Agent-based multi-edge network simulation model for knowledge diffusion through board interlocks

摘要

Interlocking directors play a crucial role in corporate decision making and profitability of an organization. They also act as information channels between corporate entities and various hypotheses have been proposed in the literature regarding effectiveness of board-interlocks. Generally these hypotheses are tested against country specific data over a given time period. Therefore, a network diffusion model of companies, with interlocking directors as the links, would serve as an expert system to test hypotheses and policies in a more general framework. Such a model will also be useful in decision making and identifying organizations and directors for board-interlock for optimal performance. In this paper, we propose a hybrid multi-edge directed weighted network model and an agent based simulation scheme for analysing the diffusion process through board interlocks. The general framework introduced in this work is capable of incorporating individual characteristics of directors such as personal identification with a corporate firm. We test the hypothesis that the organisational affinity of interlocking directors does not affect the rate of knowledge transfer using the Indian Company Affiliation Network (ICAN) and the results show that organisational affinity affects the diffusion rate in a statistically significant manner. This is further confirmed with three other random networks of different topologies. The model is also used to simulate knowledge diffusion of the Indian Company Affiliation Network (ICAN) and investigate the uniformity of diffusion rates across various clusters. (C) 2019 Elsevier Ltd. All rights reserved.