Rider Satisfaction Research Articles

Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from the Ele.me platform. Quantitative methods, including the frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze satisfaction differences between men and women riders. The findings reveal an asymmetric pattern in satisfaction preferences: women riders place more emphasis on perceived value, while men riders prioritize service perceived quality. Although both groups rank platform image, product perceived quality, and rider expectations similarly, the importance of these factors varies significantly, indicating an underlying asymmetry in their expectations and values. Women riders express higher satisfaction with platform image, rider expectations, service perceived quality, and product perceived quality, with rider expectations showing the largest difference. Additionally, the multi-criteria decision-making methods used in this study offer insights for optimizing service performance in real-time crowdsourcing logistics platforms, particularly in handling uncertainty and enhancing system adaptability through fuzzy sets. These findings provide a basis for developing gender-specific strategies aimed at enhancing rider satisfaction, minimizing turnover, and improving platform adaptability—contributing to a more inclusive and sustainable logistics supply chain.

Research on the Location Selection Problem of Electric Bicycle Battery Exchange Cabinets Based on an Improved Immune Algorithm

The rise of new energy technologies has accelerated progress towards sustainable development, and many companies are beginning to invest in renewable resource-related facilities. Electric bicycles have always been an important mode of green transportation; however, they also have problems such as slow charging, difficult charging, and that burning and short circuiting may occur during charging. Electric bicycle battery exchange cabinets effectively solve these problems by exchanging low batteries with full batteries instead of charging. However, current battery exchange cabinets face the problems of insufficient construction and unreasonable site selection. Therefore, this paper proposes a location selection model for electric bicycle battery exchange cabinets based on point demand theory, aiming to maximize rider satisfaction and the service capacity of exchange cabinets. The immune algorithm is introduced to solve the location model; however, the traditional immune algorithm has some problems such as poor stability and slow convergence. In this paper, the mutation process of the traditional immune algorithm is improved by introducing multi-point mutation, guided mutation, and local search. Finally, based on the data of electric bicycle riders in Shanghai, we verify that the location model based on point demand theory performs well on two objective functions of rider satisfaction and battery exchange cabinet service capability. We also expand the application of point demand theory to location models. Then, by conducting experiments with different parameter groups, through sensitivity analysis and convergence analysis, we verified that the improved immune algorithm performs better than the traditional immune algorithm in its accuracy, search accuracy, stability, and convergence.

Creation of a High-Precision, Single-Board Computer-Based Intelligent Passenger Counting System

This paper introduces research aimed at developing and implementing an intelligent passenger counting system in public transportation. The goal is to enhance fare evasion control and reduce financial losses for transit operators by automatically monitoring the entering and exiting of passengers. Utilizing the advanced capabilities of YOLO and DeepSORT algorithms, the system demonstrates high accuracy in detecting and tracking passengers, even in congested scenarios. Practical experiments have highlighted several challenges, including real-time frame processing rates, single-board computer performance, and the accuracy of passenger counts. It was discovered that the selection and positioning of USB cameras significantly influence system efficiency. Notably, changing the IP cameras to USB cameras significantly improves the processing speeds. A dataset containing images was created to improve the YOLO model's accuracy in detecting passengers. This dataset was particularly relevant considering the winter season, where identifying passengers could be challenging due to their bulky outerwear. To upgrade the performance of the DeepSORT system, the YOLO model was also improved with the pre-designed dataset to focus solely on the heads. This trained model achieved a recognition accuracy of 91% during peak hours. During periods of lighter traffic, when there were fewer passengers, the accuracy increased further due to reduced interference and higher precision. To enhance real-time processing efficiency, this research incorporates the status of public transport doors as a key parameter. By optimizing the number of frames forwarded to the YOLO algorithm for processing, we ensure that the system maintains accuracy without compromising on speed. Future development will focus on incorporating depth-sensing cameras and developing advanced data analysis algorithms for real-time processing on single-board computers. This will further enhance the precision of passenger counts during high-traffic periods. Expected benefits of this project include more efficient transport route planning, better management of passenger flows, improved rider satisfaction, and more effective measures against fare evasion.

