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Mosaic est le pôle multidisciplinaire de formation et de recherche d’HEC Montréal spécialisé en management de l’innovation et de la créativité. Mosaic est un accélérateur d’innovation et de créativité. La mission de Mosaic est d’aider les dirigeants et les organisations à relever le défi de l’innovation en s’inspirant de méthodologies issues de l’industrie créative, et en faisant évoluer leur pratique.
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Mosaic est le pôle multidisciplinaire de formation et de recherche d’HEC Montréal spécialisé en management de l’innovation et de la créativité. Mosaic est un accélérateur d’innovation et de créativité. La mission de Mosaic est d’aider les dirigeants et les organisations à relever le défi de l’innovation en s’inspirant de méthodologies issues de l’industrie créative, et en faisant évoluer leur pratique.
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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.
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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.
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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.
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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.
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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
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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
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Cet article rend compte de la manière dont les organisations internationales pourraient s’approprier la démarche délibérative à l’occasion de leurs efforts de régulation éthique de l’IA en présentant le projet de la délibération internationale intitulée « Dialogue inclusif sur l’éthique de l’intelligence artificielle (IA) » (ODAI) menée par Algora Lab - Université de Montréal et Mila - Institut québécois d’intelligence artificielle. Ce projet délibératif portait sur le premier instrument normatif mondial en éthique de l’IA rédigé par l’UNESCO. L’ODAI se démarque par sa portée internationale, le nombre de personnes consultées et sa réalisation en ligne. Après une présentation du cadre méthodologique et théorique de la délibération sur l’éthique de l’IA, nous opérons une analyse critique du processus et nous proposerons finalement des recommandations pratiques pour de futures délibérations en éthique de l’IA.
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The formation of social entrepreneurial intention (SEI) is a topic that attracts scholars’ attention recently. Previous studies in the literature mention the importance of personal background on the formation of such intentions (Mair and Noboa, in: Social entrepreneurship: How intentions to create a social venture are formed. In “social entrepreneurship” (pp. 121–135). Palgrave Macmillan, London, 2006); Dorado in Journal of Developmental Entrepreneurship 11:1–24, 2006; Scheiber in VOLUNTAS International Journal of Voluntary and Nonprofit Organizations. 27:1694–1717, 2016; Bacq and Alt in Journal of Business Venturing 33:333–350, 2018; Hockerts in Journal of Social Entrepreneurship 9:234–256, 2018). However, these studies often use samples from a limited number of countries and/or regions. The aim of this study is twofold. First, this study aims to examine whether the main antecedents of SEI (major hardship, radical change, encountering others’ hardship, and role model) offered in our previous study (Asarkaya and Keles Taysir in Nonprofit Management and Leadership 30:155–166, 2019) based on a sample from a specific country, is applicable within a global context and across different fields. Second, various functions of the main antecedents that lead to the formation of SEI are explored. The list of Ashoka fellows is utilized, and the personal details of 255 social entrepreneurs are analyzed. There are some common patterns in these narratives, supporting the potential influence of the main antecedents. In addition, the weights of these antecedents vary across different fields; and they have distinct functions through which SEI is formed.
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The formation of social entrepreneurial intention (SEI) is a topic that attracts scholars’ attention recently. Previous studies in the literature mention the importance of personal background on the formation of such intentions (Mair and Noboa, in: Social entrepreneurship: How intentions to create a social venture are formed. In “social entrepreneurship” (pp. 121–135). Palgrave Macmillan, London, 2006); Dorado in Journal of Developmental Entrepreneurship 11:1–24, 2006; Scheiber in VOLUNTAS International Journal of Voluntary and Nonprofit Organizations. 27:1694–1717, 2016; Bacq and Alt in Journal of Business Venturing 33:333–350, 2018; Hockerts in Journal of Social Entrepreneurship 9:234–256, 2018). However, these studies often use samples from a limited number of countries and/or regions. The aim of this study is twofold. First, this study aims to examine whether the main antecedents of SEI (major hardship, radical change, encountering others’ hardship, and role model) offered in our previous study (Asarkaya and Keles Taysir in Nonprofit Management and Leadership 30:155–166, 2019) based on a sample from a specific country, is applicable within a global context and across different fields. Second, various functions of the main antecedents that lead to the formation of SEI are explored. The list of Ashoka fellows is utilized, and the personal details of 255 social entrepreneurs are analyzed. There are some common patterns in these narratives, supporting the potential influence of the main antecedents. In addition, the weights of these antecedents vary across different fields; and they have distinct functions through which SEI is formed.
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In an increasingly globalized world, the challenges of society need to be tackled not by single organisations but by a multitude of stakeholders. Universities can contribute by extending their role and by collaborating with external stakeholders. This study employs qualitative methods to explore how a university engages with its innovation ecosystem through two different projects.The findings, connected to the development of educational and digital systems,show: 1) evidence of two extreme approaches to external stakeholder engagement and 2) three levels of tensions (multi-layered tensions) - on an overarching level, between stakeholder groups, and within groups of stakeholders. The contribution connects to literature on open innovation, quadruple helixes and lastly to university social innovation, especially responsibility diffusion.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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