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Correction to: Computational Economics https://doi.org/10.1007/s10614-020-10061-x
The original publication has been updated. In the original publication of this article, under the Introduction heading section, the corrections to the second paragraph’s inline equation were not incorporated. The author’s additional corrections have also been incorporated. The publisher apologizes for the error made during production.
India has recorded 142,186 deaths over 36 administrative regions placing India third in the world after the US and Brazil for COVID-19 deaths as of 12 December 2020. Studies indicate that south-west monsoon season plays a role in the dynamics of contagious diseases, which tend to peak post-monsoon season. Recent studies show that vitamin D and its primary source Ultraviolet-B (UVB) radiation may play a protective role in mitigating COVID-19 deaths. However, the combined roles of the monsoon season and UVB radiation in COVID-19 in India remain still unclear. In this observational study, we empirically study the respective roles of monsoon season and UVB radiation, whilst further exploring, whether the monsoon season negatively impacts the protective role of UVB radiation in COVID-19 deaths in India. We use a log-linear Mundlak model to a panel dataset of 36 administrative regions in India from 14 March 2020–19 November 2020 (n = 6751). We use the cumulative COVID-19 deaths as the dependent variable. We isolate the association of monsoon season and UVB radiation as measured by Ultraviolet Index (UVI) from other confounding time-constant and time-varying region-specific factors. After controlling for various confounding factors, we observe that a unit increase in UVI and the monsoon season are separately associated with 1.2 percentage points and 7.5 percentage points decline in growth rates of COVID-19 deaths in the long run. These associations translate into substantial relative changes. For example, a permanent unit increase of UVI is associated with a decrease of growth rates of COVID-19 deaths by 33% (= − 1.2 percentage points) However, the monsoon season, mitigates the protective role of UVI by 77% (0.92 percentage points). Our results indicate a protective role of UVB radiation in mitigating COVID-19 deaths in India. Furthermore, we find evidence that the monsoon season is associated with a significant reduction in the protective role of UVB radiation. Our study outlines the roles of the monsoon season and UVB radiation in COVID-19 in India and supports health-related policy decision making in India.
Shares of open-end real estate funds are typically traded directly between the investor and the fund management company. However, we provide empirical evidence for the growth of secondary market activities, i.e., the trading of shares on stock exchanges. We find high trading levels in situations where the fund management company suspends the issue or redemption of shares. Shares trade at a discount when the fund management company suspends the redemption, whereas shares trade at a premium when the fund management company suspends the issue. We also find evidence that secondary market trading activity is increasing since German regulation introduced a minimum holding period and a mandatory notice period for open-end real estate funds.
Consider two independent random walks. By chance, there will be spells of association between them where the two processes move in the same direction, or in opposite direction. We compute the probabilities of the length of the longest spell of such random association for a given sample size, and discuss measures like mean and mode of the exact distributions. We observe that long spells (relative to small sample sizes) of random association occur frequently, which explains why nonsense correlation between short independent random walks is the rule rather than the exception. The exact figures are compared with approximations. Our finite sample analysis as well as the approximations rely on two older results popularized by Révész (Stat Pap 31:95–101, 1990, Statistical Papers). Moreover, we consider spells of association between correlated random walks. Approximate probabilities are compared with finite sample Monte Carlo results.
Vehicle registrations have been shown to strongly react to tax reforms aimed at reducing CO2 emissions from passengers’ cars, but are the effects equally strong for positive and negative tax changes? The literature on asymmetric reactions to price and tax changes has documented asymmetries for everyday goods but has not yet considered durables. We leverage multiple vehicle registration tax (VRT) reforms in Norway and estimate their impact on within car-model substitutions. We estimate stronger effects for cars receiving tax cuts and rebates than for those affected by tax increases. The corresponding estimated elasticity is − 1.99 for VRT decreases and 0.77 for increases. As consumers may also substitute across car models, our estimates represent a lower bound.
This paper uses historical monthly temperature level data for a panel of 114 countries to identify the effects of within year temperature level variability on productivity growth in five different macro regions, i.e., (1) Africa, (2) Asia, (3) Europe, (4) North America and (5) South America. We find two primary results. First, higher intra-annual temperature variability reduces (increases) productivity in Europe and North America (Asia). Second, higher intra-annual temperature variability has no significant effects on productivity in Africa and South America. Additional empirical tests indicate also the following: (1) rising intra-annual temperature variability reduces productivity (even thought less significantly)in both tropical and non-tropical regions, (2) inter-annual temperature variability reduces (increases) productivity in North America (Europe) and (3) winter and summer inter-annual temperature variability generates a drop in productivity in both Europe and North America. Taken together, these findings indicate that temperature variability shocks tend to have stronger adverse economic effects among richer economies. In a production economy featuring long-run productivity and temperature volatility shocks, we quantify these negative impacts and find welfare losses of 2.9% (1%) in Europe (North America).
Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids
(2021)
Discrete time dynamic programming to solve dynamic portfolio choice models has three immanent issues: firstly, the curse of dimensionality prohibits more than a handful of continuous states. Secondly, in higher dimensions, even regular sparse grid discretizations need too many grid points for sufficiently accurate approximations of the value function. Thirdly, the models usually require continuous control variables, and hence gradient-based optimization with smooth approximations of the value function is necessary to obtain accurate solutions to the optimization problem. For the first time, we enable accurate and fast numerical solutions with gradient-based optimization while still allowing for spatial adaptivity using hierarchical B-splines on sparse grids. When compared to the standard linear bases on sparse grids or finite difference approximations of the gradient, our approach saves an order of magnitude in total computational complexity for a representative dynamic portfolio choice model with varying state space dimensionality, stochastic sample space, and choice variables.
The mobile games business is an ever-increasing sub-sector of the entertainment industry. Due to its high profitability but also high risk and competitive atmosphere, game publishers need to develop strategies that allow them to release new products at a high rate, but without compromising the already short lifespan of the firms' existing games. Successful game publishers must enlarge their user base by continually releasing new and entertaining games, while simultaneously motivating the current user base of existing games to remain active for more extended periods. Since the core-component reuse strategy has proven successful in other software products, this study investigates the advantages and drawbacks of this strategy in mobile games. Drawing on the widely accepted Product Life Cycle concept, the study investigates whether the introduction of a new mobile game built with core-components of an existing mobile game curtails the incumbent's product life cycle. Based on real and granular data on the gaming activity of a popular mobile game, the authors find that by promoting multi-homing (i.e., by smartly interlinking the incumbent and new product with each other so that users start consuming both games in parallel), the core-component reuse strategy can prolong the lifespan of the incumbent game.
Digital wealth and its necessary regulation have gained prominence in recent years. The European Commission has published several documents and policy proposals relating, directly or indirectly, to the data economy. A data economy can be defined as an ecosystem of different types of market players collaborating to ensure that data is accessible and usable in order to extract value from data through, for example, creating a variety of applications with great potential to improve daily life. The value of data can increase from EUR 257 billion (1.85 of EU Gross Domestic Product (GDP)) to EUR 643 billion by 2020 (3.17% of EU GDP), according to the EU Commission. The legal implications of the increasing value of the data economy are clear; hence the need to address the challenges presented by its legal regulation.
The health and genetic data of deceased people are a particularly important asset in the field of biomedical research. However, in practice, using them is compli- cated, as the legal framework that should regulate their use has not been fully developed yet. The General Data Protection Regulation (GDPR) is not applicable to such data and the Member States have not been able to agree on an alternative regulation. Recently, normative models have been proposed in an attempt to face this issue. The most well- known of these is posthumous medical data donation (PMDD). This proposal supports an opt-in donation system of health data for research purposes. In this article, we argue that PMDD is not a useful model for addressing the issue at hand, as it does not consider that some of these data (the genetic data) may be the personal data of the living relatives of the deceased. Furthermore, we find the reasons supporting an opt-in model less convincing than those that vouch for alternative systems. Indeed, we propose a normative framework that is based on the opt-out system for non-personal data combined with the application of the GDPR to the relatives’ personal data.
The quality of life: protecting non-personal interests and non-personal data in the age of big data
(2021)
Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- criminate rather than targeted data collection, because the high volumes of data are processed on an aggregated rather than a personal level and because the policies and decisions based on the statistical correlations found through algorithmic analytics are mostly addressed at large groups or society as a whole rather than specific individuals. This means that large parts of the data-driven environment are currently left unregu- lated and that individuals are often unable to rely on their fundamental rights when addressing the more systemic effects of Big Data processes. This article will discuss how this tension might be relieved by turning to the notion ‘quality of life’, which has the potential of becoming the new standard for the European Court of Human Rights (ECtHR) when dealing with privacy related cases.
