A meta-analysis and synthesis of public transport customer amenity valuation research. Issue 2 (4th March 2019)

• Record Type: Journal Article
• Authors: De Gruyter, Chris; Currie, Graham; Truong, Long T.; Naznin, Farhana
• Is Part Of: Transport reviews. Volume 39:Issue 2(2019)
• Page Start: 261
• Page End: 283
• Publication Date: 2019-03-04
• Subjects: Public transport -- transit -- customer amenity -- valuation -- in-vehicle time -- meta-analysis; Transportation -- Periodicals; Transportation engineering -- Periodicals; 380.5
• DOI: 10.1080/01441647.2018.1461708
• Languages: English
• ISSNs: 0144-1647

Abstract

ABSTRACT: This paper synthesises published research concerned with the valuation of public transport customer amenities. It includes normalisation of published values to equivalent terms, a meta-analysis of factors influencing these values, a review of valuation methods and issues faced in applying these methods, and an identification of gaps in knowledge. Some 57 separate research publications in this area were identified. Valuation methods adopted included stated preference, revealed preference, customer ratings, priority evaluator, maximum difference scaling and benefit/value transfer. Of these, stated preference was the most common published approach, however in practice benefit/value transfer is the most common method to apply values in project appraisal. Key issues associated with valuation include substantial variation in values (which are often context dependant) and the adoption of different units for expressing values, thereby limiting their transferability. Some 556 separate customer amenity values were identified relating to 97 separate amenity types. Almost all valuations were below 2 minutes of equivalent in-vehicle travel time value. Meta-analysis identified five types of significant predictors of values ( R 2 = 0.23): study location (Scandinavia), valuation method (stated preference), mode (train/metro), amenity group (access) and journey stage (boarding/alighting). Future research needs to disaggregate valuations by market segment.