Barriers and Benefits: Understanding Riders’ Views on Pooled Rideshare in the U.S.

Abstract

This manuscript provides actionable recommendations to enhance user satisfaction and address existing barriers regarding pooled rideshare (PR) in the United States. Despite PR’s intended benefits, such as reduced traffic congestion and cost savings, its adoption remains limited. To identify these actionable items, a U.S. nationwide survey with 5385 participants explored transportation preferences, barriers, and motivators for PR use in the summer of 2021. First, two factor analyses were conducted. The first factor analysis identified the five factors associated with one’s willingness to consider PR (time/cost, traffic/environment, safety, privacy, and service experience). The second factor analysis revealed the four factors related to ways to optimize one’s PR experience (comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety). Privacy concerns, for instance, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. A structural equation model evaluated the relationships among these nine key factors influencing PR usage to develop the Pooled Rideshare Acceptance Model (PRAM). The privacy, safety, trust service, and convenience factors each had a significant large effect (Cohen’s f² > 0.35) on the model. PRAM was extended using multigroup analyses to reveal the nuanced impact of 16 demographics, including gender, generation, rideshare experience, etc., highlighting the need for tailored strategies to improve PR acceptance through the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Multiple workshops were held with diverse audiences to translate the team’s findings to date into 84 actionable recommendations, categorized across topical areas like safety, routing, driver and passenger selection, user education, etc. These findings are a foundation for a future study to determine which items resonate with different user groups. In the meantime, the actional items serve as a user-driven resource for policymakers, transportation network companies, and researchers, offering a roadmap to potential improvements to PR services to address existing concerns with the goal of increasing the usage of PR.

1. Introduction

Transportation in the United States is a complex and evolving system that offers a variety of modes, including personal vehicles, public transit, carpooling, biking, and walking [1]. Despite the growing availability of alternative forms of transportation, personal vehicles remain the dominant mode of transportation, with 76% of Americans commuting alone to work [2]. This reliance on personal vehicles contributes to traffic congestion, environmental concerns, and limited accessibility for underserved populations. In response, mobility solutions have emerged, with transportation network companies (TNCs) such as Uber and Lyft reshaping many transportation landscapes [3,4,5,6].

TNCs have introduced ridesharing as a flexible and convenient option, leveraging advancements in technology to match passengers with drivers [7,8]. Ridesharing is generally categorized into two forms, namely personal rideshare, where individuals travel alone or where groups travel with companions they know, or pooled rideshare (PR), which matches riders with people they do not know who are traveling along similar routes. While personal rideshare offers more privacy and direct routes, pooled rideshare has the potential to provide broader societal benefits by reducing traffic congestion, lowering costs for riders, and supporting environmental sustainability [9,10,11]. Several studies have shown that time and cost are critical factors influencing users’ decisions to adopt ridesharing. For example, Hansen and Sener [12] reported that ridesharing is more likely to be considered by lower-income public transit users, while Waerden et al. [13] emphasized that cost and time are the two primary reasons for ridesharing acceptance. Hsieh [14] categorizes ridesharing benefits into financial, social, and accessibility incentives, enhancing convenience, trust, and financial benefits for users. Additionally, PR usage can offer greater flexibility and convenience compared to other shared mobility options like public transportation [15,16], which often involve constraints such as fixed schedules and the need to walk to designated bus stops, subways, or transit centers. However, PR adoption remains limited, with significant barriers such as safety concerns, privacy issues, and increased travel time cited by users [17,18,19,20,21,22,23,24].

The history of ridesharing in the U.S. offers valuable context for understanding its current challenges and opportunities. Ridesharing originated during World War I with jitney services—unregulated taxi-like services that offered affordable and flexible transportation but faced safety and regulatory challenges [25]. Subsequent periods of increased ridesharing during World War II and the 1970s oil crises were driven by resource conservation and economic necessity. However, the widespread availability of personal vehicles and declining fuel prices led to diminished interest in ridesharing by the 1990s [26]. The resurgence of ridesharing in the 21st century has been fueled by advancements in technology, including the proliferation of smartphones, GPSs, and real-time data systems. These innovations have enabled TNCs like Uber and Lyft to create efficient app-based platforms that integrate ride-matching algorithms, dynamic pricing, and seamless user experiences [27,28].

Pooled ridesharing represents a significant evolution in the transportation landscape, offering a model where riders share trips with others, potentially reducing the number of vehicles on the road and fostering environmental benefits. Uber Pool and Lyft Shared, introduced in 2014, popularized this concept, achieving initial success in urban markets such as San Francisco, Chicago, and New York City [29,30,31,32]. PR offers an efficient solution for reducing traffic congestion by consolidating multiple passengers into a single ride. PR offers more affordable transportation options, potentially benefiting passengers from diverse socioeconomic backgrounds by reducing trip costs [33,34,35,36]. However, challenges persist. Riders often cite concerns about traveling with strangers, increased travel time due to additional pick-ups and drop-offs, and perceived inadequacies in safety and privacy measures [37,38,39,40]. These barriers highlight the need for targeted interventions that address user concerns.

