Affiliations: [a] College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| [b] College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| [c] Key Laboratory of Data Science and Application of Hebei Province, Tangshan, China
Correspondence:
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Corresponding author. Kebing Chen, College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China. E-mail: [email protected].
Abstract: The substitutability between products or the intensity of market competition is the key parameter affecting the supplier’s pricing decision. However, the parameter cannot be accurately measured in real life. This paper provides a method based on prior information to solve this issue. First, compared to classical concept lattice theory, the interval concept lattice theory can deal with uncertain information more accurately. It is used to extract the objects within the interval parameters [α, β], and then interval concepts and lattice structure are built. Second, based on the interval concepts and lattice structure, the association rule mining algorithm is designed to further extract the association rules under different interval parameters. Third, to obtain the effective association degree between two objects, the rule optimization algorithm is put forward by comparing the update of rules. Finally, the association degree can indirectly reflect the substitutability between products. Then the price of a new product can be determined. Our paper provides some implication on pricing for suppliers in competitive supply chain.
Keywords: Pricing decision, formal context, interval concept lattice structure, optimization and mining of association rule
