Estimating the Value of Life, Injury, and Travel Time Saved Using a Stated Preference Framework

Niroomand, Naghmeh; Jenkins, Glenn P.

doi:10.1016/j.aap.2016.03.004

Cited by 16 publications

(14 citation statements)

References 28 publications

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“…(6) f indicates the number of accidents leading to fatality and the risk is calculated as the ratio of fatality to population (Niroomand and Jenkins, 2016). (7) MRS is interpreted as the implicit value of life, which gives VSL by averaging on individuals.…”

Section: Methodsmentioning

confidence: 99%

“…However, it is not real to assume that people have the same preferences. To solve this problem, we use mixed Logit model which assumes that those who answer the questionnaire have non-homogeneous preferences (Veisten et al, 2013;Niroomand and Jenkins, 2016).…”

Section: Methodsmentioning

confidence: 99%

“…As random parameters are still unknown, a non-conditional probability is used in estimating the model. The following integral is calculated by the maximum simulated probability method (Niroomand and Jenkins, 2016). (12) In this research, the willingness to pay for a reduction in the risk of fatality and the risk of injury caused by accidents are calculated separately for all road users.…”

Section: Methodsmentioning

confidence: 99%

“…In order to obtain the amount of risk reduction of fatality and the risk of injury, the willingness to pay to reduce fatality and injury should be divided by the chance of dying in a car accident or the chance of being injured in a car accident. To estimate these relationships, the average number of fatalities or injuries and the average annual kilometers travelled in the last 5 years is required (Veisten et al, 2013;Niroomand and Jenkins, 2016).…”

Section: Methodsmentioning

confidence: 99%

“…In this research, the choice set has been created using the shifted design technique. The conventional approach to this work is the orthogonal design (Niroomand and Jenkins, 2016). If a full factorial design is used allowing for occurrence of all combinations of levels of attributes and the main effects and interactions, the set of choices allows for creation of 256 choices according to the 2 four-level attributes and 4 two-level attributes.…”

Section: Methodsmentioning

confidence: 99%

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Estimating the Value of Risk Reduction for Car Occupants

Fattahi¹,

Azami²,

Naderi³

2019

ERSJ

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Purpose:The paper tries to estimate the willingness to pay the value of statistical life of drivers in Tabriz highways. Design/Methodology/Approach: Data were obtained using a questionnaire whish was distributed among people who travel daily on Tabriz highways to study or work in 2017. Stated choice technique and the mixed logit model are used to estimate the individual's preferences to reduce the risk of fatality and injury. Findings: The results indicated the effects of cost, trip time, number of fatalities and injuries, number of speed cameras and speed limits on choosing a driving route. In addition, investigation of interactive effects of demographic variables and indices shows that only the interactive effects of age, income with indices are statistically significant. Practical Implications: Some policy implications to increase investment on highways and financimg road projects by road users including drivers. Originality/Value: Goverment strategy on highways development is to eliminate or reduce the number of fatalities and injuries.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Estimating the Value of Risk Reduction for Car Occupants

Fattahi¹,

Azami²,

Naderi³

2019

ERSJ

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Discrete Choice Experiments in Health Economics: Past, Present and Future

et al. 2018

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Objectives Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990–2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges. Methods A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated. Results Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels. Conclusions The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers’ confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research. Electronic supplementary material The online version of this article (10.1007/s40273-018-0734-2) contains supplementary material, which is available to authorized users.

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