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Public transit user satisfaction: Variability and policy implications
Abstract
This research focuses on passenger's perception of transit performance with an emphasis on the variability between operators and the policy implications of such differences. Two statistical methods (factor analysis and ordered logit modeling) have been used to assess the quality implications of the variability of the users' perceived satisfaction across operators. A market segmentation analysis (between male and female respondents) provides further insight into the differences among groups of the population. Five transit systems in the two major conurbations in Greece, Athens and Thessaloniki, have been examined. The analysis demonstrated that a well-coordinated transportation environment should be the primary aim of the policy makers in Athens, followed by other quality attributes such as service frequency and accessibility. In Thessaloniki, the sole transit operator should include in its policy plans immediate corrective measures addressing the service frequency, waiting time and vehicle cleanliness attributes.
... SQ is comprised of different indicators/attributes such as frequency of services (32,33), network coverage (15), transfer facilities (31), waiting time (27,34), level of comfort (31,35,36), driver conduct (37,38), safety (38,39), information about the available services (21,38), reliability (5,33), cleanliness (38,40), accessibility (33,38), punctuality (25), security and public utilities (41), and so forth. Among the characteristics mentioned above, safety and security were observed to be the most significant when examining the public transit system's SQ in previous studies (26,(42)(43)(44). ...
... SQ is comprised of different indicators/attributes such as frequency of services (32,33), network coverage (15), transfer facilities (31), waiting time (27,34), level of comfort (31,35,36), driver conduct (37,38), safety (38,39), information about the available services (21,38), reliability (5,33), cleanliness (38,40), accessibility (33,38), punctuality (25), security and public utilities (41), and so forth. Among the characteristics mentioned above, safety and security were observed to be the most significant when examining the public transit system's SQ in previous studies (26,(42)(43)(44). ...
... SQ is comprised of different indicators/attributes such as frequency of services (32,33), network coverage (15), transfer facilities (31), waiting time (27,34), level of comfort (31,35,36), driver conduct (37,38), safety (38,39), information about the available services (21,38), reliability (5,33), cleanliness (38,40), accessibility (33,38), punctuality (25), security and public utilities (41), and so forth. Among the characteristics mentioned above, safety and security were observed to be the most significant when examining the public transit system's SQ in previous studies (26,(42)(43)(44). ...
This study analyzes the effects of certain variables on bus service quality (SQ) and how SQ and personal attitudes affect satisfaction with public buses. A total of 552 responses were collected using a questionnaire that captured socioeconomic and trip characteristics, satisfaction ratings for SQ attributes, and the personal attitudes of consumers. Factor analysis was used to uncover unobserved latent features and to generate two measurement models: for SQ and for personal attitudes of bus users. Three latent variables (''information, safety and security'', ''comfort'', and ''accessibility/availability'') were observed that signify SQ. Simultaneously, two latent variables (perceived value, and behavioral intention and involvement) were obtained representing the attitude of customers. A structural equation modeling method was employed to compute interconnections among these variables. Information and safety and security had a major influence on SQ followed by comfort and accessibil-ity/availability. Similarly, perceived value had a greater impact on personal attitudes than that on behavioral intention and involvement. Findings also show that evaluating overall SQ is better explained when consumers rate the service quality of buses after knowing about the various attributes. Findings revealed that the overall satisfaction of customers with bus services was influenced more by SQ-related attributes than by personal attitudes. The study also provided insights into public bus service quality improvements that must be emphasized and enhanced to increase ridership. This understanding of connections among SQ, personal attitudes, and overall satisfaction can assist transit officials in developing effective strategies and investment plans to meet the needs of passengers and boost customer satisfaction with public buses.
... According to this view, satisfaction is largely determined by the emotions experienced during the purchase process, which leave an imprint in the memory. Tyrinopoulos and Antoniou (2008) defined passenger satisfaction level is an aggregated metric that the user perceives for different aspects of the transport system. Fellesson and Friman (2008) examined customer satisfaction with public transport in 9 European cities, and they defined 4 dimensions of satisfaction from a factor analysis of 17 traits: regularity, comfort, staff expertise and safety. ...
... The theory of planned behaviour is associated with Ajzen's theory that there are three main predictors of one's habit of performing a certain behaviour: attitude, subjective norm and perceived behavioural control. Several studies have concluded that the most important characteristics in terms of user satisfaction are accessibility metrics, including punctuality, reliability, service frequency and travel speed (de Oña et al., 2015(de Oña et al., , 2013Mazzulla, 2015, 2007;Fellesson and Friman, 2012;Friman and Gärling, 2001;van Lierop et al., 2017;Mouwen, 2015;Shen et al., 2016;Stuart et al., 2000;Tyrinopoulos and Antoniou, 2008;Weinstein, 2000;dell'Olio et al., 2011;Redman, 2013;Allen et al., 2018aAllen et al., , 2018bGuirao et al., 2016;Román et al., 2014). While other studies highlight the importance of additional characteristics, such as comfort (de Oña et al., 2013;Fellesson and Friman, 2012;van Lierop et al., 2017;Weinstein, 2000;Redman, 2013;dell'Olio et al., 2011;Allen et al., 2018a;Guirao et al., 2016;Ingvardson and Nielsen, 2019), staff behaviour (de Oña et al., 2013;Fellesson and Friman, 2012;Friman and Gärling, 2001;van Lierop et al., 2017;Allen et al., 2018a), safety and security (Fellesson and Friman, 2012;Spears et al., 2013;Stuart et al., 2000;van Lierop et al., 2017;Allen et al., 2018b;Guirao et al., 2016;Figler et al., 2011;Nathanail, 2008;Shiwakoti et al., 2019), cleanliness Tyrinopoulos and Antoniou, 2008;van Lierop et al., 2017;Weinstein, 2000;dell'Olio et al., 2011;Allen et al., 2018a), and information availability (Allen et al., 2018a(Allen et al., , 2018bEboli and Mazzulla, 2015;Friman and Gärling, 2001;van Lierop et al., 2017;Weinstein, 2000). ...
... Several studies have concluded that the most important characteristics in terms of user satisfaction are accessibility metrics, including punctuality, reliability, service frequency and travel speed (de Oña et al., 2015(de Oña et al., , 2013Mazzulla, 2015, 2007;Fellesson and Friman, 2012;Friman and Gärling, 2001;van Lierop et al., 2017;Mouwen, 2015;Shen et al., 2016;Stuart et al., 2000;Tyrinopoulos and Antoniou, 2008;Weinstein, 2000;dell'Olio et al., 2011;Redman, 2013;Allen et al., 2018aAllen et al., , 2018bGuirao et al., 2016;Román et al., 2014). While other studies highlight the importance of additional characteristics, such as comfort (de Oña et al., 2013;Fellesson and Friman, 2012;van Lierop et al., 2017;Weinstein, 2000;Redman, 2013;dell'Olio et al., 2011;Allen et al., 2018a;Guirao et al., 2016;Ingvardson and Nielsen, 2019), staff behaviour (de Oña et al., 2013;Fellesson and Friman, 2012;Friman and Gärling, 2001;van Lierop et al., 2017;Allen et al., 2018a), safety and security (Fellesson and Friman, 2012;Spears et al., 2013;Stuart et al., 2000;van Lierop et al., 2017;Allen et al., 2018b;Guirao et al., 2016;Figler et al., 2011;Nathanail, 2008;Shiwakoti et al., 2019), cleanliness Tyrinopoulos and Antoniou, 2008;van Lierop et al., 2017;Weinstein, 2000;dell'Olio et al., 2011;Allen et al., 2018a), and information availability (Allen et al., 2018a(Allen et al., , 2018bEboli and Mazzulla, 2015;Friman and Gärling, 2001;van Lierop et al., 2017;Weinstein, 2000). According to Tyrinopoulos and Antoniou (2008), satisfaction level is an aggregate measure of user perceptions of different aspects of the transport system. ...