Ownership of databases: personal data protection and intellectual property rights on databases
(2021)
When we think on initiatives on access to and reuse of data, we must consider both the European Intellectual Property Law and the General Data Protection Regulation (GDPR). The first one provides a special intellectual property (IP) right – the sui generis right – for those makers that made a substantial investment when creating the database, whether it contains personal or non-personal data. That substantial investment can be made by just one person, but, in many cases, it is the result of the activities of many people and/or some undertakings processing and aggregating data. In the modern digital economy, data are being dubbed the ‘new oil’ and the sui generis right might be con- sidered a right to control any access to the database, thus having an undeniable relevance. Besides, there are still important inconsistences between IP Law and the GDPR, which must be removed by the European legislator. The genuine and free consent of the data subject for the use of his/her data must remain the first step of the legal analysis.
Commercialization of consumers’ personal data in the digital economy poses serious, both conceptual and practical, challenges to the traditional approach of European Union (EU) Consumer Law. This article argues that mass-spread, automated, algorithmic decision-making casts doubt on the foundational paradigm of EU consumer law: consent and autonomy. Moreover, it poses threats of discrimination and under- mining of consumer privacy. It is argued that the recent legislative reaction by the EU Commission, in the form of the ‘New Deal for Consumers’, was a step in the right direction, but fell short due to its continued reliance on consent, autonomy and failure to adequately protect consumers from indirect discrimination. It is posited that a focus on creating a contracting landscape where the consumer may be properly informed in material respects is required, which in turn necessitates blending the approaches of competition, consumer protection and data protection laws.
What are the effects of the GDPR on consumer apps? This article presents an analysis of app behavior before and after the regulatory change in data protection in Europe. Based on long-term data collection, we present differences in app permission use and expressed user concerns and discuss their implications. In May 2018, the General Data Protection Regulation (GDPR) changed the data protection obligations of the information industry with the European Union users substantially. One should expect to find changes in code, program behavior and data collection activities. To investigate this expectation, we analyzed data about Android apps request and use of permissions to access sensitive group of data on smartphones, and collected user reviews. Our data shows an overall reduction of both permissions used and of expressed user concern. However, in some areas apps have increased access or user complaints while in addition, many apps carry with them several unused access privileges.
Public kindergarten, maternal labor supply, and earnings in the longer run: too little too late?
(2021)
By facilitating early re-entry to the labor market after childbirth, public kindergarten might positively affect maternal human capital and labor market outcomes: Are such effects long-lasting? Can we rely on between-individuals differences in quarter of birth to identify them? I isolate the effects of interest from spurious associations through difference-in-difference, exploiting across-states and over-time variation in public kindergarten eligibility regulations in the United States. The estimates suggest a very limited impact in the first year, and no longer-run impacts. Even in states where it does not affect kindergarten eligibility, quarter of birth is strongly and significantly correlated with maternal outcomes.
This article investigates the roles of psychological biases for deviations between subjective survival beliefs (SSBs) and objective survival probabilities. We model these deviations through age-dependent inverse S-shaped probability weighting functions. Our estimates suggest that implied measures for cognitive weakness increase and relative optimism decrease with age. Direct measures of cognitive weakness and optimism share these trends. Our regression analyses confirm that these factors play strong quantitative roles in the formation of SSBs. Our main finding is that cognitive weakness instead of optimism becomes with age an increasingly important contributor to the well-documented overestimation of survival chances in old age.
The term structure of interest rates is crucial for the transmission of monetary policy to financial markets and the macroeconomy. Disentangling the impact of monetary policy on the components of interest rates, expected short rates, and term premia is essential to understanding this channel. To accomplish this, we provide a quantitative structural model with endogenous, time-varying term premia that are consistent with empirical findings. News about future policy, in contrast to unexpected policy shocks, has quantitatively significant effects on term premia along the entire term structure. This provides a plausible explanation for partly contradictory estimates in the empirical literature.
Contemporary information systems make widespread use of artificial intelligence (AI). While AI offers various benefits, it can also be subject to systematic errors, whereby people from certain groups (defined by gender, age, or other sensitive attributes) experience disparate outcomes. In many AI applications, disparate outcomes confront businesses and organizations with legal and reputational risks. To address these, technologies for so-called “AI fairness” have been developed, by which AI is adapted such that mathematical constraints for fairness are fulfilled. However, the financial costs of AI fairness are unclear. Therefore, the authors develop AI fairness for a real-world use case from e-commerce, where coupons are allocated according to clickstream sessions. In their setting, the authors find that AI fairness successfully manages to adhere to fairness requirements, while reducing the overall prediction performance only slightly. However, they find that AI fairness also results in an increase in financial cost. Thus, in this way the paper’s findings contribute to designing information systems on the basis of AI fairness.
Strict environmental regulation may deter foreign direct investment (FDI). The paper develops the hypothesis that regulation predominantly discourages FDI that is conducted as Greenfield investment rather than mergers and acquisitions (M&A). The hypothesis is tested with German firm-level FDI data. Empirically, stricter regulation reduces new Greenfield projects in polluting industries, but indeed has a much smaller impact on the number of M&As. This significant difference is compatible with the fact that existing operations often benefit from grandfathering rules, which provide softer regulation for pre-exisiting plants, and with the expectation that for M&As part of the regulation is capitalized in the purchase price. The heterogeneous effects help explaining mixed results in previous studies that have neglected the mode of entry.
We analyze the extent to which individual audit partners influence the audited narrative disclosures in their clients’ financial reports. Using a sample of 3,281,423 private and public client firm-pairs, we find that the similarity among audited narrative disclosures is higher when two client firms share the same audit partner. Specifically, we find that the wording similarity of management reports (notes) increases by 30 (48) percent, the content similarity by 29 (49) percent, and the structure similarity by 48 (121) percent. Moreover, we find that audit partners in particular are relevant for their clients’ narrative disclosures because the increase in narrative disclosure similarity when sharing the same audit partner is nine (four) times greater than when sharing the same audit firm (audit office). We show that this influence of audit partners goes beyond adding boilerplate statements and, using novel field evidence, we shed light on the underlying mechanisms. Our findings are economically relevant because a stronger involvement of audit partners with their clients’ narratives is associated with a higher quality of narrative disclosures, which helps users better predict the future profitability of client firms.
This study simulates three income tax scenarios in a Mirrleesian setting for 24 EU countries using data from the 2014 Structure of Earnings Survey. In scenario 1, each country individually maximizes its own welfare (benchmark). In scenarios 2 and 3, total welfare in the EU is maximized over a common budget constraint. Unlike scenario 2, the social planner of scenario 3 differentiates taxes by country of residence. If a common tax and transfer system were implemented in the EU, countries with a relatively higher mean wage rate—particularly those in Western and some of the Northern European countries—would transfer resources to the others. Scenario 2 implies increased labor distortions for almost all countries and, hence, leads to a contraction in total output. Scenario 3 produces higher (lower) marginal taxes for high- (low-) mean countries compared to the benchmark. The change in total output depends on the income effects on labor supply. Overall, total welfare is higher for the scenarios involving a European tax and transfer system despite more than two thirds of all the agents becoming worse off relative to the benchmark. A politically more feasible integrated tax system improves the well-being of almost half of all the EU but considerably reduces the aggregate welfare benefits.
Device-to-device (D2D) communication is an innovative solution for improving wireless network performance to efficiently handle the ever-increasing mobile data traffic. Communication takes place directly between two devices that are in each other’s transmission range. So far, research has focused on the technical challenges of implementing this technology and assumes a user’s general willingness to participate as forwarder in this technology. However, this simplifying assumption is not realistic, as willingness to participate in D2D communication can vary depending on the user. In this work, we consider the scenario that a user can act as a forwarder for a receiver who is not directly or insufficiently reached by the base station and accordingly has no or poor Internet connection. We take a user-centric approach and investigate the willingness to provide an Internet connection as a forwarder. We are the first to investigate user preferences for D2D communication using a choice-based conjoint analysis. Our results, based on a representative sample of potential users (N=181), show that the social relationship between the potential forwarder and the receiver has the greatest impact on the potential forwarder’s decision to provide an Internet connection to the receiver, accepting sacrifices in terms of additional battery consumption and reduced own service performance. In a detailed segment analysis, we observe significant preference differences depending on smartphone usage behavior and user age. Taking the corresponding preferences into account when matching forwarders and receivers can further increase technology adoption.
