Examining The Impact Of Sample Size In The Analysis Of Bicycle-Sharing Systems

Keywords

arrival and departure rates; bicycle infrastructure; bicycle-sharing systems; CitiBike New York; destination choice; land use and built environment; linear mixed model; multinomial logit model; Sample size

Abstract

Research efforts examining bicycle-sharing systems (BSS) employed a wide range of sample size depending on the temporal or spatial aggregation. This paper proposes a systematic evaluation of the impact of sample size on model estimates, inference measures and predictive performance using data from New York City's CitiBike. We evaluate two major dimensions of BSS data: (1) system usage–impact of contributing factors on hourly arrival and departure rates at station level, (2) user destination choice–impact of factors on users' preference of destination station choice. The model estimation exercises for system demand and destination choice are conducted on several samples of data. The performance of these sample models in terms of parameters, inference statistics and predictions relative to a base sample data is observed. The results would help the analysts to make decisions on sample size for accurately examining BSS usage.

Publication Date

2-7-2017

Publication Title

Transportmetrica A: Transport Science

Volume

13

Issue

2

Number of Pages

139-161

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/23249935.2016.1223205

Socpus ID

84986239324 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84986239324

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