... In addition, access to real-time information about the location and status of buses can reduce the stress and uncertainty associated with waiting for a bus, leading to an improved experience and higher levels of satisfaction with the service. [14] Tirinopoulos and Antoniou (2008) found that both distance to stop and waiting time affected overall satisfaction [15]. The ease of switching between different modes of transport allows users to reach their destination quickly and efficiently. ...
... If the personal space inside the vehicle is narrow and cramped, it can cause discomfort and anxiety, which can lead to user dissatisfaction. Tirinopoulos and Antoniou (2012) found that crowding was the factor that most deterred respondents from using public transport [15]. De Oña (2013) believed that the temperature inside the vehicle is important for passenger satisfaction [17]. ...
Buses are an important component of the urban public transport system, meeting the daily mobility needs of the population. However, various risks arise during the operation of public transport, which can cause serious problems in terms of safety and comfort of passengers. In this study, risk factors of public transport in the southern cities of Azerbaijan were analyzed and a risk assessment was carried out using the “bow tie” method.
... The data was collected during the worst phase of the recession (2013) and included information about metro and bus user satisfaction by measuring the importance of certain attributes as well as changes in demand. A mixture of methods were used in the analysis whose results were compared with a similar survey study by Tyrinopoulos and Antoniou (2008), which was conducted before the financial crisis. The studies revealed an increase in PT use for the ages 25 -39. ...
... One could argue that individuals are indifferent to the level of PT coverage with regards to choosing transport but given that 67% stated COVER-AGE above medium and only 6.8% below medium we can assume that it is not indifference but rather accustomation to a high level of coverage. Another possible factor is the PT user satisfaction which has the potential to influence negatively the use of PT (Tyrinopoulos and Antoniou, 2008). ...
... In order to restrain this shift, several push and pull factors can also drive the decision to select a mode to commute (Nordfjaern et al., 2019;Sharma & Chandrasekhar, 2014). In recent times, transit authorities also need to emphasise monitoring and improving their services to control the increasing rate of vehicle ownership and contribute towards providing sustainable mobility (Tyrinopoulos & Antoniou, 2008). Thus, it is equally essential to evaluate the service provided by the regional transit systems to facilitate captive commuters as well as reduce the consumption of private vehicles. ...
... In case of service related attributes, the satisfaction with frequency and punctuality is observed to influence the overall satisfaction (J. de Oña et al., 2013;Mouwen, 2015;Tyrinopoulos & Antoniou, 2008). Other attributes related to the service of public transport such as travel time Mouwen, 2015) and waiting time are also important in influencing the satisfaction of commuters. ...
... Each model used the effectiveness scores of a different strategy as the dependent variable and the same set of agency characteristics, including the type of services provided, the size of the agency, and the region where the agency was located, as the independent variables. We chose this model based on our choice of the ordinal dependent variable and multiple categorical independent variables (44)(45)(46). To test if the proportional odds assumption held for our models, we used the method proposed by Brant (47) and included the results in Appendix A. We collected the service types from a multiple-choice question that allowed for more than one entry, whereas the question on agency sizes only allowed for one entry. ...
... On the contrary, adding targeted services is rated lower by agencies in the Northeast region, and improving security and vehicle amenities is rated lower by agencies in the West region. These observations may be the result of different sociodemographic contexts (such as population density and percentage of the population that commute by transit), different factors that influence rider satisfaction (44), and different perceived risks of threatening events (such as crime and extreme weather [38]). Agencies in the Northeast region (e.g., the Metropolitan Transportation Authority in New York City, NY, and the Massachusetts Bay Transportation Authority in Boston, MA) tend to have downtown transit networks to serve high-density city centers, which may make targeted services like a downtown circulator only marginally effective in increasing ridership. ...
With COVID-19 no longer classified as a public health emergency, transit agencies are seeking strategies to boost their ridership. Although previous studies have compiled many viable strategies, there is limited knowledge about their effectiveness for agencies with differing characteristics and how their implementation may have evolved post-pandemic. This paper bridges this research gap by identifying effective strategies for agencies of different sizes, regions, and service types. We based this study on a nationwide online survey of 244 transit agencies recruited via email and employed logistic regression analyses to test associations of the perceived effectiveness of strategies with agency characteristics. The findings reveal that marketing and promotion strategy implementation rates increased during the pandemic; however, such increases were short-term and not incorporated into the agencies’ future implementation plans. Moreover, increasing the service frequency emerged as the most effective strategy, whereas fleet electrification, despite being a lower priority for ridership recovery, proved significantly more effective for agencies with firsthand experience. Policymakers and transit agency managers can use the findings of this study to identify strategies that their peer agencies of similar sizes, regions, and service types consider effective for boosting ridership and promote transit use for everyone, especially for those lacking alternative means for transportation.
... Current academic literature on measuring metro service efficacy mainly focuses on actual operational conditions. For example, some studies aim to identify key factors affecting metro service quality, such as trip accuracy, system safety, and comfort [1,2] . At the same time, the industry's approach to measuring metro service efficacy is broader. ...
... Studies focusing on the metro's own service quality are relatively mature, measuring efficacy based on actual operational conditions. Reference [2] reviews key measurement factors, including basic elements of the metro system such as route length, operating speed, capacity, and reliability. They also highlighted passenger comfort and safety, including fire safety and air quality within metros and stations, as factors of academic concern [10] . ...
The high efficacy of metro network services not only enhances residents' travel quality but also brings significant socio-economic benefits, thus is of great importance to urban land use and city development. Existing methods for measuring metro service efficacy often overlook metro network connectivity and rely heavily on subjective questionnaire data analysis from the user experience perspective. This paper proposes a method to measure metro network service efficacy from the user's perspective. The approach first calculates the connectivity index of metro network and estimates the housing premium brought by metro network connectivity, which reveals users' willingness to pay for metro network connectivity. This method objectively measures metro network service efficacy from the user's perspective. Based on this, efficacy optimization methods are proposed, providing quantitative simulation methods for metro expansion, site selection, operation quality adjustments, etc., which are of great reference value to metro management departments and even urban sustainable development.
... Overall bus satisfaction models, as appears in Table 10, show that waiting time has a positive significant impact on overall satisfaction which in line with previous studies (dell 'Olio et al., 2011;Nwachukwu, 2014;Tyrinopoulos& Antoniou, 2008). On the contrary, waiting time due to unreliability can lead to negative satisfactionon passenger particularly those with several transfers (Rietveld et al., 2001). ...
... In an attempt to improve public transport satisfaction, those facilities are important to createpositive waiting experience. The correlation is in line with the previous study revealingthat improved waiting experience will increase positive satisfaction (Lai & Chen, 2011;Nwachukwu, 2014;Tyrinopoulos & Antoniou, 2008). In addition, models also found that passenger who travels in shorter distance tend to rate more negative result than the longer distance. ...
Passenger satisfaction significantly affects behaviour towards public transport. With emerging BRT-Lite development in Indonesia, satisfaction of the services reflects the quality and performance to meet the passengers need. This paper investigates passenger satisfaction level of four BRT-lite in Indonesian cities, consists of shelter and bus service attributes, users personal and travel characteristics. Passenger satisfaction for key service attributes of bus and shelter was assessed using Customer Satisfaction Index and Ordinal Logistic Regression. The results of this study found that passenger in Bali, Surakarta, and Bandung tend to rate high satisfaction level for most attributes, whereas less satisfaction is found in Bogor. Specific attributes do have significant influence on satisfaction level which also causing the negative results in Bogor. Interesting finding found in this paper is that BRTLite which has the lowest satisfaction rate resulting in possibility to reduce the sustainability of the BRT operation.
