Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  study the problems of pricing an indivisible product to consumers who are embedded in a given social network. The goal is to maximize the revenue of the seller by the so-called iterative pricing that offers consumers a sequence of prices over time. The consumers are assumed to be impatient in that they buy the product as soon as the seller posts a price not greater than their valuations of the product. The product’s value for a consumer is determined by two factors: a fixed consumer-specified intrinsic value and a variable externality that is exerted from the consumer’s neighbors in a linear way.  focus on the scenario of negative externalities, which captures many interesting situations, but is much less understood in comparison with its positive externality counterpart. Assuming complete information about the network, consumers’ intrinsic values, and the negative externalities,  prove that it is NP-hard to find an optimal iterative pricing, even for unighted tree networks with uniform intrinsic values. Complementary to the hardness result,  design a 2-approximation algorithm for general ighted networks with (possibly) nonuniform intrinsic values.  show that, as an approximation to optimal iterative pricing, single pricing works fairly ll for many interesting cases, such as forests, Erdős–Renyi networks and Barabasi–Albert networks, although its worst-case performance can be arbitrarily bad in general networks.
['Zhigang Cao', 'Xujin Chen', 'Xiaodong Hu', 'Changjun Wang']
I am writing a research paper on a idea Approximation algorithms for pricing with negative network externalities
[{"from": "human", "value": "I am writing a research paper on a idea Approximation algorithms for pricing with negative network externalities"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  study the problems of pricing an indivisible product to consumers who are embedded in a given social network. The goal is to maximize the revenue of the seller by the so-called iterative pricing that offers consumers a sequence of prices over time. The consumers are assumed to be impatient in that they buy the product as soon as the seller posts a price not greater than their valuations of the product. The product\u2019s value for a consumer is determined by two factors: a fixed consumer-specified intrinsic value and a variable externality that is exerted from the consumer\u2019s neighbors in a linear way.  focus on the scenario of negative externalities, which captures many interesting situations, but is much less understood in comparison with its positive externality counterpart. Assuming complete information about the network, consumers\u2019 intrinsic values, and the negative externalities,  prove that it is NP-hard to find an optimal iterative pricing, even for unighted tree networks with uniform intrinsic values. Complementary to the hardness result,  design a 2-approximation algorithm for general ighted networks with (possibly) nonuniform intrinsic values.  show that, as an approximation to optimal iterative pricing, single pricing works fairly ll for many interesting cases, such as forests, Erd\u0151s\u2013Renyi networks and Barabasi\u2013Albert networks, although its worst-case performance can be arbitrarily bad in general networks."}]