Figure - available from: The Annals of Regional Science
This content is subject to copyright. Terms and conditions apply.
Source publication
Theoretical and experimental studies from psychological and behavioral sciences show that heuristics and social networks play an important role in decision-making under risk. The goal of this paper is to investigate the effects of empirical social networks and different behavioral rules on farmers’ irrigation adoption under drought risk and its imp...
Citations
... Risk-uncertain individuals may look more at their peers when deciding if and how to adapt as they feel less equipped to judge the risk on their own. They imitate peers when uncertain phenomena are theorized and documented empirically (van Duinen et al., 2016;Rendell et al., 2010). ...
Risk assessments are key for the effective management of potential environmental threats. Across probabilistic phenomena, climate change is an exemplar of paramount uncertainties. These uncertainties have been embraced in supporting governments’ decisions; yet receive scarce attention when studying individual behavior. Analyzing a survey conducted in the USA, China, Indonesia, and the Netherlands (N=6242), we explore socio-economic, psychological, and behavioral differences between individuals who can subjectively assess risks, and those who are risk-uncertain. We find that risk-uncertain individuals are more likely to belong to societal subgroups classically considered as vulnerable, and have reduced capacities and intentions to adapt to hazards—specifically floods. The distinctions between risk-aware and risk-uncertain individuals indicate that ignoring differences in individuals’ capacity to assess risks could amount to persistent vulnerability and undermine climate-resilience efforts. While we use floods emblematically, these finding have consequences for the standard practice of dropping or bootstrapping uncertain responses, irrespective of the hazard, with implications for environmental management.
... One well established economic theory is rational choice theory. It is based on the concept of full rationality, which postulates that humans have perfect information and capacities for evaluating all possible alternatives without errors to optimize their well-being (Sen, 1994;Simon, 1955Simon, , 2007van Duinen et al., 2016). However, several authors challenge these assumptions and argue that human rationality is bounded by restricted information availability, cognitive capacity, and environmental complexity (Green and Shapiro, 2014;Kahneman, 2003;Simon, 1990Simon, , 1959. ...
... Few authors have compared alternative approaches to represent farmers' decision-making in social-ecological models (Malawska and Topping, 2016;Schulze et al., 2017). They provide evidence that model assumptions regarding farmers' decision-making affect simulation outcomes and policy implications Holtz and Nebel, 2014;Schindler, 2013;Schreinemachers and Berger, 2006; van Duinen et al., 2016;Wens et al., 2020). Although some studies suggest that bounded rationality represents farmers' decision-making more realistically than perfect rationality (Cabrera et al., 2010;Holtz and Nebel, 2014;Richetin et al., 2009;Wens et al., 2020), no theory has been identified that best represents decision-making in general as the adequacy of an approach depends on the models' purpose and context (Huber et al., 2018;Parker et al., 2003). ...
... Besides, the limited number of studies comparing decision-making approaches focuses mainly on the two concepts perfect rationality and bounded rationality (e.g. Cabrera et al., 2010;Holtz and Nebel, 2014;Malawska and Topping, 2016;Schreinemachers and Berger, 2006;van Duinen et al., 2016;Wens et al., 2020). Consequently, more comparisons of decision-making approaches are needed in further contexts that include additional approaches such as the TPB (Caprioli et al., 2020;Huber et al., 2018;Parker et al., 2003;Reidsma et al., 2018;Schlüter et al., 2017;Schulze et al., 2017). ...
Advancing the transition towards more sustainable agriculture requires policy interventions that support farmers' adoption of sustainable practices. Models can support policy-makers in developing and testing interventions. For these models to provide reliable support, their underlying assumptions need to reflect reality and hence adequately represent human decision-making. This study compares several approaches that represent human decision-making. The comparison is applied to farmers' decision to adopt agroforestry. An agent-based simulation model is calibrated to a case study in rural Rwanda, where socio-economic survey data was collected from 145 small-scale farmers. Of these farmers, 72 were randomly selected to participate in a role-playing game, during which the players decided about adopting agroforestry. The game was conducted to validate the tested decision-making approaches. The simulations show that the decision-making approaches predict significantly different agroforestry adoption rates. Compared with the role-playing game, the Theory of Planned Behaviour exhibits the highest validity. Rational choice theory and the econometric approach overestimate implementation. Bounded rationality approaches underestimate the share of adopters. The results highlight the importance of adequately representing farmers' adoption decisions in models for providing reliable forecasts and effective policy support.
