"Modelling behavioral change for analysing degrowth pathways in Integrated Assessment Models (IAMs)"

Abstract

Behavioural change is considered one of the demand-side strategies for achieving sustainable development pathways. People change their behaviour by altering the way they consume or live, causing a reduction in the use of resources or waste generation. Citizens are commonly encouraged to avoid, shift, or improve their behaviour to benefit climate adaptation or mitigation. Yet, a holistic understanding of behavioural change as well as of its interactions with ecological, economic, political, and social systems is still lacking. Moreover, research on behavioural change is often focused on consumption and individual responsibility, instead of contributing to a collective degrowth strategy, including all responsible actors. Here, we develop a new modelling framework that consists of integrating behavioural change in an Integrated Assessment Model (IAM) called WILIAM (‘WIthin Limits’ IAM). WILIAM is a complex multi-sectoral and multi-regional model based on system dynamics which represents a wide variety of economy, society and environment interactions and feedback loops. Through this work, the model is qualitatively informed by a literature review on degrowth behavioural change measures and the collective and individual drivers and barriers to their adoption. Afterwards, these relationships are translated into mathematical equations and indicators that are included in the model. This modelling framework provides findings on both intentions and impacts of transformative behavioural change: we focus on systemic enablers and constraints behind behavioural change towards degrowth and also evaluate the consequences in terms of environmental and social impacts. Thus, our work represents a further contribution to the systematic planning and evaluation of degrowth as a political project.

Full text

Modelling behavioral change for analysing degrowth
pathways in Integrated Assessment Models (IAMs)
Paola López-Muñoz¹, David Álvarez-Antelo¹, Katharina Koller², Lisa Mo Seebacher², Paolo Massa³.
¹ University of Valladolid (UVa), Spain. ²Centre for Social Innovation (ZSI), Austria. ³Fondazione Bruno
Kessler (FBK), Italy.
9th International Degrowth Conference. Zagreb, Croatia. 31st September 2023.
https://www.nevermore-horizon.eu/

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Presentation
•Study setting: motivation, research questions, objectives, state of
the art, general framework…
•Case study definition
•Modelling framework and methodology
•Preliminary results
•Conclusions, further work and takeaways

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Motivation
•The Working Group III of the Sixth Assessment Report of the IPCC recognizes that innovation
and fast technological change are not enough to achieve the Paris Agreement mitigation
objectives without including other transformation such as behavioral and lifestyle change
(IPCC, 2022).
•Individual behavioral change is insufficient for climate change mitigation unless embedded in
structural and cultural change (IPCC, 2022).
•Collective behavioral change aimed at drastically reducing energy use and consumption is an
essential degrowth strategy (Díaz Muñoz, 2022).
•Yet, it is still lacking a holistic understanding of behavioral change as well as of its
interactions with ecological, economic, political, and social systems. Also, concerns about
the social feasibility of drastic lifestyle changes are still high (Azevedo et al, 2021).

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Research Objectives
•Our research aims to include behavioral change into an integrated modelling framework
by including knowledge on psychological drivers and barriers and uncertainty methods.
•Our work aims to obtain an integrated assessment model that enables the exploratory
assessment of collective behavioural change feasibility, desirability and mitigation
potential under different regions, sectors and scenarios.
Research Questions
•Which conditions are necessary for collective lifestyle transformation?
•What are the most feasible and desirable ways in which a collective behavioral change
measure can take place?
•What are the potential energy consumption reduction and greenhouse gases (GHG)
emissions reduction of collective behavioral changes?

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State-of-the-art. Current strategies for modelling degrowth-related behavioural change in
integrated assessment models (IAMs)
•Some IAMs explore lifestyle change scenarios, but always from a scenario perspective, assuming
exogenous behavioural change without exploring their drivers, barriers and thus, their social
feasibility (de Blas et al, 2020; van de Ven et al., 2018).
•Exploring endogenous behavioural change (explicit modelling of drivers and barriers) is still a
very unexplored area in IAMs (van den Berg et al, 2019).
Approach. Our modelling framework.
•We use the WILIAM IAM, a new policy-simulation model based on system dynamics with a high
level of endogenous variables and interlinkages.
•We want to integrate in WILIAM an endogenous behavioural change module fed by psychology
insights on drivers and barriers of pro-environmental behavioural change.
•Our modelling framework is suitable for exploratory modelling under uncertainty and lack of data
on behavioural change drivers, allowing to explore feedback loops and non-linear dynamics.

