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Factors affecting bus users’ satisfaction in times of economic crisis
Abstract
This paper continues the research effort that the authors begun in 2008 on the quality factors that affect adoption of public transportation and retention of its users. The objective of this paper is to explore the impacts of the deep, 7-year economic crisis, on the perceptions of public transport users, with bus as their main transport mode, about service quality. Data from three user-satisfaction surveys that were conducted in Athens in 2008 (pre-crisis), 2013 (mid-crisis) and 2017 (deep-crisis) are used for the analysis. Mann Whitney/Wilcoxon test is applied for the distribution comparison of the responses between the pairs of consecutive years (2008–2013 and 2013–2017), in order to measure the change in users’ preferences. Ordered logit models are developed for the user satisfaction and shift to public transportation after the beginning of the economic crisis.
The results of the analysis indicate that the satisfaction about quality attributes, such as service frequency, conditions at the stations and information provision, are important contributors of the total satisfaction, verifying the results of Tyrinopoulos and Antoniou (2008) and Efthymiou et al. (2014), but their impact varies over time. Despite the general decrease of commuting activities due to increase of unemployment, the shift to public transportation has increased. More specifically, demographic characteristics, such as age, occupation and gender, as well as qualitative factors, such as overall quality of service, service production, transfer quality, ticket services and environmental consciousness, have affected the decision of people to shift to and from public transportation.
... Only a few studies in the literature focus on user satisfaction in the context of public transport [8][9][10][11]. Available studies identify that frequency, reliability, driver behaviour, information, cleanliness, and comfort are typical factors that influence public transport users' satisfaction with services [2,[12][13][14]. Despite its enormous importance, user satisfaction studies are generally under-represented in the literature. ...
... Beirão and Cabral [13], Gadziński and Radzimski [28], Tyrinopoulos and Antoniou [29], and Efthymiou, Antoniou, and Tyrinopoulos [9] analysed the behaviour of public transport travellers and their perceived satisfaction with services in order to understand the underlying reasons for their preferred transport mode. They found that travellers had a strong preference for a reliable and well-coordinated transportation system. ...
... In addition, individual characteristics such as age, income, education level, household composition, travel budget, a drivers' license, and access to a motor vehicle affect mobility behaviour and the level of access to train services [9,[45][46][47]. Specifically, in order to attract potential train riders and increase ridership, train services should be designed according to the level of service preferred by current riders [13]. ...
In the public transport industry, travellers’ perceived satisfaction is a key element in understanding their evaluation of, and loyalty to ridership. Despite its notable importance, studies of customer satisfaction are under-represented in the literature, and most previous studies are based on survey data collected from a single city only. This does not allow a comparison across different transport systems. To address this underrepresentation, this paper reports on a study of train passengers’ satisfaction with the fare paid for their most recent home-based train trip in five Australian capital cities: Sydney, Melbourne, Brisbane, Adelaide, and Perth. Two data sources are used: a nation-wide survey, and objective information on the train fare structure in each of the targeted cities. In particular, satisfaction with train fares is modelled as a function of socio-economic factors and train trip characteristics, using a random parameters ordered Logit model that accounts for unobserved heterogeneity in the population. Results indicate that gender, city of origin, transport mode from home to the train station, eligibility for either student or senior concession fare, one-way cost, and waiting time as well as five diverse interaction variables between city of origin and socio-economic factors are the key determinants of passenger satisfaction with train fares. In particular, this study reveals that female respondents tend to be less satisfied with their train fare than their male counterparts. Interestingly, respondents who take the bus to the train station tend to feel more satisfied with their fare compared with the rest of the respondents. In addition, notable heterogeneity is detected across respondents’ perceived satisfaction with train fare, specifically with regard to the one-way cost and the waiting time incurred. An intercity comparison reveals that a city’s train fare structure also affects a traveller’s perceived satisfaction with their train fare. The findings of this research are significant for both policy makers and transport operators, allowing them to understand traveller behaviours, and to subsequently formulate effective transit policies.
... Previous studies that explore factors influencing the quality of public transport (PT) service often focus on the availability of PT, accessibility and affordability (Efthymiou et al. 2018;Saghapour, Moridpour, and Thompson 2016;Sohail, Maunder, and Miles 2004). For instance, Saghapour, Moridpour, and Thompson (2016) point out that in the suburbs of Melbourne (Australia), PT has a frequent service but is limited to buses. ...
... There is a growing body of literature exploring factors that influence public transport service quality (Lucas 2011;Mashiri, Molomo, and Venter 2013;Nkurunziza et al. 2012;Plano, Behrens, and Zuidgeest 2020). From these studies, it can be depicted that they often focus on a set of factors related to the Availability of PT (bus frequency), Accessibility (type of buses) and Affordability (bus fare) (Deepa et al. 2022;Efthymiou et al. 2018;Hugo and Stanbury 2001;Plano 2022;Tembe et al. 2019). However, these factors are strongly influenced by the temporal and spatial factors where the bus trip takes place (Adom-Asamoah, Asibey, and Nyarko 2021; Tao et al. 2018;Vanderschuren, Phayane, and Gwynne-Evans 2019), and the type of bus operator (Spooner et al. 2020). ...
The Maputo Metropolitan Area's bus transport service is comprised of both formal and informal operations, characterized by declined service quality. To improve service quality, the Maputo Metropolitan Transport Agency is transitioning to formal operations. The study aims to determine who experiences substandard bus service and where, to inform targeted actions. Data from 8,095 bus users were analysed using cluster analysis, Sankey diagrams, and multicriteria analysis, revealing four distinct behavioural clusters (C1–C4). C1 (Non-frequent-early evening) and C4 (Non-frequent-early morning) commuters experience low and very low service quality, respectively, needing increased bus frequency and easy-to-board buses. C2 (Non-frequent-daytime) commuters enjoy high service quality but could benefit from dedicated bus lanes to further improve frequency and convenience. C3 (Frequent-short travel time) commuters experience very high service quality but require direct bus lines from the suburbs to the CBD to reduce travel costs. The study findings form a basis for targeted bus service improvements.
... Previous studies that explore factors influencing the quality of public transport (PT) service often focus on the availability of PT, accessibility and affordability (Efthymiou et al. 2018;Saghapour, Moridpour, and Thompson 2016;Sohail, Maunder, and Miles 2004). For instance, Saghapour, Moridpour, and Thompson (2016) point out that in the suburbs of Melbourne (Australia), PT has a frequent service but is limited to buses. ...
... There is a growing body of literature exploring factors that influence public transport service quality (Lucas 2011;Mashiri, Molomo, and Venter 2013;Nkurunziza et al. 2012;Plano, Behrens, and Zuidgeest 2020). From these studies, it can be depicted that they often focus on a set of factors related to the Availability of PT (bus frequency), Accessibility (type of buses) and Affordability (bus fare) (Deepa et al. 2022;Efthymiou et al. 2018;Hugo and Stanbury 2001;Plano 2022;Tembe et al. 2019). However, these factors are strongly influenced by the temporal and spatial factors where the bus trip takes place (Adom-Asamoah, Asibey, and Nyarko 2021; Tao et al. 2018;Vanderschuren, Phayane, and Gwynne-Evans 2019), and the type of bus operator (Spooner et al. 2020). ...
