No abstract

The characteristics of communication among the members of an organization can help to identify different organizational processes. In a series of studies, we applied information theory and the Markov chain to construct quantitative models capable of determining the information distribution for infinitely repeated communication in an organization. However, the constructed models primarily focus on randomness in information processing and do not sufficiently address the concept of fuzziness. The dual ambiguity of randomness and fuzziness exists in human information processing, neither of which can be overlooked when discussing organizational communication.In this study, we considered a memory communication channel and proposed an estimation model that included randomness and fuzziness to analyze the prior information allocation ratio of each of the members in two organizations. In addition, we analyzed a communication network with isomorphic and non-isomorphic structures. The proposed model, particularly in the field of organizational theory, will provide new research perspectives that incorporate randomness and fuzziness of information in human information processing and organizational communication. Furthermore, the proposed model suggests the possibility of designing or restructuring an organization that uniformly distributes the amount of prior information to a single organization or multiple ones.

One of the widely used keywords in modern-day society is "network." Information communication networks, e.g., communication and broadcasting networks, networks of different industries across the framework of an organization, community networks of citizens, and networks of nonprofit organizations, are rapidly enhancing in various fields of social "networking." Finally, based on this trend, several researchers have focused on "network" and conducting studies in individual research fields related to social science and engineering (natural science). Several network studies have been conducted by segregating the research into social science and natural sciences. However, a few major issues remain unresolved in network studies.This study clarifies the definition and positioning of networks and networking using an interdisciplinary approach from social science (organizational theory) and engineering (graph theory). Moreover, we will focus on network connectivity and propose connection density indicators. Based on an empirical analysis, the connection density of Japanese subways will be calculated using this connection density index, and the connectivity of each subway will be examined.