Reputation-based trust evaluations through diversity

Non peer reviewedPostprin

Innovation Clusters: Combining Physical and Virtual Links

Innovation is increasingly seen as a collective action which involves many different actors operating in a cluster context. These clusters are usually conceived as local agglomerations. In this paper it will be argued that they are an important tool to study innovation, but the globalisation of companies and markets and the specific requirements of innovation processes require the expansion of cluster concepts towards virtual dimensions. It will be shown that the combination of local and virtual cluster links improves access to essential resources in innovation. An examples taken from the automotive component sector will illustrate the concept.Innovation, cluster dynamics, automotive components.

The role of decision confidence in advice-taking and trust formation

In a world where ideas flow freely between people across multiple platforms, we often find ourselves relying on others' information without an objective standard to judge whether those opinions are accurate. The present study tests an agreement-in-confidence hypothesis of advice perception, which holds that internal metacognitive evaluations of decision confidence play an important functional role in the perception and use of social information, such as peers' advice. We propose that confidence can be used, computationally, to estimate advisors' trustworthiness and advice reliability. Specifically, these processes are hypothesized to be particularly important in situations where objective feedback is absent or difficult to acquire. Here, we use a judge-advisor system paradigm to precisely manipulate the profiles of virtual advisors whose opinions are provided to participants performing a perceptual decision making task. We find that when advisors' and participants' judgments are independent, people are able to discriminate subtle advice features, like confidence calibration, whether or not objective feedback is available. However, when observers' judgments (and judgment errors) are correlated - as is the case in many social contexts - predictable distortions can be observed between feedback and feedback-free scenarios. A simple model of advice reliability estimation, endowed with metacognitive insight, is able to explain key patterns of results observed in the human data. We use agent-based modeling to explore implications of these individual-level decision strategies for network-level patterns of trust and belief formation

How Can Social Networks Ever Become Complex? Modelling the Emergence of Complex Networks from Local Social Exchanges

Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a diverse population. Agent use simple decision heuristics, based on imperfect, local information. Computer simulations show that the topological structure of the emergent social network depends heavily upon two sets of conditions, harshness of the exchange game and learning capacities of the agents. Further analysis show that a combination of these conditions affects whether star-like, small-world or power-law structures emerge.Complex Networks, Power-Law, Scale-Free, Small-World, Agent-Based Modeling, Social Exchange Theory, Structural Emergence

Talking Nets: A Multi-Agent Connectionist Approach to Communication and Trust between Individuals

A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents’ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Grice’s (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions

The Importance of Clusters for Sustainable Innovation Processes: The Context of Small and Medium Sized Regions

The purpose of the current paper is to provide a critical state-of-the-art review of current research on clusters and its correlation to innovation dynamics in small and medium-sized regions. In particular, we focus on the systematization of the main concepts and theoretical insights that are tributary to the cluster overview in terms of its relevance for the sustainability of the innovation processes, knowledge production and diffusion, which take place inside small and medium-sized regions. The present working paper takes into account the initial studies on English industrial districts (in the nineteenth century), passing through the Italian industrial districts (in the 70s and 80s of the twentieth century), until the modern theories of business clusters and innovation systems. These frameworks constitute the basis of an approach to endogenous development, which gives a central role to the interaction between economic actors, the society and the institutions and to the identification, mobilization and combination of potential resources within a particular geographical area.Cluster; Innovation; Endogenous development; Territory.

Finding the right answer: an information retrieval approach supporting knowledge sharing

Knowledge Management can be defined as the effective strategies to get the right piece of knowledge to the right person in the right time. Having the main purpose of providing users with information items of their interest, recommender systems seem to be quite valuable for organizational knowledge management environments. Here we present KARe (Knowledgeable Agent for Recommendations), a multiagent recommender system that supports users sharing knowledge in a peer-to-peer environment. Central to this work is the assumption that social interaction is essential for the creation and dissemination of new knowledge. Supporting social interaction, KARe allows users to share knowledge through questions and answers. This paper describes KARe�s agent-oriented architecture and presents its recommendation algorithm

Collective efficiency strategies: a policy instrument solution to boost competitiveness in low-density territories

This paper motivates the focus of EU cohesion policy at large and the territorial cooperation tools on the economic development of territories featuring impoverishing growth associated to low population density. An innovative policy approach to help solving this problem in many Member States is put forward here. It is based on the economic concept of “collective efficiencyâ€. It should be understood as a proposal to improve EU cohesion policy in the next programming period. As such, the paper suggests actual ideas to be included in the forthcoming Common Strategic Framework and Development and Investment Partnership Contracts.