships all had impacts on the participants' intentions to share their health data. The findings provide a novel qualitative understanding of how health data-sharing decisions and preferences may be based on heuristic processing. As patients consider the extent of risks and benefits, heuristic processes influence their assessment of anticipated outcomes, which may not result in rational, truly informed consent. This study shows how considering heuristic processing when designing current consent mechanisms opens up the opportunity for more meaningful and realistic interactions with the complex decision-making context.

This article examines the idea of mind-reading technology by focusing on an interesting case of applying a large language model (LLM) to brain data. On the face of it, experimental results appear to show that it is possible to reconstruct mental contents directly from brain data by processing via a chatGPT-like LLM. However, the author argues that this apparent conclusion is not warranted. Through examining how LLMs work, it is shown that they are importantly different from natural language. The former operates on the basis of nonrational data transformations based on a large textual corpus. The latter has a rational dimension, being based on reasons. Using this as a basis, it is argued that brain data does not directly reveal mental content, but can be processed to ground predictions indirectly about mental content. The author concludes that this is impressive but different in principle from technology-mediated mind reading. The applications of LLM-based brain data processing are nevertheless promising for speech rehabilitation or novel communication methods.

The disease burden in low-income countries is extremely high. Malaria, respiratory infections, diarrhea, AIDS, and other diseases are estimated to kill more than 15 million people each year, most of them children. Yet the great majority of these diseases can be prevented or treated. This article reviews microeconomic studies of health-seeking behavior in low-income countries. Factors examined include information, peers, liquidity constraints, and nonrational preferences, such as present bias. I then discuss the implications for policy, including the scope for mandates, subsidies, and incentives.

People often observe others' decisions before deciding themselves. Using eBay data for DVD auctions we explore the consequences of neglecting nonsalient information when making such inferences. We show that bidders herd into auctions with more existing bids, even if these are a signal of no-longer-available lower starting prices rather than of higher quality. Bidders bidding a given dollar amount are less likely to win low starting price auctions, and pay more for them when they do win. Experienced bidders are less likely to bid on low starting price auctions. Remarkably, the seller side of the market is in equilibrium, because expected revenues are nearly identical for high and low starting prices.

The mid-twentieth century “collective behavior” school asserted that (1) collective behavior—the actions of crowds, movements, and other gatherings—had distinct dynamics; (2) such action was often “nonrational,” or not governed by cost-benefit calculation; and (3) collective behavior could pose a threat to liberal democracy because of these features. While this tradition fell out of scholarly favor, the 2016 election has given us empirical reasons to revisit some elements of collective behavior approaches. We argue for three key orienting concerns, drawn from this tradition, to understand the current political era. First is a focus on authoritarianism and populism, particularly among those who feel disaffected and isolated from political institutions, pared of psychologistic determinism and geared more sensitively to their manifestations as a political style. Second is a focus on racialized resentment, strain, and perceptions of status decline, especially in how such feelings are activated when people are confronted with disruptions to their lives. Third is an analysis of “emergent norms” and the extent to which political actors produce normative understandings of contextually appropriate action that are distinct from traditional political behavior. We elaborate on these themes, apply them to examples from current politics, and suggest ways to incorporate them into contemporary sociological research.