Demographic Breakdown of Transit Rider Satisfaction

With ridership declining nationally and transit agencies looking for innovative ways to maintain and attract riders, a more complex understanding of transit riders and their satisfaction could provide additional insight and guidance to benefit the future of transit. This study challenged the traditional captive versus choice rider dichotomy and indicates the need for a more nuanced breakdown of transit riders based on the attributes most important to them. To conduct the analysis, the authors obtained rider survey data from nine agencies across the United States from varying geographic regions and representing various agency sizes. Agencies were selected based on their intentional use of demographic classifications and questions about satisfaction with various aspects of transit service. The authors then applied ordered logit regression across the 18,544 rider survey responses to predict the relative importance of service attributes on overall satisfaction. The findings suggested that different classifications of riders by gender, race, and income yielded diverse priorities, although certain service aspects such as reliability were important across demographics. In addition to the findings from the regression analysis, this study also offers a series of recommendations to facilitate future investigations by using more consistent, standardized data to further the breadth and depth of national transit rider analyses.

Designing The Perfect Queue Line

This research paper examines the factors influencing rider satisfaction in theme park queue lines, with a focus on Disney World's Magic Kingdom. This study analyzes survey responses from 61 participants to investigate the relationship between queue quality and overall attraction quality, as well as the importance of various factors in queue selection. Results indicate that rider comfort is the most critical variable, followed by temperature/weather conditions and seating/shade availability. Factors such as interactive elements and nearby amenities were found to be less important. Attractions with higher overall ride ratings also received higher overall queue ratings, highlighting the strong correlation between queue and ride experiences. Thematic content analysis of open-ended responses revealed common themes, including the importance of comfort, theming, entertainment, and efficient loading in a perfect queue. Furthermore, the study emphasizes the significance of maintaining and improving queue elements such as climate control, interactive features, and accurate wait time signage. The findings suggest that prioritizing rider comfort, incorporating interactive and age-appropriate entertainment, and optimizing queue design for efficiency are crucial for enhancing visitor satisfaction. Future research directions include comparative studies across different theme parks and longitudinal studies to track changes in queue design and visitor satisfaction over time.

Using Twitter to Gauge Customer Satisfaction Response to a Major Transit Service Change in Calgary, Canada

Measuring public opinion about the quality of transit services is a key factor in understanding and addressing customer dissatisfaction and increasing customer loyalty and ridership. Sentiment analysis using social media—in particular Twitter—is a relatively cheap and potentially powerful complement to traditional survey methods, which are expensive and limited in sample size. This study aims to evaluate customer response to the introduction of Calgary Transit’s MAX routes. We compared customer satisfaction expressed on Twitter with measured service reliability in the form of on-time performance. We also employed a qualitative research approach using content analysis from Twitter to gauge rider satisfaction over several service attributes before and after the service change. A transit-specific sentiment lexicon was developed to support this study using a hybrid approach. This lexicon outperformed generic sentiment lexicons traditionally used in transit studies with regard to both accuracy (18.4%) and F1-score (7.1%). We found that the overall perception of on-time performance from riders using Twitter was similar to the actual performance in the field. This was also observed for one individual route on which stops with poor schedule adherence were linked with negative feedback. This study concludes that combining customer-oriented measures from Twitter with operational-oriented ones would enable transit agencies to make better-informed decisions for planning and operational purposes.

