In recent years, numerous studies in the field of service quality have been carried out. However, relatively few studies have addressed the specific context of higher education. The purpose of this study has been to examine what dimensions constitute quality in higher education and to compare these with the dimensions of quality that have been developed in general service quality research. The focus has been on academic business studies and a student perspective was chosen. First, 29 in‐depth interviews were carried out. Based on the interviews, a questionnaire was constructed and responses were obtained from 448 Austrian and Swedish students. Using factor analysis, quality dimensions were defined. These dimensions are compared with the earlier research in the area of higher education and with the general research into service quality.
The Steiner tree problem is a challenging NP-hard problem. Many hard instances of this problem are publicly available, that are still unsolved by state-of-theart branch-and-cut codes. A typical strategy to attack these instances is to enrich the polyhedral description of the problem, and/or to implement more and more sophisticated separation procedures and branching strategies. In this paper we investigate the opposite viewpoint, and try to make the solution method as simple as possible while working on the modeling side. Our working hypothesis is that the extreme hardness of
In this work we present a branch-and-bound (B&B) framework for the asymmetric prizecollecting Steiner tree problem (APCSTP). Several well-known network design problems can be transformed to the APCSTP, including the Steiner tree problem (STP), prize-collecting Steiner tree problem (PCSTP), maximum-weight connected subgraph problem (MWCS) and the nodeweighted Steiner tree problem (NWSTP). The main component of our framework is a new dual ascent algorithm for the rooted APCSTP, which generalizes Wong's dual ascent algorithm for the Steiner arborescence problem. The lower bounds and dual information obtained from the algorithm are exploited within powerful bound-based reduction tests and for guiding primal heuristics. The framework is complemented by additional alternative-based reduction tests. All tests are applied in every node of the B&B tree. Extensive computational results on benchmark instances for the PCSTP, MWCS and NWSTP indicate the framework's effectiveness, as most instances from literature are solved to optimality within seconds, including most of the (previously unsolved) largest instances from the recent DIMACS Challenge on Steiner Trees. In many cases the framework even manages to outperform recently proposed state-of-the-art exact and heuristic algorithms. Since the network design problems addressed in this work are frequently used for modeling various real-world applications (e.g., in bioinformatics), the presented B&B framework will also be made publicly available.
Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that is based on the concept of activation functions is proposed together with strengthening inequalities. Exact and heuristic solution methods are developed and compared for the new problem. Our computational results also show that our approaches outperform the state-of-the-art on relevant, special cases of the GLCIP.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.