Scholars' Mine
Missouri S&T
Research Repository
Curtis Laws Wilson Library
400 W. 14th Street
Rolla, MO 65409-0060
scholarsmine@mst.edu
| Title: | Strategic product planning using neural networks |
| Author (s): | Trichinapally, Dhananjay Sankaran, Aravind Allada, Venkata |
| Department/Lab Affiliations: | Intelligent Systems Center |
| Keywords: | neural networks product design product development product planning strategic planning |
| Issue Date: | 2003 |
| Publisher: | American Society of Mechanical Engineers ASME |
| Citation: | Trichinapally, Dhananjay, Aravind Sankaran, and Venkata Allada. "Strategic product planning using neural networks." Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE 2003), Vol. 13, 2003: 857-863. |
| Abstract: | Strategic product planning is a challenging entrepreneurial task. It supplies input to product design and development and creates a business plan for profitability. One of the strategic product planning considerations is whether to develop a single product line or a product family consisting of several product variants. However at present, there are not many quantitative tools to determine whether to pursue the single product line option or a product family option. This paper proposes a four-force model that describes the factors influencing the product planning decision. Using the four-force framework, a neural network model has been developed to help strategic product planning. |
| Type: | Article - Conference proceedings text |
| In Title: | Intelligent Engineering Systems Through Artificial Neural Networks |
| Copyright Notice: | 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. Pre-print: author cannot archive; Post-print: author cannot archive; FULL COPYRIGHT INFORMATION: |
| Publisher URL: | |
| Link to this page: |
| title | Strategic product planning using neural networks |
| contributor.author | Trichinapally, Dhananjay |
| contributor.author | Sankaran, Aravind |
| contributor.author | Allada, Venkata |
| contributor.deptlab | Intelligent Systems Center |
| subject | neural networks |
| subject | product design |
| subject | product development |
| subject | product planning |
| subject | strategic planning |
| date.issued | 2003 |
| publisher | American Society of Mechanical Engineers ASME |
| identifier.citation | Trichinapally, Dhananjay, Aravind Sankaran, and Venkata Allada. "Strategic product planning using neural networks." Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE 2003), Vol. 13, 2003: 857-863. |
| identifier.pub.URI | |
| description.abstract | Strategic product planning is a challenging entrepreneurial task. It supplies input to product design and development and creates a business plan for profitability. One of the strategic product planning considerations is whether to develop a single product line or a product family consisting of several product variants. However at present, there are not many quantitative tools to determine whether to pursue the single product line option or a product family option. This paper proposes a four-force model that describes the factors influencing the product planning decision. Using the four-force framework, a neural network model has been developed to help strategic product planning. |
| type | Article - Conference proceedings |
| type.DCMIType | text |
| relation.isPartOf | Intelligent Engineering Systems Through Artificial Neural Networks |
| rights | 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. |
| rights | Pre-print: author cannot archive; Post-print: author cannot archive; |
| rights.URI | |
| rights.URI | |
| identifier.persist.URI | |
| date.available | 2009-04-21T20:35:19Z |