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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.

Social business is a new kind of business model, which integrates multiple dimensions and meanings, including management experiences from private, public, and nonprofit organizations. Social business has a goal of solving social problems through entrepreneurship, combining efficiency, innovation, and resources from a traditional enterprise with mission and values of a nonprofit organization

Social business is a new kind of business model, which integrates multiple dimensions and meanings, including management experiences from private, public, and nonprofit organizations. Social business has a goal of solving social problems through entrepreneurship, combining efficiency, innovation, and resources from a traditional enterprise with mission and values of a nonprofit organization

Social innovations have proven to be valuable in identifying, designing and implementing new solutions to social and environmental problems. The recent COVID-19 outbreak has put a spotlight on the potential of social innovation as a resilience mechanism, including for local development. This paper presents a preliminary framework for analysing social innovation ecosystems at the local level. It can help policy makers to better understand the different concepts around social innovation, and to develop policies to support social innovation and its implementation. The first section considers the features of social innovation and the benefits it can bring. The second section provides an analytical framework for social innovation at the local level. The final section sets a number of guidelines that support the implementation of social innovation ecosystems at local level, including examples of specific policy instruments.

Social innovations have proven to be valuable in identifying, designing and implementing new solutions to social and environmental problems. The recent COVID-19 outbreak has put a spotlight on the potential of social innovation as a resilience mechanism, including for local development. This paper presents a preliminary framework for analysing social innovation ecosystems at the local level. It can help policy makers to better understand the different concepts around social innovation, and to develop policies to support social innovation and its implementation. The first section considers the features of social innovation and the benefits it can bring. The second section provides an analytical framework for social innovation at the local level. The final section sets a number of guidelines that support the implementation of social innovation ecosystems at local level, including examples of specific policy instruments.

University-community engagement is emerging as an important channel for social innovation, requiring universities to act as change agents in their local settings. The role of change agent presents new challenges for universities as it requires going beyond institutional borders to collaborate with non-traditional partners such as informal enterprises, and to stimulate and support innovation that may be seen as relevant to a given local setting only. Universities are thus grappling with finding suitable mechanisms and models for engaging in institutional contexts that are vastly different from traditional formal university- and firm-based settings. Based on empirically rich case study research in a South African township, the paper presents new conceptual insights on how universities can catalyse social change in resource-poor local settings through strategically selecting mechanisms and models of engagement that align with locally-embedded institutions, practices and needs. Four types of engagement models are identified, each relate to different models of entrepreneurship and innovation and thus different modes of learning. The typology distinguishes between dominant, traditional knowledge transfer models, and emergent, socially responsive models that show greater promise for promoting collective agency and effecting systemic social change. The typology can be used to assess current practice and inform future strategies.

University-community engagement is emerging as an important channel for social innovation, requiring universities to act as change agents in their local settings. The role of change agent presents new challenges for universities as it requires going beyond institutional borders to collaborate with non-traditional partners such as informal enterprises, and to stimulate and support innovation that may be seen as relevant to a given local setting only. Universities are thus grappling with finding suitable mechanisms and models for engaging in institutional contexts that are vastly different from traditional formal university- and firm-based settings. Based on empirically rich case study research in a South African township, the paper presents new conceptual insights on how universities can catalyse social change in resource-poor local settings through strategically selecting mechanisms and models of engagement that align with locally-embedded institutions, practices and needs. Four types of engagement models are identified, each relate to different models of entrepreneurship and innovation and thus different modes of learning. The typology distinguishes between dominant, traditional knowledge transfer models, and emergent, socially responsive models that show greater promise for promoting collective agency and effecting systemic social change. The typology can be used to assess current practice and inform future strategies.

L’article est basé sur une enquête portant sur la structuration de la démarche de développement durable et responsabilité sociale (DD-RS) dans les universités françaises. Il s’appuie sur la théorie de la structuration et la Théorie Néo-Institutionnelle pour construire un cadre conceptuel à la structuration de cette mission. Ce dernier est confronté à la pratique des établissements et débouche sur une typologie fondée sur le rôle de l’implication politique, de la culture du pilotage et des isomorphismes. La discussion autour de cette typologie, à partir d’une ACM montrant l’existence de groupes homogènes d’universités quant à leur structuration d’une démarche DD-RS, permet d’affiner le rôle de chacun des facteurs du modèle conceptuel.

L’article est basé sur une enquête portant sur la structuration de la démarche de développement durable et responsabilité sociale (DD-RS) dans les universités françaises. Il s’appuie sur la théorie de la structuration et la Théorie Néo-Institutionnelle pour construire un cadre conceptuel à la structuration de cette mission. Ce dernier est confronté à la pratique des établissements et débouche sur une typologie fondée sur le rôle de l’implication politique, de la culture du pilotage et des isomorphismes. La discussion autour de cette typologie, à partir d’une ACM montrant l’existence de groupes homogènes d’universités quant à leur structuration d’une démarche DD-RS, permet d’affiner le rôle de chacun des facteurs du modèle conceptuel.

