Organizational Survival and the Emergence of Collaboration Networks: a Multi-Agent Approach

• Main Author: Pedro Campos
• Other Authors: Faculdade de Economia
• Format: Others
• Language: Portuguese
• Published: 2019
• Online Access: https://repositorio-aberto.up.pt/handle/10216/7354

The present work deals with interactions between firms. Literature that inspired our work comes from organizational ecologists, evolutionary economics and Agent-Based Computational Economics. Our general belief is that organizations are adaptive at different levels of analysis: individually, or as a group. We dedicate a special attention to the network formation and regard networks as new forms of organizations.In order to understand these interactions and the different mechanisms of adaptation, that include learning and evolution, two studies have been developed in this work: CASOS and NetOrg. Our main objective with CASOS - Cellular Automata System for Organizational Survival - is to analyse the effects of a set of parameters (organizational density, size and age) in the founding and in the mortality of organizations. The best combination of these parameters will produce the best solution for the simulation. The cellular automata approach is embedded with a Genetic Algorithm that calibrates the parameters in order to validate the final solution with real data coming from the Portuguese Industry. We have observed similar tendencies between simulated and real data that represent the evolution of the number of industries in this region. We used survival analysis techniques that also confirm the capability of the model to reproduce the reality: the effect of the size on the mortality of the firms is negative and statistically significant.NetOrg - Adaptive Networks of Organizations - is a Multi-Agent framework that aims at analyzing the dynamics of organizational survival in cooperation networks. Firms cooperate horizontally (in the same market) or vertically with other firms. Cooperation decisions involve cognitive and microeconomic modelling. To validate our approach, we considered some evidences from three industrial real life examples: Automobile manufacturing, Textile and e-Marketplaces. We observed that organizations increase their stock of knowledge due to the spread of innovation, and that this is a direct consequence of the fact that organizations are linked to networks. The network is a mechanism undergoing adaptation, where the internal synergies shape the course of evolution.