Advancements in technology have played a pivotal role in overcoming some of these challenges. Dynamic ride-matching algorithms, real-time GPS tracking, and robust user-rating systems have improved the reliability and safety of rideshare platforms [41]. Additionally, features such as pre-screening riders and integrating electric and autonomous vehicles into PR fleets offer promising avenues for enhancing user experiences and sustainability outcomes [42,43,44]. Despite these advancements, they are primarily technology-driven; achieving the widespread acceptance of PR requires a deeper understanding of user preferences, barriers, and motivators from a human factors perspective. To gain a deeper understanding of the ridesharing literature, consider reviewing the development of the Pooled Rideshare Acceptance Model (PRAM) [45,46,47].

Study Goals

This manuscript aims to synthesize the results of a series of studies conducted, providing a cohesive narrative that traces the evolution of our team’s PR research from descriptive analyses to the development of predictive models for a U.S. sample. The purpose of this body of work was to explore the reasons why individuals may be hesitant to use PR. Prior research, described below, addressed time and cost, which are used in transportation modeling. Safety, privacy, and trust have previously been explored, but our team was interested in understanding the complex relationship between the nuances of such topics combined with demographic variables such as age, gender, number of children, etc. Building on this foundation, this manuscript combines all prior results to develop actionable recommendations that align with user preferences and address existing barriers.

The goal of these studies is to offer actionable insights for policymakers, TNCs, and researchers, enabling each group to design services that align with user preferences to overcome barriers yet to be addressed to allow for a broad-scale adoption of PR. By addressing the diverse concerns of different user groups, this effort seeks to promote the broader acceptance and sustained growth of pooled ridesharing in the U.S., contributing to a more sustainable and equitable transportation ecosystem. The following sections detail the survey development, findings, and implications of the research, providing a comprehensive roadmap for advancing PR adoption in the U.S.

2. Nationwide Survey on Topics That Impact One’s Willingness to Use PR

2.1. Overview of Methodology and Framework

To provide a comprehensive understanding of PR adoption, this study employed a rigorous methodology combining quantitative and qualitative approaches, as shown in Figure 1. This manuscript builds upon a comprehensive series of research efforts to identify factors influencing PR adoption and develop potential actionable strategies to increase user acceptance. Central to this research, a nationwide survey (N = 5385) provided demographic, geographic, and experiential variables which shape PR usage. The national survey allowed for detailed analyses, beginning with verbatim responses that highlighted users concerns, followed by descriptive statistics that revealed demographic trends and usage patterns, leading to two factor analyses that identified key factors focusing on reasons why a potential user may or may not be willing to consider PR, followed by an analysis on methods to optimize a riders’ PR experience [46,47].

To analyze these factors systematically, the Pooled Rideshare Acceptance Model (PRAM) was developed using structural equation modeling (SEM). The PRAM integrates user perceptions of privacy, safety, convenience, and other critical factors to predict PR acceptance. The PRAM leverages SEM to quantify the relationships between these factors, offering a robust framework for understanding user decision-making [45]. However, the PRAM does not account for the nuanced impacts of demographic variables such as gender, age, or previous rideshare experience. To address this gap, the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs) were developed, extending the PRAM to include 16 demographic moderators and exploring their influence on PR adoption [48]. The findings from the PRAM and PRAMMAs underscored the need for a tailored approach to promoting PR services. For instance, gender-specific safety concerns, generational differences in technology adoption, and income-related cost sensitivities emerged as critical considerations. These insights highlight the inadequacy of a “one-size-fits-all” strategy and emphasize the importance of personalized interventions to address diverse user needs.

The study outcomes were further refined through workshops with diverse audiences, synthesizing statistical findings into actionable recommendations and ensuring they were data-driven and user-centered. By integrating survey findings with advanced analytical methods and stakeholder input, this research offers a practical roadmap for policymakers, transportation network companies (TNCs), and researchers aiming to promote sustainable and user-friendly PR services in the U.S.

2.2. Survey Development and Deployment

The development of the nationwide survey on topics impacting the adoption of pooled rideshare was based on a comprehensive literature review and collaborative input from industry and governmental experts. Key insights were drawn from three primary areas, namely the history and classifications of ridesharing, particularly pooled ridesharing; reports from the U.S. Department of Energy (DOE) and Department of Transportation (DOT) detailing shared mobility trends and challenges; and existing surveys examining ridesharing behaviors and preferences. These resources informed the categorization of critical topics for further exploration, laying the groundwork for a focused and effective survey design, as shown in Figure 2. Collaboration with J.D. Power, a globally recognized leader in survey data and analytics, brought valuable expertise to the project. J.D. Power’s prior experience with similar studies and access to relevant mobility reports allowed for iterative refinements that ensured the survey’s alignment with research objectives and the incorporation of best practices in survey methodology. The resulting survey was designed to capture a diverse range of perspectives on PR usage.

