دانلود رایگان مقاله انگلیسی اولویت بندی بازار B2C با استفاده از AHP زبان شناختی فازی مبهم - اشپرینگر 2017

Abstract

Commercial Internet rapidly developed through Business to Customer (B2C) businesses since 1990s. B2C provides free online services and discounted shopping to customers. There are lots of B2C firm alternatives in the internet for a customer who seeks for a profitable business. The selection among these B2C alternatives is a multiattribute decision-making problem with many tangible and intangible criteria under vagueness and impreciseness. In this paper, we propose a hesitant fuzzy linguistic analytic hierarchy process method for the selection among B2C firms. Hesitant fuzzy linguistic term sets are used for the assessments in the pairwise comparison matrices. An ordered weighted averaging operator is used for aggregation operator. A sensitivity analysis is also given to check the robustness of the obtained result.

7 Conclusion

There are three types of e-marketplaces: Customer to customer (C2C), Business to Business (B2B), and Business to Customer (B2C). We developed a hesitant fuzzy multiattribute model for the comparison of B2C marketplace alternatives. The developed model is based on hesitant fuzzy linguistic AHP method. For an efficient selection, we considered 21 sub-criteria under 7 main criteria, which were determined after a comprehensive search in the databases. The e-marketplaces of 5 international B2C firms have been compared based on these main and sub-criteria. The sensitivity analysis showed that the obtained rankings were robust to the changes in the criteria weights. For further research, we suggest a similar model to be developed using other extensions of fuzzy sets such as intuitionistic fuzzy sets, type-2 fuzzy sets, neutrosophic sets, or Pythagorean fuzzy sets. Alternatively, the MADM method may be changed to another method such as hesitant fuzzy TOPSIS, intuitionistic fuzzy ELECTRE, or an integrated method of these.