... The expected results are obtained, where all the indicators exhibit loadings well beyond 0.50 on the anticipated factor, and the variance within the multi-indicator scale is well accounted for by the obtained single factor with eigenvalue larger than 1. In the current study, factor analysis has been carried out independently for each bunch of pre-designed indicators, rather than blindly performed towards the whole items hoping that some underlying patterns would be uncovered (Tyrinopoulos & Antoniou, 2008). Instead, a conceptual foundation based on the SDT and TPB is used to motivate factor analysis applications. ...
Excessive private cars have caused serious problems for the whole society, which seriously damages human well-being and urban sustainable development. This study endeavors to empirically identify the motivational pattern and psychological process involved in individuals’ behavioral intention to use low-carbon transportation modes based on a conceptual framework accommodating two complementary theories, namely the self-determination theory (SDT) and the theory of planned behavior (TPB). Data from a field survey in Zhenjiang, Jiangsu Province, China is utilized to examine a bunch of hypothesized relationships. The results confirm that both SDT extrinsic and intrinsic motivations associated with driving reduction significantly exert positive influences on the proximal antecedents of low-carbon transportation mode-use intention in TPB, justifying the integration of the two differing theories in the transportation background. The direct influence of all three SDT motives on the target low-carbon transportation intention is also significant, and the total effect of extrinsic motivation reveals to be more prominent. From a practical perspective, such findings highlight the importance to enhance people’s feelings about internal dissatisfaction and disappointment, as well as external punishment and regulations on driving in order to effectively trigger their low-carbon transportation intention formation and enactment. Among TPB factors immediately predicting intention for low-carbon transportation modes, perceived behavioral control is confirmed as the most pivotal one. Taken together, the current findings are valuable in providing managerial implications aimed at promoting desirable motivations and travel behavior changes in the pro-environmental direction.
... In the literature, there are many researches concerning transit service quality. Examples of the most recent research are reported in TRB (2003aTRB ( , 2003b, Joewono and Kubota (2007), Tyrinopoulos and Antoniou (2008), Iseki and Taylor (2008) and Eboli and Mazzula (2009). In these studies, different attributes determining transit service quality are discussed; the main service aspects characterizing a transit service include service scheduling and reliability, service coverage, information, comfort, cleanliness, and safety and security. ...
To tackle the increased motorization, Ministry of Transportation (MoT) of Indonesia has promoted pilot cities for land transport improvement. Unfortunately, TransJogja as a new transit system has failed to encourage number of passengers in spite of the increasing of travel demand from population growth as its service quality has continually declined after over five years of operations. This research provides a comprehensive tool for measuring the overall transit service quality, named Heterogeneous Customer Satisfaction Index (HCSI), by considering different service aspects. To measure TransJogja service quality, users completed information about 8 service aspects which consists of overall 27 service attributes. The value of HCSI is 7.22 out of 10 indicating that the service delivered is about 72 percent successful in satisfying TransJogja customers. More efforts are needed to increase the level of customer satisfaction and attract new users to establish TransJogja as an appropriate transit system within the city.
... Overcrowded train compartments reduce personal space and heighten discomfort, although solitary travel can also provoke anxiety [45,47]. Environmental stressors, including excessive operational noise and ambiguous travel information during transfers, further intensify distress, highlighting the need for improved passenger information systems [89,96]. ...
As urbanization continues to expand, the design and structure of urban spaces increasingly influence the experiences of individuals, whether intentionally or inadvertently. These effects can result in both positive and negative experiences, with urban facilities generally designed to enhance the comfort and well-being of citizens. However, in certain cases, these spaces can provoke adverse emotional reactions, such as anxiety. Anxiety, a prevalent mental health disorder, is more commonly observed in urban environments than in rural areas. Among various urban settings, rail transport in large cities is often cited as one of the most stressful environments for passengers. In light of the significance of this issue, this study seeks to explore how physical and perceptual components can reduce anxiety and encourage greater use of intra-urban rail transportation. Utilizing a qualitative research approach, the study employed directional content analysis to investigate this topic. Data were collected and analyzed through an exploratory methodology with the assistance of MAXQDA software. The analysis began with guided content coding, drawing on theoretical frameworks pertinent to the research. Through this process, 2387 initial codes were identified, which were then categorized into nine main themes, with the relationships between these codes clarified. The findings were inductively derived from the raw data, leading to the development of a foundational theoretical framework. The study, employing a personalized strategy, identified three key factors that contribute to anxiety: physical, perceptual, and environmental components. Physical factors, such as accessibility, lighting, and signage, were found to have a significant impact on passengers’ psychological well-being. Perceptual factors, including personal perceptions, stress, and fear, played a crucial role in exacerbating anxiety. Additionally, environmental factors, particularly the design of metro networks, rail lines, and flexible transportation lines, such as car-sharing and micromobility, were found to significantly contribute to the overall anxiety experienced by passengers. Moreover, the study suggests that anxiety triggers can be mitigated effectively through the implementation of well-designed policies and management practices. Enhancing the sense of security within transit spaces was found to increase citizens’ willingness to utilize rail transportation. These findings indicate that targeted interventions aimed at improving both the physical and perceptual aspects of the transit environment could enhance the commuter experience and, in turn, foster greater use of rail systems.
... Frequency of service is, of course, an important factor for passengers when it comes to the availability of public rail transportation and has an impact on customer satisfaction (Eboli, et al 2017). In fact, Mouwen (2015), Tyrinopoulos & Antoniou (2018), and Shen, Xiao, & Wang (2016) suggested that public transportation users consider frequency to be the most important factor of whether they would be inclined to use public transportation instead of driving. The railway service quality factors were also discovered by Vanniarajan and Stephen (2018). ...
... Previous research has revealed many opportunities and challenges for implementing the Jakarta-Bandung HST, as noted by Putri and Widyastuti [6]; Putri and Widyastuti [6]; Kusuma, et al. [10]; Tjahjono, et al. [11] and Sunandar, et al. [13], illustrating a high likelihood of people switching to access the Jakarta-Bandung HST. However, previous research has not addressed the importance of policy improvements by operators and the government as regulators, considering factors that are crucial in formulating strategies to increase user satisfaction and continuously boost the volume of passengers as targeted [3,[14][15][16][17]. This necessitates improvements in aspects that are important considerations for users to be addressed immediately. ...
The rapidly developing business environment and the many choices that can be made by customers according to their desired expectations have caused companies to implement various innovations, especially in the selection of public transportation modes between Jakarta and Bandung, which are currently filled with travel cars, trains, high-speed trains, buses, etc. Companies innovate in order to create customer satisfaction, which in the long term will foster great loyalty. The purpose of this study was to determine the factors considered by passengers of the Jakarta-Bandung High-Speed Train to increase the level of satisfaction among service users. This study employs a quantitative method through a survey conducted on 300 respondents who used the Jakarta-Bandung High-Speed Train in January-February 2025, utilizing a questionnaire administered directly to respondents at Halim Station and Padalarang Bandung. To test the relationship between variables and validity, this study employs statistical analysis with structural equation modeling (SEM). The results of this study demonstrate a strong relationship between six dimensions: information services, accessibility, train service, train comfort, station comfort, and emergency actions, all of which contribute to increasing the satisfaction of Jakarta-Bandung High-Speed Train (HST) users. The findings of this study can be utilized by operators and the government in efforts to improve the level of Jakarta-Bandung train services and their regulations, as well as to plan the opening of new routes for HST in Indonesia in the future.