The Maputo Metropolitan Area's bus transport service is comprised of both formal and informal operations, characterized by declined service quality. To improve service quality, the Maputo Metropolitan Transport Agency is transitioning to formal operations. The study aims to determine who experiences substandard bus service and where, to inform targeted actions. Data from 8,095 bus users were analysed using cluster analysis, Sankey diagrams, and multicriteria analysis, revealing four distinct behavioural clusters (C1–C4). C1 (Non-frequent-early evening) and C4 (Non-frequent-early morning) commuters experience low and very low service quality, respectively, needing increased bus frequency and easy-to-board buses. C2 (Non-frequent-daytime) commuters enjoy high service quality but could benefit from dedicated bus lanes to further improve frequency and convenience. C3 (Frequent-short travel time) commuters experience very high service quality but require direct bus lines from the suburbs to the CBD to reduce travel costs. The study findings form a basis for targeted bus service improvements.
... The objective of this paper is to identify implicitly and not previously measured factors in a representative medium-sized European city; this paper applies an Exploratory Factor Analysis (EFA), which is a widespread methodology in transport studies [14][15][16]. Then, the impact of these factors on the Overall Satisfaction (OS) is evaluated by conducting an Ordinal Logistic Regression Model [17]. ...
... Other studies have analysed users´ satisfaction under specific and contextual conditions like economic crisis periods [15]. Lierop and El-Geneidy [3] used results from three user satisfaction surveys conducted in Athens between 2008 and 2014. ...
In recent years, the promotion and use of public transport (PT) has become key to overcoming the negative impacts of mobility, such as traffic congestion, high pollution (GHG), and traffic accidents. Improving users’ satisfaction and increasing the attractiveness of buses play an essential role in increasing PT patronage. Whilst most of the literature concentrates on large and complex bus systems, less attention has been paid to European medium-sized cities, the region’s most common urban configuration, where public transport mainly depends on bus services. To this end, a survey campaign was conducted on passengers of urban buses in Oviedo, Spain, a representative medium-sized city. An Exploratory Factor Analysis (EFA) was used to identify key user satisfaction factors. In this case, three factors were the most important: comfort and information, service performance, and integration. That was complemented by the overall satisfaction (OS) with services, which was used for ranking the importance of the factors using an ordinal logistic regression model; comfort and information appear as the most important. These findings can serve bus operators to identify service-related attributes that need more attention or investment to increase users’ satisfaction and to make the service attractive to potential users.
... Perceived value, which is affected by service quality (Cronin et al., 2000;Zeithaml, 1988) was found to be a predictor of satisfaction with public transport (Cronin et al., 2000;Petrick, 2004;Woodruff, 1997). Commonly-used statistical techniques to identify the key factors affecting people's perceptions of the transport service include: exploratory factor analysis (Hu et al., 2015;Jomnonkwao and Ratanavaraha, 2016;Nwachukwu, 2014;Popuri et al., 2011;Efthymiou et al., 2018), confirmatory factor analysis (Hu et al., 2015;Jomnonkwao and Ratanavaraha, 2016;Ratanavaraha et al., 2016), and structural equation modelling (De Oña et al., 2013;Machado-León et al., 2016;Lai and Chen, 2011;Eboli and Mazzulla, 2008;Jen and Hu, 2003). Also, the relative weight of the list of tested factors is analysed using regression analysis (Chang and Yeh, 2005;Nwachukwu, 2014), ordered logit models (Rojo et al., 2013), ordered probit models (Bordagaray et al., 2014;Rojo et al., 2013), and multinomial logit models (Dell'Olio, Ibeas, and Cecin, 2011;Eboli and Mazzulla, 2008). ...
... However, it has limitations because the level of service and its description of the service quality are assigned by the analyst. Tyrinopoulos and Antoniou (2008) and Efthymiou et al. (2018) used factor analysis, ordered logit models and triangle plots of three identified prevalent factors to study the impacts of service quality attributes on overall satisfaction across different groups of users. ...
The successful adoption of a product or service by its target market or users relies on delivering a product or service in line with their needs and expectations. Failure to do so will likely result in a low rate of uptake or use of the product or service. This study sought to identify the criteria by which potential users of a first-/last-mile automated bus (AB) service would evaluate the service, and accordingly decide whether to use or disregard the service. This research investigated various explanatory factors affecting users’ perceptions of the service’s quality and utility, and which enhanced or diminished their intentions to use it. The data analysed in this study was collected from a survey conducted in February and March of 2018 in Stockholm, Sweden, during a trial operation of a first-/last-mile AB service. Three-factor theory analysis, commonly used to analyse services, was applied to this data in order to identify users’ core perceptions about the service, which in turn influence their intention-to-use the service. Structural equation modelling was used to identify the significant factors that influence the identified perceptions influencing the intention-to-use the service. This study found that different subgroups of users prioritised different attributes. Prospective users (with no prior experience with the service) were most concerned with the frequency of service. Their intention-to-use the service greatly increased when the service frequency is comparable to the service frequency of a regular public bus service. Experienced users’ intentions to continue using the service greatly increased when the buses were made more comfortable. This study additionally found that users’ perceptions of the service’s quality were also influenced by numerous factors including the passenger’s age, income level, preferred mode of travel for daily trips, preferred mode of travel for first-/last-mile trips, being tech-savvy or not, and their level of familiarity with automated driving technology.
... Furthermore, public transit ridership in many metropolitan areas in the US dropped significantly, a trend that unlike VMT did not return to pre-recession levels (per capita transit use has dropped about 9.7% since 2014) (The Transport Politic 2018). Other studies also considered recession impacts on public transit but mostly in the context of European countries (Efthymiou et al. 2018;Ulfarsson et al. 2015;Cascajo et al. 2018). ...
... This partition of non-work activities into five timeslots also appears in prior studies (Damm 1982;Bhat and Singh 2000). For people who work only at home and do not make any work tours, we considered the longest work duration activity as a reference point and distribute 'before' and 'after' out-of-home non-work activities accordingly. ...
This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is defined as a sequence of trips and activities that begins and ends at home and contains at least one non-home activity. Tours are classified based on the presence of work and/or non-work activities. We are interested in investigating how a recession can affect an individual’s tour choices. We developed a rigorous methodological framework by using multi-group structural equation modeling (SEM) to analyze changes in tour choice. In particular, we developed a causal structure conceptualsizing the interrelationships among socio-demographic and economic characteristics, activity-travel participation, and the choice of various work and non-work tours. Using data from the American Time Use Survey (ATUS), the study found that activity-travel relationships and their role in tour choice differed in the recession year (2009) compared to pre- and post-recession years (2009 and 2012, respectively). By analyzing temporal changes in causal structure, we identified four sub-trend groups defined by: (1) norms that did not change in pre-, during, and post-recession years, (2) norms that changed during the recession but returned to the old norm, (3) norms that changed during the recession and were maintained as new norm, and finally (4) 2006 norms that did not change during the 2009 recession but changed after the recession. Via analysis of multiple group SEM, we identified instances of each of these cases and provided potential rationales in the context of how a recession can influence norms and thus can affect activity-travel behavior.
... Selection of attributes has been found to vary with cities (Abenoza, Cats, & Susilo, 2017;Fellesson & Friman, 2012), passengers' socioeconomic characteristics (R. de Oña & de Oña, 2013;Morton, Caulfield, & Anable, 2016), transit types (Celik, Aydin, & Gumus, 2014;Machado-León, de Oña, Baouni, & de Oña, 2017;Tyrinopoulos & Antoniou, 2008), route types (Bordagaray, Dell'Olio, Ibeas, & Cecín, 2014; Chica-Olmo, Gachs-Sánchez, & Lizarraga, 2018), and time period (Aydin, 2017;Efthymiou, Antoniou, Tyrinopoulos, & Skaltsogianni, 2018). Sources of information are literature available, service operators/providers' surveys, and/or pilot surveys. ...
