Abstract
Abstract The Internet of Things (IoT) is currently developing fast and its potential as driver of innovative solutions is increasing, pushed by technologies, networks, communication, and computing power, and has the potential to drive the development of technological ecosystems, such as innovation clusters. Innovation clusters are agglomeration of enterprises and research organizations, which cooperate, interact and compete, generating innovation and driving the growth of ecosystems. The narrative around innovation clusters has been developing since many years and policy-makers seek to use such clusters as a policy instrument to support the growth of technology on the one hand and regional and sectoral development on the other hand. This policy paper expands an empirical study on IoT innovation clusters in Europe and places it within the current debate around clusters and innovation clusters to provide evidence-based advice to policy-makers on what may and may not work as public policy measures. The paper highlights the findings of the interaction with several hundred European IoT innovation clusters and points out their points of view on their own creation factors, operational characteristics, and success stories, as well as their expectations in respect to policy interventions for IoT and for clusters. Suggestions for IoT policy-making are provided. The paper has also undertaken an extensive review of up-to date research on innovation cluster creation and performance, thoroughly analyzing the real possibility to define causal relationships between clusters, productivity and economic growth, and business performance, and providing suggestions for policy-makers on the approach to cluster policy.
Highlights
This policy paper combines the findings of an extensive, multimethodology empirical policy study carried out on behalf of the European Commission1 and targeting European Union Internet of Things (EU IoT) innovation clusters, with the most significant outcomes of the current debate around clusters to provide a concrete assessment of ways forward in cluster-related policy-making
We interviewed the managers of four other clusters to gain a better understanding of the research context
Innovation and pilot projects with IoT applications Funding of IoT-related research and development International dialogue (i.e.: joint actions, sharing of best practices) Development of IoT platforms cutting across sectors, industries and the value chains, and investment in physical platforms Public–private partnership building on IoT applications and other incentives of aggregation Technology transfer services Continuous monitoring of the privacy and protection of personal data questions Creation of/support for labs, testing or technological facilities Counselling on intellectual property. Source (IP) law and data ownership Standards mandates including IoT Identification of emerging risks associated with IoT EU governance of IoT
Summary
This policy paper combines the findings of an extensive, multimethodology empirical policy study carried out on behalf of the European Commission and targeting European Union Internet of Things (EU IoT) innovation clusters, with the most significant outcomes of the current debate around clusters to provide a concrete assessment of ways forward in cluster-related policy-making. 2. IoT, Security Challenges, and 5G Connectivity The accelerating development of the IoT is regarded as one of the major breakthroughs in Information and Communication Technologies (ICT) and considered a key enabler for technological solutions for society, citizens, enterprises and governments, and taking advantage of Big Data and Machine Learning techniques (Pang, 2013). IoT, Security Challenges, and 5G Connectivity The accelerating development of the IoT is regarded as one of the major breakthroughs in Information and Communication Technologies (ICT) and considered a key enabler for technological solutions for society, citizens, enterprises and governments, and taking advantage of Big Data and Machine Learning techniques (Pang, 2013) It is defined as “sensors and actuators connected by networks to computing systems,” in principle excluding intentional human input (Manyika et al, 2015). In their discussion, Kaska et al (2019) recommend a graduated approach, as the one taken in some countries, where transparent oversight was guaranteed with through the establishment of a cooperation base
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