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- W1998454512 abstract "Business operation performance is related to corporation profitability and directly affects the choices of investment in the stock market. This paper proposes a hybrid method, which combines the ordered weighted averaging (OWA) operator and rough set theory after an attribute selection procedure to deal with multi-attribute forecasting problems with respect to revenue growth rate of the electronic industry. In the attribute selection step, four most-important attributes within 12 attributes collected from related literature are determined via five attribute selection methods as the input of the following procedure of the proposed method. The OWA operator can adjust the weight of an attribute based on the situation of a decision-maker and aggregate different attribute values into a single aggregated value of each instance, and then the single aggregated values are utilized to generate classification rules by rough set for forecasting operation performance. To verify the proposed method, this research collects the financial data of 629 electronic firms for public companies listed in the TSE (Taiwan Stock Exchange) and OTC (Over-the-Counter) market in 2004 and 2005 to forecast the revenue growth rate. The results show that the proposed method outperforms the listing methods." @default.
- W1998454512 created "2016-06-24" @default.
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- W1998454512 date "2010-01-01" @default.
- W1998454512 modified "2023-10-11" @default.
- W1998454512 title "OWA rough set model for forecasting the revenues growth rate of the electronic industry" @default.
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- W1998454512 doi "https://doi.org/10.1016/j.eswa.2009.06.020" @default.
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