... Irrigation has been instrumental in reducing the risk of climate variability (Calzadilla et al., 2013), even in regions with sufficient seasonal rainfall, as average irrigated crop yields are generally over twice that of rain-fed agriculture (Grassini et al., 2009;Patle et al., 2019). Yet, despite its apparent advantages, adoption of irrigation is uneven and persistently low in some areas (van Duinen et al., 2016;Zaveri and Lobell, 2019;Sydnor and Molnar, 2020). ...
... The spatial differentiation of irrigation adoption among social neighborhoods highlights the disparate and varying degrees of exposure to resources across Alabama's farms and communities. Recent research has demonstrated that bottom-up interactions among farmers and other agricultural community members can drive system-level shifts in production methods, such as irrigation adoption (van Duinen et al., 2016;Zagaria et al., 2021) and multifunctional agriculture (Manson et al., 2009;Fernandez-Mena et al., 2020). Important localized interactions include sharing information about irrigation technologies, benefits, and best practices (e.g., Van Duinen et al., 2015); observing successful strategies for acquiring bank loans or taking advantage of government subsidies (Shange et al., 2014); and social norms for water management techniques (Liu et al., 2018). ...
Rates of poverty and economic inequality in rural Alabama are among the nation's highest and increasing agricultural productivity can provide a needed boost to these communities. The transition from rain-fed to irrigation-fed (RFtoIF) agriculture has significantly increased farm productivity and profitability elsewhere in the United States. Despite this potential to enhance stability and resilience in rural economies, irrigated cropland accounts for only 5% of Alabama's total cropland as numerous barriers remain to irrigation adoption. To encourage RFtoIF transition, it is imperative to identify the challenges faced by individual farmers at farm, community, and state levels. This study presents a multi-level mixed effects survival analysis to identify the physiographic, socioecological, and economic factors that influence the location and timing of irrigation adoption. We integrate spatiotemporal cropland and climatological data with field-verified locations of center-pivot irrigation systems, local physiographic characteristics, and parcel-level surface water access and average well depth. Access to surface water, costs to access groundwater, and soil characteristics were generally important influences in all regions, but regions were differentiated by the extent to which new irrigation was more responsive to social influences vs. precipitation and price trends. Our findings also highlighted the diversity of farming conditions across the state, which suggested that diverse policy tools are needed that acknowledge the varying motivations and constraints faced by Alabama's farmers.
... Other negative feedbacks may be biophysical; for example, the application of water in excess of plant growth requirements may lead to problems such as waterlogging, ponding, soil salinity issues, runoff and nutrient imbalance -with potentially detrimental impacts on crop yield and hence the productivity and profitability of agricultural enterprises (Feike et al., 2017;Ansari et al., 2018;Byrareddy et al., 2020). In a water-constrained environment, water security concerns should also, in theory, act to drive the adoption of on-farm water use efficiency (WUE) and other water conservation measures (Khair et al., 2015(Khair et al., , 2019van Duinen et al., 2016). ...
The way forward for irrigated agriculture in a warming and water-constrained world lies in integrated policy development and practice, including ‘sustainable intensification’, that considers the ‘food-water-energy nexus’. Such policy should incorporate both climate adaptation and climate mitigation options to minimise trade-offs and increase the potential for ‘win-win’ synergies. In this chapter, an overview of the role of irrigation in enhancing global food security is provided. The trade-offs involved when intensification of agricultural production is achieved at the expense of water and environmental security are considered together with the implications for the food production systems that intensification seeks to support.
... Farmers' social networks influence farm management decisions through the diffusion of knowledge, practices, attitudes, and values (Brown et al., 2018;Gray and Gibson, 2013). The structure of social networks-for example, the combination of close, local "bonding" and geographically and socially distant "bridging" connections-can influence the adoption of farm-level innovations (Albizua et al., 2020;Cofré-Bravo et al., 2019), including new technologies and practices, certifications and labels, or agro-environmental measures (Karali et al., 2014;Padel, 2001;Skaalsveen et al., 2020;van Duinen et al., 2016). ...
