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Approximation algorithms for pricing with negative network externalities
Cao, Zhigang1; Chen, Xujin1; Hu, Xiaodong1; Wang, Changjun2
2017-02-01
Source PublicationJOURNAL OF COMBINATORIAL OPTIMIZATION
ISSN1382-6905
Volume33Issue:2Pages:681-712
AbstractWe 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. We 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, we prove that it is NP-hard to find an optimal iterative pricing, even for unweighted tree networks with uniform intrinsic values. Complementary to the hardness result, we design a 2-approximation algorithm for general weighted networks with (possibly) nonuniform intrinsic values. We show that, as an approximation to optimal iterative pricing, single pricing works fairly well for many interesting cases, such as forests, ErdAs-R,nyi networks and Barabasi-Albert networks, although its worst-case performance can be arbitrarily bad in general networks.
KeywordPricing Approximation algorithms NP-hardness Social networks Random networks Negative externalities
DOI10.1007/s10878-015-9988-1
Language英语
Funding ProjectNNSF of China[11531014] ; NNSF of China[11222109] ; NNSF of China[11471326] ; CAS Program for Cross & Cooperative Team of Science & Technology Innovation
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Interdisciplinary Applications ; Mathematics, Applied
WOS IDWOS:000394241000019
PublisherSPRINGER
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24706
Collection应用数学研究所
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Beijing Univ Technol, Beijing Inst Sci & Engn Comp, Beijing 100124, Peoples R China
Recommended Citation
GB/T 7714
Cao, Zhigang,Chen, Xujin,Hu, Xiaodong,et al. Approximation algorithms for pricing with negative network externalities[J]. JOURNAL OF COMBINATORIAL OPTIMIZATION,2017,33(2):681-712.
APA Cao, Zhigang,Chen, Xujin,Hu, Xiaodong,&Wang, Changjun.(2017).Approximation algorithms for pricing with negative network externalities.JOURNAL OF COMBINATORIAL OPTIMIZATION,33(2),681-712.
MLA Cao, Zhigang,et al."Approximation algorithms for pricing with negative network externalities".JOURNAL OF COMBINATORIAL OPTIMIZATION 33.2(2017):681-712.
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