Multiple regression models for electronic product success prediction
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...
| _version_ | 1826110419495813120 |
|---|---|
| author | Lo, Frank Cheong Wah Foo, Say Wei Bauly, John A. |
| author2 | IEEE International Conference on Management of Innovation and Technology (1st : 2000 : Singapore) |
| author_facet | IEEE International Conference on Management of Innovation and Technology (1st : 2000 : Singapore) Lo, Frank Cheong Wah Foo, Say Wei Bauly, John A. |
| author_sort | Lo, Frank Cheong Wah |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T02:34:07Z |
| format | Conference Paper |
| id | ntu-10356/91312 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:34:07Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/913122020-03-07T13:24:46Z Multiple regression models for electronic product success prediction Lo, Frank Cheong Wah Foo, Say Wei Bauly, John A. IEEE International Conference on Management of Innovation and Technology (1st : 2000 : Singapore) 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. Accepted version 2009-04-28T03:25:29Z 2019-12-06T18:03:25Z 2009-04-28T03:25:29Z 2019-12-06T18:03:25Z 2000 2000 Conference Paper 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. https://hdl.handle.net/10356/91312 http://hdl.handle.net/10220/4587 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 10.1109/ICMIT.2000.917374 en © 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. 4 p. application/pdf |
| spellingShingle | Lo, Frank Cheong Wah Foo, Say Wei Bauly, John A. Multiple regression models for electronic product success prediction |
| title | Multiple regression models for electronic product success prediction |
| title_full | Multiple regression models for electronic product success prediction |
| title_fullStr | Multiple regression models for electronic product success prediction |
| title_full_unstemmed | Multiple regression models for electronic product success prediction |
| title_short | Multiple regression models for electronic product success prediction |
| title_sort | multiple regression models for electronic product success prediction |
| url | https://hdl.handle.net/10356/91312 http://hdl.handle.net/10220/4587 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 |
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