Understanding continuance intention in traffic-related social media: Comparing a multi-channel information community and a community-based application

Abstract

Purpose

Recent technological advances have led to the growing popularity of traffic-related social media platforms which facilitate drivers to easily share, consume and exchange traffic information instead of the traditional ways using TV or radio. By integrating the information systems success model, social capital theory and dedication-based commitment mechanism, the purpose of this paper is to examine the varying degree of effectiveness in maintaining user’s continuance intention between two different social media platforms for traffic information.

Design/methodology/approach

The data were collected through online questionnaires from two platforms. One is a multi-channel traffic information community that has been specialized in traffic information for many years and has adopted several kinds of social media to engage with its audience. The other is a community-based traffic application created to help people exchange and contribute traffic information with real-time navigation.

Findings

The findings show that the effects of satisfaction and affective commitment on continuance intention are stronger in the community-based traffic application while their antecedents play different roles in shaping satisfaction and affective commitment due to the nature and characteristics of these two groups.

Originality/value

This study will be the first attempt to understand what matters to users and what can retain users to routinely use a specific traffic-related social media platform in their daily lives. This is also one of the first empirical studies that examine both transactional and relational points of view on users’ continuance intention.

Citation

Chen, J.V., Nguyen, T. and Oncheunjit, M. (2020), "Understanding continuance intention in traffic-related social media: Comparing a multi-channel information community and a community-based application", Internet Research, Vol. 30 No. 2, pp. 539-573. https://doi.org/10.1108/INTR-02-2019-0045