Studies on public sector innovation often treat this type of innovation as something that emerges within public sector organizations. However, innovation theory argues that external sources of innovation are more fruitful sources of ideas. We claim that universities must be treated as a mandatory element in public sector innovation. This paper is aimed at clarifying the place of public sector innovation in the classification of innovations currently used in the literature. It also seeks to conceptualize an approach for future research on the topic. Our primary goal is to identify the role of different actors in the development of public sector innovation. We analyze the advantages and disadvantages of different forms of university involvement in public sector innovation. The paper consists of two parts. The first defines concepts of innovation in general and public sector innovation viewed as a variation on social innovation. The second is dedicated to an analysis of the experience of Russian universities in enhancing collaboration between actors in the public innovation system.

Studies on public sector innovation often treat this type of innovation as something that emerges within public sector organizations. However, innovation theory argues that external sources of innovation are more fruitful sources of ideas. We claim that universities must be treated as a mandatory element in public sector innovation. This paper is aimed at clarifying the place of public sector innovation in the classification of innovations currently used in the literature. It also seeks to conceptualize an approach for future research on the topic. Our primary goal is to identify the role of different actors in the development of public sector innovation. We analyze the advantages and disadvantages of different forms of university involvement in public sector innovation. The paper consists of two parts. The first defines concepts of innovation in general and public sector innovation viewed as a variation on social innovation. The second is dedicated to an analysis of the experience of Russian universities in enhancing collaboration between actors in the public innovation system.

This article explores how health innovation designers articulate are and responsibility when designing new health technologies. Towards this end, we draw on Tronto’s ethic of care framework and Responsible Research and Innovation (RRI) scholarship to analyse interviews with Canadian health innovators (n ¼ 31). Our findings clarify how respondents: 1) direct their attention to needs and ways to improve care; 2) mobilise their skill set to take care of problems; 3) engage in what we call ‘care-making’ practices by prioritising key material qualities; and 4) operationalise responsiveness to caregivers and care-receivers through user-centred design. We discuss the inclusion of health innovation designers within the care relationship as ‘caremakers’ as well as the tensions underlying their ways of caring and their conflicting responsibilities.

This article explores how health innovation designers articulate are and responsibility when designing new health technologies. Towards this end, we draw on Tronto’s ethic of care framework and Responsible Research and Innovation (RRI) scholarship to analyse interviews with Canadian health innovators (n ¼ 31). Our findings clarify how respondents: 1) direct their attention to needs and ways to improve care; 2) mobilise their skill set to take care of problems; 3) engage in what we call ‘care-making’ practices by prioritising key material qualities; and 4) operationalise responsiveness to caregivers and care-receivers through user-centred design. We discuss the inclusion of health innovation designers within the care relationship as ‘caremakers’ as well as the tensions underlying their ways of caring and their conflicting responsibilities.

Social innovation and high-quality agricultural systems are important for rural development. However, there is little information on methods for measuring the process and outcome of social innovation, particularly at the regional level. This study aimed to answer the research question: Which social innovation metrics can be applied to analyze rural development at the regional level? We carried out a systematic review of the literature on factors and indicators of social innovation, assessed the characteristics of social innovation in value-added agricultural production systems in developed countries, and proposed social innovation indicators for evaluating value-added agricultural systems in developing countries. Key elements of the process and outcome dimensions of social innovation were identified and used to generate factors, subfactors, indicators, and subindicators. The literature review showed that more research is needed on the outcomes of social innovation. Future studies should investigate the social transformations promoted by rural tourism and biodiversity valorization.

Social innovation and high-quality agricultural systems are important for rural development. However, there is little information on methods for measuring the process and outcome of social innovation, particularly at the regional level. This study aimed to answer the research question: Which social innovation metrics can be applied to analyze rural development at the regional level? We carried out a systematic review of the literature on factors and indicators of social innovation, assessed the characteristics of social innovation in value-added agricultural production systems in developed countries, and proposed social innovation indicators for evaluating value-added agricultural systems in developing countries. Key elements of the process and outcome dimensions of social innovation were identified and used to generate factors, subfactors, indicators, and subindicators. The literature review showed that more research is needed on the outcomes of social innovation. Future studies should investigate the social transformations promoted by rural tourism and biodiversity valorization.

