A study on fuzzy decision and preferred enterprise strategy

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Title:	A study on fuzzy decision and preferred enterprise strategy
Authors:	Chung, Y.-F.a , Yu, Y.L.b , Hsiao, T.-C.
Contributors:	Department of Electrical Engineering, Tunghai University
Keywords:	Fuzzy decision-making;Multi-objective system;Qualitative objective;Quantitative objective
Date:	2009
Issue Date:	2013-05-15T09:04:40Z (UTC)
Abstract:	Deciding on an enterprise strategy is often a tedious and difficult process. Although the topic in this paper has been extensively studied in the past by many researchers, this paper uses a different way of thinking to further improve the technology; the paper's view is explained in later sections of the paper. Regarding enterprise decision method, this paper shows its organization strategy and plan estimate is generally carried out using group decision method. The decision-making team shares their opinion based on their limited information and experience, and then assesses the feasibility of the plan. Hoping to efficiently and systematically create and decide on a strategy in a fuzzy environment, this study combines the opinions of various expert decision makers so as to analyze the similarity between the expert's fuzzy assessed values, and combine the fuzzy assessed values of all experts. Normally, decisions are analyzed manually, which is time-consuming as well as inadequate. The primary object of this paper is to study fuzzy enterprise decision-making. This work analyzes quantitative and qualitative objectives and strategy factors of decisions with the help of a reformed fuzzy decision-making system. Quantitative objectives are factors like annual turnover and financial condition of an enterprise. These are obtained from explicit data. Other factors like size of the distribution company, the market competitiveness, etc, are known as qualitative objectives. This study obtains the optimal decision through analyses of all quantitative and qualitative factors. We shall explain the theory of our proposal and demonstrate it through an example. The example demonstrates how an electronic parts manufacturer can select its distributor by applying our fuzzy decision-making method. ? 2009 ISSN.
Relation:	International Journal of Innovative Computing, Information and Control Volume 5, Issue 11, November 2009, Pages 3809-3826
Appears in Collections:	[Department of Electrical Engineering ] Periodical Articles

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