We analyze the joint dynamics of prices, productivity, and employment across firms, building a dynamic equilibrium model of heterogeneous firms who compete for workers and customers in frictional labor and product markets. Using panel data on prices and output for German manufacturing firms, the model is calibrated to evaluate the quantitative contributions of productivity and demand for the labor market. Product market frictions decisively dampen the firms' employment adjustments to productivity shocks. We further analyze the impact of aggregate shocks to the first and second moments of productivity and demand and relate them to business-cycle features in our data.
When requesting a web-based service, users often fail in setting the website’s privacy settings according to their self privacy preferences. Being overwhelmed by the choice of preferences, a lack of knowledge of related technologies or unawareness of the own privacy preferences are just some reasons why users tend to struggle. To address all these problems, privacy setting prediction tools are particularly well-suited. Such tools aim to lower the burden to set privacy preferences according to owners’ privacy preferences. To be in line with the increased demand for explainability and interpretability by regulatory obligations – such as the General Data Protection Regulation (GDPR) in Europe – in this paper an explainable model for default privacy setting prediction is introduced. Compared to the previous work we present an improved feature selection, increased interpretability of each step in model design and enhanced evaluation metrics to better identify weaknesses in the model’s design before it goes into production. As a result, we aim to provide an explainable and transparent tool for default privacy setting prediction which users easily understand and are therefore more likely to use.
We analyze limit order book resiliency following liquidity shocks initiated by large market orders. Based on a unique data set, we investigate whether high‐frequency traders are involved in replenishing the order book. Therefore, we relate the net liquidity provision of high‐frequency traders, algorithmic traders, and human traders around these market impact events to order book resiliency. Although all groups of traders react, our results show that only high‐frequency traders reduce the spread within the first seconds after the market impact event. Order book depth replenishment, however, takes significantly longer and is mainly accomplished by human traders’ liquidity provision.
Privacy concerns as well as trust and risk beliefs are important factors that can influence users’ decision to use a service. One popular model that integrates these factors is relating the Internet Users Information Privacy Concerns (IUIPC) construct to trust and risk beliefs. However, studies haven’t yet applied it to a privacy enhancing technology (PET) such as an anonymization service. Therefore, we conducted a survey among 416 users of the anonymization service JonDonym [1] and collected 141 complete questionnaires. We rely on the IUIPC construct and the related trust-risk model and show that it needs to be adapted for the case of PETs. In addition, we extend the original causal model by including trust beliefs in the anonymization service provider and show that they have a significant effect on the actual use behavior of the PET.
In the upcoming years, the internet of things (IoT)will enrich daily life. The combination of artificial intelligence(AI) and highly interoperable systems will bring context-sensitive multi-domain services to reality. This paper describesa concept for an AI-based smart living platform with open-HAB, a smart home middleware, and Web of Things (WoT) askey components of our approach. The platform concept con-siders different stakeholders, i.e. the housing industry, serviceproviders, and tenants. These activities are part of the Fore-Sight project, an AI-driven, context-sensitive smart living plat-form.
This article studies whether people want to control what information on their own past pro-social behavior is revealed to others. Participants are assigned a color that depends on their past pro-social behavior. They can spend money to manipulate the probability with which their color is revealed to another participant. The data show that participants are more likely to reveal colors with more favorable informational content. This pattern is not found in a control treatment in which colors are randomly assigned, thus revealing nothing about past pro-social behavior. Regression analysis confrms these fndings, also when controlling for past pro-social behavior. These results complement the existing empirical evidence, confrming that people strategically and, therefore, consciously manipulate their social image.
Optimal investment decisions by institutional investors require accurate predictions with respect to the development of stock markets. Motivated by previous research that revealed the unsatisfactory performance of existing stock market prediction models, this study proposes a novel prediction approach. Our proposed system combines Artificial Intelligence (AI) with data from Virtual Investment Communities (VICs) and leverages VICs’ ability to support the process of predicting stock markets. An empirical study with two different models using real data shows the potential of the AI-based system with VICs information as an instrument for stock market predictions. VICs can be a valuable addition but our results indicate that this type of data is only helpful in certain market phases.
Participation in further education is a central success factor for economic growth and societal as well as individual development. This is especially true today because in most industrialized countries, labor markets and work processes are changing rapidly. Data on further education, however, show that not everybody participates and that different social groups participate to different degrees. Activities in continuous vocational education and training (CVET) are mainly differentiated as formal, non-formal and informal CVET, whereby further differences between offers of non-formal and informal CVET are seldom elaborated. Furthermore, reasons for participation or non-participation are often neglected. In this study, we therefore analyze and compare predictors for participation in both forms of CVET, namely, non-formal and informal. To learn more about the reasons for participation, we focus on the individual perspective of employees (invidual factors, job-related factors, and learning biography) and additionally integrate institutional characteristics (workplace and company-based characteristics). The results mainly show that non-formal CVET is still strongly influenced by institutional settings. In the case of informal CVET, on the other hand, the learning biography plays a central role.
Learning to fly through informational turbulence: critical thinking and the case of the minimum wage
(2020)
The paper addresses online reasoning and information processing with respect to a much debated issue: the pros and cons of the minimum wage. Like with all controversial issues, one can easily remain in a self-reinforcing bubble, once one has taken sides, and immunize oneself against criticism. Paradoxically, the more information we have at our disposal, the easier this gets (Roetzel, 2019). The only (and possibly universal) antidote seems to be “critical thinking” (Ennis, 1987, 2011). However, critical thinking is a very broad concept, purported to include diverse kinds of information processing, and it is also thought to be content-specific. Therefore, we aim at addressing both understanding of content knowledge and reasoning processes. We pursue three goals with this paper: First, we conduct a conceptual analysis of the learning content and of reasoning patterns for and against the minimum wage. Second, we explicate an inferential framework that can be applied for processes of critical thinking. Third, teaching strategies are discussed to support reasoning processes and to promote critical thinking skills.
Pokémon Go is one of the most successful mobile games of all time. Millions played and still play this mobile augmented reality (AR) application, although severe privacy issues are pervasive in the app due to its use of several sensors such as location data and camera. In general, individuals regularly use online services and mobile apps although they might know that the use is associated with high privacy risks. This seemingly contradictory behavior of users is analyzed from a variety of different perspectives in the information systems domain. One of these perspectives evaluates privacy-related decision making processes based on concepts from behavioral economics. We follow this line of work by empirically testing one exemplary extraneous factor within the “enhanced APCO model” (antecedents–privacy concerns–outcome). Specific empirical tests on such biases are rare in the literature which is why we propose and empirically analyze the extraneous influence of a positivity bias. In our case, we hypothesize that the bias is induced by childhood brand nostalgia towards the Pokémon franchise. We analyze our proposition in the context of an online survey with 418 active players of the game. Our results indicate that childhood brand nostalgia influences the privacy calculus by exerting a large effect on the benefits within the trade-off and, therefore, causing a higher use frequency. Our work shows two important implications. First, the behavioral economics perspective on privacy provides additional insights relative to previous research. However, the effects of several other biases and heuristics have to be tested in future work. Second, relying on nostalgia represents an important, but also double-edged, instrument for practitioners to market new services and applications.
Inflation ist ein Konstrukt. Sie wird von unterschiedlichen Akteur*innen unterschiedlich wahrgenommen. Zum Teil passiert dies, weil Warenkörbe differieren, zum Teil weil Erwartungen unterschiedlich gebildet werden. Dieser Beitrag diskutiert die Heterogenität der Infl ation und ihrer Wahrnehmung und was dies für die Zielgröße der Zentralbankpolitik bedeutet.
Prior studies indicate the protective role of Ultraviolet-B (UVB) radiation in human health, mediated by vitamin D synthesis. In this observational study, we empirically outline a negative association of UVB radiation as measured by ultraviolet index (UVI) with the number of COVID-19 deaths. We apply a fixed-effect log-linear regression model to a panel dataset of 152 countries over 108 days (n = 6524). We use the cumulative number of COVID-19 deaths and case-fatality rate (CFR) as the main dependent variables and isolate the UVI effect from potential confounding factors. After controlling for time-constant and time-varying factors, we find that a permanent unit increase in UVI is associated with a 1.2 percentage points decline in daily growth rates of cumulative COVID-19 deaths [p < 0.01] and a 1.0 percentage points decline in the CFR daily growth rate [p < 0.05]. These results represent a significant percentage reduction in terms of daily growth rates of cumulative COVID-19 deaths (− 12%) and CFR (− 38%). We find a significant negative association between UVI and COVID-19 deaths, indicating evidence of the protective role of UVB in mitigating COVID-19 deaths. If confirmed via clinical studies, then the possibility of mitigating COVID-19 deaths via sensible sunlight exposure or vitamin D intervention would be very attractive.