... Selection of attributes has been found to vary with cities (Abenoza, Cats, & Susilo, 2017;Fellesson & Friman, 2012), passengers' socioeconomic characteristics (R. de Oña & de Oña, 2013;Morton, Caulfield, & Anable, 2016), transit types (Celik, Aydin, & Gumus, 2014;Machado-León, de Oña, Baouni, & de Oña, 2017;Tyrinopoulos & Antoniou, 2008), route types (Bordagaray, Dell'Olio, Ibeas, & Cecín, 2014; Chica-Olmo, Gachs-Sánchez, & Lizarraga, 2018), and time period (Aydin, 2017;Efthymiou, Antoniou, Tyrinopoulos, & Skaltsogianni, 2018). Sources of information are literature available, service operators/providers' surveys, and/or pilot surveys. ...
This study examines stakeholders’ perspective about nine major attribute sets which comprehensively define transit service quality. A novel linguistic AHP scale was used to form a judgement matrix based on experts’ opinion which simplifies the understanding between two criteria and thus respondents’ (stakeholders) fatigue and complexities reduces while filling the survey. The Saaty’s bi-directional scale is made unidirectional by applying the linguistic scale as extremely lower (reciprocal values) to equal and then to extremely higher. Stakeholders were from different fields of expertise like academia, research, policy makers, service operators or providers, and industry professionals. A judgement matrix was arrived at through Fuzzy-AHP analysis while using disaggregated and aggregated opinions of the stakeholders. The stakeholders’ opinion was analyzed as: individual stakeholders’ groups; academicians vs non-academicians; and combined opinion. One-way ANOVA test was performed to examine the similarity in decision making across the stakeholders. Though no statistical significance was found across stakeholder level, however, the perceptions vary or sync across the groups based on attributes’ inherent value or characteristics. The matrix allowed the categorization of the attributes based on their importance as highly, moderately, and least important. Higher importance has gone to infrastructure (system infrastructure, and ease and convenience) and operational attributes (Customer service, comfort, and service frequency) whereas, lower importance has gone to functional attributes (safety, security, and travel time reliability). The analysis allows us to arrive at probable weights which shall be given to the different attributes while planning for the improvements in the transit services in a geographical region.
... Service quality has been found to be the most important determinant of satisfaction for bus users (Efthymiou et al., 2014). More recent studies found that some factors concerning public transport satisfaction, such as on-time performance and network coverage were important throughout the years, while others such as vehicle cleanliness and environmental friendliness were deemed more important before the economic crisis than afterwards (Efthymiou et al., 2018). The COVID-19 pandemic and pilot interventions in the city center, aiming to promote walking and cycling, showed early reports of decreased public transport usage, yet increased walking and cycling especially in the city center (Baig et al., 2022;Papadimitriou, 2020). ...
This study investigates how the use of sustainable transport modes relates to travel satisfaction (general evaluation of travel) and travel affect (emotions during travel) in car-dependent compact cities. Thereby, the study provides evidence on sustainable mobility and travel-related well-being in a context of compact urban form but inadequate provisions for public transport, walking, and cycling. A mixed-methods approach was applied comprising quantitative and qualitative analyses of data from the two major cities of Greece, i.e., Athens and Thessaloniki. Travel satisfaction and travel affect are found to be highest for those who walk for commuting, independently of travel time and other factors. Conversely, travel satisfaction and travel affect are lowest for public transport users, largely due to very long travel times but also poor public transport services in one of the two cities. Results indicate that the experience of traveling by public transport, car, and motorcycle within urban areas greatly depends on transport provision and policies. Overall, findings support the idea that to shift to pleasant, satisfying, and sustainable mobility in car-dependent compact cities, car restrictions should be accompanied by massive improvements in public transport, high-quality walking and cycling infrastructure, and an integrated coordination of different modes.
... Financial factors consider many money-related decisions and results, like how much profit the company makes and how much it costs to run the system (Xu et al. 2018;Arora et al. 2022). Achieving financial stability is important for any transportation system, and it leads to more research and development (R&D) in the sector (Efthymiou et al. 2018). Table 1(c) discusses the financial factors that affect the public transportation system. ...
The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer’s trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19.
... Alhelalat, et al. [96], Ju, et al. [97], Radojevic, et al. [98,99], and Radojevic, et al. [100] all point out that a comfortable bed, a clean room and bathroom, and a certain amount of aesthetic appeal are considered important and necessary features to achieve customer satisfaction-these are also factors that will influence customer evaluations of their staying experiences. Other studies on public transportation also concluded that cleanliness and comfort are the most important factors when it comes to (dis)satisfaction, although the impact of these factors does differ depending on the socio-economic characteristics of the users [89,[101][102][103][104][105][106]. Appendix A Table A1 demonstrates a total of 17 rules. ...
Featured Application
Text Mining, Apriori Algorithm, Association Rules, Rule-based Machine Learning Method, Web Graph Analysis, Content Analysis, Qualitative Projective Technique, Textual Complaints.
Abstract
By looking at complaints made by guests of different star-rated hotels, this study attempts to detect associations between complaint attributions and specific consequences. A multifaceted approach is applied. First, a content analysis is conducted to transform textual complaints into categorically structured data. Furthermore, a web graph analysis and rule-based machine learning method are applied to discover potential relationships among complaint antecedents and consequences. These are validated using a qualitative projective technique. Using an Apriori rule-based machine learning algorithm, optimal priority rules for this study were determined for the respective complaining attributions for both the antecedents and consequences. Based on attribution theory, we found that Customer Service, Room Space, and Miscellaneous Issues received more attention from guests staying at higher star-rated hotels. Conversely, cleanliness was a consideration more prevalent amongst guests staying at lower star-rated hotels. Qualitative research was conducted to corroborate the findings. Other machine learning techniques (i.e., Decision Tree) build rules based on only a single conclusion, while association rules attempt to determine many rules, each of which may lead to a different conclusion. The main contributions of this study lie in the fact that this is one of the first attempts to detect correlations within the online complaining behaviors of guests of different star-rated hotels by utilizing rule-based machine learning.
... There are many applications of hybrid choice models among existing studies such as (Córdoba & Jaramillo, 2012;Efthymiou et al., 2017Efthymiou et al., , 2018Kamargianni et al., 2014;Sottile et al., 2015;Politis et al., 2012). Córdoba and Jaramillo (2012) stated that individual psychological variables influence a user's behaviour and incorporate the latent personality variable in estimating a hybrid discrete choice model. ...
The report draws on a variety of different sources of
information to produce a comprehensive and complete critical evaluation of the existing body of knowledge
about the travel behaviour change modelling, monitoring and evaluation especially within the context of
MaaS and a car-centric region. This will lead to the selection of robust data collection methods, travel
behaviour change theories and modelling approaches to understand the rationale/motivation behind travel
behaviours. The aim of this literature review is to show the methods can be used to model, monitor, and evaluate travel behaviour of MaaS and non-MaaS
users while observing and analysing the differences in travel behaviour for these groups.
... The output of an ordinal logistic regression contains an intercept for each level of the response variable except one, and a single slope for each explanatory variable (Efthymiou et al. 2018;Basbas et al., 2013;Milioti et al., 2020). The dependent variable in the model of the intention to purchase has 5 categories, so there are four thresholds: from not at all to a little, from a little to moderate, from moderate to a high and from high to very high. ...