... Redesigning public transportation cabins involves more than just aesthetic enhancements; it requires a comprehensive understanding of how different design elements affect the passenger experience [13,15]. Similar to any other built environments [16], one major aspect of this relationship is understanding how passengers visually interact with different cabin designs and how demographic factors influence these interactions. ...
Designing public transportation cabins that effectively engage passengers and encourage more sustainable mobility options requires a deep understanding of how users from different backgrounds, visually interact with these environments. The following study employs eye-tracking technology to investigate visual attention patterns across six distinct cabin designs, ranging from the current and poorly maintained versions to enhanced, biophilic focused, cyclist-friendly, and productivity-focused configurations. A total of N:304 participants engaged with each cabin design while their eye movements such as Fixation Counts, Time to First Fixation (TFF), First Fixation Duration (FFD), Stationary Gaze Entropy (SGE), and Gaze Transition Entropy (GTE) were recorded. Results revealed that alternative cabin configurations consistently exhibited shorter TFFs and lower entropy measures compared to the baseline current version. Specifically, designs incorporating natural elements and biophilic aspects, streamlined layouts, or functional amenities, facilitated quicker orientation and more structured gaze patterns, indicating enhanced visual engagement and possibly reduced cognitive load. In contrast, the poorly maintained cabin design was associated with higher entropy values, suggesting more scattered and less predictable visual exploration. Demographic factors, particularly ethnicity, significantly influenced FFD in certain designs, with Non-white participants showing reduced fixation durations in the enhanced and poorly maintained environments highlighting the importance of inclusive design considerations. Moreover, transportation-related demographic factors such as frequency of public transport use, trip purpose, and duration of use significantly influenced visual attention metrics in various cabin designs.
... In case of latent constrict "availability", it is highly impacted by "availability of walking infrastructure" followed by "journey time inside bus" and "availability of travel-related information at bus stop". These variables were identified as crucial factors affecting SQ in previous studies [52][53][54]. In addition rider's overall satisfaction was also significantly affected by perceived value and involvement of the riders which were found consistent with previous studies [55]. ...
Kathmandu is facing escalating challenges related to congestion, air pollution and energy consumption due to increase in demand for personalized transportation. Efforts are being made to strengthen the public transport system in Kathmandu and much imitative is introduction of electric vehicles. Development of these buses is expected to augment public transport capacity, create clean environment, and modernize the transportation system. In this context, a study has been undertaken to determine which aspects of service quality are important and to what extent the rider's overall satisfaction with the electric bus can be achieved with these aspects of service quality. Partial least square structural equation modeling (PLS-SEM) integrated with the necessary condition analysis is used to analyze the service quality and overall satisfaction of riders. 388 data were collected using the customer satisfaction questionnaire, which captured satisfaction ratings of service quality attributes, socio-demographic characteristics, and trip characteristics. After the analysis, among the latent construct of service quality it was observed that riders ‘overall satisfaction with electric buses is highly influenced by latent constructs comfort followed by security, availability, and time & reliability. Between latent construct of personal attitude, riders’ overall satisfaction is mostly affected by involvement than that of perceived value. Improving these latent constructs can boost the rider’s overall satisfaction. This study will assist electric bus operators and researchers in identifying key attributes for improving service quality and attracting more riders to public buses. Additionally, it will provide public authorities, policymakers, and researchers with essential insights into making electric buses, a sustainable and low-emission public transport option, more appealing.
... Batty et al. (2015) discussed challenges and opportunities in promoting urban modal shift to public transport by analyzing societal, political and economic obstacles that hinder people to change their travel behavior. Furthermore, the researchers also proposed a revised version of Department for Transport's (UK) Hierarchy of Transport Needs from the analysis of public transport quality attributes from other researches in UK: Tyrinopoulos & Antoniou (2008). From the most important need to the least, the factors included accessibility, reliability, comfortability & cleanliness, safety & security, affordability, speed of service, and environmental impact. ...
An initial assessment of the existing routes of the recently implemented P2P Bus Service System in Metro Manila was conducted. The service encourages mode shifting from private to public transport especially for users traversing one of the busiest roads in the metro: Epifanio de los Santos Avenue (EDSA). The characteristics of the P2P bus units that distinguish them from regular buses include fixed departure schedules, fewer pick-up and drop-off points, passenger limit, and aspects such as more comfortable seating and free internet connection. A questionnaire survey is then conducted among current P2P users to have an initial assessment of the said transit system and be able to formulate possible improvements. It was found that not all routes were able to successfully encourage private car users to shift to P2P and most of the current users are also from other modes of public transport. On the other hand, a satisfaction survey is also conducted among users and it is identified that affordability, travel time, schedule, and amenities are aspects which can be improved for the P2P bus service system.
... On the other hand, Tyrinopoulos and Antoniou (2008) found that transfer quality and quality service are the top priority in bus services for the customers in Athens. According to them, the key satisfaction indicators were the service frequency, transfer distance, ticketing system, and vehicle cleanliness. ...
Buses are the only available organized mass public transport system in Dhaka. However, the city is planning to have bus rapid transit (BRT) systems and metro systems to cater the increasing demand for public transport. The buses in Dhaka mostly remain over-crowded, which is often not accessible for the elderly or disabled people as well as for the women. Moreover, the frequency of bus service (headway) is not good. The paper reports the existing service and the users’ opinion about the service level of public bus operating within the city. For this purpose, 5 different bus routes had been chosen and a total of 175 passengers of bus (30 from each route) had interviewed with a pre determined structured questionnaire to know their experience/satisfaction and opinion about the existing service as well as their expectations. Surprisingly, it was found that most of the respondents are satisfied with the cost of ticket but very unsatisfied with the waiting time as they have to wait for the bus sometimes about an hour. Journal of Bangladesh Institute of Planners, Vol. 5, Dec 2012, pp. 93-105
... Consequently, it is necessary to consider the deterioration in the level of service (LoS) and the reliability of the systems (Wu et al. 2019). LoS can be expressed by several attributes, and punctuality, scheduled frequency and reliability have been identified as key factors in determining the satisfaction of PT users (Hensher et al. 2003;Tyrinopoulos and Antoniou 2008;Van Lierop et al. 2018). The deterioration of these factors has a significant impact on users' experience (Bates et al. 2001;Mazloumi et al. 2010;Trompet et al. 2011), potentially leading to a shift in modal choice. ...
Public Transportation (PT) is a universal service in most countries, and it is acknowledged for its social and environmental role in enhancing accessibility and promoting a sustainable transport system. However, when disruptions alter the service, the level of service (LoS) can be massively affected. Consequently, the perceived quality can be influenced, and users can be encouraged (or forced) to modify their subsequent modal choice, in accordance with the users’ socioeconomic profile. A survival analysis, namely a Cox proportional hazards model, was tested in Bologna, Italy, using real data provided by TPER S.p.A, specifically Automatic Vehicle Location (AVL) and Automatic Passenger Counter (APC). This analysis aimed to assess the variations in demand over time taking into account variables related to the socioeconomic characteristics of the demand and several service attributes. The results contribute to the literature in several ways. Firstly, they confirm the predominant role of PT in the modal alternative spectrum of disadvantaged users. Secondly, they provide insights into the perception of quality service among different user categories, including commuters and non-frequent users.
... Passengers' satisfaction with service attributes is analysed and understood through a survey [35][36][37]. Some passenger surveys are conducted on-board in a conventional way [38,39]. Some more recent surveys are conducted online and managed via a professional market research platform such as Qualtrics [1,40]. ...