We model the decisions of young individuals to stay in school or drop out and engage in criminal activities. We build on the literature on human capital and crime engagement and use the framework of Banerjee (1993) that assumes that the information needed to engage in crime arrives in the form of a rumour and that individuals update their beliefs about the profitability of crime relative to education. These assumptions allow us to study the effect of social interactions on crime. In our model, we investigate informational spillovers from the actions of talented students to less talented students. We show that policies that decrease the cost of education for talented students may increase the vulnerability of less talented students to crime. The effect is exacerbated when students do not fully understand the underlying learning dynamics.
This article discusses the counterpart of interactive machine learning, i.e., human learning while being in the loop in a human-machine collaboration. For such cases we propose the use of a Contradiction Matrix to assess the overlap and the contradictions of human and machine predictions. We show in a small-scaled user study with experts in the area of pneumology (1) that machine-learning based systems can classify X-rays with respect to diseases with a meaningful accuracy, (2) humans partly use contradictions to reconsider their initial diagnosis, and (3) that this leads to a higher overlap between human and machine diagnoses at the end of the collaboration situation. We argue that disclosure of information on diagnosis uncertainty can be beneficial to make the human expert reconsider her or his initial assessment which may ultimately result in a deliberate agreement. In the light of the observations from our project, it becomes apparent that collaborative learning in such a human-in-the-loop scenario could lead to mutual benefits for both human learning and interactive machine learning. Bearing the differences in reasoning and learning processes of humans and intelligent systems in mind, we argue that interdisciplinary research teams have the best chances at tackling this undertaking and generating valuable insights.
Information asymmetry and its implications in online purchasing behaviour: a country case study
(2020)
The objective of this study is to analyse how certain variables in the online market affect the decision-making trajectory and actions toward reducing the information asymmetry faced in online purchasing. A survey and observation are conducted in order to understand the behavior and perceptions of online buyers toward the information given in online platforms. Descriptive and correlation analysis have been employed in order to evaluate the data collected and test the correlation between variables of the research model. It results that most participants take for granted the fact that sellers have more information than them when entering into a transaction agreement and this makes them feel inferior towards the superior power sellers possess in such interactions. This makes the traditional markets more preferred for them, however multiple sources such as reviews and ratings result as an alternative way of reducing the perceived information asymmetry.
With the rapid growth of technology in recent years, we are surrounded by or even dependent on the use of technological devices such as smartphones as they are now an indispensable part of our life. Smartphone applications (apps) provide a wide range of utilities such as navigation, entertainment, fitness, etc. To provide such context-sensitive services to users, apps need to access users' data including sensitive ones, which in turn, can potentially lead to privacy invasions. To protect users against potential privacy invasions in such a vulnerable ecosystem, legislation such as the European Union General Data Protection Regulation (EU GDPR) demands best privacy practices. Therefore, app developers are required to make their apps compatible with legal privacy principles enforced by law. However, this is not an easy task for app developers to comprehend purely legal principles to understand what needs to be implemented. Similarly, bridging the gap between legal principles and technical implementations to understand how legal principles need to be implemented is another barrier to develop privacy-friendly apps. To this end, this paper proposes a privacy and security design guide catalog for app developers to assist them in understanding and adopting the most relevant privacy and security principles in the context of smartphone apps. The presented catalog is aimed at mapping the identified legal principles to practical privacy and security solutions that can be implemented by developers to ensure enhanced privacy aligned with existing legislation. Through conducting a case study, it is confirmed that there is a significant gap between what developers are doing in reality and what they promise to do. This paper provides researchers and developers of privacy-related technicalities an overview of the characteristics of existing privacy requirements needed to be implemented in smartphone ecosystems, on which they can base their work.
One striking observation in Parkinson’s disease (PD) is the remarkable gender difference in incidence and prevalence of the disease. Data on gender differences with regard to disease onset, motor and non-motor symptoms, and dopaminergic medication are limited. Furthermore, whether estrogen status affects disease onset and progression of PD is controversially discussed. In this retrospective single center study, we extracted clinical data of 226 ambulatory PD patients and compared age of disease onset, disease stage, motor impairment, non-motor symptoms, and dopaminergic medication between genders. We applied a matched-pairs design to adjust for age and disease duration. To determine the effect of estrogen-related reproductive factors including number of children, age at menarche, and menopause on the age of onset, we applied a standardized questionnaire and performed a regression analysis. The male to female ratio in the present PD cohort was 1.9:1 (147 men vs. 79 women). Male patients showed increased motor impairment than female patients. The levodopa equivalent daily dose was increased by 18.9% in male patients compared to female patients. Matched-pairs analysis confirmed the increased dose of dopaminergic medication in male patients. No differences were observed in age of onset, type of medication, and non-motor symptoms between both groups. Female reproductive factors including number of children, age at menarche, and age at menopause were positively associated with a delay of disease onset up to 30 months. The disease-modifying role of estrogen-related outcome measures warrants further clinical and experimental studies targeting gender differences, specifically hormone-dependent pathways in PD.
Making agriculture sustainable is a global challenge. In the European Union (EU), the Common Agricultural Policy (CAP) is failing with respect to biodiversity, climate, soil, land degradation as well as socio‐economic challenges.
The European Commission's proposal for a CAP post‐2020 provides a scope for enhanced sustainability. However, it also allows Member States to choose low‐ambition implementation pathways. It therefore remains essential to address citizens' demands for sustainable agriculture and rectify systemic weaknesses in the CAP, using the full breadth of available scientific evidence and knowledge.
Concerned about current attempts to dilute the environmental ambition of the future CAP, and the lack of concrete proposals for improving the CAP in the draft of the European Green Deal, we call on the European Parliament, Council and Commission to adopt 10 urgent action points for delivering sustainable food production, biodiversity conservation and climate mitigation.
Knowledge is available to help moving towards evidence‐based, sustainable European agriculture that can benefit people, nature and their joint futures.
The statements made in this article have the broad support of the scientific community, as expressed by above 3,600 signatories to the preprint version of this manuscript. The list can be found here (https://doi.org/10.5281/zenodo.3685632).
A free Plain Language Summary can be found within the Supporting Information of this article.
Perspectives on participation in continuous vocational education training - an interview study
(2020)
In European industrialized countries, a large number of companies in the healthcare, hotel, and catering sectors, as well as in the technology sector, are affected by demographic, political, and technological developments resulting in a greater need of skilled workers with a simultaneous shortage of skilled workers (CEDEFOP, 2015, 2016). Consequently, employers have to address workers who have not been taken into account such as low-skilled workers, workers returning from a career break, people with a migrant background, older people, and jobseekers and train them, in order to guarantee the professionalization of this workforce (Festing and Harsch, 2018). Continuing vocational education and training (CVET) is seen as an indispensable tool; because CVET has advantages for both employers and employees, it helps to increase the productivity of companies (Barrett and O’Connell, 2001), to prevent the widening of socioeconomic disparities (Dieckhoff, 2007), and to open up career opportunities for the workforce (Rubenson and Desjardins, 2009). However, participation rate on CVET seems to differ, depending on institutional factors (such as sector and size of the company) and individual characteristics (such as qualification level, migration background, age and time of absence from work) (e.g., Rubenson and Desjardins, 2009; Wiseman and Parry, 2017). In contrast to previous research, our study aims to provide a holistic view of reasons for and against CVET, combining the different perspectives of employers and (potential) employees. The analysis of reasons and barriers was carried out based on semi-structured interviews. Fifty-seven employers, 73 employees, and 42 jobseekers (potential employees) from the sectors retail, healthcare and social services, hotels and catering, and technology were interviewed. Results point to considerable differences in the reasons and barriers mentioned by the disadvantaged groups. These differences are particularly significant between employees on the one side and employers, as well as jobseekers, on the other side, while the reasons to attend CVET of jobseekers are more similar to those of employers. The results can be used to tailor CVET more closely to the needs of (potential) employees and thus strengthen both the qualification and career opportunities of (potential) employees and the competitiveness and productivity of companies.
Diversity and psychological health issues at the workplace are pressing issues in today’s organizations. However, research linking two fields is scant. To bridge this gap, drawing from team faultline research, social categorization theory, and the job-demands resources model, we propose that perceiving one’s team as fragmented into subgroups increases strain. We further argue that this relationship is mediated by task conflict and relationship conflict and that it is moderated by psychological empowerment and task interdependence. Multilevel structural equation models on a two-wave sample consisting of 536 participants from 107 work teams across various industries and work contexts partially supported the hypotheses: task conflict did indeed mediate the positive relationships between perceived subgroups and emotional exhaustion while relationship conflict did not; effects on stress symptoms were absent. Moreover, contrary to our expectations, neither empowerment, nor task interdependence moderated the mediation. Results indicate that team diversity can constitute a job demand that can affect psychological health. Focusing on the mediating role of task conflict, we offer a preliminary process model to guide future research at the crossroads of diversity and psychological health at work.
