Chronic obstructive pulmonary disease (COPD) accounts for one death every 20 minutes in England and Wales. RAND Europe and the University of Cambridge are conducting a study on "Living with Breathlessness" to improve the end-of-life care strategy for patients with advanced COPD: one which is based on a recognition of the slow relentless progression of non-malignant disease, its effect on patients and care-givers, and their stated care preferences.
Choice Modelling and Valuation Research
In many fields, the choices made by individuals will determine the effectiveness of policy. Therefore, understanding what drives people's choices and how these choices may change is critical for developing successful policy. Discrete choice modelling provides an analytical framework with which to examine and quantify the importance of key drivers of people’s choices. Moreover, in appraising policy options, the value placed on services, goods or environment by the population will determine whether public or private investments are worthwhile. Discrete choice modelling provides a crucial method for understanding and measuring the values attached by people to a variety of marketed and non-market goods and services.
The Choice Modelling and Valuation group provides specific expertise in using discrete choice modelling methods to understand and predict choice behaviour as a result of policy intervention. This work is frequently undertaken in the transport sector, but increasingly we are applying our expertise in other sectors, for example health and social care, post and communications and provision of regulated consumer services. Our contribution has been to take these methods out of the university environment and make them applicable to forecasting and evaluation issues in policy analysis.
More information about each is available in the Filter by Topic section below.
Our Work in the Transport Sector
RAND Europe specialises in the development of discrete choice travel demand models to address a wide range of transport policy options. The models are based entirely on evidence, using observations of individual travel behaviour. The model systems predict traveller responses under a wide range of policies, and take account of demographic changes over time. We develop models to evaluate transport policy at an urban, regional, national and international scale.
Members of RAND Europe's Choice Modelling and Valuation group have contributed to the development and testing of new modelling approaches in transport studies for decades. Several research studies have recently been conducted for the UK and other governments, as well as for transport operators.
RAND Europe has significant experience undertaking economic valuation studies to quantify the value of public sector goods and services across a range of sectors including transport, health, information and postal sectors. We provide specialist expertise in the use of stated preference methods, particularly stated choice experiments for eliciting consumers’ willingness to pay.
Valuations can be provided from DCM in the form of marginal benefits (e.g. willingness to pay) or in the form of consumer surplus or other overall measures of satisfaction.
Research Using Discrete Choice Modelling
Discrete Choice Modelling
The Choice Modelling and Valuation group has made major innovations and extensions to best practice in the area of discrete choice modelling, as a means by which to understand and predict choice behaviour.
Research in the Transport Sector
RAND Europe has contributed to the development and testing of new approaches in transport studies for over 25 years. The application of discrete choice models using observations of individual travel behaviour has allowed significant improvements in the quality and range of applicability of urban, regional and national (multi-modal) travel demand forecasting techniques.
Research in the Health Sector
The Choice Modelling and Valuation group applies its modelling expertise in such sectors as health and social care, to take these methods out of the university environment and make them applicable to forecasting and evaluation issues in policy analysis.