While existing literature has focused on modelling pedestrian movement on platforms, there is a lack of understanding of passengers' perceptions, motivations, and influential factors that shape their on‐board behaviours and choices. This study developed a conceptual framework to assess passengers' post‐boarding behaviours and perceptions, specifically focusing on their actions and choices inside the train carriages. The conceptual framework was tested through survey data of 429 passengers in Melbourne, Australia. The result shows that door access is the most influential factor when passengers choose where to stand or sit on board, followed by comfort, safety, privacy, and random factors. Furthermore, the study explores the relationship between the post‐boarding behaviour variables and travellers’ personal and trip characteristic variables. The analysis shows that carrying large items has a more significant effect on many post‐boarding behaviour variables. Gender, age group, travel frequency, waiting time, and carrying small items also play significant roles. However, variables such as travel time and frequency of group travel have lesser effects. These novel findings offer valuable insights, laying the groundwork for future modelling activities. Moreover, the understanding derived from passenger perceptions can guide transport agencies and operators in shaping strategies to improve onboard services.
... Also, having access to real-time information about the location and status of buses can reduce the stress and uncertainty associated with waiting for a bus, leading to a better experience and higher levels of satisfaction from the service. Tyrinopoulos and Antoniou (2008) found that both transfer distance and waiting time influence overall satisfaction. Ease of transfers between lines and other modes of transit impacts the overall convenience and accessibility of the service. ...
The public transit services in low-demand areas are typically poor even when it is highly subsidized. This research is a part of an extensive research proposes and examines a new method to economize public transit operations in low-demand regions. The proposed new service will enable dynamic determination of vehicles’ type, based on pre-booking seats. The scope of our research is to investigate and evaluate factors affecting passengers’ satisfaction with the current public transport and acceptance of the new proposed service. In particular, what means are needed to incentivize passengers to place their trip reservations enough time in advance.
... The methodologies addressing the importance of attributes were based on linear regression models (Weinstein, 2000;Kim andLee, 2011, Eboli andG. Mazzulla, 2010) logistic or probit regressions models (Huse and Evangelho, 2007;Tyrinopoulos and Antoniou, 2008;dell'Olio et al., 2011adell'Olio et al., , 2011b or structural equation models, combining regression, factor analysis and analysis of variance (Karlaftis et al. 2001, Eboli and Mazzulla, 2007, Minser and Webb, 2010de Oña et al., 2013). de proposed the use of index numbers to monitor the perception evolution of each attribute by the user over time. ...
The design of many transit networks is based on transfer stations. Transfers allow better service connectivity and the avoidance of deploying unaffordable door-to-door services among origin and destination points of low demand. However, these potential improvements in terms of cost and performance are achieved at the expenses of forcing users to incur a temporal disutility at transfer facilities. In this paper, we consider that the quality experienced by users at transfers mainly depends on the temporal disutility. It consists of the walking time between loading areas, the waiting time for bus arrivals at the loading area, and the variability of those times. Hence, a procedure to measure the quality at the transfer areas is proposed, integrating the three relevant components: the physical layout of the transfer area; synchronisation between connected routes; and discrepancies between their actual and scheduled service. A quadratic expression of the previous concepts is justified as a valid approach to measure the total quality of the transfer by transit operators with available data. The calibration of the parameters can be obtained considering the customer perception, the consensus of experts, and the partial consensus of experts with regularity conditions. The proposed model can monitor the transfer performance attributes that depend on service operations and allows attributing the loss of quality to each component involved in the process. The new methodology developed through the paper was applied to Barcelona’s New Bus Network, although it would be generally applicable in other modes of transport.
... Other scholars have tried to steer away from this paradigm in assessing transit user heterogeneity. To do so, they use a combination of travel (Allen et al. 2019;Shiftan et al. 2015;Sun and Duan 2019;Tao et al. 2017;Viallard et al. 2019) and personal characteristics (Allen et al. 2020;Fu et al. 2018;Mugion et al. 2018;Tyrinopoulos and Antoniou 2008;Vicente et al. 2020), attitudinal (Cheng et al. 2017;Eldeeb and Mohamed 2020;Fu and Juan 2017;Jamal et al. 2023;Kim and Ulfarsson 2012;Krizek and El-Geneidy 2007;Mesbah et al. 2022;Wang et al. 2022) and geographical (Chen 2016;Grisé and El-Geneidy 2018) variables, and transit use potential (Li et al. 2018). ...
The COVID-19 pandemic has significantly impacted the transit market leading to ridership loss and service cuts. Most of the post-pandemic transit market literature has focused on how to attract those who stopped using transit services, however little attention has been given to how rider profiles have changed. To address this gap, we examine 2019 and 2022 data regarding transit commuters from Montréal, Canada. We apply factor and k-means cluster analyses to derive market segments at both points in time considering satisfaction levels, telecommuting rates, and frequency of transit use. We build upon these analyses to report on overall and mode group-level changes in the transit market. Our market segmentation reveals that captive, captive-by-choice, and choice riders still exist in the current public transit market. However, the share of these groups in the market has changed. The proportion of captive and choice riders has increased while captive-by-choice riders have shrunk in size. Moreover, the post-pandemic market has become mostly composed of infrequent riders and higher rates of telecommuting. We further explore these trends by commute mode (i.e., bus only, metro only, and bus and metro users). The findings from this research can be of interest to practitioners and policymakers as they shed light on the evolution of the perceptions and behaviours of segments of transit riders from before to after pandemic.
... Oliver (1999) emphasised that loyalty can be described as a strong future commitment to repeat a purchase or to visit a specific product or service regularly. Transit industry analysts are currently searching for insights on how to have a beneficial impact on transit users' behavioural expectations in the future, thus affecting users' loyalty (Wen et al., 2005;Tyrinopoulos and Antoniou, 2008;Lai and Chen, 2011;Shiftan et al., 2015;Duy Quy Nguyen-Phuoc et al., 2020). Lai and Chen (2011) highlighted the need to consider loyalty in the sense of transport. ...
Kuala Lumpur is one of Southeast Asia’s most prominent modern cosmopolitan cities, having evolved from the federal capital. In consequence of this transformation, the population of Kuala Lumpur has expanded outward, leading to its city centre being mostly occupied by businesses and residents relocated to suburbs and more affordable areas. Increased commuting distances also facilitated the use of private automobiles which brings about the environmental issues. This research aims to determine factors influencing the behaviour and preferences of public transport passengers particularly Light Rail Transit (LRT) in Kuala Lumpur. In an effort to verify the theoretical model and the relationship between the variables, a structural equation model (SEM) was developed. Perceived Costs (PC), Attractive Alternatives (AA), Feeling towards Transit (FTT), and Service Quality’ (SQ) were considered as the parameters of the public transport services that could be the drivers for the key variables such as Perceived Benefits (PB), Satisfaction (SA), and Behavioural Intentions (BI). This model incorporates direct and indirect effects with the intention of providing insight into how the behaviour of transit passengers is influenced. The results indicate that Service Quality contributes to Satisfaction and Satisfaction contributes to Behavioural Intentions. According to the results, perceived benefits are positively related to satisfaction. The findings do not support the Service Quality and Attractive Alternatives as the significant indicators for the behavioural intentions. The reason for this outcome may have to do with the adverse impact of the COVID-19 pandemic on public transportation services, which in turn affected riders’ perception of these services.
... The review of the literature asserts that superior service quality attracts passengers (Tyrinopoulos & Antoniou, 2008). Understanding the passengers' various service quality expectations and their impact on performance can help private and public transporters devise an appropriate strategy (Lai & Chen, 2011). ...