Security has become one of the primary factors that cloud customers consider when they select a cloud provider for migrating their data and applications into the Cloud. To this end, the Cloud Security Alliance (CSA) has provided the Consensus Assessment Questionnaire (CAIQ), which consists of a set of questions that providers should answer to document which security controls their cloud offerings support. In this paper, we adopted an empirical approach to investigate whether the CAIQ facilitates the comparison and ranking of the security offered by competitive cloud providers. We conducted an empirical study to investigate if comparing and ranking the security posture of a cloud provider based on CAIQ’s answers is feasible in practice. Since the study revealed that manually comparing and ranking cloud providers based on the CAIQ is too time-consuming, we designed an approach that semi-automates the selection of cloud providers based on CAIQ. The approach uses the providers’ answers to the CAIQ to assign a value to the different security capabilities of cloud providers. Tenants have to prioritize their security requirements. With that input, our approach uses an Analytical Hierarchy Process (AHP) to rank the providers’ security based on their capabilities and the tenants’ requirements. Our implementation shows that this approach is computationally feasible and once the providers’ answers to the CAIQ are assessed, they can be used for multiple CSP selections. To the best of our knowledge this is the first approach for cloud provider selection that provides a way to assess the security posture of a cloud provider in practice.
Nach den Ereignissen in Gaggenau liest und hört man allenthalben von den "rechtlichen Schwierigkeiten", die hinsichtlich Verboten von Redeauftritten ausländischer Politiker bestünden. In Gaggenau hat man originär sicherheitsrechtlich argumentiert: viel zu viele Leute, viel zu kleiner Parkplatz, Chaos vorprogrammiert. Ähnliches nun in Köln: zu großer Aufwand, zu kurzfristig, Chaos vorprogrammiert. Nehmen wir einmal an, es seien im Einzelfall tragfähige Begründungen gewesen. Dann stellt sich zugleich die Frage: Was kann man tun, wenn man den Auftritt eines ausländischen Vertreters untersagen will, obwohl der Parkplatz groß genug und die Polizei ausreichend gegen Ausschreitungen gewappnet ist? ...
Considering the circumstance that literature dealing with the economic performance of agri-food businesses in general, or particularly with the German agricultural sector, mainly deals with strictly agricultural-related theory in order to explain the economic success of agri-food businesses, the present paper aims to extend existing discourses to further areas of thought. Consequently, the characteristics: a) increased size of agribusiness, b) pull-strategies, c) the development of new markets and d) focus on the processing industry, that all correspond to the current picture of the German agricultural sector and are considered to be significantly responsible for recently managing to outpace the French agri-food sector, will be first explained in their success against the background of mainly non-agricultural-related literature. By doing so helpful and rather unnoted perspectives can be contributed to existing discourses. Second, the paper presents scatter plots which portray correlations between a) the added value of agriculture and the regular labor force, b) the added value of agriculture and the number of agricultural holdings and c) the added value of agriculture and the number of enterprises concerning milk consumption. Corresponding scatter plots which show different developments in Germany and France can be related to the findings of the first part of the paper and allow new perspectives in existing discourses as well.
Risk culture during the last 2000 years - from an aleatory society to the illusion of risk control
(2017)
The culture of risk is 2000 years old, although the term “risk” developed much later. The culture of merchants making decisions under uncertainty and taking the individual responsibility for the uncertain future started with the Roman “Aleatory Society”, continued with medieval sea merchants, who made business “ad risicum et fortunam”, and sustained to the culture of entrepreneurs in times of industrialisation and dynamic economic changes in the 18th and 19th century. For all long-term commercial relationships, the culture of honourable merchants with personal decision-making and individual responsibility worked well. The successful development of sciences, statistics and engineering within the last 100 years led to the conjecture that men can “construct” an economical system with a pre-defined “clockwork” behaviour. Since probability distributions could be calculated ex-post, an illusion to control risk ex-ante became a pattern in business and banking. Based on the recent experiences with the financial crisis, a “risk culture” should understand that human “Strength of Knowledge” is limited and the “unknown unknown” can materialise. As all decisions and all commercial agreements are made under uncertainty, the culture of honourable merchants is key to achieve trust in long-term economic relations with individual responsibility, flexibility to adapt and resilience against the unknown.
Die Wettbewerbsfähigkeit der deutschen Wirtschaft steht vor gewaltigen Herausforderungen. Traditionell starke Sektoren wie die Automobilindustrie oder der Maschinenbau befinden sich angesichts disruptiver Veränderungen durch neue Technologien, den Kampf gegen den Klimawandel und veränderte regulatorische Rahmenbedingungen in einer Umbruchphase. Zahlreiche Industriezweige wandeln sich durch den Einsatz von Künstlicher Intelligenz zu „Smart Industries“. Gleichzeitig gewinnt die Kompetenz in Querschnittstechnologien wie Cloud Computing oder Cyber Security an Bedeutung, da diese den effektiven Einsatz von Künstlicher Intelligenz erst ermöglichen. Eine Analyse der Wettbewerbsposition der deutschen Wirtschaft zeigt auf, dass in manchen Zukunftsfeldern ein erheblicher Nachholbedarf besteht.
Auf die Fragen kommt es an: "Woher kommt der Mensch? wo will er hin? – und warum um alles in der Welt ist er da nicht geblieben?" Der Meister zirkulärer Sinnsuche hat als Fragender seine beste Rolle gefunden und damit den postheroischen Typus Mensch erschaffen, der in der Vieldeutigkeit der Welt erleichtert seinen Unfrieden findet: damit, dass Pazifisten Kriege verteidigen, dass die Außerparlamentarischen eine Partei gründen, dass die Konservativen die interessanteren Zeitungen machen und die Komik zur wirksamsten Waffe gegen Dummheit und Schmerz geworden ist. Matthias Beltz hat beiläufig mit Lebensweisheiten und assoziativ aufgetürmtem Scharfsinn nicht nur seine Fragen bewaffnet, in denen gewagte Antworten ihren vitalen Keim austreiben, sondern auch das Misstrauen gesät gegenüber politisch korrekten, nachgeplapperten und smarten Antworten. ...
We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.
Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the “unknown unknown.” While machine learning has been tested successfully in the regime of the “known,” heuristics typically provide better results for an active operational risk management (in the sense of forecasting). However, precursors in existing data can open a chance for machine learning to provide early warnings even for the regime of the “unknown unknown.”
A commentary on Commentary: Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking by Consoli, G. (2017). Front. Psychol. 8:1197. doi: 10.3389/fpsyg.2017.01197
In his commentary on the paper “Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking,” authored by Jan R. Landwehr and myself (Graf and Landwehr, 2017), Consoli (2017) deplores two aspects of our paper. First, an inadequate definition and operationalization of the key constructs aesthetic pleasure, aesthetic interest, and aesthetic liking, respectively aesthetic attractiveness. Second, the conclusions drawn from our empirical studies. While I acknowledge that one may have a different theoretical perspective on aesthetic perception and evaluation, it appears that Consoli's (2017) commentary does not even address the empirical data of our studies but only our theoretical assumptions and definitions. In the following, I will address Consoli's (2016, 2017) arguments in more detail, and I will corroborate our theoretical reasoning with the empirical data of our studies (Graf and Landwehr, 2017).....
Inhibitory interneurons govern virtually all computations in neocortical circuits and are in turn controlled by neuromodulation. While a detailed understanding of the distinct marker expression, physiology, and neuromodulator responses of different interneuron types exists for rodents and recent studies have highlighted the role of specific interneurons in converting rapid neuromodulatory signals into altered sensory processing during locomotion, attention, and associative learning, it remains little understood whether similar mechanisms exist in human neocortex. Here, we use whole-cell recordings combined with agonist application, transgenic mouse lines, in situ hybridization, and unbiased clustering to directly determine these features in human layer 1 interneurons (L1-INs). Our results indicate pronounced nicotinic recruitment of all L1-INs, whereas only a small subset co-expresses the ionotropic HTR3 receptor. In addition to human specializations, we observe two comparable physiologically and genetically distinct L1-IN types in both species, together indicating conserved rapid neuromodulation of human neocortical circuits through layer 1.
