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The purpose of this paper is to realize a smooth and secure brake assistance system to avoid rear‐end collision of automobiles.

It is important to judge necessity of deceleration assistance as early as possible and initiate the assistance naturally in order to reduce rear‐end crashes. However, it easily results in driver's discomfort. In addition, deceleration profile of the automatic braking is also important to realize smooth collision avoidance. In this paper, a deceleration assistance control for collision avoidance will be proposed based on the formulated braking behavior models of expert drivers to realize smooth, secure brake assistance.

The proposed brake assistance system can realize smooth deceleration profile and appropriate final status of the two vehicles for various approaching conditions. In addition, experimental results using a driving simulator will show validity of the proposed system based on subjective evaluation. It is also shown that the system realizes smooth deceleration control even under existence of the interaction between human driver and the system.

This paper does not deal with effect of the deceleration method on change of drivers' behavior, including driver's trust on the system. Over‐trust should be eliminated if any.

The originality of the paper is to derive smooth secure collision avoidance system based on the driver's perceptual risk model. This method can realize smooth collision avoidance behavior for the various approaching conditions with a unified simple algorithm.

Describes coping strategies which make it possible to counteract and prevent driver stress. Driver stress is defined by increased aggression and alertness, a dislike of driving, and frustration and irritation elicited by interaction with other road‐users, in particular in relation to overtaking. It is associated with life stresses and health and emotional problems and affects the driver′s road safety.

The purpose of this paper is to identify traits and skills of a truck driver for sustainable transportation, develop a theoretical framework and outline further research directions.

The present study undertakes a review of extant literature and appreciative inquiry, a quasi-ethnographic approach to identify traits and skills of a truck driver. Further, using a pragmatic approach, a theoretical framework has been developed.

The study proposes a theoretical framework, which can be further used for formulating training modules for truck drivers for sustainable transportation and logistics.

The present framework needs to be statistically validated using survey data and second, the proposition of the theoretical framework needs to be tested using hierarchical regression analysis. Second, in the study the authors have used AI. However, the authors have only interviewed selected senior police officials. This may lead to bias and to further strengthen the present study, one needs to identify other regulatory authorities and human resource managers of transportation companies. However, in Indian subcontinent situation the trucks are primarily owned by unorganized sector. Hence, the owners may have five to ten trucks and this case there is no human resource manager. However, in such case an interview with truck owners may provide a useful insight.

The study has outlined recommendations on the basis of a literature review of extant literature and appreciative inquiry. The recommendations can further help policy makers or technical bodies run by a government agencies or privately managed to develop a training module for truck drivers to meet the future challenges of sustainable transportation.

This research is related to truck drivers and their welfare as well as how they can contribute to sustainable transportation and logistics.

This research attempts to identify traits and skills of a truck driver for a sustainable transportation and logistics, and develops a theoretical framework and outline further research directions. This particular study ventures into new domain (the role of truck driver's role in sustainable logistics and transportation).

The Minister of Transport, in exercise of his powers under section 98 of the Transport Act 1968 and of all other enabling powers, and after consultation with representative organisations in accordance with section 101(6) of the said Act of 1968, hereby makes the following Regulations:—

This paper aims to describe a training program for 300 delivery drivers at UK retailer John Lewis.

The paper deals with the reasons for the program, the form it took and the results it has achieved.

The paper details how John Lewis teamed up with assessment company Cognisco to create the Much More than a Driver program, tailored to meet the individual training and development needs of each driver.

The paper explains that training materials and activity packs with job‐aid cards were created for the drivers. A “day in the life of a John Lewis delivery partner” video is also being created, alongside a work‐book, allowing drivers access to all elements of the training program, even from a remote location.

The paper reveals that, as more and more customers opt to shop online, a company's delivery drivers are increasingly the human face of the organization, so the drivers must have the skills, knowledge and confidence to provide great customer service.

The paper explains that, because the drivers were asked what tools and training they needed before John Lewis embarked on the program, they supported it from the start and really helped to shape the program.

Driver turnover has plagued the truckload industry in the USA since deregulation in 1980. Turnover in truck load firms averages above 100 percent in good economic times and over 40 percent in bad ones, costing the industry billions of dollars. This research sought a best‐fit regression model to show how a firm might control its own turnover.

The paper distributed a survey questionnaire to 800 truck drivers at a large US truckload motor carrier. The questionnaire included over 50 items with a seven‐point Likert‐type scale from strongly agree to strongly disagree. The paper analyzed 309 usable responses using regression analysis with scaled scores on aspects of a driver's job. The dependent variable was intent to quit (ITQ).

Research on truck driver turnover has focused on driver attitudes as determinants of ITQ, looking at drivers' attitudes that might lead to higher ITQ and higher turnover. In this research, drivers' attitudes toward top management and dispatchers did not influence ITQ, a surprising result that raises questions and suggests a new direction for research.

This research was conducted in only one firm. Its results may not generalize to all trucking firms, especially not to smaller firms. The method used, however, does generalize. Other firms may use this same approach to identify the causes of turnover in their organizations.