This study aims to examine the effect of various service quality parameters on the schedule-wise performance of intercity bus passenger transit using objective measures through a panel data regression model. The study findings show that service quality parameters such as bus fare and customer rating positively impact the operator's schedule-wise performance. In contrast, travel time hurts performance. The study also finds that bus type insignificantly affects performance, and an increase in bus fare does not impact performance. In summary, this study underscores the importance of service quality in the public transport system. It recommends that operators prioritize service quality parameters such as bus fare and customer rating to enhance their schedule-wise performance. Furthermore, this study offers valuable insights into the factors that affect the performance of intercity bus passenger transit, which can inform policymaking and management decisions in the public transport sector. Keywords: Intercity Bus Transport Performance, Service attributes, Schedule Performance, Panel data analysis of service quality
... This reduction, often necessary to handle a potentially correlated array of variables, is achieved through factor analysis (Allen et al., 2018;Stradling et al., 2007;Deb et al., 2022). This approach can be further complemented by employing additional statistical techniques such as ordered logit, as demonstrated by Tyrinopoulos and Antoniou (2008), or regression models, as exemplified in the works of Agarwal (2008), Le et al. (2020) and Lunke (2020). ...
... An interesting result is that the price of the ticket is not considered being significant and does not affect customer satisfaction directly (Beira and Cabral, 2007). Furthermore, Tyrinopoulos and Antoniou (2008) showed that service frequency, vehicle cleanness and coverage of network are the most important dimensions for passenger satisfaction followed by waiting conditions and tidiness, especially in buses. Similarly, Thompson and Schofield (2007) related passenger satisfaction with destination. ...
ABSTRACT
Urban public transport plays a vital role in connecting people to different locations. Quality transport service is a very vital element to be considered by transport companies to ensure passengers are satisfied with their services in order to attract more patronage. Passengers thereby choose urban public transport services that fulfill their needs, provide high service quality and give high satisfaction to them. The centre of the empirical examination was to appraise the passenger satisfaction of urban public transport in Port Harcourt city, Rivers State, Nigeria. The study employed quasi-experimental design and questionnaire was used to extract data
from passengers. The study selected six (6) routes zones from Port Harcourt city (Borokori�Lagos (A), Mothercat - Trans Amadi (B), Mile 3 - Mile 1 (C), Rumudara – Eneka (D), Rumuokwuta- Mgbuoba (E) and Rumuokoro-Rumuodumaya (F). 360 structured questionnaires were randomly administered to passengers commuting along the six (6) routes. The outcome indicated the manner of transport is moderately affordable, often available, moderately satisfied, reliable, moderately comfortable, and convenient but passengers feel unsafe towards the driving style and politeness in the behavior of both driver and/or conductor affects the passengers. The research outcome revealed that passenger satisfaction is a determinant of reliability, comfort, convenience, and safety but not dependent
to cost and crime. Also choice of general mobility mode is based on comfort but not related to reliability, convenience, safety, cost, and crime. It was reason that passengers are satisfied with urban general mobility in the urban centre, and taxi is mainly favored means of general mobility because it’s affordable and neatness of the automobile determines the selection of such taxi.
Keywords: Customer, Passenger, Public, Satisfaction, Transport
Given the escalating environmental challenges, it is clear that the approach to the usage of public transport (PT) must be reconsidered. Loyal PT users help attract other travelers through positive recommendations, this drives interest in exploring the relationships between service quality, satisfaction, and loyalty. Although these relationships in the PT context have been studied, there have been limited efforts to explore the variability of their effects. Therefore, this research explores how service quality, satisfaction, involvement, and prior knowledge influence the behavioral intentions to use PT across various traveler groups. The hypotheses are tested by using multi-group analysis in the structural equation modeling framework, and three user profiles are revealed by applying the latent class cluster analysis. The results indicate that involvement strongly influences the behavioral intentions, while satisfaction impacts the intentions solely when involvement acts as a moderator. Class-specific results indicate that younger females living outside the city center put greater emphasis on service quality improvements for their satisfaction and involvement in PT services compared to males and older individuals residing in the city center. Low-income students living in the city center are more likely to use PT if they feel confident how to use the service. The results are relevant for PT operators and related stakeholders in maintaining travelers' loyalty.
Systematic bikeability evaluation is essential to guide urban strategies and assess cycling infrastructure efficacy, fostering a sustainable, cyclist-friendly urban environment. While many studies use site visits or geospatial techniques to evaluate bikeability with neighborhood-level indicators, few address detailed street-level features due to data scarcity. This limitation poses significant challenges in understanding how various built environment (BE) features collectively influence bikeability. Additionally, although protected cycle lanes (segregated facilities) are widely recognized as effective for enhancing the cycling environment, their spatially heterogeneous effects on bikeability remain underexplored. This study presents a comprehensive framework using deep learning techniques and street view images (SVIs) to evaluate bikeability, validated using data from a docked bike-sharing system. Factor analysis is applied to integrate BE features into a bikeability evaluation framework, followed by a Multiscale Geographically Weighted Regression (MGWR) model revealing the hierarchical structure of bikeability: Accessibility & Feasibility, Safety, and Comfort & Pleasurability. The spatial results highlight the need for tailored measures in different functional areas to promote cycling behavior. These insights challenge the prevailing assumption that protected cycle lanes always ensure better bikeability and emphasize the importance of considering both street-level and neighborhood-level features to evaluate the biking environment heterogeneously. This study provides valuable policy implications for enhancing bike-friendly environments, especially in historical areas with distinct spatial characteristics.
This work presents a comprehensive analysis of transport services using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to identify and validate key dimensions influencing service efficiency and user satisfaction. Data was collected on 25 measurement items across six constructs, including Licensing, Registration, Permits, Taxes, Penalties, and Road Safety. EFA was employed to explore the underlying structure of the data and to group related items under cohesive factors. The results identified five distinct factors, namely Service Access, Process Support, Safety Operations, Eco Efficiency, and Penalty Awareness. CFA was then utilized to validate the factor structure and assess the model's fit to the observed data. The findings highlight critical areas for improvement in transport services, such as streamlining processes, enhancing accessibility, ensuring compliance, and promoting road safety initiatives. This study offers actionable insights for policymakers and stakeholders to optimize service delivery and enhance user satisfaction in transport management systems.
Introduction
This study highlights the significant impact of commuting on the wellbeing of university students and examines the effects of commuting effort across different modes on students’ perceived autonomy (decisional and affective) and subjective wellbeing (cognitive and affective).
Methods
Conducting a survey among 208 university students in Hamburg, Germany, the study used structural equation modeling to investigate how the effort level associated with commuting (classified as low, medium, high) influences wellbeing dimensions.
Results
Findings show that high-effort commuting modes positively correlate with decisional autonomy and cognitive wellbeing. Furthermore, both high- and low-effort commuting modes enhance affective autonomy, while intermodal commuting negatively affects it. The research also indicates that the need for autonomy moderates the relationship between low-effort commuting modes and affective autonomy.
Conclusions
These insights provide guidance for universities seeking to improve student wellbeing and policymakers focused on urban planning and transportation strategies, especially in large urban areas such as Hamburg.
The level of satisfaction of tourists with services in tourist destinations is becoming increasingly important for businesses and organizations related to the industry. The following article focuses on exploring the issues related to the development of transportation services in the tourism sector of Khorezm region. The research
identifies the satisfaction levels of domestic and foreign tourists with the transport infrastructure services in the region, as well as the key features of transport services that are important to them. Therefore, the study applies the "Importance-Satisfaction Analysis" (ISA) method to identify factors influencing tourist satisfaction.
Туристларнинг туристик дестинациялардаги хизматлардан қониқиш даражаси сайёҳлик саноати билан боғлиқ корхона ва ташкилотлар учун тобора муҳим аҳамият касб этмоқда. Ушбу мақолада Хоразм вилоятининг туризм соҳасида транспорт хизматларини ривожлантириш билан боғлиқ масалаларни ўрганишга асосий эътибор қаратилган. Тадқиқот маҳаллий ва хорижий сайёҳларнинг минтақадаги транспорт инфратузилмаси хизматларидан қониқиш даражаси ҳамда улар учун муҳим бўлган транспорт хизматларининг асосий хусусиятларини аниқлаб берган. Шунинг учун тадқиқотда туристлар қониқишига таъсир этувчи омилларни аниқлаш учун “Муҳимлик-Қониқиш Таҳлили” (Imporatce-Satisfaction Analysis) методи қўлланилган.
