arXiv subjects

Agnieszka Kowalska-Styczeń

Publications and source records attributed to Agnieszka Kowalska-Styczeń.

6 recordsLinked to original sources

arXiv2020

Are randomness of behavior and information flow important to opinion forming in organization?

We examine how the randomness of behavior and the flow of information between agents affect the formation of opinions. Our main research involves the process of opinion evolution, opinion clusters formation and studying the probability of sustaining opinion. The results show that opinion formation (clustering of opinion) is influenced by both flow of information between agents (interactions outside the closest neighbors) and randomness in adopting opinions.

econ.TH↗

arXiv2020

Noise induced unanimity and disorder in opinion formation

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.

physics.soc-ph↗

arXiv2017

Influence of a range of interaction among agents on efficiency and effectiveness of knowledge transfer within an organisation

In this study we examined how the size of non-formal groups between organization members affect the transfer of knowledge in the context of the efficiency and effectiveness of this process. To analyse the dynamics of the transfer of knowledge the cellular automata model was used. The model is based on local interactions between members of the organization, that take place in the nearest neighbourhood. These groups of close neighbours are represented by von Neumann's neighbourhood (four nearest-neighbours) and Moore's neighbourhood (four nearest-neighbours and four next-nearest neighbours) and complex neighbourhood (four nearest neighbours, four next-nearest neighbours and four next-next-neighbours). The results of the simulation show the influence of the size of the neighbourhood on the efficiency of knowledge transfer.

physics.soc-ph↗

arXiv2017

Searching for effective and efficient way of knowledge transfer within an organization

In this paper three models of knowledge transfer in organization are considered. In the first model (A) the transfer of chunks of knowledge among agents is possible only when the sender has exactly one more chunks of knowledge than recipient. This is not dissimilar with bounded confidence model of opinion dynamics. In the second model (B) the knowledge transfer take place when sender is "smarter" than recipient. Finally, in the third scenario (model C) we allow for knowledge transfer also when sender posses the same or greater number of chunks of knowledge as recipient. The simulation bases on cellular automata technique. The organization members occupy nodes of square lattice and they interact only with their nearest neighbors. With computer simulations we show, that the efficiency and the effectiveness of knowledge transfer i) for model C is better than for model B ii) and it is worse for model A than for model B.

physics.soc-ph↗

arXiv2017

Model of knowledge transfer within an organisation

Many studies show that the acquisition of knowledge is the key to build competitive advantage of companies. We propose a simple model of knowledge transfer within the organization and we implement the proposed model using cellular automata technique. In this paper the organisation is considered in the context of complex systems. In this perspective, the main role in organisation is played by the network of informal contacts and the distributed leadership. The goal of this paper is to check which factors influence the efficiency and effectiveness of knowledge transfer. Our studies indicate a significant role of initial concentration of chunks of knowledge for 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 working out incentives to share knowledge.

physics.soc-ph↗

arXiv2015

The working group performance modeled by a bi-layer cellular automaton

The problem `human and work' in a model working group is investigated by means of cellular automata technique. Attitude of members of a group towards work is measured by an indicator of loyalty to the group (the number of agents who carry out their tasks), and lack of loyalty (the number of agents, who give their tasks to other agents). Initially, all agents realize scheduled tasks one-by-one. Agents with the number of scheduled tasks larger than a given threshold change their strategy to unloyal one and start avoiding completing tasks by passing them to their colleagues. Optionally, in some conditions, we allow agents to return to loyal state; hence the rule is hysteretic. Results are presented on an influence of i) the density of tasks, ii) the threshold number of tasks assigned to the agents' forcing him/her for strategy change on the system efficiency. We show that a `black' scenario of the system stacking in a `jammed phase' (with all agents preferring unloyal strategy and having plenty tasks scheduled for realization) may be avoided when return to loyalty is allowed and either i) the number of agents chosen for task realization, or ii) the number of assigned tasks, or iii) the threshold value of assigned tasks, which force the agent to conversion from loyal strategy to unloyal one, or iv) the threshold value of tasks assigned to unloyal agent, which force him/her to task redistribution among his/her neighbors, are smartly chosen.

nlin.CG↗