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.
CHAPTER ONE INTRODUCTION
Research Background
The Sharing Economy (SE) is a business model where individuals share unused resources among them via peer to peer mediated services (Cohen & Kietzmann, 2014; Jarvenpaa & Teigland, 2017). SE has many names and some of the popular ones include collaborative- consumption, creative economy, market-mediated consumption, access-based consumption to name but a few. Casually, SE may be described as a scenario where consumers gain access to goods and services and pay for the experience, projecting that no ownership is transferred in these transactions (Pazaitis, De Filippi, & Kostakis, 2016; Rey, Aiello, Rey, & Lerman, 2017). Belk (2014) comprehensively explains it as a phenomenon where people coordinate “the acquisition and distribution of a resource for a fee or other compensation.”
In academia, SE is generally categorised into three (3) sectors namely; Peer-to-Peer economy, On-Demand Economy and Gig Economy. It is worth knowing that, SE is a profitable area as the sectors within SE are expected to grow revenue to over €100 billion of annual transactions by 2025, with no economy falling short of this milestone (Frenken & Schor, 2017; Jarvenpaa & Teigland, 2017; Jahromi, & Kizildag, 2018). From the estimates given, it shows that sharing firms profit hugely. For instance, Airbnb, the pioneer in travel accommodation, is believed to be worth $10 billion, more than well-known hotel chains such as Kempinski, Marriot and Hyatt. Additionally, Uber alone is estimated to be worth more than Facebook at about $51 billion dollars (Chen, 2016; Zervas, Proserpio, & Byers, 2015).
Digital firms operating in the rideshare or peer-to-peer transportation sector have experienced outstanding breakthroughs. By developing scalable platforms to act as matchmakers, such
companies create global networks where individuals distribute and share accessible resources to enable transportation. In view of this, it can be deduced that digital firms in digital mediated sharing are ‘eating the fruits of their labour’ because they are making huge profits. Hence, an area clearly seeking the attention of research (Berger, Chen, & Frey, 2017; Brazil & Kirk, 2016; Mittendorf, 2016).
As the study focuses on the transport sector in SE, it is worthy to highlight the two categories of ride services. The first is the traditional ride market, where no application or technology is necessarily needed to match-make or enable transportation. The second is computerised enabled transportation market, where a digital or virtual platform enables matchmaking between passengers and drivers. In view of the latter, the proliferation of digital platforms has enabled the industry to “share” and also to reach beyond the prospects of traditional transport markets. What is interesting about platform enabled transpotation is that, continues development of the relatively new business model is required due to technological advancements in contemporary times. Currently, Africa hosts nearly sixty (60) ride-sharing services across 21 countries in the last 3 years (Africa Renewal Online, 2017). Hence, it is clear that ridesharing firms driven by digitalization emerge as competitive alternative to traditional transport markets.
There are abundant opportunities and benefits in the booming market, however, there still exist many challenges. As cautioned by some pensive academics and multinational firms; many service providers of the shared economy are perceived to be callous and exploitative. When these Hi-Tech or/and innovative firms become too prosperous or dominant in their industries, they always eventually lose track of their target market’s needs and preference (Cohen- Almagor, 2018; Cohen & Kietzmann, 2014; Jordan, 2017). In recent times, some providers of
the shared and digital economy services are associated with data breaches, privacy concerns, despicable service delivery, violence and crime cases.
Customer trust, therefore, has become a global concern in all digital economies. This is because people are becoming aware of menaces associated with innovative platforms ranging from cases of data breaches, privacy concerns, violence and cybercrimes. For instances, in October 2017, personal information of 57 million drivers and customers were retrieved from Uber Technologies Inc. by hackers (Bloomberg, 2017). The firm also paid a sum of $100,000 to the attackers to keep the hack under wraps. Revelations like these promulgate academia to conclude that giant companies engaged in the sharing and digital economy, create unregulated and opaque ‘intelligence platforms’ and business brands that blindfold and expose customers to danger which in essence dampen the trust people have in firms. In view of the issues raised, there is the need to investigate the antecedents and outcome of trust in ridesharing services.
