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Multiple regression models for electronic product success prediction

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Multiple regression models for electronic product success prediction

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dc.contributor.author Lo, Frank Cheong Wah
dc.contributor.author Foo, Say Wei
dc.contributor.author Bauly, John A.
dc.date.accessioned 2009-04-28T03:25:29Z
dc.date.available 2009-04-28T03:25:29Z
dc.date.copyright 2000
dc.date.issued 2009-04-28T03:25:29Z
dc.identifier.citation Lo, F.C.W., Foo, S.W. & Bauly, J.A. (2000). Multiple regression models for electronic product success prediction. IEEE International Conference on Management of Innovation and Technology 2000: (pp. 419-422). Singapore: Singapore Polytechnic.
dc.identifier.uri http://hdl.handle.net/10220/4587
dc.description.abstract As the cost of failure in new product development is very high, product developers are looking for good product success/failure prediction models. The general direction of search is towards Knowledge Based Systems (KBS) that incorporate the wisdom of experienced developers and extracts from data of past projects. In this paper, results of investigation using multiple regression models are reported. It is found that 90% accuracy may be achieved in success/failure prediction of electronic product development using a multiple regression model based on six critical factors.
dc.format.extent 4 p.
dc.language.iso en
dc.rights © 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
dc.title Multiple regression models for electronic product success prediction
dc.type Conference Paper
dc.contributor.conference IEEE International Conference on Management of Innovation and Technology (1st : 2000 : Singapore)
dc.identifier.openurl http://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:EVII&id=doi:10.1109/ICMIT.2000.917374&genre=&isbn=0 7803 6652 2&issn=&date=2000&volume=&issue=&spage=419&epage=22&aulast=Lo&aufirst=%20F%20C%20%2DW&auinit=&title=Proceedings%20of%20the%202000%20IEEE%20International%20Conference%20on%20Management%20of%20Innovation%20and%20Technology%2E%20ICMIT%202000%2E%20%60Management%20in%20the%2021st%20Century%27%20%28Cat%2E%20No%2E00EX457%29&atitle=Multiple%20regression%20models%20for%20electronic%20product%20success%20prediction
dc.identifier.doi http://dx.doi.org/10.1109/ICMIT.2000.917374
dc.description.version Accepted version

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