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General Framework / Workflow
Drivers and
Barriers
Literature review in the fields of
psychology and sociology
WILIAM Integrated
Assessment Model
Literature review in the fields of
behavioural change modelling
in IAMs and sectoral models
Portfolio of behavioural
change measures
Literature review on
degrowth
Degrowth behavioural
change measures
Current work: 35 measures for
different sectors and classified
according to the Avoid-Shift-Improve
(ASI) framework
Current work: 75 drivers and barriers
for 19 types of behavioural change
measures across different sectors
*Currently investigating how to model degrowth-related endogenous
behavioural change in the transport sector

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Case study: transforming mobility lifestyle in
Spain towards degrowth
•Mobility is one of the key sectors that require transformative changes to meet climate mitigation
goals (IPCC, 2022).
•Promoting modal shifts to active transport (e.g., walking or cycling), shared transport (e.g.,
carsharing) and public transport (e.g., bus or train), as well as limiting airplane travelling, are
measures widely acknowledged in the degrowth literature (Fitzpatrick et al 2022; Szabo et al
2022).
•Modal shifts in transport to represent degrowth scenarios have been explored in the past (de Blas
et al, 2020) through models with exogenous scenarios, but to our knowledge, no one has
explored degrowth mobility scenarios through endogenous modelling of behavioral change
measures.
•Previous studies have explored endogenous modal shifts in transport models (Girod et al, 2013)
but they only include income and costs as drivers, leaving out many psychological and social
determinants of pro-environmental behaviour.

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Case study: transforming mobility lifestyle in Spain towards degrowth
AVOID
SHIFT
IMPROVE
Reducing travel demand,
avoiding short flights;
carpooling; carsharing;
teleworking…
Shifting airplane by train;
shifting car by bike; shifting
private transport by public
transport…
Eco-driving; reduce extra-urban
limit speed; using an alternative
fuel car…
More information on the NEVERMORE Report on ‘Society and climate change links and lifestyle changes measures’
https://www.nevermore-horizon.eu/public-deliverables/
and LOCOMOTION Report on ‘Policy measures and objectives selection and formulation’ https://www.locomotion-
h2020.eu/resources/main-project-reports/
According to Van den Berg et al (2019), ‘avoid’ and
‘shift’ measures match the sufficiency paradigm.
Sufficiency is a central concept in degrowth.
“Cultures of sufficiency and self-limitation refers to
the conscious choice of simplifying unsustainable
lifestyles by minimising biophysical footprints”.
(Fitzpatrick et al, 2022)

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‘More than 500 flights a week in Spain today cover routes that can be made
by train in two and a half hours.’
Ecologists in Action is calling for a ban on short flights in Spain similar to that
in France, while the airline industry claims that this would only reduce national
emissions by 0.1%.

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Drivers of pro-environmental behaviour: insights of
psychology
Some of the indicators that are used to determine pro-environmental behaviour are:
•Risk perception. This indicator covers the extent to which climate change is perceived as a risk, threat, or
hazard (van der Linden, 2015, 2017).
•Perceived environmental norms. This indicator captures what a person thinks other people, such as
friends, family, or their community, think and which behaviours they endorse (Bolsen et al., 2014).
•Personal environmental and biospheric values. This indicator describes the extent to which a person
considers costs and benefits for the environment rather than exclusively their own, personally values
environmental protection, and considers nature to have an intrinsic value (Davidovic & Harring, 2020;
Kácha et al., 2022; Lubell et al., 2007; Rhodes et al., 2017; Steg et al., 2005; Wolske et al., 2017).

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Drivers and barriers of shifting airplane to train:
subjective norms and values are not enough
•According to Jacobson et al (2020), some of the drivers that lead to flights reduction are climate concerns,
moral obligations and responsibility sense; but not only.
•Jacobson et al (2020) also highlights the importance of infrastructural and political transformations.
•According to the IPCC (2022, pp. 506), avoid and shift options need not only cultural change, but also new
or adapted infrastructure.
•According to Büchs (2015), the availability of alternatives and economic and political incentives are
important in determining the shift from airplane to others.
•Prices and income are also essential lifestyle indicators and drivers of consumption, affecting
competitiveness and affordability of sustainable options (Akengi & Chen, 2016).