The survey, conducted from July 2021 to August 2021, included a sample of 5385 participants. This sample comprised 2000 respondents from a nationwide pool and approximately 500 participants from each of the following six urban areas: Atlanta, Austin, Chicago, Detroit, New York City, and San Francisco. An additional 384 participants were recruited from Upstate South Carolina. Eligibility criteria required participants to be at least 18 years old and to have rideshare experience within the past five years. Participants self-reported their experiences, choosing from options such as having ridden alone or with people they know, having shared rides with people they did not know, or having driven for a rideshare company. Individuals who exclusively identified as rideshare drivers were excluded, narrowing the study’s focus to riders’ experiences and perspectives.

The survey was structured into four sections designed to explore different aspects of rideshare usage, as seen in Figure 2. The first section, “Your Transportation Needs”, gathered information on participants’ primary transportation methods and motivations for their choices. The second section, “Willingness to Consider PR”, examined the importance of items influencing participants’ decisions to consider pooled ridesharing. These responses were captured on a four-point Likert scale ranging from “Not at all important” to “Very important”. The third section, “Optimizing PR experience”, focused on participants’ willingness to use pooled rideshare in the future, with items addressing user-centered design and services. Responses were recorded on a four-point scale from “Strongly disagree” to “Strongly agree”. The final section obtained information regarding the respondent’s demographics.

The rigorous design and deployment of the survey enabled a detailed exploration of user preferences, barriers, and motivators related to pooled ridesharing. By incorporating diverse demographic, geographic, and experiential variables, the study positioned itself as a valuable resource for understanding and addressing the complexities of PR adoption in the U.S.

2.3. Preliminary Descriptive Insights on Survey Respondents

The participants’ ages ranged from 18 to 95 years, with a mean age of 46.5 years. Age distribution was grouped into generations and organized into five categories, where Gen Z (ages 18–26) accounted for 16.6% of the sample nationally, Gen Y (ages 27–44) represented 30.7%, Gen X (ages 45–56) made up 21.2%, Boomers (ages 57–75) constituted 26.8%, and Pre-Boomers (more than 75 years) accounted for 4.7%. The gender distribution was relatively balanced, with 52.1% female, 47.3% male, 0.3% self-described, and 0.4% unspecified respondents. This demographic representation suggests a comprehensive understanding of the population segments engaged in rideshare services.

When asked about rideshare experience over the past five years, participants were able to select all options that applied; 43.3% of all participants had no rideshare experience. Over half, 51.4%, reported having personal rideshare experience, while 15.6% of all participants had pooled rideshare experience. Prior to answering any specific questions about rideshare, when asked about the participants’ willingness to consider PR in the future, 41% were willing to consider it, 44% were not willing, and 15% were not sure about using PR services in the future. This variation with rideshare familiarity highlights diverse user perspectives, forming the justification for further exploration into factors influencing PR adoption.

2.4. Insights from Verbatim Responses

When participants responded to their willingness to use PR, the follow-up open-ended/verbatim responses provided valuable insights into the top reasons for hesitancy or uncertainty regarding pooled rideshare (PR) usage. Among those not willing to use PR (N = 2352), the most frequently cited concern was discomfort and lack of trust due to riding with strangers, accounting for 34% of responses, as shown in Figure 3. This was followed by a perceived lack of need for PR services (20%), concerns related to COVID-19 (17%), safety apprehensions (14%), and a preference for using personal vehicles (12%). Similarly, among respondents who were uncertain or did not know about using PR (N = 826), 25% cited strangers and trust issues, while 19% expressed COVID-19 concerns. Additionally, 12% of this group indicated they lacked experience with PR or were unsure of what to expect. These findings underscore key barriers to PR adoption, including trust, safety, and familiarity, highlighting critical areas for targeted interventions to address user apprehensions and build confidence in PR services.

2.5. Understanding Transportation Choices and Ridesharing Motivations

The first section of the survey, “Your Transportation Needs”, provided valuable insights into respondents’ transportation preferences and the factors influencing their use of ridesharing services (see Figure 4). Among the respondents, personal vehicles were the dominant mode of transportation, utilized by 80.7% of participants. Walking or biking followed at 34.4%, reflecting a notable preference for active transportation. Public transportation was used by 20.6%, while 22.2% of respondents reported using personal rideshare services like Uber or Lyft. In contrast, pooled rideshare services were used by 5.8%, indicating a dramatically lower adoption rate. Other transportation modes, such as carpooling (11.9%), car-sharing services (9.2%), and micro-mobility options like e-scooters and e-bikes (4.3%), were also used. Telecommuting accounted for 10.1% of responses, underscoring the shift toward remote work.

