When people try to decide to buy or not to, they are often influenced by both their inherentopinions and the social marketing activities e.g. advertising, social news with strong point of view.Then people will make th...When people try to decide to buy or not to, they are often influenced by both their inherentopinions and the social marketing activities e.g. advertising, social news with strong point of view.Then people will make their final choice, or even convince other people to buy. After all, this is thebrand acceptance formation process. Factually, the dynamics of brand acceptance is essentially aninterwoven dynamics of endogenous opinion dynamics disturbed by an information diffusion process.To have a better understanding of the dynamics of brand acceptance, we propose and analyze a coupledagent-based dynamic model that combines the Majority-Rule-based Voter model in opinion dynamicswith the SI Model for information spreading to analyze the dynamics of brand acceptance in socialmedia. We focus on two important parameters in diffusion dynamics： the decayed transmission rate （fl）and the diffusion frequency （f）. When the system is stable, the order parameter of the system is theduration time （r）. In the absence of opinion interaction, the simulation results indicate that, when abrand tries to occupy a larger market share through social marketing approaches, it is always effectiveto let the opponent to be the propaganda target. While with the Majority-Rule-based Voter Modelincluded, we observe that the opinion interaction could have a dual function, which shows that a brandholding a small market share in the first place needs to adopt diverse marketing approaches accordingto different marketing environment types.展开更多
In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures,focusing on a the discrete time setup.The two key operational concepts used throughout are the no...In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures,focusing on a the discrete time setup.The two key operational concepts used throughout are the notion of the LMmeasure and the notion of the update rule that,we believe,are the key tools for studying time consistency in a unified framework.展开更多
文摘When people try to decide to buy or not to, they are often influenced by both their inherentopinions and the social marketing activities e.g. advertising, social news with strong point of view.Then people will make their final choice, or even convince other people to buy. After all, this is thebrand acceptance formation process. Factually, the dynamics of brand acceptance is essentially aninterwoven dynamics of endogenous opinion dynamics disturbed by an information diffusion process.To have a better understanding of the dynamics of brand acceptance, we propose and analyze a coupledagent-based dynamic model that combines the Majority-Rule-based Voter model in opinion dynamicswith the SI Model for information spreading to analyze the dynamics of brand acceptance in socialmedia. We focus on two important parameters in diffusion dynamics： the decayed transmission rate （fl）and the diffusion frequency （f）. When the system is stable, the order parameter of the system is theduration time （r）. In the absence of opinion interaction, the simulation results indicate that, when abrand tries to occupy a larger market share through social marketing approaches, it is always effectiveto let the opponent to be the propaganda target. While with the Majority-Rule-based Voter Modelincluded, we observe that the opinion interaction could have a dual function, which shows that a brandholding a small market share in the first place needs to adopt diverse marketing approaches accordingto different marketing environment types.
基金Tomasz R.Bielecki and Igor Cialenco acknowledge support from the NSF grant DMS-1211256.Part of the research was performed while Igor Cialenco was visiting the Institute for Pure and Applied Mathematics(IPAM),which is supported by the National Science Foundation.Marcin Pitera acknowledges the support by Project operated within the Foundation for Polish Science IPP Programme“Geometry and Topology in Physical Model”co-financed by the EU European Regional Development Fund,Operational Program Innovative Economy 2007–2013.
文摘In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures,focusing on a the discrete time setup.The two key operational concepts used throughout are the notion of the LMmeasure and the notion of the update rule that,we believe,are the key tools for studying time consistency in a unified framework.
