Carmen Forciniti

Transit passengers’ behavioural intentions: the influence of service quality and customer satisfaction

ABSTRACT Knowing passengers’ behavioural intentions to use transit service can be a useful support for transit managers and marketers who can define the most convenient strategies to satisfy existing passengers and attract new ones. We retain that analysing passengers’ intentions to continue to use transit services in the future together with relevant concepts such as service quality and customer satisfaction is fundamental to understand passengers’ behaviour. For this reason, in this paper we propose a structural equation model for investigating on the relationship among some aspects influencing passengers’ behavioural intentions towards the use of transit services. The light rail transit (LRT) of Seville (Spain) offers the transit service supporting our work. We collected through an ad-hoc survey the opinions of the passengers about the used LRT system and transit system in general, and we propose a methodology to explain how passengers’ opinions influence their intentions to use the LRT again. Among the interesting findings from the model, we observe that behavioural intentions are mostly affected by passengers’ judgements about LRT service quality and their satisfaction with the service. Moreover, not only direct but indirect effects on behavioural intentions are derived, determining an accurate conclusion about the relationships of the other concepts with LRT’ users behavioural intentions.

How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior

Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, drivers socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the drivers perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors.

Willingness to use mobile application for smartphone for improving road safety

In the last few years mobile devices have reached a large amount of consumers in both developed and high-growth world economies. In 2013, 97% of the Italian population owns a mobile phone, and 62% owns a smartphone. Application software for mobile devices is largely proposed to consumers, and several mobile applications were oriented toward the improvement of road safety and road accident risk reduction. In this paper, we describe the results of a survey oriented to preventively investigate on the willingness to receive and/or to give information about road condition by means of mobile devices. Road users were informed about the characteristics of a mobile application, and then they were invited to complete a questionnaire. Experimental data were used for capturing road user attitudes toward the use of the smartphone to improve road safety, and to establish the preferences for the different features of the proposed mobile application. To this end, we choose to use the ordered probit model methodology. We demonstrate that the adopted methodology accounts for the differential impacts of the willingness to receive and/or to give information about road conditions on the overall willingness to receive and/or to give information through an application software for mobile devices.

How usual behaviour can affect perceived drivers’ psychological state while driving

AbstractRoad accidents have a relevant impact in terms of economic and social costs. As a consequence, many research studies have focused on identifying the key factors affecting accident severity. Traditionally, these factors can be included in the infrastructural, human and vehicle groups. Among these, human factors have a relevant impact on accident severity, which depends on driving experience, driver’s socio-economic characteristics, and driving behaviour, but also on the driver’s psychological state while driving. In this paper we investigate on the relationships between driving behaviour usually taken by the driver and his/her perceived psychological state while driving. In order to achieve this goal we adopt an Ordered Probit (OP) model formulation calibrated on the basis of experimental data collected by a sample survey. We demonstrate that the adopted methodology accounts for the differential impacts of certain human factors on driver’s psychological state.

Formative and reflective measurement models for analysing transit service quality

Transit service quality is a complex concept depending on different service aspects, such as service frequency and punctuality, comfort, cleanliness, information and so on. Transit service quality is generally measured through the satisfaction of the users with the service. There are relationships between the overall service quality and the different transit service aspects, and between each aspect and the characteristics describing it. Structural equation models represent a useful tool for exploring this kind of relationship and determining the influence of the different service characteristics on service quality. An investigated issue concerning structural equation models is the contrast between the formative and the reflective approach. The structural models proposed for measuring transit service quality have followed a reflective approach, according to which the latent variable (or the service aspect) is the cause of the observed measures (or the service factors describing the service aspect); but in this paper we investigate on the fact that formative variables could be considered to model the relationship among the service quality characteristics, supposing that the observed measures, which represent the service characteristics, form the latent construct. The findings from the comparison between the results obtained by applying the two different approaches suggest that the reflective model is surely more suitable for describing the phenomenon of passenger satisfaction with transit service quality. However, we retain that if some service aspects can be more conveniently investigated through a reflective approach, other service aspects could follow a formative approach in a better way.

An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions

Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. DOI: http://dx.doi.org/10.4995/CIT2016.2016.3199