Those who chose PR as one of their transportation choices (N = 314) highlighted diverse reasons for using PR services (see Figure 4), with social and recreational activities leading at 55.1%. Work-related commutes followed at 44.3%, closely matched by airport transportation at 42%. Personal travel or vacation (40.1%), vehicle maintenance (39.2%), and shopping or errands (36.9%) also emerged as common motivations for using PR. Regarding the reasons for choosing PR service (N = 314), convenience was the primary reason (see Figure 4), cited by 51.9% of respondents who found it beneficial in situations like inclement weather or challenging parking. Cost-effectiveness (45.9%) and quicker travel times (39.2%) were also influential reasons. Additionally, 38.2% of participants valued the reduced stress associated with PR, while 36.9% appreciated the ability to multitask during their journey. A notable 30.6% of respondents used PR as a preferred alternative when they were unwilling to drive, such as in the case of intoxication.

These findings highlight the diverse motivations behind transportation choices and the varying roles PR plays to meet travel needs. The findings also underscore the relatively low adoption of pooled rideshare services, suggesting an opportunity to address barriers and better position PR services to compete with personal vehicles and traditional ridesharing options. After analyzing the participants’ transportation choices, next, a more detailed statistical analysis conducted on users’ willingness to consider PR will be provided.

2.6. Factor Analyses from Nationwide Survey

Based on the results from 5385 survey respondents, the two factor analyses were conducted, including the willingness to consider PR factors (see the second column of questions in Figure 4) and optimizing one’s PR experiences (see the third column of questions in Figure 4).

In the first factor analysis, Su et al. [46] used exploratory and confirmatory factor analyses to identify key factors that influence passengers’ willingness or reluctance to consider using pooled ridesharing (PR) in the future. In order of their higher percentage of explaining total variance in factor analysis, the five higher-order factors identified to be critical to determining one’s willingness to consider PR include safety (20%), service experience (16%), time/cost (11%), traffic/environment (8%), and privacy (4%). Further analyses using binomial logistic regression revealed that service experience, traffic/environment, and time/cost positively influenced passengers’ willingness to consider PR. Service experience had the most significant impact, increasing the likelihood of willingness to use PR by 185.1%, followed by traffic/environment at 45.7% and time/cost at 29.3%. However, privacy emerged as a major concern, reducing one’s likelihood of being willing to consider PR by 76.7%. Interestingly, the safety factor did not differentiate between those willing and unwilling to use PR, suggesting that safety concerns are universally relevant regardless of passengers’ stance on PR. Additionally, for the time/cost factor, the items related to time had higher factor loadings than items related to cost.

• The key takeaways are as follows:

• Safety is important. Ensuring passenger safety is crucial, as it fosters higher trust and can significantly increase the adoption of PR.

• Time is more important than cost when considering PR, indicating that passengers prioritize the efficiency of their trips over potential savings.

• Privacy concerns can negatively impact the willingness to consider PR, as individual preferences and comparisons with other transportation modes play a key role in shaping this perception.

In the second factor analysis, Gangadharaiah et al. [47] identified four key factors that significantly impact passengers’ decisions in user-centered designs and service-related needs in PR services. In order of their higher percentage of explaining total variance in factor analysis, the four higher-order factors identified to be critical to determining one’s optimal PR experience include comfort/ease of use (26%), convenience (19%), vehicle technology/accessibility (11%), and passenger safety (8%). These factors play a pivotal role in shaping the overall user experience and influencing PR usage. Further analysis using binomial logistic regression showed that comfort/ease of use decreased the likelihood of willingness to use PR by 16%, while vehicle technology/accessibility and convenience increased it by 201.6% and 156.2%, underscoring the importance of reliable service. However, passenger safety reduced the likelihood of willingness by 46.8%, indicating that safety remains a major concern for potential users.

• The key takeaways are as follows:

• Users strongly desire a personalized and comfortable experience.

• Affordability, transparency in ride details, and minimal detours are top priorities for users.

• Hygiene and safety assurances are highly valued, particularly in the context of the post-COVID-19 environment.

It is evident that users’ willingness to consider PR depends on multiple multi-faceted factors rather than a few topics, e.g., time, cost, safety, and privacy. Analyzing and understanding these individual factors is crucial, but the question arises of how these separate analyses unite to form a comprehensive framework of the user acceptance of PR services. Given the relevance of these factors in users’ PR decision-making preferences, the following study incorporated these nine factors to evaluate perceptions and preferences regarding pooled ridesharing. Building on this assessment, a comprehensive framework was developed to better understand the user acceptance of PR.

2.7. Pooled Rideshare Acceptance Model (PRAM)

After identifying the most important factors influencing users’ willingness to use PR, a comprehensive analysis was conducted to understand how these factors interact and shape decision-making. Inspired by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), Gangadharaiah et al. [45] developed the Pooled Rideshare Acceptance Model (PRAM) using structural equation modeling (SEM) to evaluate the relationships among all nine identified factors, users’ trust in the service, their willingness and attitude toward PR, and overall user acceptance.