Untangling the Complex Relationships between Horse Welfare, Rider Safety, and Rider Satisfaction

ABSTRACT Securing the horse industry’s long-term future is becoming increasingly urgent due to community concerns for horse welfare; human behavior change may offer novel solutions to this challenging problem. Self-determination theory (SDT), a well-established theory in human behavior change, assumes humans are intrinsically motivated by three universal psychological needs: competence, autonomy, and relatedness. These align well with horse–human interaction. To explore the potential for human behavior change to improve horse welfare, this study investigated the relationship between horse welfare, rider safety, and rider satisfaction. An online survey asked equestrians about their horse-keeping and training practices, their riding accidents and injuries, and their level of satisfaction with their horse. Relative horse welfare and rider satisfaction were significantly related (r = 0.34, p < 0.001). Hyperreactive horse behavior (defined in this study as bucking, bolting, rearing, and spooking) and rider accidents and injuries were negatively related to rider satisfaction (r = −0.23, p < 0.001 and r = −0.16, p = 0.001, respectively). Further, goal achievement (r = 0.57, p < 0.001), rider control (r = 0.49, p < 0.001), and horse–human partnership (r = 0.62, p < 0.001) were all significantly related to rider satisfaction. A regression analysis testing the proposed SDT-based rider satisfaction model was significant (p < 0.001), with goal achievement, rider control, and horse–human partnership accounting for 63% of the variance of rider satisfaction scores. We found that horse welfare, rider safety, and rider satisfaction were related, with equestrian goal achievement (competence), horse control (autonomy), and horse-rider partnership (relatedness) all significantly contributing to rider satisfaction, suggesting that SDT may offer a useful framework for developing behavior change strategies. While more work is needed to develop and evaluate such strategies, a better understanding of intrinsic rider motivation represents an important first step.

Bit use and its relevance for rider safety, rider satisfaction and horse welfare in equestrian sport

Using a bit to communicate with and control the horse while riding is one of the longest standing traditions in horse riding. However, horses’ aversion to bits and high levels of bit-induced trauma have led some to question whether this practice is commensurate with modern understanding of animal welfare. This study represents one of the first attempts to compare horses ridden with and without a bit in terms of horse welfare, rider safety and rider satisfaction. Australian recreational and sport horse riders (n = 399, 94.4% female; Mdn age=46.0 years) from a range of riding disciplines were anonymously surveyed online. Only n = 20 (5.0%) participants reported riding without a bit, however, this is likely consistent with the recreational horse-riding population, given riding with a bit is mandated in most equestrian sports. A whole sample analysis and a case-matched analysis were performed where cases were matched based on horse breed and age, discipline, and rider age. Whole sample analyses found horses ridden without a bit have better relative welfare scores for management, and during riding and handling compared to horses ridden with a bit (Mdn 13.0, IQR 2.0 and Mdn 11.0, IQR 5.0; Mdn 35.0, IQR 9.0 and Mdn 32.0, IQR 6.0; and Mdn 24.0, IQR 3.25 and Mdn 23.0 IQR 4.0 respectively, p < 0.05), but did not differ in relation to health. Fewer ridden hyperreactive behaviours (bucking, spooking, rearing and bolting) were reported for bitless horses compared with bitted horses (Mdn 0.0, IQR 1.0 and Mdn 1.0, IQR 4.0, respectively, p = 0.04), however, rider safety and perceived control were similar for both groups. Riders of bitless horses were more satisfied than riders of bitted horses (Mdn 16.0, IQR 2.0 and Mdn 14.0, IQR 4.0, respectively, p = 0.01) and reported better horse-rider partnerships (Mdn 4.0, IQR 0.0 and Mdn 3.0, IQR 1.0, respectively, p < 0.001). More riders of bitless horses had knowledge of learning theory than riders of bitted horses (55.0% and 23.0% respectively, p = 0.003). Results from the case-matched analysis were consistent with the whole sample results, except for rider satisfaction and knowledge of learning theory which were not statistically significant. These findings suggest that bitless riding is not related to reduced horse control or rider safety, but is related to greater rider satisfaction and improved horse-rider partnership. Considering current challenges to the industry’s social licence to operate due to poor horse welfare, increased adoption of bitless riding may present a valuable opportunity to improve horse welfare.

