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Upon election in 2015, the Justin Trudeau Liberal government announced its intention to transform government operations by bringing nonprofit and private sector partners into the center of public sector decision making through new structures such as Policy Hubs and Innovation labs. These collaborative arrangements were intended to yield the benefits of Michael Barber’s theory of deliverology by breaking through the public sector aversion to risk and change and by creating new spaces for devising effective solutions to the increasingly complex social and economic challenges facing government. A preliminary examination of the use of policy hubs and innovation labs in Canada between 2015 and 2020 indicates that the results have been mixed for the nonprofit sector partners. Collaborative relations have offered nonprofit sector partners new opportunities and access to influence policy decisions. However, this influence also poses risks to their independence, legitimacy and effectiveness as policy advocates. Both public and nonprofit sector partners in PILs should heed certain cautions in choosing future partnerships or they may find their ability to achieve meaningful policy change is limited.

Upon election in 2015, the Justin Trudeau Liberal government announced its intention to transform government operations by bringing nonprofit and private sector partners into the center of public sector decision making through new structures such as Policy Hubs and Innovation labs. These collaborative arrangements were intended to yield the benefits of Michael Barber’s theory of deliverology by breaking through the public sector aversion to risk and change and by creating new spaces for devising effective solutions to the increasingly complex social and economic challenges facing government. A preliminary examination of the use of policy hubs and innovation labs in Canada between 2015 and 2020 indicates that the results have been mixed for the nonprofit sector partners. Collaborative relations have offered nonprofit sector partners new opportunities and access to influence policy decisions. However, this influence also poses risks to their independence, legitimacy and effectiveness as policy advocates. Both public and nonprofit sector partners in PILs should heed certain cautions in choosing future partnerships or they may find their ability to achieve meaningful policy change is limited.

For decades, the cooperative enterprise (CE) produces market goods and/or provides services in the interest to its members, such as communities, customers, and suppliers. The upsurge of interest in social enterprises, and their balancing of social and economic interests, has also led to a renewed interest in CEs, often seen as a specific type of social enterprise. However, from an organizational perspective, this renewed interest has been both limited and scattered over a variety of fields. In this paper, we systematically review papers on CE in the mainstream organizational literature, defined as literature in the fields of economics, business, management and sociology. Our review integrates and synthesizes the current topics in the mainstream organizational literature and provides a number of avenues for future research. In addition, we compare our findings in the organizational literature to the social issues literature as these appeared to be quite complimentary. We found multilevel studies, determination of social impact—in particular measurable impact, managerial practices for sustainable (organisational) development, and the entrepreneurial opportunity generation process as the four key avenues for future research.

For decades, the cooperative enterprise (CE) produces market goods and/or provides services in the interest to its members, such as communities, customers, and suppliers. The upsurge of interest in social enterprises, and their balancing of social and economic interests, has also led to a renewed interest in CEs, often seen as a specific type of social enterprise. However, from an organizational perspective, this renewed interest has been both limited and scattered over a variety of fields. In this paper, we systematically review papers on CE in the mainstream organizational literature, defined as literature in the fields of economics, business, management and sociology. Our review integrates and synthesizes the current topics in the mainstream organizational literature and provides a number of avenues for future research. In addition, we compare our findings in the organizational literature to the social issues literature as these appeared to be quite complimentary. We found multilevel studies, determination of social impact—in particular measurable impact, managerial practices for sustainable (organisational) development, and the entrepreneurial opportunity generation process as the four key avenues for future research.

Social innovation is related to new products, services, and models aiming to improve human well-being and create social relationships and collaborations. The business model innovation (BMI) context can foster social innovation and can be applied in social innovation projects and initiatives. What is important for social BMI is the social mission, which needs to be defined in order to be able to move forward with the strategy, the value proposition, and the best practices of the business. Based on the existing social innovation literature and case studies, this paper proposes an “ecosystem” approach that can provide an integrated framework for social business models. This approach adopts the quadruple/quintuple helix innovation models which are able to promote social innovation, enabling a locus-centric and triple-bottom-line-centric entrepreneurial process of knowledge discovery and exploitation. Such a framework may help to study the role, nature, and dynamics of social co-opetitive fractal ecosystems, given emphasis on civil society, political structures, environment, and sustainability. In addition, the social innovation case studies presented in this paper highlight that targeted open innovation is a key element for social BMI.

