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Pay-as-you-go contracts reduce minimum purchase requirements, which may increase market participation. This paper randomizes the introduction and price(s) of a novel pay-as-you-go contract to the California auto insurance market, where 17% of drivers are uninsured. The pay-as-you-go contract increases take-up by 10.8 p.p. (89%) and days with coverage by 4.6 days over the 3-month experiment (27%). Demand is relatively inelastic, and pay-as-you-go increases insurance coverage in part by relaxing liquidity requirements: most drivers' purchasing behavior is consistent with a cost of credit in excess of payday lending rates, and 19% of drivers have a purchase rejected for insufficient funds. [ABSTRACT FROM AUTHOR]

Importance: Although the Assessment of Motor and Process Skills (AMPS) is an excellent tool for evaluating the functional performance of instrumental activities of daily living (IADLs), a limited number of studies have used the AMPS for decisions regarding the IADL of fitness to drive and community mobility. Objective: To determine the specificity and sensitivity of the AMPS as a tool for determining a person's fitness to drive. Design: Cross-sectional observational design. Setting: Three driving rehabilitation programs in three states. Participants: Participants were 388 community-living adults (M age = 68.74 yr, SD = 11.53); 196 adults were recruited before completing a comprehensive driving evaluation, and 192 were recruited in two other studies of older drivers. Outcome and Measures: AMPS and results of comprehensive driving evaluation or on-road assessment. Results: Using a logistical regression, AMPS Motor and Process Skills scores yielded a sensitivity of 84.6% and a specificity of 88.8%. The odds ratio of the AMPS Motor Skills score was.347; for the AMPS Process Skills score, it was.014. Using cross-validations, the model with AMPS Motor and Process scores produced a cross-validation area under the curve of.918, with sensitivity and specificity of 84.6% and 88.4%, respectively, and a probability greater than.334 was used for predicting a fail or drive-with-restriction evaluation. Conclusions and Relevance: The AMPS Motor and Process Skills scores revealed significant differences between those who failed or had driving restrictions and with those who passed the driving evaluation, which supported the AMPS as an effective tool for predicting fitness to drive. Plain-Language Summary: This study demonstrates how the Assessment of Motor and Process Skills (AMPS), as a top-down occupational therapy assessment tool, can be used to differentiate between medically at-risk drivers who are likely to pass a comprehensive driving evaluation and those who are likely to fail or need restrictions. AMPS will assist occupational therapy practitioners in determining who is most appropriate to receive driving rehabilitation services and/or when to refer a person for a comprehensive driving evaluation. This study found that the Assessment of Motor and Process Skills (AMPS) can be used to differentiate between medically at-risk drivers who are likely to pass a comprehensive driving evaluation and those who are likely to fail or need restrictions. [ABSTRACT FROM AUTHOR]

Amassive market penetration of electric vehicles (EVs) associated with non-negligible energy consumption and environmental issues has imposed a big challenge on evaluating electrical power distribution and related transportation facilities improvement in response to the largescale EV charging service need. Strategical deployment of EV charging stations including location and determination ofnumber of slowcharging stations and fast charging stationshas become an emerging concern and one of the most pressing needs in planning. This paper conducts a comprehensive survey of EV charging demand and distribution models with consideration of realistic driver behaviors impacts. This is currently a shortage in academic literature, but indeed has drawn practical attention in the strategic planning process. To address the need, this paper presents an in-depth literature review of relevant studies that have identified different types of EV charging facilities, needs or concerns that are considered into EV charging demand and distribution modeling, alongside critical impacting factor identification,mathematical relationshipsof the contributing factorsandEVchargingdemand and distribution modeling. Key findings from the current literature are summarized with strategies for optimized plan of charging station deployments (i.e., location and related number of charging station), in an attempt to provide a valuable reference for interested readers. [ABSTRACT FROM AUTHOR]

This study undertakes the analysis of collision scenario using a car model with a dummy and airbags, in the event of a direct collision with a hard wall, one of the necessary studies of passive safety. To describe in detail, the input conditions, a simulation problem of the driver's seat displacements was performed and this displacements data was exported as boundary conditions for the collision simulation. The results simulation crash show that the calculated energy values and simulation results are approximately the same (7.381E+07 and 7.367E+07), energy is converted from kinetic energy into internal energy of the elements. The airbag deployment simulation results are similar to NHTSA's previous research, both in terms of graph shape and maximum value. The impact of the collision incident on the driver is not excessively large, as evidenced by surveys on head (HIC 300), thigh (F 2.8 kN), and neck (F 3.098 kN; T 190 Nm) injuries. However, the study proceeds to further analyze and assess the airbag's structure, examining its influence on these metrics, concluding that changes in the exhaust valve size (increase from 1000 mm2 to 2000 mm2 ) lead to a reduction in the evaluated parameters. These results suggest changes to the airbag structure to enhance driver safety, as well as a simpler simulation model to save analysis time. [ABSTRACT FROM AUTHOR]