Public transport service quality: Policy prioritization strategy in the importance-performance analysis and the three-factor theory frameworks

• A rigorous analytical framework was utilized to identify an appropriate service quality analysis method. • The three-factor theory was superior to the IPA due to the non-linear and asymmetric relations between service quality factors and rider satisfaction. • All the service factors were found to be performance factors for captive riders. • Eight of nine factors were performance for non-captive (vehicle-owned) riders, while environment friendliness was excitement. • This is the first study using the three-factor theory in Vietnam. Service quality is a determinant of increasing public transport rider satisfaction. However, understanding of service quality and satisfaction relations has been limited. This study seeks an appropriate method to demonstrate the nature of service quality-satisfaction relations. Thereby, research results can be methodologically, theoretically, and empirically defensible. The importance-performance analysis (IPA) and the three-factor theory, the most widely preferred for public transport service quality prioritization based on the importance of service factors to rider satisfaction, will be utilized. The study takes transit service in Ho Chi Minh City (HCMC), Vietnam, to demonstrate that the three-factor theory, which has been limitedly utilized despite being more advantageous and robust, is superior to the IPA. Although the extent to which the service quality factors affect satisfaction varied across rider segments, the types of service quality factors were found consistent. For example, captive riders considered all service factors as performance. Non-captive riders considered the environment factor as excitement. No basic factor was found across rider groups. This study contributes to the limited understanding of the non-linear and asymmetric relations between service quality and satisfaction of various rider groups, which is rarely found in transit service quality literature. Furthermore, it introduced a case study of Vietnamese urban transit services for the first time. It suggests that enhancing passenger information, rider care, and comfort are recommended as the most practical and economical measures in the short run. However, the city government should improve availability and accessibility to promote public transport ridership in the long run.

A Novel Transit Rider Satisfaction Metric: Rider Sentiments Measured from Online Social Media Data

The goal of this paper is to demonstrate the use of an innovative social media-based data source, Twitter, to evaluate transit rider satisfaction. Transit authorities have access to vast amounts of performance metrics that measure ridership, timeliness, efficiency, safety, cleanliness, and service, to name a few. These performance metrics, however, are generally one-sided; they represent the interests of the business and are not customer-based. This paper recognizes the limitations of standard performance metrics and attempts to gauge transit rider sentiments by measuring Twitter feeds. Sentiment analysis is used to classify a population of rider sentiments over a period of time. Conclusions are drawn from totals of positive and negative sentiments, normalized average sentiments, and the total number of Tweets collected over a time period.

Utah Transit Authority’s Connection Protection System: Perceptions of Riders and Operators

The effectiveness of the Utah Transit Authority’s (UTA) Connection Protection (CP) system was evaluated from the perspective of riders and operators. The CP system was installed to improve the reliability of transfers from higher frequency light rail TRAX trains to lower frequency bus services. The evaluation determined that overall satisfaction among riders with their connection experience was generally high, but operator opinion on the value of CP was mixed. The level of reported rider satisfaction was only weakly related to whether the bus trip was CP protected, and bus operators reported receiving a high number of unnecessary CP messages. Several factors were considered to have affected the results of the evaluation, including CP malfunction during the survey, low operator compliance for “hold until” messages, and the existence of inaccurate “hold until” messages. The qualitative evaluation findings gave rise to a number of suggestions for how the CP system could be improved.

Gender differences in the user satisfaction and service quality improvement priority of public transit bus system in Porto Alegre and Fortaleza, Brazil

Previous studies have shown that the rider satisfaction on bus services vary between males and females. As women make a significant number of transit trips in developing countries nowadays, it is crucial to understand their perceptions and satisfactions towards different service aspects of public transit, thus to provide transit agencies with the gender-differentiated policy suggestions. In this study, we use the QualiÔnibus rider satisfaction survey data in two Brazilian cities: Porto Alegre and Fortaleza, to examine the differences between male and female in their ratings of various transit service attributes, and their perceptions of the relative importance of different service attributes on riders’ overall satisfaction, and based on which detect the high priority service attributes to act on for each gender. The random forest method is applied to determine the attribute importance, which captures both the non-linear and asymmetry influences of the service attributes on riders’ overall satisfaction. Our findings show that the gender difference exists in terms of both the importance type and the improvement priority of the attributes. Specifically, women are associated with higher improvement priorities regarding “speed”, “customer service”, “security”, “exposure to noise and pollution” and “customer information” in Porto Alegre, and regarding “access to transport”, “customer information”, “easiness to transfer”, “comfort at integration terminals” and “speed” in Fortaleza. Our findings illustrate the effectiveness of using our methods to distinguish different importance types of service attributes between different genders, which could help the transit agency develop gender-oriented actions regarding service improvements.

