E-hailing Utilisation Analysis in Kota Kinabalu City Centre
Azwa Safiqah Darawati1*, Mohd Azizul Ladin1, Rusdi Rusli2, Muhamad Razuhanafi Mat Yazid3, Almando Abbil4, Hussin A. M Yahia5
1 Faculty of Civil Engineering, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia
2 College of Engineering, Universiti Teknologi Mara, Shah Alam, Malaysia
3 Fakulti Kejuruteraan Alam dan Bina, Universiti Kebangsaan Malaysia, Selangor, Malaysia
4 Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
5 Civil Engineering Department, Middle East College Knowledge Oasis, Al Rusayl, Sultanate of Oman
*Corresponding Author: [email protected]
Accepted: 15 December 2022 | Published: 31 December 2022
DOI:https://doi.org/10.55057/ijbtm.2022.4.4.5
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Abstract: The prevalence of smartphones and the IoT in today's modern world is only expected to grow. Since its inception, the use of e-hailing apps—which allow users to order a car, taxi, limo, or other modes of transportation via a mobile device—has skyrocketed. Due in large part to the efforts of transportation network businesses, e-hailing services have become a significant driver of economic growth. Many people choose e-hailing services because they provide more privacy and convenience than public transportation. E-hailing services in Kota Kinabalu, Sabah, are analyzed in this study to determine the factors that affect how users see these services. This study's objective was to understand the e-hailing service in Kota Kinabalu, Sabah. The Stated Preference Survey (SPS) method was used in this study. In order to gather the necessary data, an online questionnaire was created and sent out to 300 participants. The data were analyzed using descriptive statistics and Spearman's Correlation. Price value and perceived safety when utilizing e-hailing services were shown to have significant correlations of rs=.161 (p≤0.05) and rs =.118 (p≤0.05), respectively. As a result, e-hailing businesses should advertise the affordability and security of their services.
Keywords: e-hailing, transportation, smartphones, customers' perception
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1. Introduction
Located in eastern Malaysia, across the South China Sea from the rest of the country, is Kota Kinabalu, the capital of Sabah. The city's population is 553,900 (Jeffree et al., 2020; Lin et al., 2019). Since most of the city's inhabitants live there for economic reasons, Kota Kinabalu is a great place to find gainful employment (Noor et al., 2014). Hence, during the week, the neighbourhood's streets became clogged with cars going in and out. Morning and evening rush hours saw a spike in gridlock as residents travelled to and from work and home. Congestion and its negative effects on people's daily lives and the environment are only two of the many negative outcomes of the fast rise in the usage of private automobiles (Ladin et al., 2015).
Therefore, studies suggested that an efficient public transit network may help reduce road congestion (Bohari et al., 2014; Jais & Marzuki, 2018).
Taxi services, e-hailing services, local buses, long-distance buses, and trains are available in Kota Kinabalu (Besar et al., 2020). While Kota Kinabalu's public transportation options are
many, most visitors were not happy with the level of service they received. Inadequate service infrastructure also increases travel time and makes it more difficult to reach the service site (Kamaruddin et al., 2017; Sukri et al., 2017). Customers conclude that driving their cars is more pleasurable than taking the bus or train. E-hailing companies have emerged as a viable alternative to public transportation thanks to their ability to supply passengers with a private car service. E-hailing refers to ordering a car, taxi, limousine, or other means of transportation via a mobile device. Using this system, customers can find where approved cars are parked, and drivers can pinpoint the precise position of passengers who are ready to go (Fassbender, 2016).
For several reasons, Malaysia's e-hailing sector is thriving. Now that more people than ever have access to the Internet, people living in metropolitan areas are better able to adapt to changing circumstances by making use of digital tools. In Malaysia, the e-hailing sector has exploded due to the unparalleled level of service provided by a single e-hailing provider (Su et al., 2021). Other than that, more people are using the service because the rates are affordable (Nor et al., 2016). Passengers and drivers were safe because of the convenience of cashless purchases (Ubaidillah et al., 2019). Given the preceding, it is crucial for the e-hailing sector in Malaysia to understand how customers in Kota Kinabalu, Sabah, feel about e-hailing services to boost their service and expand their company. This study analyses the elements influencing consumers' opinions of e-hailing services in Kota Kinabalu, Sabah, Malaysia.
