Empirically grounded agent-based models of innovation diffusion: a critical review

Zhang, Haifeng; Vorobeychik, Yevgeniy

doi:10.1007/s10462-017-9577-z

Cited by 113 publications

(89 citation statements)

References 107 publications

(150 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In short, agent-based models help us to gain insight into the emergence of complex systems by systematically testing a variety of different parameters and the combined impact they exert on the emergent system [58]. Previous research has extensively used agent-based models to study phenomena such as spatial segregation [60], opinion diffusion [61], the adoption of innovation [62], and cascade effects [63].…”

Section: Agent-based Modelmentioning

confidence: 99%

The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict

Kohne

Gallagher

Kirgil

et al. 2019

Computational Social Sciences

View full text Add to dashboard Cite

Social norms can facilitate societal coexistence in groups by providing an implicitly shared set of expectations and behavioral guidelines. However, different social groups can hold different norms, and lacking an overarching normative consensus can lead to conflict within and between groups. In this chapter, we present an agent-based model that simulates the adoption of norms in two interacting groups. We explore this phenomenon while varying relative group sizes and homophily/heterophily (two features of network structure), and initial group norm distributions. Agents update their norm according to an adapted version of Granovetter's threshold model, using a uniform distribution of thresholds. We study the impact of network structure and initial norm distributions on the process of achieving norma-(eds). Computational Conflict Research. Cham: Springer Nature.) 1 2 J. Kohne, N. Gallagher, Z.M. Kirgil, R. Paolillo, L. Padmos, F. Karimi tive consensus and the resulting potential for intragroup and intergroup conflict. Our results show that norm change is most likely when norms are strongly tied to group membership. Groups end up with the most similar norm distributions when networks are heterophilic, with small to middling minority groups. High homophilic networks show high potential intergroup conflict and low potential intragroup conflict, while the opposite pattern emerges for high heterophilic networks.

show abstract

Section: Agent-based Modelmentioning

confidence: 99%

The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict

Kohne

Gallagher

Kirgil

et al. 2019

Computational Social Sciences

View full text Add to dashboard Cite

show abstract

“…mass communication, news media) and promoted by internal, social influence [9] (via word-of-mouth, viral marketing, etc.). The model assumes a homogeneous population of adopters and it predicts that aggregated sales data has an s-shaped pattern as a function of time [6,10].…”

Section: Introductionmentioning

confidence: 99%

Service Adoption Spreading in Online Social Networks

Iñiguez¹,

Ruan²,

Kaski³

et al. 2018

Computational Social Sciences

View full text Add to dashboard Cite

The collective behaviour of people adopting an innovation, product or online service is commonly interpreted as a spreading phenomenon throughout the fabric of society. This process is arguably driven by social influence, social learning and by external effects like media. Observations of such processes date back to the seminal studies by Rogers and Bass, and their mathematical modelling has taken two directions: One paradigm, called simple contagion, identifies adoption spreading with an epidemic process. The other one, named complex contagion, is concerned with behavioural thresholds and successfully explains the emergence of large cascades of adoption resulting in a rapid spreading often seen in empirical data. The observation of real world adoption processes has become easier lately due to the availability of large digital social network and behavioural datasets. This has allowed simultaneous study of network structures and dynamics of online service adoption, shedding light on the mechanisms and external effects that influence the temporal evolution of behavioural or innovation adoption. These advancements

show abstract

“…The conceptual notion of innovation can be applied "far more broadly to consider the spread of ideas and practices" [63]. It has been evidenced to be "a driver of regional economic development", and innovation diffusion is strongly correlated to economic growth [64].…”

Section: Innovation Diffusion (Id) and Sed In Chinamentioning

confidence: 99%

Innovation, the Flying Geese Model, IPR Protection, and Sustainable Economic Development in China

Cao

2019

Sustainability

View full text Add to dashboard Cite

China has achieved an "economic miracle" with 40 years of continual high-speed growth and the simultaneous realization of global innovation prowess. In this study, a large panel dataset from 1985 to 2017 was used in an effort to explore how innovation (at the enterprise level), the flying geese model (at the global and national level), and intellectual property rights (IPR) protection (at the governmental level) have facilitated China's sustainable economic development (SED). We employed ridge regression to compensate for the obvious multicollinearity among independent variables. For control purposes, we included multiple variables, namely, population, the labor force, the exchange rate, human capital, and research and development (R&D) expenditures. The results show that all three factors have significant explanatory power for China's SED.

show abstract

Empirically grounded agent-based models of innovation diffusion: a critical review

Cited by 113 publications

References 107 publications

The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict

The Role of Network Structure and Initial Group Norm Distributions in Norm Conflict

Service Adoption Spreading in Online Social Networks

Innovation, the Flying Geese Model, IPR Protection, and Sustainable Economic Development in China

Contact Info

Product

Resources

About