消费者小世界社会网络下双寡头产品定价策略

doi:10.16182/j.issn1004731x.joss.201706003

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (6): 1174-1185.doi: 10.16182/j.issn1004731x.joss.201706003

消费者小世界社会网络下双寡头产品定价策略

李锋¹, 魏莹²

1.华南理工大学工商管理学院,广东广州 510640;
2.暨南大学企业管理系,广东广州 510632

收稿日期:2015-07-12 修回日期:2016-01-03 出版日期:2017-06-08 发布日期:2020-06-04
通讯作者: 魏莹(1977-)，女，江西萍乡，博士，副教授，研究方向为运营管理、库存管理。
作者简介:李锋(1975-),男,河北邢台,博士,副教授,研究方向为运营管理。
基金资助:
国家自然科学基金(71171085, 71572070),广东省自然科学基金(2014A030313262)

Impact of ‘Small World' Social Network of Consumers on Pricing Decision in Duopoly Market

Li Feng¹, Wei Ying²

1. School of Business Administration, South China University of Technology, Guangzhou 510640, China;
2. Department of Business Administration, Jinan University, Guangzhou 510632, China

Received:2015-07-12 Revised:2016-01-03 Online:2017-06-08 Published:2020-06-04

摘要/Abstract

摘要： 鉴于现实世界中消费者的购买决策普遍受到“朋友”的影响,在Hotelling模型基础上,研究当消费者之间的社会关系网络满足“小世界”特性时,双寡头竞争下的产品定价策略。通过建立研究对象的多智能体模型,仿真分析了需求方的小世界网络对供应方的产品定价问题的影响。仿真结果表明市场中受他人影响的消费者数量越多,消费者受他人影响的程度越大,即消费者非完全理性程度增大,供应方能够通过抬高产品价格而获利。受到小世界网络结构的影响,其中一个供应方具有明显的价格和利润优势。并且,供应方的促销策略也因此有较大的差异。

关键词: Hotelling模型, 小世界网络, 消费者行为, 销售努力, 多智能体建模仿真

Abstract: Noticing the influences of friends on consumers purchasing decisions, the impact of ‘small world' social network on price competition in a duopoly hotelling model was studied. A multi-agent based modeling approach was proposed to represent the consumers' decisions, which related to their connected friends in a social network, as well as the firms' pricing decisions. Simulation results reveal that the ‘small world' social network has a significant impact on the competing firms' pricing decisions. In specific, with the increasing number of consumers who are impacted by their friends, or the increasing likelihood of following friends' decisions, consumers then behave less rational. Both firms benefit from such bounded rationality and gain profits by raising their selling prices. In addition, one firm may benefit more than the other due to the network structure of the ‘small world'. As a result, policies of sales effort investment are also different for the two competitors.

Key words: hotelling model, small world network, consumer behavior, sale effort, multi-agent modeling and simulation

中图分类号:

TP391.9

李锋, 魏莹. 消费者小世界社会网络下双寡头产品定价策略[J]. 系统仿真学报, 2017, 29(6): 1174-1185.

Li Feng, Wei Ying. Impact of ‘Small World' Social Network of Consumers on Pricing Decision in Duopoly Market[J]. Journal of System Simulation, 2017, 29(6): 1174-1185.