2. Literature Review
The proliferation of private automobiles has emerged as a problem because of the ease with which they may be operated (Ambak et al., 2016). Previous studies have shown that the unreliability of public transportation is the primary reason why the vast majority of passengers choose to rent a car instead (Van Truong & Shimizu, 2017). According to Ismail et al. (2012), inflexibility, a lack of direct access, lengthier travel times, and a lack of safety when using public transportation are some issues that deter consumers from making that choice. One of the main issues in Kota Kinabalu, as noted by Noor et al. (2014), is the inefficiency of the public transportation system. Congestion on city streets may be alleviated partly by improving access to public transit (Ladin et al., 2014). Therefore, the introduction of e-hailing services in Malaysia could not have come at a better moment. In Kota Kinabalu, e-hailing services like GrabCar make getting around easier and faster.
Thus, the e-hailing services' arrival in Malaysia could not have come at a better time. E-hailing, sometimes known as "ridesharing," is a relatively new kind of public transportation that offers passengers the use of privately owned vehicles. As a result, it satisfies the needs of Malaysians who prefer their cars, wants shorter commutes, and value simplicity of use. Customers in Kota Kinabalu, Sabah, benefit from the availability of e-hailing services like GrabCar since it facilitates faster, more convenient travel between locations (Lin et al., 2019). Therefore, it is essential to understand the level of client satisfaction with the e-hailing service in Kota Kinabalu and for the industry to identify the key elements of its service that may promote development and universal adoption.
Perception, as defined by Warokka et al. (2012), is the process by which people assign meaning to their surroundings via the integration and interpretation of sensory data. Thus, it has been shown that security and safety features, rates, payment methods, and convenience of use all play a role in customers' happiness with e-hailing services.
Customer's peace of mind is paramount while using an e-hailing service. Customers have been worried about the security of ridesharing services for quite some time, as reported by Teo et al.
(2018). Because of this, measures have been put in place to guarantee the customers' security, such as a tracking system that broadcasts the names, licence numbers, and drivers' current locations (Onyango, 2016).
Users' ideas of what constitutes a fair charge play a big role in evaluating e-hailing. In comparison to using a taxi, e-hailing services are more cost-effective (Gan et al., 2021). The e- hailing service frequently provides discount codes that further cut costs (Chen & Nazar, 2021).
People are more likely to have a favourable impression of the e-hailing industry if fares are considered fair and affordable.
E-apps, or app-based e-apps, are helpful because they enable customers to quickly book a car at their preferred rate, with their preferred driver, and in their preferred vehicle. Additionally, the flexibility of cash and credit payments has allowed for various payment alternatives that meet the requirements of different clients (Chen & Nazar, 2021). The convenience of e-hailing applications, where a ride can be requested with the tap of a smartphone, has also increased its use (Yusoff & Daud, 2015).
This study aims to investigate how people in Kota Kinabalu perceive and adapt to e-hailing services. Initially, the variables that influence user impressions are discovered and validated.
These include security features, prices, and usability. This study's conceptual framework is represented in Figure 1 below.
Figure 1: Conceptual Framework
From the conceptual framework, the following hypotheses were formulated:
H1: Security features have no significant relationship with customers' perception of e-hailing services
H2: Fare has no significant relationship with customers' perceptions of e-hailing services.
H3: Convenience has no significant relationship with customers' perceptions of e-hailing services.
3. Methodology
The surveys are sent via Google forms, and the research is conducted in Kota Kinabalu, Malaysia. Kota Kinabalu has a population of about 500,000, and 300 people were polled to get to 95% confidence. The questionnaire's design was informed by a review of the relevant literature, and it has questions on cost, accessibility, and safety. Then, the researcher conducted the questionnaire survey to get the information needed to test the study model. These
characteristics may largely describe customers' impressions and degrees of satisfaction with e- hailing services.
