Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/206132 
Authors: 
Year of Publication: 
2018
Citation: 
[Journal:] Cogent Business & Management [ISSN:] 2331-1975 [Volume:] 5 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2018
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
This research intends to aid product managers at early stages (before detailed design stage) of product development to identify and thus benchmark the minimal risk prone design concept for further development and commercialization. As requirements pertaining to relevant functional divisions within the enterprise are needed to be included at the project initiation stage of design process, it can be easily ascertained that pertinent techno-commercial risks be included for development of the predictive framework. Bayesian network methodology has been deployed to draw the relationships amongst various risk parameters corresponding to different functional divisions. The devised framework has been validated and tested using a real-life case from construction and mining equipment industry. The key benefit arising out of my evolved methodology is that product development agencies within manufacturers would be able to iteratively converge upon the design concepts representing moderate to lower risk as far as effective execution of downstream organizational processes such as production, sourcing, distribution etc. is concerned.
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Creative Commons License: 
cc-by Logo
Document Type: 
Article

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