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This paper aims to look at the implementation of project-funded research governance and its potential to induce organisational learning on responsible research and innovation (RRI). This paper analysed what types of organisational learning and change can take place within organisations of an Europe-funded project and to what extent. This paper examined whether and how change occurs and how it is shaped and co-produced with other orderings.

The paper is based on materials and evidence collected while working on the internal evaluation of a Horizon 2020-funded project. Analysis of the results of the mixed methods evaluation design was used to characterise occurrences of organisational learning and change.

The authors identified different forms of learning (single-loop learning, double-loop learning, reflexive and reflective learning and situational learning). The extent of learning that could lead to long-lasting organisational change was limited. This was due to the project-based and organisational design, the key-based definition of RRI and the indeterminacy of what constitutes learning and change – both at the level of funding and performing the project. For organisational change to occur, the authors argue for governance mechanisms based on reflexive learning that consider a range of structural conditions and measures.

Organisational learning plays an important role in change processes, which has so far been given too little consideration concerning the governance and implementation of RRI through project-based funding. The authors argue for a restructuring of governance and funding mechanisms to create more space for reflexivity and learning.

Policy-oriented responsibility initiatives are institutional attempts to make innovations more responsible. One such initiative is offered by the European Commission’s responsible research and innovation (RRI) keys (public engagement, gender equality, science education, open access and ethics). This study is conducted in the context of an EU Horizon 2020 project and focuses on the introduction of RRI keys to innovation projects of the additive manufacturing (AM) industry. This study aims to understand how these RRI keys are perceived and adopted by industry project partners.

The authors use an ethnographic study based on “participant observation”, supported by interviews and workshops with AM industry experts. In particular, the analysis covers two specific innovation use cases – one in the medical field, and second in the automotive field, in the context of the EU project. The analysis, based on ethnographic data, is inductive and interpretative.

The authors take a critical approach towards the implementation of RRI policy keys as measurable indicators, and argue that they are not easy tools to implement. The authors portray how RRI keys were understood and welcomed by industrial organisations, and how their implementation raised controversies. The authors also found that RRI keys are difficult to understand. They are not easy to measure and report, and this contrasts with earlier proposals of how RRI keys should be governed or implemented. The governance, meaning the dialogue between stakeholders both internal and external to the organisation, was time-consuming and required constant organisational learning.

Due to the insightful ethnographic methodology, the authors could well underline the faults and difficulties of the application of policy-oriented responsibility in innovation. The findings illustrate the difficulty of implementing RRI in an industry that mainly operates business-to-business. This can help future policymakers to find more successful ways of pushing industry and innovators to be more responsible. It can also suggest better ways of reaching higher organisational learning for the purpose of more responsible innovations.

The purpose of this study is to analyze reported good institutional responsible research and innovation (RRI) practices from an organizational and learning perspective to discuss the usefulness of RRI as a broad umbrella concept.

This study connects neo-institutional and translation accounts of diffusion to different modes of learning and discusses reported best practices from 12 reports, including in total 23 organizations in the research system worldwide, in light of this theoretical framework. This study categorizes the good practices identified in the reports and discusses how the nature of the practices influences the potential learning from them. The authors then apply the results from the discussion of this study to current policy developments on RRI.

The two most often mentioned good practices overall are organizational policies and the establishment of organizational units, but the type of good practices recommended differs across the various aspects of the RRI umbrella concept. This diversity within the RRI construct is a practical argument against the effectiveness of RRI as an umbrella concept.

This study is novel in the fact that the authors, building on Wæraas (2020), systematically relate types of good practice to neo-institutional theory and translation perspectives explicitly combined with learning approaches and apply this approach in the field of research organizations. The policy implications from the empirical and theoretical analyses are novel and timely in these early phases of the EU funding framework programme Horizon Europe and can also be relevant for the increasingly important umbrella concept of Open Science.

This study aims to discuss science governance in Europe and the network of associated nonprofit institutions. The authors posit that this network, which comprises both (partial) learning organizations and non-learning organizations, has been observed to postpone taking up “responsibility” as an issue in science governance and funding decisions.

This paper discusses the challenge of learning and policy implementation within the European science governance system. By exploring how learning on responsible innovation (RI) in this governance system can be provoked, it addresses the question how Senge’s insights in organizational learning can clarify discourses on and practices of RI and responsibility in research. This study explores the potential of a new organizational form, that of Social Labs, to support learning on Responsible Research and Innovation (RRI) in standing governance organizations.

This study concludes that Social Labs are a suitable format for enacting the five disciplines as identified by Senge, and a Social Lab may turn into a learning organization, be it a temporary one. Responsibility in research and innovation is conducive for learning in the setting of a Social Lab, and Social Labs act as intermediary organizations, which not merely pass on information among actors but also actively give substantive shape to what they convey from a practice-informed, normative orientation.

This empirical work on RRI-oriented Social Labs therefore suggests that Social Lab–oriented temporary, intermediary learning organizations present a promising form for implementing complex normative policies in a networked, nonhierarchical governance setting.