Research Problem
The Internet arguably remains the most revolutionary innovation in the 21st century; a medium that enables people to communicate, gather information and carry out business transactions devoid of physical barriers. Over the past decade, the internet technology has become a springboard for newer and more innovative business models like the SE. Hence, the scope of the digital market place keeps widening. In spite of the munificent benefits derived from SE, the issue that has earned a growing concern is the building of online trust and understanding its relationship with online consumers and their behavioural outcomes. The core reason for the growing concern regarding online trust with the absence of face-to-face interactions in online platforms which creates perceived risk and behavioural uncertainty, hence the distrust in these platforms (McKnight, Choudhury, & Kacmar, 2002; Mittendorf, 2017). The field of SE is
becoming popular in academia due to two principal facts: first, SE is rapidly coming of age with high revenue growth rates and second, the buoyant economy still harbours basic challenges that affect the economy as a whole.
Trust is the “currency” of sharing economy (Botsman, 2012). Some academic researchers have attempted to understand the phenomenon as to why trust is the most cited factor within most sectors in the SE especially with ridesharing services. For instance, Jarvenpaa and Teigland (2017) organized their first mini-track panel discussion and the focused on trusted systems in digital environments, identity and trust which was aimed at understanding to what degree trust matters, when trust matters, what nature trust takes, and what the reprecussions are. This panel discussion exhausted most of the questions on trust. However, the research took clustered users into a single perspective without intricately discussing what triggers comsumer trust.
Further, extant literature on trust and sharing economy have been done mainly from the perspective of e-commerce (Bartikowski & Merunka, 2015; C. Liu, Lin, & Deng, 2015; Oliveira, Alhinho, Rita, & Dhillon, 2017a), general online transaction (Filieri et al., 2015; Moriuch & Takahashi, 2016; Azam, 2015), and general sharing economy (Mittendorf, 2017; Möhlmann, 2016; Jarvenpaa & Teigland, 2017; Trang et al., 2017; Amirkiaee & Evangelopoulos, 2018; Simmons, 2018; Lee et al., 2018) with no specific focus on trust in the transportation sector within sharing economy. For example, Filieri et al. (2015) examined the antecedents and consequences of online trust and found that information quality predicts source credibility, customer satisfaction, and website quality. The authors also found that consumers’ intentions could be influenced by the trust they have in media websites designed to suit them.
Similarly, Oliveira et al. (2017) in their study on consumer trust dimensions in e-commerce assert that consumers with high levels of trust possess higher intentions to engage online activities. While these two studies provide insight about trust, they tend not to focus on trust in ridesharing services. Additionally, these studies failed to examine if trust can play a mediating role between antecedents elements and outcomes. Evidently, studies on sharing economy and trust are few, the few do not pay attention to the antecedents and outcome of trust. For example, Mittendorf (2017) conductied a to investigate the implications of trust from the perspective of a potential customers. The author employed Gefen’s (2000) model in analysing the influence of trust on customers’ intentions to inquire about drivers and to request a ride. Although this study considered two antecedents of trust and two outcomes, it examined trust from a potential consumer perspective and it also failed to explore the role of trust as mediator between the antecedents and outcomes. It would have revealed how potential customers react to the trust, whether they could request a ride and inquire about a driver without necessarily trusting the platform or not.
Lastly, extant literature in developing economies have not gulped their fair share of research relating to trust and the ridesharing sector of the sharing economy. For instance, Simmons (2018) conducted a study to understand the disruptive influence of ridesharing on traditional taxi services in Ghana. The study pointed out four main affordances which enable ridesharing applications to be a disruption to the traditional taxi industry in a developing economy. However, the qualitative study neither concentrated on the subject of trust nor solicit interest from specific actors in ridesharing such as consumers or drivers. Lastly, study did not involve any form of statistics (numbers) to quantify the extent of disruption that ridesharing poses. There is, therefore, the need for studies that investigate the relationship between the factors that
lead to consumer trust in ridesharing services and also understand how trust mediates the relationship between the antecedent factors and the outcome of trust.
Research Purpose
The purpose of this study is to investigate antecedent factors and mediating role of consumer trust in ridesharing services.
Research Objectives
The research seeks to specifically meet the following objectives:
- To assess the antecedents of consumer trust in ridesharing services.
- To determine the mediating role of trust between antecedent factors and word-of- mouth in ridesharing services.
Research Questions
The research seeks to specifically meet the following objectives:
- What are the antecedents of consumer trust in ridesharing services?
- What is the mediating role of trust between its antecedent factors and word of mouth in ridesharing services?
