Firms must adapt to a business environment in constant flux. Economic and political factors and the constant interruption of new technologies force firms and organizations to change and to adapt, so that they are not left behind. Over recent years, the development of disruptive innovations has completely revolutionized past scenarios. These innovations break with what is already established and firms from various sectors face no choice other than to incorporate them into their project management portfolios, so as to ensure survival and business sustainability. Using MIVES methodology as its foundation, a business sustainability management model is presented in this paper for the management of disruptive innovation projects that a firm may wish to develop within a given sector. The management model is designed to facilitate disruptive innovation project management for firms within technological-industrial sectors, by assessing the sustainability of the project. The model is applied to two firms, one from the machine-tooling sector and another from the construction sector. Finally, a sensitivity analysis was performed, the results of which verified the validity and the stability of the proposed model.

Grinding is a critical technology in the manufacturing of high added-value precision parts, accounting for approximately 20–25% of all machining costs in the industrialized world. It is a commonly used process in the finishing of parts in numerous key industrial sectors such as transport (including the aeronautical, automotive and railway industries), and energy or biomedical industries. As in the case of many other manufacturing technologies, grinding relies heavily on the experience and knowledge of the operatives. For this reason, considerable efforts have been devoted to generating a systematic and sustainable approach that reduces and eventually eliminates costly trial-and-error strategies. The main contribution of this work is that, for the first time, a complete digital twin (DT) for the grinding industry is presented. The required flow of information between numerical simulations, advanced mechanical testing and industrial practice has been defined, thus producing a virtual mirror of the real process. The structure of the DT comprises four layers, which integrate: (1) scientific knowledge of the process (advanced process modeling and numerical simulation); (2) characterization of materials through specialized mechanical testing; (3) advanced sensing techniques, to provide feedback for process models; and (4) knowledge integration in a configurable open-source industrial tool. To this end, intensive collaboration between all the involved agents (from university to industry) is essential. One of the most remarkable results is the development of new and more realistic models for predicting wheel wear, which currently can only be known in industry through costly trial-and-error strategies. Also, current work is focused on the development of an intelligent grinding wheel, which will provide on-line information about process variables such as temperature and forces. This is a critical issue in the advance towards a zero-defect grinding process.

Research and development organisations (RTOs) are at the heart of innovation systems. They help to connect innovation system actors to foster industrial innovation. Due to this intermediary role, they act as paradigmatic open innovation (OI) actors. In this context, RTOs need to balance their knowledge stocks and flows, while assuring their own innovation capabilities and positively impacting the innovation system they influence. Thus, RTOs need to develop collaboration approaches that support their own performance while increasing their capabilities and not threatening their competitive advantages derived from their knowledge stock. In this study we extend the OI research to research organisations analysing their OI approach and the impact on its own performance, developing a new framework for OI study in RTOs using a partial least squares structural equation modelling (PLS-SEM) approach. The research, based on a sample of Spanish RTOs, arises two substantive conclusions. First, an increased number of collaboration partners (collaboration breadth) and the use of a variety of OI practices have a strong impact on RTOs’ overall performance (scientific, transference, and economic results). Second, RTOs need to foster their aperture and promote an active management to benefit from collaborating partners, whereas managers should pay special attention to questions related to the protection and management of intellectual property when promoting the use of different OI practices. Both results also emphasise the importance of managing firms’ knowledge flows in the implementation of OI in RTOs.

The central role of R&D centers in the advancement of technology within industrial enterprises is undeniable and clearly affects their strategies, their competitiveness and their business sustainability. R&D centers assume responsibility for technology recognition, collection, acquisition, development and transition. Among their activities, the efficient choice of emerging technologies in the Technology Management Process is becoming a real challenge. In such heterogeneous scenarios, Multiple Criteria Decision Making (MCDM) models are commonly proposed as an appropriate decision-making approach. Multiple research works address the selection of particular technologies in industrial applications, but very few references can be found related to research institutions, and R&D centers in particular. Therefore, a decision-making model is provided in this study following the MIVES multi criteria method for the assessment of one or more technologies. The model is then applied to two case studies related to the selection process of new technologies at a Spanish R&D Center specialized in manufacturing.