Based on this research funding and governance organizations in research, policy-makers in other domains may take up and create such intermediary organizations to aid learning in (science) governance.

This research suggests that RRI-oriented Social Labs present a promising form for implementing complex normative policies, thus integrate learning on and by responsible practices in various governance settings.

European science governance is characterized by a network of partial Learning Organization (LOs) and Non-Learning Organization (nLOs) who postpone decision-making on topics around “responsibility” and “solving societal challenges” or delegate authority to reviewers and individual actors, filtering possibilities for collaborative transformation toward RRI. social lab (SLs) are spaces that can address social problems or social challenges in an open, action-oriented and creative manner. As such, they may function as temporary, intermediary LOs bringing together diverse actors from a specific context to work on and learn about issues of science and society where standing organizations avoid doing so. Taken together, SLs may offer temporary organizational structures and spaces to move beyond top-down exercise of power or lack of real change to more open, deliberative and creative forms of sociopolitical coordination between multiple actors cutting across realms of state, practitioners of research and innovation and civil society. By taking the role of temporary LOs, they may support existing research and innovation organizations and research governance to become more flexible and adaptive.

The purpose of this paper is to explore how relationships between different actors are being shaped to allow industry to come to acceptable and desirable uses of research and innovation (R&I) that address societal challenges.

Building on existing notions of responsibility proposed in the literature, the paper develops a theoretical account of “networks of responsibility” which capture the interlinked nature of responsibility relationships. The usefulness of the approach is evaluated by exploring two cases of R&I in industry deploying a qualitative research approach that involves interviewing and document analysis. For this, a multinational company from Germany was involved, as well as a small- and medium-sized company from Denmark.

The study surfaced 68 responsibility relationships involving a range of different objects, subjects, authorities and norms. By describing overlaps in objects, subjects and other aspects across relationships, the theoretical model proved adequate in untangling and displaying interrelatedness of responsibilities. Furthermore, the analysis surfaced characteristics of responsible research and innovation (RRI) that are already in place in the R&I processes of two innovative companies, such as anticipation, foresight and stakeholder engagement. Not all aspects of responsibility outlined in the theoretical model could be extracted from the interview data for every responsibility relationship, pointing to the need for further research.

The paper is practically relevant because it supports policy development on an organisational, as well as societal level. Moreover, the networks of responsibility model offer a fine-grained assessment of responsibilities in R&I practice by mapping existing responsibilities which supports translating RRI principles into everyday organisational practices.

RRI sets an ambitious agenda to ensure a more social and ethical R&I. Much work is still needed to bridge the gap between these theoretical and political aspirations and daily R&I practice, especially in non-academic contexts such as industry. By offering a way to understand and untangle the complexity of responsibility relationships, the networks of responsibility model seem to offer a promising approach that can support this endeavour.

The paper offers a novel theoretical approach to understanding and analysing responsibility allocations in R&I in industry. It demonstrates the reliability of this theoretical position empirically. It is practically important because it supports policy development on an organisational as well as societal level.

Responsible research and innovation (RRI) is taking a role in assisting all types of stakeholders, including industry members, in moving their research and innovation (R&I) initiatives to tackle grand challenges. The literature on RRI, however, focuses little on how industry can implement RRI principles. To solve this gap, the purpose of this study is to construct a conceptual framework for managing and assessing RRI principles in the industry.

Qualitative research was used to build the RRI key performance indicator list; 30 interviews were conducted to design a framework which was pilot tested in a company to identify how to align technology outcomes to the values, needs and expectations of the society.

This study depicts five successive RRI implementation levels and exhibits RRI key performance indicators. Drawing on extant models, this study develops RRI levels and indicators to discuss why industry should become engaged in RRI, how it can embed RRI principles into R&I processes and how RRI indicators can be managed systematically.

The connection between RRI key performance indicators and RRI levels determines how industry can integrate principles and methodologies of RRI into R&I processes. The model in the study shows how companies move from one RRI stage to another and this study aims to exhibit an ideal stage of RRI for industry.

This study aims to investigate whether the learning organization, as envisioned by Peter Senge in The Fifth Discipline (1990), facilitates responsible innovation.

The authors analyze the component characteristics of the learning organization as defined by Senge (1990) to identify any conceptual or causal connections to responsible research and innovation (RRI). To define RRI, the authors make use of a commonly cited framework from the academic literature that is consistent with the vision of RRI promoted in European Union policy.

The authors find significant complementarities between being a learning organization and practicing responsible innovation. Some of the practices and characteristics of a learning organization in the sense of Senge (1990) do not merely facilitate RRI, they are RRI by definition. One important caveat is that to qualify as a responsible innovator according to the proposed framework, an organization must involve external stakeholders in the innovation process, a requirement that has no parallel in The Fifth Discipline. The authors conclude that there is at most a small step from being a learning organization to becoming a responsibly innovating learning organization.

