For deep decarbonisation, the design of climate policy needs to account for consumption choices being influenced not only by pricing but also by social learning. This involves changes that pertain to the whole spectrum of consumption, possibly involving shifts in lifestyles. In this regard, it is crucial to consider not just short-term social learning processes but also slower, longer-term, cultural change. Against this background, we analyse the interaction between climate policy and cultural change, focusing on carbon taxation. We extend the notion of “social multiplier” of environmental policy derived in an earlier study to the context of multiple consumer needs while allowing for behavioural spillovers between these, giving rise to a “cultural multiplier”. We develop a model to assess how this cultural multiplier contributes to the effectiveness of carbon taxation. Our results show that the cultural multiplier stimulates greater low-carbon consumption compared to fixed preferences. The model results are of particular relevance for policy acceptance due to the cultural multiplier being most effective at low-carbon tax values, relative to a counter-case of short-term social interactions. Notably, at high carbon tax levels, the distinction between social and cultural multiplier effects diminishes, as the strong price signal drives even resistant individuals toward low-carbon consumption. By varying socio-economic conditions, such as substitutability between low- and high-carbon goods, social network structure, proximity of like-minded individuals and the richness of consumption lifestyles, the model provides insight into how cultural change can be leveraged to induce maximum effectiveness of climate policy.

Car-centric societies face substantial challenges in moving towards sustainable
mobility systems, with internal combustion engine vehicles remaining a major
source of emissions. Electric vehicles play a critical role in addressing this challenge, yet their diffusion depends on the interaction of consumer behaviour, firm
innovation, and policy incentives. This paper develops an agent-based model to
examine these dynamics, calibrated on the data for the state of California over
2001-2023. In the model, heterogeneous car users influenced by their social peers
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The model presented here is extensively described in the paper ‘Talk less to strangers: How homophily can improve collective decision-making in diverse teams’ (forthcoming at JASSS). A full replication package reproducing all results presented in the paper is accessible at https://osf.io/76hfm/.

Narrative documentation includes a detailed description of the model, including a schematic figure and an extensive representation of the model in pseudocode.

The model develops a formal representation of a diverse work team facing a decision problem as implemented in the experimental setup of the hidden-profile paradigm. We implement a setup where a group seeks to identify the best out of a set of possible decision options. Individuals are equipped with different pieces of information that need to be combined to identify the best option. To this end, we assume a team of N agents. Each agent belongs to one of M groups where each group consists of agents who share a common identity.
The virtual teams in our model face a decision problem, in that the best option out of a set of J discrete options needs to be identified. Every team member forms her own belief about which decision option is best but is open to influence by other team members. Influence is implemented as a sequence of communication events. Agents choose an interaction partner according to homophily h and take turns in sharing an argument with an interaction partner. Every time an argument is emitted, the recipient updates her beliefs and tells her team what option she currently believes to be best. This influence process continues until all agents prefer the same option. This option is the team’s decision.

This article presents an agent-based model of an Italian textile district where thousands of small firms specialize in particular phases of fabrics production. It reconstructs the web of communication between firms as they arrange production chains. In turn, production chains result in road traffic between the geographical areas on which the district extends. The reconstructed traffic exhibits a pattern that has been observed, but not foreseen, by policy makers.

This model is developed as a theoretical agent-based model to study the general phenomena of network-based targeting strategies on eco-innovation adoption and diffusion through inter-firm networks.

We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.

The dynamic agent based model of system which turn out the self-adjusting system, are considered in this text.

The General Housing Model demonstrates a basic housing market with bank lending, renters, owners and landlords. This model was developed as a base to which students contributed additional functions during Arizona State University’s 2020 Winter School: Agent-Based Modeling of Social-Ecological Systems.

The Emergent Firm (EF) model is based on the premise that firms arise out of individuals choosing to work together to advantage themselves of the benefits of returns-to-scale and coordination. The Emergent Firm (EF) model is a new implementation and extension of Rob Axtell’s Endogenous Dynamics of Multi-Agent Firms model. Like the Axtell model, the EF model describes how economies, composed of firms, form and evolve out of the utility maximizing activity on the part of individual agents. The EF model includes a cash-in-advance constraint on agents changing employment, as well as a universal credit-creating lender to explore how costs and access to capital affect the emergent economy and its macroeconomic characteristics such as firm size distributions, wealth, debt, wages and productivity.

The Modern Wage Dynamics Model is a generative model of coupled economic production and allocation systems. Each simulation describes a series of interactions between a single aggregate firm and a set of households through both labour and goods markets. The firm produces a representative consumption good using labour provided by the households, who in turn purchase these goods as desired using wages earned, thus the coupling.

Each model iteration the firm decides wage, price and labour hours requested. Given price and wage, households decide hours worked based on their utility function for leisure and consumption. A labour market construct chooses the minimum of hours required and aggregate hours supplied. The firm then uses these inputs to produce goods. Given the hours actually worked, the households decide actual consumption and a market chooses the minimum of goods supplied and aggregate demand. The firm uses information gained through observing market transactions about consumption demand to refine their conceptions of the population’s demand.

The purpose of this model is to explore the general behaviour of an economy with coupled production and allocation systems, as well as to explore the effects of various policies on wage and production, such as minimum wage, tax credits, unemployment benefits, and universal income.

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