v2.0.0 – Green Consumption ABM: Social Tipping and Policy Dynamics. (1.0.0)
Green Consumption ABM – Version 2.0.0
This release presents an updated agent-based modelling (ABM) framework developed to investigate social tipping dynamics in green consumption markets.
The model integrates heterogeneous consumer preferences, social influence, firm-level economic decision-making, endogenous pricing, and environmental policy interventions to examine how individual behavioural responses can generate collective market transitions.
Key Features
- Consumer behaviour: Heterogeneous preferences, social interactions, and adaptive purchasing decisions.
- Firm dynamics: Production costs, pricing decisions, profitability, and responses to changing market conditions.
- Environmental policies: Policy mechanisms affecting the relative competitiveness of green and conventional products.
- Social tipping: Investigation of nonlinear market transitions, critical thresholds, and the emergence of widespread green consumption.
- Simulation experiments: Computational experiments designed to investigate market trajectories under different behavioural and policy conditions.
- Reproducible research: Python implementation supporting simulation analysis and the generation of experimental outputs.
Research Context
This model accompanies the research paper Weak Preferences, Strong Transitions: An Agent-Based Model of Social Tipping in Green Consumption.
The repository provides the computational framework for examining the interaction between consumer behaviour, firm-level economic mechanisms, and environmental policy in driving transitions towards sustainable consumption.
Version: 2.0.0
Language: Python
Research areas: Agent-Based Modelling, Computational Economics, Sustainable Consumption, Social Tipping, Environmental Policy.
Release Notes
Version 2.0.0 – Green Consumption ABM: Social Tipping and Policy Dynamics
This release presents a Python-based agent-based model developed to investigate social tipping dynamics and sustainability transitions in green consumption markets.
The model incorporates heterogeneous consumer preferences, social influence, habit formation, firm pricing strategies, production costs, and environmental policy interventions.
It provides a computational framework for examining nonlinear adoption dynamics, behavioural tipping, and the conditions required for sustained transitions towards greener consumption.
The software accompanies the research paper Weak Preferences, Strong Transitions: An Agent-Based Model of Social Tipping in Green Consumption.
The model is intended for academic research, computational experimentation, and reproducible simulation analysis.
Associated Publications
v2.0.0 – Green Consumption ABM: Social Tipping and Policy Dynamics. 1.0.0
Green Consumption ABM – Version 2.0.0
This release presents an updated agent-based modelling (ABM) framework developed to investigate social tipping dynamics in green consumption markets.
The model integrates heterogeneous consumer preferences, social influence, firm-level economic decision-making, endogenous pricing, and environmental policy interventions to examine how individual behavioural responses can generate collective market transitions.
Key Features
- Consumer behaviour: Heterogeneous preferences, social interactions, and adaptive purchasing decisions.
- Firm dynamics: Production costs, pricing decisions, profitability, and responses to changing market conditions.
- Environmental policies: Policy mechanisms affecting the relative competitiveness of green and conventional products.
- Social tipping: Investigation of nonlinear market transitions, critical thresholds, and the emergence of widespread green consumption.
- Simulation experiments: Computational experiments designed to investigate market trajectories under different behavioural and policy conditions.
- Reproducible research: Python implementation supporting simulation analysis and the generation of experimental outputs.
Research Context
This model accompanies the research paper Weak Preferences, Strong Transitions: An Agent-Based Model of Social Tipping in Green Consumption.
The repository provides the computational framework for examining the interaction between consumer behaviour, firm-level economic mechanisms, and environmental policy in driving transitions towards sustainable consumption.
Version: 2.0.0
Language: Python
Research areas: Agent-Based Modelling, Computational Economics, Sustainable Consumption, Social Tipping, Environmental Policy.
Release Notes
Version 2.0.0 – Green Consumption ABM: Social Tipping and Policy Dynamics
This release presents a Python-based agent-based model developed to investigate social tipping dynamics and sustainability transitions in green consumption markets.
The model incorporates heterogeneous consumer preferences, social influence, habit formation, firm pricing strategies, production costs, and environmental policy interventions.
It provides a computational framework for examining nonlinear adoption dynamics, behavioural tipping, and the conditions required for sustained transitions towards greener consumption.
The software accompanies the research paper Weak Preferences, Strong Transitions: An Agent-Based Model of Social Tipping in Green Consumption.
The model is intended for academic research, computational experimentation, and reproducible simulation analysis.