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Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.

This chapter focuses on network links as knowledge flows and relationships. Knowledge links are defined as channels for communicating and distributing knowledge. The literature on network links is aligned with the literature on knowledge sharing, transfer, exchange, and appropriation. This chapter focuses on the peculiar attributes of knowledge network links. The authors identify the attributes to include a link’s direction, length and distance, strength and durability, concentration and congestion, velocity and impact, meaning and intention, and the coverage and spread. The authors also describe standard configurations of knowledge networks.

This chapter aims to investigate the driving forces in the creation of knowledge and in the process of innovation and the relevance of the governance model with respect to the free market model or the government model in the regulation of the knowledge and innovation networks.

According to a cognitive approach, a conflict is the result of a closer spatial distance between two actors or firms, leading to a contact stimulus and a reciprocal stimulus, which is perceived as a threat for the respective security or identity. This occurs when the two considered parties are characterised by a too large cognitive distance or a too different mindset or culture, which hinders collaboration.

This chapter highlights that the fragmentation of a modern knowledge economy and the pervasive conflicts between various interest groups, conflicts of interests in the roles of the same actors, bottlenecks, rents and income and power disparity in society require a new form of regulation, that is, multi-level governance and new instruments in innovation policies.

The governance or partnership model is based on the principles of negotiation, exchange and consensus, which are different from the principle of authority as in the planning model and from the principle of competition and survival of the fittest as in the free market model. Governance is an approach to the industrial policy that is more suitable to steer or manage a modern capitalist system and the knowledge and innovation networks that characterise this system.

This study deals with the processes of innovation in the medium technology industrial sectors. First, it illustrates the differences between the linear model of innovation and the systemic and cognitive model of knowledge creation. Then, it focuses on the concepts of connectivity, creativity, and speed of change, which characterize the processes of interactive learning in the industrial clusters. Finally, it illustrates a typology of regions, where problems and policy fields are different, and it indicates the guidelines of a governance of interregional knowledge and innovation networks.

In this paper I employ the perspective of embodied cognition to develop a ‘cognitive’ theory of the firm and organisations more in general. An organisation is any form of coordinated behavior, while a firm is a special form of organisation, with a legal identity concerning property rights, liability and employment. A possible misunderstanding of terminology should be eliminated from the start. In this paper, the terms ‘knowledge’ and ‘cognition’ have a wide meaning, going beyond rational calculation. They denote a broad range of mental activity, including proprioception, perception, sense making, categorisation, inference, value judgments, and emotions. Following others, and in line with the perspective of embodied cognition, I see cognition and emotion (such as fear, suspicion), and body and mind, as closely linked (Merleau-Ponty, 1942, 1964; Simon, 1983; Damasio, 1995, 2003; Nussbaum, 2001).

This chapter provides an overview of two generally applicable frameworks relating to the use of technology-enhanced learning – ‘affordances’ and multimedia learning effects. First, the concept of ‘affordances’ as action potentials of technologies is identified as a way to think through technology-enhanced learning design possibilities, so as to help make technology selection decisions. Second, multimedia learning effects including the multimedia effect, the modality effect, the redundancy effect, the split-attention effect, and the personalization effect are presented as a scientific basis for understanding how to create cognitively effective learning experiences using text, images, sound, and video. Both affordances and multimedia learning effects are characterized as ongoing areas of research that are somewhat related, with the successful utilization of each depending on critical application by the designer.

“It is now becoming widely recognised that many of the central unresolved problems in economics turn on questions of knowledge” (Loasby, 1986, p. 41). Nearly twenty years after that was written, it may be appropriate to take a (necessarily selective) look at ideas about human knowledge and to suggest some implications for the practice of economists. The ideas with which we shall begin long predate the observation that I have just recalled; and the delay in recognising their implications indicates how the growth of knowledge is dependent on the formation of appropriate linkages – which of course are not recognised as appropriate until they have been formed. Adam Smith, Alfred Marshall and Friedrich Hayek were all confronted with the uncertain basis of knowledge before they began their study of economics; and what their responses have in common is not only a theoretical focus on the process by which people develop what we call “knowledge” but also a reliance on similar kinds of process, which result in the formation of connections within particular domains. Each author recognises the impossibility of demonstrating that any such process can deliver proven truth; instead each envisages sequences of trial and error within particular contexts, leading to the preservation of what seems to work – until it no longer does, when a new sequence of trial and error begins. In other words, they all offer evolutionary theories, Marshall and Hayek explicitly so, while Smith, directly and indirectly, had a major influence on the development of Darwin’s ideas.