Adapting the governance of social–ecological systems to behavioural dynamics: An agent-based model for water quality management using the theory of planned behaviour
Introduction
Water resources are vulnerable due to demographic pressures, climate change and human activities. Accordingly, water security has become a prominent concern (FAO, 2011; Deng et al., 2018). Water pollution leads to the degradation of aquatic ecosystems, causes problems in drinking water supply and negatively affects economic activities such as fisheries and tourism. Sources of water pollution are diverse: industry effluents, discharge from urban wastewater treatment and losses from agriculture. Many European waterbodies are affected by pollutants and/or altered habitats, and more than half of the rivers and lakes in Europe are reported to have less than good ecological status (EEA, 2020).
In 2000, the European Union adopted the Water Framework Directive (WFD), with the objectives of preventing and reducing water pollution, promoting the sustainable use of water, protecting the environment and improving the status of aquatic ecosystems. At the French level, the WFD has led, for example, to the identification of 1000 priority drinking water catchments as being particularly threatened by nonpoint source pollution where measures targeting farmers' practices have been implemented (MTE, 2020). The measures implemented include information and advisory instruments as well as economic instruments such as the agri-environmental schemes (AES) of the EU Common Agricultural Policy (CAP), which aim to encourage the adoption of environmentally friendly farming practices.
The implementation of the various protection measures is based on the voluntary commitment of farmers. Several studies have shown that the participation rate of farmers in agri-environmental programmes is generally low, particularly for measures involving changes in farming practices (Villien and Claquin, 2012; Epice and ADE, 2011; Chabé-Ferret and Subervie, 2013; Carvin and Saïd, 2020). However, the participation rate plays a determinant role in the effectiveness and efficiency of agri-environmental programmes (Dupraz and Pech, 2007; Kuhfuss et al., 2012). Policy effectiveness corresponds to the difference between the outcomes achieved and the outcomes expected, and efficiency is the relationship between the human and financial means used and the policy outcomes. Both indicators constitute commonly used criteria for evaluating the performance of environmental policies (OECD, 2008), including policy instruments for water quality protection (Shortle and Horan, 2013).
Understanding the factors that affect farmers' participation in environmental programmes is crucial to enhance the effectiveness and efficiency of such programmes. These factors have been extensively studied (Lastra-Bravo et al., 2015; Dessart et al., 2019). Many studies have highlighted the role of economic factors (such as farm size, farm area, farm capital, land tenure and income level) in farmers' decisions to participate in agri-environmental programmes (Toma and Mathijs, 2007; Mzoughi, 2011; Baumgart-Getz et al., 2012; Mettepenningen et al., 2013; Gachango et al., 2015; Floress et al., 2017). More recently, several studies have shown that not only economic factors but also noneconomic factors, including behavioural factors and institutional factors, influence the decision-making process of farmers. The behavioural factors include social, dispositional and institutional factors.
The institutional factors that influence farmers' behaviours are diverse. Mettepenningen et al. (2013) have shown that the characteristics of agri-environmental programmes (duration, payment level) and the level of information about the programmes have an effect on farmers' intentions to participate. Prokopy et al. (2008), in a review of the literature about the adoption of agricultural best management practices, also highlighted that the level of financial compensation has a positive effect on adoption. Gachango et al. (2015) have shown that access to information and farmers' attitude towards subsidies are two factors influencing the adoption of voluntary water pollution reduction technologies.
The behavioural factors include dispositional and social factors. Dispositional factors are individual characteristics that influence an individual to behave in a certain way (Malle, 2011). One factor of interest is environmental concern, which has been found to influence farmers' participation in collective action for water quality management (Amblard, 2019) and their adoption of environmental practices (Giovanopoulou et al., 2011). Toma and Mathijs (2007) have shown that the perception of environmental risk regarding the health of farmers' own family as well as their crops and livestocks is a strong determinant of farmers' propensity to participate in organic farming programmes. The dispositional factors also include more general feelings of responsibility towards nature, the environment, cultural landscapes and the common good (Walder and Kantelhardt, 2018).
Several studies have highlighted the role of social factors and, more specifically, social norms. Le Coent et al. (2016) and Kuhfuss et al. (2015) showed that farmers' decisions to enrol in an agri-environmental programme are influenced by an injunctive norm (the desire to comply with the rule) and a descriptive norm (the desire to behave like the group). Showing to others one's environmental commitment can also influence farmers' adoption of pro-environmental practices (Mzoughi, 2011).
Ajzen and Fishbein (1980) proposed a theory that makes it possible to integrate diverse social, economic, institutional and environmental issues into behavioural analysis: the theory of reasoned action, which was later extended to the theory of planned behaviour (TPB) (Ajzen, 1991). It is one of the most frequently used approaches to understanding farmers' decision-making with regard to agri-environmental policies (Falconer, 2000; Toma and Mathijs, 2007). Within this framework, the intention towards a behaviour is considered a trustworthy predictor as to whether the behaviour will be performed. Individual intention is influenced by three main factors: attitude, subjective norm and perceived behavioural control (PBC) (Ajzen, 1991).
