Research on Pricing and Revenue Coordination Strategy of Online Group Buying

doi:10.12005/orms.2017.0169

Operations Research and Management Science ›› 2017, Vol. 26 ›› Issue (7): 117-124.DOI: 10.12005/orms.2017.0169

• Application Research • Previous Articles Next Articles

Research on Pricing and Revenue Coordination Strategy of Online Group Buying

WU Cui-lian¹, WANG Qian^1,2,3, TIAN Xin^1,2,3, CAI Li⁴

1.School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;
2.Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China;
3.Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China;
4.Shanghai HEADING Information Engineering Co., Ltd., Shanghai 201112, China

Received:2014-11-10 Online:2017-07-25

网络团购的定价与收益协调策略研究

吴翠莲¹, 王谦^{1, 2, 3}, 田歆^{1, 2, 3}, 蔡笠⁴

1.中国科学院大学经济与管理学院,北京 100190;
2.中国科学院虚拟经济与数据科学研究中心,北京 100190;
3.中国科学院大数据挖掘与知识管理重点实验室,北京 100190;
4:上海海鼎信息工程股份有限公司,上海 201112

作者简介:吴翠莲,硕士研究生;王谦,副教授,硕士生导师,博士;田歆,副研究员,硕士生导师,博士。
基金资助:
国家自然科学基金资助项目(71371178,71390331);中国科学院大学校长基金资助项目(Y35102LN00);中国科学院大数据挖掘与知识管理重点实验室开放课题,山东省自主创新及成果转化专项(2014ZZCX03302)

Abstract

Abstract: How to achieve a win-win situation between the group buying website and participating merchant is a big challenge in our country. A game model of pricing and revenue sharing is built according to the characteristics of online grouping buying in China. Then, the corresponding coordination strategy is given using the Nash negotiation model. Finally, a numerical example is designed to analyze the influence of the change of the main parameters to price and revenue. The results show that online group buying is better for the website and participating merchant when the size of sensitive market is larger, and the advertising effect is bigger or the unit cost is smaller.

Key words: online group buying, pricing, revenue sharing, coordination

摘要： 如何实现团购网站和团购参与商家之间的双赢是我国网络团购目前面临的一大挑战性问题。结合我国网络团购的特点,构建团购网站和商家之间定价与收益分配的博弈模型,针对博弈结果运用纳什谈判模型给出协调策略。最后,通过数值算例分析主要参数的变化对价格与收益的影响。结果表明,敏感市场的规模和团购网站的广告效应越大、商品的单位成本越小、开展网络团购对商家和团购网站越有利。

关键词: 网络团购, 定价, 收益分成, 协调

CLC Number:

C931.1

WU Cui-lian, WANG Qian, TIAN Xin, CAI Li. Research on Pricing and Revenue Coordination Strategy of Online Group Buying[J]. Operations Research and Management Science, 2017, 26(7): 117-124.

吴翠莲, 王谦, 田歆, 蔡笠. 网络团购的定价与收益协调策略研究[J]. 运筹与管理, 2017, 26(7): 117-124.

References

[1] 中国电子商务研究中心.2013年度中国网络团购市场数据检测报告[R].2014.
[2] Dholakia, Utpal M. how businesses fare with daily deals: a multi-site analysis of groupon, livingsocial, opentable, travelzoo, and buy with me promotions[R].working paper, June 13, 2011, Available at SSRN: http://ssrn.com/abstract=1863466.
[3] Kauffman R J, Wang B. New buyers’ arrival under dynamic pricing market microstructure: the case of group-buying discounts on the Internet[J]. Journal of Management Information Systems, 2001, 18(2): 157-188.
[4] Anand K S, Aron R. Group buying on the web: a comparison of price-discovery mechanisms[J]. Management Science, 2003, 49(11): 1546-1562.
[5] Tai C L, Hong J Y, Chang C M, Chen L C. Determinants of consumer's intention to participate in group buying[J]. Social and Behavioral Sciences, 2012, 57: 396-403.
[6] Shiau W L, Luo M M. Factors affecting online group buying intention and satisfaction: a social exchange theory perspective[J]. Computers in Human Behavior, 2012, 28: 2431-2444.
[7] 陈宇,柏杨.网络团购模式下消费者行为意向研究[J].商业时代,2012,17:37-38.
[8] 吴佳欣,陈慧.群体因素对网络团购消费者从众行为影响的实证研究[R].中国科技论文在线,2012.http://www.paper.edu.cn/releasepaper/content/201212-991.
[9] Cheng H H, Huang S W. Exploring antecedents and consequence of online group-buying intention: an extended perspective on theory of planned behavior[J]. International Journal of Information Management, 2013, 33(1): 185-198.
[10] Liang X Y, Ma L J, et al. The information aspect of the group-buying mechanism[J]. European Journal of Operational Research, 2014, 234(1): 331-340.
[11] 陈剑,陈熙龙,宋西平.逢低买入拍卖中的共谋研究[J].系统工程理论与实践,2002,22(10):94-104.
[12] Chen R R, Li C, Zhang R Q. Group buying mechanisms under quantity discounts[R]. Working Paper, University of California at Davis, CA, 2010.
[13] Edelman B S, Jaffe S D, Kominers. To Groupon or not to groupon: the profitability of deep discounts[R]. Harvard Business School NOM Unit Working Paper No. 11-063, 2011.
[14] Jing X Q, Xie J H. Group buying: a new mechanism for selling through social interactions[J]. Management Science, 2011, 57(8): 1354-1372.
[15] 白莹,李明杰,袁冲,邓舒,胡春.基于双边市场的网络团购平台定价模型研究[J].北京邮电大学学报,2012,14(2):52-57.
[16] 晏妮娜,黄小原,刘兵.电子市场环境中供应链双源渠道主从对策模型[J].中国管理科学,2007,15(3):98-102.

