Innovation la mise sur le marché mondial de nouveautés, de produits et de services nouveaux ou significativement améliorés ;l'adoption en leur sein d'une gestion de l'innovation, aussi basée sur des changements et des mesures internes améliorant[5] leur efficacité et leur efficience. Comprendre le concept d'innovation[6] implique que l'on distingue bien le résultat concret (produit, service, procédé, etc.) de l'action d'innover, du processus abstrait qui permet de les réaliser. Concrètement, une innovation[9],[10] — c'est quelque chose qui, produit ou reproduit en grand nombre et commercialisé ou déployé pour la première fois avec succès, a amélioré, changé, modifié, transformé ou révolutionné un secteur d'activité, une pratique sociale ou la vie d'un grand nombre d'individus, ceci le plus souvent de façon inattendue et inconsciente. Histoire et étymologies du concept et du terme d'innovation[modifier | modifier le code] Histoire du concept d'innovation[modifier | modifier le code] Henri Bergson. 5.
Knowledge management Knowledge management (KM) is the process of capturing, developing, sharing, and effectively using organizational knowledge.[1] It refers to a multi-disciplined approach to achieving organisational objectives by making the best use of knowledge.[2] An established discipline since 1991 (see Nonaka 1991), KM includes courses taught in the fields of business administration, information systems, management, and library and information sciences.[3][4] More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy.[5] Columbia University and Kent State University offer dedicated Master of Science degrees in Knowledge Management.[6][7][8] History[edit] In 1999, the term personal knowledge management was introduced; it refers to the management of knowledge at the individual level.[14] Research[edit] Dimensions[edit] The Knowledge Spiral as described by Nonaka & Takeuchi. Strategies[edit] Motivations[edit]
Demos | Publications From astronomy to activism, from surfing to saving lives, Pro-Ams - people pursuing amateur activities to professional standards - are an increasingly important part of our society and economy. For Pro-Ams, leisure is not passive consumerism but active and participatory, it involves the deployment of publicly accredited knowledge and skills, often built up over a long career, which has involved sacrifices and frustrations. The 20th century witnessed the rise of professionals in medicine, science, education, and politics. In one field after another, amateurs and their ramshackle organisations were driven out by people who knew what they were doing and had certificates to prove it. The Pro-Am Revolution argues this historic shift is reversing. Based on in-depth interviews with a diverse range of Pro-Ams and containing new data about the extent of Pro-Am activity in the UK, this report proposes new policies to support and encourage valuable Pro-Am activity.
Enterprise social networking Enterprise social networking focuses on the use of online social networks or social relations among people who share business interests and/or activities. Enterprise social networking is often a facility of enterprise social software (regarded as a primary component of Enterprise 2.0), which is essentially social software used in "enterprise" (business/commercial) contexts. It encompasses modifications to corporate intranets (referred to as social intranets) and other classic software platforms used by large companies to organize their communication, collaboration and other aspects of their intranets. Enterprise social networking is also generally thought to include the use of a standard external social networking service to generate visibility for an enterprise. History[edit] Social networking sites started to form in the 1990s; an example of these websites is Theglobe.com, which began in 1995. Emerging trends[edit] Business impacts[edit] Applications[edit] Issues[edit] Transparency[edit]
Les Shadoks Un article de Wikipédia, l'encyclopédie libre. Les Shadoks Titre de la série Les Shadoks. Synopsis[modifier | modifier le code] La série relate les différentes histoires et mésaventures des Shadoks, des êtres anthropomorphes aux apparences d'oiseaux (à ce jour, toujours non-identifiés) rondouillards possédant de longues pattes et de petites ailes ridicules. Les Shadoks ont pour ennemis principaux — ou plutôt comme rivaux[pas clair] — les Gibis qui leur sont intellectuellement supérieurs. Les Shadoks possèdent pour tout vocabulaire quatre mots monosyllabiques : « Ga, Bu, Zo, Meu ». Genèse[modifier | modifier le code] Avant les Shadoks[modifier | modifier le code] Jacques Rouxel propose[Quand ?] Prémices[modifier | modifier le code] Réalisation[modifier | modifier le code] Réception[modifier | modifier le code] Séries[modifier | modifier le code] Les trois premières séries n'ont jamais eu de titre officiel[8] et la quatrième série est nommée « Les Shadoks et le big blank ».