Changes taking place in the economy affect the emergence of innovations. It is primarily technological progress that influences the creation of new solutions. Logistics is one area where innovations and improvements are needed. New solutions are primarily process improvements, the implementation of autonomous vehicles, solutions that help to supervise transport processes, and the effectiveness and costs of their implementation. The greatest benefits of technological progress are the provision of knowledge and information about the journey, the efficiency of a given car and driver, and changes in the market (e.g., information about the demand and supply for given services). This article aims to identify the possibilities of using freight exchanges in transport and forwarding management. It is based on a literature analysis and statistical data from systems dedicated to transport and forwarding, as well as surveys conducted by the author. The article uses analyses of demand, supply and prices based on data from transport exchanges. Possibilities of obtaining information for better management of a transport company were presented. Possibilities of obtaining information for better management of a transport company were presented. The article presents the relationship between the use of the transport exchange and the size of the company, fleet and the number of countries served as part of transport services. The possibilities of using transport exchanges and the possibility of replacing software dedicated to transport and forwarding by the discussed programs were indicated. [ABSTRACT FROM AUTHOR]

According to global estimates, there are 10 million people with disability who are displaced representing diverse ethnic, religious, cultural and linguistic backgrounds. Little is known about the refugee experiences of people with disability and their family members or the journeys they have undertaken to seek refuge. This paper explores the drivers and destinations underpinning the refugee journeys made by people with disability and family members fleeing wars in Syria and Iraq, to settle in Australia. Indepth life history interviews were conducted in Arabic with two men with disability and two mothers with sons with disability to understand their refugee journeys. Results are grouped under three journey-related themes developed from seminal work by BenEzer and Zetter: ‘Why’ (Drivers and Temporal Characteristics) participants fled their country of origin, ‘How’ (the Process and Content of the Journey), including the dangers they faced while leaving, their experiences arriving at and living in the transit country, and ‘Where’ participants travelled from their country of origin to (Destinations and Temporal Characteristics). This study demonstrates that the refugee journeys made by people with disability and family members from Syrian and Iraqi backgrounds are complex and multi-dimensional, with the overlay of disability central to their journey experiences. [ABSTRACT FROM AUTHOR]

Due to their strong emotional interest and ownership control, family firm owners significantly influence their firm's strategies and governance, which has consequences for their business sustainability practices. The failure to establish or maintain formal organizational structures, and adopt good governance principles, may hinder family firms in their pursuit of long-term sustainability. This study empirically investigated the impact of corporate governance on family firms' sustainability, with women's empowerment and culture as moderating and mediating factors, respectively. Data for the study were obtained from a sample of 126 family firms from Saudi Arabia. The study adopted the partial least squares structural equation modelling (PLS-SEM) method. The study results empirically confirmed that corporate governance is positively associated with women's empowerment, which also assists in achieving business sustainability in family-controlled firms. The adoption of good corporate governance policies, and empowerment of women through their appointment on corporate boards operating in a supportive culture, can reinforce an organization's mission, purpose and strategies, which can create an enabling environment for family business sustainability. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market. Design/methodology/approach: Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model. Findings: The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant. Practical implications: The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases. Originality/value: To the best of the authors' knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market. [ABSTRACT FROM AUTHOR]

Mental stress and associated heart disorders are some of the considerable causes of death in India and globally, as reported by the World Health Organization (WHO). The long-term presence of mental stress and hypertension in lifestyle can lead to significant disorders, including cardiac arrhythmias. Some researchers in the past have proposed methods to assess mental health by considering various physiological signals and artificial intelligence methods. Most studies have used complex algorithms and a combination of features extracted from bio-signals such as electroencephalogram (EEG), electrocardiogram (ECG), etc. This work aims to develop a simple and efficient method to classify mental stress from Heart Rate Variability (HRV) features of ECG signal. The proposed method for stress assessment is implemented using 1-min segments of real-time ECG signals from the Stress Recognition in Automobile Drivers (SRAD) database. We derived the HRV signal from the de-noised ECG signal and extracted time-domain statistical features. Correlation analysis is applied to statistical HRV features to establish the relationship among different metrics of HRV. The main contribution is to develop a Multiple Linear Regression (MLR) model to predict Heart Rate (HR) using statistically correlated HRV features. Another contribution is the design of a multinomial logistic classifier to classify the mental stress level into three classes: low, medium, and high stress. Simulation results demonstrate that time-domain HRV features are statistically correlated, and with a suitable choice of parameters, the proposed method can achieve a classification accuracy of 90.32%. The findings suggest that using fewer relevant features of ECG, the proposed method provides improved classification performance comparable to the state-of-the-art methods. Because of the non-invasive and simple approach, the proposed technique is suitable for accurately assessing mental stress in real-time environments. The presented approach strongly promotes the development of remote and automatic methods of mental stress assessment for real-world applications using wearable sensors and the Internet of Things. [ABSTRACT FROM AUTHOR]