Purpose
Drawing on the reciprocity principle of social exchange theory situated within Service-dominant Logic, this study aims to examine how customers’ perception of knowledge sharing in co-production, their inherent scepticism and prosocial orientation relate to their willingness to co-create and provide feedback on services. The authors also explored the interplay between these factors to identify conditions in configurations comprising scepticism, which may help navigate its adverse effects.
Design/methodology/approach
The authors surveyed 556 online and offline mobile payment service users. They used a combination of partial least squares structural equation modelling (PLS-SEM) to assess the relationships among variables, and fuzzy-set qualitative comparative analysis (fsQCA) to identify configurations associated with feedback behaviour.
Findings
The study determined that customer perception of co-production knowledge sharing is positively associated with willingness to co-create and feedback behaviour. Additionally, prosocial orientation positively affects this relationship, while scepticism has an adverse effect. Willingness to co-create mediates the relationship between customer perception of co-production knowledge sharing and feedback behaviour. The fsQCA findings revealed configurations for potentially navigating doubts regarding feedback. To encourage valuable customer feedback, businesses may consider promoting a collaborative and supportive atmosphere, emphasising shared advantages or building trust even among hesitant and doubtful individuals.
Originality/value
This study uniquely examines how both prosocial tendencies and scepticism relate to customer feedback behaviour in co-creation by using a hybrid PLS-SEM/fsQCA approach to identify co-existing conditions in configurations comprising scepticism that may help navigate its adverse effects and leverage customer feedback for business improvement.
Public transportation serves as a critical infrastructure in developing countries, essential for promoting mobility and sustainability. However , traditional transit systems often contribute to environmental degradation through emissions. Recognising this challenge, nations such as India are actively pursuing strategies to reduce energy consumption and carbon emissions. An important initiative involves integrating electric buses into urban transit systems. To optimise the effectiveness of these electric bus services and encourage greater public transportation usage, it is essential to align service offerings with customer needs and expectations. This research aims to assess customer satisfaction among electric bus users in Aligarh using the Customer Satisfaction Index (CSI) analysis. Critical attributes such as affordability, safety, comfort, and accessibility will be examined to identify areas for improvement. An analysis will be conducted to gain insights into service quality attributes crucial for enhancing customer satisfaction in public transportation operations and the strategies for improving customer satisfaction to be defined.
Transport quality has long been recognized as an important factor in influencing travelers’ behavior, and transport terminal quality undoubtedly plays no small part. Indeed, transit promotion policies explicitly based on qualitative factors and high-standard architecture are increasingly being adopted in designing new bus terminals and stops. High architectural standards can be found in several bus terminals worldwide. Nevertheless, the literature in transport sector has yet to explore the impact of bus terminal “hedonic quality” on users’ behavior or use their willingness to pay (WTP) in cost–benefit analyses or other transport policy applications. Hedonic value is here intended as the aggregate of all elements related to travelers’ pleasure in spending time in a terminal where architectural beauty and the passenger services offered are arguably the most visible and representative attributes. Within this context, we propose a quantitative analysis of the perceived hedonic value of bus nodes in terms of users’ WTP (pure preference) for a high-quality bus terminal. To this end a discrete choice experiment based on a visual immersive experience was performed, and data were collected from 324 residents of Milan (Italy) traveling for tourism. Different binomial Mixed Logit models with panel data and random coefficients were estimated for the purpose. Monetary valuation of pure preference for using a high-quality bus terminal was estimated with a mean of about 25 % of the average trip cost observed for the case study considered. This pure preference means that the Italian tourist is willing to spend up to €4.35/trip more for a high-quality bus waiting space or travel up to 28.2 min/trip more, instead of using a traditional bus terminal for the same trip. Category-specific analyses show that females > 30 years old have a greater pure preference for a high-quality bus terminal (up to + 220 %) against males and young users. The employed also have a higher (+42 %) pure preference for the beauty of a bus terminal against others. The results of this paper should be compared with those from other case studies as they have a potential impact for transportation planning applications, underling the importance of also incorporating “hedonic quality” as explicit design variables for new/revamped transportation hub. At the same time, new challenges are posed for modeling user behavior and determining quality-related indicators and measures.
This study attempts to explore the factors impacting customer satisfaction in Nepal’s banking industry with a focus on the service quality that the banks offer. The respondent and the study area of the authors are 20 banks located in the Kathmandu Metropolis. Descriptive statistics, Pearson correlation analysis and regression analysis were employed to assess the subjects under study. The Pearson correlation results indicated a positive correlation between customer satisfaction and service quality characteristics. The ordinary Least Squares (OLS) regression model showed tangibility and empathy as key factors. The regression model, however demonstrates tangibility, responsiveness, and empathy as significant in influencing customer satisfaction. Study findings affirm the validity of hypothesis (H1) and highlight the importance of tangibility, responsiveness, and empathy in predicting customer satisfaction, suggests the enhancement of banks’ competitive advantage by improving their service quality.
This meta-analysis compiles data from 30 studies on the quality of public transport services conducted in different countries. The studies collectively investigate different forms of public transportation, such as buses, paratransit, and rail services, utilizing a range of methodological approaches. The recurring themes in service quality are key dimensions such as reliability, responsiveness, assurance, empathy, and tangibles. The analysis demonstrates that these dimensions have a significant impact on user satisfaction, perceived value, and behavioural intentions. This emphasizes the widespread relevance of service quality measures such as SERVQUAL and SERVPERF. Furthermore, the results emphasize the differences in how service quality is perceived in different regions and the urgent requirement for targeted policy interventions to improve public transportation systems worldwide.
This paper introduces new forms, sampling and estimation approaches fordiscrete choice models. The new models include behavioral specifications oflatent class choice models, multinomial probit, hybrid logit, andnon-parametric methods. Recent contributions also include new specializedchoice based sample designs that permit greater efficiency in datacollection. Finally, the paper describes recent developments in the use ofsimulation methods for model estimation. These developments are designed toallow the applications of discrete choice models to a wider variety ofdiscrete choice problems. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/47225/1/11002_2004_Article_138116.pdf
Preface
Introduction
Transportation is integral to developed societies. It is responsible for personal mobility which includes access to services, goods, and leisure. It is also a key element in the delivery of consumer goods. Regional, state, national, and the world economy rely upon the efficient and safe functioning of transportation facilities.
In addition to the sweeping influence transportation has on economic and social aspects of modern society, transportation issues pose challenges to professionals across a wide range of disciplines including transportation engineers, urban and regional planners, economists, logisticians, systems and safety engineers, social scientists, law enforcement and security professionals, and consumer theorists. Where to place and expand transportation infrastructure, how to safely and efficiently operate and maintain infrastructure, and how to spend valuable resources to improve mobility, access to goods, services and healthcare, are among the decisions made routinely by transportation-related professionals.
Many transportation-related problems and challenges involve stochastic processes that are influenced by observed and unobserved factors in unknown ways. The stochastic nature of these problems is largely a result of the role that people play in transportation. Transportation-system users are routinely faced with decisions in contexts such as what transportation mode to use, which vehicle to purchase, whether or not to participate in a vanpool or telecommute, where to relocate a business, whether or not to support a proposed light-rail project and whether to utilize traveler information before or during a trip. These decisions involve various degrees of uncertainty. Transportation-system managers and governmental agencies face similar stochastic problems in determining how to measure and compare system measures of performance, where to invest in safety improvements, how to efficiently operate transportation systems and how to estimate transportation demand. As a result of the complexity, diversity, and stochastic nature of transportation problems, the methodological toolbox required of the transportation analyst must be broad.
