Scenarios are widely used in research to simulate decision-making environments

Their study found a significant number of behavioural bio-security policies in seven European countries, many of which appeared to match theoretical behavioural change frameworks. However, the most frequent strategies relied on the most basic interventions , and there was little evidence of the systematic use of methods from the behavioural sciences to develop these policies. If this suggests there remains some way to travel before the social sciences are integrated within bio-security policy making, other research continues to highlight the potential value of these approaches. For example, research on the role of information cues reveals that bio-security behaviours can be improved when messages are shown graphically, rather than linguistically or numerically.Drawing on Kahneman and Tversky’s ‘prospect theory’ in which avoiding losses are preferable to accruing gains, Hansson and Lagerkvist show how farmers’ disease management decisions reflect farmers individual assessments of risk. However, when farmers are faced with managing an ongoing disease outbreak, decisions reflect a preference of avoiding losses; gains are only preferred when they seek to prevent future disease outbreaks. Other research has sought to examine how social information and the behaviour of other farmers can influence farmers’ bio-security decisions. Using an experimental simulation, Merrill et al. for instance show that willingness to invest in bio-security decreases when information on environmental disease prevalence is uncertain,stacking pots reflecting an optimism bias that farmers’ herds will not become infected.

Alternatively, when more information is provided about bio-security practices on neighbouring farms, bio-security investment decreases. This work is interesting in that it suggests that social norms of what constitutes ‘bio-security citizenship’ , appropriate conduct or what has been referred to as ‘good farming’ may not be influential in bio-security decision making. Burton suggests that ‘good farming’ refers not only to economic forms of capital, but symbolic cultural capital: the visible demonstration of practical knowledge such as good stockman ship, symbols of appropriate farm maintenance such as clean farmyards and tidy hedgerows, and attributes such as hard work. These symbols are encoded and disseminated within discursive scripts, reinforcing their cultural legitimacy . In this way, good farming acts as a heuristic to provide a strategy to guide, interpret and make decisions in conditions of uncertainty. Other strategies of decision-making are available to farmers, however, and the selection of good farming to guide decisions represents what Sunstein and Ullmann-Margalit refer to as a second-order decision. For Burton and Paragahawewa , the value of the good farmer approach lies in recognising and utilising cultural capital to create more culturally salient agricultural policy. Rather than simply rely on financial payments, they instead recommend the development and incorporation of measures of cultural capital into agricultural policy, and/or restructuring agricultural policy to directly encourage the generation of cultural capital. This may include directly measuring farmers’ ‘skills’ in order to allow them to publicly demonstrate what is valued by the farming community. Whilst Burton and Paragahawewa note that some cultural values might be hard to measure , objectifying cattle purchasing skills may provide a relatively easy way of incorporating the cultural capital of good farming into animal disease management policy. For example, recent research has established a link between farmers’ understandings of good farming and bio-security practices .

In particular, cattle purchasing is likely to be connected to and reflect good farming in a number of ways. Firstly, purchasing cattle risks the introduction and transmission of new diseases to animals within the herd and, for some diseases that can be subsequently transmitted within the local environment, to animals on neighbouring farms. For those farms that need to replace stock, however, different forms of institutional capital – such as certification and ranking schemes – can help provide assurance to the purchaser that they are buying from a good farmer and are running the risk of being labelled a bad farmer by introducing disease into their herd or area. For example, Enticott et al. describe how the number of years a farm has been free from disease effectively establishes a good farming rating that may incentivise improved bio-security when it is required to be displayed at the point of sale. The extent to which these forms of information are a reliable guide to whether the farmer is a ‘good farmer’ may, however, be compromised by farmers’ own spatial understanding of disease transmission and by blaming disease outbreaks on perceived government failings, rather than ‘bad farming’ . Secondly, the avoidance of disease through careful cattle purchasing should allow farmers to display other forms of symbolic cultural capital. An outbreak of bTB, for instance, would lead to a farm’s business being subject to a range of trading restrictions, denying the opportunity to farm with autonomy, which is highly valued by farmers in the farming script of ‘being my own boss’ which symbolises farmers’ success at running their own farm well rather than being told how to farm by government. Indeed, an outbreak of bTB would mean that many farming decisions would be subject to bureaucratic procedures and determined by government officials: farmers would be unable to attend market to sell their cattle. As a result, farms may become over-stocked, and cattle suffer poor welfare. Failing to avoid disease through responsible cattle purchasing therefore compromises farmers’ abilities to display the embodied and practical skills of the good farmer symbolised by good-looking cattle either on show at markets or at pasture. Similarly, participation at livestock markets reflects the significance of the autonomous farmer consistent with good farming. Providing measures of good farming in relation to animal disease may therefore help cattle purchasers identify good farmers, and help them avoid becoming a bad farmer as a consequence of poor cattle purchases. The extent to which such measures can successfully symbolise the good farmer and influence cattle purchasing is explored in the remainder of this paper.

