An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

Abstract

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.

Keywords

E-marketplace / broker / multi-attributes / matching approach / economic model / objective function

References

[1] Alpár F. Z.. Matchmaking framework for b2b e-marketplaces. Informatica Economica, 2010, 14(4): 164-169.

[2] Badia L., LindströM M., Zander J., Zorzi M.. An economic model for the radio resource management in multimedia wireless systems. Computer Communications, 2004, 27(11): 1056-1064.

[3] Badia L., Merlin S., Zanella A., Zorzi M.. Pricing VoWLAN services through a micro-economic framework. IEEE Wireless Communications, 2006, 13(1): 6-13.

[4] Badidi E.. A broker-based framework for integrated sla-aware saas provisioning. International Journal on Cloud Computing: Services and Architecture (IJCCSA), 2016, 6(2): 1-19.

[5] Easley D., Kleinberg J.. Networks, Crowds, and Markets., 2010.

[6] Fletcher R.. Practical Methods of Optimization, 2013.

[7] Han L., Hong S.H.. In-house transactions in the real estate brokerage industry: matching outcome or strategic promotion?, 2013

[8] Jiang Z.Z., Fan Z.P., Ip W., Chen X.. Fuzzy multi-objective modeling and optimization for one-shot multi-attribute exchanges with indivisible demand. IEEE Transactions on Fuzzy Systems, 2016, 24(3): 708-723.

[9] Jiang Z.Z., Fan Z.P., Tan C.Q., Yuan Y.. A matching approach for one-shot multi-attribute exchanges with incomplete weight information in e-brokerage. International Journal of Innovative Computing, Information and Control, 2011, 7(5): 2623-2636.

[10] Jiang Z.Z., Ip W.H., Lau H.C.W., Fan Z.P.. Multi-objective optimization matching for one-shot multi-attribute exchanges with quantity discounts in e-brokerage. Expert Systems with Applications, 2011, 38(4): 4169-4180.

[11] Jung J.J., Jo G.S.. Brokerage between buyer and seller agents using constraint satisfaction problem models. Decision Support Systems, 2000, 28(4): 293-304.

[12] Ketter W., Collins J., Reddy P., Weerdt M.. The 2012 power trading agent competition, 2012

[13] Kuate R. T., He M., Chli M., Wang H.. An Intelligent broker agent for energy trading: An MDP approach. the Twenty-Third International Joint Conference on Artificial Intelligence, 2013, 234-240: 2013

[14] Le D.T., Zhang M., Ren F.. A broker-based optimal matching approach of buyers and sellers for multi-attribute exchanges in open markets. IEEE International Conference on Systems, 2015 2015

[15] Le D.T., Ren F., Zhang M.. Membership function based matching approach of buyers and sellers through a broker in open e-marketplace. Smart Simulation and Modelling for Complex Systems: Multi-Agent and Complex Systems, 2016, 125-137: 2016

[16] Le D.T., Zhang M., Ren F.. A multi-criteria group based matching approach of buyers and sellers through a broker in open e-marketplaces. the Ninth International Workshop on Agent-based Complex Automated Negotiations (ACAN2016), 2016, 17-23: 2016

[17] Li X., Murata T.. Priority based matchmaking method of buyers and suppliers in b2b e-marketplace using multi-objective optimization. the International MultiConference of Engineers and Computer Scientists, 2009, 1: 2009

[18] Peters M., Ketter W., Saar-Tsechansky M., Collins J.. A reinforcement learning approach to autonomous decision-making in smart electricity markets. Machine Learning, 2013, 92(1): 5-39.

[19] Srivastava N. K., Singh P., Singh S.. Optimal adaptive CSP scheduling on basis of priority of specific service using cloud broker. the 9th International Conference on Industrial and Information Systems, 2014, 1-6: 2014

[20] Standing S., Standing C., Love P.E.. A review of research on e-marketplaces 1997–2008. Decision Support Systems, 2010, 49(1): 41-51.

[21] Tiwari A., Nagaraju A., Mahrishi M.. An optimized scheduling algorithm for cloud broker using adaptive cost model. the IEEE 3rd International Advance Computing Conference (IACC), 2013, 28-33: 2013

[22] Wang X., Zhang M., Ren F., Ito T.. GongBroker: a broker model for power trading in smart grid markets. the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015, 21-24: 2015

[23] Wang X., Zhang M., Ren F.. A hybrid-learning based broker model for strategic power trading in smart grid markets. Knowledge-Based Systems, 2017, 119: 142-151.

[24] Wu L., Garg S.K., Buyya R., Chen C., Versteeg S.. Automated SLA negotiation framework for cloud computing. the 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2013, 235-244: 2013