基于蚁群相似权算法的网络团购信用评价模型研究<sup>*</sup>

doi:10.11925/infotech.1003-3513.2016.01.07

现代图书情报技术

2016, Vol. 32

Issue (1): 40-47 https://doi.org/10.11925/infotech.1003-3513.2016.01.07

研究论文

本期目录 | 过刊浏览 | 高级检索

基于蚁群相似权算法的网络团购信用评价模型研究^*

张亚明(

),李娜,赵培卿

燕山大学经济管理学院秦皇岛 066004

Study on Credit Evaluation Model of Online Group-buying by Using ACO and Similarity Weight Algorithm

Yaming Zhang(

),Na Li,Peiqing Zhao

School of Economy and Management, Yanshan University, Qinhuangdao 066004, China

摘要
参考文献
相关文章
Metrics

全文: PDF (548 KB) HTML ( 42 )
输出: BibTeX | EndNote (RIS)

摘要 【目的】帮助网络团购消费者快速找到优质商家, 商家可以有效地提高自身信用水平。【方法】利用相似权测度法对指标体系分配权重, 得出的综合指标变量作为蚁群算法参数, 建立基于蚁群相似权的信用评价模型。【结果】实证研究表明, 该模型能够快速有效地求出节约时间成本和货币成本的最短路径, 找出优质商家。【局限】 未考虑退款和刷单等特殊交易对网络团购信用评价的影响; 对蚁群算法的其他参数未进行具体研究, 直接采用前人研究结论。【结论】有助于商家提高信用、提升团体满意度, 为进一步研究网络团购问题提供参考。

	服务

	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	张亚明
	李娜
	赵培卿

关键词 ：网络团购, 信用评价, 相似权, 蚁群算法

Abstract：

[Objective] To help online group-buying consumers find high quality merchants quickly and help merchants improve their credit efficiently. [Methods] Use similarity weight to distribute the weights of index system, consider the gotten composite indicator variables as the parameters of ant colony algorithm, and establish the credit evaluation model based on ACO and Similarity Weight Algorithm. [Results] Empirical results show that the model can effectively find out the shortest path to save time and money cost, obtain high quality merchant. [Limitations] Not considering the impact of special trade on online group-buying credit evaluation, such as refund and fictitious trading; directly using previous research conclusion of other parameters in ACO. [Conclusions] The results can help merchants improve credit, promote satisfaction of consumer group, and provide the references for further research on online group-buying problems.

Key words： Online group-buying Credit evaluation Similarity weight Ant Colony Optimization(ACO)

出版日期: 2016-02-04

基金资助:*本文系国家自然科学基金项目“云环境用户多兴趣图谱的移动商务关联性推荐模型及算法研究”(项目编号:71271186)、教育部人文社会科学研究规划基金项目“云环境下基于用户兴趣图谱的网络社区营销推荐机理研究”(项目编号:12YJA630191)和河北省教育厅自然科学基金青年项目“云环境多源异构情境信息融合的移动商务推荐模型与方法研究”(项目编号:QN2015248)的研究成果之一

引用本文:

张亚明,李娜,赵培卿. 基于蚁群相似权算法的网络团购信用评价模型研究^*[J]. 现代图书情报技术, 2016, 32(1): 40-47.
Yaming Zhang,Na Li,Peiqing Zhao. Study on Credit Evaluation Model of Online Group-buying by Using ACO and Similarity Weight Algorithm. New Technology of Library and Information Service, 2016, 32(1): 40-47.

链接本文:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.01.07 或 https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2016/V32/I1/40

