An Agent-Based Model for Adoption of Clean Technology Using the Theory of Planned Behavior

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Mohammad H. Pakravan ◽  
Nordica MacCarty
Keyword(s):  
Technology Adoption ◽  
International Development ◽  
Low Income ◽  
Intervention Strategy ◽  
Holistic Approach ◽  
Clean Technology ◽  
Agent Based Model ◽  
Information Campaigns ◽  
Agent Based ◽  
Clean Cookstoves

Abstract Technology adoption in low-income regions is among the key challenges facing international development projects. Nearly 40% of the world's population relies on open fires and rudimentary cooking devices exacerbating health outcomes, deforestation, and climatic impacts of inefficient biomass burning. Clean technology alternatives such as clean cookstoves are among the most challenging technologies to approach their target goals through sustainable adoption due to a lack of systematic market-driven design for adoption. Thus, a method is needed to provide insight regarding how target customers evaluate and perceive causes for adopting a clean technology. The holistic approach of this study captures technology adoption through lenses of social networks, individual and society scale beliefs, and rational decision-making behavior. Based on the data collected in the Apac region in Northern Uganda, an agent-based model is developed to simulate emerging adoption behavior in a community. Then, four different scenarios investigate how adoption patterns change due to the potential changes in technology or intervention strategy. These scenarios include influence of stove malfunctions, price elasticity, information campaigns, and strength of a social network. Results suggest that higher adoption rates are achievable if designed technologies are more durable, information campaigns provide realistic expectations for users, policymakers, and education programs work toward women's empowerment, and communal social ties are recognized for influence maximization. The application of this study provides insight for technology designers, project implementers, and policymakers to update their practices for achieving sustainable and to the scale clean technology adoption rates.

An Agent-Based Modeling Approach for Clean Technologies Adoption Using Theory of Planned Behavior Based Decision-Making

2019 ◽  
Author(s):  
Mohammad H. Pakravan ◽  
Nordica MacCarty
Keyword(s):  
Decision Making ◽  
Technology Adoption ◽  
International Development ◽  
Low Income ◽  
Intervention Strategy ◽  
Clean Technology ◽  
Policy Makers ◽  
Information Campaigns ◽  
Agent Based ◽  
Behavior Based

Abstract Technology adoption in low-income regions is among the key challenges facing international development projects. Nearly 40% of the world’s population relies on open fires and rudimentary cooking devices exacerbating health outcomes, deforestation, and climatic impacts of inefficient biomass burning. Clean technology alternatives such as clean cookstoves are among the most challenging technologies to approach their target goals through sustainable adoption due to lack of systematic market-driven design for adoption. Thus, a method is needed to provide insight regarding how target customers evaluate and perceive causes for adopting a clean technology. The holistic approach of this study captures the three main aspects of technology adoption through lenses of social networks, individual and society scale beliefs, and rational decision-making behavior. Based on data collected in the Apac region in Northern Uganda, an Agent-Based Model is developed to simulate emerging adoption behavior in a community. Then, four different scenarios investigate how adoption patterns change due to potential changes in technology or intervention strategy. These scenarios include influence of stove malfunctions, price elasticity, information campaigns, and strength of social network. Results suggest that higher adoption rates are achievable if designed technologies are more durable, information campaigns provide realistic expectations for users, policy makers and education programs work toward women’s empowerment, and communal social ties are recognized for influence maximization. Application of this study provides insight for technology designers, project implementers, and policy makers to update their practices for achieving sustainable and to the scale clean technology adoption rates.

scholarly journals An agent-based model to simulate technology adoption quantifying behavioural uncertainty of consumers

2019 ◽  
Vol 255 ◽  
pp. 113795 ◽  
Author(s):  
Vassilis Stavrakas ◽  
Sotiris Papadelis ◽  
Alexandros Flamos
Keyword(s):  
Technology Adoption ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model

PLoS ONE ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. e0231134
Author(s):  
Linghui Jiang ◽  
Xiaoyan Li ◽  
May C. Wang ◽  
Nathaniel Osgood ◽  
Shannon E. Whaley ◽  
...  
Keyword(s):  
Los Angeles ◽  
Low Income ◽  
Los Angeles County ◽  
Agent Based Model ◽  
Agent Based ◽  
Population Impact ◽  
Low Income Population

scholarly journals Informal risk-sharing between smallholders may be threatened by formal insurance: Lessons from a stylized agent-based model

