On the Ethics of Trade Credit: Understanding Good Payment Practice in the Supply Chain

In spite of its commercial importance and signs of clear concern in public policy arenas, trade credit has not been subjected to systematic, extended analysis in the business ethics literature, even where suppliers as a stakeholder group have been considered. This paper makes the case for serious consideration of the ethics of trade credit and explores the issues surrounding slow payment of debts. It discusses trade debt as a kind of promise, but— noting that not all promises are good ones—goes on to develop an analysis of the ethics of trade credit grounded in an understanding of its fundamental purpose. Making a distinction between ‘‘operating’’ trade credit and ‘‘financial’’ trade credit, the paper provides an account of the maximum period for which it is appropriate for one company to delay payment to another from which it has purchased goods or services. The concern of commentators and policy makers that companies should not take too long to pay their debts is affirmed, but the understanding of what timely payment means is significantly finessed, with one conclusion being that, if debts have not already been settled according to acceptable standard terms of trade, cash should pass quickly back along the supply chain once the customer in the final product market has paid. The analysis has implications not only for companies that take credit but also for external parties that seek to rate companies or set regulations according to speed of payment—an approach that is shown to be misleadingly simplistic, albeit well intentioned. A corresponding important responsibility for suppliers, not to extend excessive credit (and thus act as a quasi-bank), also follows from the analysis developed. Having provided a novel analysis of an important business problem, the paper then discusses some of the related practical issues and makes suggestions for further research

Seascape Genetics of a Globally Distributed, Highly Mobile Marine Mammal: The Short-Beaked Common Dolphin (Genus Delphinus)

Identifying which factors shape the distribution of intraspecific genetic diversity is central in evolutionary and conservation biology. In the marine realm, the absence of obvious barriers to dispersal can make this task more difficult. Nevertheless, recent studies have provided valuable insights into which factors may be shaping genetic structure in the world's oceans. These studies were, however, generally conducted on marine organisms with larval dispersal. Here, using a seascape genetics approach, we show that marine productivity and sea surface temperature are correlated with genetic structure in a highly mobile, widely distributed marine mammal species, the short-beaked common dolphin. Isolation by distance also appears to influence population divergence over larger geographical scales (i.e. across different ocean basins). We suggest that the relationship between environmental variables and population structure may be caused by prey behaviour, which is believed to determine common dolphins' movement patterns and preferred associations with certain oceanographic conditions. Our study highlights the role of oceanography in shaping genetic structure of a highly mobile and widely distributed top marine predator. Thus, seascape genetic studies can potentially track the biological effects of ongoing climate-change at oceanographic interfaces and also inform marine reserve design in relation to the distribution and genetic connectivity of charismatic and ecologically important megafauna

Mixed Models for the Analysis of Optimization Algorithms

We review linear statistical models for the analysis of computational experiments on optimization algorithms. The models offer the mathematical framework to separate the effects of algorithmic components and instance features included in the analysis. We regard test instances as drawn from a population and we focus our interest not on those single instances but on the whole population. Hence, instances are treated as a random factor. Overall these experimental designs leads to mixed effects linear models. We present both the theory to justify these models and a computational example in which we analyze and comment several possible experimental designs. The example is a component-wise analysis of local search algorithms for the 2-edge-connectivity augmentation problem. We use standard statistical software to perform the analysis and report the R commands. Data sets and the analysis in SAS are available in an online compendium.

A Benders Approach to the Minimum Chordal Completion Problem

This paper introduces an integer programming approach to the minimum chordal completion problem. This combinatorial optimization problem, although simple to pose, presents con-siderable computational difficulties and has been tackled mostly by heuristics. In this paper, an integer programming approach based on Benders decomposition is presented. Computa-tional results show that the improvement in solution times over a simple branch-and-bound algorithm is substantial. The results also indicate that the value of the solutions obtained by a state-of-the-art heuristic can be in some cases significantly far away from the previously unknown optimal solutions obtained via the Benders approach