The model revealed that privacy, safety, trust in the service, and convenience significantly (Cohen’s f² > 0.35) impacted user acceptance, highlighting their crucial role in passengers’ decisions to use PR, as shown in Figure 5. The results demonstrated that passengers appreciate privacy and security when traveling with unknown people, desire stronger trust in TNC services, and prioritize features that improve the convenience of their ride. After constructing the PRAM, the next study further explored how demographic variables influence the relationships within this framework, providing deeper insights into user preferences and the acceptance of pooled ridesharing.

• The key takeaways are as follows:

• Lack of privacy, safety, and service experience were deterring factors.

• Users prioritize privacy and safety, which strongly influence their attitudes toward PR.

• Convenience greatly positively influenced the acceptance of PR.

• Trust in the PR service is crucial to have a positive attitude and acceptance.

• Safety improvement features, ride information, service transparency, and user communication greatly influenced PR acceptance.

• Traffic and environmental concerns moderately influenced PR acceptance.

• Although time and cost were not significant on their own, they became important when linked to overall convenience.

• Once safety concerns are addressed and services are perceived as convenient, time and cost become key factors in building trust in PR.

• Convenient services that save time, offer cost benefits, and provide service transparency can significantly improve user confidence in using PR.

While the PRAM provided a comprehensive understanding of user acceptance factors, it did not account for the potential influence of moderators such as age, gender, geographical location, or previous rideshare experience. Understanding these moderators is essential because they may highlight how different segments of the population might perceive and accept PR differently. In the PRAM, moderators may affect the strength of the relationship between factors, attitudes toward PR, and/or user acceptance of PR. To bridge this gap, the following study incorporated a multigroup analysis using the same data from the national survey. By understanding the impact of these potential moderators, the study can provide a more nuanced perspective on rideshare acceptance and point toward specific interventions tailored to different population segments.

2.8. Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs)

Different demographic variables can affect a person’s willingness to use pooled rideshare services. Gangadharaiah et al. [48] conducted multigroup analyses to establish the demographics that could impact PR usage decisions. The analyses focused on 16 demographics (see Table 1), including gender, generation, geographic area, whether they held a driver’s license, whether they had previous pooled ridesharing experience, education level, employment status, the number of people in their household, their number of children, household annual income, their number of owned vehicles, and the transportation they used to commute (personal vehicle, public transportation, walk/bike, telecommute, and carpool).

The Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs) examined how various demographic factors influence users’ willingness to use PR. PRAMMAs revealed significant variations in user preferences based on these demographics, as seen in Figure 6. For gender, female participants emphasized privacy and safety more, often viewing these concerns as barriers to PR adoption. Generational differences showed that younger users prioritized convenience and environmental impact, while older users focused more on trust and service reliability. Geographic location (urban, suburban, or rural) did not significantly influence the relationship between key factors, suggesting consistency in perceptions across regions. Users with a driver’s license were more concerned about safety, while those without a license focused more on traffic and environmental issues. Rideshare experience also played an important role. Participants with prior experience were more trusting of PR services, while those without were more concerned about privacy. Higher education levels and employment status were associated with fewer privacy concerns, especially among employed individuals.

Household size influenced trust, with larger households emphasizing service reliability, while income level and vehicle ownership showed that wealthier individuals with more vehicles had higher safety expectations. Lastly, commuting preferences revealed that users of personal vehicles required a higher level of trust in PR services. In contrast, non-vehicle users were more open to PR adoption provided their privacy concerns were addressed. These findings emphasize the opportunity for rideshare companies to customize services based on user demographics to increase acceptance.

The multigroup analyses suggest that addressing the unique concerns and preferences of different user groups is crucial compared to a “one size fits all” approach, which may not be effective. Addressing the distinct needs of these groups may significantly enhance the acceptance and usage of PR.

Figure 7 summarizes the results of the PRAMMAs, categorizing different groups based on the moderating factors significantly influencing their likelihood of using PR. Some groups are most likely to use PR due to its potential to reduce traffic congestion and improve the environment, as well as their positive attitude toward PR and when trust in the service is established. The PRAMMAs also highlight groups that have reservations about using PR, primarily due to concerns over privacy, safety, and inadequate service experience compared to other transportation options. Finally, the PRAMMAs identify a category of users who may consider utilizing PR if their specific needs and requirements are met.

• The key takeaways are as follows:

• Gender, generation, and income strongly influence PR adoption, with each group having distinct concerns.

• Privacy and safety are key barriers for women and first-time users, requiring targeted solutions.

• Trust and service reliability are critical factors for all users, especially older generations and frequent riders.

• Younger and eco-conscious users are more likely to adopt PR for its traffic and environmental benefits.