This research demonstrated a method for researching the causes of driver turnover that are practical and accessible to firms of all sizes.

This research was conducted in only one firm. Its results may not generalize to all trucking firms, especially not to smaller firms. The method used, however, does generalize. Other firms may use this same approach to identify the causes of turnover in their organizations.

The results of this research suggest that the relationship between drivers and the firm have changed, probably because of the extensive use of new technology. The methods used here will help large trucking firms allocate resources for driver management and retention. They may also help smaller firms understand the implications of investment in sophisticated technology.

This paper aims to present a methodology for activity‐based costing, which combines simulation modeling and association rule mining, one of the core data‐mining techniques. The objective of the proposed methodology is to deal with the problem of defining cost drivers.

Activity‐based costing uses the output produced by the simulation of cost drivers as inputs. As opposed to the integration of the ABC technique with simulation modeling, the possibility of estimating an empirical distribution of the simulated cost drivers does not exist in the proposed methodology. This is achieved with the use of data‐mining techniques and is based on the proposition that, if an association is found between a cost driver, whose estimation or calculation is time‐consuming, and another cost driver, which can easily be estimated or calculated, then the latter can lead to the estimation or calculation of the former.

The extracted association rules correspond to existing dependencies between the cost drivers.

The paper presents a combined methodology to deal with the problem of defining cost drivers in activity‐based costing. An example of the proposed methodology in healthcare is also presented.

This paper reports an employee‐management consensus approach for identifying safety initiatives that are both appropriate to the working environment and also perceived to be appropriate by the workforce. Issues affecting the success of employee involvement schemes are discussed and the methods used during the implementation stages of the programme to address them are described. The case study was set in the UK distribution division of an international oil company and was applied to safety issues affecting the division’s tanker drivers. The study used an employee questionnaire to assess drivers’ perceptions of safety management, workplace conditions and safety concerns. Factor analysis and structural equation modelling were used to develop a management/workplace/workforce model to describe the drivers’ working environment. The model was then used to discuss and explain the drivers’ choices of safety initiatives.

Rapid urbanization and the shortcomings of traditional construction methods motivate construction professionals to explore faster and more sustainable approaches such as off-site construction (OSC). Thus, the purpose of this paper is to identify the drivers influencing OSC adoption and to explore the key drivers of its widespread adoption in Egypt.

A comprehensive global literature review was performed initially to develop an up-to-date list of OSC adoption drivers, which was confirmed in the Egyptian context through a pilot study. Then, social network analysis (SNA) was utilized to determine the most influential drivers as well as shortlist them to construct the final questionnaire survey. A total of 57 stakeholders in the Egyptian construction industry responded. Lastly, the relative importance index (RII) was calculated to rank the drivers, revealing the key drivers.

The results revealed that higher productivity, improving project quality control, shortening construction time, improving product quality and improving supervision and inspection are the top five drivers. On the contrary, government policies and regulations is the least significant driver.

This research contributes to the body of knowledge by introducing a comprehensive, up-to-date list of drivers, which helps the stakeholders gain a better understanding of the driving enablers of adopting OSC generally and helps Egyptian stakeholders make more informed decisions about its implementation specifically.

The need to enhance student support is evident in higher education (HE) curricula. In addition to the complications created by the COVID-19 pandemic, the current strategies used in academia are criticised for their lack of appropriate student support in HE. The study focused on the themes under Section 4 of the National Student Survey (NSS): availability to contact tutors, receiving good advice and guidance and availability of good advice. The study aimed to provide recommendations for enhancing academic support by developing drivers that need implementation during course delivery.

A documental analysis and a qualitative survey were adopted for this study. A documental analysis of 334 mid-module reviews (MMRs) from levels three to six students in the built environment (BE) discipline. Critical themes identified from the MMRs were fed forward in developing a questionnaire for academics. A sample of 23 academics, including a Head of school, a Principal lecturer, Subject leads and Lecturers, participated in the questionnaire survey. Content analysis is adopted through questionnaire data to develop drivers to enhance academic support in BE. These drivers are then modelled by interpretive structural modelling (ISM) to identify their correlation to NSS Section 4 themes. A level partition analysis establishes how influential they are in enhancing academic support.

The study identified nine drivers, where two drivers were categorised as fundamental, two as significant, four as important, and one insignificant in enhancing academic support in HE. Module leaders’/tutors’ improving awareness and detailing how academic support is provided were identified as fundamental. Differentiating roles in giving advice and the importance of one-to-one meetings were identified as significant. A level partitioning diagram was developed from the nine drivers to illustrate how these drivers need to be implemented to promote the best practices in academic support in HE.

The identified drivers and their categories can be used to set prioritised guidelines for academics and other educational institutions to improve students’ overall satisfaction.

Novelty from the study will be the developed drivers and the level partitioning diagram to assist academics and academic institutions in successfully integrating academic support into HE curricula.