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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 article’s purpose is to develop The Model for Smart, Self-learning and Adaptive Resilience Building (SARB).

Products and patents of methods and systems analysis was carried out in the fields of BIM application, Smart, Self-learning and Adaptive Resilience Building. Based on other researchers’ findings, The SARB Model was proposed.

Analysis of the literature showed that traditional decisions on the informational modelling do not satisfy all the needs of smart building technologies owing to their static nature. The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life.

The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life. The SARB Model does have some limitations: (1) the processes followed require the collection of much unstructured and semi-structured data from many sources, along with their analyses to support stakeholders in decision-making; (2) stakeholders need to be aware of the broader context of decision-making and (3) the proposal is process-oriented, which can be a disadvantage during the model’s implementation.

Two directions can be identified for the practical implications of the SARB Model. The initial expectation is the widespread installation of SARB Model within real estate and construction organisations. Furthermore, development of the SARB Model will be used to implement the ERASMUS+ project, “Advancing Skill Creation to ENhance Transformation—ASCENT” Project No. 561712-EPP-1-2015-UK-EPPKA2-CBHE-JP.

The practical implications of this paper are valuable.

This chapter establishes the conceptual and analytic framework for the book. It relates not only to much of the existing work in evolutionary and institutional economics, but also to work in cultural science and cultural semiotics domains as well as in media convergence and transmedia studies. The central concept it first deploys is ‘innovation systems’ as applied in national, regional, international and sectoral contexts. It then builds on the general theory of economic evolution by Kurt Dopfer and Jason Potts and reviews the tools this theory provides to carry out a meso-level analysis of industries co-innovating and converging. It then proposes a new concept – ‘cross-innovation’ – to refer to the emergence of new structures and ‘rules’ at the boundaries of existing industries.

The purpose of this paper is to study the introduction of 3D-printing of concrete in the construction sector.

A survey was conducted to collect professional view on ongoing innovations in the construction sector, including 3D-printing. Participants were selected among the members of Norwegian networks for project and construction management research.

The survey highlighted effective leadership, collaboration with partners and industry-academia collaboration as primary enablers of innovation. Few of the respondents to the survey have used 3D-printing technologies.

It is difficult to obtain representative samples in this type of research, including this study. The study can be seen as a snapshot of attitudes in the sector.

3D-printing appear as a potentially interesting technology, especially for unstandardized construction components. Further work is needed to materialise the expectation for technological development in the construction sector.

Most research on 3D-printing has focused on demonstrating technical potential. This study adds a practitioners’ perspective, with a large dose of pragmatism.

This paper aims to provide decision support for precast concrete contractors about both precast concrete supply chain strategies and construction configurations.

This paper proposes a simulation-based optimisation for supply chain and construction (SOSC) during the planning phase of PC building projects. The discrete event simulation is used to capture the characteristics of supply chain and construction processes, and calculate construction objectives under different plans. Particle swarm optimisation is combined with simulation to find optimal supply chain strategies and construction configurations.

The efficiency of SOSC is compared with the parametric simulation approach. Over 70 per cent of time and effort used to simulate and compare alternative plans is saved owing to SOSC.

Building simulation model costs a lot of time and effort. The data requirement of the proposed method is high.

The proposed SOSC approach can provide decision support for PC contractors by optimising supply chain strategies and construction configurations.

This paper has two contributions: one is in providing a decision support tool SOSC to optimise both supply chain strategies and construction configurations, while the other is in building a prototype of SOSC and testing it in a case study.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

The paper aims to investigate the emergence the Hong Kong Building Environmental Assessment Methods (HK BEAM) certification scheme and starts to explore the impact of BEAMs on the building industry and the potential emergence and stabilisation of a green building field.

The research presented draws upon content analysis of all 19 versions of the HK BEAM scheme(s) as well as 94 policy reports. This is complemented by an investigation and collation of the participating companies in 100 HK BEAM certified projects. The theoretical framework of Strategic Action Fields is applied to explore the emergence of a potential green building field.

The findings are tentative, but they point out that a green building field is yet to emerge in Hong Kong.

The research is still ongoing and parts of the analysis are yet to be finalised. Therefore, only tentative conclusions are drawn.

From a practical perspective, the findings point towards a correlation between the memberships in the working committees charged with deciding on the content of the BEAMs and their content.

So far, very little is known about how exactly BEAMs have come into being. Furthermore, their impact on working practices outside of “certified” projects has received little research attention. This research project is an attempt to rectify this.

This chapter analyzes what happens to media use when everyday life is suddenly disrupted, focusing on how the COVID-19 pandemic transformed work, socializing, communication and everyday living. The empirical case is changing media use in Norway during the pandemic, building on a qualitative questionnaire survey conducted in early lockdown, and follow-up interviews eight months later. Expanding on the ideas of destabilization of media repertoires developed in the former chapter, this analysis discusses transforming media repertoires as more digital, as less mobile (but still smartphone-centric) and as essentially social. The chapter further explains new concepts for pandemic media use practices, such as doomscrolling and Zoom fatigue.