Quelles sont les conditions de la maximisation de l’impact, et notamment sa pérennisation, du mécénat de compétence tech au profit des organisations dont la mission relève directement et prioritairement de la gestion du bien commun au service de l’intérêt général ? Telle est la question de recherche que la Fondation Devoteam a posée à l’ESSEC au moment de la mise en place de son programme #TechFor-People, afin de s’assurer de la pertinence de ce programme pour répondre aux besoins sur le long terme des structures de l’ESS (Économie Sociale et Solidaire) en transformation digitale. Afin de répondre à cette problématique l’ESSEC a réalisé une évaluation d’impact social fondée sur les cadres théoriques de la théorie du changement et de la théorie des parties prenantes, avec l’analyse de besoin, une collecte de données qualitatives ex-ante ainsi qu’une collecte de données quantitative ex-ante et ex-post. L’analyse de ces collectes révèle une dichotomie spécifique aux structures de l’ESS utilisant le programme que nous avons catégorisées en Tech Driven d’une part, ou Tech Powered d’autre part, avec des besoins et des conditions de pérennisation spécifiques en fonction de la catégorie qui leur correspond.

In the past twenty years, innovation has slowly, but steadily, become an important presence in development cooperation discourse and practice. The ambitious UN 2030 Sustainable Development Agenda has accelerated this trend, providing a strong framework for the main argument in favour of an innovation agenda for international development: without new ideas and innovative solutions, solving the current global development challenges will not be possible. Although this innovation-push is in line with a wider predominant view of innovation as an inherently positive force of progress, that alone does not explain when, how, and why innovation becomes a key topic in the field. This paper seeks to fill this gap in the literature, providing an initial overview of innovation in development cooperation in the post-2000s. It argues, firstly, that innovation has always been part of international development policy and practice. Secondly, it links the recent strengthening of the innovation discourse to three trends in the systemic transformation of the field: the triumph of metrics-based agendas, the ICTs and digitalization revolutions, and the role of private sector actors. It concludes by critically assessing the implications of this narrative in changing the politics of innovation towards more inclusive sustainable development policies and practices.

In the past twenty years, innovation has slowly, but steadily, become an important presence in development cooperation discourse and practice. The ambitious UN 2030 Sustainable Development Agenda has accelerated this trend, providing a strong framework for the main argument in favour of an innovation agenda for international development: without new ideas and innovative solutions, solving the current global development challenges will not be possible. Although this innovation-push is in line with a wider predominant view of innovation as an inherently positive force of progress, that alone does not explain when, how, and why innovation becomes a key topic in the field. This paper seeks to fill this gap in the literature, providing an initial overview of innovation in development cooperation in the post-2000s. It argues, firstly, that innovation has always been part of international development policy and practice. Secondly, it links the recent strengthening of the innovation discourse to three trends in the systemic transformation of the field: the triumph of metrics-based agendas, the ICTs and digitalization revolutions, and the role of private sector actors. It concludes by critically assessing the implications of this narrative in changing the politics of innovation towards more inclusive sustainable development policies and practices.

Social businesses, despite having a huge potential to generate substantial and sustainable value, are often structurally and financially fragile. Technological interventions, such as social media analytics, big data, Internet of Things, and blockchain can help social businesses by leveraging the practices towards financial and operational sustainability. This study is the first of its kind in that it analyses existing scholarly works on social businesses using bibliometric analysis. In so doing, this paper presents an in-depth statistical analysis of the literature on technological interventions in sustainable social business, showcasing the development of the scholarship, major themes, and possible future research trajectories. The SCOPUS database is used to identify a large section of articles. The study shows that most of the work in social business has been done by scholars based in developed countries, with limited contributions emanating from developing countries. The study proposes a framework for the use of technology in sustainable social businesses with focus areas of research such as social innovation, digital technology, information systems, and decision making for sustainability. The results show that digital technologies are increasingly being accepted as tools for the sustainability and scalability of social businesses. The paper offers useful recommendations for future research in relevant fields.

Social entrepreneurship is today an imperative across the world. The scarcity of resources, the needs of the growing population, and the growing burden on the environment have made people realize a need for organizations that can be profitable while bringing positive change in society and the environment. Sustainable, out-of-the-box solutions are required for solving social challenges. The onus of providing these solutions are often taken by aspiring entrepreneurs, who see opportunity in the challenges and are willing to take risks to create innovative and effective solutions for society’s benefit. The chapter elucidates the meaning of social entrepreneurship, the difference between commercial and social entrepreneurship, the models of social enterprises in practice, and the recommended methodology to evaluate social impact. The chapter features international case studies (through secondary research) and cases about social entrepreneurs who have dramatically improved the lives of people while being financially sustainable – an organization like SELCO Solar Lights Private Ltd, ARMAAN, Yellow Leaf and Arvind Eye Hospital, and many others have provided solutions for the economically weaker section of society. Many of these new-age social entrepreneurs use Big Data and artificial intelligence to ensure that their initiatives create greater social change. Some of these initiatives are highlighted in the chapter.