Clean technologies in German economic literature: a bibliometric analysis

Over the past two decades, clean technologies (cleantech) have emerged as an important economic factor with remarkable progress. Fueled by growing concerns about climate change and diminishing fossil fuel resources, governments have put aggressive stimulus packages in place to support emerging technologies that drive cleantech businesses. The industry operates in highly regulated market conditions which in turn raises the question of whether economists have addressed private and public information requirements. To answer this question and to explore the relationship between environmental economics and clean technologies, this paper examines German literature using co-citation analysis methods. Based on the co-citation analysis of 588 documents, our results suggest that researchers have provided a rather small and fragmented set of business knowledge for the cleantech industry. Despite its economic and environmental importance, research on the private use and economic impact of cleantech remains scarce.     

A tutorial on spectral clustering

In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectral clustering appears slightly mysterious, and it is not obvious to see why it works at all and what it really does. The goal of this tutorial is to give some intuition on those questions. We describe different graph Laplacians and their basic properties, present the most common spectral clustering algorithms, and derive those algorithms from scratch by several different approaches. Advantages and disadvantages of the different spectral clustering algorithms are discussed.     

The Governance of International Nongovernmental Organizations: How Funding and Volunteer Involvement Affect Board Nomination Modes and Stakeholder Representation in International Nongovernmental Organizations

The governance of civil society organizations (CSOs) is a crucial determinant of organizational legitimacy, accountability, and performance. International nongovernmental organizations (INGOs) are a subtype of CSOs and have received a lot of attention as actors in global governance. Research suggests that INGOs can follow a membership model, where the board is elected by the membership, or a board-managed model, where the board is appointed to represent major stakeholders. Following resource dependency theory, we argue that the choice between these two models depends on the INGOs different sources of funding and the degree of volunteer involvement: As donors and volunteers provide important resources, they are in turn granted the right to nominate board members or to sit on the board. In our quantitative study we show that individual members, regional member organizations, and governmental donors hold a stronger position in the governance of INGOs than philanthropists, foundations and volunteers. Our results inform research on CSO governance by highlighting the relevance of board nomination modes and by showing how CSOs can incorporate stakeholders into their governance mechanisms.     

Repeat and Non-returning Volunteers: The Promise of Episodic Events for Volunteer Recruitment and Retention

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In this article, we are concerned with the recruitment potential of one-off episodic events for attracting and retaining...     

Gewalt als Reaktion auf Anerkennungsdefizite?

Violence between adolescents is primarily a male phenomenon. For this reason, the analysis of violent behavior focuses on 4.213 male adolescents from three different backgrounds: adolescents of Turkish descent, late migrants from Russia and Poland (Aussiedler) and native Germans. They all are attending schools (10th grade) in Northrhine-Westfalia, Germany. The data have been provided by the Youth-Survey 2001 of the Institute for Interdisciplinary Research on Conflict and Violence (IKG). The theoretical framework is provided by the theory of disintegration developed at the IKG. In comparison to Germans, Turkish adolescents show a higher rate of violence. The bivariate effect of Turkish descent on violent behavior can in multivariate logistic regression analysis partly be explained by a lack of recognition at the institutional and at the socio-structural dimensions of integration: In comparison to Germans, Turkish adolescents experience more discrimination, both in their daily life and in their school career. Those German adolescents and late migrants who suffer from a comparable degree of discrimination show similar patterns of violent behavior. Lack of recognition at the socio-emotional dimension (i.e. the relationship with the parents) have a smaller effect on violent behavior. In sum, especially the accumulation of deficits at different dimensions of integration in Germany heightens the risk for violent action.     

Comparing Experimental Designs for Benchmark Dose Calculations for Continuous Endpoints

The BMD (benchmark dose) method that is used in risk assessment of chemical compounds was introduced by Crump (1984) and is based on dose-response modeling. To take uncertainty in the data and model fitting into account, the lower confidence bound of the BMD estimate (BMDL) is suggested to be used as a point of departure in health risk assessments. In this article, we study how to design optimum experiments for applying the BMD method for continuous data. We exemplify our approach by considering the class of Hill models. The main aim is to study whether an increased number of dose groups and at the same time a decreased number of animals in each dose group improves conditions for estimating the benchmark dose. Since Hill models are nonlinear, the optimum design depends on the values of the unknown parameters. That is why we consider Bayesian designs and assume that the parameter vector has a prior distribution. A natural design criterion is to minimize the expected variance of the BMD estimator. We present an example where we calculate the value of the design criterion for several designs and try to find out how the number of dose groups, the number of animals in the dose groups, and the choice of doses affects this value for different Hill curves. It follows from our calculations that to avoid the risk of unfavorable dose placements, it is good to use designs with more than four dose groups. We can also conclude that any additional information about the expected dose-response curve, e.g., information obtained from studies made in the past, should be taken into account when planning a study because it can improve the design.     

On the Nature of Fair Behavior

This article shows that identical offers in an ultimatum game generate systematically different rejection rates depending on the other offers that are available to the proposer. This result casts doubt on the consequentialist practice in economics to define the utility of an action solely in terms of the consequences of the action irrespective of the set of alternatives. It means in particular that negatively reciprocal behavior cannot be fully captured by equity models that are exclusively based on preferences over the distribution of material payoffs.