SERVICE QUALITY AND BRAND REPUTATION AS ANTECEDENTS OF BRAND CHOICE: THE CASE OF RIDE-HAILING APPLICATIONS IN SOUTHEAST ASIA

Currently, internet-linked ride-sharing services are active in several Southeast Asian nations. This research aimed to investigate the impacts on consumer brand preference by examining the relationships between the variables of service quality, perceived value, and brand image. Cross-sectional data was used, and a quantitative technique strategy was taken. Customers of online ride-sharing service alliances in Southeast Asia were the subject of the unit analysis, which included 384 respondents from each of the following countries: Malaysia, Indonesia, Cambodia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. The representative offices of the ride-sharing businesses in the target nations were the distribution points for surveys used in the sampling method, which combined random sampling with purposive sampling. Path analysis was the method of data analysis employed. The results showed that perceptions of service quality, perceived value and brand reputation influenced brand choice simultaneously and significantly.


INTRODUCTION
A survey on congestion in nine large Asian cities, conducted by the Boston Consulting Group in 2017, involving around 9000 respondents, showed that citizens complained about too much wasted time due to traffic jams (84%), difficulty finding parking spaces (60%) and high parking fees (45%). Additionally, as many as 72% of respondents in Asia admit to being late or missing an important event due to traffic jams (Pradana & Wisnu, 2021). A ride-sharing service provider is one of several forms of partnership service providers introduced within the scope of a populist economy philosophy, also known as a sharing economy . This is a concept of equality between drivers and partners (a peer-to-peer driver-partner concept), in which the majority of drivers are vehicle owners who partner with transportation service providers (Gusfei & Pradana, 2022). Table 1 shows partnerships with online ride-hailing companies operating in Southeast Asia.
Consumers have accepted the concept of online taxi partnerships due to their safety, reliability, and affordability as an alternative to traditional transportation services. Furthermore, driving partnerships can potentially offer significantly more benefits for customers. Online transportation providers, such as ride-sharing apps, can help to solve traffic problems in Southeast Asia in a few ways. The first one is reducing the number of private vehicles on the road. With the convenience of ride-sharing services, people may opt to use them instead of driving their own vehicles (Natyari & Pradana, 2016), which can contribute to reducing traffic congestion. The second one is by utilizing technology to optimize routes. Ride-sharing apps use algorithms to match drivers with riders, which can help to optimize routes and reduce travel time. It can reduce the time spent in traffic and help ease congestion on busy roads (Susanto et al., 2022). The existence of these apps also encourages carpooling. Some ride-sharing services offer carpooling options, where multiple riders can share a ride to a common destination (Natyari & Pradana, 2016). This can further help reduce the number of vehicles on the road and reduce the overall cost of transportation for riders. Ridesharing apps also provide an alternative to public transportation.
In some areas, public transportation may not be reliable or convenient. Ride-sharing services can provide a more accessible and reliable alternative, which might encourage people to rely on public transportation less frequently (Rahmawaty et al., 2021).
While ride-sharing services can help reduce traffic congestion in certain areas, they may also contribute to increased traffic in other areas . There are also concerns about the impact of ride-sharing services on traditional taxi drivers' livelihoods and the riders' safety. Therefore, considering the potential benefits and drawbacks of ride-sharing services in the context of each specific location and community is imperative. Wardhana & Konadi (2015) state that the various benefits of online taxi services include tariffs, ease of ordering, cost savings, time savings, practicality, assurance, comfort, and security. Due to the availability of smartphone applications, social media, GPS navigation devices, and online services, customers who need a taxi can more easily connect with a driver by simply tapping a screen to choose a taxi all while considering various factors such as driver profile, ratings, reviews, GPS tracking, and order notifications.
The presence of application-based online taxi service partnerships has presented challenges for conventional taxi companies. In Indonesia, partnership ride services provided a rapid change in the transportation service business in the mid-2010s, where companies such as Uber, as well as well-known local brands such as Grabcar and GoCar services, implemented a guerrilla marketing strategy to attract consumers' attention with a variety of discounts (Djaswadi et al. al., 2017). Over the years, this dynamic development in the industry left the two biggest players --Grabcar and GoCar -on top, as of 2018.
