Abstract
With the rapid development of e-commerce , the automatic transaction has been a potential demand of enterprises. Concentrating on B2C e-commerce scenario, this paper designs a human-computer negotiation model and algorithm, through which an agent can negotiate with a human using natural language. To validate the model and algorithm, we conducted a between-group experiment based on a prototype system comparing the negotiation effect between the groups with and without arguments. The experimental results show that adding arguments into price negotiation can significantly increase the success rate of the human-computer negotiation. Moreover, there is a significant positive impact on the buyer’s subjective feelings on system using, as well as the seller agent’s economic utility, so that it can finally help both sides to reach a win-win situation in the negotiation. The contribution of our study can apply to B2C e-commerce platforms for improving the performance of their intelligent customer service agent. Our study is also meaningful for helping the two parties to increase their trading efficiency and decrease their trading cost.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
eMarketer, Worldwide Retail Ecommerce Sales Will Reach $1.915 Trillion This Year. 2016. https://www.emarketer.com/Article/Worldwide-Retail-Ecommerce-Sales-Will-Reach-1915-Trillion-This-Year/1014369
V. Zeng et al., China Online Retail Forecast, 2014 to 2019. Forrester Research (2015)
Y. Li, D. Wei, R. Cao, Negotiation support system for e-commerce. J. Manag. Sci. 4(6), 13–17 (2001)
C. Team, China Double 11 Shopping Festival Sales Statistics 2017. China Internet Watch 2017 [cited 2018; https://www.chinainternetwatch.com/22791/double-11-2017/
Y.P. Yang, S. Singhal, Y.J. Xu, Alternate strategies for a win-win seeking agent in agent-human negotiations. J. Manag. Inf. Syst. 29(3), 223–255 (2012)
M. Cao et al., Automated negotiation for e-commerce decision making: a goal deliberated agent architecture for multi-strategy selection. Decis. Support Syst. 73, 1–14 (2015)
R. Lin, S. Kraus, Can automated agents proficiently negotiate with humans? Commun. ACM 53(1), 78–88 (2010)
P. Chen, T. Gao, Y. Li, Research on agent-oriented Markov multi-issue automated negotiation model. J. Manag. Eng. 28(3), 203–208 (2014)
H. Li, N. Cui, X. Xu, Negotiation mode of dual-channel supply chain wholesale price based on bargaining power. J. Manag. Eng. 29(4), 124–132 (2015)
I. Rahwan et al., Argumentation-based negotiation. Knowl. Eng. Rev. 18(04), 343–375 (2003)
A. Carrera, C.A. Iglesias, A systematic review of argumentation techniques for multi-agent systems research. Artif. Intell. Rev. 44(4), 509–535 (2015)
S.L. Huang, F.R. Lin, The design and evaluation of an intelligent sales agent for online persuasion and negotiation. Electron. Commer. Res. Appl. 6(3), 285–296 (2007)
A. El-Sisi, H. Mousa, Argumentation-based negotiation in multi-agent system. Int. Arab J. e-Technol. 3(3), 155–162 (2014)
A. Monteserin, A. Amandi, Agents that learn how to generate arguments from other agents. New Gener. Comput. 32(1), 31–58 (2014)
A. Beigi, N. Mozayani, A new dialogue strategy in multi-agent systems. J. Intell. Fuzzy Syst. 27(2), 641–653 (2014)
O. Marey et al., Decision making under subjective uncertainty in argumentation-based agent negotiation. J. Ambient Intell. Humaniz. Comput. 6(3), 307–323 (2015)
A. Monteserin, A. Amandi, A reinforcement learning approach to improve the argument selection effectiveness in argumentation-based negotiation. Expert Syst. Appl. 40(6), 2182–2188 (2013)
H. Sun, W. Jinghua, T. Huang et al., A concession model based on classification of agent persuasion and its implementation. Oper. Res. Manag. 23(6), 252–256 (2014)
Acknowledgments
This work was supported by the China Scholarship Council (Grant# 201706315032), and the Natural Science Foundation of China (Grant# 71671154), and the Fundamental Research Funds for the Central Universities of China (Grant# 20720161052).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Cao, M., Jing, G. (2020). Study on an Argumentation-Based Negotiation in Human-Computer Negotiation Service. In: Yang, H., Qiu, R., Chen, W. (eds) Smart Service Systems, Operations Management, and Analytics. INFORMS-CSS 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-30967-1_23
Download citation
DOI: https://doi.org/10.1007/978-3-030-30967-1_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30966-4
Online ISBN: 978-3-030-30967-1
eBook Packages: Business and ManagementBusiness and Management (R0)