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Key elements of policy design to enable sustainable lifestyles. Source: Akengi & Chen (2016).
Train Fleet Relative Prices (Airplanes vs
Train)
Climate change risk
perception Perceived environmental
norms Personal environmental and
biospheric values

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Modelling Methodology

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The WILIAM transport module

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The model
Energy demand

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The behavioural change model

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Technical methodology
1) We are currently using the transport model isolated and disconnected from the rest of the WILIAM for the shake
of simplicity, and we are linking it with the behavioural change model. The transport model is calibrated to
represent the modal share distribution in 2015,on which we apply the shifts due to behavioural change. The
simulation period is 2015-2050 and behavioural change starts working in the initial year.
2) We parametrise the behavioral change model according to previous literature (Eker et al, 2019).
3) We conduct a sensitivity analysis by varying the uncertain behavioural parameters between pre-defined
uncertainty ranges (also according to Eker et al, 2019) and running multiple simulations (5000 so far) in which
parameters randomly change according to a uniform probability distribution.
4) We observe the spreading on the key outputs: rail and airplane shares, energy consumption and GHG emissions
(only CO2 for the time being).
5) We find the best situations (those that lead to higher GHG emissions reductions) and we qualitatively evaluate its
meaning in terms of feasibility and desirability.

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Parametrization of the behavioural change module
•We use logistic functions to develop three attitude multipliers (perceived climate
change risk, infrastructure effect on attitude and perceived environmental norms) as it
is done in Eker et al (2019). We use the model developed in Beckage et al (2018) for
the perceived risk indicator.
•Parameters of the three logistic functions are L, K and Xo. (L= ref 4.45, min 1.4, max
7.75;K= ref 5, min 1, max 9; Xo= ref 1.3, min 0.5, max 2.25).
•Personal environmental norms and biospheric values is a constant parameter given
the reference value of 1.2 and min and max values of 0.6 and 1.8 respectively.
•Prices are a lineal inverse function of passengers demand, and are calibrated so that
to calculate a coherent relative price (airplane to train) ratio.
•We take into account that 40%of the domestic flights are to islands and cannot be
substituted by rail.
•Further details on the transport sub-module methods and data are in D9.2
LOCOMOTION https://www.locomotion-h2020.eu/resources/main-project-reports/ .

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Preliminary results*
(Do not share them or take them very seriously)

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Domestic flights shares.

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Train shares.

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Total Passenger transport energy consumption.

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Total Passenger transport CO2 emissions.

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Under which conditions do we reach the most desirable
situation?
Total Passenger transport CO2 emissions.
•We took the two best situations and we compare them in terms of behavioural change
indicators
*

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Behavioural change indicators trends in the two more optimal
simulations.
Infrastructure Perceived Risk
Perceived
environmental
norms
Personal
environmental
and biospheric
values Relative Prices

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Preliminary conclusions
•According to our modelling structure, it is feasible to reach a total shift of airplane by train if we
do a good effort in incentivizing the different drivers and barriers behind this behavioural change.
•We can obtain the same target with different combinations of drivers leading to very different
social desirability scenarios, which can help to identify degrowth scenarios.
•This behavioral change measure alone does not achieve very large emission reductions, but there
are large differences depending on the level of implementation.
•*Limitations: high uncertainty and dependency on the model structure and parametrization.

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Further work
•Short term
-Increase the number of simulations in the sensitivity analysis (10.000 simulations).
-Link to the rest of the WILIAM model to include our scenarios in holistic degrowth scenarios.
-Test new model specifications and parametrizations.
-Obtain results for different the environmental policy scenarios regarding changes in prices
and infrastructure
•Mid term
-Include more drivers and barriers indicators, more measures, more sectors, and more
methodologies to deal with uncertainty and lack of data.

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Takeaways for degrowth practicioners
•Since IAMs are used for policy recommendations, including social elements can support decision-
making in terms of social desirability of policies.
•Despite the uncertainty, this exploratory tool allows to close the gap between social sciences &
humanities and IAMs. The modelling framework can involve multidisciplinarity and insights from
participatory processes with civil society. Ideas are welcome!

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Thanks for your attention ☺
Suggestions are welcome!