Social innovation is related to new products, services, and models aiming to improve human well-being and create social relationships and collaborations. The business model innovation (BMI) context can foster social innovation and can be applied in social innovation projects and initiatives. What is important for social BMI is the social mission, which needs to be defined in order to be able to move forward with the strategy, the value proposition, and the best practices of the business. Based on the existing social innovation literature and case studies, this paper proposes an “ecosystem” approach that can provide an integrated framework for social business models. This approach adopts the quadruple/quintuple helix innovation models which are able to promote social innovation, enabling a locus-centric and triple-bottom-line-centric entrepreneurial process of knowledge discovery and exploitation. Such a framework may help to study the role, nature, and dynamics of social co-opetitive fractal ecosystems, given emphasis on civil society, political structures, environment, and sustainability. In addition, the social innovation case studies presented in this paper highlight that targeted open innovation is a key element for social BMI.

Social innovation is conceptualised as having two intimately related pillars: institutional innovation and locally embedded innovation, in the sense of social economy. Two main research questions were addressed: how political, institutional innovation is fostered and how does it influence social economy? A mixed methods research was conducted in the Mühlviertel NUTS3 region. Despite a framework of enhanced autonomy and institutional innovation for the main stakeholders, both macro and micro analysis illustrate a lack of intermediate space to: a) link the innovative agenda to high-state political agendas, and b) link institutional innovation to social economy.

Social innovation is conceptualised as having two intimately related pillars: institutional innovation and locally embedded innovation, in the sense of social economy. Two main research questions were addressed: how political, institutional innovation is fostered and how does it influence social economy? A mixed methods research was conducted in the Mühlviertel NUTS3 region. Despite a framework of enhanced autonomy and institutional innovation for the main stakeholders, both macro and micro analysis illustrate a lack of intermediate space to: a) link the innovative agenda to high-state political agendas, and b) link institutional innovation to social economy.

Social innovation has been increasingly regarded as an instrument through which transformative structural change, necessary to address grand societal challenges can be achieved. Social innovations are encouraged by the emergence of innovation systems that support changes not exclusively driven by a techno-economic rationality. In the context of this special issue, there has been both little understanding of social innovation systems within mainstream innovation ecosystem approaches and little analysis of the roles played by universities in social innovation systems. We here focus on the institutional complexity of universities and their field-level dynamics as serving as a potential break on the institutionalisation of social innovation. To deepen our understanding of this, we utilise a literature around institutional logics to foreground characteristics of organisational fields with regard to social innovation. Drawing on empirical data gathered in two public universities located in different countries, we show that in one case the potential of social innovation is undermined by two dominant institutional logics, in the other its permeation across the organisational field is seriously challenged by a more powerful dominant logic. The institutional logic approach is useful to highlighting the barriers to building productive innovation ecosystems incorporating social considerations, and helps to explain the persistent difficulties in reframing ecosystems approaches to reflect wider societal dynamics.

With the advent of smart cities (SCs), governance has been placed at the core of the debate on how to create public value and achieve a high quality of life in urban environments. In particular, given that public value is rooted in democratic theory and new technologies that promote networking spaces have emerged, citizen participation represents one of the principal instruments to make government open and close to the citizenry needs. Participation in urban governance has undergone a great development: from the first postmodernist ideals of countering expert dominance to today’s focus on learning and social innovation, where citizen participation is conceptualized as co-creation and co-production. Despite this development, there is a lack of research to know how this new governance context is taking place in the SC arena. Addressing this situation, in this article, we present an exhaustive survey of the research literature and a deep study of the experience in participative initiatives followed by SCs in Europe. Through an analysis of 149 SC initiatives from 76 European cities, we provide interesting insights about how participatory models have been introduced in the different areas and dimensions of the cities, how citizen engagement is promoted in SC initiatives, and whether the so-called creative SCs are those with a higher number of projects governed in a participatory way.

With the advent of smart cities (SCs), governance has been placed at the core of the debate on how to create public value and achieve a high quality of life in urban environments. In particular, given that public value is rooted in democratic theory and new technologies that promote networking spaces have emerged, citizen participation represents one of the principal instruments to make government open and close to the citizenry needs. Participation in urban governance has undergone a great development: from the first postmodernist ideals of countering expert dominance to today’s focus on learning and social innovation, where citizen participation is conceptualized as co-creation and co-production. Despite this development, there is a lack of research to know how this new governance context is taking place in the SC arena. Addressing this situation, in this article, we present an exhaustive survey of the research literature and a deep study of the experience in participative initiatives followed by SCs in Europe. Through an analysis of 149 SC initiatives from 76 European cities, we provide interesting insights about how participatory models have been introduced in the different areas and dimensions of the cities, how citizen engagement is promoted in SC initiatives, and whether the so-called creative SCs are those with a higher number of projects governed in a participatory way.

