1,720,958 research outputs found
Cognitive biases in expectation formation : lab evidence on preferences for redistribution, financial forecasting, and subscription traps
No full textChapter 1: Bringing existing inequality in South Africa (high) and Switzerland (low) to the lab, we study how people’s preferences for redistribution change with the level of income inequality, income mobility, uncertainty of initial income positions, source of income (random or based on real-effort). We find that uncertainty and overconfidence undermine demand for redistribution.
The effect magnifies with larger income disparity (South Africa). It further induces a reverse POUM effect: since wealth ambitions of rich aspirants are better preserved under low than under high mobility, demand for redistribution grows with the degree of mobility. These results combined propose an inequality trap: today’s inequality favors income overestimation, winding up less demand for redistribution with less mobility, which propels advanced inequality tomorrow.
Chapter 2: Learning-to-Forecast experiments have been found to replicate price volatility of demand-driven markets quite accurately. Yet, the scope of prior studies neither exceeded 50 periods nor limited severely decision time, and thereby neglected two central features of financial markets: long runtime and time pressure. This work studies whether “bubble and crash” dynamics persist in the long run (150 periods) and how decision time (6 vs. 25 seconds) influences market volatility? We observe converging prices to the fundamental value with increasing market length. Parallel to the change in dynamics, we identify a switch from trendextrapolating to rather adaptive strategies in the low time pressure condition. Increasing time pressure in contrast, limits trend-chasing behavior and aggregated coordination right from the beginning. Both seems to exert a stabilizing effect on prices.
Chapter 3: This paper explores a novel menu effect in the context of subscriptions. Providers typically capitalize on arranging offers such that the longer, but costlier option is chosen over its cheaper alternative. We find that sizing the shorter subscription down to single use raises its attraction. This suspects that the presence of single-use prompts rational evaluation based on a realistic estimate to use the subscription again. Alternatives in the former case, both time spans, are instead decoded into the same category - referred to pigeonholing - with the consequence that other comparative criteria come to the fore. Two-dimensional models present in most behavioral theories fail to explain this type of preference reversal. Inspired by the intuition of transaction utility and the availability heuristic we propose a generalization of salience theory to capture the effect of pigeonholing
Between enthusiasm and refusal: A cluster analysis on consumer types and attitudes towards peer-to-peer sharing
No full textThe rise of peer-to-peer platforms for sharing private resources has introduced new possibilities for access beyond ownership. Although experiencing fast growth, the academic literature has only recently begun to study individual user attitudes towards such new forms of consumption. Building on findings on the underlying consumer motives for peer-to-peer sharing, this study differentiates prototypical consumers by means of cluster analysis. Based on data from a large-scale online survey (n = 745) on consumer motives, we identify 5 main dimensions (concerns, benefits, product-specific aspects, social aspects, and ownership-related aspects). On these grounds, we identify 4 consumer types with distinct demographic and attitudinal characteristics: Social Enthusiasts, Conflicted Materialists, Skeptic Ascetics, and Individualistic Refuseniks. Based on these clusters' differences with regard to demographics and sharing behaviors, we derive implications for practitioners to tailor their business models and marketing strategies to the specific motivational patterns of the respective user groups
The income inequality trap: When redistributive preferences do not correct greater inequality
No full textIn a lab study, we examine how preferences for redistribution are affected by income inequality, uncertainty of income class, income mobility, and the source of income (random or effort based). Under income class uncertainty we discover an inequality trap where individuals exposed to a more unequal pre-tax distribution also demonstrate greater acceptance of post-tax inequality. This effect is particularly pronounced in the effort condition and with low mobility. However, as individuals become aware of their true economic positions, the conflict between the poor and the rich intensifies, decreasing tolerance for inequality. These findings indicate that traditional rational-expectations models which solely rely on risk aversion and inequality aversion cannot fully explain subjects'redistributive preferences. We also consider other factors, such as fairness considerations, social class memberships, and overconfidence in income expectations as potential drivers
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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