• A one-size-fits-all approach is insufficient. Customized approaches are needed to address the unique needs of different user groups and improve PR usage.

• Convenience, comfort, and passenger safety features were important to all and showed no significant variation by moderators.

Next, the transition from a deep dive into the data to a series of workshops bridged the statistical insights with real-world perspectives, enabling the creation of actionable recommendations tailored to diverse user needs and preferences.

3. Insights and Outcomes from Workshops

These analyses provide valuable insights into the factors influencing PR acceptance and lay the groundwork for future research and policy development. Leveraging a large national sample that included participants with and without prior PR experience allowed for rigorous statistical analyses, offering findings that can guide policymakers, rideshare companies, and researchers in improving PR usage and user satisfaction in the U.S. After the statistical analyses were complete, workshops were conducted using descriptive statistics to guide the development of actionable items.

The initial workshop involved members of the broader research team to determine if a workshop method could be effective and to assess if a poster was an appropriate method to present the summary statistics to the audience followed by two rounds of subsequent workshops with over a dozen undergraduate and graduate students interested in human factors and automotive engineering. They all analyzed the descriptive statistics to guide the development of actionable items. Five posters were used to present descriptive statistics across different demographic perspectives, including poster 1: the entire survey sample; poster 2: comparisons of those with and without PR experience; poster 3: PR usage frequency; poster 4: willingness to consider PR; and poster 5: the likelihood of using PR after addressing user concerns. These workshops played a crucial role in refining the insights and shaping the development of actionable insights to guide future research. Some of the highlighted insights of each poster are described below.

3.1. Insights from Poster 1: All Individuals

• Enhance and communicate safety measures: focus on implementing robust safety checks and privacy features and educate female users about services to build trust and safety concerns.

• Customized marketing strategies: develop marketing initiatives tailored to different demographics, emphasizing convenience for younger users, family cost-effectiveness, and luxury options for higher-income users.

• Optimize convenience and efficiency: improve routing algorithms to reduce wait times and ensure quicker, more convenient pick-up and drop-off experiences.

• Diverse service options: offer a range of PR services catering to different needs—including family-friendly, premium, and social.

• Targeted outreach and incentives: utilize demographic insights to create targeted marketing campaigns and incentives and encourage trials for hesitant users, especially those new to PR and/or without personal vehicles.

• Partnerships and event-focused services: collaborate with event organizers and venues to provide dedicated PR services, making it the preferred choice for transportation to social and recreational events.

3.2. Insights from Poster 2: Individuals with and Without PR Experience

3.2.1. Riders with Previous PR Experience

• Show greater importance of trust in the drivers and a more significant focus on safety and service experiences.

• More likely to use PR due to convenience, multitasking ability, and cost-effectiveness.

• Tend to prefer privacy but are more open to the social aspects of PR compared to non-experienced users.

3.2.2. Potential Riders Without Prior PR Experience

• These potential customers value trust in drivers across demographics but are less inclined to use PR due to a lack of familiarity and comfort with the service.

• Express less interest in the social aspects of PR.

• Show interest in cleanliness, pre-screened passengers, and accurate ride information, indicating that improved service transparency and safety assurances could lower barriers to use.

3.3. Insights from Poster 3: Frequency of PR Usage (Multiple Times a Day, a Few Times a Week, a Few Times a Month vs. Rarely)

• Individuals who use PR services more frequently value reliability and time-saving features. They are more likely to appreciate the service’s convenience and are open to advanced technologies.

• Infrequent users (a few times a month, rarely) express more conditional willingness to use PR services. If their specific needs, especially regarding safety, convenience, and cost, are met, they may be more likely to consider PR as an option.

• Social and recreational uses dominate among reasons for PR, especially among younger users and those who use PR infrequently. This suggests that marketing strategies could focus on PR as a safe, convenient option for nights out, business travel, or events.

3.4. Insights from Poster 4: Individuals Who Would vs. Would Not Consider PR

• Common concerns: trust in drivers and passengers, ease of use of the rideshare service app, wait time, reliability, cost-effectiveness, and desire for privacy are pivotal factors influencing PR consideration across different groups.

• Safety and privacy: Safety concerns are more pronounced among females, and suggestions for female passengers to utilize female drivers to increase comfort are common. The desire for privacy and the comfort of traveling alone is common, yet there is an interest in socializing opportunities, especially among younger generations.

• PR is mainly utilized for social/recreational activities, airport transit, and commuting. The attraction lies in its convenience, affordability, and time efficiency.

• Higher-income individuals prioritize convenience and multitasking, indicating a targeted approach for marketing PR services could be effective.

• Clear, accurate information pre-booking and cleanliness standards are highlighted as essential for optimizing user experience.

3.5. Insights from Poster 5: Likelihood to Use PR After All Concerns Addressed (Definitely Will Not, Probably Will Not, Probably Will vs. Definitely Will)

• Trust in the driver and passengers is fundamental across demographics.

