The University of Southampton
University of Southampton Institutional Repository

Passengers as defenders: unveiling the role of customer-company identification in the trust-customer citizenship behaviour relationship within ride-hailing context

Passengers as defenders: unveiling the role of customer-company identification in the trust-customer citizenship behaviour relationship within ride-hailing context
Passengers as defenders: unveiling the role of customer-company identification in the trust-customer citizenship behaviour relationship within ride-hailing context

Ride-hailing platforms such as Didi, Uber, and Lyft have changed the travel industry. Promoting the passengers' trust in platform and customer citizenship behaviour (CCB) is both challenging and important. This study employed a mixed-methods design, consisting of 21 interviews and 351 online surveys, to develop and examine the trust-CCB model in the ride-hailing context. Our findings reveal that platforms can foster passengers' trust by sending service-related signals (i.e., service quality and structure assurance) and a firm-related signal (i.e., platform reputation). Customer-company identification (CCI) mediates the relationship between passengers' trust and CCB, where passengers engage in CCB by providing recommendations, exhibiting forgiving behaviour, providing feedback, and participating in research in ride-hailing. Additionally, firm-related signals, including platform size and reputation, enhance the positive relationship between trust and CCI. These findings contribute to the body of knowledge on trust, CCB, and signaling theory, providing potential practical implications for ride-hailing platforms.

Customer citizenship behaviour, Ride-hailing, sharing economy, signaling theory, trust
0261-5177
Su, Linlin
56cf7586-66c9-49ad-96dd-0a16ff1ae346
Cheng, Xusen
eaa8bd72-259e-43e0-912f-eb724b132fd7
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc
Su, Linlin
56cf7586-66c9-49ad-96dd-0a16ff1ae346
Cheng, Xusen
eaa8bd72-259e-43e0-912f-eb724b132fd7
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc

Su, Linlin, Cheng, Xusen and Zarifis, Alex (2024) Passengers as defenders: unveiling the role of customer-company identification in the trust-customer citizenship behaviour relationship within ride-hailing context. Tourism Management, 107, [105086]. (doi:10.1016/j.tourman.2024.105086).

Record type: Article

Abstract

Ride-hailing platforms such as Didi, Uber, and Lyft have changed the travel industry. Promoting the passengers' trust in platform and customer citizenship behaviour (CCB) is both challenging and important. This study employed a mixed-methods design, consisting of 21 interviews and 351 online surveys, to develop and examine the trust-CCB model in the ride-hailing context. Our findings reveal that platforms can foster passengers' trust by sending service-related signals (i.e., service quality and structure assurance) and a firm-related signal (i.e., platform reputation). Customer-company identification (CCI) mediates the relationship between passengers' trust and CCB, where passengers engage in CCB by providing recommendations, exhibiting forgiving behaviour, providing feedback, and participating in research in ride-hailing. Additionally, firm-related signals, including platform size and reputation, enhance the positive relationship between trust and CCI. These findings contribute to the body of knowledge on trust, CCB, and signaling theory, providing potential practical implications for ride-hailing platforms.

Text
Passengers as defenders 1-s2.0-S026151772400205X-main Alex Zarifis - Version of Record
Available under License Creative Commons Attribution.
Download (4MB)

More information

Accepted/In Press date: 6 November 2024
Published date: 14 November 2024
Keywords: Customer citizenship behaviour, Ride-hailing, sharing economy, signaling theory, trust

Identifiers

Local EPrints ID: 496349
URI: http://eprints.soton.ac.uk/id/eprint/496349
ISSN: 0261-5177
PURE UUID: a6dd52b2-cf20-4e28-9bec-d60c1ccf09df
ORCID for Alex Zarifis: ORCID iD orcid.org/0000-0003-3103-4601

Catalogue record

Date deposited: 12 Dec 2024 17:38
Last modified: 13 Dec 2024 03:10

Export record

Altmetrics

Contributors

Author: Linlin Su
Author: Xusen Cheng
Author: Alex Zarifis ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×