University of Mannheim

About: University of Mannheim is a education organization based out in Mannheim, Germany. It is known for research contribution in the topics: Context (language use) & Politics. The organization has 4448 authors who have published 12918 publications receiving 446557 citations. The organization is also known as: Uni Mannheim & UMA.

True health vs response styles: exploring cross-country differences in self-reported health.

Abstract: The aim of this paper is to decompose cross-national differences in self-reported general health into parts explained by differences in 'true' health, measured by diagnosed conditions and measurements, and parts explained by cross-cultural differences in response styles. The data used were drawn from the Survey of Health, Ageing and Retirement in Europe 2004 (SHARE), using information from 22 731 individuals aged 50 and over from 10 European countries. Self-rated general health shows large cross-country variations. According to their self-reports, the healthiest respondents live in the Scandinavian countries and the least healthy live in Southern Europe. Counterfactual self-reported health distributions that assume identical response styles in each country show much less variation in self-reports than factual self-reports. Danish and Swedish respondents tend to largely over-rate their health (relative to the average) whereas Germans tend to under-rate their health. If differences in reporting styles are taken into account, cross-country variations in general health are reduced but not eliminated. Failing to account for differences in reporting styles may yield misleading results.

More than fun and money. Worker motivation in crowdsourcing - a study on mechanical turk

Abstract: The payment in paid crowdsourcing markets like Amazon Mechanical Turk is very low, and still collected demographic data shows that the participants are a very diverse group including highly skilled full time workers. Many existing studies on their motivation are rudimental and not grounded on established motivation theory. Therefore, we adapt different models from classic motivation theory, work motivation theory and Open Source Software Development to crowdsourcing markets. The model is tested with a survey of 431 workers on Mechanical Turk. We find that the extrinsic motivational categories (imme-diate payoffs, delayed payoffs, social motivation) have a strong effect on the time spent on the platform. For many workers, however, intrinsic motivation aspects are more important, especially the different facets of enjoyment based motivation like “task autonomy” and “skill variety”. Our contribution is a preliminary model based on established theory intended for the comparison of different crowdsourcing platforms.

Rhetoric and Myth in Management Fashion

Abstract: A count of publications over a period of time indicates that management concepts come and go like fashions. After a discussion of theories of fashion in aesthetic and technical objects, it is argue...

A Blockchain Research Framework

Abstract: While blockchain technology is commonly considered potentially disruptive in various regards, there is a lack of understanding where and how blockchain technology is effectively applicable and where it has mentionable practical effects. This issue has given rise to critical voices that judge the technology as over-hyped. Against this backdrop, this study adapts an established research framework to structure the insights of the current body of research on blockchain technology, outline the present research scope as well as disregarded topics, and sketch out multidisciplinary research approaches. The framework differentiates three groups of activities (design and features, measurement and value, management and organization) at four levels of analysis (users and society, intermediaries, platforms, firms and industry). The review shows that research has predominantly focused on technological questions of design and features, while neglecting application, value creation, and governance. In order to foster substantial blockchain research that addresses meaningful questions, this study identifies several avenues for future studies. Given the breadth of open questions, it shows where research can benefit from multidisciplinary collaborations and presents data sources as starting points for empirical investigations.

Overconfidence and trading volume

Abstract: Theoretical models predict that overconfident investors will trade more than rational investors. We directly test this hypothesis by correlating individual overconfidence scores with several measures of trading volume of individual investors (number of trades, turnover). Approximately 3000 online broker investors were asked to answer an internet questionnaire which was designed to measure various facets of overconfidence (miscalibration, the better than average effect, illusion of control, unrealistic optimism). The measures of trading volume were calculated by the trades of 215 individual investors who answered the questionnaire. We find that investors who think that they are above average in terms of investment skills or past performance trade more. Measures of miscalibration are, contrary to theory, unrelated to measures of trading volume. This result is striking as theoretical models that incorporate overconfident investors mainly motivate this assumption by the calibration literature and model overconfidence as underestimation of the variance of signals. The results hold even when we control for several other determinants of trading volume in a cross-sectional regression analysis. In connection with other recent findings, we conclude that the usual way of motivating and modelling overconfidence which is mainly based on the calibration literature has to be treated with caution. We argue that our findings present a psychological foundation for the differences of opinion'' explanation of high levels of trading volume. In addition, our way of empirically evaluating behavioral finance models - the correlation of economic and psychological variables and the combination of psychometric measures of judgment biases (such as overconfidence scores) and field data - seems to be a promising way to better understand which psychological phenomena drive economic behavior.