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References
Akengi, L., & Chen, H. (2016). A framework for shaping sustainable lifestyles. United Nations Environment Programme,.
https://www.oneplanetnetwork.org/sites/default/files/a_framework_for_shaping_sustainable_lifestyles_determinants_and_strategies_0.pdf
Azevedo, I., Bataille, C., Bistline, J., Clarke, L., & Davis, S. (2021). Net-zero emissions energy systems: What we know and do not know. Energy
and Climate Change, 2, 100049. https://doi.org/10.1016/j.egycc.2021.100049
Beckage, B., Gross, L.J., Lacasse, K. et al. Linking models of human behaviour and climate alters projected climate change. Nature Clim Change
8, 79–84 (2018). https://doi.org/10.1038/s41558-017-0031-7
Bolsen, T., Leeper, T. J., & Shapiro, M. A. (2014). Doing What Others Do: Norms, Science, and Collective Action on Global Warming. American
Politics Research, 42(1), 65–89. https://doi.org/10.1177/1532673X13484173
Büchs, M., Saunders, C., Wallbridge, R., Smith, G., & Bardsley, N. (2015). Identifying and explaining framing strategies of low carbon lifestyle
movement organisations. Global Environmental Change, 35, 307–315. https://doi.org/10.1016/j.gloenvcha.2015.09.009
Davidovic, D., & Harring, N. (2020). Exploring the cross-national variation in public support for climate policies in Europe: The role of quality of
government and trust. Energy Research & Social Science, 70, 101785. https://doi.org/10.1016/j.erss.2020.101785
de Blas, I., Mediavilla, M., Capellán-Pérez, I., & Duce, C. (2020). The limits of transport decarbonization under the current growth paradigm.
Energy Strategy Reviews, 32, 100543. https://doi.org/10.1016/j.esr.2020.100543
Díaz Muñoz, M. (2022). An overview of strategies for social-ecological transformation in the field of energy. In Degrowth & Strategy: How to
bring about social-ecological transformation. Mcfly.
Eker, S., Reese, G., & Obersteiner, M. (2019). Modelling the drivers of a widespread shift to sustainable diets. Nature Sustainability, 2(8),
Article 8. https://doi.org/10.1038/s41893-019-0331-1

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References
IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas,
R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi:
10.1017/9781009157926
Jacobson, L., Åkerman, J., Giusti, M., & Bhowmik, A. K. (2020). Tipping to Staying on the Ground: Internalized Knowledge of Climate Change Crucial
for Transformed Air Travel Behavior. Sustainability, 12(5), Article 5. https://doi.org/10.3390/su12051994
Kácha, O., Vintr, J., & Brick, C. (2022). Four Europes: Climate change beliefs and attitudes predict behavior and policy preferences using a latent class
analysis on 23 countries. Journal of Environmental Psychology, 81, 101815. https://doi.org/10.1016/j.jenvp.2022.101815
Lubell, M., Zahran, S., & Vedlitz, A. (2007). Collective Action and Citizen Responses to Global Warming. Political Behavior, 29(3), 391–413.
https://doi.org/10.1007/s11109-006-9025-2
Rhodes, E., Axsen, J., & Jaccard, M. (2017). Exploring Citizen Support for Different Types of Climate Policy. Ecological Economics, 137, 56–69.
https://doi.org/10.1016/j.ecolecon.2017.02.027
Steg, L., Dreijerink, L., & Abrahamse, W. (2005). Factors influencing the acceptability of energy policies: A test of VBN theory. Journal of
Environmental Psychology, 25(4), 415–425. https://doi.org/10.1016/j.jenvp.2005.08.003
van de Ven, D.-J., González-Eguino, M., & Arto, I. (2018). The potential of behavioural change for climate change mitigation: A case study for the
European Union. Mitigation and Adaptation Strategies for Global Change, 23(6), 853–886. https://doi.org/10.1007/s11027-017-9763-y

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References
van den Berg, N. J., Hof, A. F., Akenji, L., Edelenbosch, O. Y., van Sluisveld, M. A. E., Timmer, V. J., & van Vuuren, D. P. (2019). Improved modelling of
lifestyle changes in Integrated Assessment Models: Cross-disciplinary insights from methodologies and theories. Energy Strategy Reviews, 26,
100420. https://doi.org/10.1016/j.esr.2019.100420
van der Linden, S. (2015). The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. Journal of
Environmental Psychology, 41, 112–124. https://doi.org/10.1016/j.jenvp.2014.11.012
van der Linden, S. (2017). Determinants and Measurement of Climate Change Risk Perception, Worry, and Concern (SSRN Scholarly Paper 2953631).
https://doi.org/10.2139/ssrn.2953631
Wolske, K. S., Stern, P. C., & Dietz, T. (2017). Explaining interest in adopting residential solar photovoltaic systems in the United States: Toward an
integration of behavioral theories. Energy Research & Social Science, 25, 134–151. https://doi.org/10.1016/j.erss.2016.12.023