CONTEXT
Farm numbers are steadily declining in Europe and globally while farms become larger and more intensive. Driven in part by worsening macroeconomic conditions, these structural changes and the associated rationalization of agricultural supply chains have affected social relations in rural areas. In turn, farmers' social contacts influence farming decisions. Social and structural changes are thus interconnected, and they affect the resilience of rural areas through their influence on environmental, social, and economic capital.
OBJECTIVE
We examine the connection between farm structures and farmers' social contacts in the UNESCO Biosphere Reserve Entlebuch (UBE), a mountain region in central Switzerland with a strong presence of family farms, and explore the implications of social and structural change for rural resilience.
METHODS
We conduct a survey of N = 102 farming households and combine it with farm-level agricultural census data and interviews with key stakeholders (N = 13) to analyze farmers' current social contacts and their changes since the year 2000. We use regression and cluster analyses to examine the relationship between (changes in) social contacts and farm-level characteristics.
RESULTS AND CONCLUSIONS
Farmers in the UBE have a high, but decreasing frequency of contacts with family, friends, and colleagues and lower, but increasing frequency of commercial and administrative contacts. Workloads have increased by 6% in five years, driven by farm-level expansion of agricultural area (+5%)—including expanding ecological compensation areas—and intensification in managed areas (+3%), leading to parallel processes of intensification and extensification. Since most of these family farms do not hire workers, growing workloads directly impinge on farmers' free time, affecting informal contacts most. Farm managers in larger and more intensive farms have more frequent and more diverse, but also more rapidly declining, social contacts. Our results point to a net loss in social capital as social contacts become less frequent and shift from local and informal to regional and national professional contacts.
SIGNIFICANCE
A 17% decline in farm numbers in 15 years reflects the vulnerability of farms in this region. Growing financial strain, workloads, time pressure and the associated erosion of informal contacts contribute to this vulnerability. Policymakers from local to national should recognize the contribution of farmers' diverse social networks towards rural resilience and seek options to maintain and enhance such networks. Beyond direct interventions that foster social capital, policymakers should more rigorously consider the short- and long-term interconnections and tradeoffs between different forms of capital.
... Drought resilience and adaptation literature have identified the adaptation strategies that are usually adopted across different agricultural or rural settings (Booker et al., 2005;Chen et al., 2014;Hurlbert & Gupta, 2019;Laforge & McLeman, 2013;Makaya et al., 2020;Medeiros & Sivapalan, 2020;Mwangi, 2019;O'Farrell et al., 2009;Sapountzaki & Daskalakis, 2018;van Duinen et al., 2016;Wenger et al., 2017;Yila & Resurreccion, 2014;Zipper et al., 2017). One of the oldest strategies is the transhumance or seasonal migration toward new climatic regions. ...
... Most of the literature uses quantitative surveys, statistical analyses, and mathematical models to measure resilience levels and estimate the correlation between prevailing adaptation strategies and socioenvironmental characteristics of the area ( Moore et al., 2018;Pendley et al., 2020;Quiroga et al., 2011;Sapountzaki & Daskalakis, 2018;Su et al., 2017;van Duinen et al., 2016;Yates et al., 2013;Yila & Resurreccion, 2014). Sociohydrological studies apply numerical models to simulate adaptive behaviors of different stakeholders and their long-term socioenvironmental dynamics (Hund et al., 2018;van Duinen et al., 2016;Wens et al., 2019). ...
... Most of the literature uses quantitative surveys, statistical analyses, and mathematical models to measure resilience levels and estimate the correlation between prevailing adaptation strategies and socioenvironmental characteristics of the area ( Moore et al., 2018;Pendley et al., 2020;Quiroga et al., 2011;Sapountzaki & Daskalakis, 2018;Su et al., 2017;van Duinen et al., 2016;Yates et al., 2013;Yila & Resurreccion, 2014). Sociohydrological studies apply numerical models to simulate adaptive behaviors of different stakeholders and their long-term socioenvironmental dynamics (Hund et al., 2018;van Duinen et al., 2016;Wens et al., 2019). Interdisciplinary examinations often employ qualitative methods to elaborate deeper investigations about local contexts and historical trajectories (Downard & Endter-Wada, 2013;Du et al., 2018;Hurlbert & Gupta, 2019;King-Okumu et al., 2018;Laforge & McLeman, 2013;Lindsay et al., 2017;Makaya et al., 2020;Mwangi, 2019;Sousa Júnior et al., 2016;Wiener et al., 2016). ...