Studies of behavioural influences in disease management reveal two distinct methodological approaches. On the one hand, agricultural economists, drawing on methodologies from behavioural psychology, have conducted experiments to simulate the effects of information provision and financial incentives upon bio-security behaviours. On the other hand, sociological research has sought to conceptualise and describe in-depth farmers’ responses to disease events and policy interventions. Each has their problems. Despite the promise of the experimental approach, research participants are often students responding to hypothetical situations wholly divorced from the practical skills and situational awareness that farmers use to respond to real-life context-dependent situations . By contrast, qualitative analyses of good farming and bio-security, whilst focused on real-world policies and disease incursions, are retrospective and subject to recall and social desirability biases. Rather than adopting one or the other, we seek to develop an innovative mixed-methods approach that allows us to quantitatively and qualitatively assess the value of symbolising good farming to influence farmers’ cattle purchasing decisions to prevent bTB. The following sections firstly provide information on the importance of bTB and the relevance of cattle purchasing before providing a detailed account of our methodological approach. In the United Kingdom, bTB is the UK’s most challenging endemic disease, resulting in the premature death of approximately 35,000 cattle and costing the taxpayer in excess of £100 m every year . Managed by the government, the disease has a complex epidemiology involving transmission by legally protected wildlife, the culling of which for disease control purposes has raised political, social and economic challenges . 2007. Cattle movements have become recognised as an important part of the epidemiology of bTB. Studies have shown how the movement of cattle is one of the most important risk factors in infected herds, whilst movements also translocate disease from areas of high to low prevalence . Whilst infected farms are restricted by law from buying or moving cattle on or off farms, all other farms are free to act as they please. Nevertheless, the limitations of diagnostic tests and their frequency mean that these movements still pose a risk to other farmers.

Indeed, other countries with successful bTB eradication schemes, have governed the movement of all cattle between areas of different epidemiological risk using statutory and/or voluntary policies of ‘risk based trading’ and in doing so identify and provide cultural capital to good farmers. Whilst no such scheme currently exists in the UK for bTB, policy makers view cattle purchasing as an important practice on which to apply the behavioural sciences in order to govern cattle movements through behavioural nudges rather than regulation. To understand the impact of different ways of objectifying good farming,sawtooth greenhouse we devised a novel mixed-methods approach. Avoiding experimental approaches involving non-farmers, our approach involved simulating cattle purchasing with farmers who buy and sell cattle. Many studies within the behavioural sciences involve randomised controlled trials, but this approach was not available and not suitable: we were not able to alter the information provided at the point of sale.The diversity of cattle, buyers and sellers also makes controlling for the effect of a single intervention a significant methodological challenge. Instead, our approach sought to simulate cattle purchasing, whilst also allowing farmers to reflectively deliberate on the reasons for their purchases and the value of different behavioural insights. To do this, we developed cattle purchasing game in Mural – a web-based interactive whiteboard – in which participants moved around a Monopoly-style board . Players progressed around the board by rolling one die. All games were played online via Zoom due to Covid 19 lockdown restrictions. Game play was organised using a “branch and bottleneck” structure. Branches reflect different contextual influences that participants land on at random throughout the game. This allowed us to introduce an element of competitiveness between players: points were awarded for landing on squares that reflected ‘positive’ contexts. No points were awarded for landing on negative blue squares. Red squares were a bTB test: if players landed on these, they were required to roll an even number to pass the bTB test,otherwise they would miss a go. Bottlenecks were cattle purchasing events that all players had to complete at the same time and were located in each corner square of the game board. Once one player reached a corner square, all other players also moved there.

Players were then read a cattle purchasing scenario and asked to make a choice between four adverts.They provide opportunities to elicit attitudes and beliefs about complex and potentially sensitive situations and to examine how people may respond to future events . Scenarios work best when they are based on plausible and familiar situations . Scenarios were therefore developed based on a prior research project on cattle purchasing involving farmers and vets. To ensure the scenarios reflected real-world cattle purchasing opportunities, specific versions were developed for three sectors: dairy, store cattle, and calf-rearing. For each scenario, adverts contained information to symbolise good farming in order to influence purchase choices. Firstly, farmers could use pictures of the animals to derive good farming information. For scenarios 1 and 2, pictures were of cattle in a livestock market, but for scenarios 3 and 4 animals were pictured on farm. Secondly, adverts featured two different conceptual measures of good farming. All adverts contained a logo stating how many years free the herd had been from bTB and the geographical average years free for the area in which the farm was located. Values were set randomly. In this method, good farming is symbolised by longer periods of disease freedom; ‘bad farmers’ would avoid purchasing from farms who had recently had an outbreak for fear of introducing disease. Scenarios 2 and 4 also contained a ‘Good Farmer Rating’ to graphically indicate the percentage of satisfied previous customers for each vendor. The aim of this logo was to convey levels of trust and reputation of the seller, which had seen to be important considerations when purchasing cattle from our previous research, and found in other research by Hidano et al. . Presented as a star rating, the logo was similar to review ratings found on internet shopping sites. Two ratings were set at 95% and two at 70% satisfaction. In addition to these measures of good farming, scenarios 1 and 3 explored the effect of different compensation regimes upon purchase decisions. Two different schemes were presented: two sales adverts stated that the purchaser would receive 50% compensation if the animal ever tested positive for bTB in future.