Agent-Based Modelling of Adoption of Novel Proteins in the UK: Impacts and Interactions with Transitions to Sustainable Systems

英国采用新型蛋白质的基于主体的建模：与可持续系统过渡的影响和相互作用

• 批准号: 2035260
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2035260
• 关键词: Agent; Based; Modelling; Adoption; Novel

Strategic themes: Mathematical Sciences, EnergyResearch Area(s): Resource Efficiency, Non-Linear SystemsResearch objectives of the project: Sustainable protein sources are a key component in achieving global climate goals. However, much uncertainty remains, especially with regards to how this techno-social transition may occur. The research aims to develop realistic computational simulations of individual decision-making to understand this 'how'. The key objective is to construct a bottom-up model that can reliably, with appropriate uncertainty, simulate trajectories of the adoption of novel sustainable protein (e.g. plant-based, cell-based, insect) in British consumers, and pose 'what-if' scenarios to generate evidence of a range of possible outcomes. Embedded in this is the analysis of interactions between several UN Sustainable Development Goals (SDGs) - namely hunger (SDG2), energy (SDG7), health (SDG3), land (SDG14), water (SDG6) and climate (SDG13) systems. Specifically, it seeks to answer the following question - how may accelerators and barriers to widespread adoption of novel proteins by British consumers impact sustainable food transitions and related systems?The novel science methodology of the research within EPSRC's remit. What will the student be doing?The project will employ an agent-based modelling (ABM) approach to simulate the adoption of novel proteins within the British public. The novel element of this research is twofold. This project, using an ABM approach, is among the first to model this particular transition. It pursues a systems led approach that cuts across research disciplines, assimilating evidence and data from the mathematical and social sciences. Secondly, the interactions between SDGs continues to receive much research interest, with a number of different methods being applied. However, none to date have employed an ABM approach. The outputs of this project will offer new insights that existing methods have difficulty in capturing, for example the non-linearity and unpredictability of interactions. Furthermore, it will provide evidence to policymakers on how best to support uptake of novel proteins, and to industry and manufacturers on scientifically grounded consumer adoption trajectories. Specifically, the student will be studying how the factors for acceptance or rejection for conventional protein substitutes (e.g. plant-based, cell-based, and insect alternatives) at the individual level, may play out at societal level, and the possible non-linear, path dependent nature of adoption and mass behaviour change. The student will also, taking a systems approach, link these food choices to a set of energy, greenhouse gas emissions, health, land, and water impacts to understand wider SDG interactions and the consequences for resource efficiency.

战略主题：数学科学、能源研究领域：资源效率、非线性系统项目研究目标：可持续蛋白质来源是实现全球气候目标的关键组成部分。然而，仍然存在很多不确定性，特别是关于这种技术社会转型如何发生。该研究旨在开发个人决策的真实计算模拟，以了解这种“如何”。主要目标是构建一个自下而上的模型，该模型可以在适当的不确定性下可靠地模拟英国消费者采用新型可持续蛋白质（例如基于植物的、基于细胞的、基于昆虫的）的轨迹，并提出“假设” '场景来生成一系列可能结果的证据。其中包含对多个联合国可持续发展目标 (SDG) 之间相互作用的分析，即饥饿 (SDG2)、能源 (SDG7)、健康 (SDG3)、土地 (SDG14)、水 (SDG6) 和气候 (SDG13) 系统。具体来说，它试图回答以下问题：英国消费者广泛采用新型蛋白质的加速器和障碍如何影响可持续食品转型和相关系统？ EPSRC 职权范围内的研究的新颖科学方法。学生将做什么？该项目将采用基于代理的建模 (ABM) 方法来模拟英国公众对新型蛋白质的采用。这项研究的新颖之处是双重的。该项目使用 ABM 方法，是最早对这一特定转变进行建模的项目之一。它追求一种系统主导的方法，跨越研究学科，吸收数学和社会科学的证据和数据。其次，可持续发展目标之间的相互作用继续受到广泛的研究兴趣，并应用了许多不同的方法。然而，迄今为止还没有采用 ABM 方法。该项目的成果将提供现有方法难以捕获的新见解，例如相互作用的非线性和不可预测性。此外，它将向政策制定者提供关于如何最好地支持新型蛋白质的吸收的证据，并为工业界和制造商提供基于科学依据的消费者采用轨迹的证据。具体来说，学生将研究个人层面上接受或拒绝传统蛋白质替代品（例如基于植物的、基于细胞的和昆虫的替代品）的因素如何在社会层面上发挥作用，以及可能的非线性，采用的路径依赖性质和大众行为改变。学生还将采用系统方法，将这些食物选择与一系列能源、温室气体排放、健康、土地和水影响联系起来，以了解更广泛的可持续发展目标相互作用以及对资源效率的影响。