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In the cold war era, perhaps there were no greater heroes of the Soviet Union than the as many as 700,000 firefighters, workers, and military personnel who fought the blazing fires at the Chernobyl nuclear reactor that burned out of control for months until smothered by a makeshift concrete structure, called the “sarcophagus” built to contain radioactive releases. Whether this sarcophagus will last as long as the Egyptian monuments, its name evokes has been a matter of grave continuing concern. And it is doubtful that its symbolism as a lasting evidence of 20th century life will be equally appreciated through the ages. But in April 26, 1986, northern Europe had been placed in dire peril by the catastrophic accident in the number 4 reactor at Chernobyl. Smoke pouring from the fires lofted high in the sky to carry radioactive contaminants eventually across the Northern Hemisphere. Some 100 million curies of radiation were released within 10 days of the initial explosion, comprising the word's worst civilian radiation release (Lawrence Livermore, 1999). And, the reactor threatened to unleash a nuclear explosion that would have dwarfed the effects of what already was the world's worst nuclear accident. The situation demanded extreme sacrifice (see also Zykova, this volume).

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.

Anthropomorphism in Artificial Intelligence (AI)-powered devices is being used increasingly frequently in consumer-facing situations (e.g., AI Assistants such as Alexa, virtual agents in websites, call/chat bots, etc.), and therefore, it is essential to understand anthropomorphism in AI both to understand consequences for consumers and to optimize firms' product development and marketing. Extant literature is fragmented across several domains and is limited in the marketing domain. In this review, we aim to bring together the insights from different fields and develop a parsimonious conceptual framework to guide future research in fields of marketing and consumer behavior.

We conduct a review of empirical articles published until November 2021 in Financial Times Top 50 (FT50) journals as well as in 41 additional journals selected across several disciplinary domains: computer science, robotics, psychology, marketing, and consumer behavior.

Based on literature review and synthesis, we propose a three-step guiding framework for future research and practice on AI anthropomorphism.

Our proposed conceptual framework informs marketing and consumer behavior domains with findings accumulated in other research domains, offers important directions for future research, and provides a parsimonious guide for marketing managers to optimally utilize anthropomorphism in AI to the benefit of both firms and consumers.

We contribute to the emerging literature on anthropomorphism in AI in three ways. First, we expedite the information flow between disciplines by integrating insights from different fields of inquiry. Second, based on our synthesis of literature, we offer a conceptual framework to organize the outcomes of AI anthropomorphism in a tidy and concise manner. Third, based on our review and conceptual framework, we offer key directions to guide future research endeavors.

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.

The chapter offers complete details of the latest SGL version particularly suitable for dealing with large security systems and emerging crisis situations. It describes main types of constants representing information, physical matter or both and five very different and specific types of variables operating in fully distributed spaces and even being mobile themselves when serving spreading algorithms. Also given full repertoire of the language operations, called rules, which can be arbitrarily nested and carry different navigation, creation, processing, assignment, control, verification, context, exchange, transference, echoing, timing and other loads. The rules equally operate with local and remote values, process both, matter and distributed networked knowledge, and can express active graph-based patterns navigating, matching, conquering and changing distributed environments. Elementary programming examples in SGL are also provided.

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.