A software called Statistical Packages for the Social Sciences (SPSS) is used to analyze the information gathered from the questionnaires. The process of turning raw data into a format used to understand data analysis is known as data transformation. Data transformation refers to converting raw data into a format suitable for analysis. This way, we may investigate any potentially important connection between independent and dependent variables.
Data will be evaluated using descriptive statistics and Spearman's Correlation. Zikmund et al.
(2013) state that the replies to a survey may be summarised using descriptive analysis.
Reorganizing, organizing, and modifying raw data into descriptive information is all part of the analytical process.
An ordinal or higher scale may be used with Spearman's rank correlation coefficient since it is a non-parametric measure of the strength of the relationship between two categorical variables (Sharma & Suryawanshi, 2016). Spearman's rank order coefficients are explained in Table 1.
The p-value is used to determine whether or not the results of a hypothesis test are statistically significant. Significant evidence exists to reject the null hypothesis in favour of the alternative when the p-value is less than 0.05. (H1). If the p-value is greater than 0.05, however, the alternative hypothesis (Ha) (H1) is rejected, and the null hypothesis (H0) is accepted. Positive ('+') and negative ('-') signs indicate whether the association is positive or negative (Chen &
Nazar, 2021).
Table 1: Clarification of Spearman's Rank Order Correlation Coefficient
Spearman, ρ Strength of Association
≥ ±0.7 Very strong
±0.40 – ±0.69 Strong
±0.30 – ±0.39 Moderate
±0.20 – ±0.29 Weak
±0.01 – ±0.19 No or negligible
Source: (Leclezio et al., 2015)
4. Result and Discussion
4.1 Demographic Analysis
Women between the ages of 18 and 23 and males between the ages of 18 and 23 who were either students, working adults, or unemployed made up the majority of the samples in this research, which was conducted in Kota Kinabalu, Sabah. Demographic information about the respondents is summarized in Table 2.
Table 2: Summary of Statistics on Respondents' Information
Demographic Description Characteristics of Respondents (%)
Gender Female 50.7
Male 49.3
Age Less than 18 years old 17.0
18 – 23 years old 30.0
24 – 29 years old 19.7
30 – 39 years old 12.0
40 – 50 years old 14.0
More than 50 years old 7.3
Occupation Unemployed 5.3
Student 50.3
Government Sector 18.0
Private Sector 19.3
Self-employed 7.0
Table 2 provides a statistical breakdown showing that females made up 50.7% of respondents and males 49.3%. 30 % of the sample was comprised of people aged 18 to 23. As a result, respondents older than 30 made up 19.7% of the total, followed by 17.0% of those younger than 18. Generation X accounts for 7.3% of the respondents, while Millennials comprise 26.0%. Next, in this research, the researchers also consider utilizing private vehicles and possessing a valid driver's license among users, as these are significant in determining the characteristics that influence respondents' use of e-hailing services among KK residents. Table 3 provides an overview of respondents' private car ownership and license status.
Table 3: Summary of Owning a Private Vehicle and Driving License
Own a driving license
Yes No Total
Own a private vehicle Yes 51.7% 2.3% 54.0%
No 16.0% 30.0% 46.0%
Table 3 shows that of the respondents who provided information about their driver's license and private vehicle ownership, 51.7% had both. However, 16% of respondents have a licence but do not possess a vehicle. Only 2.3% of respondents do not have a valid driving licence, which is likely since the respondent inherited a private automobile from his or her family. That is why 30% of those polled had neither a driver's licence nor access to a car due to financial constraints.
