1,721,808 research outputs found
Learning tensions – a multilevel model of organisational learning: an empirical study
No full textThere is a growing recognition that the study of Organisational learning needs to be considered across three levels of analysis: individual, group, and organisational levels (March, 1991; Nonaka and Takeuchi, 1995; Crossan et al., 1999; 2011). Given the potential of multilevel research to extend the boundaries of the understanding of the field, this thesis aims to address how organisations learn as a multilevel system. The answers to the research inquiry were drawn from both theoretical works and by conducting an empirical investigation.To assist the investigation of the OL phenomenon in multilevel settings, a multilevel model of OL was proposed. The model provides analytical foci by specifying the learning tensions at the individual, group, and organisational levels. The model was employed in a case study of a Vietnamese public organisation, which had successfully undergone a business transformation. Through the contributions of this thesis, the author hopes to spark more interest in multilevel research of OL
The interplay of ranks of submatrices
Full text linkA banded invertible matrix T has a remarkable inverse. All "upper" and "lower" submatrices of T⁻¹ have low rank (depending on the bandwidth in T). The exact rank condition is known, and it allows fast multiplication by full matrices that arise in the boundary element method.
We look for the "right" proof of this property of T⁻¹. Ultimately it reduces to a fact that deserves to be better known: Complementary submatrices of any T and T⁻¹ have the same nullity. The last figure in the paper (when T is tridiagonal) shows two submatrices with the same nullity n – 3. Then C has rank 1. On and above the diagonal of T⁻¹, all rows are proportional.Singapore-MIT Alliance (SMA
Sharp bound on the support of integer linear optimal solutions
No full textWe study the support of optimal solutions of integer linear programs (ILP) that are of the form . We provide an upper bound on the size of the support as (m-1)+\ceil{\log_2(g^{-1} \sqrt{det(AA^T)})} and show that the bound is tight in the following senses. First, we provide a class of problem where equality hold. Second, we provide a variation of \citet{aliev2018support} asymtotic lower bound of the size of the support that matches the form of the upper bound better
A fast approximation algorithm for solving the complete set packing problem
No full textWe study the complete set packing problem (CSPP) where the family of feasible subsets may include all possible combinations of objects. This setting arises in applications such as combinatorial auctions (for selecting optimal bids) and cooperative game theory (for finding optimal coalition structures). Although the set packing problem has been well-studied in the literature, where exact and approximation algorithms can solve very large instances with up to hundreds of objects and thousands of feasible subsets, these methods are not extendable to the CSPP since the number of feasible subsets is exponentially large. Formulating the CSPP as an MILP and solving it directly, using CPLEX for example, is impossible for problems with more than 20 objects. We propose a new mathematical formulation for the CSPP that directly leads to an efficient algorithm for finding feasible set packings (upper bounds). We also propose a new formulation for finding tighter lower bounds compared to LP relaxation and develop an efficient method for solving the corresponding large-scale MILP. We test the algorithm with the winner determination problem in spectrum auctions, the coalition structure generation problem in coalitional skill games, and a number of other simulated problems that appear in the literature
Der Bildungskompass : eine kritische Untersuchung
No full textNguyen Tri Minh, BAAbstract in englischer SpracheMasterarbeit Universität Innsbruck 202
The fairest core in cooperative games with transferable utilities
No full textThe core and the Shapley value are important solution concepts in cooperative game theory. While the core is designed for the stability of the game, the Shapley value aims for fairness among the players. However, the Shapley value might not lie within the core and a core solution might not be ‘fair’. We introduce a new solution concept called the ‘fairest core’, one that aims for both stability and fairness. We show attractive properties of the fairest core
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