Analytical behaviour: a study of decision-making facilitated by visual analytics
Analytical behaviour: a study of decision-making facilitated by visual analytics
This thesis explores the application of economics to the study of decision-making in visual analytics. It builds initially on an analysis of nine models from visual analytics and human-computer interaction; the result is a set of four principles that form the basis of a new theory and model of ‘analytical behaviour’. The term analytical behaviour is defined as the process of decision-making facilitated by visual analytics. Along with a survey of real-world applications looking at the design space of the same topic, the proposed theory and model aim to characterise analytical behaviour prior to the application of prospect theory.
There are two assumptions underlying this work. Firstly, that analytical behaviour can be formally characterised and also modelled descriptively, not just normatively. Secondly, that such a model would need to account for representation effects that bias decision-making. Empirical evidence from the main experiment in this thesis shows a significant number of people make different choices when the visual display of data is changed, such as the height-to-width ratio of a line chart.
This thesis concludes that prospect theory- a descriptive model of decision-making from economics - can be applied to the study of analytical behaviour, but it does not fully account for the impact of representation effects on risk perception for some people. This conclusion is based on the analysis presented in the final chapter, which builds on the theory and model of analytical behaviour with calculations added to prospect theory to account for representation effects and the perception of risk for most decision-makers.
University of Southampton
Booth, Paul Michael
6311e94d-8edd-4c9a-8467-7aeabff6559e
10 November 2019
Booth, Paul Michael
6311e94d-8edd-4c9a-8467-7aeabff6559e
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Booth, Paul Michael
(2019)
Analytical behaviour: a study of decision-making facilitated by visual analytics.
University of Southampton, Doctoral Thesis, 196pp.
Record type:
Thesis
(Doctoral)
Abstract
This thesis explores the application of economics to the study of decision-making in visual analytics. It builds initially on an analysis of nine models from visual analytics and human-computer interaction; the result is a set of four principles that form the basis of a new theory and model of ‘analytical behaviour’. The term analytical behaviour is defined as the process of decision-making facilitated by visual analytics. Along with a survey of real-world applications looking at the design space of the same topic, the proposed theory and model aim to characterise analytical behaviour prior to the application of prospect theory.
There are two assumptions underlying this work. Firstly, that analytical behaviour can be formally characterised and also modelled descriptively, not just normatively. Secondly, that such a model would need to account for representation effects that bias decision-making. Empirical evidence from the main experiment in this thesis shows a significant number of people make different choices when the visual display of data is changed, such as the height-to-width ratio of a line chart.
This thesis concludes that prospect theory- a descriptive model of decision-making from economics - can be applied to the study of analytical behaviour, but it does not fully account for the impact of representation effects on risk perception for some people. This conclusion is based on the analysis presented in the final chapter, which builds on the theory and model of analytical behaviour with calculations added to prospect theory to account for representation effects and the perception of risk for most decision-makers.
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Final thesis
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Published date: 10 November 2019
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Local EPrints ID: 438599
URI: http://eprints.soton.ac.uk/id/eprint/438599
PURE UUID: 03e36c19-ac30-40b6-9f8f-5bd98791fad3
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Date deposited: 18 Mar 2020 17:30
Last modified: 17 Mar 2024 02:32
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Author:
Paul Michael Booth
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