• Clear and upfront information about the ride, including cost, route, and estimated time, is crucial for all users, particularly first-time users.

• Individuals with previous rideshare experience are more open to PR.

• Families, especially those with children, show varied interest in PR based on their specific needs, such as commuting, errands, and/or recreational activities.

• Gen Z, Y, and X are more inclined to use PR for commuting, influenced by the convenience and environmental benefits.

4. Developing and Finalizing Actionable Items for PR Adoption

After reviewing the insights gathered from the workshops, the comments and observations were consolidated into actionable items. The verbatim responses, two factor analyses, the PRAM, PRAMMAs moderator analysis, and posters were then revisited to ensure all relevant potential actionable items were captured. Subsequently, J.D. Power reviewed the list of actionable items, refined the list further by removing suggestions that were too general or vague, modified the wording to suit a general audience, and eliminated redundancies. The final actionable items were organized into the following categories: vehicle selection, driver selection, passenger selection, routing, safety/security, in-ride experience, pre/post ride experience, inexperienced riders, and education/other, as shown in Figure 8, Part A and Part B. These actionable items derived from the analyses are the key results of this body of work. These items encapsulate the results and provide practical recommendations for addressing the barriers and motivators identified, offering a clear path forward for improving pooled rideshare services.

5. Limitations and Future Research

While this study offers valuable insights into the factors influencing PR adoption and provides actionable recommendations, it has certain limitations that present opportunities for future research. The primary goal of this study was to provide actionable insights and recommendations to rideshare companies and policymakers to enhance PR adoption and user satisfaction. The data were collected in July to August of 2021; it would be valuable to collect a similar dataset in the future to see if/how user attitudes and behaviors change over time. Future research should consider longitudinal approaches to track evolving attitudes toward PR, especially in light of rapid technological advancements and shifting societal norms. Collaborations with transportation network companies to access real-world usage data could further enhance the robustness of models like the PRAM and PRAMMAs, leading to more precise and effective strategies for promoting PR adoption.

This study provides a robust framework that can serve as a template for examining PR usage in other regions around the world. While the findings are specific to the U.S. context, the methodologies employed—such as the nationwide survey design, factor analyses, and development of predictive models like the PRAM and PRAMMAs—are universally applicable. The identification of critical factors such as safety, privacy, trust, and convenience, as well as the incorporation of demographic moderators, offers a comprehensive approach that can be adapted to explore regional variations in PR adoption. Future research in other countries could leverage this framework while tailoring survey instruments and analyses to reflect local cultural, economic, and infrastructural contexts. With the growth of autonomous vehicles, research is needed to examine riders’ attitudes toward various autonomous shared mobility experiences.

6. Conclusions

This research provides comprehensive insights into the factors influencing the acceptance of pooled rideshare (PR) in the U.S. and offers a roadmap for enhancing user adoption and satisfaction. Through the national survey and development of the Pooled Rideshare Acceptance Model (PRAM) and its Multigroup Analyses (PRAMMAs), the body of knowledge identified key factors, including privacy, safety, trust, and convenience that shape users’ willingness to consider PR, as shown in Figure 1. The use of a large national sample (N = 5385), including participants with varying levels of PR experience, enabled rigorous statistical analyses, revealing that demographic variables significantly influence PR adoption decisions. These findings underscore the need for a customized approach rather than a one-size-fits-all strategy to address the unique preferences and concerns of different user groups.

Workshops played a crucial role in translating statistical findings into actionable recommendations and refining actionable items that address the barriers and motivators for PR adoption. The iterative process of developing this list of items was informed by survey data, statistical analyses, and workshop feedback, ensuring a comprehensive understanding of user wants and needs. A comprehensive review and refinement of the actionable items from multiple perspectives, including J.D. Power, helped streamline strategies across key areas, including safety, service transparency, user education, and convenience.

This study serves as a vital resource for researchers, policymakers, and industry experts seeking to understand PR dynamics. It bridges the gap between academic research and practical applications by providing data-driven insights and actionable recommendations to address barriers to PR adoption. Readers can better understand how demographic and experiential variables shape user behavior, making the findings relevant for improving transportation policies, service design, and future research endeavors. Combining rigorous methodology with practical outcomes, this research supports the advancement of sustainable and user-friendly transportation systems.

The findings offer a roadmap for promoting efficient and sustainable transportation options. By focusing on user-centric improvements, stakeholders can enhance PR services, reduce traffic congestion, and improve mobility. Future research should explore emerging trends and demographic shifts to ensure PR services remain aligned with evolving user needs.

Author Contributions

Conceptualization, R.G. and J.B.; methodology, R.G.; software, R.G.; validation, J.B., L.B., K.K. and Y.J.; formal analysis, Y.J.; investigation, R.G.; resources, R.G. and J.B.; writing—original draft preparation, R.G.; writing—review and editing, J.B.; funding acquisition, Y.J. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data are available upon request due to restrictions, e.g., privacy or ethical.

