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Working conditions on many digital work platforms often contribute to the grand challenge of establishing decent work. While research has examined the public regulation of platform work and worker resistance, little is known about private regulatory models. In this paper, we document the development of the “Crowdwork Agreement” forged between platforms and a trade union in the relatively young German crowdworking field. We find that existing templates played an important role in the process of negotiating this new institutional infrastructure, despite the radically new work context. While the platforms drew on the corporate social responsibility template of voluntary self-regulation via a code of conduct focusing on procedural aspects of decent platform work (i.e., improving work conditions and processes), the union contributed a traditional social partnership template emphasizing accountability, parity and distributive matters. The trade union’s approach prevailed in terms of accountability and parity mechanisms, while the platforms were able to uphold the mostly procedural character of their template. This compromise is reflected in many formal and informal interactions, themselves characteristic of a social partnership approach. Our study contributes to research on institutional infrastructures in emerging fields and their role in addressing grand challenges.

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.

The development of Research Management and Administration (RMA) in Europe is strongly connected with the development of the Science and Technology (S&T) policy of the European Union (EU). These policies were the result of a continuous debate between the member states and the European Commission and European Parliament.

Although there is no data on the early development of RMA, there are some publications on the history of the development of the S&T policy in Europe: the excellent publication ‘A History of European Union Research Policy’ by Luca Guzzetti (Guzzetti, 1995). Guzzetti’s book investigates the history of EU research policies from 1948 up to the preparation of the Fourth Framework Programme (FP) (1994–1998).

The RMA aspects are constructed mainly by oral history complemented with some written sources. The history shows a gradual development of the profession unevenly spread in time and European geography. This has mainly with the EU enlargement in the same period, when new member states were connected to the FP. The profession started with a few colleagues’ way back in the eighties of the last century as financial people were dealing with the first European financial reporting up to the present day where RMA is becoming a field of work attracting many new colleagues.

As the means and harms of technology-facilitated violence have become more evident, some governments have taken steps to create or empower centralized bodies with statutory mandates as part of an effort to combat it. This chapter argues that these bodies have the potential to meaningfully further a survivor-centered approach to combatting technology-facilitated violence against women – one that places their experiences, rights, wishes, and needs at its core. It further argues that governments should consider integrating them into a broader holistic response to this conduct.

An overview is provided of the operations of New Zealand's Netsafe, the eSafety Commissioner in Australia, Nova Scotia's Cyberscan Unit, and the Canadian Centre for Child Protection in Manitoba. These types of centralized bodies have demonstrated an ability to advance survivor-centered approaches to technology-facilitated violence against women through direct involvement in resolving instances of violence, education, and research. However, these bodies are not a panacea. This chapter outlines critiques of their operations and the challenges they face in maximizing their effectiveness.

Notwithstanding these challenges and critiques, governments should consider creating such bodies or empowering existing bodies with a statutory mandate as one aspect of a broader response to combatting technology-facilitated violence against women. Some proposed best practices to maximize their effectiveness are identified.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

Traditional studies in the sociology of science have highlighted the self-organized character of the academic community. This article focuses on recent interrelated changes that alter that distinctive governance structure and its related patterns of competition and cooperation. The changes that we identify here are contractualization and large-scale cooperative research. We use different data sources to exemplify these new patterns and discuss the illustrative role of research clusters in German academia. Research clusters as funded by the German Research Foundation (DFG) are both a highly prestigious scarce good in the competition for reputation and resources and a means of fostering cooperation. Our analysis of this German example reveals that this new institutional configuration of universities as organizations, academic researchers, and the state has a profound effect on organizational practices. We discuss the implications of our empirical findings with regard to collegiality in academia. Ultimately, we anticipate a further weakening of collegial bonds, not only because universities and the state have become more active in shaping the nature of academic competition and cooperation but also because of the increasing strategic and individualistic orientation of academic researchers. In the final section, we summarize our findings and address the need for further research and an international comparative perspective.

In recent years, both academics and institutions have acknowledged the crucial role multinational enterprises (MNEs) can play in addressing the sustainability challenges, as formalized by the sustainable development goals (SDGs). Nevertheless, because of their extensiveness and their design as country-level targets, SDGs have proven challenging to operationalize at a firm level. This problem opens new and relevant avenues for research in international business (IB). This chapter attempts to frame the topic of extended value chain sustainability in the IB literature. In particular, it addresses a specific topic, that is, how sustainability and resilience-building practices interact in global value chains (GVCs). To do so, the present study develops the case of STMicroelectronics (ST), one of the biggest semiconductor companies worldwide.