Nowadays, enterprises in global markets must achieve high levels of performance and competitiveness to stay "alive". According to several authors and as frequently mentioned by reports of practical case studies, one of the most relevant sources of competitive advantage is the innovation capacity. The identification and quantification of the existing or potential innovation risks in a collaborative environment, is an important element for the wide adoption of the innovation ecosystem paradigm. However, models to understand the innovation risks in a collaborative environment are lacking. To address this issue, this paper introduces an approach based on a qualitative assessment, including a quantitative basis, whose development was supported by fuzzy logic for analyzing the level of risk in co-innovation projects. Finally, based on experimental results from a Portuguese collaborative network, a discussion about the benefits and challenges found are discussed.
Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident. (C)
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