Business-to-Consumer Mobile Agent-Based Internet Commerce System (MAGICS)
We present MAGICS, a mobile agent-based system for supporting business-to-consumer electronic commerce (e-commerce) or mobile commerce (m-commerce) applications. To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless applicati...
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Veröffentlicht in: | IEEE transactions on human-machine systems 2007-11, Vol.37 (6), p.1174-1189 |
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container_title | IEEE transactions on human-machine systems |
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creator | Hui Chen Lam, P.P.Y. Chan, H.C.B. Dillon, T.S. Cao Jiannong Lee, R.S.T. |
description | We present MAGICS, a mobile agent-based system for supporting business-to-consumer electronic commerce (e-commerce) or mobile commerce (m-commerce) applications. To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless application protocol (WAP) terminal. Having obtained the requirements, mobile agents are generated to carry out tasks for the consumers including getting offers from merchants, evaluating offers, and even completing purchases. In the case of mobile commerce, consumers can generate a mobile agent to conduct a search and evaluation in the digital marketspace before making a purchase in the physical marketplace. To make it possible to choose an offer that best satisfies the consumer's requirement(s), we present a mathematical model for evaluating multiple decision factors. To test the basic functions of the mobile agent-based Internet commerce system (MAGICS), we have built a prototype system. To minimize the average cost of a product (including the cost of sending agents), we have also developed an analytical model that can determine how many agents should be sent to compare prices. Four different price distributions and some real price information are analyzed based on the model. The analysis provides valuable insights into the design of mobile agent-based shopping applications for m-commerce, in particular, and for e-commerce, in general. |
doi_str_mv | 10.1109/TSMCC.2007.900653 |
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To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless application protocol (WAP) terminal. Having obtained the requirements, mobile agents are generated to carry out tasks for the consumers including getting offers from merchants, evaluating offers, and even completing purchases. In the case of mobile commerce, consumers can generate a mobile agent to conduct a search and evaluation in the digital marketspace before making a purchase in the physical marketplace. To make it possible to choose an offer that best satisfies the consumer's requirement(s), we present a mathematical model for evaluating multiple decision factors. To test the basic functions of the mobile agent-based Internet commerce system (MAGICS), we have built a prototype system. To minimize the average cost of a product (including the cost of sending agents), we have also developed an analytical model that can determine how many agents should be sent to compare prices. Four different price distributions and some real price information are analyzed based on the model. The analysis provides valuable insights into the design of mobile agent-based shopping applications for m-commerce, in particular, and for e-commerce, in general.</description><identifier>ISSN: 1094-6977</identifier><identifier>ISSN: 2168-2291</identifier><identifier>EISSN: 1558-2442</identifier><identifier>EISSN: 2168-2305</identifier><identifier>DOI: 10.1109/TSMCC.2007.900653</identifier><identifier>CODEN: ITCRFH</identifier><language>eng</language><publisher>New-York, NY: IEEE</publisher><subject>Agents (artificial intelligence) ; Applied sciences ; Business ; Commerce ; Computer science; control theory; systems ; Computer systems and distributed systems. 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To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless application protocol (WAP) terminal. Having obtained the requirements, mobile agents are generated to carry out tasks for the consumers including getting offers from merchants, evaluating offers, and even completing purchases. In the case of mobile commerce, consumers can generate a mobile agent to conduct a search and evaluation in the digital marketspace before making a purchase in the physical marketplace. To make it possible to choose an offer that best satisfies the consumer's requirement(s), we present a mathematical model for evaluating multiple decision factors. To test the basic functions of the mobile agent-based Internet commerce system (MAGICS), we have built a prototype system. To minimize the average cost of a product (including the cost of sending agents), we have also developed an analytical model that can determine how many agents should be sent to compare prices. Four different price distributions and some real price information are analyzed based on the model. The analysis provides valuable insights into the design of mobile agent-based shopping applications for m-commerce, in particular, and for e-commerce, in general.