SummaryHow companies report their data is undergoing digitization and sustainable transformation. Sustainability is important; therefore, various stakeholders are interested in sustainability information. Companies provide the required information and strive toward the use of information systems to ensure efficient data processing. A possible approach for information provision is open data. This research introduces the idea of corporate sustainability open data (CSOD) as one new mechanism of companies' sustainability self‐reporting. Since CSOD is not yet commonly practiced by companies, a strategic analysis of the situation and its possible consequences is conducted with an analysis of strengths, weaknesses, opportunities, and threats. This research provides an overview of companies' sustainable development through open data. Moreover, it identifies drivers, challenges, and reasonable strategies for CSOD adoption. Thus, the research contributes to the establishment of an innovative application of open data in the private sector to support sustainable transformation worldwide.
We consider the online problem of packing circles into a square container. A sequence of circles has to be packed one at a time, without knowledge of the following incoming circles and without moving previously packed circles. We present an algorithm that packs any online sequence of circles with a combined area not larger than 0.350389 of the square's area, improving the previous best value of π/10 ≈ 0.31416; even in an offline setting, there is an upper bound of π/(3 + 2 √ 2) ≈ 0.5390. If only circles with radii of at least 0.026622 are considered, our algorithm achieves the higher value 0.375898. As a byproduct, we give an online algorithm for packing circles into a 1×b rectangle with b ≥ 1. This algorithm is worst case-optimal for b ≥ 2.36.
We consider dynamic loading and unloading problems for heavy geometric objects. The challenge is to maintain balanced configurations at all times: minimize the maximal motion of the overall center of gravity. While this problem has been studied from an algorithmic point of view, previous work only focuses on balancing the final center of gravity; we give a variety of results for computing balanced loading and unloading schemes that minimize the maximal motion of the center of gravity during the entire process.In particular, we consider the one-dimensional case and distinguish between loading and unloading. In the unloading variant, the positions of the intervals are given, and we search for an optimal unloading order of the intervals. We prove that the unloading variant is NP-complete and give a 2.7-approximation algorithm. In the loading variant, we have to compute both the positions of the intervals and their loading order. We give optimal approaches for several variants that model different loading scenarios that may arise, e.g., in the loading of a transport ship with containers. * This is the full version of an extended abstract that
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