Previous studies have found that drivers' physiological conditions can deteriorate under noise conditions, which poses a potential hazard when driving. As a result, it is crucial to identify the status of drivers when exposed to different noises. However, such explorations are rarely discussed with short-term physiological indicators, especially for rail transit drivers. In this study, an experiment involving 42 railway transit drivers was conducted with a driving simulator to assess the impact of noise on drivers' physiological responses. Considering the individuals' heterogeneity, this study introduced drivers' noise annoyance to measure their self-noise-adaption. The variances of drivers' heart rate variability (HRV) along with different noise adaptions are explored when exposed to different noise conditions. Several machine learning approaches (support vector machine, K-nearest neighbour and random forest) were then used to classify their physiological status under different noise conditions according to the HRV and drivers' self-noise adaptions. Results indicate that the volume of traffic noise negatively affects drivers' performance in their routines. Drivers with different noise adaptions but exposed to a fixed noise were found with discrepant HRV, demonstrating that noise adaption is highly associated with drivers' physiological status under noises. It is also found that noise adaption inclusion could raise the accuracy of classifications. Overall, the random forests classifier performed the best in identifying the physiological status when exposed to noise conditions for drivers with different noise adaptions. [ABSTRACT FROM AUTHOR]

Objective: This paper used three feature selection methods on a Jordanian automobile drivers' dataset to identify the most significant features for stress prediction algorithm performance. The dataset contains "stress" and "no-stress" classes with 30 features, categorised into physiological and contextual subsets. Methods: Eighteen classifiers from six prediction algorithm categories were evaluated: Rule-based, Tree-based, Ensemble-based, Function-based, Naïve Bayes-based and Lazy-based. Three Feature Subset Selection (FSS) methods were used: Gain Ratio, Chi-square and feature separation. Eight evaluation measures included F 1, Accuracy, Specificity, Sensitivity, Kappa Statistics, Mean Absolute Error (MAE), Area Under Curve (AUC) and Precision Recall Curve Area (PRCA). Results: Among the classifiers, Lazy-based LocalKNN performed significantly well in F 1, Accuracy, Kappa and MAE. Naïve Bayes-based Bayesian Network excelled in other measures. The original dataset with all features yielded the best overall performance, followed by the physiological-only subset. Gain Ratio and Chi-square FSS methods also showed promising results, though not significant. Conclusion: Four physiological (EMG, EMG Amplitude, Heart rate, Respiration Amplitude) and seven contextual (time range of driving, gender, age, driving skills, general accidents, last year's accidents, stress frequency) features contributed to the best prediction outcomes. The study highlights the importance of proper feature selection and identifies optimal algorithms for specific measures. [ABSTRACT FROM AUTHOR]

Purpose: This study examines the role of Saudi women's work motivational drivers on work–home conflict (WHC) and work–home enrichment (WHE). It considers the moderating role of psychological detachment from work during the evening between one workday and the next and how it impacts on the mediating role of WHC and WHE on work performance. Design/methodology/approach: Drawing on self-determination theory and enrichment and depletion perspectives on the work–home interface, the study employs a quantitative lagged study over a period of three consecutive working days, with data collected from 358 Saudi women working in academia. Findings: Moderated mediation structural equation modelling (MMSEM) analysis reveals that intrinsic motivation is significantly, positively related to WHE and home–work enrichment (HWE), whereas extrinsic motivation is only significantly and positively related to home–work conflict (HWC). Results show that detaching from work weakens the positive association between intrinsic motivation and HWE. In line with predictions, WHE is significantly, positively related to citizenship behaviour towards both individuals and organizations, whilst HWE is significantly related to citizenship behaviour towards individuals only. HWC is only significantly related to citizenship behaviour towards the organisation. Social implications: The research highlights the enriching experiences for Saudi women, who have the opportunity to pursue a career and highlight benefits of their ongoing empowerment. Originality/value: This research brings a unique motivational perspective to work–life research and addresses a shortcoming of work–life research in considering an understudied culturally distinct population. It emphasises on the enriching experiences of Saudi women who have the opportunity to pursue a career, highlighting the benefits of their ongoing empowerment. [ABSTRACT FROM AUTHOR]

This paper summarizes the research on countermeasures against driver fatigue based on a comprehensive systematic literature review. Driver fatigue, induced by task monotony during conditional automated driving (CAD, SAE Level 3), can increase the risk of road accidents. There are several measures that counteract driver fatigue and aim to reduce the risk caused by a fatigued driver in the context of CAD. Twelve selected articles focusing on driver fatigue countermeasures in CAD were analyzed. The findings and conclusions are presented, focusing on the countermeasures themselves and their implementation. The countermeasures were critically discussed, especially regarding effectiveness and applicability. They seem to be effective in counteracting driver fatigue. However, the measures are not easily compared because they were studied in various experimental settings and various driver fatigue measurements were used. Different countermeasures have proven to be effective in reducing fatigue during CAD. For this reason, further investigation is needed to gain further insights into their applications, advantages, and disadvantages. Further studies will be conducted to verify the best solution regarding their effectiveness and applicability. [ABSTRACT FROM AUTHOR]