{"title":"Recognised cognitive biases: How far do they explain transport behaviour?","authors":"Stephen John Watkins , Charles Musselwhite","doi":"10.1016/j.jth.2024.101941","DOIUrl":null,"url":null,"abstract":"<div><div>Human beings think in a slow, careful and logical way for important and complex issues and a fast, intuitive way for most decisions. The logical mechanism takes too much effort for the myriad of daily decisions. For example, logical thinking can be combined only with walking slowly not quickly. Hence behavioural approaches that assume humans make decisions logically are contrary to the evidence. Intuitive thinking is open to perceptual errors called ‘cognitive biases’. Cognitive biases are common and wide spread. In this paper we review salient cognitive biases that effect decision-making around transport using Dror's eight sources of cognitive bias described in three categories: (i) case specific biases (to do with the data or knowledge itself); (ii) environment, culture and experience bias, (between the data and the person acting upon the data), and; (iii) bias originating from human nature, (the cognitive make-up of the human brain shared across all people, regardless of the specific case, data or knowledge or the specific person doing the analysis).</div><div>These influence people's transport behaviour and the decisions of policy makers and engineers. Of especial importance are <em>loss aversion</em> (valuing something you have about twice as highly as you would value it if you were considering acquiring it); various other biases favouring the status quo; and various errors of risk perception. We conclude by suggesting more education and training and multi sectoral and multidisciplinary working is needed to help develop awareness of bias and identifying susceptibility to bias and how to overcome them where possible.</div><div>This description is an expansion of a table contained in Health on the Move 3:the Reviews (Mindell and Watkins, 2024)</div></div>","PeriodicalId":47838,"journal":{"name":"Journal of Transport & Health","volume":"40 ","pages":"Article 101941"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transport & Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214140524001877","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Human beings think in a slow, careful and logical way for important and complex issues and a fast, intuitive way for most decisions. The logical mechanism takes too much effort for the myriad of daily decisions. For example, logical thinking can be combined only with walking slowly not quickly. Hence behavioural approaches that assume humans make decisions logically are contrary to the evidence. Intuitive thinking is open to perceptual errors called ‘cognitive biases’. Cognitive biases are common and wide spread. In this paper we review salient cognitive biases that effect decision-making around transport using Dror's eight sources of cognitive bias described in three categories: (i) case specific biases (to do with the data or knowledge itself); (ii) environment, culture and experience bias, (between the data and the person acting upon the data), and; (iii) bias originating from human nature, (the cognitive make-up of the human brain shared across all people, regardless of the specific case, data or knowledge or the specific person doing the analysis).
These influence people's transport behaviour and the decisions of policy makers and engineers. Of especial importance are loss aversion (valuing something you have about twice as highly as you would value it if you were considering acquiring it); various other biases favouring the status quo; and various errors of risk perception. We conclude by suggesting more education and training and multi sectoral and multidisciplinary working is needed to help develop awareness of bias and identifying susceptibility to bias and how to overcome them where possible.
This description is an expansion of a table contained in Health on the Move 3:the Reviews (Mindell and Watkins, 2024)