Electric vehicle proliferation is still at exceptionally low level in Greece. The subsidy program “I move electrically” aims to accelerate the transition to EVs providing incentives both for company and private electric vehicles. In order to analyze the factors that affect the consumers’ intention to purchase private electric vehicles in Attica a questionnaire survey was conducted. Discrete choice models were developed to analyze the factors that influence the intention of users to purchase and willingness to pay extra for an EV compared to a conventional car. Travel and demographic characteristics, provision of financial incentives, environmental awareness, charging time and charging infrastructure were found to affect the intention to purchase an EV in Greece. The paper concludes with policy measures and recommendations regarding the charging infrastructure, the provision of financial incentives and marketing policies that could support the adoption of EVs.
... Despite the heterogeneities across rider segments, the transport literature has widely claimed that improving service quality is positively associated with riders' re-intention and word-of-mouth (Lai & Chen, 2011;Mouwen & Rietveld, 2013;Nguyen-Phuoc et al., 2020; van Lierop & El-Geneidy, 2016). It also positively stimulates a modal shift from private to public transport (Efthymiou et al., 2018;Redman et al., 2013). ...
Service quality is a determinant of increasing public transport rider satisfaction. However, understanding of service quality and satisfaction relations has been limited. This study seeks an appropriate method to demonstrate the nature of service quality-satisfaction relations. Thereby, research results can be methodologically, theoretically, and empirically defensible. The importance-performance analysis (IPA) and the three-factor theory, the most widely preferred for public transport service quality prioritization based on the importance of service factors to rider satisfaction, will be utilized. The study takes transit service in Ho Chi Minh City (HCMC), Vietnam, to demonstrate that the three-factor theory, which has been limitedly utilized despite being more advantageous and robust, is superior to the IPA. Although the extent to which the service quality factors affect satisfaction varied across rider segments, the types of service quality factors were found consistent. For example, captive riders considered all service factors as performance. Non-captive riders considered the environment factor as excitement. No basic factor was found across rider groups. This study contributes to the limited understanding of the non-linear and asymmetric relations between service quality and satisfaction of various rider groups, which is rarely found in transit service quality literature. Furthermore, it introduced a case study of Vietnamese urban transit services for the first time. It suggests that enhancing passenger information, rider care, and comfort are recommended as the most practical and economical measures in the short run. However, the city government should improve availability and accessibility to promote public transport ridership in the long run.
... Satisfaction has been the focus of many studies in the transport scientific literature, given the demonstrated relevance in attracting and retaining users. There are numerous studies, including PT infrastructure and combined modes (Abenoza et al. 2018;Hernandez et al. 2016;Susilo and Cats 2014), bus (Efthymiou et al. 2018;Echaniz et al. 2018;Figler et al. 2011), rail (Nathanail 2008;Zhang et al. 2017;Machado-León et al. 2017;Eboli and Mazzulla 2015;Eboli et al. 2018) and airlines (Chow 2015;Pakdil and Aydin 2007) An exhaustive literature review on this subject was developed by van Lierop et al. (2018), helpful for researchers and practitioners studying on this matter. ...
Bike-sharing systems (BSS) are gaining popularity in cities worldwide, as a part of a generalized strategy to mitigate the problems derived from motorized transportation (congestion, pollution, noise, etc.). These systems have proved to have positive effects on cities, moreover, many of them have reached a performance peak and require improvements to attract/retain users and compete against emerging soft mobility alternatives. Whilst there are broad studies evaluating BSS demand and design, less attention has been paid to user satisfaction and the complexities underlying the relationships between the system attributes importance. This study proposes a novel combination of two methodologies for satisfaction assessment that allows decision-makers to identify the most influential system attributes on user satisfaction. The combined methods are the direct, explicit, Importance Performance Analysis (IPA), and the nonlinear, implicit Three-Factor Theory (3FT), which combined generate a three-dimensional scheme that facilitates the comprehension of the results. The combination was applied to a dataset of Madrid´s BSS to identify the attributes that perform poorly, and then assess their implicit influence on satisfaction to establish improvement priorities. The results suggest that station occupancy and bicycle availability and totem functioning are key service attributes to enhance satisfaction. Also, the combination of the two methodologies makes it possible to differentiate that maintenance is a priority for subscribers and network extension for occasional users. The pedelec system is a key attribute that might help overcome Madrid´s unfavorable cycling environment. This user-centric evaluation is a valuable tool that guides precise measure implementation, service operation, future design, and planning oriented to increase ridership.
... He mentioned other factors in his analysis (gender, age, income, occupation, trip purpose, and the relative level of service offered by the available transport modes on the choice set of the traveler for a particular trip). (Dimitrios, Constantinos, & Yannis, 2017) found that factors that have affected the decisions of people to shift to and from public transportation are:( age, occupation, gender, quality of service, service production /transfer quality, ticket service, and environmental consciousness). (Ander, Oihane, Ainhoa, & Cruz, 2018) found that factors that affect an Individual's Choice are:( time, cost, comfort, and environmentally friendly awareness). ...
This study aims to calculate the financial and economic benefits of the
application of electric buses in an urban area in Egypt. This is done by estimating
the benefits and disbenefits of using this system in Benha, Egypt. In Egypt, there is
no clear method to determine the benefits and disbenefits of using electric buses.
Therefore, a logical way is used to determine the benefits and disbenefits of this
application and to set some policies. This is achieved through the application of the
sequential method (4-step model), which consists of four stages as follows: trip
generation, trip distribution, model split, and traffic assignment. The questionnaires
were designed to determine the factors that affect the choice of electric buses. The
data was analyzed and calibrated into a model which predicts the volume of demand
for electric buses, the importance of each variable was studied, and the advantages
and disadvantages of implementing the electric bus system in Egypt were studied.
The questionnaire provided three suggestions for using electric buses. The logistic
regression was used to find the best-proposed suggestion for using electric buses if it
was the first suggestion or to choose another suggestion according to the following
independent variables (travel time) and the following categorical variables (address,
gender, age, education, vehicle ownership, income, and trip purpose). The three
models were obtained and estimated to obtain the utility function of each suggestion.
From the analysis, the best suggestion is the first, as the total number of trips using
electric buses is larger than the other two suggestions. By comparing the air pollution
with and without electric buses, it is clear that the use of electric buses will reduce
air pollution by 69 %. The benefits of electric bus application in Benha, Egypt were
estimated by evaluating the money value of air pollution and the value of time. The
value of time was calculated by knowing the average travel time with and without
electric buses, the average salary from the questionnaire, and the total working hour.
Finally, the total reduction of the value of time was estimated and found to be 8.3
*10^5 LE.
... Congestion is the reason for low satisfaction with car commuting [23,24]. Service levels regarding transfers, connections, departure frequencies, platform facilities, and information acquisition are the reasons for low satisfaction with public transportation (buses and subways) [25][26][27]. For built environments, the residents of compact urban neighborhoods have better commuting satisfaction than residents of sprawling suburban neighborhoods [28]; the walking satisfaction can be explained by the safety, lack of congestion, and cleanliness of sidewalks [29]; the availability of bike lanes and whether buses are running along the bike lanes affect the commuting satisfaction for cyclists [30]. ...
