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Nowadays—and due to an increasingly competitive world—organizations need to collaborate in an open innovation context to be efficient and effective by achieving high levels of innovation with their products and services. However, the existing resources—as well as the innovation achieved from the diversity of partners involved—brings challenges to the management; in particularly with risk management. To fulfill such needs, risk management frameworks have been created to support managers, on preventing threats with systems development, although without properly account the influence of each system component, on the entire system, as well as the subjectivity within human perception. To account for these issues, a framework supported by fuzzy logic is presented in this work, to evaluate the risk level on system development in open innovation environment. The approach robustness is assessed by using a case study, where the challenges and benefits found are discussed.

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Currently, sustainability is considered a priority by society, with the household appliances being one of the economic sectors involved in achieving sustainability. However, the existence of several issues (e.g., energy and water consumption, reliability, initial cost, and illuminance, among others) together with the diversity of brands and models on the market, make the consumer’s decisions regarding sustainable options difficult, according to their concerns and related to each sustainability dimension (economic, environmental, and social). By combining evolutionary algorithms (EA) with multicriteria techniques, it is possible to achieve sustainable solutions for the consumer based on their requirements. In this paper, a method is presented to support the consumer by obtaining a set of sustainable household appliances on the market that suit their preferences, concerns, and needs. By using a case study to apply the approach developed here, a set of sustainable appliances from the market is obtained, where several benefits are achieved (e.g., energy and water consumption savings, avoidance of CO2 emissions) during the lifecycle of each appliance, chosen from the appliance’s industry.

Virtual enterprises (VE), is well-known to make use of open innovation to achieve competitiveness, through innovation on product development. However, its limited resources, combined with the innovation resulted from the diversity of partners involved, rises some challenges to its management, specifically regarded with risk management. To fulfill these requirements, risk management's models, have been conceived to assist managers, on preventing threats with such risks, although without adequately incorporate the influence of each process domain on product development, as well as the subjectivity regarding human perception. In order to consider these issues, this work presents an approach, supported by fuzzy logic, to assess the risk's level on product development in an open innovation context. The model robustness, will be assessed through a case study, where it will be also discussed the benefits and challenges found.

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Although collaborative networks (CN) are widespread in academia and have come to be even more used in corporations all over the world, they still face several challenges on behalf of the new product development (NPD) context, especially in regard to the selection of the CN’s right partner. This becomes even more evident when it comes to promoting sustainable development goals within a CN’s activities, by selecting the right partners with a wide consensus from a CN’s management board, avoiding, therefore, the subjectivity around managers’ perception of a CN’s partner selection. Therefore, this work attempts to answer this problem, by presenting a soft-computing-based framework, to support the managers’ board on partner search and selection. The method presented here is further assessed by using a case study, based on the development of a green product, where, according to the obtained results, it is demonstrated that the proposed approach is extremely effective for partner selection, by assessing and prioritizing each candidate involved. The most suitable candidate that fulfills the CN’s requirements is then selected to be integrated as a future partner.

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