No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

The purpose of this study was to answer the question: how do children influence attraction choice while on vacation? A cross-sectional, self-administered, web-based survey of 99 adult facilitators visiting one of three tourist attractions in Winnipeg, Canada with at least one child between the ages of six and 17 was used to: 1) gain insight on how groups with a child/children prefer to travel; 2) understand the reasons why groups with a child/children choose to visit a select type of attraction; 3) examine the views of adult facilitators who travel with a child/children on the child/children’s participation with regards to the selection of tourist attractions; and 4) investigate which attraction characteristics adult facilitators believe provide their entire group with the most satisfying experience. Results indicate that children have relatively little direct influence within the family or group unit on attraction choice.

Traditionally, feasibility analysis in the construction sector is limited to financial considerations. As the concept of sustainability becomes increasingly important, the methods used in a feasibility analysis have to be reconfigured in a way that incorporates elements of sustainability. This research uses water recycling systems (within the built environment) as an example to demonstrate how sustainability factors can be integrated quantitatively in feasibility studies. The model is structured in a triple-bottom-line framework, which consists of economic, environmental, and social aspects. Each aspect is measured by a spectrum of parameters, which evaluate three project outcomes of water recycling systems—water savings, project requirements, and positive image. Based on the quantified parameters, Green Factor, a decision making method, is formulated to assist in sustainability oriented feasibility analysis for construction projects.

No description available.

This thesis investigates the representation of operational decision makers within simulation modelling. Artificial Intelligence concepts, such as expert systems focus on the problem of representing, in high-level code, complex real-world decision making problems. The author therefore proposes that the use of expert system technology may provide an improved means of representing operational decision tasks and that as a consequence, apriori possibilities may exist in the context of model experimentation based on alternative operational policies. The thesis further investigates the nature of operational decision making and the potential need to represent within a model, inter-dependencies between decision makers. A prototype system called ESSIM is developed which comprises of two interlinked components, a discrete event simulation module and expert system module. The benefits of the proposed approach are then assessed by comparing the functionally of ESSIM with conventional modelling techniques. The comparison is carried out by developing three alternative models of an automated container port, one of these using ESSIM. Experiments were then devised and executed which seek to draw conclusions on the thesis proposal.