Adaptive build-up and breakdown of trust: An agent based computational approach

This article employs Agent-Based Computational Economics (ACE) to investigate whether, and under what conditions, trust is viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents develop trust in a partner as a function of observed loyalty. They select partners on the basis of their trust in the partner and potential profit, with adaptive weights. On the basis of realized profits, they adapt the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Trust and loyalty turn out to be viable under fairly general conditions.Agent-based computational economics;Inter-firm relations;Transaction costs;Governance;Trust;Complex adaptive systems

Network Embeddedness and the Exploration of Novel Technologies: Technological Distance, Betweenness Centrality and Density

In this paper we analyze the innovative performance of alliance networks as a function of the technological distance between partners, a firm's network position (centrality) and total network density.We study how these three elements of an alliance network, apart and in combination, affect the 'twin tasks' in exploration, namely novelty creation on the one hand and its efficient absorption on the other hand.For an empirical test, we study technology-based alliance networks in the pharmaceutical, chemical and automotive industry.innovation networks;cognitive distance;centrality;density

Agent based computational model of trust

This paper employs the methodology of Agent-Based Computational Economics (ACE) to investigate under what conditions trust can be viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents adapt their trust in a partner, the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Adaptation occurs on the basis of realized profit. Trust turns out to be viable under fairly general conditions

Permeability characteristics of human endothelial monolayers seeded on different extracellular matrix proteins.

OBJECTIVE: To investigate whether endothelial monolayer permeability changes induced by inflammatory mediators are affected by the extracellular matrix protein used for cell seeding. METHODS: Human umbilical venular endothelial cells (HUVEC) were grown to confluent monolayers on membranes coated with either collagen, fibronectin or gelatin. The permeability to albumin and dextran was then assessed, both under normal conditions and after treatment with tumor necrosis factor-alpha (TNF-alpha) and bacterial lipopolysaccharide (LPS). RESULTS: With any of the three protein coatings, tight junctions were formed all over the monolayers. The permeability of the coated membranes to albumin and dextran was reduced strongly by confluent monolayers; the relative reduction was similar for the three matrix proteins used. Pre-incubation of the monolayers with either TNF-alpha or LPS increased permeability dose dependently. However, the relative increase due to either treatment was independent of the protein used for membrane coating. CONCLUSION: The extracellular matrix protein used for initial seeding of endothelial cultures plays a minor role in determining the permeability changes induced in HUVEC monolayers by inflammatory mediators