The social influence is at the centre of consideration in social science. In industrial engineering, although the enterprise has reached the age of the electronic communication, the human direct communication is not sufficiently considered even if it remains critical communication vector to transmit information. The idea is to predict some human attributes behavior that will help enterprise to make efficient decision. The research in the domain gives significant results but the impact of information on individuals within a social network is, mostly, statically modelled where the dynamic aspect is not frequently tackled. The individual's reaction to a change within an organization or ecosystem (implementation of a new system, new security instructions...etc.) is not always rationale. The opinion of individuals is influenced by information gathered about the attributes of the technology from other members of their social network. In addition, the works about modelling and simulation of the population's reactions to an event do not use explicit specification languages to support their models. A behavioural specification model is one critical missing link. Adding a clear behavioural model can help for specification verification and reuse. From literature, the DEVS formalism (Discrete EVent system Specifications) appears being general enough to represent such dynamical systems (Zeigler et al., 2000). It provides operational semantics applicable to this domain. The contributions of this work are dynamic models of individuals using low-level language to simulate the propagation of information among a group of individuals and its influence on their behaviour. In more details, we define a set of models of individuals characterized by a set of state variables and the mesh between the individuals within a social network. Then, we introduce the information diffusion based on epidemic spreading algorithms and we transpose them into the case of the message propagation in a social network. Finally, a basic scenario is used to give a beginning of validation to our models using a platform based on DEVS formalism.

Social simulation implies two preconditions: determining a population and simulate the information diffusion within it. A population represents a group of interconnected individuals sharing information. In this paper, the population we generate is detailed by socio-cultural features, specifically the way that people tend to link together. To this end, the use of a social network is a little bit restrictive: people are linked by only one relationship. Multidimensional Social Networks (MSN) model 3D social networks where each dimension represent a kind of relationship [1]. This architecture allows us to better represent the diversity of humans relations but also define distinctive rules for the message diffusion simulation. The inner idea is that information disseminates differently according to the links through which the information propagates. So, we present in this paper the modeling of our MSN based on social science and a simulation using propagation rules set for each dimension.

The adoption of business processes (BP) can help healthcare providers in structuring the way information systems and people have to interact. Business process management (BPM) is a methodology that structures a way of representing system processes. At the same time, the human resources are organized in identified or implicit structures that allows individuals to exchange information either related to their work function or not. Nevertheless, the human organizations structure and communication channels are not, up to now, fully captured by the information systems. It may lead to losing part of the useful information exchanged by participants. Accordingly, this article focuses on multi-agent solutions representing social networks in the healthcare domain associated with BPM of patient pathways. The purpose is to study the feasibility of combining BP with agent-based models in order to better improve performance, manage resources, and ensure coordination between them.