VNHSGE: VietNamese High School Graduation Examination Dataset for Large Language Models

The VNHSGE (VietNamese High School Graduation Examination) dataset, developed exclusively for evaluating large language models (LLMs), is introduced in this article. The dataset, which covers nine subjects, was generated from the Vietnamese National High School Graduation Examination and comparable tests. 300 literary essays have been included, and there are over 19,000 multiple-choice questions on a range of topics. The dataset assesses LLMs in multitasking situations such as question answering, text generation, reading comprehension, visual question answering, and more by including both textual data and accompanying images. Using ChatGPT and BingChat, we evaluated LLMs on the VNHSGE dataset and contrasted their performance with that of Vietnamese students to see how well they performed. The results show that ChatGPT and BingChat both perform at a human level in a number of areas, including literature, English, history, geography, and civics education. They still have space to grow, though, especially in the areas of mathematics, physics, chemistry, and biology. The VNHSGE dataset seeks to provide an adequate benchmark for assessing the abilities of LLMs with its wide-ranging coverage and variety of activities. We intend to promote future developments in the creation of LLMs by making this dataset available to the scientific community, especially in resolving LLMs' limits in disciplines involving mathematics and the natural sciences.Comment: 74 pages, 44 figure

IMPROVING METHODS TO ESTIMATE THE TRAFFIC CONGESTION IMPACTS OF URBAN PUBLIC TRANSPORT

Public transport is considered to be an efficient solution that can deal with traffic congestion. The thesis aims to develop a more precise approach for assessing the traffic congestion impacts of public transport. The main methodology using to assess the congestion impacts associated with public transport is to contrast the level of congestion on the road network in two scenarios ‘with public transport’ and ‘without public transport’. The findings show that in the morning peak hours, Melbourne’s public transport system contributes to reduce vehicle time travelled and total delay on the road network by around 48%

How does perceived risk affect passenger satisfaction and loyalty towards ride-sourcing services?

The present study quantitatively investigates the influence of booking app-related risk and vehicle &amp; driver-related risk on ride-sourcing passengers’ trust, satisfaction and loyalty. A conceptual model was developed and tested with data collected from 545 ride-sourcing users in Ho Chi Minh City, Vietnam. The findings indicated that perceived vehicle &amp; driver-related risk directly affected passengers’ satisfaction and loyalty significantly. At the same time, trust mediated the relationships between perceived booking app-related risks and satisfaction and loyalty. These findings enable practitioners and policymakers to better prioritise risk dimensions when developing strategies to increase passengers’ trust, satisfaction and loyalty. Finally, the insights provided in this investigation can be used as a guide for ride-sourcing companies to improve risk manangement and risk communication efforts to increase patronage.</p

What makes passengers continue using and talking positively about ride-hailing services? The role of the booking app and post-booking service quality

Ride-hailing services are increasingly consolidating their role in the transport sector in low- and middle-income countries where there is limited investment in public transport. However, much is unknown about the determinants of ride-hailing service use and quality of the service. The present study investigates the direct and indirect influences of perceived quality of ride-hailing service including perceived booking app and perceived post-booking service quality on continuous usage intention and word-of-mouth (WOM) of ride-hailing passengers. Emerging research has aimed to understand the hierarchical structure of ride-hailing service quality (including booking app and post-booking service). Therefore, this study proposes a formative hierarchical component model of perceived booking app quality consisting of seven dimensions (i.e., privacy and security, ease of use, functionality, design, information accuracy, route detection, and service). Likewise, the perceived post-booking service quality is comprised of four dimensions (i.e., reliability, personal, convenience, and tangibility). Data used for testing the model was collected from 536 ride-hailing service users in Ho Chi Minh city, Vietnam. The results provide insights into attributes forming perceived quality of ride-hailing booking apps and perceived post-booking service quality and how these constructs affect passenger loyalty. The results are also useful for ride-hailing companies in their efforts to prioritise critical service attributes and ensure their service quality meets or exceeds passengers’ expectations.</p

How do social cues from other passengers affect word-of-mouth and intention to continue using bus services? A second-order SEM approach

Word-of-mouth (WOM) and intention to continue use (ICU) are the two critical components of customer loyalty towards a particular service. There has been a large body of research investigating the effect of determinants on the loyalty formation of public transport passengers. However, the impact of social cues from other passengers, which are part of the social environment, have received less attention. This study developed a theoretical model to examine the complex relationships among the cues from other passengers, perceived security and safety, perceived value, WOM and ICU. Cues from other passengers involved three dimensions: similarity, physical appearance, and suitable behaviour. These three dimensions were measured using a formative approach in structural equation modelling (SEM). Additionally, the moderating effects of demographic characteristics on the formation of public transport passenger behaviours were explored by multi-group SEM. The model was empirically tested using data collected from more than 870 bus passengers in two big cities in Vietnam (Ho Chi Minh and Danang city). The results showed that social cues from other passengers have a strong predictive power over the WOM and ICU of bus passengers. The study successfully demonstrated the critical role of demographic characteristics as moderators on loyalty formation. The findings reported in the present investigation provide several theoretical and practical implications.</p

Factors influencing road safety compliance among food delivery riders: An extension of the job demands-resources (JD-R) model

