Understanding the potential for behavioural economics to inform more effective planning and delivery of cycling projects

Author(s):  
Matt Higgins
Author(s):  
Ceri Sullivan

Abstract The political and dramatic intentions behind the use of appeals to the early modern public (on and off stage) have already been examined by Shakespeareans. This article points out the technical workings of such appeals by using two new areas of research on decision-making: the ethnography of public meetings and behavioural economics on how to influence choosers. These theories can illuminate the strategies used by the tribunes in handling the citizens of Coriolanus, by Antony in dealing with the plebeians in Julius Caesar, and by Buckingham and Richard when gathering support from the Londoners in Richard III. Using six common psychological biases (anchor-and-adjust, availability, representativeness, priming, arousal, and group norms), Shakespeare’s politicians prompt their hearers to change their minds: a celebrity warrior is recast as a wily tyrant, an execution as a murder, and a regent as the legitimate king.


2014 ◽  
Vol 56 (6) ◽  
pp. 717-736 ◽  
Author(s):  
Kyle Findlay ◽  
Jan Hofmeyr ◽  
Alice Louw

The traditional market research paradigm believes that, the more data you measure, the more potential for insight the data will hold. However, this paper takes the counter-intuitive standpoint that ‘less is more’. Drawing on the authors’ familiarity with neuroscience and behavioural economics, as well as five years’ worth of panel behavioural data in three categories and data from 2,769 studies across 1.9 million respondents, the paper argues that, just as it is important to ask the right questions in a survey, it is similarly important to measure ‘just enough’ but not too much information about brands. We show that measuring too much data is unnecessary and can even be detrimental to the richness of your data. Readers should take away practical guidelines for creating shorter, smarter surveys that still maintain the integrity of their data … and perhaps even improve it.


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