[1]	中国电子商务研究中心. 2014年度中国电子商务用户体验与投诉检测报告[R/OL]. [2015-03-13]. .
[1]	(China E-Business Research Center. The 2014 Report of China E-Business Market Data Monitoring [R/OL]. [2015-03-13].
[2]	Steve W.Retailer Credit Cards: A Competitive Threat[J]. International Journal of Bank Marketing, 1990, 8(4): 3-9.
[3]	Altman E I, Saunders A.Credit Risk Measurement: Developments over the Last 20 Years[J]. Journal of Banking & Finance, 1997, 21(11-12): 1721-1742.
[4]	Ohlson J A.Financial Ratios and the Probabilistic Prediction of Bankruptcy[J]. Journal of Accounting Research, 1997, 18(1): 109-131.
[5]	李梅, 马国建. 中小企业信用评价指标体系的构建[J]. 统计与决策, 2005(12): 63-64.
[5]	(Li Mei, Ma Guojian.Construction of the Credit Evaluation Index System for Minor Enterprise[J]. Statistics & Decision, 2005(12): 63-64. )
[6]	Yuan D, Lu T, Yang X, et al.A Theory Analysis and Model Research on E-Commerce Credit Risk Management[C]. In: Proceedings of the 2010 International Conference on E-Business and E-Government, Guangzhou, China. 2010.
[7]	Adnan K.Credit Risk Evaluation Using Neural Networks: Emotional Versus Conventional[J]. Applied Soft Computing, 2011, 11(8): 5477-5484.
[8]	Ioannis E T.Firm Credit Risk Evaluation: A Series Two-stage DEA Modeling Framework[J]. Annals of Operations Research, 2014, 233(1): 483-500.
[9]	王春峰, 赵欣, 韩冬. 基于改进蚁群算法的商业银行信用风险评估方法[J]. 天津大学学报: 社会科学版, 2005, 7(2): 81-85.
[9]	(Wang Chunfeng, Zhao Xin, Han Dong.A Model on Modified Ants Algorithm for Credit Risk Assessment in Commercial Banks[J]. Journal of Tianjin University: Social Sciences, 2005, 7(2): 81-85.)
[10]	张玉洁, 孟祥武. 利用蚁群算法求解电信客户初始信用评分问题[J]. 北京邮电大学学报, 2010, 33(1): 124-128.
[10]	(Zhang Yujie, Meng Xiangwu.Initial Credit Scoring for Telecom Customers Using Ant Colony Algorithm[J]. Journal of Beijing University of Posts and Telecommunications, 2010, 33(1): 124-128.)
[11]	杨韵. C2C交易中的动态信用评价模型[J]. 情报科学, 2010, 28(4): 563-566.
[11]	(Yang Yun.A Dynamic Trust Evaluation Model on C2C Marketplaces[J]. Information Science, 2010, 28(4): 563-566.)
[12]	张洪祥, 毛志忠. 基于多维时间序列的灰色模糊信用评价研究[J]. 管理科学学报, 2011, 14(1): 28-37.
[12]	(Zhang Hongxiang, Mao Zhizhong.Research of Multidimensional Time Series Credit Evaluation Based on Gray-fuzz Analysis Model[J]. Journal of Management Sciences in China, 2011, 14(1): 28-37.)
[13]	张发明. 一种融合SOM与K-means算法的动态信用评价方法及应用[J]. 运筹与管理, 2014, 23(6): 186-192.
[13]	(Zhang Faming.Research on a Dynamic Credit Evaluation Method Integrating SOM and K-means Clustering Algorithm[J]. Operations Research and Management Science, 2014, 23(6): 186-192.)
[14]	周国强, 王雪青, 刘锐. 一种基于改进云模型的信用评价方法[J]. 系统工程, 2013, 31(4): 60-66.
[14]	(Zhou Guoqiang, Wang Xueqing, Liu Rui.A Credit Evaluation Method Based on the Modified Cloud Model[J]. Systems Engineering, 2013, 31(4): 60-66.)
[15]	郭伟, 仝克宁, 邵宏宇, 等. 基于RS与AHP的中小企业云制造模式下多服务主体信用评价体系构建[J]. 计算机集成制造系统, 2013, 19(9): 2340-2347.
[15]	(Guo Wei, Tong Kening, Shao Hongyu, et al.Small and Medium-sized Enterprises Multi-service Agent Credit Rating System Construction Under Cloud Manufacturing Mode Based on RS and AHP[J]. Computer Integrated Manufacturing Systems, 2013, 19(9): 2340-2347.)
[16]	Webster F E, Wind Y.A General Model for Understanding Organizational Buying Behavior[J]. Journal of Marketing, 1972, 36(2): 12-19.
[17]	Lee J S.An Innovative Electronic Group-buying System for Mobile Commerce[J]. Electronic Commerce Research and Applications, 2013, 12(1): 1-13.
[18]	Marcelo V N.How to Reduce Perceived Risk When Buying Online: The Interactions Between Intangibility, Product Knowledge, Brand Familiarity, Privacy and Security Concerns[J]. Journal of Retailing and Consumer Services, 2014, 21(4): 619-629.
[19]	罗晓娜, 史彦虎, 朱先奇. 基于博弈的网络团购供应链信任协调机制研究[J]. 数学的实践与认识, 2014, 44(22): 47-54.
[19]	(Luo Xiaona, Shi Yanhu, Zhu Xianqi.Research on the Trust Coordination Mechanism in Supply Chain of Network Group Purchase Based on Game[J]. Mathematics in Practice and Theory, 2014, 44(22): 47-54.)
[20]	管晓永, 陈红, 刘润然, 等. 基于公众可获得信息的团购网信用特性研究[J]. 科研管理, 2013, 34(5): 144-152.
[20]	(Guan Xiaoyong, Chen Hong, Liu Runran, et al.The Credit Behavior Characteristics of Online Group Buying Business Based on the Information Available to the Public[J]. Science Research Management, 2013, 34(5): 144-152.)
[21]	GB/T26842-2011, 基于电子商务活动的交易主体企业信用评价指标与等级表示规范[S]. 北京: 中国标准出版社, 2011.
[21]	(GB/T26842-2011, Transaction Subject Based upon Activities of Electronic Commerce-Specification for Enterprise Credit Assessment Index and Credit Grade [S]. Beijing: China Standard Press, 2011.)
[22]	张成, 吴映梅, 魏强. 基于关系式交易的网络团购模式及其信用评价体系分析[J]. 商业时代, 2012(20): 43-44.
[22]	(Zhang Cheng, Wu Yingmei, Wei Qiang.Analysis of Online Shopping Pattern and Its Credit Evaluation System Based on E-Commerce Activities[J]. Commercial Time, 2012(20): 43-44.)
[23]	赵培卿. C2B模式下网络团购信用评价研究[D]. 秦皇岛: 燕山大学, 2010.
[23]	(Zhao Peiqing.Research on the Credit Evaluation of Group Shopping Traders Based on C2B Model [D]. Qinhungdao: Yanshan University, 2010.)

[1]	谷俊, 朱紫阳. 基于聚类算法的本体层次关系获取研究[J]. 现代图书情报技术, 2011, 27(12): 46-51.

Viewed

Full text

Abstract

Cited

Shared

Discussed