Although existing research has established that aesthetic pleasure and aesthetic interest are two distinct positive aesthetic responses, empirical research on aesthetic preferences usually considers only aesthetic liking to capture participants’ aesthetic response. This causes some fundamental contradictions in the literature; some studies find a positive relationship between easy-to-process stimulus characteristics and aesthetic liking, while others suggest a negative relationship. The present research addresses these empirical contradictions by investigating the dual character of aesthetic liking as manifested in both the pleasure and interest components. Based on the Pleasure-Interest Model of Aesthetic Liking (PIA Model; Graf and Landwehr, 2015), two studies investigated the formation of pleasure and interest and their relationship with aesthetic liking responses. Using abstract art as the stimuli, Study 1 employed a 3 (stimulus fluency: low, medium, high) × 2 (processing style: automatic, controlled) × 2 (aesthetic response: pleasure, interest) experimental design to examine the processing dynamics responsible for experiencing aesthetic pleasure versus aesthetic interest. We find that the effect of stimulus fluency on pleasure is mediated by a gut-level fluency experience. Stimulus fluency and interest, by contrast, are related through a process of disfluency reduction, such that disfluent stimuli that grow more fluent due to processing efforts become interesting. The second study employed product designs (bikes, chairs, and lamps) as stimuli and a 2 (fluency: low, high) × 2 (processing style: automatic, controlled) × 3 (product type: bike, chair, lamp) experimental design to examine pleasure and interest as mediators of the relationship between stimulus fluency and design attractiveness. With respect to lamps and chairs, the results suggest that the effect of stimulus fluency on attractiveness is fully mediated by aesthetic pleasure, especially in the automatic processing style. Conversely, disfluent product designs can enhance design attractiveness judgments due to interest when a controlled processing style is adopted.
The purpose of the data presented in this article is to use it in ex post estimations of interest rate decisions by the European Central Bank (ECB), as it is done by Bletzinger and Wieland (2017) [1]. The data is of quarterly frequency from 1999 Q1 until 2013 Q2 and consists of the ECB's policy rate, inflation rate, real output growth and potential output growth in the euro area. To account for forward-looking decision making in the interest rate rule, the data consists of expectations about future inflation and output dynamics. While potential output is constructed based on data from the European Commission's annual macro-economic database, inflation and real output growth are taken from two different sources both provided by the ECB: the Survey of Professional Forecasters and projections made by ECB staff. Careful attention was given to the publication date of the collected data to ensure a real-time dataset only consisting of information which was available to the decision makers at the time of the decision.
Does the rotten child spoil his companion? : spatial peer effects among children in rural India
(2014)
This paper identifies the effect of neighborhood peer groups on childhood skill acquisition using observational data. We incorporate spatial peer interaction, defined as a child's nearest geographical neighbors, into a production function of child cognitive development in Andhra Pradesh, India. Our peer group definition takes the form of networks, whose structure allows us to identify endogenous peer effects and contextual effects separately. We exploit variation over time to avoid confounding correlated with social effects. Our results suggest that spatial peer and neighborhood effects are strongly positively associated with a child's cognitive skill formation. Further, we explore the effect of peer groups in helping to provide insurance against the negative impact of idiosyncratic shocks to child learning. We find that the data reject full risk-sharing, but cannot rule out the existence of partial risk-sharing on behalf of peers. We show that peer effects are robust to different specifications of peer interactions and investigate the sensitivity of our estimates to potential misspecification of the network structure using Monte Carlo experiments.
This paper presents a comprehensive extension of pricing two-dimensional derivatives depending on two barrier constraints. We assume randomness on the covariance matrix as a way of generalizing. We analyse common barrier derivatives, enabling us to study parameter uncertainty and the risk related to the estimation procedure (estimation risk). In particular, we use the distribution of empirical parameters from IBM and EURO STOXX50. The evidence suggests that estimation risk should not be neglected in the context of multidimensional barrier derivatives, as it could cause price differences of up to 70%.
We consider a class of panel tests of the null hypothesis of no cointegration and cointegration. All tests under investigation rely on single-equations estimated by least squares, and they may be residual-based or not. We focus on test statistics computed from regressions with intercept only (i.e., without detrending) and with at least one of the regressors (integrated of order 1) being dominated by a linear time trend. In such a setting, often encountered in practice, the limiting distributions and critical values provided for and applied with the situation “with intercept only” are not correct. It is demonstrated that their usage results in size distortions growing with the panel size N. Moreover, we show which are the appropriate distributions, and how correct critical values can be obtained from the literature.
Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature), quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.
We analyze and compare the social, cultural and historical determinants that influence the international competitiveness of China and India. Starting with the discussion why pure economic determinants cannot solely explain a country's competitiveness, we will analyze previous qualitative research and evaluate quantitative data to assess which country has more favorable socio-economic factors influencing its economic performance in the long run.
We study platform design in online markets in which buying involves a (nonmonetary) cost for consumers caused by privacy and security concerns. Firms decide whether to require registration at their website before consumers learn relevant product information. We derive conditions under which a monopoly seller benefits from ex ante registration requirements and demonstrate that the profitability of registration requirements is increased when taking into account the prospect of future purchases or an informational value of consumer registration to the firm. Moreover, we consider the effectiveness of discounts (store credit) as a means to influence the consumers’ registration decision. Finally, we confirm the profitability of ex ante registration requirements in the presence of price competition.
Telecommunications companies traditionally offer several tariffs from which their customers can choose the tariff that best suits their preferences. Yet, customers sometimes make choices that are not optimal for them because they do not minimize their bill for a certain usage amount. We show in this paper that companies should be very concerned about choices in which customers pick tariffs that are too small for them because they lead to a significant increase in customers churn. In contrast, this is not the case if customers choose tariffs that are too big for them. The reason is that in particular flat-rates provide customers with the additional benefit that they guarantee a constant bill amount that consumption can be enjoyed more freely because all costs are already accounted for.
Marketers increasingly use word of mouth to promote products or acquire new customers. But is such companystimulated WOM effective? Are customers who are referred by other customers really worth the effort? A recent study clearly says “yes”. In a study of almost 10,000 accounts at a German bank, the referred customers turned out to be 25 % more profi table than customers acquired by other means. Over a 33-month period, they generated higher profi t margins, were more loyal and showed a higher customer lifetime value. The difference in lifetime value between referred and non-referred customers was most pronounced among younger people and among retail (as opposed to private banking) customers. The reward of € 25 per acquired customer clearly paid off. Given the average difference in customer lifetime value of € 40, this amount implied a return on investment (ROI) of roughly 60 % over a six-year period. The encouraging results of this study, however, do not imply that “viral-for-hire” works in each and every case. Referral programs would be most beneficial for products and services that customers might not appreciate immediately. Products and services that imply some kind of risk would also benefit to a more than average degree from referrals because prospects are likely to feel more confi dent when a trusted person has positive experiences. Companies should consider carefully which prospects to target with referral programs and how large a referral fee to provide.
The success stories of design-oriented companies like Apple, Audi or Nike have put design on the agenda in many marketing departments. Consumers cannot elude the effect of aesthetics and therefore design is a major factor for business success. Typically consumers choose the product with the best design, all other aspects being equal. Only when the interplay of product characteristics, brand and design is carefully coordinated can successful products be created. This requires an integrated approach to design, one which is applied right at the beginning of the value chain. Product development, marketing and design need to work in close cooperation, communicate well and frequently, and collect feedback from the market. Superior aesthetics are always important but should be a top priority in cases where efficiency-oriented Asian competitors are able to offer functionally similar products at much lower prices.
In many markets, design is one of the key factors in determining a product’s success. The present research offers insights into the role of design for the success of cars, and offers procedures to measure the quality of the designs objectively. The authors show that visual design plays a major role in a product’s success in the automobile market. In the study, two visual design aspects were already sufficient to significantly improve traditional sales forecasting models for cars. Visual prototypicality and visual complexity both had a positive impact on sales, and designs that were perceived as both prototypical and complex were the ones that displayed the best results. Most design evaluation used to be based on subjective measures, but the researcher applied a new, objective procedure to measure prototypicality and complexity. While the latter was detected by the disk space needed by the compressed image file, the new approach for measuring prototypicality was even more sophisticated. It relied on the technique of image morphing. Morphing is a technique that allows the construction of a visual synthesis – or average picture – from a number of individual pictures. Once a car morph is developed, one can determine the visual similarity of different car models to the morph in order to obtain its prototypicality. In principle, this procedure can be automated completely, and including a large number of versions is possible. These measures therefore seem suitable for supporting design decision processes in practice.