Previous work has shown that each factor has a relative importance in the intention that is highly dependent on the investigated behaviour and population (Ajzen and Fishbein, 2005; Fife-Schaw et al., 2007; Ajzen, 2011). The relative effects of the TPB factors on intention can vary among different populations, depending on the cultural and institutional contexts (e.g., Ajzen and Klobas, 2013). Previous studies have highlighted that the relative importance of factors can differ between countries in the European context (Kaufmann et al., 2009; Mettepenningen et al., 2013). However, the specific effect of these relative weights has not been widely studied, especially in the case of farmers' behaviour. This article contributes to this literature by focusing on TPB factors and their relative importance, as they influence farmers' participation in a water protection programme and therefore the efficiency and effectiveness of protection programmes.
The objective of our study has been to analyse how the characteristics of farmers and the policies implemented jointly influence the evolution of agricultural practices and, therefore, the concentration of pollutants in drinking water catchment areas. For this purpose, we use a conceptual framework based on the social–ecological system (SES) framework developed by Ostrom (Ostrom, 2009; McGinnis and Ostrom, 2014) and the TPB (Section 2). We built an agent-based model of a water catchment area, which is described in the third section. This model allowed us to analyse how water quality management is influenced by the governance system and actor characteristics and dynamics (Section 4). More particularly: (1) We identified how the characteristics of farmers in a catchment area affect policy effectiveness. We focused on the relative importance of the factors and on the characteristics of the population in the catchment area and the interactions between them (Section 4.1). (2) We characterised the effectiveness of different water quality protection programmes. We analysed the marginal effect of different policy measures targeting different farmer populations and have shown that their effectiveness is influenced by the interaction between the characteristics of the measures implemented and farmers' behavioural characteristics (Section 4.2). (3) We assessed the efficiency of different water quality protection programmes that are also influenced by both the characteristics of the policy measures implemented and farmers' behavioural characteristics (Section 4.3). Finally, Section 5 offers a discussion of the findings and a conclusion.
Section snippets
Agent-based models of social–ecological water systems
Water catchments are areas where rainfall feeds the aquifer and thus contribute to the renewal of the resource. In these areas, different actors interact with each other and with the water system. To explore such interactions, we built a model based on the SES framework (Ostrom, 2009; McGinnis and Ostrom, 2014).
The SES framework was developed from the Institutional Analysis and Development approach (Ostrom, 2011) for analysing the governance of common-pool resources (Ostrom, 2007, Ostrom, 2009
Agent-based model
The purpose of the proposed ABM is to explore how farmers, who are connected in a network, are influenced in their choice to join a protection programme by (1) different behavioural characteristics of the farmer populations and (2) different characteristics of the protection programme (see Appendix 1 for the Overview Design concepts and Details (ODD) protocol description).
Three subsystems are modelled:
- •
The resource system entity represents a groundwater catchment area that has a certain
Results
Based on the reference scenario, we explore how policy effectiveness, i.e., the evolution of farmers' practices and water pollution levels, is influenced by the characteristics of the farmer population (Section 4.1). Then, we examine how the characteristics of the protection programme, interacting with the behavioural characteristics of the farmer population, impact the policy effectiveness (Section 4.2) and efficiency (Section 4.3).
Discussion and conclusions
The purpose of our study was to explore how the behavioural characteristics of farmer populations in drinking water catchments impact the efficiency and effectiveness of programmes designed to protect water quality. Our results showed that the involvement of farmers in protection programmes depends closely on the interactions between their behavioural characteristics and the governance system. Farmers' behavioural characteristics must be taken into account to design efficient and effective
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
The authors acknowledge the support received from the Agence Nationale de la Recherche from the French Government through the programme “Investissements d'Avenir” (16-IDEX-0001 CAP 20-25) and through the VIRGO Project (ANR-16-CE03-0003). We are grateful to two anonymous reviewers for their insightful comments on previous versions of the paper.
References (122)
The theory of planned behavior
Organ. Behav. Hum. Decis. Process.
(1991)- et al.
Agent-based modelling for ecological economics: a case study of the Republic of Armenia
Ecol. Model.
(2017) - et al.
Agent-based modelling of interactions between air pollutants and greenery using a case study of Yerevan, Armenia
Environ. Model Softw.
(2019) Collective action for water quality management in agriculture: the case of drinking water source protection in France
Glob. Environ. Chang.
(2019)Modeling human decisions in coupled human and natural systems: review of agent-based models
Ecol. Model.
(2012)- et al.
Why farmers adopt best management practice in the United States: a meta-analysis of the adoption literature
J. Environ. Manag.
(2012) - et al.
Explaining farmers’ conservation behaviour: why do farmers behave the way they do?
J. Environ. Manag.
(1999) - et al.
Integrating multiple perspectives on payments for ecosystem services through a social–ecological systems framework
Ecol. Econ.
