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A fuzzy reasoning approach to assess innovation risk in ecosystems

Bibliographic Details
Main Author: Abreu, António
Publication Date: 2018
Other Authors: Martins, José Moleiro, Calado, João Manuel Ferreira
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.21/9280
Summary: Currently, companies to be competitive must achieve high rates of innovation and respond quickly to market needs. According to a number of managers and researches innovation is crucial for companies to stay “alive." Taking into account several reports, the development of co-innovation networks based on a collaborative environment is the best strategy to support innovation projects. However, the absence of mechanisms to detect and even anticipate potential risks of innovation based on a collaborative approach is an obstacle to the proliferation of this way of working. To address this issue, this paper discusses an approach based on fuzzy reasoning for analyzing the level of risk in co-innovation projects. It is discussed how this approach can be applied to co-innovation projects within the contexto of a collaborative ecosystem. At last, it is discussed the benefits, and challenges found on experimental results from a Portuguese co-innovation network.
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spelling A fuzzy reasoning approach to assess innovation risk in ecosystemsRisk analysisFuzzy logicFuzzy reasoningCoinnovationCollaborative ecossytemsAnálise de riscoCurrently, companies to be competitive must achieve high rates of innovation and respond quickly to market needs. According to a number of managers and researches innovation is crucial for companies to stay “alive." Taking into account several reports, the development of co-innovation networks based on a collaborative environment is the best strategy to support innovation projects. However, the absence of mechanisms to detect and even anticipate potential risks of innovation based on a collaborative approach is an obstacle to the proliferation of this way of working. To address this issue, this paper discusses an approach based on fuzzy reasoning for analyzing the level of risk in co-innovation projects. It is discussed how this approach can be applied to co-innovation projects within the contexto of a collaborative ecosystem. At last, it is discussed the benefits, and challenges found on experimental results from a Portuguese co-innovation network.De GruyterRCIPLAbreu, AntónioMartins, José MoleiroCalado, João Manuel Ferreira2019-01-08T10:57:25Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/9280eng2391-5439https://doi.org/10.1515/eng-2018-0067info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-12T07:52:14Zoai:repositorio.ipl.pt:10400.21/9280Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:51:55.773040Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A fuzzy reasoning approach to assess innovation risk in ecosystems
title A fuzzy reasoning approach to assess innovation risk in ecosystems
spellingShingle A fuzzy reasoning approach to assess innovation risk in ecosystems
Abreu, António
Risk analysis
Fuzzy logic
Fuzzy reasoning
Coinnovation
Collaborative ecossytems
Análise de risco
title_short A fuzzy reasoning approach to assess innovation risk in ecosystems
title_full A fuzzy reasoning approach to assess innovation risk in ecosystems
title_fullStr A fuzzy reasoning approach to assess innovation risk in ecosystems
title_full_unstemmed A fuzzy reasoning approach to assess innovation risk in ecosystems
title_sort A fuzzy reasoning approach to assess innovation risk in ecosystems
author Abreu, António
author_facet Abreu, António
Martins, José Moleiro
Calado, João Manuel Ferreira
author_role author
author2 Martins, José Moleiro
Calado, João Manuel Ferreira
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Abreu, António
Martins, José Moleiro
Calado, João Manuel Ferreira
dc.subject.por.fl_str_mv Risk analysis
Fuzzy logic
Fuzzy reasoning
Coinnovation
Collaborative ecossytems
Análise de risco
topic Risk analysis
Fuzzy logic
Fuzzy reasoning
Coinnovation
Collaborative ecossytems
Análise de risco
description Currently, companies to be competitive must achieve high rates of innovation and respond quickly to market needs. According to a number of managers and researches innovation is crucial for companies to stay “alive." Taking into account several reports, the development of co-innovation networks based on a collaborative environment is the best strategy to support innovation projects. However, the absence of mechanisms to detect and even anticipate potential risks of innovation based on a collaborative approach is an obstacle to the proliferation of this way of working. To address this issue, this paper discusses an approach based on fuzzy reasoning for analyzing the level of risk in co-innovation projects. It is discussed how this approach can be applied to co-innovation projects within the contexto of a collaborative ecosystem. At last, it is discussed the benefits, and challenges found on experimental results from a Portuguese co-innovation network.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2019-01-08T10:57:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/9280
url http://hdl.handle.net/10400.21/9280
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2391-5439
https://doi.org/10.1515/eng-2018-0067
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv De Gruyter
publisher.none.fl_str_mv De Gruyter
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