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This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

The chapter aims to provide an overview of organisational structures in Research Management and Administration (RMA); in doing so, the chapter moves from explaining main sources of knowledge – broadly on HE Management (HEM) and specifically on RMA – to assessing institutionalisation and maturity level of the profession.

Understanding these forms of knowledge will help readers design research support services and develop a competency/career development plan.

Additionally, the chapter aims to call for individuals and institutions to engage with the varied forms of knowledge associated with different phases of a research project life cycle (RPLC). The goal is to raise individual awareness while helping countries improve their RMA maturity.

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.

This chapter is based on the findings of the empirical material gathered in Finland and Sweden through interviews with education and audiovisual (AV) media actors and policymakers in 2017–2018. The aim of the chapter is to discuss the innovation systems of the education sector and Finland and Sweden in general, compare the sectoral innovation models of the two sectors, and conclude with discussing the resulting challenges for policymakers. Our results show that a new EdTech sector employing the competences of the education, information and communication technology, and AV media sectors has begun to emerge and actors in the both countries have eagerly taken actions to boost its development as a business and export field. We discuss the reasons and consequences of this development.

This chapter focuses on clarifying the cooperation and convergence between tourism and audiovisual (AV) sectors in Hamburg and Riga. In light of increasingly easier and more accessible travel, the tourism sector is a growing trend in most countries and regions. To what extent does this affect cooperation with the AV sector? The chapter gives an overview of different types of cooperation in these regions and brings out the main obstacles for innovation. When describing the innovation systems, focus is put on institutional frameworks in these two regions. We end by arguing that raising the demand for innovation in the tourism sector is a real challenge and demonstrating that the public sector plays an important role in driving the cross-innovation processes between the observed sectors.

The present chapter explicates urban and rural childhoods in India. It presents childhood as a dynamic product arising out of an intersection of children's experiences in different familial–socio-cultural contexts, and children's positions within parent–child interactions and relations. These contexts and interactions tend to colour and shape the childhoods that children inhabit. Drawing on fieldwork conducted in urban and rural India, the chapter documents (1) nature of children's engagements and (2) parent–child relations, explicitly observed in parent–child interactions, provisioning warmth and care; parental control and supervision over children and children's participation in the overall fabric of family life and so forth. Forty-eight parents (24 urban and 24 rural) of children aged 7–11 years participated in the study. Qualitative data gathered through semi-structured interviews and home observations revealed distinctions in urban and rural Indian childhoods. Urban childhood is characterised by rights and privileges, and the centrality of academic pursuits, while rural childhood is featured with subtle induction into economic and social fabric of rural life. Although the world of ‘Indian childhood’ seemed plural, childhood playfulness and learning seemed to be the unifying themes. Geared to the fact that children have to make a living with limited means in the future, both childhoods were accelerated in preparation for future. Dwelling on the complexities in children's lives, this article appreciates diversity and multiplicity in childhoods.

This chapter discusses the various ways in which audiovisual (AV) media industries have cooperated with the tourism industry and explores the emergent areas for cross-innovation. It demonstrates the gradual mediatisation of tourism, but also how the added value from location tourism has started to affect, for instance, the operation of the film industry. It then discusses the emergence of tourism gamification that came about with the arrival of smartphones equipped with an ever-increasing variety of sensors relevant to location and mobility awareness. The chapter finishes by discussing the affordances and forms of augmented reality being used in the service of the cultural heritage sector and the broader tourism sector.