scholarly journals Can Zakat Charity Help Reduce Economic Inequality?

2020 ◽  
pp. 279-294
Author(s):  
Muhammad Asif Jaffer
Keyword(s):  
Distribution Pattern ◽  
Model Simulation ◽  
Wealth Distribution ◽  
Economic Problem ◽  
Economic Behavior ◽  
Agent Based Model ◽  
Power Law Distribution ◽  
Agent Based ◽  
The Rich ◽  
The Impact

Purpose – This paper suggests an agent based model of economic behavior based on which it argues that the Islamic charity of Zakat can be rationalized as it significantly reduces wealth inequalities.  Design/methodology/approach – An Agent Based Model (ABM) of wealth distribution (Wilensky, 1998) is configured to introduce Zakat in the model. Simulations were run in the model with ordered and random distribution of Zakat charity and wealth distribution pattern compared with the standard simulation without Zakat. Findings – The impact of this very small charity on the part of the rich (2.5% of net wealth) showed significant impact on wealth distribution pattern as it changed the power law distribution into normal distribution of wealth. Practical implications – The results emphasize non-conventional handling of the economic problem of poverty and wealth signifying the importance of faith based policing Originality/value – The paper contributes an agent based simulation which is a relatively newer technique to study human behavior and is commensurate to complexity theory. Its use is relatively rare in Islamic Economics and the paper is the first to propose a decentralzied model simulation of Islamic charity of Zakat.

scholarly journals An agent based model of Creative Social Entrepreneurship Behaviour in the context of creative economy

2021 ◽  
Vol 21 (1) ◽  
pp. 7
Author(s):  
Anggraeni Permatasari ◽  
Wawan Dhewanto ◽  
Dina Dellyana
Keyword(s):  
Economic Development ◽  
Social Entrepreneurship ◽  
Model Simulation ◽  
Social Entrepreneur ◽  
Agent Based Model ◽  
Agent Based ◽  
Entrepreneurial Behaviour ◽  
Local Resources ◽  
Socio Economic Development ◽  
The Impact

This paper presents an agent-based model that illustrates creative-social entrepreneurial behaviour and its impact on socio-economic development and local resources sustainability. This study conducted an agent-based model simulation test to demonstrate the potential of the model developed through a literature review. The model approach assumes the interactions between agents are influenced by three purposes, which are profit entrepreneur, social entrepreneur and hybrid entrepreneur. The process is captured from the ability of entrepreneurial creativity in exploiting and conserving local resources. The results show the success of a dynamic model in integrating characteristics and creative-social entrepreneurial behaviour. The final model used as a reference to validate the impact and the relationship of creative-social entrepreneurial action on the socio-economic development and sustainability of a region's local resources. Keywords—Creative-social Entrepreneurship, Agent Based Model, Hybrid Entrepreneurs, Socio-Economic Development Local Resources Sustainability

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

scholarly journals Examining the Impact of the Walking School Bus With an Agent-Based Model

2014 ◽  
Vol 104 (7) ◽  
pp. 1196-1203 ◽  
Author(s):  
Yong Yang ◽  
Ana Diez-Roux ◽  
Kelly R. Evenson ◽  
Natalie Colabianchi
Keyword(s):  
Agent Based Model ◽  
School Bus ◽  
Agent Based ◽  
Walking School Bus ◽  
The Impact

scholarly journals Conceptual Agent Based Model Simulation for the Port Nautical Services

2019 ◽  
Vol 52 (3) ◽  
pp. 19-24
Author(s):  
I.Y. Davydenko ◽  
R.W. Fransen
Keyword(s):  
Model Simulation ◽  
Agent Based Model ◽  
Agent Based

scholarly journals A Computational Study of the Effect of Experience on Problem/Solution Space Exploration in Teams

2019 ◽  
Vol 1 (1) ◽  
pp. 11-20
Author(s):  
Marija Majda Perisic ◽  
Tomislav Martinec ◽  
Mario Storga ◽  
John S Gero
Keyword(s):  
Computational Study ◽  
Space Exploration ◽  
Solution Space ◽  
Problem Solution ◽  
Design Team ◽  
Design Teams ◽  
Agent Based Model ◽  
Problem Space ◽  
Agent Based ◽  
The Impact

AbstractThis paper presents the results of computational experiments aimed at studying the effect of experience on design teams’ exploration of problem-solution space. An agent-based model of a design team was developed and its capability to match theoretically-based predictions is tested. Hypotheses that (1) experienced teams need less time to find a solution and that (2) in comparison to the inexperienced teams, experienced teams spend more time exploring the solution-space than the problem-space, were tested. The results provided support for both of the hypotheses, demonstrating the impact of learning and experience on the exploration patterns in problem and solution space, and verifying the system's capability to produce the reliable results.

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