On-demand food delivery involves transport services based on gig-economy models. Food delivery services rely on motorcycles in many jurisdictions, resulting in safety risks. Motorcycles are generally-two-wheeled and therefore inherently unstable. They also lack rider restraint or roll cage to minimise the consequences of a collision. Given the risks of motorcycle food delivery, there is a need to understand how job design may influence safety behaviour on the roads and regulate this economic activity to minimise potential harmful health consequences on the riders. This study investigated the impact of job demands and resources on food delivery riders' compliance with road safety regulations. The job demands-resources (JD–R) model was used as the theoretical framework for this research. Data were collected using a cross-sectional design involving 550 motorcycle delivery riders in two megacities in Vietnam. A structural equation analysis indicated that job demands (e.g., time pressure, work/life imbalance, working environment) and job resources (e.g., social support, feedback) influence, directly and indirectly, job strain, risk-taking attitude, and road safety compliance. Control variables such as age, gender, and income also influenced road safety compliance. This study has critical implications for the food delivery industry that can help achieve sustainable development goals in the global south

Intentions to use ride-sourcing services in Vietnam: What happens after three months without COVID-19 infections?

The COVID-19 pandemic has brought new risks and stress for paid transport users worldwide. COVID-19 has changed mobility dynamics worldwide, including low- and middle-income countries (e.g., Vietnam). The present study aims to provide an in-depth understanding of ride-sourcing passengers' behavioural intentions when COVID-19 pandemic management successfully prevented community transmission by extending the TPB with two constructs: perceived virus infection risk and problem-focused coping. Using self-administered questionnaires, data were collected from ride-sourcing customers in Ho Chi Minh City (Vietnam). A total of 540 responses were used for validating the proposed theorethical model. The structural equation model results indicate that problem-focused coping is a multi-faceted construct with two dimensions: problem-solving and self-protection. Also, problem-focused coping has the highest total effect on the intention to use ride-sourcing services following a period of COVID-19 suppression (3 months without identified cases). The findings also reveal that attitude partially mediates the link between problem-focused coping and behavioural intention. The results of this study could be used to develop strategies to promote ride-sourcing services in the aftermath of the COVID-19 pandemic.</p

Turn signal use among motorcyclists and car drivers: The role of environmental characteristics, perceived risk, beliefs and lifestyle behaviours

Turn signal neglect is considered to be a key contributor to crashes at intersections, yet relatively little research has been undertaken on this topic, particularly in developing countries. Using a case study of Vietnam, this research aimed to explore the role of environmental characteristics, perceived risk, beliefs and lifestyle behaviours on the frequency of turn signal use at intersections. A self-administered questionnaire was distributed to motorcyclists (n = 527) and car drivers (n = 326) using online and offline methods. Using partial least squares structural equation modelling (PLS-SEM), key findings indicate that perceived risk, beliefs and environmental characteristics play a significant role in affecting the frequency of turn signal use among motorcycle riders and car drivers at intersections. While lifestyle behaviours were not found to be a good predictor of turn signal use among car drivers, they were found to indirectly affect turn signal use among motorcycle riders through the mediation of beliefs and perceived risk. The findings can help inform the development of more targeted measures to increase turn signal use.</p

Passengers' self-protective intentions while using ride-hailing services during the COVID-19 pandemic

In the transport context, there has been limited research examining passengers' health-protective behaviour while travelling during a health-related crisis such as COVID-19. This study develops a conceptual model aiming to explore determinants associated with passengers' self-protective intentions using the context of ride-hailing services in Vietnam. Ride-hailing services are popular in countries where public transport is underdeveloped. The conceptual model is based on perceived risk and self-efficacy as the main predictor of self-protective intentions when using ride-hailing services. In addition, the proposed conceptual model explores the direct and indirect impact of subjective knowledge and the perceived effectiveness of preventive measures on self-protective intentions. The proposed conceptual model was tested on a large sample of ride-hailing users in Vietnam (n = 527). The structural equation modelling (SEM) analysis results indicate that self-efficacy has the highest total impact on self-protective behaviour, followed by subject knowledge and perceived effectiveness of preventive measures. Self-efficacy also plays a fully mediating role in the linkage between the perceived effectiveness of preventive measures implemented by ride-hailing organisations and the intention to engage in self-protective behaviour. The results of this study expand the current understanding of ride-hailing passengers' health-protective behaviour and contribute to the transport and public health literature.</p

Deadly meals: The influence of personal and job factors on burnout and risky riding behaviours of food delivery motorcyclists

Food delivery riders are overrepresented in road crashes. Arguably, the increased risk experienced by food delivery riders is linked to the working conditions offered by the “gig economy”. Research is needed to fully understand the safety-related issues this vulnerable group of road users face daily and identify opportunities for counter measures. In this investigation, we proposed a new theoretical model to explain the risky behaviour of food delivery motorcyclists based on the well-established Job Demands-Resources (JD-R) model. Following the JD-R, we considered the impact of job demands (job aspects that require sustained effort) and job resources (job aspects that help achieve work-related goals, reduce job demands and stimulate personal development) on the risky riding behaviours of food delivery motorcyclists. The JD-R model was also extended with three constructs, including personal demands, personal resources, and perceived safety risk to explore the role of individuals' within-person aspects. The developed model was tested using data collected from 554 food delivery riders in the two biggest cities in Vietnam. The results showed that job burnout, job resources, and personal demands directly impact risky riding behaviours, in which job burnout was the most significant predictor. Constructs such as job demands, personal resources, and perceived safety risk were not significant predictors of risky riding behaviours. This research shows that organisation-level factors could be modified to prevent risky riding behaviour. The gig economy industry can do much more to improve the safety of delivery riders.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Safety and Security Scienc