کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5091793 | 1478394 | 2016 | 19 صفحه PDF | دانلود رایگان |
- We conduct a controlled experiment to understand the value of information in a driving context.
- We estimate risk attitudes of individuals with and without the presence of information.
- Information results in reduced risk aversion characteristics of individuals.
- Individuals overestimate the value of information in less risky situations.
- Greater levels of risk aversion result in a greater value of reliability.
Risk attitudes are an important behavioural characteristic that influences people's valuation of information and reliability. In a transport context, information has become widely accessible to road users through ITS systems, GPS technology and the internet justifying the importance of understanding the valuation of information by travellers. There have been a number of studies that have looked at the value of information and the value of reliability for a road user. However, to date there has not been a study that explicitly evaluates the impact of having information within a choice set on an individual's risk attitudes, which ultimately affects their valuation for information and reliability. This study conducts a controlled laboratory experiment, using methods of experimental economics, to measure the risk attitudes of users with and without the presence of information in the choice set. A model derived from Expected Utility Theory is used to infer the risk attitudes of the participants. The results of the analysis indicate that the presence of information in the choice set reduces risk aversion, which causes a reduction in people's valuation of information and reliability. It is critical to systematically incorporate these differences into behaviour models, since neglecting this fundamental difference could result in erroneous policy decisions, with respect to overpricing information, or inappropriately allocating funds for information systems.
Journal: Journal of Choice Modelling - Volume 20, September 2016, Pages 16-34