Acknowledgments

This research was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under award number DE-EE0009205. The views and conclusions presented in this study are those of the authors and do not necessarily represent the official policies or opinions of the U.S. Department of Energy or the U.S. Government. We extend our gratitude to Hoatian Su, Joe Paul, Casey Jenkins, Megan Gilstrap, Rebecca Pool, and Patrick Rosopa for their invaluable support, contributions, and meticulous review of the data analysis.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Table

Figure 1. Comprehensive design, development, and analysis of pooled rideshare acceptance.

Figure 2. Survey flow diagram.

Figure 3. Based on verbatim responses, the top 5 reasons respondents were NOT willing to use PR and did not know if they were willing to use PR (Note: open-ended verbatim comments were coded into the categories listed above).

Figure 4. Survey items used for the first national survey. Note: the willlingness to consider PR factors and optimizing experience for PR factors are presented based upon the findings of the two factor analyses [46,47] rather than the original groupings; for each factor, the percentage in the bracket indicates that factor’s variance in factor analysis, while for each survey item, the value in the bracket indicates that item’s factor loading.

Figure 5. Pooled Rideshare Acceptance Model (PRAM) [45]. Arrows indicate causal relationships. For example, the privacy factor directly influences safety and service experience. Also, privacy indirectly influences PR acceptance mediated through safety, trust service, and willingness towards PR, as well as mediated through service experience.

Figure 6. Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Aligning with the red and green arrows, the red box indicates the demographics that are negatively significant between groups and the green box indicates the demographics that are positively significant between groups.

Figure 7. Categorization of user groups for PR services grouped by responses of user groups who are most likely to use, have concerns of using, and may be willing to use PR services.

Figure 8. (A). The list of potential actionable items providing recommendations for the topical areas related to the PR ride experiences, route planning and passenger safety, and onboarding and rider support. (B). The list of potential actionable items providing recommendations for the topical areas related to vehicle selection, rider and driver personalization, and additional recommendations related to accessibility and vulnerable populations.

Figure 8. (A). The list of potential actionable items providing recommendations for the topical areas related to the PR ride experiences, route planning and passenger safety, and onboarding and rider support. (B). The list of potential actionable items providing recommendations for the topical areas related to vehicle selection, rider and driver personalization, and additional recommendations related to accessibility and vulnerable populations.

Table 1

Distribution of participants’ demographics and transportation needs.

	Sample(N = 5385)		Sample (N = 5385)
Gender		Number of children
Male	52.1%	Zero	66.5%
Female	47.3%	One	15.5%
Prefer to self-describe 1	0.3%	Two	13.6%
Prefer not to answer 1	0.3%	More than two	4.2%
Generation		Prefer not to answer 1	0.2%
Gen Z (1995–2004) < 27 years	16.6%	Household annual income
Gen Y (1977–1994) 27–44 years	30.7%	Less than USD 25,000	14.4%
Gen X (1965–1976) 45–56 years	21.2%	USD 25,000 to USD 79,999	39.9%
Boomers (1946–1964) 57–75 years	26.8%	USD 80,000 to USD 149,999	26.8%
Pre-boomers (before 1946) > 75 years	4.7%	USD 150,000 to USD 199,999	7.2%
Geographic area		USD 200,000 to USD 249,999	2.4%
Urban	37.8%	USD 250,000 or more	3.2%
Suburban	54.9%	Prefer not to answer1	6.1%
Rural	7.1%	Number of vehicles
Prefer not to answer 1	0.2%	Zero	7.3%
Driver’s license 2		One	40.8%
Has license	89.2%	Two	35.3%
No license	10.8%	More than two	16.4%
Rideshare experience		Prefer not to answer 1	0.2%
Has rideshare experience	56.7%	Typical transport used to commute 2
Does not have rideshare experience	43.3%	Personal vehicle
School completion		Uses personal vehicle	80.7%
High school/technical school or less	23.0%	Does not use personal vehicle	19.3%
Some college	22.7%	Public transport
4-year college degree	26.4%	Uses public transport	20.6%
Graduate school/advanced degree	27.9%	Does not use public transport	79.4%
Employment status		Walk/bike
Employed	57.5%	Walks/bikes	34.4%
Student	6.0%	Does not walk/bike	65.6%
Seeking employment	7.2%	Telecommute
Retired	22.1%	Uses telecommute	10.1%
Unable to work	7.1%	Does not use telecommute	89.9%
Number of people in the household		Carpool
One	19.9%	Uses carpool	11.9%
Two	33.9%	Does not use carpool	88.1%
Three	18.3%
More than three	27.5%
Prefer not to answer 1	0.4%

¹ The responses are considered missing data. ² The response is taken from the your transportation needs section. All other responses are from the demographics section.

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