(2015) - et al.
Simplistic understandings of farmer motivations could undermine the environmental potential of the common agricultural policy
Land Use Policy
(2021) - et al.
How much green for the buck? Estimating additional and windfall effects of French agro-environmental schemes by DID-matching
J. Environ. Econ. Manag.
(2013)
A moral basis for recycling: extending the theory of planned behaviour
J. Environ. Psychol.
Farm-level constraints on agri-environmental scheme participation: a transactional perspective
J. Rural. Stud.
Explaining landholders’ decisions about riparian zone management: the role of behavioural, normative, and control beliefs
J. Environ. Manag.
Toward a theory of farmer conservation attitudes: dual interests and willingness to take action to protect water quality
J. Environ. Psychol.
Adoption of voluntary water-pollution reduction technologies and water quality perception among Danish farmers
Agric. Water Manag.
Modeling farmer participation in agri-environmental nitrate pollution reducing schemes
Ecol. Econ.
Exploring the influence of an extended theory of planned behaviour on preferences and willingness to pay for participatory natural resources management
J. Environ. Manag.
The ODD protocol: A review and first update
Ecol. Model.
Behaviour in commons dilemmas: homo economicus and homo psychologicus in an ecological-economic model
Ecol. Econ.
Social factors and private benefits influence landholders’ riverine restoration priorities in tropical Australia
J. Environ. Manag.
Simulating the diffusion of organic farming practices in two new EU member states
Ecol. Econ.
Agent-based model simulations of future changes in migration flows for Burkina Faso
Glob. Environ. Chang.
What drives farmers’ participation in EU agri-environmental schemes?: results from a qualitative meta-analysis
Environ. Sci. Pol.
Conservation technology adoption decisions and the theory of planned behavior
J. Econ. Psychol.
Determinants of performance of community-based drinking water organizations
World Dev.
Investigating the influence of the institutional organisation of agri-environmental schemes on scheme adoption
Land Use Policy
Describing human decisions in agent-based models – ODD + D, an extension of the ODD protocol
Environ. Model. Softw.
Farmers adoption of integrated crop protection and organic farming: do moral and social concerns matter?
Ecol. Econ.
A micro-level simulation for the prediction of intention and behavior
Cogn. Syst. Res.
Decision support for ethical problem solving: a multi-agent approach
Decis. Support. Syst.
Determinants of spatio-temporal patterns of energy technology adoption: an agent-based modeling approach
Appl. Energy
A framework for mapping and comparing behavioural theories in models of social-ecological systems
Ecol. Econ.
Normative influences on altruism
Agent-based modeling of the diffusion of environmental innovations — an empirical approach
Technol. Forecast. Soc. Chang.
Les traitements phytosanitaires en 2014
Les Dossiers
Students’ responses to improve environmental sustainability through recycling: quantitatively improving qualitative model
Appl. Res. Qual. Life
Behavioral interventions: design and evaluation guided by the theory of planned behavior
Understanding Attitudes and Predicting Social Behavior
The influence of attitudes on behavior
Fertility intentions: an approach based on the theory of planned behavior
Demogr. Res.
The effect of environmental concern and scepticism on green purchase behaviour
Mark. Intell. Plan.
La coopération entre producteurs d’eau potable et acteurs agricoles en France
IRSTEA. ONEMA
Theory-driven subgroup specific evaluation of an intervention to reduce private car use
J. Appl. Soc. Psychol.
Interplay of multiple goods, ecosystem services, and property rights in large social-ecological marine protected areas
Ecol. Soc.
Decentralisation of agri-environmental policy design
Eur. Rev. Agric. Econ.
Using social-psychology models to understand farmers’ conservation behaviour
J. Rural. Stud.
Incentives and Prosocial Behavior
Governance in social-ecological agent-based models: a review
Ecol. Soc.
Contrat agro-environnemental et participation des agriculteurs
Écon. Rur.
Fuzzy association rules for estimating consumer behaviour models and their application to explaining trust in internet shopping
Fuzzy Econ. Rev.
Cited by (12)
Analysis of social network effects on water trade in an informal water market
2023, Journal of Cleaner ProductionIs rationality or herd more conducive to promoting farmers to protect wetlands? A hybrid interactive simulation
2022, Habitat InternationalCitation Excerpt :This is because Chinese farmers value not only the connotation of social norms, but also the feelings of respect and social identity brought by such behaviors. Moreover, they also internalize social norms as a part of their own interests (Bijttebier et al., 2018; Bourceret et al., 2022). In this study, this type of farmers, which was assumed to pay more attention to social networks and peer effects when making decisions, was labeled as “bounded self-interest farmers".
IMPLEMENTATION OF THE THEORY OF PLANNED BEHAVIOR IN THE PRIMARY AND BUSINESS ECONOMIC SECTORS: A SYSTEMATIC LITERATURE REVIEW
2024, Corporate Governance and Organizational Behavior Review