We study the effects of the recent economic crisis on firms׳ bidding behavior and markups in sealed bid auctions. Using data from Austrian construction procurements, we estimate bidders׳ construction costs within a private value auction model. We find that markups of all bids submitted decrease by 1.5 percentage points in the recent economic crisis, markups of winning bids decrease by 3.3 percentage points. We also find that without the government stimulus package this decrease would have been larger. These two pieces of evidence point to pro-cyclical markups.
Markets are central to modern society, so their failures can have devastating effects. Here, we examine a prominent failure: price bubbles. We propose that bubbles are affected by ethnic homogeneity in the market and can be thwarted by diversity. Using experimental markets in Southeast Asia and North America, we find a marked difference: Market prices fit true values 58% better in diverse markets. In homogenous markets, overpricing is higher and traders’ errors are more correlated than in diverse markets. The findings suggest that price bubbles arise not only from individual errors or financial conditions, but also from the social context of decision making. Informing public discussion, our findings suggest that diversity facilitates friction that enhances deliberation and upends conformity.
Spätestens seit die Europäische Zentralbank (EZB) ihr Ankaufprogramm für Wertpapiere bekannt gegeben hat, ist die Diskussion über die Wirksamkeit dieser Maßnahmen auch in Europa angekommen. Wegen der besonderen institutionellen Umstände des Euroraums – Kauf von Anleihen der einzelnen Nationalstaaten und des Verbots der monetären Finanzierung – reichen die möglichen Nebenwirkungen hierzulande über den rein geldpolitischen Horizont hinaus.
"Ökonomische Modelle und Geschichtswissenschaften gehören zusammen", konstatiert der französische Wissenschaftler Thomas Piketty, dessen Thesen weltweit diskutiert werden, und ergänzt in einem Interview in der "Süddeutschen Zeitung" provokant: "Forscher arbeiten mit hochentwickelten Modellen und anspruchsvoller Mathematik, um Kleinigkeiten zu erklären. Manchmal zeigen diese Modelle auch gar nichts." Der Frankfurter Ökonom Bertram Schefold nimmt die Entwicklung seines Fachs – insbesondere in Frankfurt – unter die Lupe.
The aim of the following paper is to examine the complementarities (and divergences) between the paleoliberal Adam Smith and the ordoliberal Walter Eucken. Following the hypothesis that Smith is among the forerunners and predecessors of Ordoliberalism and Social Market Economy, we try to provide the reader with an insight into the socio-political philosophy of Smith and Eucken pointing at similarities and differences alike. Therefore, we base our examination on a systematic primary source text analysis comparing the books and essays written by Eucken and Smith. The paper tackles these questions in two main steps: The first part highlights Smith's and Eucken's complex and interdependent system of natural liberty. The second section reviews Smith's and Eucken's philosophy of the state.
Eucken's writings are rich in content not only from an (constitutional) economic perspective but also from an economic and business ethics perspective – an often neglected perspective of the reception of German Ordoliberalism in general and the Freiburg School of Economics in particular. The paper gives a first insight into the ethical-normative thinking of Eucken, as one of the main representatives of Ordoliberalism, and explains Eucken’s conception of Social Market Economy as a functioning and humane order as well as Eucken’s Kantian understanding of freedom. To conclude the essay tries to classify Eucken’s Ordoliberalism as a part of the spectrum of modern economic and business ethics.
Wie lässt sich das anthropologische Fundament des Ordoliberalismus und der Sozialen Marktwirtschaft beschreiben? Welche Prämissen liegen ihm zugrunde? Ist ein derartiges Menschenbild überhaupt noch zeitgemäß? Welchen Gefahren ist es ausgesetzt und welche institutionellen Vorkehrungen lassen sich treffen? Diese und andere Fragen stehen im Mittelpunkt des nachfolgenden Essays. Dieser ist dabei wie folgt gegliedert: Das zweite Kapitel analysiert die anthropologischen Grundlagen des Ordoliberalismus. Ein Schwerpunkt liegt dabei auf dem kantischen ‚Programm der Freiheit als Autonomie‘. Das darauf folgende dritte Kapitel thematisiert mögliche Gefahrenpotenziale für eben jenes ordoliberale Menschenbild. Hierbei werden insbesondere die Vermachtung der Wirtschaft und die Instrumentalisierung und Funktionalisierung der Wissenschaft eingehender untersucht. Im vorletzten Kapitel schließlich werden die häufig vorgeschlagenen institutionellen Vorkehrungen kritisch evaluiert. Wichtige Beiträge hierzu stammen aus der Feder von Röpke (Clercs und Nobilitas naturalis) und Hayek (Zwei-Kammern-Verfassungsmodell).
As recent newspaper headlines show the topic of patents/patent laws is still heavily disputed. In this paper I will approach this topic from a theoretical-historical and history of economic thought-perspective. In this regard I will link the patent controversy of the nineteenth century with Walter Eucken’s Ordoliberalism – a German version of neoliberalism. My paper is structured as follows: The second chapter provides the reader with a historical introduction. At the heart of this paragraph are the controversy and discourse on patent laws in nineteenth century Europe as well as the pro and contra arguments presented by the anti-patent/free-trade movement respectively by the advocates of patent protection. The focus of my paper is on the struggle for the protection of inventions and innovations in nineteenth century Germany, since Walter Eucken, main representative of the Freiburg School of Law and Economics, picks up the counter-arguments presented in the national debate and in particular by the Kongress deutscher Volkswirthe. The third chapter deals intensively with the question whether patent laws are just ‘nonsense upon stilts’ from an ordoliberal perspective. Here, Eucken’s arguments against the current patent system are elaborated in great detail. The paper ends with a summary of my main findings.
Zeit seines Lebens beschäftigte sich Goethe mit ökonomischen Theorien; in seinem dichterischen Werk entwarf er wirtschaftliche Visionen, die das späte 19. und das frühe 20. Jahrhundert übersahen. Seine positive Vision des Kapitalismus ist von einer Sittlichkeit durchdrungen, die extreme Formen des Erwerbsstrebens und der Ausbeutung hemmt. Dagegen steht Goethes Schreckensbild eines uns modern erscheinenden Kapitalismus, wie es im »Faust« beschworen wird.
Vielfältige Einschnitte im Rentensystem haben die Bedeutung der privaten Altersvorsorge in den vergangenen Jahren massiv erhöht. Neben Immobilienbesitz, Lebensversicherungen und staatlich geförderten Programmen zur privaten Vorsorge hat sich inzwischen auch die eigenverantwortliche Altersvorsorge mit Wertpapierdepots etabliert, so dass die Anzahl privater Depots in den letzten 25 Jahren von 8,0 auf 27,9 Millionen gestiegen ist. Vor diesem Hintergrund ist die Frage von zentraler Bedeutung, wie gut Anleger ihr Geld investieren.
Kaum eine andere Industrie wurde in den vergangenen beiden Jahrzehnten so massiv durch den Einzug der Informationstechnologie geprägt wie der Wertpapierhandel. Traditionelle Geschäftsmodelle haben sich grundlegend verändert. Das klassische Börsenparkett ist nahezu vollständig elektronischen Handelsplattformen gewichen.
Die Rechnung kommt immer zum Schluss – und sie zu bezahlen, macht in der Regel keine Freude. Wenn wir aber schon eher ungern bezahlen, soll die Zahlungsmethode selbst wenigstens einfach, überall verfügbar und sehr sicher sein. Insbesondere die Sicherheit ist beim Bezahlen im 21. Jahrhundert ein wichtiges Thema, zu dem es interdisziplinäre Forschungsansätze aus Wirtschaftswissenschaften, Informatik und Recht in einem von dynamischer Entwicklung geprägten Umfeld gibt.
We analyze the implications of the governance structure in academic faculties for their recruitment decisions when competing for new researchers. The value to individual members through social interaction within the faculty depends on the average status of their fellow members. In recruitment decisions, incumbent members trade off the effect of entry on average faculty status against alternative uses of the recruitment budget if no entry takes place. We show that the best candidates join the best faculties but that they receive lower wages than some lesser ranking candidates. We also study the allocation of surplus created by the entry of a new faculty member and show that faculties with symmetric status distributions maximize their joint surplus under majority voting.