Analyzing commuting-time satisfaction could help to improve the subjective well-being of society. This study aimed to explore the nonlinear relationship between commuting satisfaction and commuting times in different groups and its influencing factors. An empirical study was conducted in Kunming, China. Firstly, applying a random forest algorithm revealed that there was a nonlinear relationship between commuting satisfaction and commuting time. Secondly, the k-means clustering algorithm was used to divide the respondents into three types of commuter: short-duration-tolerant (group 1), medium-duration-tolerant (group 2), and long-duration-tolerant (group 3). It was found that the commuting-time satisfaction of these three clustered groups had different threshold effects. Specifically, the commuting satisfaction of group 1 showed a nonlinear downward trend, which decreased significantly at 12 and 28 min, respectively; the commuting satisfaction of group 2 rapidly decreased at 35 min; the commuting satisfaction of group 3 first increased in the range of 20–30 min, decreased significantly after 45 min, and decreased sharply above 70 min. These time thresholds were consistent with the ideal commuting times (ICTs) and tolerance thresholds of the commuting times (TTCTs) of the three clustered groups, which indicates that the ICT and TTCT had significant effects on commuting satisfaction. Lastly, the results of the multinominal logistic model showed that variables such as the commuting mode, job–housing distance, income, and educational background had significant effects on the three clustered groups. The policy implications of the study are that commuting circles should be planned with the TTCT as a constraint boundary and ICT as the optimal goal; in addition, different strategies should be adopted for different commuting groups to improve commuting satisfaction.
... In the first part, there are questions to measure the demographic characteristics of the participants (gender, age, education level, occupation, 7 regions of Turkey). In the second part of the survey, the Covid-19 psychological stress scale consisting of 13 statements , the public transportation satisfaction scale consisting of 23 questions (Efthymiou et al. 2018) were used. Participation (7 questions) and behavioral intention (3 questions) scales were adapted from the study carried out by Irtema et al. (2018). ...
... Some of the common techniques and tools used by researchers to analyse commuters' perception are factor analysis (Tyrinopoulos and Antoniou, 2008;Fellesson and Friman, 2012) and ordered logit models (Tyrinopoulos and Antoniou, 2008;Buehler and Pucher, 2012;Efthymiou and Antoniou, 2017), hybrid choice models combining latent variables in discrete choice models (Efthymiou et al. 2014(Efthymiou et al. , 2018, logistic regression models and neural networks, Structural Equation Models (SEM), as well as SEM-MIMIC models Allen et al., 2018. Tyrinopoulos and Antoniou (2008 suggest that less complex methods, such as factor analysis and principal component analysis, may give a quicker insight on relevant indicators of satisfaction. ...
Multimodality in Public Transport has been proven to be one of the main drivers of sustainability and economic feasibility for the last few decades. Consequently, user satisfaction for transfers is the key to adequately serving demand. This research studies on commuters’ perception of comfort at interchanges, focusing on the connection between metro systems and other modes. Satisfaction analysis and modelling is conducted using weighted regression, factor analysis and ordered logit models for nine transfers at major interchanges in two Indian cities (New Delhi and Kolkata) and one German city (Munich); aiming at revealing the differences in user satisfaction in developing and developed economy, and for different Public Transport quality and interchanges. The results indicate that factors of transfer quality, accessibility and physical hindrances are significant in Indian case and the human factor, and transfer quality are significant in the case of Munich, Germany. Additionally, it is found that perceived comfort differs on commuters’ experiences with transfer distance and time.
... In emerging economies like India, this has aggravated the already declining ridership rates in PT. The decline in PT patronage was hitherto attributed to factors such as the substandard services of the public transportation (PT) systems [4,16], the psycho-socio-economic features of the commuters [6,8,21,26], their travel characteristics, the appeal of private vehicle ownership and usage [20,22], and other miscellaneous factors. But with the COVID-19 pandemic, other factors like over-crowdedness [10,24], fear of contagion and safety concerns come into play [3,9,11,23]. ...
Public transport (PT) ridership has seen a continual decline over the past years as more people are opting to use private vehicles, contributing to increased traffic congestions, road accidents, pollution, etc. The COVID-19 pandemic has exacerbated this problem, with official guidelines discouraging the use of PT systems to prevent contagion. Passenger attraction policies for a post-pandemic phase should be formulated by examining the changes in daily trips brought about by the COVID-induced lockdowns. With data collected from employees working in Thiruvananthapuram city, the present study develops a post-lockdown mode-choice model using fuzzy logic programming to evaluate different policies to increase PT ridership. The policies such as introducing parking prohibition on major streets, reducing return-trip fares, improving PT coverage and supply, and early-bird pre-peak hour discounts were tested using sensitivity analysis and the choice model estimated a (private to PT) modal shift of 5.8%, 6.9%, 6.2% and 6.2%, respectively. It is concluded that passenger attraction policies should concentrate more on improving PT services than discouraging private modes to improve ridership.
... A number of recent studies have investigated the determinants of PT loyalty, based on the framework of satisfaction-loyalty theory. They have looked into the effects of service quality on passengers' satisfaction and their loyalty de Oña et al., 2016a;de Oña et al., 2013de Oña et al., , 2016bde Oña et al., 2016c;Dell'Olio et al., 2010Efthymiou et al., 2018;Figler et al., 2011;Foote et al., 2001;Shiftan et al., 2015). Regarding the results of previous studies, service quality is generally recognized as an antecedent of satisfaction, and exerts a positive impact on loyalty (de Oña, 2020). ...
Sustaining passengers' loyalty towards bus service has been regarded as the key to secure its market share. However, passengers are not homogenous in terms of behavioral loyalty or atti-tudinal loyalty. Therefore, the determinants to retain loyalty may differ across each group of passengers. This study proposed a data-fusion based clustering method to segment passengers. An empirical study of Xiamen, China was given. Specifically, by fusing the smart card data and the survey data, the method measured passengers' behavioral and attitudinal loyalty simultaneously. As a result, spurious-loyalty passengers were identified, who were characterized as behaviorally loyal but attitudinal disloyal; they held the most potential to shift to other transport modes. In order to retain the spurious-loyalty passengers, a novel model framework was built to investigate the determinants of driving them to continue using public transportation. The results indicated that the passengers' satisfaction fully mediated between service value and attitudinal loyalty, as found in previous studies. Service value was unveiled to exert a significant and positive impact on predicting the passengers' satisfaction and attitudinal loyalty. However, service value was not only determined by the passengers' utilitarian value (perceived service quality), but also involved with their hedonic value (emotional dependence on public transportation which came from the passengers' long-term involvement); hedonic value was demonstrated highly correlated with utilitarian value. In addition, we justified that utilitarian value could be separately measured by the quality of basic service attributes and the quality of value-added service attributes; they were revealed to exhibit non-linear and heterogeneous effects on the passengers' satisfaction. Moreover , the index score of variables was employed to indicate the specific service attributes that needed to be improved to sustain the targeted passengers; practical suggestions to the specific direction of improvement were provided for transport sectors and public transport operators.
... Although a large number of studies have explored the influencing factors of bus satisfaction, these studies mainly focus on the cities in developed countries [10][11][12][13][14][15][16][17][18][19] or large cities in developed regions of China [20]. Due to the obvious differences of economic development level, public transit infrastructure development, and residents' subjective satisfaction with public transit between the developed cities and small-medium cities, the existing results from developed cities may not be suitable for guiding the satisfaction improvement of public transit for smallmedium cities in backward areas of China. ...
