455 research outputs found

    Disgust Promotes Disposal: Souring the Status Quo

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    Humans naturally dispose of objects that disgust them. Is this phenomenon so deeply embedded that even incidental disgust--i.e., where the source of disgust is unrelated to a possessed object--triggers disposal? Two experiments were designed to answer this question. Two film clips served as disgust and neutral primes; the objects were routine commodities (boxes of office supplies). Results revealed that the incidental disgust condition powerfully increased the frequency with which decision makers traded away a commodity they owned for a new commodity (more than doubling the probability in each condition), thereby countering otherwise robust status quo bias (Samuelson & Zeckhauser, 1988). Decision makers were unaware of disgust's impact. Even when warned to correct for it, they failed to do so. These studies presented real choices with tangible rewards. Their findings thus have implications not only for theories of affect and choice, but also for practical improvements in everyday decisions.

    The Political Economy: Political Attitudes and Economic Behavior

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    It has long been recognized that voters bring their political behaviors in line with economic assessments. Recent work, however, suggests that citizens also engage in economic behaviors that align with their confidence—or lack thereof—in the political system. This alignment can happen consciously or, as we suggest, unconsciously, in the same way that positivity carries over to other behaviors on a micro-level. Using monthly time series data from 1978 to 2008, we contribute further evidence of this relationship by demonstrating that political confidence affects consumer behavior at the aggregate level over time. Our analyses employ measures more closely tied to the theoretical concepts of interest while simultaneously accounting for the complex relationships between subjective and objective economic indicators, economic behavior, political attitudes, and the media. Our results suggest that approval of the president not only increases the electorate’s willingness to spend money, but also affects the volatility of this spending. These findings suggest that the economy is influenced by politics beyond elections, and gives the “Chief Economist” another avenue by which they can affect the behavior of the electorate

    The Organizational Psychology of Hyper-Competition: Corporate Irresponsibility and the Lessons of Enron

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    What I want to do here is first explain my fears and then explore the Enron story from the standpoint of both social psychology and organizational behavior. My sense going in, at least, is that the social forces and selfish norms that emerge fairly naturally in highly competitive settings such as these dominate as behavioral influences over anything but high-powered legal controls. The kind of firm that I want to concentrate on is the new economy sort that requires a high rate of creative productivity from a large number of key managers and employees. Thus, I will put to the side the few remaining monopolistic public utilities, as well as firms with high rates of free cash flow from entrenched market power. The paradigmatic examples that I am interested in are knowledge and service-based firms in markets with relatively low barriers to entry and high rewards for innovation. Enron clearly was one of these

    Feelings and Consumer Decision Making: The Appraisal-Tendency Framework

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    as a basis for predicting the influence of specific emotions on consumer decision making. In particular, the ATF addresses how and why specific emotions carry over from past situations to color future judgments and choices. After reviewing the main assumptions and the 5 main principles of the framework, 2 streams of research are presented. One stream addresses emotional carryover effects on the assessment of risk; the other addresses carryover effects on the assessment of monetary value. Because risk assessment and value assessment are fundamental psychological processes, understanding them has the potential to yield manifold implications for consumer judgment and decision making. The concluding sections highlight limitations and future directions of the framework

    Audio-Visual Sentiment Analysis for Learning Emotional Arcs in Movies

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    Stories can have tremendous power -- not only useful for entertainment, they can activate our interests and mobilize our actions. The degree to which a story resonates with its audience may be in part reflected in the emotional journey it takes the audience upon. In this paper, we use machine learning methods to construct emotional arcs in movies, calculate families of arcs, and demonstrate the ability for certain arcs to predict audience engagement. The system is applied to Hollywood films and high quality shorts found on the web. We begin by using deep convolutional neural networks for audio and visual sentiment analysis. These models are trained on both new and existing large-scale datasets, after which they can be used to compute separate audio and visual emotional arcs. We then crowdsource annotations for 30-second video clips extracted from highs and lows in the arcs in order to assess the micro-level precision of the system, with precision measured in terms of agreement in polarity between the system's predictions and annotators' ratings. These annotations are also used to combine the audio and visual predictions. Next, we look at macro-level characterizations of movies by investigating whether there exist `universal shapes' of emotional arcs. In particular, we develop a clustering approach to discover distinct classes of emotional arcs. Finally, we show on a sample corpus of short web videos that certain emotional arcs are statistically significant predictors of the number of comments a video receives. These results suggest that the emotional arcs learned by our approach successfully represent macroscopic aspects of a video story that drive audience engagement. Such machine understanding could be used to predict audience reactions to video stories, ultimately improving our ability as storytellers to communicate with each other.Comment: Data Mining (ICDM), 2017 IEEE 17th International Conference o

    Calling on the CFPB for Help: Telling Stories and Consumer Protection

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    Since it began operating in 2011, the Consumer Financial Protection Bureau (CFPB) has handled more than a million complaints regarding consumer financial product and services. Beginning in June 2015, the CFPB began publishing consumers’ narratives submitted with their complaints. This Article analyses a random sample of 5,000 of these narratives to assess how people engage with the complaint mechanism in light of the CFPB’s role in processing complaints. I find that people predominately use the complaint function for two distinct purposes: to express their anger and frustration about companies’ practices, or to express sadness and fear about how companies’ practices have impacted their lives. When people write with anger and frustration, they typically direct their comments to the subject company, which aligns with the CFPB’s role in processing complaints. In contrast, when people write with sadness and fear, they often plead with the CFPB for individualized help in solving their broader problems. But the CFPB is not equipped to help people on an individual basis and such is not the goal of its complaint mechanism. Identifying that some consumers seem to expect the CFPB to provide this type of assistance presents an opportunity for the CFPB to address the serious problems that these consumers are voicing and to enhance how it utilizes the complaint data to further its goal of consumer protection. However, the CFPB is but one government agency that allows people to write narratives describing their problems. This Article thus provides suggestions for how agencies generally may mine their narrative databases to help people in need and to advance their missions
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