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What encourages people to carpool? An evaluation of factors with meta-analysis

What encourages people to carpool? An evaluation of factors with meta-analysis
What encourages people to carpool? An evaluation of factors with meta-analysis
Non-household carpools (where two or more commuters from different residences travel together in the same private vehicle) bring public benefits. To encourage and incentivise it, transport practitioners and researchers must understand its private motivations and deterrents. Existing studies often report conflicting results or non-generalisable findings. Thus, a quantitative systematic review of the literature body is needed. Using meta-analysis, this study synthesised 22 existing empirical studies (representing over 79,000 observations) to produce an integrated review of the carpooling literature. The meta-analysis determined 24 non-household carpooling factors, and their effect sizes. Factors such as number of employees (\(\bar{r} = 0.42\)), partner matching programs (\(\bar{r} = 0.42\)), female (\(\bar{r} = 0.22\)) and fixed work schedule (\(\bar{r} = 0.15\)) were found to have strong effects on carpooling while judgmental factors (such as the motivation to save costs) only exhibited small influence (\(\bar{r} < 0.1\)). Based on the significant effects, the paper discussed prospects for improving carpooling uptake by developing: (i) target demographics, (ii) selling points for marketing, (iii) carpooling partner programs and (iv) multiple employer ‘super-pools’. The results warrant caution due to the small amount of studies synthesised. Transport practitioners might plan carpooling policies based on the findings; and transportation researchers might use the list of factors to model carpooling behaviour
carpool, liftshare, rideshare, meta-analysis, transport demand management
0049-4488
423-447
Neoh, Jun Guan
2bbc9ad6-b5ad-477f-b62e-6db65c153687
Chipulu, Maxwell
12545803-0d1f-4a37-b2d2-f0d21165205e
Marshall, Alasdair
93aa95a2-c707-4807-8eaa-1de3b994b616
Neoh, Jun Guan
2bbc9ad6-b5ad-477f-b62e-6db65c153687
Chipulu, Maxwell
12545803-0d1f-4a37-b2d2-f0d21165205e
Marshall, Alasdair
93aa95a2-c707-4807-8eaa-1de3b994b616

Neoh, Jun Guan, Chipulu, Maxwell and Marshall, Alasdair (2017) What encourages people to carpool? An evaluation of factors with meta-analysis. Transportation, 44 (2), 423-447. (doi:10.1007/s11116-015-9661-7).

Record type: Article

Abstract

Non-household carpools (where two or more commuters from different residences travel together in the same private vehicle) bring public benefits. To encourage and incentivise it, transport practitioners and researchers must understand its private motivations and deterrents. Existing studies often report conflicting results or non-generalisable findings. Thus, a quantitative systematic review of the literature body is needed. Using meta-analysis, this study synthesised 22 existing empirical studies (representing over 79,000 observations) to produce an integrated review of the carpooling literature. The meta-analysis determined 24 non-household carpooling factors, and their effect sizes. Factors such as number of employees (\(\bar{r} = 0.42\)), partner matching programs (\(\bar{r} = 0.42\)), female (\(\bar{r} = 0.22\)) and fixed work schedule (\(\bar{r} = 0.15\)) were found to have strong effects on carpooling while judgmental factors (such as the motivation to save costs) only exhibited small influence (\(\bar{r} < 0.1\)). Based on the significant effects, the paper discussed prospects for improving carpooling uptake by developing: (i) target demographics, (ii) selling points for marketing, (iii) carpooling partner programs and (iv) multiple employer ‘super-pools’. The results warrant caution due to the small amount of studies synthesised. Transport practitioners might plan carpooling policies based on the findings; and transportation researchers might use the list of factors to model carpooling behaviour

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More information

e-pub ahead of print date: 16 September 2015
Published date: 1 March 2017
Keywords: carpool, liftshare, rideshare, meta-analysis, transport demand management
Organisations: Centre of Excellence in Decision, Analytics & Risk Research

Identifiers

Local EPrints ID: 381789
URI: http://eprints.soton.ac.uk/id/eprint/381789
ISSN: 0049-4488
PURE UUID: bbbe74a6-0226-4a81-b242-30c9a93464be
ORCID for Maxwell Chipulu: ORCID iD orcid.org/0000-0002-0139-6188
ORCID for Alasdair Marshall: ORCID iD orcid.org/0000-0002-9789-8042

Catalogue record

Date deposited: 15 Oct 2015 13:05
Last modified: 15 Mar 2024 03:33

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Contributors

Author: Jun Guan Neoh
Author: Maxwell Chipulu ORCID iD

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