This paper aims to explore the factors influencing passengers’ satisfaction toward bus transit and develop the improvement strategy for the small-medium city. Data including individual attributes, travel activity attributes, and perceived service attributes were collected in the city of Weinan, China. The ordered logit (OL) model and ordered Probit (OP) model were employed to explore the significant factors associated with passengers’ satisfaction toward bus transit. The odds ratio (OR) was applied to quantitatively measure the effects of the significant factors. Improving strategies of bus transit service were proposed based on the model results using the three-factor theory. Results show that the OL model outperforms the OP model. The age, daily average waiting time, perceived waiting time, transferring convenience, the attitude of the driver, intelligent travel information service, hygienic environment inside the bus, ticket price, bus route setting, and bus stop setting significantly affect the passengers’ satisfaction. Among them, the ticket price, perceived waiting time, bus stop setting, intelligent travel information service, transferring convenience, and bus route setting were identified as exciting factors. It is recommended that optimization of bus route and bus stop setting, building bus dedicated lanes, optimizing dynamic charging system, and providing intelligent travel information service could be effective strategies to improve passengers’ satisfaction toward bus transit in Chinese small-medium cities.
... In addition, it was found that the measures undertaken to encourage public transport, with public incentives and restrictions on the circulation of cars at certain times and especially in urban centers, have proved useful in increasing the spread of buses and reducing environmental impacts [60]. In addition, in many European cities, there is a greater economic convenience of the bus compared to the car, and thanks to the increase in overall quality of service, service production, transfer quality, ticket services, and environmental consciousness, a growing number of people shifted to public transportation [61]. ...
This paper provides an overview of the environmental impacts of different types of passenger transportation means (i.e., bicycles, motorcycles, cars, buses, trains, and airplanes). The method has been applied to the European scenario. The study was performed by using life cycle assessment in accordance with international standard ISO 14040/44 for assessing the CO2 eq., SO2, and PM10 of the transportation means by exploiting data (i.e., vehicles features and environmental impacts) from 24 scientific papers from the literature that have been manually analyzed. The functional unit is defined as the impact per 1 passenger over 1 km. The study identified that planes are the most impacting for CO2 eq. with up to 380 g/pkm, while cars are the most impacting for SO2 with up to 1.78 g/pkm and PM10 with 0.98 g/pkm. Electric and hybrid models proved to be significantly better than others, while buses are the most sustainable in general. Referring to the overall European scenario, cars constitute up to 95% of the overall impacts. By comparing some improvements for reducing the impacts, it emerged that the limitation of diesel cars along with the increase of buses and trains are the most effective. The provided outcomes may be useful for legislators, manufacturers, and users for favoring the choice of the transportation means in a more environmentally conscious way.
... Alhelalat et al. (2017); Ju et al. (2019) and Radojevic et al. (2015) added that comfortable beds, clean rooms and bathrooms and physical attractiveness were considered important and necessary to achieve customer satisfaction. Other studies on public transportation found that cleanliness and comfort were the most impact factors of user satisfaction; however, the impact of these factors did differ based on the socio-economic characteristics of the user (Efthymiou et al., 2018). ...
... These evaluations define the level of satisfaction users have with the different aspects of the PT service and also with the service bundle as a whole. The attributes to be evaluated by the respondent are usually derived from previous studies, as in the case of Hensher et al. (2003) where 13 representative items of the service were defined, or in Efthymiou et al. (2018) where factors that affect satisfaction are analysed for times of economic crisis. The subsequent analysis of the obtained data has been carried out in different ways over the years. ...
Customer overall satisfaction towards a public transport system depends mainly on two factors: how satisfied they are with different aspects that make up the service and how important each of the service aspects is to the customer. Traditionally, researchers use revealed preference surveys and ordered probit/logit models to estimate the contribution of each service attribute towards the overall satisfaction. This paper aims to verify the possibility of replacing the traditional method with the more cost-effective best-worst case 1 method, using a customer survey recently conducted in Santander, Spain. The results show that the satisfaction level obtained from these alternative methods are remarkably similar. The relative importance of each attribute delivered by the two methods differ, with the Best-Worst approach showing more intuitive and consistent results with the literature on public transport customer satisfaction. A regression method is de- veloped to derive customer satisfaction with each service attribute from Best-Worst modelling results.
... Various accident research studies used this approach to examine the effects of geodemographic characteristics on the severity of injuries sustained by vehicle occupants (Srinivasan, 2002;Wang and Kockelman, 2005;Quddus, 2015), to evaluate factors contributing to bicycle-vehicle conflicts (Stipancic et al., 2016) and pedestrian injury severity (Kwigizile et al., 2011). Ordered logit methodology was also used to determine the influence of service quality on demand of buses (Rojo et al., 2012;Efthymiou et al., 2017) and bikeshare usage (Faghih-Imani and Eluru, 2016). However, to date this model was not applied to determine the price sensitivity of transit or bikeshare systems. ...
Pricing is one of the major factors that affects ridership and revenue of the bikeshare systems. This paper examines bikeshare users' sensitivity to changes in price and preferences on service by conducting an intercept survey at Capital Bikeshare (CaBi) stations. Monadic price testing approach was used to design survey questions and elicit responses on sensitivity of users to price changes in fare products. Ordered logit regression results indicated that higher household income groups and 'White' users are less sensitive to price compared to other income groups and other races/ethnicities, respectively. An illustrative application of the demand curves is presented, which showed that low-income groups are more sensitive to price than the middle and high-income groups. White users were found to be approximately 20% less price sensitive than other races for both casual users purchasing single-trips and annual members. The price elasticities revealed that females are about 30% and 10% more price sensitive than males for single-trip fare (STF) and annual membership, respectively. Also, sightseeing trips are 30% less price sensitive than work trips for STF purchasers. An illustrative application of income-based elasticities indicated that reducing the STF to 2.00 per trip and annual membership to 85 per year) were found to improve both ridership and revenue. It is expected that the contributions from this study would provide insights and guidance on evaluating future pricing policy changes at various bikeshare systems.
... A large number of previous studies have made efforts to better measure bus service quality as well as loyalty, and try to understand how passengers' perceptions of bus service quality and other factors influence their satisfaction and loyalty (Allen et al., 2019;Allen et al., 2018;de Oña and de Oña, 2015;de Oña et al., 2016a;de Oña et al., 2016b;Mazzulla, 2010, 2011;Efthymiou et al., 2018;Van Lierop and El-Geneidy, 2016;Webb, 2010). Chou and Kim (2009) assessed passengers' loyalty through repeat patronage, willingness of recommending to others, and high price tolerance. ...
Sustaining and improving passengers’ loyalty has become an effective strategy for the development of bus priority. Passengers’ loyalty towards public transportation could be generally assessed in both attitudinal and behavioral levels. Thus, in this context, spuriously loyal passengers could be characterized by attaching a relatively low level of attitude to public transit users who have high behavioral patronage. Due to the lack of attitudinal preference, these passengers have the potential to turn to alternative transportation modes. Therefore, their loyalty should be better assessed, and targeted approaches should be provided to maintain the market share. This paper adopted a cross-classification framework to divide bus riders by considering different levels of loyalty in both attitudinal and behavioral dimensions. The framework led to four specific segments of passengers, and spurious-loyalty users were identified by using clustering analysis methods in a case study in Xiamen, China. Then, Structural Equation Modeling approach was employed, and hypotheses accounting for public transit loyalty were examined and analyzed in a baseline model. Moreover, key factors leading to spurious loyalty were identified, and index score of corresponding variables was calculated. Surprisingly, the results indicated that over half of users who highly adhered to public transit were not attitudinally loyal. However, although these passengers were dissatisfied with the current level of public transit service in specific regions as expected, their willingness of continuing-to-use public transit maintained at a high level. It implied that the cost of shifting to private motorization in Xiamen might still be high, so most spuriously loyal passengers had to continue choosing public transit in the near future. Nevertheless, the key to successfully sustain the long-term development of public transit should still focus on delivering passenger-value-oriented quality services. Therefore, with regards to the improvement of bus service to maintain the market share, targeted measures should be taken in terms of “crowdedness in the bus during peak hours”, “driving stability and comfort”, “bus speed”, “waiting time at stations” and “convenience of route transfers”.
