We propose an opinion dynamics model based on Latané’s social impact theory. Actors in this model are heterogeneous and, in addition to opinions, are characterised by their varying levels of persuasion and support. The model is tested for two and three initial opinions randomly distributed among actors. We examine how the noise (randomness of behaviour) and the flow of information among actors affect the formation and spread of opinions. Our main research involves the process of opinion formation and finding phases of the system in terms of parameters describing noise and flow of the information for two and three opinions available in the system. The results show that opinion formation and spread are influenced by both (i) flow of information among actors (effective range of interactions among actors) and (ii) noise (randomness in adopting opinions). The noise not only leads to opinions disorder but also it promotes consensus under certain conditions. In disordered phase and when the exchange of information is spatially effectively limited, various faces of disorder are observed, including system states, where the signatures of self-organised criticality manifest themselves as scale-free probability distribution function of cluster sizes. Then increase of noise level leads system to disordered random state. The critical noise level above which histograms of opinion clusters’ sizes loose their scale-free character increases with increase of the easy of information flow.
In the era of limited resources and progressive environmental degradation, the circular economy is a practical application of sustainable development. It is an alternative, but also competitive way to achieve economic growth in accordance with the principles of sustainable development. This issue was considered in this paper in the context of the Ukrainian economy. The Ukrainian economy’s transformation into a circular one needs to find ways to choose practical tools for such a transition, considering the destructive impact of economic activities on the environment, population, and economy. The goal was to develop a method of choosing tools for the circular transformations of economic activities for each cluster and to reduce man-made damage to the environment. Cluster analysis, fuzzy C-means method, and grouping of economic activities were used. Two analyzed sectors turned out to be the most interesting: mining and quarrying, and electricity, gas, steam, and air conditioning supply, which were finally assigned to the cluster with a high level of destructive impact, defined as ‘environmentally unfriendly’. The proposed method allows the choice of circular transformation tools for economic activities depending on the destructive impact of these economic activities within each cluster.
1 January 2018 in Journal of Artificial Societies and Social Simulation
Many studies show that the acquisition of knowledge is the key to building the competitive advantage of companies. We propose a simple model of knowledge transfer within the organisation and we implement the proposed model using the cellular automata technique. In this paper the organisation is considered in the context of complex systems whereby the main role in the organisation is played by the network of informal contacts (informal communication). The goal of this paper is to ascertain which factors influence the efficiency and effectiveness of knowledge transfer. Our studies indicate a significant role of initial distribution of chunks of knowledge for the knowledge transfer process, and the results suggest taking action in the organisation to shorten the distance (social distance) between people with different levels of knowledge, or determining incentives to share knowledge.
We use a general cellular automata model to study the consumer decision-making process. Within this general model we use three different rules governing word-of-mouth communication (w-o-m), one majority rule and two unanimity rules, and ask the question if differences between these three w-o-m rules, introduced on the microscopic level, will manifest on the macroscopic level. We show that in the model with the majority rule the neighborhood plays a significant role in terms of the market shares whereas movement (interpreted as seeking for information in other sources) is almost negligible. Exactly the opposite phenomena are observed for models in which unanimity, instead of majority, is needed to convince agents. We also introduce a modification of the unanimity rule, based on the Latane theory of the social influence, and show that on the macroscopic level this modification is indistinguishable from the simple unanimity rule. We conclude the paper with a recommendation which rules are more appropriate to model particular marketing phenomena.