User satisfaction and service quality improvement priority of bus rapid transit in Belo Horizonte, Brazil

The implementation of Bus Rapid Transit (BRT) is intended to provide higher-quality services and significantly improve rider satisfaction. Previous studies have investigated rider satisfaction and its determinants to improve BRT services as well as the comparison between BRT and conventional bus/rail transit regarding the rider satisfaction. However, many of previous studies have assumed that service attributes have linear and symmetric influences on rider satisfaction, and among the very few studies that capture the non-linear or asymmetric relationship, there is no combination of different methods to achieve the advantages of both. Besides, to our knowledge, no previous studies have examined changes in the performance and importance of different service attributes after BRT implementation. This paper analyzes the QualiÔnibus rider satisfaction survey data in Belo Horizonte, Brazil, and compares rider satisfaction and the importance of service attributes to overall satisfaction across three cases: two years prior to the BRT implementation, one year after the BRT was implemented, and four years after the BRT implementation. A combination of the ordinal logit regression (OLR) approach and random forest (RF) approach is adopted, which enables a nonlinear relationship between service attributes and rider satisfaction, considers the impact effect size in determining the importance of service attributes, and captures the attitudinal randomness of different riders when rating their satisfaction. Our results show that “expenses with public transport” (i.e. fares) should be addressed first among all the attributes, and the improvement priorities of “speed”, “reliability” and “customer service” increased after the BRT opening. These findings can help policymakers fine-tune improvement strategies targeted at different types of services.

Listen to E-scooter riders: Mining rider satisfaction factors from app store reviews

Abstract In this study, app store reviews from two major micromobility companies are investigated using machine learning techniques to identify the factors that influence rider satisfaction. The Latent Dirichlet Allocation model is applied to over 12,000 rider-generated reviews to identify twelve topics discussed within the reviews. These topics cover areas such as pricing, safety, customer service, map, refund, payment, app interface, and ease of use, to name a few. Using logistic regression, the most significant factors influencing rider satisfaction were identified. Moreover, name-centered gender prediction analysis is employed to identify rider gender and then discover differences in review content and factors of satisfaction across gender. Results suggest rider satisfaction levels tend to vary across topics and gender. Women were more satisfied with the services and exhibited more positive sentiment than men. Yet, scooter is still a male dominated mode of transportation. Findings contribute to the existing literature by demonstrating the use of app store reviews in a transportation mobility study. The development of a method to assess factors contributing to rider satisfaction offers the ability to evaluate e-scooter rider needs and barriers. An apparent policy opportunity to increase scooter ridership includes an emphasis on contributing factors such as ease of use, safety (speed and riding lane), as well as app issues that showed significant influence on user satisfaction. It is recommended that a policy approach focused on improving rider satisfaction and delivering service improvements incorporate opinion mining as a methodology.

Exploring satisfaction of choice and captive bus riders: An impact asymmetry analysis

The literature offers ample evidence on the associations between transit attributes and rider satisfaction. However, their asymmetric relationships are often overlooked. Few studies emphasize the attributes critical to choice and captive riders in developing countries. This study employs an impact asymmetry analysis to explore the correlates of bus satisfaction of choice and captive riders in Harbin, China. Most service attributes have asymmetric associations with overall satisfaction of both choice and captive riders. The waiting area, driver’s operating behavior, complaint handling, and stop announcement are critical to overall satisfaction of both choice and captive riders. However, planners should know that, because of the asymmetricity, planning goals differ when trying to satisfy choice and captive riders. Furthermore, they should emphasize convenience and comfort to satisfy captive riders and focus on bus availability to incentivize choice riders. Future studies should consider the non-linear associations and investigate the varying needs of different population groups.

