An Innovation Model for Collaborative Networks of SOA-Based Software Providers

Part 5: Service Orientation in Collaborative Networks

Orchestrating New Markets Using Cloud Services

Part 5: Service Orientation in Collaborative Networks

Enterprise Collaboration Framework for Managing, Advancing and Unifying the Functionality of Multiple Cloud-Based Services with the Help of a Graph API

Part 5: Service Orientation in Collaborative Networks

Methodological and Technological Support for the Coordination of Smart Networks of SMEs

Part 2: Behaviour and Coordination

Identifying social influence in complex networks: a novel conductance eigenvector centrality model

Identifying influential peers is an important issue for business to promote commercial strategies in social networks. This paper proposes a conductance eigenvector centrality (CEC) model to measure peer influence in the complex social network. The CEC model considers the social network as a conductance network and constructs methods to calculate the conductance matrix of the network. By a novel random walk mechanism, the CEC model obtains stable CEC values which measure the peer influence in the network. The experiments show that the CEC model can achieve robust performance in identifying peer influence. It outperforms the benchmark algorithms and obtains excellent outcomes when the network has high clustering coefficient.

Aplicaciones de los modelos de predicción bio-inspirados en la administración

Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.

Financing innovative start-ups in Portuguese context: what is the role of business angels networks?

Business angels provide both financing and managerial experience, which increase the likelihood of the survival of innovative start-ups. Over the last years, European countries with developing informal venture capital markets have seen governments support the creation of business angels networks (BANs) to increase and consolidate these markets. Using the Portuguese context to carry out the empirical work, this paper provides an assessment of value added provided by angels’ networks. A total of 88 useable responses were received and analysed using non-parametric statistical techniques. This paper demonstrates that is evidence of positive contribution of BANs in terms of bringing together investors and linking them with entrepreneur’s seeking finance. BANs played an important role in financing innovative start-ups also in peripheral regions. Results lead us to conclude that government support BANs would appear to be an effective mechanism to stimulate the angel market in developing informal venture capital markets. The conclusions of this paper are likely to have relevance for countries where there is growing interest in the potential of business angels as a means of financing innovative start-ups.