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Meta-organizations are crucial devices to tackle grand challenges. Yet, by bringing together different organizations, with potentially diverging views on these grand challenges, meta-organizations need to cope with the emergence of contradictory underlying social orders. Do contradictory orders affect meta-organizations’ ability to govern grand challenges and if so, how? This paper investigates these essential questions by focusing on the evolution and intermeshing of social orders within international governance meta-organizations. Focusing on the International Whaling Commission and the grand challenge of whale conservation, we show how over time incompatible social orders between the meta-organization and its members emerge, evolve and clash. As our study shows, this clash of social orders ultimately removes the “decidability” of certain social orders at the meta-organizational level. We define decidability as the possibility for actors to reach collective decisions about changing an existing social order that falls under a collective’s mandate. We argue that maintaining decidability is a key condition for grand challenges’ governance success while the emergence of “non-decidability” of controversial social orders can lead to substantial failure. We contribute to both the emerging literature on grand challenges and organization theory.

Collegiality is often discussed and analyzed as a challenged form of governance, a form of working that used to function well in universities prior to the emergence of contemporary and modern forms of governance. This seems to suggest that collegiality used to dominate, while other forms of governance are now taking over. The papers in volume 86 of this special issue support the notion of challenged collegiality, but also show that for the most part, nostalgic notions of “the good old days” are neither true nor helpful if we are to revitalize academic collegiality. After examining whether a golden age of collegiality ever existed, we discuss why collegiality matters. Exploring what are often described as limitations or “dark sides” of collegiality, we address four such “dark sides” related to slow decision-making, conflicts, parochialism, and diversity. This is followed by a discussion of how these limitations may be handled and what measures must be taken to maintain and develop collegiality. With a brief summary of the remaining papers under two headings, “Maintaining collegiality” and “Revitalizing collegiality,” we preview the rest of this volume.

The French higher education system has experienced reforms since the 2000s that gradually emphasized the executive power of universities and the centralization of decision-making. This culminated with the excellence initiatives (Idex) that concentrated 7.7 billion euros on only nine institutions to create “world-class” universities and made their leaders responsible for the local allocation of this substantial endowment. The universities’ executives had four years to complete changes in governance in order to see their institution permanently awarded the title and the funding of Idex. The hiring process is one of the elements that this policy impacted the most within these universities, enabling leaders to create new kinds of positions and control the hiring process. However, by looking at the hiring practices within three different Idex, we will show that collegiality did not disappear but rather it evolved: in the three cases, the closest colleagues have been marginalized but decision-making remained collective and in the hands of academics chosen by the university executives. Variations in the intensity of this evolution could be observed according to two dimensions. First, the scientific reputation of the university: the higher it is, the less collegiality is transformed. Second, the level of external pressures: the less collegial universities have relaxed their hiring practices after the evaluation that permanently granted them the label of Idex.

Reality breakdowns generate reflexivity and awareness of the constructed nature of social reality. These pivotal moments can motivate institutional inhabitants to either modify their social worlds or reaffirm the status quo. Thus, reality breakdowns are the initial points at which actors can conceive of new possibilities for institutional arrangements and initiate change processes to realize them. Studying reality breakdowns enables scholars to understand not just how institutional change occurs, but also why it does or does not do so. In this paper, we investigate how institutional inhabitants responded to a reality breakdown that occurred during our ethnography of collegial governance in a large North American university that was undergoing a strategic change initiative. Our findings suggest that there is a consequential process following reality breakdowns whereby institutional inhabitants construct the severity of these events. In our context, institutional inhabitants first attempted to restore order to their social world by reaffirming the status quo; when their efforts failed, they began to formulate alternative possibilities. Simultaneously, they engaged in a distributed sensemaking process whereby they diminished and reoriented necessary changes, ultimately inhibiting the formulation of these new possibilities. Our findings confirm reality breakdowns and institutional awareness as potential drivers of institutional change and complicate our understanding of antecedent microprocesses that may forestall the initiation of change efforts.

A policy of surveillance which interferes with the fundamental right to a private life requires credible justification and a supportive evidence base. The authority for such interference should be clearly detailed in law, overseen by a transparent process and not left to the vagaries of administrative discretion. If a state surveils those it governs and claims the interference to be in the public interest, then the evidence base on which that claim stands and the operative conception of public interest should be subject to critical examination. Unfortunately, there is an inconsistency in the regulatory burden associated with access to confidential patient information for non-health-related surveillance purposes and access for health-related surveillance or research purposes. This inconsistency represents a systemic weakness to inform or challenge an evidence-based policy of non-health-related surveillance. This inconsistency is unjustified and undermines the qualities recognised to be necessary to maintain a trustworthy confidential public health service. Taking the withdrawn Memorandum of Understanding (MoU) between NHS Digital and the Home Office as a worked example, this chapter demonstrates how the capacity of the law to constrain the arbitrary or unwarranted exercise of power through judicial review is not sufficient to level the playing field. The authors recommend ‘levelling up’ in procedural oversight, and adopting independent mechanisms equivalent to those adopted for establishing the operative conceptions of public interest in the context of health research to non-health-related surveillance purposes.

Little research is devoted to how salary allocation processes interfere with gender inequality in talent development in universities. Administrative data from a university indicated a substantial salary gap between men and women academics, which partially could be explained by the unequal distribution of men and women in the academic job levels after acquiring a PhD, from lecturer to full professor, with men being overrepresented in the higher job levels, as well as in the more senior positions within each job level. We demonstrated how a lack of transparency, consistency and accountability can disqualify apparent fair, merit-based salary decisions and result in biased gender differences in job and salary levels. This chapter reflects on how salary decisions matter for the recognition of talent and should be an integral part of talent management.

Recent changes in university systems, debates on academic freedom, and changing roles of knowledge in society all point to questions regarding how higher education and research should be governed and the role of scientists and faculty in this. Rationalizations of systems of higher education and research have been accompanied by the questioning and erosion of faculty authority and challenges to academic collegiality. In light of these developments, we see a need for a more conceptually precise discussion about what academic collegiality is, how it is practiced, how collegial forms of governance may be supported or challenged by other forms of governance, and finally, why collegial governance of higher education and research is important.

We see collegiality as an institution of self-governance that includes formal rules and structures for decision-making, normative and cognitive underpinnings of identities and purposes, and specific practices. Studies of collegiality then, need to capture structures and rules as well as identities, norms, purposes and practices. Distinguishing between vertical and horizontal collegiality, we show how they balance and support each other.

Universities are subject to mixed modes of governance related to the many tasks and missions that higher education and research is expected to fulfill. Mixed modes of governance also stem from reforms based on widely held ideals of governance and organization. We examine university reforms and challenges to collegiality through the lenses of three ideal types of governance – collegiality, bureaucracy and enterprise – and combinations thereof.

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.

Universities are large, complex and highly hierarchical organisations with deeply engrained gendered values, norms and practices. This chapter reflects on the experiences of two universities in initiating structural change towards gender equality as supported by the TARGET project. A common aspect thereby is the lack of a national policy in higher education and research providing specific support for implementing gender equality policies. The process of audit, design, implementation, monitoring and evaluation of the first gender equality plan (GEP) in each of these universities was conceived as a first step in a long journey, providing a framework for engaging different institutional actors and fostering reflexive, evidence-based policy making. The analysis deals with reflexivity and resistance and seeks to draw lessons from bottom-up and top-down experiences of GEP implementation. It is the result of shared reflection between the GEP ‘implementers’ in the two universities and the team who provided support and acted as ‘critical friends’.

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.