Table 4: Summary of Utilization of E-hailing among KK Residents
Demographics Description Frequency of Usage (per week) (%) Daily Once per
week
2 – 5 times Less than 10 Never
Gender Female 2.0 17.1 15.1 25.0 40.8
Male 0.0 22.3 23.0 12.8 41.9
Table 4 provides a summary of weekly E-hailing use among respondents. The data table shows that just 2.0% of female respondents reported everyday usage, whereas no male respondents
did. While for "Once per week" usage, among the respondents, 17.1% were women, and 22.3%
were men. In comparison, 23.0% of male respondents have a frequency of usage between 2 to 5 times weekly. Less than 10 times per week was reported by 25% of women. The table also reported that 41.9% of males do not use e-hailing, and 40.8% of female respondents do not use e-hailing services. Based on these data, it can be concluded that most of the respondents do not use e-hailing services daily, so they opt to use their own private vehicle or any other type of transportation.\
4.2 Spearman's Correlation Analysis
Using Spearman's Correlation analysis, researchers could assess the degree and direction of the association between the variables. In conjunction, the R-value is used to determine the significance of the variables. Table 5 displays the correlation coefficient between security features, fare, and convenience variables.
Table 5: Spearman's Correlation Coefficient Analysis
Variables Fare (IV1)
Safety (IV2)
Convenience (IV3)
Customer's Perception (Gender) (DV)
IV1 1.000
IV2 .243** 1.000
IV3 .286** .438** 1.000
DV .161** .118** .051 1.000
N = 300, ** Correlation is significant at the 0.01 level (2-tailed)
Table 6: Significant value of DV vs IV
Variables Fare (IV1)
Safety (IV2)
Convenience (IV3)
Customer's Perception (Gender) (DV)
IV1 .000
IV2 .000
IV3 .000
DV .005 .041 .382 .000
R-value of 0.1 or above, the result indicates a substantial positive correlation between the dependent variable and the independent factors. R-value of 0.161, the price has a positive significant but weak correlation with customer perception. The following variable, safety, has a positive significant but weak or negligible relationship with the dependent variable, with an R-value of 0.118. Finally, with an R-value of 0.051, there is no significant relationship between the dependent variable and the ease of utilizing an e-hailing system, indicating that the variables have no or negligible relationship.
Based on table 6, the significant price level is .005, which is lower than or equal to 0.05 (p ≤ 0.05). As a result, it is possible to conclude that there is a significant relationship between pricing and consumer perception. The safety factors are essential to the customer's impression with a p-value of .041, p ≤ 0.05. Finally, with a p-value of .382, indicating p ≥ 0.05, there is no significant association between convenience and consumer impression.
Based on the analysis conducted, the hypothesis tested for the 3 variables: security features, fare and convenience.
H1: Security features have no significant relationship with customers' perception of e-hailing services.
Based on Table 6, with p-value = .041 ≤ .05, thus there is a significant relationship between security features and customers' perception of e-hailing services. Therefore, H1 is rejected.
H2: Fare has no significant relationship with customers' perceptions of e-hailing services.
Based on Table 6, with p-value = .005 ≤ .05, thus there is a significant relationship between fare and customers' perception of e-hailing services. Therefore, H2 is rejected.
H3: Convenience has no significant relationship with customers' perceptions of e-hailing services.
Based on Table 6, with p-value = .382 ≥ .05, thus there is no significant relationship between convenience and customers' perception of e-hailing services. Therefore, H3 is accepted.
5. Conclusion
This research examines how customers in Kota Kinabalu, Sabah, perceive e-hailing services.
According to the findings of the descriptive and inferential analyses, there is a significant opportunity for businesses to provide e-hailing services in Kota Kinabalu since 51.7% of respondents continue to depend primarily on their private automobiles. The management of different e-hailing businesses should market their services based on the industry's strengths, including safety features, affordable fares, and convenience. This will help draw more customers to employ e-hailing services, which will attract more customers. Because of these factors, the number of clients using their services will dramatically increase. In addition, the firm that provides online taxi services has to participate in effective marketing to entice clients from various demographics and age groups. When the R-value is 0.1 or above, the correlation analysis indicates that consumers are much more likely to use e-hailing services if safety and price value are considered key motivating factors. According to these figures, most customers select e-hailing because of the safety aspects supplied by these e-hailing services and the inexpensive pricing offered by these e-hailing services. Additionally, because of the costs of petrol, parking fees, and maintenance that must be taken into consideration, clients may often save more money if they travel by using e-hailing services instead of driving their own cars.
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