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248757
Author(s):  
Meike Will ◽  
Jürgen Groeneveld ◽  
Karin Frank ◽  
Birgit Müller
Keyword(s):  
Side Effects ◽  
Low Income ◽  
Risk Sharing ◽  
Agent Based Model ◽  
Long Term Effects ◽  
Agent Based ◽  
Positive Effects ◽  
Negative Side Effects ◽  
Informal Risk Sharing

Microinsurance is promoted as a valuable instrument for low-income households to buffer financial losses due to health or climate-related risks. However, apart from direct positive effects, such formal insurance schemes can have unintended side effects when insured households lower their contribution to traditional informal arrangements where risk is shared through private monetary support. Using a stylized agent-based model, we assess impacts of microinsurance on the resilience of those smallholders in a social network who cannot afford this financial instrument. We explicitly include the decision behavior regarding informal transfers. We find that the introduction of formal insurance can have negative side effects even if insured households are willing to contribute to informal risk arrangements. However, when many households are simultaneously affected by a shock, e.g. by droughts or floods, formal insurance is a valuable addition to informal risk-sharing. By explicitly taking into account long-term effects of short-term transfer decisions, our study allows to complement existing empirical research. The model results underline that new insurance programs have to be developed in close alignment with established risk-coping instruments. Only then can they be effective without weakening functioning aspects of informal risk management, which could lead to increased poverty.

scholarly journals An Agent-Based Model for Tertiary Educational Choices in Italy

2021 ◽  
Author(s):  
Silvia Leoni
Keyword(s):  
Higher Education ◽  
Labor Market ◽  
Low Income ◽  
Financial Support ◽  
Individual Preference ◽  
Agent Based Model ◽  
Average Income ◽  
Agent Based ◽  
Low Level ◽  
The Individual

AbstractAlthough the low level of tuition fees and the absence of other access barriers, Italy is characterized by low educational attainments at the university level. This work models the choice of young Italians to attend university or leave education and enter the labor market, by making use of an agent-based model that reproduces the Italian higher education and policy system. The aim is to analyze the determinants behind university enrollment decisions possibly causing the low level of attainment and explore three alternative scenarios that propose the expansion of financial support and the increase in the average income gap between skilled and unskilled individuals. The model implies that the individual preference to enroll at university depends upon (i) economic motivations, represented by the expectations on future income, which are formed through interaction within individuals’ social network; (ii) influence from peers; (iii) effort of obtaining a university degree. Results show that the model can reproduce observable features of the Italian system, and highlights low income levels and the following full resort to regional scholarships. Experimented scenarios show that policies expanding financial support to education are ineffective, while an increase in the gap between average income of skilled and unskilled workers leads to an increase in enrollment in university, signaling that labor market policies may be more effective than educational policies in raising the number of students in higher education.

scholarly journals COVID-19 AGENT-BASED MODEL: AN EPIDEMIOLOGICAL SIMULATOR APPLIED IN VACCINATION SCENARIOS FOR QUEZON CITY, PHILIPPINES

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 65-70
Author(s):  
V. P. Bongolan ◽  
K. K. Ang ◽  
J. J. Celeste ◽  
J. M. Minoza ◽  
S. Caoili ◽  
...  
Keyword(s):  
Low Income ◽  
Programming Model ◽  
The Philippines ◽  
Agent Based Model ◽  
Policy Makers ◽  
Quezon City ◽  
Agent Based ◽  
Low Income Groups ◽  
Front Line Workers ◽  
Vaccine Distribution

Abstract. COVID-19 vaccines are rolling out in the Philippines but the supply remains limited; there is a need to optimize the distribution. In this study, we developed a COVID-19 agent-based model for Quezon City, a COVID-19 hotspot in the country. This model, in conjunction with a multi-objective linear programming model for equitable vaccine distribution, was then used to simulate four vaccination scenarios. Experiments were conducted with the front-line workers always added to the groups: mobile workers, elderly and low-income. Main results are: prioritizing the mobile workers minimizes infections the most (by 4.34%), while prioritizing the low-income groups minimizes deaths the most (by 1.93%). These results demonstrate that protecting the population with the most interactions (mobile workers) effectively reduces future infections. On the other hand, protecting the most vulnerable population (low income and elderly) decreases the likelihood of death. These results may guide the policy-makers in Quezon City.

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