Der verstärkte Umgang mit Wissen in den Wirtschaftswissenschaften ist in den letzten Jahren in den Fokus der Wissenschaftler geraten. Ausgeblendet wurde dabei größtenteils die Kehrseite von Wissen, die Frage nach dem "Nichtwissen". Das Nichtwissen ist aufgrund der vorherrschenden Auffassung des gesellschaftlichen Bildes mit einer negativen Notation behaftet. Die zunehmende Auseinandersetzung des Nichtwissens in den Geisteswissenschaften bringt die positiven Funktionen zur Geltung. Der vorliegende Artikel zeigt zunächst die erfolgsfördernden Funktionen des Nichtwissens auf und implementiert somit Chancen des Nichtwissens in einem wirtschaftwissenschaftlichen Rahmen. Im Anschluss werden empirische Befunde, resultierend aus einer Befragung, die an der Goethe Universität Frankfurt am Main durchgeführt wurde, präsentiert.
We propose a model of the dynamics of organizational communication. Our model specifies the mechanics by which communication impact is fed back to communication inputs and closes the gap between sender and receiver of messages. We draw on language critique, a branch of language philosophy, and derive joint linguistic actions of interlocutors to explain the emergence and adaptation of communication on the group level. The model is framed by Te'eni's cognitive-affective model of organizational communication.
An information system is more than just the information technology; it is the system that emerges from the complex interactions and relationships between the information technology and the organization. However, what impact information technology has on an organization and how organizational structures and organizational change influence information technology remains an open question. We propose a theory to explain how communication structures emerge and adapt to environmental changes. We operationalize the interplay of information technology and organization as language communities whose members use and develop domain-specific languages for communication. Our theory is anchored in the philosophy of language. In developing it as an emergent perspective, we argue that information systems are self-organizing and that control of this ability is disseminated throughout the system itself, to the members of the language community. Information technology influences the dynamics of this adaptation process as a fundamental constraint leading to perturbations for the information system. We demonstrate how this view is separated from the entanglement in practice perspective and show that this understanding has far-reaching consequences for developing, managing, and examining information systems.
Theory building is not only underdeveloped in IT services management research, but in
general in IS. Given the paradigm shift that comes from the development away from a
networked economy towards a network economy, the lack of spending enough attention to
theorizing in IS becomes even more obvious. In the light of other "megatrends" in IS
research, such as the increasing professionalization and use of statistical methods and the
exploitation of extremely large sets of data (often harvested from social media sites), we
might lose interest in theorizing in the presence of the tremendous amount of available
empirical data. In this position paper, the author advocates that services science researchers
should focus on rigor and relevance in their research approaches.
Vom "Netz-Doktor" bis "Health 2.0" : welche Möglichkeiten das Internet chronisch Kranken bieten kann
(2011)
Jeder fünfte Deutsche ist inzwischen bereits über 65 Jahre, und der demografische Wandel schreitet voran. Mit dem wachsenden Anteil Älterer nimmt auch die Zahl der chronisch Kranken stetig zu. Diese Patienten haben einen besonders hohen Bedarf an aktuellen medizinischen Informationen; das stellt neue Herausforderungen an alle Beteiligten im Gesundheitssystem. Unter dem Stichwort "Health 2.0" untersucht der Wirtschaftsinformatiker Christoph Rosenkranz, welche interaktiven Möglichkeiten das Internet den Betroffenen bisher schon bietet und was es darüber hinaus in Zukunft leisten sollte.
The Dagstuhl Perspectives Workshop "Online Privacy: Towards Informational Self-Determination on the Internet" (11061) has been held in February 6-11, 2011 at Schloss Dagstuhl. 30 participants from academia, public sector, and industry have identified the current status-of-the-art of and challenges for online privacy as well as derived recommendations for improving online privacy. Whereas the Dagstuhl Manifesto of this workshop concludes the results of the working groups and panel discussions, this article presents the talks of this workshop by their abstracts.
Der "Generationenvertrag" der gesetzlichen Rentenversicherung hat die Grenzen seiner Leistungsfähigkeit erreicht. Damit ist die "erste Säule" der Alterssicherung, die auf diesem Umlageverfahren basiert, ins Wanken geraten. Schuld daran ist die zunehmende Überalterung der Gesellschaft, aber auch die anhaltend hohe Arbeitslosigkeit, die zu enormen Beitragsausfällen führt. Schon heute sind die Rentenzahlungen nur noch zu rund 75 Prozent durch die Sozialversicherungsbeiträge der arbeitenden Bevölkerung gedeckt, der Rest muss – ähnlich wie bei den Beamtenpensionen – aus dem allgemeinen Steueraufkommen finanziert werden. Das birgt vor allem für die jungen Beitragszahler substanzielle Risiken. Angesichts dieser Perspektiven sind immer weniger junge Menschen bereit, steigende Rentenbeiträge bei stetig sinkenden Leistungen zu akzeptieren. Kann die kapitalgedeckte Alterssicherung diese Defizite auffangen? Wie lassen sich die vielfältigen Konzepte der privaten Alterssicherung bewerten?
We propose a theory characterizing information systems (IS) as language communities which use and develop domain-specific languages for communication. Our theory is anchored in Language Critique, a branch of philosophy of language. In developing our theory, we draw on Systems Theory and Cybernetics as a theoretical framework. "Organization" of a system is directly related to communication of its sub-systems. "Big systems" are self-organizing and the control of this ability is disseminated throughout the system itself. Therefore, the influence on changes of the system from its outside is limited. Operations intended to change an organization are restricted to indirect approaches. The creation of domain-specific languages by the system itself leads to advantageous communication costs compared to colloquial communication at the price of set-up costs for language communities. Furthermore, we demonstrate how our theoretical constructs help to describe and predict the behavior of IS. Finally, we discuss implications of our theory for further research and IS in general. Keywords: Language Critique, language communities, communication, self-organization, IS research
Immer auf den ersten Rängen : Leibniz-Preis für den Frankfurter Volkswirtschaftler Roman Inderst
(2010)
Wenn es um Superlative geht, dann steht der 40-jährige Prof. Roman Inderst immer ganz oben auf dem Treppchen: jung und schon auf den ersten Rängen unter den Top Ten der europäischen Wirtschaftswissenschaftler. Und am 15. März wurde er auch noch als jüngster unter den zehn Preisträgern mit dem wichtigsten deutschen Forschungspreis, dem mit 2,5 Millionen Euro dotierten Gottfried Wilhelm Leibniz-Preis 2010, ausgezeichnet.
Plattformen für Social Communities im Internet, wie Facebook, StudiVZ und XING, haben in den vergangenen Jahren rasant an Popularität gewonnen. Auf ihnen versammeln sich bereits heute Millionen von Nutzern weltweit. Sie verbinden sich über virtuelle Freundeslisten und tauschen sich über gemeinsame Interessen und Aktivitäten aus. Immer häufger werden dazu auch mobile Endgeräte wie Handys verwendet, erlauben diese doch ständig in Kontakt mit der Community zu bleiben. Allerdings wollen viele Nutzer längst nicht jedem Mitglied einer Community alles preisgeben. Doch wie lässt sich die Privatsphäre in solchen Communities besser schützen? Dieser Frage geht das Forschungsprojekt PICOS nach.
In diesem Beitrag zur Frage nach dem Ausmaß von Einkommensarmut von Familien stehen zwei Aspekte im Mittelpunkt. – Zum einen ist im Vorfeld von Verteilungsanalysen die Art der Einkommensgewichtung in Mehrpersonenhaushalten zu klären. Nach Abwägung verschiedener Ansätze zur Ableitung einer Äquivalenzskala wurde eine Präferenz für ein institutionell orientiertes Gewichtungsschema, approximiert durch die alte OECD-Skala, begründet. – Zum anderen wurde der Einfluss der Frauenerwerbsbeteiligung auf die Einkommenssituation von Familien mit Kindern empirisch untersucht. Von prekären Einkommensverhältnissen und Einkommensarmut sind vor allem Familien mit geringfügig beschäftigter oder nichterwerbstätiger Partnerin sowie Alleinerziehende – Letztere wiederum bei fehlender Erwerbstätigkeit besonders stark – betroffen, wobei in den neuen Ländern die Situation wesentlich brisanter ist als in den alten Ländern. Bei politischen Maßnahmen sollten Erwerbswünsche der Frauen und Bedürfnisse der Familien berücksichtigt werden. Von daher sind Transfers im Rahmen des Familienleistungsausgleichs und die öffentliche Förderung von Kinderbetreuungseinrichtungen nicht als konkurrierende, sondern eher als komplementäre Konzepte zu diskutieren.
The recent success of some alternative trading systems (ATSs) has had a strong impact on the traditional stock exchange industry and many observers expect even more dramatic changes in the future. This paper investigates the nature of competition between stock exchanges and ATSs and argues that the introduction of ATSs weakens the level of competition between market-makers in the traditional exchange...