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From social interactions to private environmental behaviours: The case of consumer food waste

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Highlights

  • Private food waste behaviours can deviate from the opinions stated during social interactions.

  • We create an ABM of opinion exchange with interaction threshold and behaviour-opinion gap.

  • Calibration with Italian data on food waste shows that limited inter-group mixing is enough to trigger change.

  • Committed individuals can convince others if they show some between-group variability and open mindedness.

  • Policy against food waste should promote face-to-face interactions between diverse groups.

Abstract

Consumer food waste, like many environmental behaviours, takes place in private, and is not directly subject to social monitoring. Nevertheless, social interactions can affect private opinions and behaviours. This paper builds an agent-based model of interactions between consumers heterogeneous in their sociability, their initial opinions and behaviours related to food waste, and their willingness to consider different opinions, in order to assess how social interactions can affect private behaviours. Compared to existing models of opinion dynamics, we innovate by including a range of “cognitive dissonance” between stated opinions and actual behaviours that consumers are willing to accept before changing one of the two. We calibrate the model using questionnaire data on household food waste in Italy. We find that a limited degree of mixing between different socio-demographic groups, namely adult and young consumers, is enough to trigger change, but a certain openness of mind is required from more wasteful individuals. Equally, a small group of environmentally committed consumers can attract a sizeable share of the population towards low-waste behaviours if they show a certain variability of opinions and are willing to compromise with individuals in their close neighbourhood in terms of opinions. These findings can help design effective interventions to promote pro-environmental behaviours, taking advantage of the beneficial network effects while anticipating negative externalities.

Introduction

Food waste is a societal challenge drawing a burgeoning amount of attention in the agendas of public and private actors. In developed countries, consumers are responsible for the largest share of waste along value chains (Gunders, 2012, Gustavsson, Cederberg, Sonesson, Van Otterdijk, Meybeck, 2011, Stenmarck, Jensen, Quested, Moates, Buksti, Cseh, Juul, Parry, Politano, Redlingshofer, et al., 2016), equalling 53% of the total food waste in the EU.1 This implies the waste of valuable resources like soil, energy and water, but also the unnecessary emission of huge amounts of CO2 contributing to climate change. There has thus been an increasing focus on interventions to reduce food waste at the consumption stage. Most of the current literature on this matter focuses on the identification of socio-demographic and situational drivers (Barr, 2007, Canali, Amani, Aramyan, Gheoldus, Moates, Östergren, Silvennoinen, Waldron, Vittuari, 2017, Parizeau, von Massow, Martin, 2015, Setti, Falasconi, Segrè, Cusano, Vittuari, 2016, Sonesson, Anteson, Davis, Sjödén, 2005, Wassermann, Schneider, 2005, Wenlock, Buss, Derry, Dixon, 1980, WRAP), and their relative influence (Grainger et al. 2018b). A social component has also been identified (Evans 2011), suggesting that food waste is not simply an individual problem. However, there has been limited attention to the interaction between idiosyncratic and social aspects of consumers’ food waste behaviour, including though simulation models. An attempt to study the process of consumers’ food waste generation through extensive agent-based simulations has been made by Ravandi and Jovanovic (2019). However, their agent-based model (ABM) focuses on logistic issues in a very specific setting (food-service operations), with limited role for social influence.

To fill this gap, this paper merges evidence from the food waste literature on the one side, and social simulation on the other side, to develop an ABM that explores how individual food waste behaviours are influenced by peers through exchanges of opinions. In particular, we study the impact on food waste of interactions between individuals belonging to different socio-demographic groups. First, we focus on the role of mixing between adult and young consumers; second, we explore the convincing power of a small group of individuals committed to food waste reduction. We pay particular attention to the mismatch between publicly-stated opinions and private behaviours. Unlike most ABMs, which are calibrated qualitatively using general stylised facts, our model is partially calibrated with real-world data.

Our simulations show that peers can influence each other’s behaviour even when this behaviour is highly heterogeneous and private. Networks and similarity emerge as moderators between social influence and behavioural change. Rather than overall convergence, we observe the emerging of different clusters, as behaviours tend to align with individuals from the same group. The case study of adult and young consumers, with the former wasting little and the latter wasting much, suggests that if individuals are sufficiently open-minded, small degrees of mixing between groups are enough to reduce the share of those with “extreme” behaviours. The case study of populations with a small group of committed individuals shows that, under certain conditions, these can convince a significant share of the overall population. Being the first model to assess the impact of social influence on food waste generation though extensive simulations, there is a lack of research for comparison. Nevertheless, our results suggest that policies addressing food waste should promote interaction opportunities among different socio-demographic groups to achieve larger impact.

The paper is structured as follows. First, we review the literature on food behaviours and social influence. Second, we describe our theoretical model and characterise our case studies starting from the literature and available data. Third, we present and discuss the results of extensive simulations. Finally, we draw our conclusions and illustrate their implications for research and policy design.

Section snippets

Literature review

Recent advancements in consumer studies have departed from the assumption that consumers make their decisions in isolation, based only on individual preferences and attitudes. The economics, psychology and sociology literature has been focusing on the impact of social embeddedness (i.e., of constraints due to the social context where economic activities take place) (Jackson, 2005, Jackson, 2010, Jackson et al., 2017), and peers’ opinions (Carroni, Pin, Righi, 2020, Galeotti, 2010, Lamberton,

Data and methods

This section describes the theoretical model, and the data used to characterise the two case studies through calibration.

Results and discussion

As a preliminary step, we consider the dynamic behaviour of our model. Fig. 3 shows the results of baseline simulations where two equally-sized groups of agents (blue and red) are characterised by the same level of confirmation bias dinti, and the same level of cognitive dissonance dcd. The network density λ is equal to 0.5. In both groups, the initial levels of waste follow a triangular distribution, with Tri(W¯±0.33); however, the groups are heterogeneous in their initial average level of

Conclusions and policy implications

The present model, in its simplicity, has uncovered interesting stylised facts concerning the influence of social interactions on private environmental behaviours, providing insights into behaviour change critical for the design of effective policy interventions. To this end, we have explored the effects of social interactions on stated opinions and private food waste behaviours by means of an ABM. We built two numerical case studies of heterogeneous populations by calibrating the model with

CRediT authorship contribution statement

Simone Piras: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft. Simone Righi: Conceptualization, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft. Marco Setti: Conceptualization, Funding acquisition, Writing – original draft. Nazli Koseoglu: Validation, Writing – review & editing. Matthew J. Grainger: Writing – review & editing. Gavin B. Stewart: Writing – review & editing. Matteo

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research received funding from the Horizon 2020 Framework Programme of the European Union (project REFRESH “Resource Efficient Food and dRink for the Entire Supply cHain”, Grant Agreement 641933) and the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS RD3.2.4 “Food Culture and Dietary Choice”). The views reflected in this paper represent the professional views of the authors and do not necessarily reflect the views of the funders.

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