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老師:朱大中 教授
Prof. Ta-Chung Chu
M977Z224 Charindech Santiwatthana
M97Q0211梁耀文
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In the present economy that shaped up by globalization, the
enable of accessibility to information and the increasing of
competition, the intangible assets such as knowledge become
the critical competitive advantage. In the technological
competition era, while business tend to increase their
investment, billions of dollar have been spend annually to many
projects(Williams, 2005).
Successful project consist of organization’s strategic objective,
economic environment, well-developed working structure and
projects tend to be failed when lacking of project management
(PM) discipline and professional(William, 2005).
Nidiffer and Dolan (2005) observed that people and process are
the heart to successful project development, not tools or
technology, that underscore the need of precisely select the
manager of the project.
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In Many research studies have defined the project managerial
performance in to multidimensional concepts. Several
research yield that the study of managerial performance have
to consider of social aspect and technical aspect, both
consist of qualitative such as leadership behavioral
characteristic, attribute, managerial skills..etc. and
quantitative such as time, cost, financial performance (NPV),
discount cash flow (DCF)..etc. However, most studies focused
to the project managerial performance model, not the
evaluation.
Project managerial evaluation has been a very difficult to
make. The criteria that should considered to evaluate may
have different important weights in the perspective of
different decision maker. Therefore, fuzzy set application can
be a very suitable approach.
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This research has the following objective:
◦ Establish a fuzzy weight average model for making the
evaluation of the project managerial performance.
◦ Study the relevant of the project managerial evaluation
literature and determine the criteria needed for effective
evaluation.
◦ Conduct the numerical example to show the computational
procedure and the feasibility of the propose model.
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The limits of the research can be describe as
follows:
◦ There is a huge amount of criteria that can be consider
when trying to evaluate the outcome, so in this research
will be limited the amount of criteria.
◦ We assume all the criteria are independent.
◦ We assume all the quantitative criteria are normally
distributed.
◦ The model depend largely on the degree of precision
judgment and evaluation of the decision –maker to scale
the degree of importance weight of criteria and give the
rating to each alternative versus each criteria.
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Chapter 1: Introduction
Chapter 2: Literature review
Chapter 3 : Fuzzy set theory
Chapter 4 : Fuzzy weighted average
arithmetic model
Chapter 5 : Numerical example
Chapter 6 : Conclusion