These two companies have become partners with conventional taxi companies, such as Blue Bird and Express in providing a fast responsive taxi ordering system (Santoso & Wahyuni, 2018 (Gusfei & Pradana, 2022). A study conducted in the United States found that partnership driving services were essentially not available because only 8% of consumers were willing to use them for travel . The factors that were found to significantly influence consumer decisions to use online taxi partnership services are better vehicles, cheaper services, driving comfort, and trusted drivers (www.channelnewsasia.com, 2015).
Other factors that influence the choice to use online taxi service partnerships are lower rates, ease of ordering, cost savings, time savings, practicality, assurance, comfort, and security (Wardhana & Konadi, 2015). Meanwhile, Hasbi et al. (2022) found that price fixing, failure of major services, failure of contact with drivers, and ethical problems were also factors that affected online taxi partnerships (Elisa et al., 2022).
When it comes to public transportation, there is a stark difference between developed countries like the US, Singapore, Japan, and Germany and less developed countries like Indonesia and Cambodia. Developed countries have invested heavily in public transportation infrastructure, which is often modern, efficient, and well-maintained (Ullah et al., 2022). For example, cities like Tokyo and Singapore have extensive subway systems that cover large areas and run frequently. On the other hand, less developed countries often have limited infrastructure, and transportation can be slow and unreliable. In Indonesia, for example, many people rely on motorcycles or informal minivans (Mansoor et al., 2022). Public transportation in developed countries can be expensive, but it is generally more affordable than in less developed countries. For example, a subway ride in Tokyo might cost around 200-300 yen (about $2-3), while in Jakarta, Indonesia, a similar ride on the Transjakarta bus system costs about 3500 rupiah (about $0.25). In these less developed countries, however, many people may not be able to afford even these relatively low fares, especially if they have to travel long distances (Kartawinata et al., 2021).
In developed countries, public transportation is often designed to be accessible to people with disabilities and the elderly, with features like elevators, ramps, and reserved seating areas (Hasbi et al., 2021). Less developed countries may not have such accommodations, making it difficult for people with disabilities or mobility issues to use public transportation. Public transportation in developed countries is also generally considered to be safe and secure, with low rates of crime and accidents. In contrast, transportation in less developed countries may be more dangerous, with issues like overcrowding, poorly-maintained vehicles, and theft or harassment by other passengers .
Overall, the differences between public transportation in developed and less developed countries reflect broader disparities in wealth, infrastructure, and social welfare. While developed countries have invested in public transportation as a way to promote economic growth, reduce traffic congestion, and mitigate environmental problems, less developed countries often lack the resources to do so (Ullah et al., 2022). As a result, many people in these countries must rely on informal transportation options, which can be slow, expensive, and unsafe (Mansoor & Wijaksana, 2022).
Various literatures indicate that partnered online taxi transportation services are preferred due to the ease of using reliable mobile applications. These apps provide detailed information about the driver, including vehicle type and number and registration, the route taken, and the estimated time from departure to arrival time at the destination. Despite the increasing demand for partnership online taxi services, there are still limited studies on the factors that influence customers in choosing partnership online taxi services in Malaysia, Indonesia, Cambodia, Myanmar, Philippines, Singapore, Thailand, and Vietnam. Furthermore, the majority of studies regarding these services are still conceptual in real and ad-hoc conditions.
The obstacles that occur in the selection of these brands are services that are canceled by the driver, promotions that are not as promised, nonstandard vehicle conditions, long waiting processes, bad driver behavior, error applications, unpopular brands, and unilateral cancellations by the user. The tendency for customers to choose to use a well-known service brand (17%), determined by brand trustworthiness (24%) and their satisfaction with the service (15%) (Mansoor & Wijaksana, 2021). Trust in a brand is determined by the quality of service they receive (32%), value received (37%), and brand reputation (41%). Meanwhile, customer satisfaction is determined by the quality of service they receive (42%), the value received (34%) and brand reputation (34%) .
