Supply Chain Service Quality Improvement by E-marketplace Automation
E-marketplaces have become an essential part of e-commerce. In our research, a decentralized agent-based e-marketplace platform was devised. Although there are significant agent-based supply chain models in the literature, measuring quality performance using agents is still a subject of investigation. In order to improve overall supply chain service quality by allowing companies' agents to evaluate the service quality of their partners through the history of their transactions, this article proposes a service quality agent model. The model is designed using MCDM tools to suit different approaches to supply chain management. Consequently, since more informed procurement decisions are taking place continuously and autonomously at each node of a supply chain, supply chain service quality is being improved along the whole supply chain. At the end, the service quality valuation model of the supply chain is empirically evaluated.
 Zhang W, Reimann M. Towards a multi-objective performance assessment and optimization model of a two-echelon supply chain using SCOR metrics. Central European Journal of Operations Research. 2014;22(4): 591-622.
 Niraj R, Gupta M, Narasimhan C. Customer profitability in a supply chain. Journal of Marketing. 2001;65(3): 1-16.
 Ketchen DJ, et al. Best value supply chains: A key competitive weapon for the 21st century. Business Horizons. 2008;51(3): 235-243.
 Seth N, Deshmukh S, Vrat P. A framework for measurement of quality of service in supply chains. Supply Chain Management: An International Journal. 2006;11(1): 82-94.
 Chow G, Heaver TD, Henriksson LE. Logistics performance: definition and measurement. International Journal of Physical Distribution & Logistics Management. 1994;24(1): 17-28.
 Sahay B, et al. A conceptual model for quality of service in the supply chain. International Journal of Physical Distribution & Logistics Management. 2006;36(7): 547-575.
 Lyons A, et al. Supply Chain Performance Measurement. In: Customer-Driven Supply Chains. Springer London; 2012. p. 133-148.
 Mes M, van der Heijden M, Schuur P. Interaction between intelligent agent strategies for real-time transportation planning. Central European Journal of Operations Research. 2013;21(2): 337-358.
 Gumzej R, Gajšek B. Introducing quality of service criteria into supply chain management for excellence. In: Luo Z. Technological Solutions for Modern Logistics and Supply Chain Management; 2013. p. 70-86.
 Gumzej R, Sukjit P, Unger H. Modelling Overlay Networks for Autonomous Supply Chain Systems. Logistics & Sustainable Transport. 2012;3(2).
 Rashad W, Gumzej R. The Information Technology in Supply Chain Integration: Case Study of Reda Chemicals with Elemica. International Journal of Supply Chain Management. 2014;3(1).
 Kim K, Paulson BC Jr, Petrie CJ Jr. Agent based electronic markets for project supply chain coordination. Proceedings of the AAAI-00 Workshop on Knowledge-Based Electronic Markets, USA, 1999.
 Pal K, Karakostas B. A multi agent-based service framework for supply chain management. Procedia Computer Science. 2014;32: 53-60.
 Evangelista P, Mogre R, Perego A, Raspagliesi A, Sweeney E. A survey based analysis of IT adoption and 3PLs' performance. Supply Chain Management: An International Journal. 2012;17(2): 172-186.
 Kovalchuk Y. A Multi-agent decision support system for supply chain management. PhD thesis. University of Essex; 2009.
 Rady HA. Multi-agent system for negotiation in a collaborative supply chain management. International Journal of Video & Image Processing and Network Security. 2011;11(5).
 Bearzotti LA, Salomone E, Chiotti OJ. An autonomous multi-agent approach to supply chain event management. International Journal of Production Economics. 2012;135(1): 468-478.
 Ameri F, McArthur C. A multi-agent system for autonomous supply chain configuration. The International Journal of Advanced Manufacturing Technology. 2013;66(5-8): 1097-1112.
 Wang G, Wong T, Wang X. An ontology based approach to organize multi-agent assisted supply chain negotiations. Computers & Industrial Engineering. 2013;65(1): 2-15.
 Hernández JE, et al. Collaborative planning in multi-tier supply chains supported by a negotiation-based mechanism and multi-agent system. Group Decision and Negotiation. 2014;23(2): 235-269.
 Sitek P, Nielsen IE, Wikarek J. A hybrid multi-agent approach to the solving supply chain problems. Procedia Computer Science. 2014;35: 1557-1566.
 Domínguez R, Cannella S, Framinan JM. SCOPE: A Multi-Agent system tool for supply chain network analysis. EUROCON 2015-International Conference on Computer as a Tool, IEEE. IEEE; 2015.
 Dominguez R, et al. Using multi-agent systems to explore information sharing in arborescent supply chain networks. Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM). IEEE; 2013.
 Fu J, Fu Y. An adaptive multi-agent system for cost collaborative management in supply chains. Engineering Applications of Artificial Intelligence. 2015;44: 91-100.
 Kumari S, et al. A multi-agent architecture for outsourcing SMEs manufacturing supply chain. Robotics and Computer-Integrated Manufacturing. 2015;36: 36-44.
 Gumzej R, Čišić D. Decentralized Agent-based Electronic Marketplace Supply Chain Ecosystem. Scientific Journal of Maritime Research. 2018;32: 21-27.
 Román Gallego JÁ, Rodríguez González S. Improvement in the distribution of services in multi-agent systems with SCODA. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal. 2015;4(3): 31-46.
 Gnanasambandam S-N. Performance modeling and resource allocation for adaptive agent-based systems. PhD thesis. The Pennsylvania State University; 2007.
 Saaty TL. Relative Measurement and its Generalization in Decision Making: Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors – The Analytic Hierarchy/Network Process. Review of the Royal Academy of Exact, Physical and Natural Sciences, Series A: Mathematics (RACSAM). 2008;102(2): 251-318. Available from: doi:10.1007/bf03191825 [Accessed 22 Dec 2008].
 Weyl EG. A price theory of multisided platforms. The American Economic Review. 2010;100(4): 1642-1672.
 Signature of a digital cooperation between CMA CGM and Alibaba OneTouch. Available from: https://www.cma-cgm.com/news/1496/signature-of-a-digital-cooperation-between-cma-cgm-and-alibaba-onetouch [Accessed on March 2018].
 Alibaba Is Teaming Up with This Shipping Giant. Available from: http://fortune.com/2017/01/04/alibabamaersk-shipping-partnership-onetouch/ [Accessed on March 2018].
 Giannakis M, Louis M. A multi-agent based framework for supply chain risk management. Journal of Purchasing and Supply Management. 2011;17(1): 23-31.
 Bellifemine FL, Caire G, Greenwood D. Developing multi-agent systems with JADE. Vol. 7. John Wiley & Sons; 2007.
 Russell S, Norvig P. Artificial Intelligence: A modern approach. Englewood Cliffs: Prentice-Hall; 1995.
 Fensel D. Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce. Berlin, Heidelberg: Springer; 2001. p. 11-18.
 Bellifemine F, Poggi A, Rimassa G. Developing multiagent systems with a FIPA-compliant agent framework. Software-Practice and Experience. 2001;31(2): 103-128.
 Subramanian H. Decentralized Blockchain-based Electronic Marketplaces. Communications of the ACM. 2018;61(1): 78-84.
 Saaty TL, Kirti P. Group Decision Making: Drawing out and Reconciling Differences. Pittsburgh, Pennsylvania: RWS Publications; 2007.
Copyright (c) 2019 Tanja Poletan Jugović, Roman Gumzej, Dragan Čišić
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).