Open innovation Open innovation is a term promoted by Henry Chesbrough, adjunct professor and faculty director of the Center for Open Innovation at the Haas School of Business at the University of California,[1] in a book of the same name,[2] though the idea and discussion about some consequences (especially the interfirm cooperation in R&D) date as far back as the 1960s[citation needed]. Some instances of open innovation are Open collaboration,[3] a pattern of collaboration, innovation, and production. The concept is also related to user innovation, cumulative innovation, know-how trading, mass innovation and distributed innovation. “Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology”.[2] Alternatively, it is "innovating with partners by sharing risk and sharing reward. Advantages[edit] Disadvantages[edit] Models of open innovation[edit] See also[edit]
Complex adaptive system They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.[1][2] Overview[edit] The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. The fields of CAS and artificial life are closely related. The study of CAS focuses on complex, emergent and macroscopic properties of the system.[3][11][12] John H. General properties[edit] What distinguishes a CAS from a pure multi-agent system (MAS) is the focus on top-level properties and features like self-similarity, complexity, emergence and self-organization. Characteristics[edit] Some of the most important characteristics of complex systems are:[14] Robert Axelrod & Michael D.
Collaborative network A collaborative network, is a network consisting of a variety of entities (e.g. organizations and people) that are largely autonomous, geographically distributed, and heterogeneous in terms of their operating environment, culture, social capital and goals, but that collaborate to better achieve common or compatible goals, and whose interactions are supported by computer networks. The discipline of collaborative networks focuses on the structure, behavior, and evolving dynamics of networks of autonomous entities that collaborate to better achieve common or compatible goals.[1][2] There are several manifestations of collaborative networks, e.g.:[1] Virtual enterprise (VE).Virtual Organization (VO).Dynamic Virtual Organization.Extended Enterprise.VO Breeding environment (VBE).Professional virtual community (PVC).Business Ecosystem.Virtual manufacturing network Applications[edit] Elements[edit] The seven essential elements of collaborative networks: Reference models[edit] Challenges[edit]
Système complexe adaptatif Un article de Wikipédia, l'encyclopédie libre. Complex Adaptive System Un système complexe adaptatif ou système complexe auto-adaptatif est l'ensemble des cas particuliers d'un système complexe capable de s'adapter à son environnement par des expériences d'apprentissage. Le terme anglais complex adaptive systems (CAS) a été introduit par l'Institut interdisciplinaire de Santa Fe notamment par John H. Observations[modifier | modifier le code] En 1962, Vero Copner Wynne-Edwards a observé la sélection de groupe à l’œuvre dans les communautés d’oiseaux sauvages. Par ailleurs, David Sloan Wilson (en) a démontré qu’un réseau social qui applique les règles du « système adaptatif complexe » constitue la plus puissante machine à apprendre et gagne presque à tous les coups[1]. Exemples[modifier | modifier le code] Notes et références[modifier | modifier le code] ↑ (fr) Le principe de Lucifer : le cerveau global, Howard Bloom (trad.
Knowledge engineering Knowledge engineering (KE) was defined in 1983 by Edward Feigenbaum, and Pamela McCorduck as follows: KE is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise.[1] It is used in many computer science domains such as artificial intelligence,[2][3] including databases, data mining, bioinformatics, expert systems, decision support systems and geographic information systems. Various activities of KE specific for the development of a knowledge-based system: Assessment of the problemDevelopment of a knowledge-based system shell/structureAcquisition and structuring of the related information, knowledge and specific preferences (IPK model)Implementation of the structured knowledge into knowledge basesTesting and validation of the inserted knowledgeIntegration and maintenance of the systemRevision and evaluation of the system. Knowledge engineering principles[edit] Bibliography[edit]
Global Management