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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.

This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

Industry 4.0 or the Fourth Industrial Revolution is characterized by robotic process automation and machine-to-machine communications. Since computers, machines, and robots share information and knowledge more swiftly and effectively than humans, the question is what human beings' role could be in the era of the Internet-of-Thing. The answer would be beneficial to institutions for higher education to anticipate. The literature reveals a gap between the intended learning outcomes in higher education institutions and the needs of employers in Industry 4.0. Evidence is shown that higher education mainly focused on knowledge (know-what) and theory-based (know-why) intended learning outcomes. However, competent professionals require knowledge (know-what), understanding of the theory (know-why), professional (know-how) and interpersonal skills (know-how and know-who), and need intrapersonal traits such as creativeness, persistence, a result-driven attitude et cetera. Therefore, intended learning outcomes in higher education should also develop interpersonal skills and intrapersonal characteristics. Yet, personality development is a personal effort vital for contemporary challenges. The history of the preceding industrial revolutions showed the drawbacks of personality and character education; politicians have abused it to control societies in the 19th and 20th centuries. In the discussion section, the institutions for higher education are alerted that the societal challenges of the twenty-first century could lead to a form of personality education that is not in the student's interest and would violate Isaiah Berlin's philosophical concept of ‘positive freedom’.

The construction industry is one of the least automated industries. In the aspect of automation, the technical understanding is very dominant. Focus has mostly been on tools, robots and industrialisation. sociomaterial design shows us that what may first appear technologically deterministic can be replaced and actually call for reinvisioning the traditional focus. The purpose of this study is to introduce the agency of a sociomaterial designer in construction.

This is a conceptual paper with an empirical example. To understand the sociomaterial complexity and dynamics of automation, practice theories are applied. To test this approach, the authors give an example from a Danish (global) supplier engaged in a development project about technical aid (tools) in mounting and assembling gypsum walls.

The sociomaterial-designer can help to understand and make innovation happen when doing automation in construction; as the centre of innovation in construction processes, she works all day with practice, together with practitioners, focusing on material arrangements as located not only in practice, but also in the artefacts. She can help the supplier of construction materials in understanding different professional practices and the transformation to use smarter tools.

This research is within a new practice domain “sociomaterial-design” and it has to follow up with an empirical study that covers a development project with a sociomaterial-design approach.

Developing competences (agency) as a sociomaterial-designer when linking the sociotechnical understanding of Automation with practice.

This research showcases how sociomaterial perspectives can inform automation in construction.

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.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.

This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.