Nous proposons un regard réflexif sur deux expériences de recherche-projet menées dans le cadre de thèses de doctorat. Notre réflexion porte sur les apports et limites de cette démarche dans le cadre de projets ancrés dans les champs de la santé et du handicap, plus spécifiquement des troubles du sommeil et des troubles du spectre de l’autisme. La proposition repose sur la démonstration de l’intérêt de la conception participative propre à la recherche-projet dans ces domaines sensibles au sein desquels l’enjeu de l’inclusion des acteurs apparaît comme majeur.

Nous proposons un regard réflexif sur deux expériences de recherche-projet menées dans le cadre de thèses de doctorat. Notre réflexion porte sur les apports et limites de cette démarche dans le cadre de projets ancrés dans les champs de la santé et du handicap, plus spécifiquement des troubles du sommeil et des troubles du spectre de l’autisme. La proposition repose sur la démonstration de l’intérêt de la conception participative propre à la recherche-projet dans ces domaines sensibles au sein desquels l’enjeu de l’inclusion des acteurs apparaît comme majeur.

Artificial Intelligence (AI) reshapes companies and how innovation management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel management to rethink a company's entire innovation process. In response, we review and explore the implications for future innovation management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for innovation management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of innovation. We conclude our study by exploring directions for future research.

The importance of knowledge co-creation – the joint production of innovation between industry, research and possibly other stakeholders, such as civil society – has been increasingly acknowledged. This paper builds on 13 cross-country case studies and co-creation experiences during the COVID-19 pandemic to characterise the diversity of knowledge co-creation initiatives and identify lessons for policy. The paper identifies a strong rationale for policy to support knowledge co-creation because the benefits of successful co-creation initiatives outweigh the initial co-ordination costs. Moreover, knowledge co-creation initiatives can contribute to democratising innovation. Successful initiatives engage all stakeholders and have effective governance and management structures. They also have clearly defined ownership and use rights of the collaborations’ outcomes and benefit from favourable conditions to operate, including temporary staff mobility and institutional set-ups that facilitate collaboration and effective communication among participants.

The importance of knowledge co-creation – the joint production of innovation between industry, research and possibly other stakeholders, such as civil society – has been increasingly acknowledged. This paper builds on 13 cross-country case studies and co-creation experiences during the COVID-19 pandemic to characterise the diversity of knowledge co-creation initiatives and identify lessons for policy. The paper identifies a strong rationale for policy to support knowledge co-creation because the benefits of successful co-creation initiatives outweigh the initial co-ordination costs. Moreover, knowledge co-creation initiatives can contribute to democratising innovation. Successful initiatives engage all stakeholders and have effective governance and management structures. They also have clearly defined ownership and use rights of the collaborations’ outcomes and benefit from favourable conditions to operate, including temporary staff mobility and institutional set-ups that facilitate collaboration and effective communication among participants.

Social innovation is not well understood within the context of macro-social work. Frameworks for understanding social innovation as having dimensions of social entrepreneurship, social intrapreneurship, and social advocacy are elaborated. Challenges to the comprehensive understanding and utility of social innovation for macro social work are discussed, especially an overemphasis on social entrepreneurship as the only typical expression of social innovation as well as a mistargeted, deficit-based approach which assumes that contemporary social work is dysfunctional and can only be made functional through social innovation and entrepreneurship. Global and multidisciplinary insights and applications of social innovation for macro social work are reviewed. Finally, how the macro-social work approach to social innovation builds on and advances business approaches to social innovation is discussed.

Local energy policy agendas require commonly defined desirable future visions and collective agenda-setting to spur collaborative action. However, methods designed for multi-stakeholder engagement often do not sufficiently open up deliberative processes to all voices, and efforts to envision desired futures built from current local energy challenges are usually designed by and oriented towards specialists. With this paper, we aimed to explore how the theoretical strengths of storytelling for supporting local policy processes play out in practice. We contrast what the literature states about the potential of storytelling for solving complex challenges and facilitating collaborative processes to the lessons learnt from actually using storytelling in a set of 17 multi-stakeholder workshops across 17 European countries run as part of the H2020 SHAPE ENERGY project. The workshops were each designed around a tangible local energy policy challenge. We found storytelling has unique strengths in terms of enabling significant (un)learning regarding stakeholder relationships, allowing participants to step into others’ perspectives, keeping hold of diversity, and the use of ‘we’ in stories leading to concrete future initiatives. We also note specific learnings about when these outcomes may not be achieved, for example due to fears, traditions, hierarchical structures, as well as the need for sufficient time for planning, facilitator training and stakeholder invitations. We conclude that as an innovative, playful and flexible methodology, storytelling can undoubtedly be a valuable additional tool for policymakers where there is a desire for deliberative stakeholder involvement, and appetite to tailor approaches to local contexts.