Research on Pricing and Revenue Coordination Strategy of Online Group Buying

网络团购的定价与收益协调策略研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

[1]	SHI Yuan, WANG Xin-hua, GAO Hong-wei. Research on Equilibrium Pricing and Market Performance of Firms in Three-tier Supply Chain with Cross-shareholding [J]. Operations Research and Management Science, 2021, 30(9): 145-151.
[2]	WANG Dao-ping, SONG Yu-qing. Study on Retailer's Two-Stage Dynamic Pricing Considering Consumer Behavior Transformation [J]. Operations Research and Management Science, 2021, 30(9): 152-157.
[3]	LIU Gui-fang, XU Wei-jun, HUANG Jing-long, ZHAO Qi. European Vulnerable Option Pricing Considering Corporate Information Disclosure Emotion [J]. Operations Research and Management Science, 2021, 30(9): 164-171.
[4]	JIN Liang, XIONG Jing, XU Lu. Pricing and Market Eentry of the Green Product: Based on the Perspective of Power Structures [J]. Operations Research and Management Science, 2021, 30(9): 225-231.
[5]	YANG Hong-lin, DOU Tian-dan, GAO Ming-yun. Ordering Decision in a Capital-constrained Supply Chain with RFID Applications [J]. Operations Research and Management Science, 2021, 30(8): 93-98.
[6]	GUO Jin-sen, YANG Ping, ZHOU Yong-wu, YANG Yu-zhen. Dual Channel Supply Chain Coordination Strategy Based on Uniform Pricing and Promotion [J]. Operations Research and Management Science, 2021, 30(8): 99-107.
[7]	YANG Hua-long, YU Ze-tao, XIN Yu-chen. Inventory Routing and Dynamic Regional Pricing with Horizontal Collaboration Strategy [J]. Operations Research and Management Science, 2021, 30(8): 153-161.
[8]	QU Chen-rui, ZENG Qing-cheng, CHEN Chao, ZHANG Qian. Model of Connecting Service Pricing under Revenue Sharing Strategies [J]. Operations Research and Management Science, 2021, 30(8): 162-168.
[9]	LUO Ming, LI Zeng-lu. Study of In-store Referral Strategies of E-retailers with Suppler Discriminatory Pricing [J]. Operations Research and Management Science, 2021, 30(8): 175-180.
[10]	TAN Chun-ping, QIN Xue-zhi, WANG Wen-hua, WANG Lin. Study on Solution Approach for Firm's Financial Distress via Equity Refinancing and Strategic Debt Service [J]. Operations Research and Management Science, 2021, 30(8): 181-189.
[11]	LI Xiao-yan, LI Feng. Dynamic Optimization and Coordination of Low Carbon Supply Chain Based on Double Differential Game in Competitive Environment [J]. Operations Research and Management Science, 2021, 30(7): 89-94.
[12]	CAO Bing-bing, YOU Tian-hui, LIU Chun-yi, WU Xue-yan. Stackelberg Pricing Strategy in Dyadic Supply Chain Considering the Deposit and Loan of Bank Based on the Payment of Cash on Delivery [J]. Operations Research and Management Science, 2021, 30(7): 146-153.
[13]	LEI Ming, CHEN Shu-xin, YE Wu-yi. A Comparative Study of Option Pricing Models: Based on Bilateral Gamma Distribution Model and B-S Model [J]. Operations Research and Management Science, 2021, 30(7): 190-194.
[14]	YAO Feng-min, YAN Ying-luo, LIU shan, TENG Chun-xian. Recycling and Pricing Decisions for Closed-loop Supply Chain Considering Corporate Social Responsibility Investment under Government's Subsidy [J]. Operations Research and Management Science, 2021, 30(6): 69-76.
[15]	LI Yan-feng, GONG Gui-lin. Study on Tourist Bus Pricing Based on Tourist Age Characteristics [J]. Operations Research and Management Science, 2021, 30(6): 159-165.