An opinion dynamics model for the diffusion of innovations

Martins, André C. R.; Pereira, Carlos de Brito; Vicente, Renato

doi:10.1016/j.physa.2009.04.007

Cited by 71 publications

(42 citation statements)

References 18 publications

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“…A number of innovation diffusion models have adopted ideas from the rich stream of opinion dynamics literature, stipulating that consumers develop preferences in a collective process of opinion formation. In a so-called CODA (continuous opinions, discrete actions) model put forward by Martins et al (2009), for example, each agent has a probabilistic opinion assigned to the proposition "A is the best choice that can be made". This opinion is updated by means of Bayesian interference based on observed adoption behavior of neighboring agents.…”

Section: Opinion Dynamics Approachesmentioning

confidence: 99%

“…In the following, we group papers by the topologies being compared. (Alkemade and Castaldi 2005;Delre et al 2007b;Kocsis and Kun 2008;Martins et al 2009;Choi et al 2010) have analyzed diffusion in small-world networks with varying degrees of randomness (i.e., interpolations between regular and random networks, cf. Watts and Strogatz 1998).…”

Section: Structural Effect Of Social Network Topologymentioning

confidence: 99%

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Agent-based simulation of innovation diffusion: a review

Kiesling

Günther

Stummer

et al. 2011

Cent Eur J Oper Res

433

243

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Mathematical modeling of innovation diffusion has attracted strong academic interest since the early 1960s. Traditional diffusion models have aimed at empirical generalizations and hence describe the spread of new products parsimoniously at the market level. More recently, agent-based modeling and simulation has increasingly been adopted since it operates on the individual level and, thus, can capture complex emergent phenomena highly relevant in diffusion research. Agent-based methods have been applied in this context both as intuition aids that facilitate theory-building and as tools to analyze real-world scenarios, support management decisions and obtain policy recommendations. This review addresses both streams of research. We critically examine the strengths and limitations of agent-based modeling in the context of innovation diffusion, discuss new insights agent-based models have provided, and outline promising opportunities for future research. The target audience of the paper includes both researchers in marketing interested in new findings from the agent-based modeling literature and researchers who intend to implement agent-based models for their own research endeavors. Accordingly, we also cover pivotal modeling aspects in 123 184 E. Kiesling et al. depth (concerning, e.g., consumer adoption behavior and social influence) and outline existing models in sufficient detail to provide a proper entry point for researchers new to the field.

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Section: Opinion Dynamics Approachesmentioning

confidence: 99%

Section: Structural Effect Of Social Network Topologymentioning

confidence: 99%

Agent-based simulation of innovation diffusion: a review

Kiesling

Günther

Stummer

et al. 2011

Cent Eur J Oper Res

433

243

View full text Add to dashboard Cite

show abstract

“…Estimates of adoption rates in health systems are usually based on studies of diffusion rates of technological innovations; which are influenced by population characteristics, including communication among individuals (e.g., prescription, marketing, or patients' requests) and predisposition for technology adoption (e.g., physicians' or patients' preferences for innovation); however, there are controversies regarding the magnitude of effect from diverse variables 5,11,12,13,14,15,16 . Consequently, information to perform BIA is usually based on market-specific evidence or experts' consultations.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with the diffusion rate of innovations: a pilot study from the perspective of the Brazilian Unified National Health System

et al. 2016

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Budget Impact Analyses require a set of essential information on health technology innovation, including expected rates of adoption. There is an absence of studies investigating trends, magnitude of budgetary effects and determinants of diffusion rates for health technology innovations worldwide during the last decades. The present study proposes a pilot assessment on main determinants influencing diffusion rates of pharmaceutical innovations within the Brazilian Unified National Health System (SUS). Data from the Brazilian Health Informatics Department (DATASUS) was gathered to establish the main determinants of diffusion rates of health technology innovations in Brazil, specifically referring to pharmaceutical innovations incorporated in the Brazilian Program for Specialized Pharmaceutical Services (CEAF) at SUS. Information was retrieved on DATASUS relating to patients who had used one of the medicines incorporated into CEAF at least three years prior to the beginning of the study (2015) for treatment of each health condition available. Thus, data from patients adopting 10 different medicines were analyzed in the study. Results from the zero-one inflated beta model showed a higher influence on diffusion rates of pharmaceutical innovations due to: number of pharmaceutical competitors for treatment of the same disease available at CEAF (negative); medicine used in combination with other medication (positive); and innovative medicine within the SUS (positive). Further research on diffusion rates of health technology innovations is required, including wider scope of diseases and medications, potential confusion factors and other variables that may influence rates of adoption in different health systems.

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“…for simulating spreading of epidemics and in simulations of information flow bottlenecks. In order to simulate bottleneck information spreading in a stock exchange market, a modified CODA (agents with continuous opinions and discrete actions) model was used [13].…”

Section: The Model For Bottleneck Information Spreadingmentioning

confidence: 99%

Identification of Insider Trading Using Network Numerical Models

Jakimowicz

Baklarz

2016

Acta Phys. Pol. A

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This article presents a network algorithm for identifying transactions which may constitute a violation of restricted periods, namely, making transactions in company shares by persons possessing inside information. The empirical research was performed on the basis of publicly available information on exchange trading, originating from the Warsaw Stock Exchange. The analysis is based on a numerical model which describes information spreading in a network with an information bottleneck. The applied method can confirm with high probability the use of inside information for carrying out unauthorized stock market transactions.

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An opinion dynamics model for the diffusion of innovations

Cited by 71 publications

References 18 publications

Agent-based simulation of innovation diffusion: a review

Agent-based simulation of innovation diffusion: a review

Factors associated with the diffusion rate of innovations: a pilot study from the perspective of the Brazilian Unified National Health System

Identification of Insider Trading Using Network Numerical Models

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