Local energy policy agendas require commonly defined desirable future visions and collective agenda-setting to spur collaborative action. However, methods designed for multi-stakeholder engagement often do not sufficiently open up deliberative processes to all voices, and efforts to envision desired futures built from current local energy challenges are usually designed by and oriented towards specialists. With this paper, we aimed to explore how the theoretical strengths of storytelling for supporting local policy processes play out in practice. We contrast what the literature states about the potential of storytelling for solving complex challenges and facilitating collaborative processes to the lessons learnt from actually using storytelling in a set of 17 multi-stakeholder workshops across 17 European countries run as part of the H2020 SHAPE ENERGY project. The workshops were each designed around a tangible local energy policy challenge. We found storytelling has unique strengths in terms of enabling significant (un)learning regarding stakeholder relationships, allowing participants to step into others’ perspectives, keeping hold of diversity, and the use of ‘we’ in stories leading to concrete future initiatives. We also note specific learnings about when these outcomes may not be achieved, for example due to fears, traditions, hierarchical structures, as well as the need for sufficient time for planning, facilitator training and stakeholder invitations. We conclude that as an innovative, playful and flexible methodology, storytelling can undoubtedly be a valuable additional tool for policymakers where there is a desire for deliberative stakeholder involvement, and appetite to tailor approaches to local contexts.

The world is witnessing an unprecedented disruption due to the COVID-19 pandemic in almost all spheres of socio-economic activity. This black swan moment is unprecedented since the advent of the Industrial Revolution. Simultaneously, there is a shift towards effective use of data and technology. There is an exponential increase in the quantum of data collected and has subsequently necessitated a paradigm shift in the functioning of Industry 4.0. Data intelligence, data science, artificial intelligence, machine learning, and deep assimilation of nuanced knowledge revolutionize business and society worldwide. This heralds a potential transition towards data-intensive economies, governments, industrial and social sectors. The accelerated pace of data processing, data intelligence, and analytics encompasses business intelligence, data sciences and machine learning. The spectrum of such upheavals and associated technological transitions is a watershed moment and impacts business and social transformations. In the paper on the role of data in the social realm (Technology as a catalyst for sustainable social business: Advancing the research agenda, 2019). Ashraf et al. opine that “Despite its immense potentials as a sustainable and innovative means to solve specific social problems, the basic concept of the social business model remains unclear to many”. In recent times there has been an inconsistent approach towards social business research. Subsequently, the contemporary business scenario is yet to optimally capitalize on the advantages of the Social Business concept and address the divergent socio-economic and ecological issues worldwide, with profits intact. This should in no way dilute profit maximization for optimizing socio-economic benefits for value creation and sustainability. “Although the social enterprise is often considered to have positive future potential, it is currently underdeveloped” (Bell, 2003). Therefore, social entrepreneurship should generate and ensure nuanced and effective innovations, addressing underserved needs. In contemporary times, tools harnessing Big Data are becoming widely applied, leading to a huge reservoir of untapped diverse data. This subsequently creates an immense opportunity to accelerate the use of Big Data towards social good and sustainability. Though this is a recent trend, it indeed holds promise in the post-COVID world that would be privy to unprecedented socio-economic upheavals and an increased need to address issues of humankind for greater global welfare. In the recent past, diverse data sets have created large-scale solutions in diverse spheres ranging from weather forecasts to airline tickets. Insightful correlations and Big Data go hand in hand and hold the key to several complicated pressing social issues. Therefore, a new crop of social entrepreneurs in public health, social welfare, and humanitarian relief would surely emerge by default. Therefore, it is all the more relevant to make sense of a deluge of Big Data towards alleviating a disease, ecological imbalance, war, and most importantly, the patterns to cope with the disease and its aftermath. This chapter proposes anticipating and predicting the immense possibilities of optimizing Big Data and digitization as key critical drivers of empirical simulation and troubleshooting. Good governance, inclusive society, elimination of corruption, and streamlining policy measures would emerge as default collectives of such social entrepreneurial ventures. The chapter would draw inferences from such models of socially inclined data analytics by data scientists, leading to relevant social models of significance. Implications of the chapter would be to assuage the fault lines, draw inferences from the past, and delve into the plausibility and relevance of Big Data to replicate and innovate socially relevant models to map bigger social issues. This, of course, should have embedded benchmarks of equality, ethics, and empowerment while processing Big Data for a greater social good in a post-COVID world gaping at us.