Thriving Innovation Ecosystems: Synergy Among Stakeholders, Tools, and People

An innovation ecosystem is a multi-stakeholder environment, where different stakeholders interact to solve complex socio-technical challenges. We explored how stakeholders use digital tools, human resources, and their combination to gather information and make decisions in innovation ecosystems. To comprehensively understand stakeholders' motivations, information needs and practices, we conducted a three-part interview study across five stakeholder groups (N=13) using an interactive digital dashboard. We found that stakeholders were primarily motivated to participate in innovation ecosystems by the potential social impact of their contributions. We also found that stakeholders used digital tools to seek "high-level" information to scaffold initial decision-making efforts but ultimately relied on contextual information provided by human networks to enact final decisions. Therefore, people, not digital tools, appear to be the key source of information in these ecosystems. Guided by our findings, we explored how technology might nevertheless enhance stakeholders' decision-making efforts and enable robust and equitable innovation ecosystems

Systems of innovation and innovation ecosystems: a literature review in search of complementarities

This paper aims to clarify to what extent the emerging theory of innovation ecosystems (IE) and the theory of systems of innovation (SI) are complementary and then identify how its communities could benefit from cross-fertilization. We performed a critical literature review of both topics using meta-synthesis as method to identify, analyze and compare the two theories. Using a framework, this paper explores the elements belonging to each theory’s domain, in order to identify the key factors necessary to compare the two theories. The results of this analysis show that both theories involve the assessment of three key aspects: the understanding of innovation activities, the role of the agents involved, and the interaction and resulting networks among them. A similarity was found showing that these two different theories are applications of System Thinking approach. Another finding, which has not been mentioned in previous research on the topic, is that the construction of the initial concepts of the IE theory was originally rooted in several SI elements. Finally, we found key factors that may be the cross-fertilization link between the two communities that represent each theory

Exploring the relational dimension of Local Innovation Systems. The case of Biopharma in Greater Boston Area

This thesis provides an original framework to study the relational dimension of local innovation systems (LIS). More specifically, this work aims to explore which configurations of network structure and network portfolio composition are associated to high performing LISs by conducting a Social Network Analysis of the benchmark case of Greater Boston Biopharma ecosystem and by interviewing key stakeholders in the area

Assessment of innovation ecosystems for technology roadmapping at firm level

RÉSUMÉ: L'environnement économique n'est plus le même et sa complexité évolue à une vitesse défiante aux entreprises basées sur la technologie. Même les entreprises non technologiques souffrent indirectement des conséquences du changement technologique et social. La relation entre les acteurs du marché est plus dynamique, elle est “en ligne”. En quelques secondes, les informations stratégiques peuvent être entre les mains d'un concurrent d'un simple clic sur un bouton de la souris. De nos jours la façon dont nous envisageons la concurrence de points de vue industriels, sectoriels ou des clusters a ses limites ignorent de nombreux aspects commerciaux tels que la valeur capturée des relations informelles des acteurs sociaux, la coévolution entre entreprises concurrentes, les communautés sociales créant de la valeur pour les entreprises et autres qui montrent l'obsolescence de ces perspectives et des outils associés. Depuis le travail fondateur de James Moore intitulé “The Death of Competition” publié au début des années 90, on a beaucoup conjecturé sur la “nouvelle” innovation. Selon Moore, nous nous trouvons dans un scénario où la frontière de l'entreprise n'a aucune signification, mais son interaction intense avec d'autres acteurs indique sa capacité à innover dans un lieu appelé “écosystème de l’innovation”. Ce lieu est l'endroit où l'innovation a son importance grâce à un flux continu de connaissances qui capturent et créent de la valeur pour le client. Tout cela est articulé à travers des modèles commerciaux ouverts impliqués dans les interactions entre tous les acteurs participant à l'écosystème. Mais comment cartographier un écosystème, ses relations? Ses modèles d'affaires? Et surtout, comment identifier et évaluer ses stratégies bénéficiant uniquement aux entreprises et aux acteurs qui intègrent ce lieu ? Ces questions constituent cette recherche. Dans notre revue de littérature, nous identifions “l’état de l’art” des écosystèmes d'innovation (article 1). Pour comprendre les aspects empiriques de ce nouveau lieu d'innovation, nous avons développé une analyse de terrain à travers des tests, des conjectures précédentes, des comparaisons et une évaluation des résultats trouvés (article 2). En identifiant les concepts par l'observation sur le terrain et une revue littéraire systématique, nous avons développé un outil d'analyse pour l'évaluation de l'écosystème de l'innovation intégrée à la planification stratégique technologique (article 3). Les considérations de cette expérience sont partagées dans la section de discussion générale de la thèse et la dernière section concerne nos conclusions. Cette section identifie les principales contributions de la recherche entreprise par les limitations de la recherche, mais aussi les opportunités à saisir pour la recherche future dans le domaine de l'innovation technologique.----------ABSTRACT: The economic environment is no longer the same and its complexity changes at a challenging speed for technology-based companies. Even non-technological companies suffer in some indirect way the results of technological and social change. The relationship between market players is more dynamic, it is “online”. In a few seconds, strategic information can be in the hands of the opponent with just a click on the mouse button. Nowadays, the way we view competition from industrial, sectoral or cluster perspectives has its limitations and ignores many business aspects like the captured value from informal relationships of social actors, the co-evolution between competing companies, the social communities creating value for companies and others that show the obsolete of these perspectives and related tools. Since James Moore's seminal work entitled “The Death of Competition” published in the early 1990s, much has been conjectured about the “new” innovation. According to Moore, we are inside of a scenario where the frontier of the firm has no significance but its intense interaction with other actors indicates its ability to innovate in a locus named the “innovation ecosystem”. This locus is where innovation takes place through the continuous flow of knowledge that captures and creates value for the customer. All of this is articulated through open business models involved in interactions between all actors participating in the ecosystem. But how to map an ecosystem, its relationships? its business models? And above all how to identify and assess its strategies benefiting only the companies and actors that integrate this locus. These issues make up this research. In our literature review, we identify the “state of the art” of innovation ecosystems (article 1). To understand the empirical aspects of this new locus of innovation, we develop a grounded analysis and speculations by testing, comparing and evaluating the results found (article 2). By identifying constructs through field observation and a systematic evidence literary review we developed an analytical tool for assessment of innovation ecosystem integrated with technological strategic planning (article 3). The considerations of this experience are shared in the general discussion chapter of the thesis, and the final chapter is concerning our conclusions. This chapter identifies the main contributions of the research undertaken by research limitations but also opportunities to be taken in future research in the field of technology innovation

