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The purpose of the chapter is to focus on the global industrial robotics market and trends of its development. In the framework of this chapter, the authors made the forecast of industrial robots' market future values in this chapter with the linear regression method and an econometric model. This analysis has provided a conclusive answer to the question about the prospects of the industrial robotics market and the leading countries. The completed forecast showed that the global robotics market will continue to grow, thanks to the wider adoption of industrial robots, which will be used in new industries, the development of contactless user interfaces, which, among other things, will be implemented in the automotive applications, the focus on predictive maintenance and remote monitoring of equipment, as well as the transition of a large number of enterprises to digital management and full automation of existing equipment to improve the quality and productivity of processes. The authors show that in 2020 the global robotics market volume decreased due to the COVID-19 pandemic and major shift in production value chains, but in 2021 the indicator will grow again, but not so rapidly, at a more moderate pace. By 2025, the global industrial robotics market may exceed $61.4 billion, with a growth rate of 8.5%.

We investigate product innovation by a cohort of entrants who use technology that eventually suffers disruption. We concentrate on two types of entrants – those with and those without relevant prior experience in the disrupted technology. Using the industrial robotics industry as the context of our study, we explore product innovation using disrupted technology during two time periods: the first prior to sales takeoff of the disruptive products and the second subsequent to takeoff. We find that the two types of entrants did not differ in product innovation prior to takeoff, but firms with prior experience in the disrupted technology manufactured more innovative products subsequent to the sales takeoff of disruptive products. Our research underscores that the boundary conditions of the utility of prior experience is more nuanced than that which literature suggests – it affects product innovation only in the post-sales takeoff period when the demand uncertainties are relatively low. Our findings also suggest that the boundary conditions of Christensen’s thesis are narrower than predicted by prior literature.

Unlike the historical robots, the contemporary and futuristic ‘working’ robots within organisations are capable of taking decisions without human intervention. This chapter reviews the technical evolution of robots across history with the necessary evolution of operational procedures regarding laws and ethical standards. The objective of this review is to have a futuristic holistic insight into the new generation of robots that are invading our working environment within organisations. Out of the very wide perspective of robotics research field, this chapter only discusses the ‘working’ robots (excluding domestic, social, and warfare robots) in organisations along with its ethical and legal associated issues. To achieve this objective, the recent ‘working robot’ definition and associated expected ethics and laws, termed in this chapter as ‘Ten Commandments’ would be necessary for the utilisation of robotics before releasing ‘intelligent’ robots in the workplace environment. The proposed ‘Ten Commandments’ can be utilised by robot manufacturer to embed ‘machine testimony’ to their products. Providing that such ‘robot ethics’ built as part of the algorithmic structure of robots, a useful innovation like robot–manager is also identified in the organisational environment which can have multiple benefits as discussed in this chapter.

The aim of this chapter is to introduce the reader to the complexities of marketing organization especially in bigger firms. This chapter draws attention to one of these major drivers for change — globalization. This is done with the help of an in-depth case study of ABB Robotics.

The case describes how a change is achieved through a major marketing reorganization process. Initially, there are major difficulties grasping the organizational problem and identifying its causes. Many different organizational “issues” are part of the problem in the multifaceted case. Relying on complexity theory, the case suggests that a more complex environment with greater number of relevant players, which are — themselves — interconnected through networks, will also exhibit a greater range of change. Change and reorganization processes like the one confronting the case company would rather be the normal situation for companies embedded in complex global networks.

Industry 4.0 refers to an era in which human work, creative activities and professional knowledge are largely replaced by artificial intelligence (AI) and robots. Due to the current exponential rate of technological development and the infinite expansion and generalisation of technologies, it is not difficult to predict that these technologies will spread at exponential rates and will spur massive changes in the adopted production, management and governance mechanisms and in the future employment market. Especially, employment changes are inevitable with the rise in automation and the job scope and prospects are bound to vary widely. In this chapter, confrontation strategies for employment in Industry 4.0 are proposed. It is hoped that this study will be able to provide an accurate direction for future employment and will be able to contribute to the study of employment policies and Industry 4.0.

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.

In this chapter, the authors offer a critical appraisal of predictions of a jobless future due do rapid technological change, as well as provide evidence on whether the rate of occupational change has been increasing. The authors critique the “task replacement” methodology that underlies the most powerful and specific predictions about the impact of technology on employment in particular occupations. There are a number of reasons why assuming a correspondence between task replacement and employment declines is not warranted. The authors also raise questions about how rapidly the development, acceptance, and diffiusion of labor-displacing technologies is likely to occur. In the empirical portion of the chapter, the authors compare the current rate of employment disruption with those observed in earlier periods. This analysis is based on an analysis of occupation data in the US covering the period 1870–2015. Using an index of dissimilarity as the metric, the authors find that the rate of occupational change from 1870 to 2015 does not provide evidence of a sharp uptick in the rate of occupational shifts in the information age. Instead, the rate of occupation shifts has been declining slowly throughout the second half of the twentieth century. Thus, the issues and results discussed here suggest that imminent massive employment displacement is not a foregone conclusion.