参考文献

[1] Kwak H, Lee C, Park H, et al.What is Twitter, a Social Network or a News Media?[C]// Proceedings of the 19th International Conference on World Wide Web. USA: ACM, 2010: 591-600.
[2] Yang D H, Yu G.Static analysis and exponential random graph modeling for micro-blog network[J]. Journal of Information Science (S0165-5515), 2014, 40(1): 3-14.
[3] 苑卫国, 刘云, 程军军. 微博网络中用户特征量和增长率分布的研究[J]. 计算机学报, 2014, 37(4): 767-778.
(Yuan WG, Liu Y, Cheng J J.Research on the user characteristics and growth rates distribution in microblog[J]. Chinese Journal of Computers, 2014, 37(4): 767-778.)
[4] Yan Q, Wu L, Zheng L.Social network based microblog user behavior analysis[J]. Physica A (S0378-4371), 2013, 392(7): 1712-1723.
[5] Java A, Song X, Finin T, et al.Why We Twitter: Understanding Microblogging Usage and Communities[C]// Proceedings of International Conference on Knowledge Discovery and Data Mining. USA: ACM, 2007: 56-65.
[6] Fu F, Liu L, Wang L.Empirical analysis of online social networks in the age of Web 2.0[J]. Physica A,(S0378-4371), 2008, 387(2/3): 675-684.
[7] Lerman K, Ghosh R.Information Contagion: an Empirical Study of the Spread of News on Digg and Twitter Social Networks[C]// Proceedings of the 4th International AAAI Conference on Weblogs and Social Media. USA: AAAI, 2010: 90-97.
[8] Li F, Du T C.Listen to me- evaluating the influence of micro-blog[J]. Decision Support Systems (S0167-9236), 2014, 62: 119-130.
[9] Du Y, Gao C, Hu Y, et al.A new method of identifying influential nodes in complex networks based on TOPSIS[J]. Physica A (S0378-4371), 2014, 399: 57-69.
[10] Katona Z, Zubcsek P P, Sarvary M.Network effects and personal influences: the diffusion of an online social network[J]. Journal of Marketing Research (S0022-2437), 2011, 48(3): 425-443.
[11] Fan W, Yeung K H, Wong K Y.Assembly effect of groups in online social networks[J]. Physica A (S0378-4371), 2013, 392(5): 1090-1099.
[12] Yan S, Tang S, Pei S, et al.The spreading of opposite opinions on online social networks with authoritative nodes[J]. Physica A (S0378-4371), 2013, 392(17): 3846-3855.
[13] Kurmyshev E, Juarez H A, Gonzalez-Silva R A. Dynamics of bounded confidence opinion in heterogeneous social networks: concord against partial antagonism[J]. Physica A (S0378-4371), 2011, 390(16): 2945-2955.
[14] 李林, 孙军华. 基于社会网络冲突信息传播的群体特征[J]. 系统工程理论与实践, 2014, 34(1): 207-214.
(Li L, Sun J.Population characteristics based on conflict information spreading on social network[J]. Systems Engineering-Theory & Practice, 2014, 34(1): 207-214.)
[15] Kumar V, Bhaskaran V, Mirchandani R, et al.Creating a measurable social media marketing strategy: increasing the value and ROI of intangibles and tangibles for Hokey Pokey[J]. Marketing Science (S0732-2399), 2013, 32(2): 194-212.
[16] Han B, Yang L.Social networks, information acquisition, and asset prices[J]. Management Science (S0732-2399), 2013, 59(6): 1444-1457.
[17] Albuquerque P, Pavlidis P, Chatow U, et al.Evaluating promotional activities in an online two-sided market of user-generated content[J]. Marketing Science (S0732-2399), 2012, 31(3): 406-432.
[18] Ho T H, Li S, Park S E, et al.Customer influence value and purchase acceleration in new product diffusion[J]. Marketing Science (S0732-2399), 2012, 31(2): 236-256.
[19] Li F, Wei Y.An Intelligent Agent Simulation Model to Evaluate Herd Behavior and Sales Effort in a Duopoly Market [C]// Proceedings of 10th International Conference on Intelligent Computing. Germany: Springer International Publishing, 2014: 456-465.
[20] 金淳, 董秋, 吕苗. 基于Agent的网站促销下消费者行为仿真研究[J]. 系统工程理论与实践, 2014, 34(4): 845-853.
(Jin C, Dong Q, Lv M.Agent-based simulation for consumer behavior under website promotion[J]. Systems Engineering- Theory & Practice, 2014, 34(4): 845-853.)
[21] Wei Y, Li F.Impact of Heterogeneous Consumers on Pricing Decisions under Dual-Channel Competition[J]. Mathematical Problems in Engineering (S1024-123X), 2015: 1-9. DOI: 10.1155/2015/584084.
[22] 李锋, 魏莹. 消费者理性程度对供应链定价影响的仿真研究[J]. 系统仿真学报, 2015, 27(12): 2898-2907.
(Li F, Wei Y.Simulation research on impact of consumer bounded rationality on optimal pricing strategy in supply chain[J]. Journal of System Simulation (S1004-731X) 2015, 27(12): 2898-2907.)
[23] Watts D J, Strogatz S H.Collective Dynamics of ‘Small-World' Networks[J]. Nature (S0028-0836), 1998, 393: 440-442.
[24] Moreno Y, Nekovee M, Pacheco A F.Dynamic of Rumor Spreading in Complex Networks[J]. Physical Review E (S1550-2376), 2004, 69(6): 066130.

消费者小世界社会网络下双寡头产品定价策略

Impact of ‘Small World' Social Network of Consumers on Pricing Decision in Duopoly Market

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 6

编辑推荐

Metrics

本文评价

[1]	李锋, 魏莹. 复杂网络对羊群效应现象影响的仿真研究[J]. 系统仿真学报, 2021, 33(3): 539-553.
[2]	郭庆军, 闫竑宇, 李博森. 地铁施工中隐患的传播及控制分析[J]. 系统仿真学报, 2020, 32(8): 1617-1625.
[3]	李锋, 魏莹. 小世界网络下病毒式信息传播的仿真分析[J]. 系统仿真学报, 2019, 31(9): 1790-1801.
[4]	李锋, 魏莹. 小世界网络环境下谣言传播对产品定价的影响[J]. 系统仿真学报, 2018, 30(2): 533-542.
[5]	董崇杰. 全局分配策略在级联故障中的建模与研究[J]. 系统仿真学报, 2018, 30(11): 4172-4179.
[6]	王世龙. 小世界网络中的合作行为传染仿真研究[J]. 系统仿真学报, 2017, 29(10): 2316-2322.