Ecossistema de inovação para eficiência do gasto público : uma pesquisa-ação no Ministério da Educação

Tese (doutorado) — Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade e Gestão Pública, Programa de Pós-Graduação em Administração, 2021.Em um mundo de organizações cada vez mais especializadas, uma única organização normalmente não possui recursos internos para o desenvolvimento e para a implantação de uma inovação ou de uma melhoria significativa da gestão. O ecossistema de inovação possibilita construir uma estratégia em rede permitindo que as organizações possam colaborar e evoluir conjuntamente, sobretudo em organizações públicas em que é crescente a expectativa da população por melhores serviços e os recursos são escassos. Assim, para o desenvolvimento desta tese, propõe-se a utilização da teoria do ecossistema de inovação para estruturar mecanismos para eficiência do gasto, no âmbito das instituições da rede federal brasileira de educação (universidades e institutos federais). Essa escolha se justifica pela lacuna apontada por Grobbelaar (2018) de que, embora o ecossistema de inovação tenha sido explorado no contexto empresarial, sua aplicação no contexto universitário continua escassa. A pesquisa foi realizada com abordagem qualitativa e o procedimento utilizado foi a pesquisa-ação, com a aplicação no Ministério da Educação (MEC), e com foco nas 110 instituições da rede federal brasileira de educação. Após o levantamento e análise das publicações científicas sobre a estruturação do ecossistema de inovação e sobre a eficiência do gasto público, foi construído o modelo denominado Ecossistema de Inovação para Eficiência do Gasto Público em Instituições da Rede Federal Brasileira de Educação. O modelo é composto por três camadas: a (1) camada central, composta pelo MEC como órgão supervisor e que exerce influência sobre as instituições; a (2) camada plataforma, que deve ser fornecida pela organização central; e a (3) camada de desenvolvimento e aplicação composta por atores que têm relacionamentos próximos com as atividades do ecossistema de inovação. Como resultados foram estruturados no ecossistema de inovação, 16 projetos para melhoria da eficiência do gasto nas instituições, sendo nove projetos novos, que foram desenvolvidos a partir da estrutura do ecossistema de inovação e sete projetos existentes, que foram incorporados ao ecossistema e disponibilizados para todas as instituições. Por fim, entende-se que os objetivos foram alcançados, com destaque para as seguintes contribuições principais: a construção de um modelo de ecossistema de inovação para eficiência do gasto nas instituições da rede federal brasileira de educação e a apresentação de como as instituições públicas, sobretudo aquelas ligadas a área de educação federal, podem se organizar e articular desenhos de parcerias para promover a inovação e a eficiência do gasto público.In a world of increasingly specialized organizations, a single organization usually does not have the internal resources to develop and implement an innovation or a significant improvement in management. The innovation ecosystem makes it possible to build a network strategy allowing organizations to collaborate and evolve together, especially in public organizations, in which people's expectation for better services is growing and resources are scarce. Consequently, to develop this thesis, the case study seeks to use the ecosystem of innovation theory to structure mechanisms for efficiency of expenditure, within the scope of the institutions of the Brazilian federal education network (universities and federal institutes). This choice is justified by the gap pointed out by Grobbelaar (2018), who stated that although the innovation ecosystem has been explored in the business context, its application in the university context remains scarce. The study was conducted with a qualitative approach and the procedure used was action research, with application in the Ministry of Education (MEC) and focusing on 110 institutions of the Brazilian federal education network. After surveying and analyzing scientific publications on the structuring of the innovation ecosystem and on the efficiency of public spending, the model called Innovation Ecosystem for Public Spending Efficiency in Institutions of the Brazilian Federal Education Network was built. The model is composed of three layers: (1) the central layer, with the MEC as a supervisory body in which exerts influence over the institutions; the (2) platform layer that must be provided by the central organization; and the (3) development and application layer composed of actors that have close relationships with the activities of the innovation ecosystem. As a result, sixteen projects were structured in the innovation ecosystem to improve the efficiency of spending in institutions, nine new projects, which were developed from the structure of the innovation ecosystem and seven existing projects, which were incorporated into the ecosystem and made available for all institutions. Finally, it is understood that the objectives were achieved, with emphasis on the following main contributions: the construction of an innovation ecosystem model for efficient spending in institutions of the Brazilian federal education network; and the presentation of how public institutions, especially those linked to the area of federal education, can organize and articulate partnership designs to promote innovation and efficiency in public spending

