Irshad, M., Petersen, K., & Poulding, S. (2018). A systematic literature review of software requirements reuse approaches. Information and Software Technology, 93, 223–245.
Oelze, N., Brandenburg, M., Jansen, C., & Warasthe, R. (2018). Applying Sustainable Supply Chain Management Frameworks to Two German Case Studies. IFAC-PapersOnLine, 51, 293–296. http://doi.org/10.1016/j.ifacol.2018.11.304
Abstract
Sustainability has become a highly relevant factor for companies, economies and societies. As a consequence, the consideration of environmental and social factors is crucial to manage supply chains sustainably. The study at hand analyses and compares conceptual frameworks and empirical studies on sustainable supply chain management. The gained insights are transferred to case studies of two German firms.
Usman, M., Petersen, K., Börstler, J., & Neto, P. S. (2018). Developing and using checklists to improve software effort estimation: A multi-case study. Journal of Systems and Software, 146, 286–309.
Brandenburg, M. (2018). Design and Implementation of a Measurement and Management System for Operational and Supply Chain Performance. IEEE Engineering Management Review, 46, 117–123. http://doi.org/10.1109/EMR.2018.2848968
Gencel, C., & Petersen, K. (2018). Special Section on Measurement for Future Software Industry: Driving Value Creation. Information and software technology, 215–215.
E., O.-D., Parrot, D., Blümel, M., Labes, A., & Tasdemir, D. (2018). Molecular Networking-Based Metabolome and Bioactivity Analyses of Marine-Adapted Fungi Co-cultivated With Phytopathogens. Frontiers in Microbiology, 9, 2072.
Papatheocharous, E., Wnuk, K., Petersen, K., Sentilles, S. everine, Cicchetti, A., Gorschek, T., & Shah, S. M. A. (2018). The GRADE taxonomy for supporting decision-making of asset selection in software-intensive system development. Information and Software Technology, 100, 1–17.
Moehrle, M. G., Wustmans, M., & Gerken, J. M. (2018). How business methods accompany technological innovations—a case study using semantic patent analysis and a novel informetric measure. R&D Management, 48, 331–342.
Brandenburg, M., & Hahn, G. J. (2018). Sustainable aggregate production planning in the chemical process industry - A benchmark problem and dataset. Data in Brief, 18, 961–967. http://doi.org/10.1016/j.dib.2018.03.064
Abstract
Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). The need for powerful and efficient approaches to solve complex APP problems persists. Problem-specific solution approaches are advantageous compared to standardized approaches that are designed to provide basic decision support for a broad range of planning problems but inadequate to optimize under consideration of specific settings. This in turn calls for methods to compare different approaches regarding their computational performance and solution quality. In this paper, we present a benchmarking problem for APP in the chemical process industry. The presented problem focuses on (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates and (ii) integrated campaign planning with production mix/volume on the operational level. The mutual trade-offs between economic, environmental and social factors can be considered as externalized factors (production-related carbon emission and overtime working hours) as well as internalized ones (resulting costs). We provide data for all problem parameters in addition to a detailed verbal problem statement. We refer to Hahn and Brandenburg [1] for a first numerical analysis based on and for future research perspectives arising from this benchmarking problem.
eri, J. S. M., Petersen, K., & Mendes, E. (2018). Towards understanding the relation between citations and research quality in software engineering studies. Scientometrics, 117, 1453–1478.