Barriers to the use of technology-based crime prevention methods to protect agricultural assets.

Abstract

Agricultural assets are becoming increasingly attractive to organised criminal groups targeting farmers globally. As such, there is a need to better understand the crime prevention methods farmers currently use, and how they choose those methods.Farm crime prevention decision-making is affected by a range of behavioural science influences, which move away from the idea of farmers as utility maximisers. Examples of behavioural factors that influence crime prevention decision-making include social norms, fatalism, hyperbolic discounting and risk aversion, stress, and gambler’s fallacy (Smith, 2018). Farmers decisions are driven by cost, convenience, time, ease of implementation, and level of information on the efficacy of crime prevention methods (Smith, 2018).

Description

There is a range of existing research relating to farm crime prevention (Bunei, Rono, Chessa, 2014; Harkness, 2017; Nunns, Wills, Montrose, 2022; O’Brien, Windle, 2022), as well as farmer behaviour and decision-making (Small, Maseyk, 2022; Feola et al., 2015; Austin et al., 1998; Edwards-Jones, 2006; Willock, at al., 1999). However, there is little research existing that explores farmer crime prevention decision-making (Smith & Byrne, 2017; Smith, 2018). This project will extend the earlier work of the Project Lead to explore how farmer behaviour and underlying attitudes are influencing technology-based crime prevention use, adoption, and non-use within the UK.

National efforts have been made in very recent times to address the issues relating to rural and farm crime. This includes the establishment of the National Rural Crime Unit in April 2023, the passing of the Equipment Theft (Prevention) Act 2023, and the introduction of the Rural Crime (Strategy) Bill 2023, although this latter initiative did not reach its second reading in the House of Commons before Parliament was dissolved. However, it is recognised that criminality in the rural space is becoming more organised in its nature, and as such will become increasingly agile in responding to farmer and police efforts to protect agricultural assets (Smith & Byrne, 2019; Smith, 2024; Tudor, 2024). As such, the need for an understanding around farmer choices around the use of technology-based crime prevention methods, and how to frame the information to influence greater uptake, may lend a hand in the deterrence of organised criminals in the rural space.

Farm crime prevention decision-making is affected by a range of behavioural science influences, which move away from the idea of farmers as utility maximisers. Examples of behavioural factors that influence crime prevention decision-making include social norms, fatalism, hyperbolic discounting and risk aversion, stress, and gambler’s fallacy (Smith, 2018). Farmers decisions are driven by cost, convenience, time, ease of implementation, and level of information on the efficacy of crime prevention methods (Smith, 2018).