Responsible Innovation in Business:A Framework and Strategic Proposal

Companies are the main contributors and developers of technological innovation, generating an enormous impact on people’s lives. Unrestricted innovation fosters both economic development and inventiveness. Real-world situations, however, pose valid questions about whether science and technology can be left to operate autonomously in the market without regulation and societal guidance. Some headline stories include Volkswagen’s emission scandal, misuse of data in the Facebook–Cambridge Analytica case, or the Pegasus surveillance spyware targeting human rights activists, journalists and dissidents. In a fast-changing world increasingly dependent on technology and with business wielding enormous power, one may ask how to ensure that the impact of technology on humans and society will lead to improved technologies that are sustainable, ethically acceptable and socially desirable. What do our fundamental rights and values look like in the techno- and digital age? Who has the right to decide what the world should look like and how we want to live? And what role and responsibilities do companies have regarding their technological innovations? The main challenge taken on in this work is the problem of the responsibility of companies for their technological innovation, which can be placed in the context of the ongoing discussions around the nature of companies’ responsibility towards society and the environment. This work explores and explicates a strategic approach to responsible innovation in business

Modeling the innovation ecosystem and development of a dynamic innovation index

The topic of innovation currently generates a tremendous amount of interest around the world. Innovation is considered an essential part of the solution to creating more jobs and improving the socio-economic conditions of many countries around the globe. Innovation comes about through the existence of many interrelated solutions to socio-economic problems in an extensively interconnected network, which create value for each other. Such a complex creativity and innovation value-creating network is here called an Innovation Ecosystem (IE). The main objective of this dissertation research is to improve the current understanding of the IE by developing a simulation model that uses a broad set of relevant static and dynamic variables and incorporates the principles of system dynamics (SD). The proposed model, which is named the IECO-model is based on the relationships between 91 variables and the combined influences of the 43 parameters. Available data for 32 countries, representing a full span of GDP worldwide, was used to study the level of innovation in each of these countries. The result of the developed IECO-model is a novel ranking of the level of innovation through a dynamic innovation index, called the DII. The DII is a new tool to evaluate the innovation and entrepreneurship level of a given country in the context of the global economy. The most significant differentiator from other existing indices of innovation is that the DII is focusing more on the entrepreneurship qualities in 19 of the 43 parameters by looking at cultural values and belief systems, the social context, existing entrepreneurial culture, innovation attitudes, and mentality of each of the considered countries. According to DII-based ranking, the ten most innovative countries in the world are 1. Switzerland, 2. USA, 3. Finland, 4. Netherlands, 5. Iceland, 6. Sweden, 7. Germany, 8. Denmark, 9. The United Kingdom, and 10. Austria