The Driverless Public Bus Transport Ridership In Malaysia: An Explorative Study

Technology acceptance model (TAM)

There have been a few types of research that exists on the mechanisms which can increase the intention of consumers to use driverless public bus transport. In order to investigate the ridership of driverless public bus transport, a priori acceptability of technology will be addressed to evaluate the technology itself, which is known as the technology acceptance model (TAM). TAM is an information system theory that simulates the intention of users to accept and use the technology. According to Davis and Venkatesh (1996), TAM is widely used by researchers to understand and explain the acceptance of the user towards the technologies. In this study, TAM believes that the impact of external variables (safety, environment, availability and awareness) on user behaviour is determined by perceived usefulness and perceived ease of use. Also, many empirical studies have shown that TAM is a robust and straightforward technology acceptance behaviour model for a variety of information systems (Davis et al., 1989; Davis & Venkatesh, 1996). According to TAM, perceived ease of use is also affect perceived usefulness, due to the easier it is to use it, the more useful the system is (Venkatesh & Davis, 2000). Besides, according to Choi and Ji (2015), the belief and attitudes of an individual will influence their intention to use or accept that technology. It also agreed by few studies which stated that attitudes and prior acceptability are correlated as the intention of using the technology can be predicted to some extent by user’s attitude and prior acceptability (Parasuraman et al., 1992; Payre et al., 2014).

Ridership

Several studies have been developed to determine the success factors that contribute to increasing increase in transit ridership. For example, Haire and Machemehl (2010) has pointed out the impacts of fuel prices on ridership. The introduction of new technology such as autonomous driving technology will play an essential role in increasing ridership for public transport system without decreasing the fare revenue. Besides, technology not only will allow transit companies to improve their operation at a reasonable cost and effort but also assists them in the daunting and challenging task such as reintroducing and repromotion public transportation to masses when they embrace the technology (Liwag & Drummond, 2011). Public transportation is more useful to transport the masses than small driverless vehicles such as a self-driving car, and thus public transportation will be transformed with the advent of autonomous driving technology. Also, public bus transportation is the most flexible compared to another transport mode such as rail, subway or tram as they do not travel strictly on a fixed route.

Safety

Safety can be defined as how a public transport service safe from traffic accidents and their safety that passengers feel when they are travelling (Redmana et al., 2013). According to Redmana et al. (2013), a study on public transport ridership showed a 5% increase over five years due to the improvements of comfortability such as safety and cleanliness. The study revealed that satisfaction increased which 5% of 2400 passengers satisfied with the improvement in service quality, especially safety. There were 80% of respondents stated that they would consider using driverless public bus transport because they believed that driverless vehicle is safer than a human-operated vehicle. However, there were also 57% of respondents choose not to use driverless public bus transport as they think the driverless vehicle is less safe than a human-driven vehicle. Therefore, safety is considered as one of the essential factors that will influence the driverless public bus transport ridership (Piao et al., 2016). Moreover, a study on the factors influences the selection of transport mode among older adolescents resulted in three main categories, which are including personal factor, social factor and physical environment factor. Safety as one of the concerned factor as it will not influence the choice of transport mode. The study focuses on older adolescents, shown that safety was not a very important factor for choosing transport mode for travelling short distances. This is because of the transport users reported that the riders more focuses on oneself carefulness instead of the safety of the vehicle.

Environmental Impact

According to Beirao and Cabral (2007), the study indicated that the environmental impact did not be the essential factor to be considered by the respondents when they are choosing the transport mode. Some supporting researches explained about although the rise of awareness and concerns on negative environmental impact among the car users, but the users’ behaviour would not change significantly. However, part of the car users will view the car pollution as motivation, and this may eventually make them switch from private car to public transport. Some of the car users said that busses are also responsible for pollution. Although public bus transit is not as environmentally friendly as rail, it still can be used to reduce pollution emission (Liwag & Drummond, 2011). Therefore, this study also developed to investigate the relationship between the user’s concern on environmental impact and the ridership of driverless public bus transport. It is vital to promote the public bus ridership in terms of emission reduction and efficiency compared to rail because the emission from private vehicles will be reduced and increase the occupancy rates of the bus. Thus, driverless public bus transport that studied in this research will be sustainable transportation that able to reduce the emission efficiently and should be promoted to reduce the dependency of private vehicles.

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Analysis

Inferential analyses had been used to address the research questions and to determine the significant relation between perceived ease of use (PEOU); environmental impact (EI) and safety (SAFE) with driverless public bus transport ridership (DR) (see Figure 02 ). Besides, the reliability test has been used in this study to know the reliability of the variables. Cronbach’s Alpha shown the value of 0.909, which is higher than 0.7, represented that all six variables are reliable and valid for further data analysis in this study.

Correlation Analysis

Correlation analysis is used to investigate the strength of the relationship between independence variables and dependence variables as tabulated in Table 01 .

In this study, the research set out to determine the relationship between perceived ease of use (PEOU), safety (SAFE), environmental impact (EI) and driverless public bus transport ridership (DR). Finding from correlation analysis shows that PEOU and SAFE are not significant at 0.01 level with r=-0.016, p <0.05 and r = 0.030, p < 0.05 respectively. Furthermore, findings of correlation analysis show EI is correlated with DR (r = 0.357, p < 0.05), which means EI is weak correlated with DR. The correlation analysis shows the existence of a significant relationship between EI and DR while PEOU and SAFE have no significant relationship with DR.

Multiple Regressions

Based on the Model Summary in Table 02 , R² is 0.352, which means that 35.20% of the variance in the driverless public bus transport ridership is explained by perceived ease of use, safety and environmental impact.

According to Table 03 for ANOVA analysis, the regression model is statistically significant (R² = 0.352, F (6,393) = 35.510, p < 0.05). When the p-value is less than 0.05, which means there is a significant difference.

Results show in Coefficient Table (can refer Table 04 ), suggest that there is a relationship between environmental impact and driverless public bus transport (β = 0.156, p < 0.05), which the environmental impact increased by 1 unit, there will be 0.156 increase in the driverless public bus transport ridership, and we confirmed that this result is consistent to the previous study (Gefen et al., 2000).

Furthermore, the result also shows that there is a relationship between perceived ease of use and driverless public bus transport (β = -0.120, p < 0.05). However, it is a negative relationship, which indicates that the perceived ease of use increased by 1 unit, there will be 0.120 decreases in the driverless public bus transport ridership. This result agreed by Nordhoff et al. (2018), indicated that low rating was obtained for thinking that driverless vehicles would be more comfortable to use than current transport. Research has shown that perceived usefulness (PU) affects the intended adoption of IT but has mostly failed to do so regarding the perceived ease of use (PEOU) (Gefen et al., 2000). Also, the results show that safety to driverless public bus transport ridership is not significant (β = 0.094, p < 0.05). This result is further supported by past study (Simons, et al., 2013). Simons et al. (2013) point out that the public will not concern on safety issue when they are using the public bus transport for their daily routine. Meanwhile there is no significant relationship between safety (SAFE) and driverless public bus transport ridership (DR).