FUZZY AGGREGATION FOR RANKING IN BUSINESS

Authors

  • Eva Rakovská University of Economics in Bratislava, Faculty of Economic Informatics, Department of Applied Informatics

DOI:

https://doi.org/10.12955/peb.v2.258

Keywords:

assessment, ranking, fuzzy aggregation, knowledge discovery in databases

Abstract

Today, businesses depend strongly on data and the opinion of customers or the experience of managers or experts. The large databases contain non-heterogeneous data, which is the ground for further decisions. Business uses multicriterial decisions in more areas (e.g., customer care, marketing, product development, risk management, HR, etc.) and often it is based on assessment. One of the assessment methods is the ranking, which can be done by crisp values of data where the sharp borders between evaluated entities do not give the adequate ranking result. On the other hand, the ranking process is based on the qualitative assessment, which has linguistic expression. It is more familiar and understandable for people. The article shows how to treat non-heterogeneous data to prepare them for a ranking process using fuzzy sets theory. The article aims at offering several types of ranking methods based on different inputs and preferences of the user and describes appropriate fuzzy aggregations for solving the ranking problem.

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Published

2021-10-24

How to Cite

Rakovská, E. . (2021). FUZZY AGGREGATION FOR RANKING IN BUSINESS. Proceedings of CBU in Economics and Business, 2, 81-87. https://doi.org/10.12955/peb.v2.258
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