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Using a fuzzy analytic hierarchy process (FAHP), the weights of criteria and subcriteria are determined and then the final ranking is determined by technique for order preference by similarity to ideal solution (TOPSIS). As the human decision-making process usually contains fuzziness and vagueness, a hierarchy of MADM model based on fuzzy-sets theory is used in this research. Many quantitative and qualitative factors must be considered to determine the suitable criteria. However, the nature of these kinds of decisions is usually complex and unstructured. Over the past few years, the determination of suitable cost-effectiveness criteria in the supply chain has become a key strategic issue.
The aim of this paper is to evaluate and prioritize the proposed cost-effectiveness criteria in supply chain management using fuzzy multiple attribute decision-making (MADM) approach.
The results obtained point out possible increasing/decreasing demands among separate user groups, therefore giving a factual basis for logistics changes.
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This software offers graphical representation of statistical data for selected brands based on the social network statuses, its implications, as well as target group demographic and territorial structure. Filtering is being done by already developed software for neurolinguistics social network analysis – “Symbols”. In this paper we present a procedure for finding and analyzing valuable information related to the specific products, and its effect on logistics system decision-making. Having the possibility to extract the information of interest from a huge amount of hand created data about the users’ personal affinities and their usage within logistics system, it is facilitated to meet the customers’ needs.
According to the statistical data, the users share their impressions daily in the form of statuses about upcoming events and present state of affairs, their problems, plans, novel experiences about the products, political stances, and alike. Facebook is currently the world’s most populous “country” with more than 1.
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