784 resultados para Organizational Complexity
Resumo:
This conceptual paper aims to improve our understanding of how internationalised firms use outsourcing and offshoring strategies to manage knowledge and information through the life-cycle of integrated product-service solutions. More precisely, we identify the appropriate theoretical framework for this analysis and investigate through in-depth case studies how UK engineering firms organise, coordinate, and incentivise work that is executed in globally distributed teams. Our research focuses on their UK and India offices to study the organisation and governance of distributed teams. The research has several theoretical dimensions - organization; geography; time and knowledge - that it addresses as boundary challenges.
Resumo:
Requirements analysis focuses on stakeholders concerns and their influence towards e-government systems. Some characteristics of stakeholders concerns clearly show the complexity and conflicts. This imposes a number of questions in the requirements analysis, such as how are they relevant to stakeholders? What are their needs? How conflicts among the different stakeholders can be resolved? And what coherent requirements can be methodologically produced? This paper describes the problem articulation method in organizational semiotics which can be used to conduct such complex requirements analysis. The outcomes of the analysis enable e-government systems development and management to meet userspsila needs. A case study of Yantai Citizen Card is chosen to illustrate a process of analysing stakeholders in the lifecycle of requirements analysis.
Resumo:
In models of complicated physical-chemical processes operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The recently rediscovered weighted splitting schemes have the great advantage of being parallelizable on operator level, which allows us to reduce the computational time if parallel computers are used. In this paper, the computational times needed for the weighted splitting methods are studied in comparison with the sequential (S) splitting and the Marchuk-Strang (MSt) splitting and are illustrated by numerical experiments performed by use of simplified versions of the Danish Eulerian model (DEM).
Resumo:
In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the integral equation by a system of algebraic equations. Then the Markov chain iterative Monte Carlo is used to solve the system. The assumption here is that the corresponding Neumann series for the iterative matrix does not necessarily converge or converges slowly. We use a special technique to accelerate the convergence. An estimate of the computational complexity of Monte Carlo algorithm using the considered approach is obtained. The estimate of the complexity is compared with the corresponding quantity for the complexity of the grid-free Monte Carlo algorithm. The conditions under which the class of grid Monte Carlo algorithms is more efficient are given.