Approach
The third edition of Statistical and Econometric Methods offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics, to address reader and reviewer comments on the first and second editions, and to provide an increasing range of examples and corresponding data sets.
This book describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. Every book must strike an appropriate balance between depth and breadth of theory and applications, given the intended audience. This book targets two general audiences. First, it can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. There is sufficient material to cover two 3-unit semester courses in statistical and econometric methods. Alternatively, a one semester course could consist of a subset of topics covered in this book. The publisher’s web-site contains the numerous datasets used to develop the examples in this book so that readers can use them to reinforce the modeling techniques discussed throughout the text. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Sufficient analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications.
Data-Driven Methods vs. Statistical and Econometric Methods
In the analysis of transportation data, four general methodological approaches have become widely applied: data-driven methods, traditional statistical methods, heterogeneity models, and causal inference models (the latter three of which fall into the category of statistical and econometric methods and are covered in this text). Each of these methods have an implicit trade-off between practical prediction accuracy and their ability to uncover underlying causality. Data-driven methods include a wide range of techniques including those relating to data mining, artificial intelligence, machine learning, neural networks, support vector machines, and others. Such methods have the potential to handle extremely large amounts of data and provide a high level of prediction accuracy. On the down side, such methods may not necessarily provide insights into underlying causality (truly understanding the effects of specific factors on accident likelihoods and their resulting injury probabilities). Traditional statistical methods provide reasonable predictive capability and some insight into causality, but they are eclipsed in both prediction and providing causal insights by other approaches Heterogeneity models extend traditional statistical and econometric methods to account for potential unobserved heterogeneity (unobserved factors that may be influencing the process of interest). Causal-inference models use statistical and econometric methods to focus on underlying causality, often sacrificing predictive capability to do so.
Even though data-driven methods are often a viable alternative to the analysis of transportation data if one is interested solely in prediction and not interested in uncovering causal effects, because the focus of this book is uncovering issues of causality using statistical and econometric methods, data-driven methods are not covered.
Chapter topics and organization
Part I of the book provides statistical fundamentals (Chapters 1 and 2). This portion of the book is useful for refreshing fundamentals and sufficiently preparing students for the following sections. This portion of the book is targeted for students who have taken a basic statistics course but have since forgotten many of the fundamentals and need a review.
Part II of the book presents continuous dependent variable models. The chapter on linear regression (Chapter 3) devotes additional pages to introduce common modeling practice—examining residuals, creating indicator variables, and building statistical models—and thus serves as a logical starting chapter for readers new to statistical modeling. The subsection on Tobit and censored regressions is new to the second edition. Chapter 4 discusses the impacts of failing to meet linear regression assumptions and presents corresponding solutions. Chapter 5 deals with simultaneous equation models and presents modeling methods appropriate when studying two or more interrelated dependent variables. Chapter 6 presents methods for analyzing panel data—data obtained from repeated observations on sampling units over time, such as household surveys conducted several times to a sample of households. When data are collected continuously over time, such as hourly, daily, weekly, or yearly, time series methods and models are often needed and are discussed in Chapters 7 and 8. New to the 2nd edition is explicit treatment of frequency domain time series analysis including Fourier and Wavelets analysis methods. Latent variable models, discussed in Chapter 9, are used when the dependent variable is not directly observable and is approximated with one or more surrogate variables. The final chapter in this section, Chapter 10, presents duration models, which are used to model time-until-event data as survival, hazard, and decay processes.
Part III in the book presents count and discrete dependent variable models. Count models (Chapter 11) arise when the data of interest are non-negative integers. Examples of such data include vehicles in a queue and the number of vehicle crashes per unit time. Zero inflation—a phenomenon observed frequently with count data—is discussed in detail and a new example and corresponding data set have been added in this 2nd edition. Logistic Regression is commonly used to model probabilities of binary outcomes, is presented in Chapter 12, and is unique to the 2nd edition. Discrete outcome models are extremely useful in many study applications, and are described in detail in Chapter 13. A unique feature of the book is that discrete outcome models are first considered statistically, and then later related to economic theories of consumer choice. Ordered probability models (a new chapter for the second edition) are presented in Chapter 14. Discrete-continuous models are presented in Chapter 15 and demonstrate that interrelated discrete and continuous data need to be modeled as a system rather than individually, such as the choice of which vehicle to drive and how far it will be driven.
Finally, Part IV of the book contains massively expanded chapter on random parameters models (Chapter 16), a new chapter on latent class models (Chapter 17), a new chapter on bivariate and multivariate dependent variable models (Chapter 18) and an expanded chapter on Bayesian statistical modeling (Chapter 19). Models that deal with unobserved heterogeneity (random parameters models and latent class models) have become the standard statistical approach in many transportation sub-disciplines and Chapters 16 and 17 provide an important introduction to these methods. Bivariate and multivariate dependent variable models are encountered in many transportation data analyses. Although the inter-relation among dependent variables has often been ignored in transportation research, the methodologies presented in Chapter 18 show how such inter-dependencies can be accurately modeled. The chapter on Bayesian statistical models (Chapter 19) arises as a result of the increasing prevalence of Bayesian inference and Markov Chain Monte Carlo Methods (an analytically convenient method for estimating complex Bayes’ models). This chapter presents the basic theory of Bayesian models, of Markov Chain Monte Carlo methods of sampling, and presents two separate examples of Bayes’ models.
The appendices are complementary to the remainder of the book. Appendix A presents fundamental concepts in statistics which support analytical methods discussed. Appendix B provides tables of probability distributions used in the book, while Appendix C describes typical uses of data transformations common to many statistical methods.
While the book covers a wide variety of analytical tools for improving the quality of research, it does not attempt to teach all elements of the research process. Specifically, the development and selection of research hypotheses, alternative experimental design methodologies, the virtues and drawbacks of experimental versus observational studies, and issues involved with the collection of data are not discussed. These issues are critical elements in the conduct of research, and can drastically impact the overall results and quality of the research endeavor. It is considered a prerequisite that readers of this book are educated and informed on these critical research elements in order to appropriately apply the analytical tools presented herein.
Simon P. Washnington
Mathew G. Karlaftis
Fred L. Mannering
Panigiotis Ch. Anastasopoulos
The project conceived in 1929 by Gardner Murphy and the writer aimed first to present a wide array of problems having to do with five major "attitude areas"--international relations, race relations, economic conflict, political conflict, and religion. The kind of questionnaire material falls into four classes: yes-no, multiple choice, propositions to be responded to by degrees of approval, and a series of brief newspaper narratives to be approved or disapproved in various degrees. The monograph aims to describe a technique rather than to give results. The appendix, covering ten pages, shows the method of constructing an attitude scale. A bibliography is also given.
The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.
Extending the quality of public transport. Final Report and its Annex: Practical Handbook
- Rtd Eu
- Programme
EQUIP, 2000. Extending the quality of public transport. Final Report and its Annex:
Practical Handbook, EU, RTD Programme.
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and services-public passenger transport-service quality definition, targeting
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PORTAL, 2003. Promotion of results in transport research and learning. Final
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Quality approach in tendering/contracting urban public transport operations
QUATTRO, 1998. Quality approach in tendering/contracting urban public transport
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A handbook for measuring customer satisfaction and service quality
Transportation Research Board, 1999. A handbook for measuring customer
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Transit Capacity and Quality of Service Manual
Transportation Research Board, 2004. Transit Capacity and Quality of Service
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The demand for public transport: a practical guide
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