This study examines credit lending decision adjustments of executive board members of German banks following different levels of auditor materiality threshold disclosures. Based on an experimental research design, we find that if a materiality threshold, which is in line with current audit...

Advances in data analytics is fundamentally changing the field of auditing. The primary objective of this paper is to develop a holistic, multidimensional framework to better understand the dynamics of the diffusion of audit data analytics (ADA). The framework we developed covers categories...

In this paper, we investigate in a controlled laboratory experiment physician behavior in the case of payment heterogeneity. In the experiment, each physician provides medical care to patients whose treatments are paid for either under fee-for-service (FFS) or capitation (CAP). We observe that...

We compare voluntary contributions to the financing of a public good in a symmetric setting to those in asymmetric settings, in which four players have different, randomly allocated endowments. We observe that a weak asymmetry in the endowment distribution leads to the same contribution level as...

In a public-good experiment with heterogeneous endowments, we investigate if and how the contribution level as well as the previously observed "fair-share" rule of equal contributions relative to one´s endowment (Hofmeyr et al., 2007; Keser et al., 2014) may be influenced by minimum-contribution...

The minimum sum-of-squares clustering problem is a very important problem in data mining and machine learning with very many applications in, e.g., medicine or social sciences. However, it is known to be NP-hard in all relevant cases and to be notoriously hard to be solved to global optimality...

The European gas market is implemented as an entry-exit system, which aims to decouple transport and trading of gas. It has been modeled in the literature as a multilevel problem, which contains a nonlinear flow model of gas physics. Besides the multilevel structure and the nonlinear flow model,...

Linear bilevel optimization problems have gained increasing attention both in theory as well as in practical applications of Operations Research (OR) during the last years and decades. The latter is mainly due to the ability of this class of problems to model hierarchical decision processes....

k -means clustering is a classic method of unsupervised learning with the aim of partitioning a given number of measurements into k clusters. In many modern applications, however, this approach suffers from unstructured measurement errors because the k -means clustering result then represents a...

Bilevel optimization is an increasingly important tool to model hierarchical decision making. However, the ability of modeling such settings makes bilevel problems hard to solve in theory and practice. In this paper, we add on the general difficulty of this class of problems by further...