ABSTRACT
Ridesharing is gradually replacing traditional taxi and mini-bus services due to numerous benefits associated with it. However, the subject of trust continues to be the most predominant issue in the sharing economy and ridesharing service is not an exception. Extant studies relating to consumer trust have examined trust antecedents and outcome and the most studies concentrate on trust in e-commerce, whereas areas such as ridesharing is given less attention.
This study sought to investigate the antecedents and outcome of consumer trust in ridesharing services and determined to find the mediating role of trust between the antecedents and outcome. Guided by trust path model, the study adopted the quantitative survey research methodology. A total of 364 Uber consumers within a university in Accra responded to the questionnaire and were conveniently sampled for the data. The university campus was chosen for the study because it cradles a cosmopolitan mix of transport services as the general public and uber drivers converge near designated places.
Covariance Based Sturctural Equation Modeling (CB-SEM) approach was employed in analysing the data gathered from the respondents of the study. The results showed that trust significantly influences word-of-mouth in ridesharing services. Furthermore, the antecedent factors of trust namely perceived application quality, information quality, user experience and proficiency, and brand recognition significantly influence trust. The result further indicated that brand recognition in ridesharing services proved to be the strongest antecedent factor of trust. Regarding the mediating role of trust between trust antecedent factors and word of mouth, it was found that trust produced no mediation between the antecedents factors of trust and word of mouth.
The no-mediation role that Trust plays between antecedents’ factors and outcome can be attributed to the fact that, ridesharing is a new entry in the transport sector. Secondly, the favourable reputation couched for the ridesharing services such Uber may be attributed to the service nature of ridesharing. The very fact that ridesharing service is electronic-oriented, intangible and novel, the motivation to engage the service far outweighs the social concern of trust.
In terms of research, the study adds to the body of knowledge on sharing economy by concentrating on the subject of trust in digital economies, particularly in the transport sector. Secondly, the study amplifies the genenralization power of the conceptual model as it can be added to particular sets of theories that have dominated extant literature in ridesharing. The study recommends that ridesharing firms should provide incentives and promotions to evince the benevolence aspect of trust. Further, a more tailored set of government policies for ridesharing firms should be developed to provide a comprehensive guideline and strategy for them to be distinct from traditional taxi systems.
The study is also limited in various ways. First, the study employed only the quantitative methodology to deduce the antecedent factor that impacts user trust in ridesharing. Also, the approach allowed the researcher to obtain in-depth knowledge into the issue under study and it was largely influenced by the understanding of the researcher. There is a need for future research to focus on antecedent factors that affect user trust from multi-user perspective and over a long period of time. Lastly, because the research was conducted in a University environment, it portrays that the study is skewed towards young, educated and working-class people. It would be insightful for future research to delve other groups of people to know if the results will differ.
