Abstract

Abstract
Network effects occur when the benefit that agents derive from a good or service depends on how many other agents adopt the same good or service. This strategic complementarity between consumers' actions has several implications on tie behavior of firms: For instance, firms need to gain advantage from early marketing stages. Network effects are intrinsically a dynamic phenomenon: past consumption of the good influences the utility of present consumers. This effect can be either direct, when consumers value interaction with their peers, and/or indirect, through an increase in the quality of the good. This chapter surveys the literature on dynamic network effects. First we provide general formulations for the modelization of network effects in a dynamic setting. Second, we analyse recent developments in the literature on firms' strategies in the context of dynamic network effects. We survey the literature both on monopoly and oligopoly markets. In the case of oligopoly markets, we distinguish between situations in which firms produce horizontally and vertically differentiated goods. Main results on pricing and evolution of market shares are exposed.

Abstract
This conceptual paper is developed in the realm of strategic change communication. The purpose of this paper is to present our Business Narrative Modelling Language (BNML) (Oliveira and Ferreira, 2010a) as a tool for facilitating change. We illustrate how BNML has been used in real life cases to discuss strategy. Following data collection using a qualitative methodology and an analysis of the "As-Is" situation we proceed to construct a representation of the future desired ("To-Be") situation, in both situations using BNML. We start by defining the organizational actors relevant to value creation, we then map out their interactions in the organizational context, and study how relevant deliverables are exchanged, both tangible and intangible, along various storylines, one per actor. The social interaction leading to value creation happens according to a pattern sequence (using patterns taken from Bjork and Holopainen, 2005, which are intuitively comprehensible) and is instantiated according to an Enterprise Ontology (Uschold et al., 1998) (Oliveira and Ferreira, 2010a, b). By combining various sensemaking strategies such as the narrative, visual mapping and quantification our BNML scores high on accuracy, simplicity and generality (Langley, 1999) thus providing an attractive alternative to other techniques available to researchers and consultants and used to "connect and organize dispersed organizational knowledge" (Huff and Jenkins, 2002, p. 14).

Abstract
Innovation is today a widely used buzzword in the enterprises environments, because it is seen today as the support for long-term surviving and a lever for the creation of new and differentiated products or services. The Fuzzy Front-End of Innovation (FFE) is often experimental, involving strong interaction with the end-users. This enables the knowledge transfer from users, communities or Collaborative Innovation Networks to organizations. Enterprises may master a set of Dynamic Capabilities in order to manage, learn and integrate that shared knowledge. Today, using Web 2.0 applications, users are able to easily join together, share ideas, catalog information, spread and share their knowledge in a variety of ways. This paper presents a model to enable those Dynamic Capabilities using a Web 2.0 Mashup in the FFE of innovation.

Abstract
This paper looks at the adoption challenges of multiagent systems as an implementation of the intelligent manufacturing concept, which intends to offer a system characterized by its flexibility, reconfigurability, autonomy, reliability and learning capabilities. It describes the concept of multi-agent systems, its generic architecture and some relevant industrial implementations. Additionally, it analyzes the main multi-agent challenges looking for its benefits in the manufacturing industry, but also exposing its limitations and barriers for a widely industry adoption. © 2010 IEEE.

Abstract
The project XPRESS introduces a completely new scalable concept of an expertonic networked factory, which is composed by a co-ordinated team of specialized autonomous objects (expertons), each knowing how to do a certain process optimally. This paper looks in particular to the transport experton implementation, which is an experton responsible to carry material at the shop-floor. It is suggested an architecture based in a multi-agent approach that uses a conveyor belt transport experton to perform this task. Additionally, it is presented an implementation of the conveyor belt transport experton that uses the. NET framework integrated with the expertonic framework.