... This study adds evidence of the behaviour of PT users during an economic downturn. They subsequently analysed both periods (2008 and 2013) plus the 2017 period (Efthymiou et al., 2018) using ordered logit models, they find slight differences in priorities across years. Still, their analysis does not focus on any effect of a specific network reform during the analysed timeframe. ...
Before enduring a substantial network reform in a system, it is of utmost importance to understand if, how, and why the users’ perception of the system will be affected. In the PT literature, we find evidence about what drives users’ satisfaction. Still, past studies have utilised data that has been mostly retrieved from user surveys during periods where the network and its services were quite stable, or during an economic downturn, in contrast to facing a structural network transformation. Barcelona public bus company (TMB) reformed into a transfer based-network, the NXB (Nova Xarxa de Bus) since 2012. This reform allows discerning which operative, travel, and sociodemographic characteristics affect the users’ satisfaction and their priorities, during a major network reform. We use a three-year customer satisfaction survey (n = 12,511), for our study. Employing a structural equation (SEM) approach, with both numeric and ordinal Probit models, we assess whether critical variables from the bus network reform affect users’ satisfaction significantly. Following a two step-approach, initially an SEM-MIMIC model for the whole population, then a Multi-Group Analysis (MGA), we appraise for different satisfaction models across subpopulations. We propose a reflective latent variable to measure the socioeconomic status (SES), which resulted in significant and negative estimates towards satisfaction, as expected, in all models. Our most important result confirms that users value reliability over other latent satisfaction constructs. Besides the satisfaction constructs, users give an additional relevance to the NXB lines, indicating that intrinsically the users perceive added-value from these lines. Most of the transfers between buses and other transport modes do not affect bus-users satisfaction. Our results imply that efficiently designed transfer-based networks may be a suitable solution from users’ perspective.
... Various accident research studies used this approach to examine the effects of geodemographic characteristics on the severity of injuries sustained by vehicle occupants (Srinivasan, 2002;Wang & Kockelman, 2005;Quddus, 2015), to evaluate factors contributing to bicycle-vehicle conflicts (Stipancic et al., 2016) and pedestrian injury severity (Kwigizile, Sando, & Chimba, 2011). Ordered logit methodology was also used to determine the influence of service quality on demand of buses (Rojo et al., 2012;Efthymiou et al., 2017) and bikeshare usage (Faghih-Imani & Eluru, 2016). However, to date this model was not applied to determine the price sensitivity of transit or bikeshare systems. ...
In the decade since 2007, public bikeshare systems (PBS) have disrupted the landscape of
urban transportation systems all over the world. The rapid pace at which urban systems
are enduring this disruption due to PBS has left cities and researchers play catch up on
understanding various factors impacting the usage and impacts of PBS. Comprehending
the profiles and preferences of bikeshare users have a substantial role to play in policymaking,
planning and operational management at all bikeshare systems. However, the
research is scant related to these factors.
As its first major objective, this research evaluated the impact of pricing on
bikeshare ridership and revenue. As a case study, the introduction of single-trip fare
(STF) for $2 by Capital Bikeshare (CaBi) was studied. Aggregate analysis results showed
that the first-time casual (short-term) users increased by as much as 79% immediately
after the introduction of STF. Jurisdiction-level analysis indicated a statistically
xiv
significant increase in casual user ridership for identical 12-month periods before and
after the introduction of STF. The introduction of STF did not impact ridership and
revenues of registered (annual or monthly) members. Casual user revenues before and
after the introduction of STF were also compared at the station-level, while controlling
for seasonal and weather factors. The results showed a statistically significant increase in
ridership and decrease in revenue per ride for casual users after the introduction of STF.
Even though casual bikeshare users account for a large share of revenue, literature
provides very little insights about the casual users. As the second major objective of this
research, profiles and preferences of bikeshare users (registered members and casual
users) were obtained by conducting an intercept survey of CaBi users. Survey findings
indicated that, when compared to casual users, registered members are more likely to
earn more and are more sensitive to service as reflected by station density. A typical
White user has 2.4 times greater odds of being registered member than a user of different
race. Analysis also revealed that each additional increase in the number of monthly trips
leads to about 18% increase in the odds of the bikeshare user being a registered member.
As the third major objective, this research evaluated price sensitivities and
elasticities of bikeshare fare products using monadic design implemented in the survey
instrument. Higher household income groups and White users were found to be less
sensitive to price compared to other income groups and other races/ethnicities. Pivotprice
elasticities revealed that females are about 30% and 10% more price sensitive than
males for single-trip fare (STF) and annual membership, respectively. Also, sightseeing
xv
trips are 30% less price sensitive than work trips for STF purchasers. Results from this
study would be useful in policy-making, planning and operations for bikeshare systems.
This paper revisits the approaches and methods of Transit Performance Evaluation (TPE) in the context of developing countries, where existing TPE measures are found to have certain deficiencies. TPE approaches and measures are discussed related to efficiency and effectiveness, service quality, Level of Service (LOS), community perspectives and a combination of them. Efficiency and effectiveness measures are related to administration and logistics or system function and operation. Service quality considers passengers' perception towards offered services. LOS approach allows comparison based on indicator thresholds subjective the transit systems have equitable environments. It is observed that community perspectives are given lesser weightage. This review helped in the identification of areas which need to be improved in the existing frameworks. Proposed framework is an index-based framework and is comprehensive, inclusive, has universal applicability and considers the complete ensemble of transit system. It includes stakeholders' perspectives to develop three indices covering operational, service quality, and community and society domains. While developing the framework, data availability, variability and heterogeneity are taken into consideration.
With the in-depth study of taxi services, mobile crowdsourcing has become an emerging paradigm for solving location-based assignment tasks. However, only considering the task completion and regional coverage balance may reduce user’s satisfaction. Therefore, designing effective methods that not only address coverage balance but also take into account user’s satisfaction is a problem that needs to be addressed. We investigate the problem of regional coverage balance with users’ satisfaction and propose a service selection method based on transfer learning. This method comprises user’s trajectory prediction and service’s reputation to recommend services to users. In the user’s trajectory prediction part, an incentive mechanism is considered to ensure an even distribution of taxi services in each sub-region. Taking the service providers’ moving as the input, we design an adaptive ant colony algorithm that incorporates transfer learning to provide users with the optimal services. We validate the effectiveness of this method with datasets collected from the real world and compare the performance with existing regional coverage balance strategies. The experimental results show that user’s satisfaction increases by 53%, and the imbalance reduces by 24%.
O investimento na infraestrutura de modos sustentáveis nos centros urbanos não tem causado mudança na demanda e freado o uso crescente do automóvel. Dessa forma, se faz necessário compreender os determinantes subjetivos do comportamento da demanda que podem ser capazes de promover o uso de modos sustentáveis. Portanto, o objetivo deste artigo é identificar na literatura como os aspectos psicológicos – relação social, hábito e conscientização – podem influenciar o comportamento de escolha do modo. Estes aspectos são vistos como potenciais causadores de mudança do uso do automóvel. A partir de uma análise de trabalhos teóricos e empíricos, identificou-se as principais teorias, fatores psicológicos e hipóteses de relações destes fatores com o comportamento de escolha do modo de transporte. O trabalho contribui, então, na definição de uma representação conceitual apresentando as hipóteses de relações entre fatores psicológicos no processo comportamental de escolha do modo, que pode servir como base para estudos futuros.
