Technology Infusion Analysis‐Based Research and Development Project Portfolio Valuation.
Saved in:
| Title: | Technology Infusion Analysis‐Based Research and Development Project Portfolio Valuation. |
|---|---|
| Authors: | Jang, Hojin1 (AUTHOR), Suh, Eun Suk2 (AUTHOR) essuh@snu.ac.kr |
| Source: | Systems Engineering. Nov2025, Vol. 28 Issue 6, p675-690. 16p. |
| Subjects: | Cost benefit analysis, Research & development projects, Resource allocation, Computer performance, Technological innovations, Competitive advantage in business, Project evaluation, New product development |
| Abstract: | Technology‐driven companies must invest significant resources in developing new technologies to enhance product performance, reduce costs, and maintain a competitive edge in their markets. However, resource constraints often limit the number of projects these companies can pursue within their research and development (R&D) portfolios. A key responsibility of the chief technology officer and system architect is to identify and prioritize the technologies that will provide the highest value to the company. This selection process requires an objective evaluation of each candidate's technology's costs and benefits, necessitating a standardized methodology for assessing potential engineering design changes, system performance improvements, required investments, and expected returns. To address this need, we are introducing a technology infusion analysis‐based R&D project portfolio valuation process. This approach evaluates the costs and benefits of proposed technologies by analyzing the corresponding engineering design changes and system performance modifications. The effectiveness of this process is demonstrated through a case study on valuing an R&D project portfolio for a toner distribution system in a printing system. [ABSTRACT FROM AUTHOR] |
| Copyright of Systems Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
