About 23% of the German energy demand is supplied by natural gas. Additionally, for about the same amount Germany serves as a transit country. Thereby, the German network represents a central hub in the European natural gas transport network. The transport infrastructure is operated by...

A decision support system relies on frequent re-solving of similar problem instances. While the general structure remains the same in corresponding applications, the input parameters are updated on a regular basis. We propose a generative neural network design for learning integer decision...

In this article, we introduce the Maximum Diversity Assortment Selection Problem (MDASP), which is a generalization of the two-dimensional Knapsack Problem (2D-KP). Given a set of rectangles and a rectangular container, the goal of 2D-KP is to determine a subset of rectangles that can be placed...

Firms operate in an environment that is increasingly permeated with digital technology. The incorporation of digital technology into products, services, and operations has significant implications on how firms can attain and sustain competitive advantage. Traditional strategic models of...

Using a laboratory experiment, we study the evolution of economic networks in the context of fragmented social identity. We create societies in which members can initiate and delete links to others, and then earn payoffs from a public goods game played within their network. We manipulate whether...

We consider an optimal liquidation model in which an investor is required to execute meta-orders during intraday trading periods, and his trading activity triggers child orders and endogenously affects future order flow, both instantaneously and permanently. Under the assumptions of risk...

We experimentally explore public good production levels, and the endogenous formation of network structures to facilitate output sharing, among agents with heterogeneous production costs or valuations. Results corroborate the key theoretical insights of Kinateder & Merlino (2017) characterizing...

In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...