The research on customer loyalty and brand choice in the context of ride-sharing apps is an active area of study, but there are still several gaps that need to be addressed. A potential research gap in this area is exploring the impact of customer loyalty on brand choice. Although customer loyalty is often considered an important factor in determining brand choice, the relationship between these two constructs in the context of ride-sharing apps is not well understood. This study, as well as future research, could explore how customer loyalty affects brand choice and how ride-sharing companies can leverage loyalty to retain customers. By utilizing the unified theory of acceptance and use of technology (UTAUT), combined with the technology acceptance model (TAM) as guiding theories, followed by perceived service quality, perceived value, brand reputation trust, and choice and customer satisfaction as middle theories, this research aims to explore research gaps that have not been discussed within the topic of ride-sharing transportation in Asia.

LITERATURE REVIEW
UTAUT and TAM as Basic Theories UTAUT (Unified Theory of Acceptance and Use of Technology) is a theory in the field of technology adoption that aims to explain and predict the acceptance and use of technology. It was first proposed by Venkatesh et al. in 2003 and has been widely used and tested in various research studies . The principle of UTAUT suggests that four key factors influence the adoption and use of technology: • Performance expectancy -the degree to which individuals believe that using technology will help them to improve their job performance.
• Effort expectancy -the degree to which individuals believe that using technology will be easy and require little effort.
• Social influence -the degree to which individuals feel social pressure to adopt and use technology.
• Facilitating conditions -the degree to which individuals believe that they have the resources and support necessary to use technology.
According to UTAUT, these four factors can explain up to 70% of the variance in technology adoption and use. Additionally, the theory suggests that gender, age, experience, and voluntariness of use can moderate the relationship between these factors and technology adoption and use (Rubiyanti et al., 2022).
On the other hand, TAM (Technology Acceptance Model) is a theoretical framework used to explain and predict how people accept and use new technologies. The model was first introduced by Fred Davis in 1989 and has since been widely used in the field of information systems and technology management (Nafisa et al., 2022). The TAM theory suggests that people's attitudes towards using technology are influenced by two main factors: perceived usefulness and perceived ease of use (Mansoor et al., 2022). Perceived usefulness refers to the extent to which a technology is perceived to improve one's job performance or enhance the overall quality of life (Rubiyanti et al., 2022). Perceived ease of use refers to the extent to which a technology is perceived to be easy to learn and use. According to the TAM model, these two factors directly affect individuals' attitudes towards using a new technology, which in turn influences their intention to use it. Ultimately, their actual usage of the technology is determined by their intention to use it. Overall, the TAM theory has been widely used in research to understand and predict technology adoption and use, and has been applied to various technologies and contexts, such as e-commerce, mobile applications, and healthcare technologies (Nafisa et al., 2022).
For this research, service quality is used as a variable, as it can be defined as the assessment of the actual service performed. Customer satisfaction can be defined as the degree to which customers are happy with the use of products that are provided to them by the companies (Mansoor et al., 2022). The dimensions and indicators of perceived service quality and customer satisfaction were adopted from Mansoor et al. (2022) and Chao (2015).
Perceived service quality, perceived value, and brand reputation as predictor variables Perceived service quality can be defined as the assessment of the actual service performed. Customer satisfaction can be defined as the degree to which customers are happy with the use of products that are provided to them by the companies (Mansoor et al., 2022). The dimensions and indicators of perceived service quality and customer satisfaction were adopted from Mansoor et al. (2022) (2016), Rasheed (2014), Rizwan (214), and Tabaku (2013). These dimensions consist of reliability, security, response, tangibility, and empathy. Perceived value can be defined as the assessment of the difference in perception between actual service performed and customers' expectations (Rasheed & Abadi, 2014). The perceived value dimensions and indicators are adopted from Ladhari (2007), Ngo (2018), and Nuviala (2012), consisting of three dimensions, namely employee value, image value, and services value. Brand reputation alludes to the customer's view of service quality related to the brand name (Sharma, 2018).
The definition of brand reputation is adopted from Ngo (2018) and Wang (2010), consisting of three dimensions -trustworthiness, reputability, and making honest claims. Brand trust is a brand's promise to their customers to fulfill their expectations. The dimensions and indicators of brand trust were adopted from Mansoor et al. (2022), and Zhang et al. (2013), consisting of reliability and intentionality. The choice of brand name for a product can alter the consumers' judgment about the product and their purchase decision-making process (Mansoor et al., 2022). The dimensions and indicators of brand choice are adopted from Laforet & Chen (2012) and Mahmud (2017) and includes ten dimensions, namely service, price, place, promotion, physical evidence, process, people, mobile application, brand name, and consumer behavior.
Brand reputation, customer satisfaction, and brand choice as outcome variables Brand reputation, customer satisfaction, and brand choice are all important outcome variables in the field of marketing and branding. Brand reputation refers to the overall perception of a brand in the marketplace. It encompasses a variety of factors, such as the quality of the products or services offered, the level of customer service provided, the brand's values and messaging, and the brand's overall image. A positive brand reputation can lead to increased customer loyalty, higher sales, and improved financial performance, while a negative brand reputation can have the opposite effect. The relationship between perceived service quality and perceived value and brand reputation is stated by Husda et al (2017), Mutle & Shonhe (2017), and Ngo (2018). The relationship between perceived sevice quality, perceived value, brand reputation, and brand trust has been previously explained by Naggar & Bendary (2017) and Sharma & Matur (2018).
Customer satisfaction refers to how happy and content customers are with a brand's products or services. It is typically measured through surveys and feedback mechanisms, and can have a significant impact on a brand's success. High levels of customer satisfaction can lead to increased customer loyalty, positive word-ofmouth marketing, and improved financial performance.
The relationship between perceived service quality, perceived value, brand reputation, and customer satisfaction has been stated by Maghzi et al (2011) Brand choice refers to the decision-making process that consumers go through when selecting a particular brand over others. It is influenced by a variety of factors, such as brand awareness, brand reputation, perceived quality, and pricing. Brand choice can have a significant impact on a brand's success, as consumers who choose a particular brand are more likely to become repeat customers and advocates for that brand. Overall, brand reputation, customer satisfaction, and brand choice are all important outcome variables in the world of marketing and branding. Brands that perform well in these areas are more likely to succeed and achieve their business objectives. The relationship between perceived service quality and brand choice has been stated by Kumar (2014) and Erdem & Swait (2004). The relationship between brand trust and brand choice has been defined by Ha (2004), Laforet & Chen (2012), and Mahmud (2017). The relationship between customer satisfaction and brand choice was confirmed by Abbasi et al. (2021). The framework in this study can be described in Figure 1.

METHODOLOGY
A quantitative method approach and crosssectional data were used for this study. According to Fakhri et al. (2020), the use of crosssectional data helps researchers reveal possible relationships or collect primary data to support research. The research object here is the online ride-sharing taxi service company Grabcar operating in 8 Southeast Asian countries, namely Malaysia, Indonesia, Cambodia, Myanmar, Philippines, Singapore, Thailand, and Vietnam . The selection of Grabcar as the largest online taxi service provider in Southeast Asia is based on the similarity of the company's operations in 8 Southeast Asian countries, and the study period was two years .
The population in this study were customers of Grabcar's online taxi service partnerships in Malaysia, Indonesia, Cambodia, Myanmar, Philippines, Singapore, Thailand, and Vietnam, the number of which is over 1,000,000 customers and cannot be known with certainty, and were developed based on behavioral models of attitudes and perceptions. According to Ary, et al. (1996), a comprehensive study of all individuals is not required to understand the phenomenon with various considerations. Therefore, this study uses a sampling method (Castillo, 2009). Sulistijono et al. (2020) states that for a population above 1,000,000 customers, the minimum sample size is 384 respondents, which is sufficient for hypothesis testing. Therefore, 1,536 respondents were assigned a sample size consisting of 384 respondents in each country. Data was collected using online questionnaires.
Respondents in this study were based on: gender (50% women and 50% men); age (25% under 25 years, 50% 25 to 50 years, 25% over 50 years); work (40% students, 40% employees, and 20% other). The method of data collection was a survey method, acquired through distributing questionnaires with a Likert scale. The questionnaire was adapted from Chao (2015), Dahiyat et al. (2011), Mahmud (2017, Mutle & Shonhe (2017), Oh (2016), Prameka (2016), andNgo (2018). Then, the validity and reliability of the questionnaire were tested. Path analysis was used as the data analysis technique and was chosen because each independent variable has a relationship (multicorrelation). According to Moeliono et al. (2020), the path analysis model is used to analyze the pattern of relationships between variables in order to determine the effect of variable X on variable Z and its effect on variable Y. The brand/service offers value based on previous experiences; brand/service is value for money compared with that of major competitors; brand/service always delivers superior service performance; consistent quality; is well made; brand/service offerings make users feel confident; brand/service gives its owners social approval; brand/service helps customers make good impressions on other people.

3.
Brand Reputation trustworthy, reputability, making honest claims Respectable; able to solve problems attention to detail; helpful; clear Information on safety; friendly; punctual; courteous; honest in briefing of tour itinerary; welltrained; knowledge of destination; arranged service as promised.

4.
Brand Trust Reliability, intentionality Strong impression on senses; brand induces positive user emotions, physical actions, and behaviors when using; stimulates user curiosity; stimulates user problem solving. 5.
Brand Choice service, price, place, promotion, physical evidence, process, people, mobile application, brand name, consumer behavior.
Convenience; reasonable pricing; availability taxis; car condition; online booking; service during the trip; politeness of driver; knowledge of driver; trust of driver; simplicity of mobile application feature; clear, userfriendly navigation; fast loading times; professional app design; lifestyle; influential people; social network; social trending.
In this study, hypothesis testing is based on the significance test: if the probability value of 0.05 is smaller than the probability value of Sig or [0.05 <sig], then Ho is accepted and Ha is rejected, meaning it is not significant; if the probability value is 0, 05 is greater or equal to the probability value Sig or [0.05 ≥ sig], then Ho is rejected and Ha is accepted, meaning that it is significant. In general, the data used in parametric statistics is interval in nature, but the data obtained in this study is on an ordinal scale. Therefore, the ordinal data from the obtained questionnaires were transformed into interval data, in accordance with the minimum requirements for using the statistical parametric path analysis technique, achieved by the method of success interval (Li et al., 2022).
This study uses the structural equation modeling (SEM) method. According to Gilang et al. (2019) and Sulistijono et al. (2020), interpreting the structural equation model is an analysis that combines the factor analysis approach (factor analysis), structural model, and path analysis. In SEM analysis, three types of activities can be carried out simultaneously: checking the validity and reliability of the instrument (related to factor analysis); testing the relationship between variables (related to path analysis); and activities to obtain a suitable model to be predicted (with regard to structural model analysis).

