In this paper, we study the asset pricing implication of imprecise knowledge about rare events. Modeling rare events as jumps in the aggregate endowment, we explicitly solve the equilibrium asset prices in a pure-exchange economy with a representative agent who…

This paper presents a knowledge-based approach for capturing data and rationale, so
that the experience and insights gained while pursuing a major project or endeavor can
be utilized when pursuing future endeavors of a similar nature. The proposed

Complex goods and processes require ever more sophisticated and specialized knowledge; harnessing multiple kinds of expertise to execute tasks, solve problems, and develop strategies is increasingly critical to organizations' survival. When specialists come together, however, they often speak in different…

An increasing number of organizations are involved in the development of strategic
information systems for effective linkages with their suppliers, customers, and other
channel partners involved in transportation, distribution, warehousing and maintenance
activities. An efficient inter-organizational inventory…

Learning from experience, the cyclical interplay of thinking and doing, is increasingly
important as organizations struggle to cope with rapidly changing environments and more
complex and interdependent sets of knowledge. This paper confronts two central issues
for organizational learning: (1)…

Seroepidemiological studies have demonstrated that the presence of the tapeworm carrier in the household or in the close environment is the main risk factor associated to human and swine cysticercosis. Intervention measures evaluated are: 1) Mass treatment against the adult…

The consumer knowledge, attitudes and behaviour of a probability sample of English public CEGEP (Grades XII and XIII) students in the province of Quebec are investigated to provide a basis for the development of consumer education curricula. Results indicate that…

Most neural network learning algorithms cannot use knowledge other than what is provided in the training data. Initialized using random weights, they cannot use prior knowledge such as knowledge stored in previously trained networks. This manuscript thesis addresses this problem.…

Descripción completa.

Descripción completa.