The authors propose a reconsideration of the scope of applicability of Senge’s theory, opening new possibilities for drawing inspiration from The Fifth Discipline 30 years after the book was first published. The authors conclude that there may be significant non-economic advantages to being a learning organization, and that The Fifth Discipline may be more valuable for its ethical perspectives on the organization than as a prescription for how to achieve business success.

How to derive policy implications from five future scenarios of transformed research and innovation (R&I) systems? This paper analyzes methodological and content issues of five future scenarios of transformed R&I systems. The aim of this paper is to provide an outlook on strategic policies capable of facilitating or moderating these transformative changes in R&I practices is discussed in light of overarching intentions to foster “responsible” ambitions (in Europe and beyond, discussed as responsible research and innovation, RRI).

The paper elaborates a four-step methodology to assess the scenario’s policy implications: first, by articulating the scenario implications for six core dimensions of R&I systems; second, an RRI assessment framework is developed to assess in each scenario opportunities and limitations for transforming R&I systems towards responsibility goals; the third involves a cross-scenario analysis of similarities and differences between the scenarios, allowing the identification of robust policy options that make sense in more than one scenario. The last analytical step includes again the richness of the individual scenario assessments aiming to provide a broader outlook on transformative policy orientations.

The paper concludes with outlining the contours of a future-responsible R&I system together with some suggestions for transformative policy orientations that aim to govern the R&I system towards such a future, as a source of inspiration and reflection.

The analysis is based on five future scenarios that do not systematically cover future developments external to the R&I system.

An outlook of strategic policies capable of facilitating or moderating these transformative changes in R&I practices is discussed in light of the overarching European Union goal of encouraging the performance of RRI.

This paper provides inspirational anticipatory strategic intelligence for fostering the responsible ambitions of research with and for society.

The purpose of this study is to provide insights into how accounting and accountability systems can contribute to transforming metrics used thus far in research performance evaluation. New metrics are needed to increase research impact on the challenges addressed by science. In particular, we document and reflect on accounting transformations towards responsible research and innovation (RRI).

The study draws on the European H2020 MULTI-ACT research project that focuses on the development of a collective research impact framework in the area of health research. We document, analyse and report our engagement in this project, which also included research funders, patient organizations, health researchers, accounting practitioners and health care providers. Drawing on RRI, Mode 2 knowledge production and accounting performativity, we inquire into the potential of accounting technologies to foster knowledge production and increase research impact.

The study shows how the engagement of accounting with other disciplines enables the development of new and relevant forms of research impact assessment. We document how accounting can be mobilised for the development of new forms of research impact assessment (i.e. indicators that evaluate key accountability dimensions to promote RRI) and how it helps to overcome the difficulties that can emerge during this process. We also show how the design of multiple accountabilities’ indicators, although chronically partial, produced a generative interrogation and discussion about how to translate RRI to research assessment in a workable setting, and the pivotal role of certain circumstances (e.g. the presence of authoritative actors) that appear during the knowledge production process for creating these generative opportunities.

This study illustrates the key role of accounts in the generation of knowledge. It also shows the value of considering the stakes of all affected actors in devising fruitful accounting approaches. This collective perspective is timely in the accounting discipline and could foster the connection between academics and practice which is so far under-reported. This perspective should be useful for policymakers such as the European Union and managers in the design of new policies, initiatives and practices.

Discussing and devising appropriate research assessment frameworks is strategic for the maximization of the social impact of research results. Accounting has a key role to play in optimizing a sustainable return on investment in research.

How to assess research impact in a more balanced way is in an early stage of development. The study provides empirical and practical material to advance further work and develop its potential to broaden the conceptualization of accountability.

Many of the ethical issues of additive manufacturing (AM) are not well known or understood, and there remains a policy vacuum that needs to be addressed. This paper aims to describe an approach that has been applied successfully to other emerging technologies, referred to as the responsible research and innovation (RRI) framework programme. A case is then made for the application of this approach in the AM industry with an illustration of how it might be used.

The research uses an RRI approach referred to as AREA, an acronym for Anticipate, Reflect, Engage and Act, to assess the ethical implications of AM. For the anticipation phase, horizon scanning was done to explore the ethical issues of AM based on extant literature, while reflective analysis was carried out all through the work to reflect on the data being collected and the research process. The engage phase involved interviews with five participants from small- and medium-sized enterprises (SMEs) involved in 3D printing.

The findings indicate that although AM appears to pose a threat to intellectual property rights, many in the industry do not care about this issue. As AM becomes mainstream, intellectual property will likely become a big problem. Also, very little is known about the health impacts of AM. This study shows that AM can be hazardous.

Only users at SME level were sampled. Other researchers might test the usefulness of AREA at the enterprise level.

The research demonstrates how the AREA framework may be useful in information systems and social science research by enabling a more anticipatory and reflective research process.

The paper responds to the need for a novel approach to identifying ethical issues of AM.