The Costs of Power Interruptions in Germany: A Regional and Sectoral Analysis

A high standard of security of electricity supply comes at serious electricity system costs. However, these system costs have to be balanced with the economic costs induced by an insecure supply of electricity. Following a macroeconomic approach, we analyze the economic costs imposed by potential power interruptions in Germany. Using an extensive dataset on industries and households, we estimate both Values of Lost Load and the associated hourly costs of power interruptions for different German regions and sectors. We find that interruption costs vary significantly over time, between sectors and regions. Peaking at midday on a Monday in December at 750 Mio € per hour, the average total national outage costs amount to approximately 430 Mio € per hour. A missing gigawatt hour creates average outage costs of about 7.6 Mio €.     

The use of sampling methods in advertising research: a gap between theory and practice

In this research note, we reflect critically on the use of sampling techniques in advertising research. Our review of 1028 studies published between 2008 and 2016 in the four leading advertising journals shows that while current academic literature advocates probability sampling procedures, their actual usage is quite scarce. Most studies either lack information on the sampling method used, or engage in non-probability sampling without making adjustments to compensate for unequal selection probabilities, non-coverage, and sampling fluctuations. Based on our results, we call on researchers to revisit the fundamental aspects of sampling to increase their research results’ rigour and relevance.     

The EU Internal Market and the Transformation of Energy Systems to Sustainability

Intereconomics - Sustainability requires taking the lasting effects of current actions into account, while acknowledging uncertainty over future preferences and technology. In other words, it is a...     

Twenty-five years of research on institutions,entrepreneurship, and economic growth: what has been learned?

Small Business Economics - This paper analyzes an emergent stream of research shedding light on the institutional factors shaping entrepreneurial activity and its effect on economic growth. This...     

Trading algorithms with learning in latent alpha models

Alpha signals for statistical arbitrage strategies are often driven by latent factors. This paper analyzes how to optimally trade with latent factors that cause prices to jump and diffuse. Moreover, we account for the effect of the trader's actions on quoted prices and the prices they receive from trading. Under fairly general assumptions, we demonstrate how the trader can learn the posterior distribution over the latent states, and explicitly solve the latent optimal trading problem. We provide a verification theorem, and a methodology for calibrating the model by deriving a variation of the expectation–maximization algorithm. To illustrate the efficacy of the optimal strategy, we demonstrate its performance through simulations and compare it to strategies that ignore learning in the latent factors. We also provide calibration results for a particular model using Intel Corporation stock as an example.     

Imperfect legal unbundling of monopolistic bottlenecks

We study an industry with a monopolistic bottleneck supplying an essential input to several downstream firms. Under legal unbundling the bottleneck must be operated by a legally independent upstream firm, which may be partly or fully owned by an incumbent active in downstream markets. Access prices are regulated but the upstream firm can perform non-tariff discrimination. Under perfect legal unbundling the upstream firm maximizes only own profits; with imperfections it is biased and to some extent accounts also for the incumbent’s downstream profits. We show that increasing the incumbent’s ownership share increases total output if the upstream firm’s bias is sufficiently small, while otherwise effects are ambiguous. Stronger regulation that reduces the bias without changing ownership shares generally increases total output. We also endogenize the bias and show that it can depend non-monotonically on the ownership share.     

Shaping the Next Incarnation of Business Intelligence

The body of knowledge generated by Business Intelligence (BI) research is constantly extended by a stream of heterogeneous technological and organizational innovations. This paper shows how these can be bundled to a new vision for BI that is aligned with new requirements coming from socio-technical macro trends. The building blocks of the vision come from five research strings that have been extracted from an extensive literature review: BI and Business Process Management, BI across enterprise borders, new approaches of dealing with unstructured data, agile and user-driven BI, and new concepts for BI governance. The macro trend of the diffusion of cyber-physical systems is used to illustrate the argumentation. The realization of this vision comes with an array of open research questions and requires the coordination of research initiatives from a variety of disciplines. Due to the embedded nature of the addressed topics within general research areas of the Information Systems (IS) discipline and the linking pins that come with the underlying Dynamic Capabilities Approach such research provides a contribution to IS.     

Retail customers' self-awareness: The deindividuation effects of others

The presence of others often affects retail shopping behavior. Other customers tend to increase one's self-awareness and cause negative self-conscious emotions. This research's findings suggest fellow customers also mitigate focal customers' evaluative concerns. Deindividuation theory, which posits that other customers create anonymity and reduce self-awareness, helps explain this phenomenon. A laboratory experiment and a quasi-experimental field study in a retail setting support the notion that the presence of other customers creates a deindividuation effect on a focal customer during unwanted social evaluation from salespeople. Results show a small group of other customers resulted in lower levels of emotional discomfort and behavioral inhibition than either an empty store or a larger group size, suggesting a U shape relationship.