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.

Exploring the asymmetric influences of stop attributes on rider satisfaction with bus stops

Bus stop is an essential component for transit trips. Few studies have emphasized how stop amenities contribute to rider satisfaction with the waiting environment. Using the 2019 data from Harbin, China, this study employed asymmetric importance-performance analysis to identify the non-linear associations between stop amenities and rider satisfaction with the waiting area. We found that trashcans, comfort while waiting, and security cameras affect rider satisfaction only when they perform poorly; safety while waiting contributes to satisfaction only when it exceeds rider expectation; while other attributes tested here have linear associations with rider satisfaction. The results further showed that, to enhance rider satisfaction, transit agencies should prioritize improving trashcans and comfort while waiting, followed by shelters, advertisement infrastructure, and benches. We also compared these results with conventional importance-performance analysis and highlighted the importance of asymmetricity in transit satisfaction research.

Exploring rider satisfaction with arterial BRT: An application of impact asymmetry analysis

Previous studies focus on rider satisfaction and its determinants to improve transit ridership. However, many incorrectly assume that service attributes have linear and symmetric influences on rider satisfaction. To overcome the limitation, this study employs an impact asymmetry analysis to explore the non-linear influence of service attributes on rider satisfaction with an arterial BRT in the Twin Cities, Minnesota. The results show that most service attributes have a non-linear influence on rider satisfaction, and that “paying fare is easy” has the largest contribution to overall satisfaction, followed by “hours of operation” and “handling of concerns/complaints.” Overall, this study introduces a more reliable and salient method to the field of transit quality of service to reveal the nuanced relationships between service attributes and rider satisfaction.

Relating Pavement Condition Index and Present Serviceability Rating for Asphalt-Surfaced Pavements

In response to the two latest transportation funding authorization bills, the Moving Ahead for Progress in the 21st Century Act and the Fixing America’s Surface Transportation Act, rules that require the reporting of specific pavement condition measures have been developed and encoded into federal regulation. Pavement performance rules published to the federal register require the reporting of the International Roughness Index (IRI), percent cracking, rutting (for asphalt-surfaced pavements) and faulting (for jointed concrete pavements). Allowing that the measurement of the IRI on pavements with a speed limit below 40 mph is not expected to provide a reliable estimation of ride quality, the rules permit the reporting of the present serviceability rating (PSR) on these routes. However, many agencies do not measure the PSR or collect the slope variance data required to estimate the PSR. In light of not having the data required to directly estimate the PSR, this paper presents a model to estimate the PSR using data collected during a Pavement Condition Index (PCI) survey. Furthermore, this paper explores the reasons why pavements can have a good PCI and poor PSR and vice versa. The model presented in this paper provides a reasonable estimate of the PSR, though it is noted that agencies who wish to report PSR should conduct an updated assessment of rider satisfaction to develop a stronger correlation of PSR and PCI.

Exploring rider satisfaction with transit service in Indore, India: an application of the three-factor theory

This study introduces the three-factor theory to identify a factor structure of tranist service. It classifies service attributes into basic, perfomance,and excitement factors according to their importance to overall satisfaction with transits then identifies improvement priorities. Using a 2013 survey of Bus, Bus Rapid Transit (BRT) and Van riders in Indore, India, this study intends to draw implications for transit planning by answering following questions: What service attributes are critical for customer satisfaction with BRT, Bus and Van?What attributes should be prioritized to improve satisfaction with existing transit services in Indore? Are the answers to the two questions consistent across the three types of transit? We found that across all three types of transit, comfort while riding and safety while waiting are two common basic factors and safety while riding is a common key performance factor. Furthermore, several Van atttributes require extensive improvements while BRT need the least improvements.