Modeling rational, psychological, and social behavior toward diffusion of new technology using agent-based simulation: the case of the public utility jeepney (PUJ) fleet in Metro Manila
In most developing countries, over-aged vehicles play a significant role in energy demand and air pollution, which make the transportation sector a suitable choice for investigating opportunities to mitigate climate change. Apparently, people heterogeneity, social influence, and network configuratio...
Saved in:
Published in: | Adaptive behavior Vol. 25; no. 4; pp. 165 - 183 |
---|---|
Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
London, England
SAGE Publications
01-08-2017
|
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | In most developing countries, over-aged vehicles play a significant role in energy demand and air pollution, which make the transportation sector a suitable choice for investigating opportunities to mitigate climate change. Apparently, people heterogeneity, social influence, and network configuration affect diffusion of innovation. This study presents an agent-based model (ABM) to simulate the rational decision-making, psychological behavior, and social interaction of people to explore their reaction to policy scenarios toward adopting technological changes over time. The aim of model is to assist policymakers for energy and environmental policy design based on consumers’ behavior. The jeepney owners in the old public utility jeepney (PUJ) fleet in Metro Manila are chosen as case study to prove the applicability of the model. The results show that rational, psychological, and social interaction of owners could not lead to diffusion of technology without intervention of policy instruments. However, by implementing incentive-based policies, the entire jeepney fleet could be renovated before the end of simulation horizon and the government could launch a 5-year plan to combat pollution of the fleet. The model could be applied to evaluate and prioritize strategies for reducing the future energy requirements and emissions in other fleets and regions. |
---|---|
ISSN: | 1059-7123 1741-2633 |
DOI: | 10.1177/1059712317716264 |