Human activities have increasingly intensified the severity, frequency, and negative impacts of droughts in several regions across the world. This trend has led to broader scientific conceptualizations of drought risk that account for human actions and their interplays with natural systems. This review focuses on physical and engineering sciences to examine the way and extent to which these disciplines account for social processes in relation to the production and distribution of drought risk. We conclude that this research has significantly progressed in terms of recognizing the role of humans in reshaping drought risk and its socioenvironmental impacts. We note an increasing engagement with and contribution to understanding vulnerability, resilience, and adaptation patterns. Moreover, by advancing (socio)hydrological models, developing numerical indexes, and enhancing data processing, physical and engineering scientists have determined the extent of human influences in the propagation of drought hazard. However, these studies do not fully capture the complexities of anthropogenic transformations. Very often, they portray society as homogeneous, and decision‐making processes as apolitical, thereby concealing the power relations underlying the production of drought and the uneven distribution of its impacts. The resistance in engaging explicitly with politics and social power—despite their major role in producing anthropogenic drought—can be attributed to the strong influence of positivist epistemologies in engineering and physical sciences. We suggest that an active engagement with critical social sciences can further theorizations of drought risk by shedding light on the structural and historical systems of power that engender every socioenvironmental transformation.
This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives
... MBR is used because it produces actor behavior that is short-sightedly rational and requires only local information. However, as van Duinen et al. (2016) demonstrate, an actor selecting new technology strategies may switch between policy update processes using repetition, deliberation, social comparison and imitation depending on the actor's 16/31 level of satisfaction and uncertainty. MBR is a deliberative policy update rule. ...
Robust designs protect system utility in the presence of uncertainty in technical and operational outcomes. Systems-of-systems, which lack centralized managerial control, are vulnerable to strategic uncertainty from coordination failures between partially or completely independent system actors. This work assesses the suitability of a game-theoretic equilibrium selection criterion to measure system robustness to strategic uncertainty and investigates the effect of strategically robust designs on collaborative behavior. The work models interactions between agents in a thematic representation of a mobile computing technology transition using an evolutionary game theory framework. Strategic robustness and collaborative solutions are assessed over a range of conditions by varying agent payoffs. Models are constructed on small world, preferential attachment and random graph topologies and executed in batch simulations. Results demonstrate that systems designed to reduce the impacts of coordination failure stemming from strategic uncertainty also increase the stability of the collaborative strategy by increasing the probability of collaboration by partners; a form of robustness by environment shaping that has not been previously investigated in design literature. The work also demonstrates that strategy selection follows the risk dominance equilibrium selection criterion and that changes in robustness to coordination failure can be measured with this criterion.
... Nevertheless, these authors note that when integrating a measure of spatial regularities to the ABMs models tend to perform significantly worse [28], i.e. this phenomenon is not analysed for solar PVs. Secondly, the decision-making process in ABMs commonly assumes that agents have access to perfect market information and can evaluate the benefit of their decisions [17,[33][34][35]. It is these challenges associated with undertaking such complicated calculations that led Noori and Tatari [36] to propose considering alternative and more realistic behavioural models by including other characteristics of human decision-making, namely artificial neural networks (ANN). ...
... Commonly ABMs use rational choice principles where one assumes that agents have access to perfect market information and can evaluate the benefit of their decisions. However, this is rather limiting as some of the drivers such as peer-effect or personal beliefs have subjective value, and individuals rarely possess perfect market information [17,[33][34][35]. Authors then use a utility or social threshold to characterise their decision-making process [62,63]. ...
... Despite ABMs' strength in providing insights on emergent system behaviour, two main limitations are still outstanding: the use of rational choice-based decision-making [33][34][35] and synthetic characterisation of their temporal dynamics, rather than utilising actual time horizons. Then, the use of ANNs as a basis for decision-making could be considered to help address the limitations of ABM. ...
This paper investigates the spatio-temporal patterns of solar photovoltaic (PV) adoption, solving the ongoing need to inform the management of the distribution networks with spatially explicit estimations of PV adoption rates. This work addresses a key limitation of agent-based models (ABMs) that use rule or equation-based decision-making. It achieves this by adopting an aggregated definition of the agents using artificial neural networks (ANN) as the criteria for decision-making. This novel approachdraws from both ABM and Spatial Regression methods. It incorporates spatial and temporal dependencies as well as social dynamics that drive the adoption of PVs. Consequently, the model yields a more realistic characterisation of decision-making whilst reflecting individual behaviours for each location following the real-world layout. The model utilises the ANN’s approximation capabilities to generate knowledge from historical PV data, as well as adapt to changes in data trends. First, an autoregressive model is developed. This is then extended to capture the population heterogeneity by introducing socioeconomic variables into the agent’s decision-making. Both models are empirically validated and benchmarked against the Bass Model.