</description><subject>Agents (artificial intelligence)</subject><subject>Applied sciences</subject><subject>Business</subject><subject>Commerce</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Consumers</subject><subject>Cost analysis</subject><subject>Cost engineering</subject><subject>Costs</subject><subject>E-commerce</subject><subject>Electronic commerce</subject><subject>Exact sciences and technology</subject><subject>Internet</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>Mobile agents</subject><subject>Mobile commerce</subject><subject>Prototypes</subject><subject>Software</subject><subject>Studies</subject><subject>System testing</subject><subject>Web server</subject><subject>Wireless application protocol</subject><issn>1094-6977</issn><issn>2168-2291</issn><issn>1558-2442</issn><issn>2168-2305</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkEtLw0AQx4MoWKsfQLwEQaiH1H1lH8c2-Ci0eGg9L5vtRFLyqLvJod_erSkKnnaW-c2fmV8U3WI0xRipp816lWVTgpCYKoR4Ss-iEU5TmRDGyHmokWIJV0JcRlfe7xDCjCk6ihbz3pcNeJ90bZK1je9rcPGqzcsK4tknNF0yNx628aLpwDXQxVlbB8RCvD74Dup4spq9LrL143V0UZjKw83pHUcfL8-b7C1Zvof-bJlYqmSXCJobzGwKlhHGacqITYVQdssVGE5FUbCCAjXGyJQQQbigCOe2wFvBVB5-42gy5O5d-9WD73RdegtVZRpoe68xopiG-4gM6P0_dNf2rgnbackZkRLLI4QHyLrWeweF3ruyNu4QkvTRrf5xq49u9eA2zDycgo23piqcaWzp_wYVloghFLi7gSsB4LfNKAsqOP0GvVt_gQ</recordid><startdate>20071101</startdate><enddate>20071101</enddate><creator>Hui Chen</creator><creator>Lam, P.P.Y.</creator><creator>Chan, H.C.B.</creator><creator>Dillon, T.S.</creator><creator>Cao Jiannong</creator><creator>Lee, R.S.T.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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User interface</topic><topic>Consumers</topic><topic>Cost analysis</topic><topic>Cost engineering</topic><topic>Costs</topic><topic>E-commerce</topic><topic>Electronic commerce</topic><topic>Exact sciences and technology</topic><topic>Internet</topic><topic>Mathematical model</topic><topic>Mathematical models</topic><topic>Mobile agents</topic><topic>Mobile commerce</topic><topic>Prototypes</topic><topic>Software</topic><topic>Studies</topic><topic>System testing</topic><topic>Web server</topic><topic>Wireless application protocol</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hui Chen</creatorcontrib><creatorcontrib>Lam, P.P.Y.</creatorcontrib><creatorcontrib>Chan, H.C.B.</creatorcontrib><creatorcontrib>Dillon, T.S.</creatorcontrib><creatorcontrib>Cao Jiannong</creatorcontrib><creatorcontrib>Lee, R.S.T.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on human-machine systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hui Chen</au><au>Lam, P.P.Y.</au><au>Chan, H.C.B.</au><au>Dillon, T.S.</au><au>Cao Jiannong</au><au>Lee, R.S.T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Business-to-Consumer Mobile Agent-Based Internet Commerce System (MAGICS)</atitle><jtitle>IEEE transactions on human-machine systems</jtitle><stitle>TSMCC</stitle><date>2007-11-01</date><risdate>2007</risdate><volume>37</volume><issue>6</issue><spage>1174</spage><epage>1189</epage><pages>1174-1189</pages><issn>1094-6977</issn><issn>2168-2291</issn><eissn>1558-2442</eissn><eissn>2168-2305</eissn><coden>ITCRFH</coden><abstract>We present MAGICS, a mobile agent-based system for supporting business-to-consumer electronic commerce (e-commerce) or mobile commerce (m-commerce) applications. To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless application protocol (WAP) terminal. Having obtained the requirements, mobile agents are generated to carry out tasks for the consumers including getting offers from merchants, evaluating offers, and even completing purchases. In the case of mobile commerce, consumers can generate a mobile agent to conduct a search and evaluation in the digital marketspace before making a purchase in the physical marketplace. To make it possible to choose an offer that best satisfies the consumer's requirement(s), we present a mathematical model for evaluating multiple decision factors. To test the basic functions of the mobile agent-based Internet commerce system (MAGICS), we have built a prototype system. To minimize the average cost of a product (including the cost of sending agents), we have also developed an analytical model that can determine how many agents should be sent to compare prices. Four different price distributions and some real price information are analyzed based on the model. The analysis provides valuable insights into the design of mobile agent-based shopping applications for m-commerce, in particular, and for e-commerce, in general.</abstract><cop>New-York, NY</cop><pub>IEEE</pub><doi>10.1109/TSMCC.2007.900653</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Agents (artificial intelligence) Applied sciences Business Commerce Computer science control theory systems Computer systems and distributed systems. User interface Consumers Cost analysis Cost engineering Costs E-commerce Electronic commerce Exact sciences and technology Internet Mathematical model Mathematical models Mobile agents Mobile commerce Prototypes Software Studies System testing Web server Wireless application protocol |
title | Business-to-Consumer Mobile Agent-Based Internet Commerce System (MAGICS) |
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