Co-opetition of TV broadcasters in online video markets : a winning strategy?

This article focuses on TV broadcasters adopting co-opetition strategies for launching online video services. It is claimed that the emergence of online video platforms like YouTube and Netflix is driving TV broadcasters to collaborate with their closest competitors to reduce costs and reach the necessary scale in the global marketplace. The article sheds light on online video platforms that were developed following a co-opetition strategy (Hulu and YouView). The establishment of joint ventures in online video, however, has been scrutinised by competition authorities which fear that collaboration between close competitors lessens rivalry and reduces consumer choice. Therefore, several co-opetition projects (among others BBC’s Kangaroo and Germany’s Gold) have been prohibited by competition authorities

Activity-Centric Computing Systems

• Activity-Centric Computing (ACC) addresses deep-rooted information management problems in traditional application centric computing by providing a unifying computational model for human goal-oriented ‘activity,’ cutting across system boundaries. • We provide a historical review of the motivation for and development of ACC systems, and highlight the need for broadening up this research topic to also include low-level system research and development. • ACC concepts and technology relate to many facets of computing; they are relevant for researchers working on new computing models and operating systems, as well as for application designers seeking to incorporate these technologies in domain-specific applications

Modularity Archetypes and Their Coexistence in Technological Development: The Case of a Telecoms Company from Analogue Voice to 5G

Modularity is a key concept in the research and practice of information systems. Yet, it has been variously interpreted. Synthesizing the literature, we inductively develop a two-by-two matrix encapsulating two dualities of modularity: architectural vs. governance dimensions, and bottom-up vs. top-down perspectives. This matrix groups the literatures into four archetypical approaches to modularity (Engineering, Ecosystem, Generative and Logical). We next illustrate these archetypes through a qualitative study of a large global telecommunications firm. Drawing upon archival data and interviews, we show how each of these four approaches to modularity become dominant at different times, but also how they overlap and coexist

Ecosystem-Oriented Distributed Evolutionary Computing

We create a novel optimisation technique inspired by natural ecosystems, where the optimisation works at two levels: a first optimisation, migration of genes which are distributed in a peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. We consider from the domain of computer science distributed evolutionary computing, with the relevant theory from the domain of theoretical biology, including the fields of evolutionary and ecological theory, the topological structure of ecosystems, and evolutionary processes within distributed environments. We then define ecosystem- oriented distributed evolutionary computing, imbibed with the properties of self-organisation, scalability and sustainability from natural ecosystems, including a novel form of distributed evolu- tionary computing. Finally, we conclude with a discussion of the apparent compromises resulting from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102, arXiv:0910.067

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa