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The service quality imperative: Sustaining ridesharing adoption in the developing world
Abstract
This study aims to assess user perceived quality and its impact on sustaining the adoption of app-based ride- sharing services in the context of a developing country. Adopting the E-S-QUAL model as a theoretical frame- work, data have been collected from 250 ride-sharing app users in Bangladesh. Utilizing the PLS-SEM method, the structural model confirms that service quality is a hierarchical second order model which extensively impacts customer satisfaction and positively affects service loyalty. Specifically, fulfillment, security & privacy, system availability, and efficiency factors of e-service quality emerged as significant determinants of user loyalty and satisfaction. In addition, customer satisfaction fully mediates the relationship between service quality and intention to continue using the ridesharing services. The findings highlight the role of delivering high-quality digital services in fostering customer loyalty, commitment, and retention in the ride-sharing domain, particu- larly in developing economies. In addition, this study highlights that Bangladeshi perspectives on the sharing economy emphasize the need for better infrastructure, improved safety and privacy for women, and affordable, reliable service, insights that are also relevant for other emerging economies. Theoretically, this study extends the research of ridesharing services by applying the well-established E-S-QUAL framework while assessing the mediating role of customer satisfaction in ensuring service viability. Practically, it provides implications for ride- sharing platforms to enhance service attributes such as responsiveness, timeliness, and system reliability, thereby improving user experience and encouraging continued usage.
... The WebQual method is a measurement method for website quality based on the perceptions of end users (the public) [13]. This method is an extension of Servqual and has evolved from WebQual 1.0, which focused on analyzing information quality but had shortcomings in service interaction [14]. Then, WebQual 2.0 emphasized analysis of interactions but lacked in analyzing information quality. ...
This study aims to analyze the quality of the PCNU Kota Depok online news website in relation to user satisfaction. The method used is WebQual 4.0, one of the techniques for measuring website quality based on user perceptions across four dimensions: usability, information quality, interaction quality, and overall impression. The results of the study, based on Crosstab and Chi-Square tests, indicate that differences in perception across attributes in the four dimensions are not entirely influenced by respondent characteristics such as education, gender, age, and occupation. According to user perceptions, the service quality of the PCNU Kota Depok website can be measured by the highest levels of satisfaction in the following order: Overall Impression (4.09), Information Quality (3.92), Usability (3.76), and Interaction Quality (3.61). These results provide valuable insights for improving user experience and guiding future development of the PCNU Kota Depok website.
This study explores how system-based and cognitive-based factors affect platform trust and its role in the actual use of PayLater services (buy now, pay later or BNPL) in Indonesia and Malaysia. PayLater, a fintech innovation, provides fast and convenient payment options through online platforms. By incorporating platform trust into the technology acceptance model (TAM), the research investigates whether borrowing intention acts as a mediator between platform trust and actual usage. Utilizing a quantitative approach with purposive sampling, data were gathered from 106 respondents in Indonesia and 169 in Malaysia, with 62 and 85 respondents meeting the criteria, respectively. Partial least squares (PLS) analysis indicates notable differences in how Indonesian and Malaysian users perceive platform trust, while the effect of platform trust on borrowing intention remains consistent across both nations. Borrowing intention emerges as a crucial factor influencing the actual use of PayLater services. The results offer important insights into the adoption of fintech services in emerging markets, highlighting the significance of platform trust in shaping user behavior. This research provides practical suggestions for fintech providers to improve platform trust and user engagement in cross-country scenarios.
Shared electric scooter services (SESS) have gained popularity in many cities as an emerging mobility mode. However, SESS is attributed to low utilization rates in some cities. In this context, the significance of users’ satisfaction with the provided services, along with their loyalty, becomes particularly pronounced. Therefore, it is essential to evaluate the service quality (SQ) from the users’ perspective and understand its effect on satisfaction and loyalty, which are critical factors for the long-term durability and success of service. Thus, this study examines the determinants of user satisfaction and loyalty toward SESS. For this, we conducted an online survey among the SESS users in Chicago. We analyzed the responses using partial least squares structural equation modeling (PLS-SEM) and reflexive thematic analysis (TA). Our results confirm the quality-value-satisfaction-loyalty paradigm and indicate that users’ perceptions of SQ, including safety and security, service availability, interface, and perceived affordability, significantly contribute to user loyalty enhancement toward SESS. Perceived value (hedonic value, utilitarian value, and perceived affordability) and satisfaction mediate the impact of SQ on loyalty. Additionally, the results indicate that those who perceive SESS as cost-effective report higher satisfaction levels. Furthermore, users who have pro-environmental attitudes and view SESS as environmentally friendly are more likely to derive hedonic value from the service and exhibit higher loyalty. The TA uncovers key challenges from the user perspective, including pricing, service timing, end-trip facilities (e.g., parking), street pavement condition, vendor operational zoning, and fleet quality, with a specific emphasis on GPS accuracy. These findings provide valuable insights into user behavioral mechanisms, which can be considered as a manifest for service improvement and enhancing efficiency.
Introduction
The oldest olds (aged 85 and over) are the fastest-growing age segment. However, our understanding of their mobility is limited. To address this gap, we invited 19 U.S. and 30 Chinese “oldest old” to take part in focus groups and complete a mobility questionnaire. We focus on travel mode choice, which includes changes in travel modes, frequency of usage, and perceptions of comfort.
Methods
Older adults’ familiarity and acceptance of new mobility technologies (e.g., ridesharing, carsharing, and autonomous vehicles) were measured by questionnaire and focus group. Word clouds were also used to illustrate people’s reasons for choosing their primary mode of transportation.
Results and discussion
The results show that both panels of older adults similarly feel some extent of travel limitations. But the responses among the two groups differ: 18 American participants chose “drive myself” as their primary option a decade ago, while 11 chose it now; no Chinese participants selected it either a decade ago or now. Both currently and 10 years ago, there was a significant difference in mode choice between participants in China and the United States. However, this gap has narrowed over the past decade. Participants in China have significantly changed their transportation preferences compared to 10 years ago, while participants in the US have remained nearly unchanged. American respondents consider “ease” as an important factor, while Chinese respondents pay more attention to “safety” and “no other option to get around” when making travel mode choices. Compared to Chinese participants, American participants were more comfortable with driving an autonomous vehicle. These differences may result from the various developmental stages and transportation policies of the two countries. This study supports the development of new mobility technologies for the oldest old to improve their quality of life.
Various studies have been conducted to measure the level of service provided by an institution or service, including hospitals, in order to determine the level of customer satisfaction. The purpose of this research is to assess the role of the quality of services offered by a hospital in predicting customer satisfaction. This study was conducted at Bunda Purwokerto Hospital. The participants consisted of 380 samples. Hypothesis testing using the Smart PLS method yielded an R-square value of 0.413 for the customer satisfaction variable. The results of H1 revealed a favourable influence on the satisfaction of outpatient patients at Bunda Purwokerto Hospital. The original sample produced a coefficient of 0.130, a t statistic of 2.163 (> 1.96), and a p-value of 0.031 (< 0.05). The relationship between trust and job performance was deemed positive and significant, as evidenced by the t-statistic exceeding 1.96. This study confirms that an improvement in the quality of healthcare services shapes patient satisfaction and loyalty. Aspects encompassing healthcare service quality, such as the physical environment, customer-oriented atmosphere, responsiveness, effective communication, privacy maintenance, and safety, demonstrate a positive correlation with patient loyalty towards the hospital’s image.
The paper investigates the impact of negative online word-of-mouth (OWOM) generated from online consumer-run communities on brand hate and brand activism and the moderating role of collectivism in cultural orientation. Specifically, the authors used Stimulus-organization-response and cognitive dis-sonance theories to develop the research model. Data were collected from 337 valid responses from customers who are members of consumer-run groups to support the constructed hypotheses. Smart-PLS was used to analyze data. Negative OWOM was found to be a driver of psychological discomfort, which, in turn, generates brand hate. The formation of brand hate from negative OWOM can lead to anti-brand activism. The results highlighted that collectivist orientation significantly moderates the relationship between negative OWOM and psychological discomfort in consumers, as well as the relationship between brand hate and anti-brand activism. This study enriches existing literature by further understanding OWOM in virtual communities and emphasizing the role of cultural orientation on behavioral outcomes. Our takeaways provide valuable implications for brand and promotion practitioners to understand users' mechanisms to select the appropriate tool such as the emphasize on KOC (key-opinion-consumers) and KOL (key-opinion-leaders) interaction to handle the negative consequences within time limits, reducing contradicting affective states before anti-brand activism and negative OWOM escalate.
This study aims to explore the role of travel-related self-efficacy in sustained behavior change. Community-based electric ride-sharing as a pilot project has been introduced to reduce residents’ reliance on private cars in Bangkok, Thailand. This study integrated the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and goal-framing theory to explain the cognitive process from intending a trial ride to sustaining behavioral change to substitute present travel modes. A sample of 101 valid responses was collected from the service users. The findings show a pivotal role of travel-related self-efficacy in encouraging users to keep using the promoted
service by finding eudaimonic and normative goals during the intervention. Multi-group analysis was further applied to examine the moderating roles of transport mode preferences on hypothesized relationships. Pilot service users showed overall high self-efficacy associated with community-based mobility, and the stated self-efficacy was positively related to the intention to sustain behavior change. However, a drastic decrease was shown in user intention to pay for the service. Additional evidence was given to inform the importance of an affordable mobility service to secure residents’ self-efficacy in daily transport. Based on research findings, this study provides recommendations on practical applications and future research directions.
Lately, smartphones have had a significant impact on how individuals act, mainly when they shop. In Malaysia, Shopee is the online shopping website that has garnered the most traffic from e-commerce sites. Shopee Express recognizes the importance of customer happiness and brand loyalty in measuring consumer purchasing behavior for long-term performance. Some prior studies have had mixed results on the factors that influence online shopping apps’ brand loyalty with the interactive effect of other variables. To contribute to resolving these varied views, this study proposes that customer satisfaction mediates the antecedent factors that influence students’ loyalty to the Shopee app. As a cross-sectional online survey, we obtained data from 298 university students using the Shopee application. Partial least squares structural equation modeling (PLS-SEM) was used to analyze data, whereby the results confirmed a significant effect of the accuracy of delivery on brand loyalty and customer satisfaction, the price of delivery and customer satisfaction, and information quality on brand loyalty and customer satisfaction. Furthermore, easy payment also significantly affected brand loyalty and customer satisfaction, and customer satisfaction mediates delivery accuracy and brand loyalty, the price of delivery, information quality, and the brand loyalty link of students to the Shopee application. This study’s novelty is uncovering the intervening role of customer satisfaction in the antecedent factors of brand loyalty of the Shopee app. This study further contributes by providing helpful information to the stream of online logistic firms like Shopee to meet client needs and by providing valuable insights for scholars.
Understanding user's perception of service variability is essential to discern their overall perception of any type of (transport) service. We study the perception of waiting time variability for ride-hailing services. We carried out a stated preference survey in August 2021, yielding 936 valid responses. The respondents were faced with static pre-trip information on the expected waiting time, followed by the actually experienced waiting time for their selected alternative. We analyse this data by means of an instance-based learning (IBL) approach to evaluate how individuals respond to service performance variation and how this impacts their future decisions. Different novel specifications of memory fading, captured by the IBL approach, are tested to uncover which describes the user behaviour best. Additionally, existing and new specification of inertia (habit) are tested. Our model outcomes reveal that the perception of unexpected waiting time is within the expected range of 2-3 times the value-of-time. Travellers seem to place a higher reward on an early departure compared to a penalty for a late departure of equal magnitude. A cancelled service, after having made a booking, results in significant disutility for the passenger and a strong motivation to shift to a different provider. Considering memory decay, our results show that the most recent experience is by far the most relevant for the next decision, with memories fading quickly in importance. The role of inertia seems to gain importance with each additional consecutive choice for the same option, but then resetting back to zero following a shift in behaviour.
Currently, linked internet ride-sharing services are active in several Southeast Asian nations. This research aimed to investigate the relationships between the various variables by looking at the impact of perceived service quality, perceived value, and brand image on consumer brand preference. Cross-sectional data was used, and a quantitative technique strategy was taken. Customers of online ride-sharing service alliances in Southeast Asia are the subject of the unit analysis, which includes 384 respondents from each of the following countries: Malaysia, Indonesia, Cambodia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. The representative offices of the die-sharing businesses in our target nations were the distribution points for surveys used in the sampling method, which combined random sampling with purposive sampling. Path analysis is the method of data analysis employed. The results showed that perceptions of service quality, perceived value and brand reputation influence brand choice simultaneously and significantly.
For logistics service providers (LSPs), improving customer satisfaction and obtaining customer re-use intention are key to gaining sustainable competitive advantages and success. Logistics service quality (LSQ) is a concern for logistics service providers, retailers, and customers. The proposed model, which is based on the stimuli-organism-response theory and the logistics service quality framework, integrates operational quality, resource quality, information quality, personal contact quality, customization quality, and customer satisfaction to study logistics service re-use intentions. The data were obtained from an online survey using a structured questionnaire given to those with experience in logistics service. Using partial least squares structural equation modeling on 810 respondents who were adult Chinese customers, this study discovered that operational, resource, information, personal contact, and customization qualities positively affect the satisfaction of logistics service customers, while customer satisfaction positively affects re-use intention. Moreover, the results of the mediation analysis revealed that customer satisfaction mediated the connection between the five components of LSQ and the re-use intention of logistics services. The originality of the study lies in its comprehensive examination of the direct and indirect effects of service quality dimensions on customer satisfaction and logistics service re-use intention in the context of logistics services. This study provides valuable insights into the importance of customer satisfaction in the logistics industry and highlights the need for logistics companies to prioritize customer satisfaction and improve their overall performance and competitiveness.
Traditional taxi providers are slowly losing their clients to online taxi providers, which are becoming increasingly popular. These companies typically provide a commercial, centralized platform in order to provide these services. The concept of centralization gives those providers significant power over their users, such as demanding and changing fees and collecting data over provided services. We aim to discuss how a decentralized approach using blockchains can solve those problems. A ride-sharing platform with the most essential functionality is implemented using a decentralized application based on smart contracts, which are, in turn, deployed on different blockchains. Various effects with respect to implementing and providing a decentralized ride-sharing service are taken in to account, especially regarding the effective cost for users. The fees of the developed platform heavily depend on which blockchain it is deployed on. Blockchains may compete in term of cost with traditional ride-sharing platforms, but choosing a suitable blockchain for the application is essential. Furthermore, the prototype shows that the time it takes for a transaction to be manifested into a block and subsequently confirmed is multiple times longer than a traditional web service response. These new problems require a new approach to implementing those requests that do not negatively affect the user experience.
In a fast-growing global economy, there is much debate in the socio-economic models about the sharing economy, which is a digital platform that benefits society and improves people’s quality of life. A significant benchmark of the sharing economy is that it enables individuals to monetize their assets that need to be used fully. This highlights an individual’s ability and perhaps their preference to either rent or borrow goods rather than own them. This study investigated Saudi Arabian students’ User Satisfaction (US) and their Re-Purchase Intentions (RPI) in the context of the sharing economy. We employed a deductive approach that utilized cross-sectional data collected through online sampling. The results were derived from 324 acceptable completed questionnaires. We used a Structural Equation Model (SEM) to confirm the positive and significant predictive power of Trust, Economic Benefits (EBs), Sharing Economy Philosophy (SEP), Service Quality and Net Benefits (NBs) on US and RPI. The results also demonstrated a positive and significant effect of concerns such as Lack of Trust (LoT) and Expected Effort (EE) on US. Finally, among Saudi Arabian students, US is a positive and significant predictor of RPI. In the context of a developing country such as Saudi Arabia, this study’s insights to the practical and theoretical spheres contribute to operational management and the literature about online digital learning.
The novel coronavirus (COVID-19) pandemic created an environment where nearly all aspects of mobility changed to ensure the health and safety of the public. The Centers for Disease Control and Prevention (CDC) recommended that people quarantine for 14 days if they were potentially exposed to the virus, stay at least six feet apart from others, and stay at home as much as possible. Delivery via third-party restaurant app, grocery, and package delivery quickly became an essential service. This study assesses customer's changes in use and perceived quality of delivery services in Southwest Virginia, via an online stated-preference survey (n = 423). The responses were analyzed using ordered logit and generalized ordered logit models to identify which population segments had changing delivery behavior and perceptions due to the pandemic. Findings include that before the pandemic, only households with an income greater than 25,000. During the pandemic, all income brackets had a significantly higher demand for package delivery "weekly" than households with less than a 25,000 to 50,000, 50,000 to 100,000, respectively. This trend highlights that package delivery became necessary during the pandemic. Respondents who lived within town limits were statistically significantly more likely to use third-party restaurant delivery apps at least once a week before (3.10%), during (9.20%), and after (4.50%) the pandemic compared to those outside town limits. The results also found people who lived within town limits were 7.77% more likely to be satisfied with delivery services in general than those who lived outside town limits. The findings from this paper identify expanding delivery equity gaps within the population and provide recommendations for policymakers and delivery agencies. Some limitations include that low sample size did not allow for fully segmented models and meant that the study should be considered exploratory in nature.
Recent technology developments and the numerous availabilities of mobile users, devices and Internet technologies together with the growing focus on reducing traffic congestion and emissions in urban areas have led to the emergence of new paradigms for ridesharing and crowdsourcing for smart cities. Compared to carpooling approaches where the driver and participant passengers or riders are usually prearranged and the journey details known beforehand, the paradigm for ridesharing requires the participants to be selected at short notice and the rider trips are often dynamically formed. Crowdsourcing techniques and approaches are well suited to match drivers and riders for these dynamic scenarios, although there are many challenges to be addressed. This paper aims to survey this new paradigm of ridesharing and crowdsourcing for smart city transportation environments from several technological and social perspectives including: (1) Ridesharing and architecture in transportation; (2) Techniques for ridesharing; (3) Artificial intelligence for ridesharing; (4) Autonomous vehicles and systems ridesharing; and (5) Security, policy and pricing strategies. The paper concludes with some use cases and lessons learned for the practical deployment of ridesharing and crowdsourcing platforms for smart cities.
The provision of on-demand door-to-door trips within the hailing sector has experienced significant disruptions in the last years due to the advent of ride-hailing services. The evolution of the sector is ongoing and one of the latest novelties is the introduction of e-hailing, which allows the booking of conventional regulated taxis through digital applications. The regulatory and technological dimensions of taxi and ride-hailing seem to play a key role when trying to explain users’ choices of hailing services. For this reason, providing travelers with an option that combines traditional regulated services with the advantages of digital applications promises significant changes in users’ preferences. This paper aims to understand the preferences of hailing users taking Spain as case study because of the controversy after the advent of competition in the hailing market. To that end, a Generalized Structural Equation Model (GSEM) has been built to simultaneously study the influence of socioeconomic characteristics, latent psychological constructs, and mobility habits on individuals’ frequency of use of hailing services and their probability to belong to a specific hailing user profile. The results show that the adoption of ride-hailing and e-hailing is mainly influenced by psychological constructs. Individuals who wish to enjoy a high quality of service, but are not so liberal from the economic perspective, are more likely to have used e-hailing. Furthermore, the frequency of use of hailing services is affected by psychological constructs as much as by socio-economic variables and mobility habits. Finally, the effect of the openness to competition in the hailing market is discussed.
The integration of automation and shared mobility services would significantly affect transportation demand, especially mode choice. However, little is known about how attitudes, travel attributes, and demographic factors affect the modal shift to shared autonomous vehicles (SAVs). A stated preference survey was designed to determine the preferences of car and transit users in relation to a modal shift to SAVs. The binary logit models’ results revealed distinct behavior patterns and systematic heterogeneity among transit and private car users based on a representative sample of 607 individuals in 2021. The shifting behavior of both users is positively affected by attitudinal factors, including consumer innovativeness, perceived usefulness, sharing intention, and ecological awareness, while negatively affected by privacy concerns. In terms of travel-related attributes of SAVs, car users are eight times more sensitive to waiting times compared to transit users, who are three times more concerned with travel costs. Further, privacy concerns, the number of passengers sharing a trip, and the ratio of waiting time to travel time of SAVs were the major barriers to shifting the likelihood of car users’ behavior. In light of these findings, based on the likely effects of SAVs on shifting behavior, a number of practical implications are suggested for more effective policy making.
Customer satisfaction is at the heart of any successful business entity. The influence of service quality on the role of customer orientation in achieving greater customer satisfaction in the banking industry from the perspective of customers has not received the required attention in the marketing literature. This study sought to respond to the question of whether service quality could influence the effect of customer orientation on customer satisfaction. The study adopts a quantitative research approach with a descriptive survey design. With the aid of PLS-SEM, data from 391 commercial bank customers was analysed. It was identified that, within the banking industry, customer orientation is a key predictor of customer satisfaction. Customer satisfaction would improve when service quality improves, and service quality plays a partial role in the relationship between customer orientation and service quality. The study recommends that policymakers develop comprehensive policies and also direct the management of commercial banks to develop customer orientation programmes.
Nonprofit ridesharing presents an underutilized opportunity for increasing transportation sustainability, as well as users’ economic and social benefits, while reducing adverse environmental impacts. However, while app-based ridesharing has achieved only modest uptake, mostly limited to longer trips, in certain contexts, self-organized ridesharing (SORS) has shown significant achievements, even for the challenging short- and mid-range commuting trips. Still, knowledge regarding the key elements and mechanisms behind successful SORS is partial, hindering the ability to effectively leverage SORS diffusion and scaling potential. Following the premise that successful initiatives may provide learning opportunities, this study aims at narrowing this knowledge gap by performing a comparative cross-cultural systematic study of eight diverse SORS cases. The study uses a recently designed conceptual framework and multiple research methods (mainly online data exploration, personal interviews, observations, and documents analysis) to comprehensively examine SORSs’ attributes and evolution stages and processes. Study findings highlight repeated patterns as well as the role of context, official actors, and local practices in shaping initiative’s dynamics towards success. The study offers general and specific policy recommendations for supporting the early development, growth, and diffusion of SORS, as well as reflections on post pandemic ridesharing.
Ride‐hailing platforms such as Uber and Lyft promise to reduce negative externalities of driving and improve access to transportation. However, recent empirical evidence has been mixed about the impact of ride‐hailing on US cities, often resulting in a net increase in traffic congestion and greenhouse gas (GHG) emissions, largely due to increased travel demand and competition with public transit. Pooled rides, in which multiple passengers share a single vehicle, is an effective solution to improve the sustainability of ride‐hailing, reducing GHG emissions and traffic congestion and appealing to price‐sensitive population segments by offering relatively cheaper rides. Yet most ride‐hailing trips are unprofitable currently, resulting from ride‐hailing rides being subsidized (especially pooled) to compete with cheaper transportation alternatives such as public transit. In this paper, we consider whether price optimization can be used to improve ride‐hailing revenues while also reducing the environmental impacts of ride‐hailing, particularly as the cost of ride‐hailing is expected to fall into the future with the introduction of automated vehicles. Using a discrete choice experiment and multinomial logit choice model with a representative sample of the U.S. population, we estimate consumer preferences for the attributes of ride‐hailing services and use them to explore how ride prices affect the revenue of ride‐hailing platforms and the total vehicle miles traveled (VMT) by the ride‐hailing fleet. We show that as the costs of driving fall, continuously increasing the difference between the prices of individual and pooled rides is financially optimal for ride‐hailing platforms. Importantly, this pricing strategy also significantly reduces total VMT, resulting in a win‐win for ride‐hailing platforms and cities. We perform extensive sensitivity analyses and show that our results are qualitatively robust under a wide range of consumer preferences and market conditions, but that the optimal trajectory of prices and realized gains vary, highlighting opportunities for ride‐hailing services to influence the future of urban transportation. This article is protected by copyright. All rights reserved
Despite numerous studies focusing on ride-sourcing services, most have concentrated on users' pre-usage behaviour. This study explores users' post-usage behaviour, aiming to identify significant factors affecting existing users' intentions to continue using app-based ride-sourcing services in Egypt. Integrating the Expectation-Confirmation Model (ECM), the Technology Acceptance Model (TAM), and the Technology Readiness Model (TRM), this research identifies key determinants influencing users' perceptions and continued usage intentions. An online questionnaire collected empirical data from 381 respondents, analysed using partial least squares structural equation modelling (PLS-SEM). The results highlight the essential roles of optimism, innovativeness, discomfort, and insecurity in shaping users' perceptions of ride-sourcing apps' usefulness. Additionally, perceived ease of use is determined by innovativeness and discomfort. Furthermore, users' continuance usage intention is significantly associated with satisfaction level, perceived usefulness, and perceived ease of use. This study's findings offer valuable insights for service providers, aiding their understanding of variables influencing users' decisions to continue using ride-sourcing apps and enabling them to retain and satisfy their current users effectively.
This study develops a novel theoretical framework to explore the different paths of basic needs and advanced needs on users’ ridesharing intention and ridesharing behavior. Employing partial least squares structural equation modeling and multi-group analysis, questionnaire responses from 1044 users in China were empirically evaluated. The results show that basic needs influence ridesharing intention and ridesharing behavior mediated through psychological factors, while advanced needs directly stimulate ridesharing intention and ridesharing behavior. Factors of basic needs have a greater impact on ridesharing intention and ridesharing behavior than those of advanced needs. Additionally, the effects of the same factor on ridesharing intention and ridesharing behavior vary among users with different genders, ages, incomes, and education levels. Finally, we propose a framework for implementing ridesharing intervention strategies. The aforementioned findings can contribute to the development of specific measures for ride-sourcing platforms and policymakers, thereby playing a significant role in guiding ridesharing at the national level.
Tele-driving refers to a novel concept by which drivers can remotely operate vehicles (without being physically in the vehicle). By putting the human back in the loop, tele-driving has emerged recently as a more viable alternative to fully automated vehicles with ride-hailing (and other on-demand transportation-enabled services) being an important application. Because remote drivers can be operated as a shared resource (any driver can be assigned to any customer regardless of trip origin or destination), it may be possible for such services to deploy fewer drivers than vehicles without significantly reducing service quality. In this paper, we examine the extent to which this is possible. Using a spatial queueing model that captures the dynamics of both pickup and trip times, we show that the impact of reducing the number of drivers depends crucially on system workload relative to the number of vehicles. In particular, when workload is sufficiently high relative to the number of vehicles, we show that, perhaps surprisingly, reducing the number of drivers relative to the number of vehicles can actually improve service level (e.g., as measured by the amount of demand fulfilled in the case of impatient customers). Having fewer drivers than vehicles ensures that there are always idle vehicles; the fewer the drivers, the likelier it is for there to be more idle vehicles. Consequently, the fewer the drivers, the likelier it is for the pickup times to be shorter (making overall shorter service times likelier). The impact of shorter service time is particularly significant when the workload is high, and in this case, it is enough to overcome the loss in driver capacity. When workload is sufficiently low relative to the number of vehicles, we show that it is possible to significantly reduce the number of drivers without significantly reducing service level. In systems in which customers are patient and willing to queue up for the service, we show that reducing the number of drivers can also reduce delay, including stabilizing a system that may otherwise be unstable. In general, relative to a system in which the number of vehicles equals the number of drivers (as in a system with in-vehicle drivers), a system with remote drivers can result in savings in the number of drivers either without significantly degrading performance or actually improving performance. We discuss how these results can, in part, be explained by the interplay of two counteracting forces: (1) having fewer drivers increasing service rate and (2) having fewer drivers reducing the number of servers with the relative strength of these forces depending on system workload.
This paper was accepted by Baris Ata, stochastic models and simulation.
Funding: This work was supported by the US National Science Foundation [Grant SCC-1831140], and the Guangdong (China) Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [2023B1212010001].
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01687 .
Purpose-This study aims to investigate the impact of several factors on customer satisfaction and intention of reusing ride-hailing services that is a new type of passenger urban transport service.
Design/methodology/approach-This research applied the Partial Least Squares Structural Equation Modeling analysis method to examine the measurement scale and to analyze the primary data collected from 388 passengers in Vietnam.
Findings-This study demonstrates that three dimensions of perceived value, namely, functional value, hedonic value and economic value, positively influence customer satisfaction. The other dimension of perceived value, which is social value, has an ambiguous effect on satisfaction. In addition, personal innovativeness promotes all dimensions of perceived value. In particular, this study highlights that customer satisfaction and corporate image positively impact reuse intention, and corporate image moderates the relationship between customer satisfaction and reuse intention.
Originality/value-This study enriches knowledge about customer behavior using services based on the sharing economy business model. In particular, theoretical and practical implications are provided for researchers and enterprises to find suitable strategies for business.
Ride-hailing services are a component of the transportation system in many developing countries due to limitations in public transportation services. However, incidents still often occur that are detrimental to passenger safety. Therefore, this research aims to analyze the impact of service quality and perceived safety on passenger satisfaction and attitudinal loyalty in ride-hailing services. This research is quantitative with a data collection method using a questionnaire distributed online to 499 service users in nine major cities in Indonesia using a purposive sampling technique. Survey data were analyzed using the partial least squares-structural equation modeling (PLS-SEM) method. This research proves that ride-hailing service quality positively affects passengers’ perceived safety, satisfaction, and attitudinal loyalty. Perceived safety positively affects the satisfaction and attitudinal loyalty of passengers. Finally, satisfaction has a positive effect on passenger attitudinal loyalty. This research contributes that fostering a sense of security is crucial for the ride-hailing industry because it can determine satisfaction and loyalty in ride-hailing services.
Ride-hailing is a sustainable transportation paradigm where riders access door-to-door traveling services through a mobile phone application, which has attracted a colossal amount of usage. There are two major planning tasks in a ride-hailing system: 1) matching, i.e., assigning available vehicles to pick up the riders; and 2) repositioning, i.e., proactively relocating vehicles to certain locations to balance the supply and demand of ride-hailing services. Recently, many studies of ride-hailing planning that leverage machine learning techniques have emerged. In this article, we present a comprehensive overview on latest developments of machine learning-based ride-hailing planning. To offer a clear and structured review, we introduce a taxonomy into which we carefully fit the different categories of related works according to the types of their planning tasks and solution schemes, which include collective matching, distributed matching, collective repositioning, distributed repositioning, and joint matching and repositioning. We further shed light on many real-world data sets and simulators that are indispensable for empirical studies on machine learning-based ride-hailing planning strategies. At last, we propose several promising research directions for this rapidly growing research and practical field.
Purpose
This study aims to understand the effect of cultural dimension (individualism/ collectivism) on promotional rewards (social or economic) resulting in incentivizing consumers to engage in electronic word-of-mouth (eWOM), further impacting their repurchase intentions.
Design/methodology/approach
In Study 1, a 2 (culture: individualism vs collectivism) × 2 (promotional rewards: social vs economic) between-subjects design was used. Structural equation modeling was used to test the hypotheses. In Study 2, culture was measured instead of just being manipulated. The authors used regression analysis in this study.
Findings
Owing to the characteristics of collectivistic individuals, consumers in collectivistic cultures were more likely to respond to social rewards as an incentive to engage in eWOM. However, consumers in individualistic cultures were more motivated to engage in eWOM when economic rewards were offered.
Originality/value
Despite the global nature of eWOM, little research has explored the effects of cultural traits on consumer response to amplified eWOM strategy. Additionally, though many organizations now offer various promotional incentives to reviewers, little research has explored the effects of promotional offers on a reviewer’s subsequent behavior, and no research has explored the relationship between cultural dimensions and current and future response to promotional eWOM rewards.
Recent literature highlights the necessity of adapting conventional brand equity theories to emerging digital business models. To fill this need, the current study proposes a brand resonance model tailored to on-demand ride-hailing brands. The model was tested on 363 ride-hailing users from two diverse countries, the USA and Pakistan. The findings indicate that users’ perceptions of value and personal reputation have a direct impact on brand resonance, while brand trust mediates the influence of personal reputation, value, and digital platform performance on brand resonance. Moreover, the study reveals that digital natives in both countries exhibit similar patterns of user behaviour and service expectations. Notably, the study highlights that being a ‘trusted brand’ is a crucial aspect of the on-demand ride-hailing brand identity.
Keywords: ride-hailing; brand equity; brand trust; sharing economy; digital branding.
Purpose
Although the sharing economy improves comfort and convenience, it is yet unclear how it affects subjective well-being. This study aims to offer a conceptual model for understanding the linkages between the antecedents and consequences of subjective well-being in ridehailing services.
Design/methodology/approach
Using a non-probabilistic sampling method and a pre-tested survey instrument, 450 responses were collected from January to March 2020. The data were analysed using structural equation modelling.
Findings
Experience quality and perceived convenience are correlated with subjective well-being. Perceived value and personal innovativeness were not correlated with subjective well-being, as the former does not contribute to the latter’s development. Continuous usage intention significantly correlated with subjective well-being, followed by customer relationship proneness and advocacy. Regarding gender and age differences, men place higher value on customer relationship proneness than women, while women place higher value on subjective well-being than men. Older users value perceived convenience and customer relationship proneness in ridehailing services more than younger users.
Practical implications
Understanding key factors contributing to user well-being in ridehailing would promote a more affordable mobility sector globally. This understanding would enable ridehailing businesses to create more effective business and marketing plans while prioritising user well-being, thus enhancing user happiness and reducing turnover rates.
Originality/value
This research demonstrates how crucial it is for users’ well-being to have a positive experience and find the service convenient. It also highlights the importance of building strong customer relationships and examines how gender and age influence people’s adoption and use of these services.
Purpose
This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.
Design/methodology/approach
Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.
Findings
The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.
Research limitations/implications
Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.
Practical implications
The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.
Originality/value
Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.
Purpose-The purpose of this study is to explore the interplay between electronic service quality, user experience (UX) and overall customer satisfaction. Additionally, it aims to assess the suitability of E-S-QUAL and UX metrics within the cultural context of Greece.
Design/methodology/approach-Data were collected from 310 Internet users based on their last online purchase from an e-retail website. To evaluate the conceptual model, the authors used partial least squares structural equation modeling (PLS-SEM).
Findings-The findings of this study validate the scales' reliability and validity in the realm of electronic commerce (e-commerce) in Greece. The findings also emphasize the favorable association between e-service quality and UX with overall satisfaction, while indicating that e-service quality plays a partial mediating role in the relationship between UX and customer satisfaction.
Originality/value-The authors' study enhances the existing theory by introducing a new multi-dimensional conceptual framework that illuminates the relative importance of the dimensions within the scales. Additionally, it offers valuable insights into the impacts of e-service quality and UX on overall satisfaction, providing managers and practitioners with a tool to evaluate the quality of their electronic services and make necessary adjustments to meet the needs of their customers.
With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed.
With the rapid development of ubiquitous computing, our society is witnessing a rapid expansion of mobility-on-demand services, in which ridesharing (e.g., Uber, Lyft, and DiDi) has become one of the most successful applications and has percolated into people’s daily life. Even though a large number of research studies have been conducted to understand the demand and supply patterns or improve the operation efficiency of ridesharing services, little is known at a comprehensive level on their evolution, especially during the widely-initiative vehicle electrification process that electric vehicles start to take over conventional gas vehicles gradually. Different from conventional gas vehicles, electric vehicles have some unique characteristics, e.g., long charging time compared to the refueling process of gas vehicles, which potentially makes a difference in providing ridesharing services. In this paper, we seek to shed light on the evolution of city-scale ridesharing services with the penetration of large-scale electric vehicles. In particular, our study is based on a ridesharing operation dataset from the Chinese city Shenzhen in 2019, including all orders served by over 50,000 unique ridesharing drivers. We perform a set of observations on the differences between gas vehicle and electric vehicle drivers for ridesharing services from different dimensions, e.g., spatial, temporal, and income, etc. Our study shows that understanding the evolution of city-scale ridesharing with the penetration of electric vehicles has strong implications for ridesharing drivers, passengers, operators, and city governments. On the one hand, our findings paint a promising picture of electric vehicles for ridesharing services, showing its prosperity in the Chinese city Shenzhen. On the other hand, our study also has the potential to provide some meaningful guidelines for other cities that plan to replace their vehicles for ridesharing services with electric vehicles based on the obtained insights, e.g., possible drawbacks for long trips and charging infrastructure deployment.
The gig economy provides workers with the benefits of autonomy and flexibility but at the expense of work identity and coworker bonds. Among the many reasons why gig workers leave their platforms, one unexplored aspect is the lack of an organization identity. In this study, we develop a team formation and interteam contest field experiment at a ride-sharing platform. We assign drivers to teams either randomly or based on similarity in age, hometown location, or productivity. Having these teams compete for cash prizes, we find that (1) compared with those in the control condition, treated drivers work longer hours and earn 12% higher revenue during the contest; (2) the treatment effect persists two weeks postcontest, albeit with half of the effect size; and (3) drivers in hometown-similar teams are more likely to communicate with each other, whereas those in age-similar teams continue to work longer hours and earn higher revenue during the two weeks after the contest ends. Together, our results show that platform designers can leverage team identity and team contests to increase revenue and worker engagement in a gig economy.
This paper was accepted by David Simchi-Levi, behavioral economics and decision analysis.
Funding: Financial support from the platform through the Michigan Institute for Data Science is gratefully acknowledged.
Supplemental Material: The e-companion are data are available at https://doi.org/10.1287/mnsc.2022.4624 .
Customer Satisfaction and loyalty are critical indicators of the sharing economy’s long-term viability, particularly in developing countries. The main objective of this study is to develop a service quality model applicable in the sharing economy based on the ridesharing service perspective.Through synthesizing existing theories and literature, the dynamics of ridesharing service quality (RSSQUAL) have been conceptualized. To verify the study using thePLS-SEM analysis technique, data have been collected in Dhaka from 210 users of ridesharing services through an online questionnaire survey. This study finds that ridesharing service quality is a second- order model, whereby six primary dimensions including service availability, ease of use, empathy, tangibles, security & privacy, and cost constitute the primary dimensions. The study also finds significant relationships among RSSQUAL, service loyalty and customer satisfaction. Theoretically, this study extends the research of sharing economy through proposing the RSSQUAL model in a new research context. Practically, companies can focus on key quality dimensions to better satisfy the customers. Finally, the viability of sharing economy in the developing countries has been assessed through the determination of customer service loyalty and satisfaction.
This paper uses a difference‐in‐differences strategy and an event‐study analysis to evaluate the effect of Uber entries on vehicle miles travelled in 346 US Metropolitan statistical areas between 2011 and 2017. Empirical results demonstrate that Uber entries have no significant effect on the total vehicle miles travelled in a city. However, Uber is found to decrease the vehicle miles travelled on highways but increase them on collector roads. All these effects come mainly from large metropolitan statistical areas. A simulation exercise suggests that Uber entries cause longer travel times if the share of travel time spent on collector roads is high. Les services de covoiturage causent‐ils de l'encombrement de la circulation? Cet article utilise une stratégie des doubles différences et une analyse d'étude d'événement afin d'évaluer l'effet de l'arrivée du service Uber sur les véhicules‐milles parcourus (VMP) dans 346 régions métropolitaines aux États‐Unis entre 2011 et 2017. Les résultats empiriques montrent que l'arrivée d'Uber n'a aucun effet significatif sur les VMP totaux dans une ville. Toutefois, nous constatons qu'en raison d'Uber, les VMP diminuent sur les autoroutes et augmentent sur les routes collectrices. Tous ces effets proviennent surtout des grandes régions métropolitaines. Un exercice de simulation donne à penser que l'arrivée d'Uber provoque un temps de déplacement plus long si la proportion du temps de déplacement sur les routes collectrices est élevée.
Ridesharing services such as Uber and Lyft have been substantially affected by the ongoing COVID-19 pandemic. Drawing on social capital theory, the current research investigates how social trust relates to three types of trust in compliance with COVID-19 guidelines and consumers' ridesharing intentions. Analyzing data from two economically and culturally distinct countries, the results suggest that social trust positively affects trust in platform companies' compliance with COVID-19 guidelines (TPC), but not (or to a lesser extent) trust in drivers' (TDC) and other riders (TRC) compliance with COVID-19 guidelines in both the United States and Bangladesh. Importantly, TPC, TDC, and TRC are positively related with consumers' ridesharing intentions in the United States but not in Bangladesh. Furthermore, the analysis reveals two counterintuitive moderating effects of fear of COVID-19 and trust in God. The results provide important insights on factors affecting the ridesharing industry in the context of the COVID-19 pandemic, and they emphasize the importance of considering cultural context in understanding consumers’ intentions to engage in the sharing economy.
This study aims to investigate the effects of coffee brand service quality and customer experience on brand equity, brand personality, and brand reputation. To achieve this purpose, the proposed research model was examined with structural equation modeling using R. Empirical analysis indicates that brand personality and brand reputation are determined by brand equity, which is formed by customer experience explained by service quality. Specific service quality factors that affect customer experience are interaction and result qualities. However, physical environmental quality did not have a statistically significant effect on customer experience. Analysis results suggest that the personality, reputation, and equity that customers have in a coffee brand can be enhanced by customer experience through service quality. The results of this research support the idea of needing to compete with strong brands and how marketing and management tactics around service quality and customer experience can help a company compete.
In light of the increasing development of technological innovation and information and communication technologies, features of mobile apps functions are also increasingly developed to meet people's needs and wants. Amongst the variety, shared transportation apps (STA) have emerged to optimize people's daily transportation needs. This study modified the expectation-confirmation theory and the post-acceptance model of information system continuance to examine the effects of customers' perceived STA performance (service performance, content provision, and system performance) and benefits (function, money worthiness, pleasure, and social interaction) on customer satisfaction with the usage of STA, which is expected to have a positive effect on customer retention on STA in a new theoretical framework, called the performance-benefit of the STA continuance model (PBCM). Moreover, brand awareness was expected to be an essential moderator on the effect of perceived performance and perceived benefits on customer satisfaction. 397 respondents were recruited online through a convenient sampling technique in the Vietnam market. Results show that service performance, money worthiness, pleasure, and social interaction are four important determinants of customer satisfaction with STA. Moreover, brand awareness significantly moderates the effects of service performance, system performance, money worthiness, and social interaction on customer satisfaction. Findings also contribute rational strategies for e-commerce managers in general and STA managers in particular.