DISCUSSION
The results showed that the first research hypothesis, namely that perceived service quality, perceived value, and brand reputation simultaneously and significantly affect brand choice by 58.2%. This supports research conducted by Kumar (2014) and Salsabila et al. (2021). The results also show the second hypothesis, defined as perceived service quality, perceived value, and brand reputation, simultaneously and significantly affect brand trust by 63.7%. This supports research conducted by Maghzi et al (2011), Dahiyat et al (2011), Zhang et al (2013, Rasheed & Abadi (2014), Han, Nguyen, and Lee (2015), Oh, Chung, & Park (2016), Prameka, Do, & Rofiq (2016), Husda et al (2017), Naggar &Bendary (2017), andSharma &Matur (2018). Furthermore, the results show the third hypothesis, concerning perceived service quality, perceived value, and brand reputation, simultaneously and significantly affect customer satisfaction by 52.5%. This supports research conducted by Maghzi et al (2011), Dahiyat et al (2011), Nuviala et al (2012, Subagio & Saputra (2012), Malik (2012), Raza et al (2012), Tabaku & Kushi (2013), Rizwan et al (2014), Ebrahimi & Tootoonkavan (2014), Chao, Wu, & Yen (2015), Oh, Chung, &Park (2016), andHusda et al (2017). Finally, the results show that the fourth hypothesis, namely that brand trust mediates the relationship between perceived brand quality, perceived value, brand reputation, and customer brand choice by 33.2%. This supports research conducted by Maghzi et al (2011) (2017), and Abbasi et al. (2021). The results showed that perceived service quality, perceived value, and brand reputation had a significant effect, with the highest to lowest effect being perceived service quality, brand reputation, and perceived value. The results also partially show that it is only perceived service quality that significantly affects brand trust, while perceived value and brand reputation do not significantly affect brand trust. Likewise, the results partially show that only perceived service quality and perceived value affect customer satisfaction significantly, while brand reputation does not significantly affect customer satisfaction. The overall research model can be described in Figure 3.
The current result differs from Natyari & Pradana (2016), who argue that brand trust and satisfaction contribute little to brand choice. In this case, customer satisfaction is an essential mediator of the relationship between perceived brand quality, perceived value, brand reputation, and customer brand choice. That said, this result corresponds to the results found by Elisa et al. (2022), who explain that brand reputation and satisfaction have strong relationship that can lead to stronger brand choice. Based on the results of the reports described above, we try to provide some suggestions that would be useful for the company. It can be concluded that the influence of perceived service quality, perceived value, brand reputation, and customer satisfaction affect the magnitude of brand trust, for which the relationship between perceived brand quality, perceived value, and brand reputation affects customer brand choice. Moreover, the influence of customer satisfaction mediates the relationship between perceived brand quality, perceived value, brand reputation, and customer brand choice. Perceived service quality, perceived value, and brand reputation influence brand trust simultaneously and significantly. Perceived service quality, perceived value, and brand reputation affect customer satisfaction simultaneously and significantly. Brand trust mediates the relationship between perceived brand quality, perceived value, brand reputation, and customer brand choice. Customer satisfaction mediates the relationship between perceived brand quality, perceived value, brand reputation, and customer brand choice.
This study is important because ride-sharing taxi service providers are one of several forms of partnership service providers within the scope of a populist economic philosophy (sharing economy). A survey on congestion in large Asian cities conducted by Uber and The Boston Consulting Group in 2017 showed that citizens largely complained that too much time was wasted due to traffic jams, difficulty finding parking spaces, and expensive parking fees, even being late to or missing an important event due to traffic jams. In conclusion, ride-sharing apps have been proven to have a positive effect in reducing traffic congestion. These apps have introduced a new and convenient mode of transportation that allows individuals to share rides and reduce the number of vehicles on the road. The reduction of cars on the road has contributed to less congestion and reduced travel times. Additionally, ride-sharing apps have also contributed to a reduction in greenhouse gas emissions, making them a sustainable and environmentally friendly transportation option.
Furthermore, ride-sharing apps provide individuals with a more affordable option for transportation, making travel more accessible to people who cannot afford vehicles. This has helped to reduce the number of cars on the road and the overall level of congestion. Ride-sharing apps have begun to revolutionize the transportation industry, providing a sustainable, affordable, and convenient option that has a positive effect on reducing traffic congestion.
Nevertheless, the current study has some limitations, namely those elements outside of the control of the researchers, the restrictions of which might have impacted the study's findings. One notable drawback, in particular, was the short amount of time available for data collection, which resulted in a relatively small respondent pool for information. As such, following studies can expand the number of respondents and focus on other variables that might influence brand choice in order to expand perspectives in the field of marketing. Marketing and promotional strategies can be powerful tools for influencing brand choice and loyalty in ridesharing apps, but the effectiveness of these strategies has not been well studied. Future research could explore how different marketing and promotional strategies affect brand choice and loyalty in this industry and identify the most effective strategies for retaining customers.