A Multiplex Network Perspective of Innovation Diffusion: An Information-Behavior Framework

Yu, Qian; Yu, Zhehao; Ma, Ding

doi:10.1109/access.2020.2975357

Cited by 10 publications

(4 citation statements)

References 56 publications

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“…Another aspect that affects percolation in a multiplex network is the structure of each layer. Yu et al (2020) compared ER, SF, and SW random networks as different layers of a duplex (two-layer) diffusion network. This concept has also been generalized to multilayer networks, comparing structures of random graphs as they affect information diffusion (Wang et al 2013).…”

Section: 11mentioning

confidence: 99%

Emergency Warning Dissemination in a Multiplex Social Network

Koll

Lindell

Chen

et al. 2023

JASSS

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Disasters vary in many characteristics, but their amount of forewarning-the amount of time remaining until the disaster strikes-is a crucial factor affecting the dissemination of emergency warnings. People can be warned by public safety officials through broadcast channels, such as commercial TV and radio, that transmit simultaneous warnings to mass audiences. In addition, however, warnings are also transmitted by peers through informal warning networks that operate through contagion from one person to another. This paper establishes an interdisciplinary agent-based model with Monte Carlo simulations to assess the relative effects of these broadcast and contagion processes in a multiplex social network. This multiplex approach models multiple channels of informal communication-phone, word-of-mouth, and social media-that vary in their attribute values. Each agent is an individual in a threatened community who, once warned, has a probability of warning others in their social network using one of these channels. The probability of an individual warning others is based on their warning source and the time remaining until disaster impact, among other variables. We model warning dissemination using simulation parameter values chosen from empirical studies of disaster warnings along with the spatial aspects of the Coos Bay, OR, USA and Seaside, OR, USA communities. Results indicate that the initial broadcast size has a negative correlation with the critical percolation threshold, which varies from approximately 1-5%, depending on the size of an initial broadcast. A sensitivity analysis on the model parameters indicates that, along with initial broadcast size and sharing probability, forewarning and confidence in the warning significantly affect the total number of warning recipients. The results generated from this study identify areas for future research and can inform community officials about the effects of event and community characteristics on the dissemination of emergency warnings in their communities.

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Section: 11mentioning

confidence: 99%

Emergency Warning Dissemination in a Multiplex Social Network

Koll

Lindell

Chen

et al. 2023

JASSS

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“…With the development of innovation ecosystem and innovation network (Nylund et al, 2019;Yu et al, 2020), innovation subjects cooperate to carry out open innovation, or cross-border disruptive innovation, they provide more possibilities for the generation of new ideas. In the future, innovative ideas based on the flow and application of interdisciplinary knowledge and information may subvert the whole industry.…”

Section: Generation Of Disruptive Innovative Ideasmentioning

confidence: 99%

Ex-ante project management for disruptive product innovation: A review

Guo¹,

Shi²,

Peng³

et al. 2023

10.5267/j.jpm

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Disruptive innovation has attracted much interest, discussion and argument in academia and industry since it was defined. Based on a review of the related research publications, this paper aims to clarify the concept of disruptive innovation on controversies, summarize ex-ante studies on project management for disruptive product innovation, and propose potential research areas of the disruptive product innovation. The ex-ante studies are classified into three aspects: timing and conditions of disruptive innovation, factors for the implementation of disruptive innovation, forecasting and implementation of disruptive innovation. After a review of the existing methods of disruptive innovation, the potential research of disruptive innovation is presented.

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“…The results showed that the formation of people's green consensus is closely related to the dissemination of green information, and the dissemination of green information in turn promotes the adoption of green behaviors. Literature [13] pointed out that in the process of innovation diffusion, individuals make adoption decisions based on the information they have obtained, and the influence of information transfer between individuals on innovation adoption behavior is particularly important. Literature [14] proposed an optimal strategy model for epidemics by considering interactions between individuals and the impact of online emotional information on human behavior, striving to minimize the infection burden on the health care system and the financial loss of economic activity during the lockdown.…”

Section: Introductionmentioning

confidence: 99%

Research on the Interaction between Information and Behavior Based on Small Group Effect on Multilayer Social Networks

You,

Zhang,

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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In the era of big data, massive amounts of information play an important role in individual behavior and decision-making. In order to investigate the interaction mechanism between information and individual behavior, we consider the influence of the "small group" network structure in social networks, and construct an information-behavior coupled dynamics propagation model (UAL-NBN) based on small group effect. Then we carry out theoretical analysis and derive the dynamic evolution equations for the model used the Micro Markov Chain Approach (MMCA). And we verify the correctness of the theoretical analysis by performing Monte Carlo simulations (MC). The results show that the small group effect does promote the spread of information and behavior in the population, which is reflected in reducing the epidemic threshold and increasing the outbreak size. In addition, we also conclude that the more small group structures exist in social networks, the more significant the promotion effect of the small group effect is. Finally, we describe the specific application of the model in scenarios such as epidemic control, rumor governance, social behavior advocacy, and consumer marketing, and provide theoretical reference and suggestions for the government and other relevant departments to formulate policies which promote the spread of behavior in society through information dissemination.

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A Multiplex Network Perspective of Innovation Diffusion: An Information-Behavior Framework

Cited by 10 publications

References 56 publications

Emergency Warning Dissemination in a Multiplex Social Network

Emergency Warning Dissemination in a Multiplex Social Network

Ex-ante project management for disruptive product innovation: A review

Research on the Interaction between Information and Behavior Based on Small Group Effect on Multilayer Social Networks

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