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This paper gives a practical approach to the area of business ethics, in particular to Corporate Social Responsibility (CSR), via analyzing how the retail chain REWE shows its commitment to its social responsibilities as defined by the four-part model of CSR. As Fairtrade offers one way for fulfilling social responsibilities, in particular the ethical and philanthropic responsibilities of CSR, REWE’s participation in selling Fairtrade products is analyzed. This analysis is conducted by applying the criteria for receiving the Fairtrade Award to REWE which allows drawing conclusions about REWE’s commitment to Fairtrade. Information for this assessment is taken from publicly available sources as well as from personal communication with the Fairtrade organization TransFair. The paper further gives an indication about the match between REWE’s communication – as the selling of Fairtrade products is communicated via REWE’s sustainability program – and REWE’s action concerning social responsibility, expressed by its commitment to Fairtrade. Implementing a sustainability program is one way for companies to exercise CSR and thus the analysis conducted concerning REWE’s commitment to Fairtrade is an attempt to answer the question whether companies’ communication about their CSR efforts matches their actions.
This study paper introduces different tools, i.e. analytical methods and visualizations, in business intelligence environments. It especially emphasizes the use of OLAP-based technologies as a tradtional kind of data analysis in contrast to as graph analysis and formal concept analysis as rather new approaches in the area of visual analytics.
A level graph G = (V,E,λ) is a graph with a mapping λ : V → {1,...,k}, k ≥ 1, that partitions the vertex set V as V = V1 ∪...∪ Vk, Vj = λ-1(j), Vi ∩ Vj = ∅ for i ≠ j, such that λ(v) = λ(u) + 1 for each edge (u, v) ∈ E. Thus a level planar graph can be drawn with the vertices of every Vj, 1 ≤ j ≤ k, placed on a horizontal line, representing the level lj , and without crossings of edges, which can be drawn as straight line segments between the levels. Healy, Kuusik and Leipert gave a complete characterization of minimal forbidden subgraphs for level planar graphs (MLNP patterns) for hierarchies [4]. Minimal in terms of deleting an ar- bitrary edge leads to level planarity. A radial graph partitions the vertex set on radii, which can be pictured as concentric circles, instead of levels, lj = (j cos(α), j sin(α)), α ∈ [0,2π), mapped around a shared center, where j, 1 ≤ j ≤ k indicates the concentric circles’ radius. Comparing embeddings of radial graphs with that of level graphs we gain a further possibility to place an edge and eventually avoid edge crossings which we wish to prevent for planarity reasons. This offers a new set of minimal radial non planar subgraphs (MRNP patterns). Some of the MLNP pat- terns can be adopted as MRNP patterns while some turn out to be radial planar. But based on the radial planar MLNP patterns and the use of augmentation we can build additional MRNP patterns that did not occur in the level case. Furthermore we point out a new upper bound for the number of edges of radial planar graphs. It depends on the subgraphs in- duced between two radii. Because of the MRNP patterns these subgraphs can either consist of a forest or a cycle with several branches. Applying the bound we are able to characterize extremal radial planar graphs. Keywords: radial graphs, minimal non-planarity, extremal radial planar