Modeling coordination in organizations and markets
Management Science
Organizational response: the cost performance tradeoff
Management Science
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Knowledge and Organization: A Social-Practice Perspective
Organization Science
Coordinating Expertise in Software Development Teams
Management Science
SLACER: A Self-Organizing Protocol for Coordination in Peer-to-Peer Networks
IEEE Intelligent Systems
Evolving specialisation, altruism, and group-level optimisation using tags
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
Preface to special issue on cooperation in selfish systems
Computational & Mathematical Organization Theory
| Hi-index | 0.00 |
The increasing knowledge intensity of jobs, typical of a knowledge economy, highlights the role of firms as integrators of know how and skills. As economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, firms need to allocate skills to tasks and traditional hierarchical control may result increasingly ineffective. In this work, we explore under what circumstances networks of agents, which bear specific skills, may self-organize in order to complete tasks. We use a computer simulation approach and investigate how local interaction of agents, endowed with skills and individual decision-making rules, may produce aggregate network structure able to perform tasks. To design algorithms that mimic individual decision-making, we borrow from computer science literature and, in particular, from studies addressing protocols that produce cooperation in P2P networks. We found that self-organization depends on imitation of successful peers, competition among agents holding specific skills, and the structural features of, formal or informal, organizational networks embedding both professionals, holding skills, and project managers, holding access to jobs.