Results suggest that the model can account for the spatio-temporal and social dynamics that drive the adoption process and that the ABM and ANN integrated model has superior adaptive capabilities to the Bass model. The proposed model can estimate spatio-temporally explicit forecasts for up to five months with an accuracy of 80%. In line with the literature, results suggest that income, electricity consumption and the average household size variables yield the best results.
... The decision-making process is the process by which an individual commits to following a choice when alternatives exist, even when these alternatives are not known or analyzed [21]. Few studies have focused on the influence of decision-making process factors on the heterogeneity of practices [22][23][24][25]. Some studies modeled the decision-making process in order to better understand farmers' behavior [18,25,26]. ...
... Few studies have focused on the influence of decision-making process factors on the heterogeneity of practices [22][23][24][25]. Some studies modeled the decision-making process in order to better understand farmers' behavior [18,25,26]. Daydé (2017) developed a conceptual model of the decision-making process and hypothesized that the heterogeneity of the process among farmers explained the heterogeneity of practices. ...
... Thus, the more reactive the farmer was, the later the farmer started irrigating. In a previous study of factors that influence fungicide applications on soft wheat [25], a high level of reactivity was associated with adaptive behavior. Similarly, Rodriguez et al. (2011) showed that reactivity (or plasticity) provided greater resilience to change than anticipation (or rigidity) when facing uncertainty since it improved adaptive behaviors and strategies [45]. ...
Agricultural practices are heterogeneous among farmers in the face of climate hazards. Structural and material resources as well as risk preferences explain some of this heterogeneity, but little is known about how psychological factors associated with the decision-making process may explain differences in practices among farmers. The aim of this study was to understand whether decision-making process factors help explain the heterogeneity of a specific practice—the date of first irrigation—among maize farmers, along with material and structural factors. We conducted semi-directed interviews with 35 farmers who irrigated maize in southwestern France. We analyzed discriminating factors of the decision-making process, such as reactivity (i.e., capacity to change plans), deliberation (i.e., level of internal information used to make decisions) and assistance (i.e., level of external information used to make decisions). We used two complementary statistical methods (linear regression and regression trees) to analyze the database. Our study confirms the influence of material and structural factors, and also reveals the strong influence of decision-making process factors. A high level of reactivity is associated with adaptive behavior. Moreover, using decision-support tools and technologies helps farmers to manage the use of water resources. These elements could be used by advisors and public policy-makers in the agriculture sector to improve adaptation.
... Agent-based models have been deployed to investigate decisionmaking regarding household adaptation to evolving flood risks 36 and the potential for consequent outmigration 37 . A further body of literature has explored farmer decision-making and economic outcomes under various climate and policy scenarios [38][39][40][41] . A subset of these ABMs has explored smallholder farmer migration decisions and dynamic push-pull factors, including changing environmental conditions 14,[42][43][44][45][46][47] . ...
Climate change is anticipated to impact smallholder farmer livelihoods substantially. However, empirical evidence is inconclusive regarding how increased climate stress affects smallholder farmers’ deployment of various livelihood strategies, including rural–urban migration. Here we use an agent-based model to show that in a South Asian agricultural community experiencing a 1.5 oC temperature increase by 2050, climate impacts are likely to decrease household income in 2050 by an average of 28%, with fewer households investing in both economic migration and cash crops, relative to a stationary climate. Pairing a small cash transfer with risk transfer mechanisms significantly increases the adoption of migration and cash crops, improves community incomes and reduces community inequality. While specific results depend on contextual factors such as risk preferences and climate risk exposure, these interventions are robust in improving adaptation outcomes and alleviating immobility, by addressing the intersection of risk aversion, financial constraints and climate impacts. Smallholder farmers will be impacted substantially by climate change and need to adapt. Agent-based modelling shows that interventions, particularly cash transfer paired with risk transfer mechanisms, lead to increased migration and uptake of cash crops, with higher income and lower inequality.