Abstract Paper aims This study aimed to analyze how the satisfaction level of public transport (PT) users is influenced by their socioeconomic characteristics. Originality The analysis of how socioeconomic variables influence the satisfaction level through the association between MANOVA and exploratory analysis is still not explored, especially in Brazil and in medium-sized cities, which represent the majority of Brazilian cities. Research method Data collection was carried out by questionnaire in a Brazilian city. The 330 users of PT evaluated their satisfaction level concerning 12 quality indicators. Statistical analyses were performed using Pearson's correlation and MANOVA. Main findings Most socioeconomic variables influenced user satisfaction in at least one indicator, gender and schooling being the most prominent. The results showed that women’s mean level of satisfaction is lower than men’s concerning indicators affected by gender. Fare was the indicator with the worst score, being influenced by users’ occupation. Implications for theory and practice The study presents practical and methodological contributions. The results provides technical and scientific subsidies for public policies and service improvement. It possible to improve each indicator according to the users’ socioeconomic characteristics, encouraging the use of PT and contributing to the urban environment sustainability.
Customer satisfaction has always been a pivotal indicator of public transport service quality. However, most existing studies on public transport satisfaction focused on passenger perception without considering the actual traveling performance. Thus, whether passenger perception veritably reflects the actual performance remains to be investigated. This paper adopts the gradient boosting decision trees approach to reveal the relationship between actual on-board performance and passenger satisfaction driven by individual perception. The work utilizes a mixed dataset combining customer satisfaction survey (CSS) with actual traveling data collected in Shijiazhuang, China. Instead of a direct equivalence, the results indicate the complex non-linear relationship between passenger perception and actual on-board performance. These findings enable deriving strategies for administrators and operators to improve the public transport service quality and customer satisfaction in a more effective and targeted way.
Background
Public buses are a major transportation mode in large cities in the developing country Indonesia. Nevertheless, most societies still use passenger cars. Therefore, the road authority has developed an important policy to improve public bus services soon. One of the public bus services is to change the bus operational system, including the manual ticketing system to an electronic ticket (e-ticket) system. In order to make the policy succeed, the road authority should ask for passengers’ opinions.
Objective
The purposes of this study are to ensure that the bus e-ticket is needed to support the policy and then to determine important priority factors of bus e-ticket implementation.
Methods
The data were collected using a direct survey with a questionnaire in large cities, Surabaya and Denpasar in Indonesia. A total of 565 bus passengers participated in this survey. An analysis was conducted through cross tabulation between the respondents’ demographic data and their perceived level of need and priority of implementation with regard to various factors of the e-ticket system. The Simple Additive Weighting method was used to determine the important priority factors.
Results
Results indicated that a bus e-ticket needed for the cross tabulation average value is more than 3.60 out of 5.00 for all factors. Furthermore, the three highest values of factors based on the Simple Additive Weighting method are ease of access, availability of the bus routes information, and affordability of the e-ticket price.
Conclusion
Since respondents indicate that the e-ticket is needed and is a priority, then the policy is beneficial not only to improve bus services in Indonesia but also in other developing countries with similar traffic and geometric conditions.
As an emerging technology that does not rely on the construction of several parking facilities and effectively relieves the pressure of urban parking, shared parking is widely promoted. However, users may turn to conventional parking mode because of concerns about the performance of shared parking modes. Therefore, to determine why users change parking mode and to improve the behavior patronage rate of shared parking mode, studying the factors influencing users’ behavior intentions is very important. Technology acceptance model and satisfaction–loyalty model are combined to construct a comprehensive framework for analyzing the key factors that affect the behavioral intentions of shared parking mode and to describe the multidimensional characteristics of the behavioral intentions. The hypotheses were tested and analyzed on the basis of the empirical data of Harbin and the structural equation model (SEM). Eventually, a multigroup SEM analysis, which takes gender as a moderating variable, is used. Results show that the re-patronage of shared parking is significantly affected by its technology acceptance and that the perceived risk is the key variable leading to change parking mode. In addition, the factor invariance of the identified model framework is examined against gender, and few significant differences are found. The framework is expected to contribute to operators in increasing their market share of shared parking services and to governments in promoting new transportation technologies in cities.
The work aimed at proposing a decision support interdisciplinary model for the assessment of the quality of public transport based on the multi-criteria approach. A case study was carried out in a medium-sized Brazilian municipality, considering the importance of indicators and the level of users' satisfaction. The methodology relied on the disaggregated and aggregated analysis of the indicators with Analytic Hierarchy Process (AHP), generating a quality index for the municipality under study and sensitivity analysis. The results show the relevance of the proposed model, highlighting the main indicators and the final index for the case studied. The operational group was considered a priority for the municipality, with the lowest Public Transport Quality Index (PTQI) per group. The results emphasized the low quality of the service in the municipality, which presented a PTQI of 0.472. The work contributes to the state of the art by proposing a model to assess the quality of the PT (Public Transport), and assists public authorities and operating agents in the decision-making process with regard to the improvement of the public transport system.
The quality of bus transport to school and its synergistic effects on school attendance, quality teaching, and learning are best measured using experiences and perceptions of users. The study sought to investigate 43 obstacles to the delivery of quality bus service via 20 selected private schools in the Sunyani Municipality, Ghana. The survey was an exploratory case study which focused on the use of a questionnaire. Survey participants of 403 students were selected to respond, using the probability sampling technique. Descriptive statistics were used to define essential socio-demographic and bus service-related characteristics and their effects on schoolchildren's mobility decision-making as well as academic work. Exploratory factor analysis was used to construct four latent factors which describe obstacles to perceived service quality (PSQ) delivery. The theoretical factor structure of the data was tested using confirmatory factor analysis in AMOSS 23. Simultaneously, path analysis was employed to investigate the direct and indirect effects of barriers to PSQ in the private schools' transport system. The principal component analysis highlighted four constructs as barriers to bus PSQ in the municipality: (1) perceived scheduling and routing barriers, (2) perceived safety and bus attribute barriers, (3) pedestrian and bus stop facilities barriers and (4) efficiency, effectiveness, and equity-related barriers. We recommend that Private School Authorities and Municipal Board of Education adopt policies and draft operational safety and guideline manuals that clarify acceptable bus service delivery benchmarks and performance indicators for schools.
In order to determine the level of satisfaction of the public transport services, the passengers jointly evaluate the various attributes that represent the different aspects of the level of service. From a methodological viewpoint this means finding the weighting that individuals use to evaluate those attributes within what is considered as the level of global satisfaction or utility. In this paper we obtain indicators that permit the aggregate measurement of the quality of the public transport bus services on Gran Canaria in Spain. The analysis focuses on obtaining the preferences using designs of Stated Preferences (SP) that give the individual the choice between the current service and a hypothetical service defined, from a combination of the most relevant variables. With this information multinomial logit models are estimated that permit us to obtain a linear representation of the utility function parameters, from which a measure of the global quality of the service is obtained. The results of the analysis demonstrate that passengers have clearly different behaviour, depending on whether they are urban or interurban users; this is especially relevant in their perception of certain attributes such as frequency, and to some extent the willingness to pay relative to the components of total travelling time.