Envisioning the emergence of a new technological paradigm involves several issues, spanning from strategic assessments and managerial actions to design decisions and technology related choices. The present study focuses on this latter perspective, by proposing a model that estimates the success probability of innovative products as a function of design actions. The focus on the design decisions that underlie radical shifts is not conflicting, but complementary to the more traditional perspectives. The model is based on a database of past successful and unsuccessful innovations, which are used to build a logistic regression model, whose evidences can assist both designers and managers. The former get advice on how specific design choices affect product perception, while the latter are supported in addressing resources to the most promising projects.
A Decision Support Model to Assess Technological Paradigms / CASAGRANDE-SERETTI, Alessandro; Montagna, Francesca; Cascini, Gaetano. - In: INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT. - ISSN 0267-5730. - 80:1/2(2019), pp. 61-84. [10.1504/IJTM.2019.10021436]
A Decision Support Model to Assess Technological Paradigms
Alessandro Casagrande-Seretti;Francesca Montagna;
2019
Abstract
Envisioning the emergence of a new technological paradigm involves several issues, spanning from strategic assessments and managerial actions to design decisions and technology related choices. The present study focuses on this latter perspective, by proposing a model that estimates the success probability of innovative products as a function of design actions. The focus on the design decisions that underlie radical shifts is not conflicting, but complementary to the more traditional perspectives. The model is based on a database of past successful and unsuccessful innovations, which are used to build a logistic regression model, whose evidences can assist both designers and managers. The former get advice on how specific design choices affect product perception, while the latter are supported in addressing resources to the most promising projects.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2720764
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