Fleet Drivers Research Articles

You're driving me crazy! How emotions elicited by negative driver behaviors impact customer outcomes in last mile delivery

AbstractWith the growth of e‐commerce and associated home deliveries, understanding the role of drivers in shaping the customer experience in last‐mile delivery is now more crucial than ever. Delivery drivers increasingly act as retailers' frontline employees and are thus instrumental in developing pseudorelationships between customers and retailers. Industry surveys, however, reveal that drivers admit to engaging in unprofessional behaviors with customers and often refuse to address customers' requests beyond package delivery. Following a middle‐range theorizing approach and leveraging Cognitive Appraisal Theory, we investigate how two negative driver behaviors, inappropriate behavior and inflexibility, impact customer satisfaction and repurchase intentions. We also examine the moderating effect of driver affiliation, private versus outsourced, in altering the magnitude of customer responses. Results from a scenario‐based experiment indicate that while the negative effects of driver inappropriate behavior on customer outcomes are mediated by anger, the effects of driver inflexibility are mediated by sadness. Moreover, the negative effect of driver inflexibility on customer outcomes is weaker for outsourced logistics than for private fleet drivers. In turn, driver inappropriate behavior exhibits similar negative effects on customer outcomes for both driver affiliations. These findings offer important insights for last‐mile delivery strategy and operations research and practice.

Perbaikan Rute Distribusi Bahan Baku untuk Minimasi Jarak Tempuh dan Beban Kerja pada UKM Kuliner Mie

Delivery activities have a great role for a business actor. However, delivery issues are there all the time. This was experienced by a noodle culinary SME that experienced delays in the delivery of various noodle raw materials and noodle toppings which caused noodle sales activities to be disrupted. In addition, these raw materials have a lifespan (without preservatives) so they must be delivered according to a predetermined schedule and hours. This research will solve this problem by minimizing delays through finding the shortest mileage delivery route. Because each delivery location has its own schedule and time window, the Nearest Neighbor method by paying attention to the time window is used. Based on the calculation results, each distribution route with the shortest distance was obtained, as evidenced by a reduction in the middle route by 0.23 km and the northern route by 5.88 km. In addition, this proposed delivery route was able to save fuel consumption on the middle route by 3% and the northern route by 10%. In terms of the workload aspect, car fleet drivers were also reduced by 31% and motorbike fleet drivers by 47%.

A machine learning pipeline for fuel-economical driving model

PurposeA cost-effective way to achieve fuel economy is to reinforce positive driving behaviour. Driving behaviour can be controlled if drivers can be alerted for behaviour that results in poor fuel economy. Fuel consumption must be tracked and monitored instantaneously rather than tracking average fuel economy for the entire trip duration. A single-step application of machine learning (ML) is not sufficient to model prediction of instantaneous fuel consumption and detection of anomalous fuel economy. The study designs an ML pipeline to track and monitor instantaneous fuel economy and detect anomalies.Design/methodology/approachThis research iteratively applies different variations of a two-step ML pipeline to the driving dataset for hatchback cars. The first step addresses the problem of accurate measurement and prediction of fuel economy using time series driving data, and the second step detects abnormal fuel economy in relation to contextual information. Long short-term memory autoencoder method learns and uses the most salient features of time series data to build a regression model. The contextual anomaly is detected by following two approaches, kernel quantile estimator and one-class support vector machine. The kernel quantile estimator sets dynamic threshold for detecting anomalous behaviour. Any error beyond a threshold is classified as an anomaly. The one-class support vector machine learns training error pattern and applies the model to test data for anomaly detection. The two-step ML pipeline is further modified by replacing long short term memory autoencoder with gated recurrent network autoencoder, and the performance of both models is compared. The speed recommendations and feedback are issued to the driver based on detected anomalies for controlling aggressive behaviour.FindingsA composite long short-term memory autoencoder was compared with gated recurrent unit autoencoder. Both models achieve prediction accuracy within a range of 98%–100% for prediction as a first step. Recall and accuracy metrics for anomaly detection using kernel quantile estimator remains within 98%–100%, whereas the one-class support vector machine approach performs within the range of 99.3%–100%.Research limitations/implicationsThe proposed approach does not consider socio-demographics or physiological information of drivers due to privacy concerns. However, it can be extended to correlate driver's physiological state such as fatigue, sleep and stress to correlate with driving behaviour and fuel economy. The anomaly detection approach here is limited to providing feedback to driver, it can be extended to give contextual feedback to the steering controller or throttle controller. In the future, a controller-based system can be associated with an anomaly detection approach to control the acceleration and braking action of the driver.Practical implicationsThe suggested approach is helpful in monitoring and reinforcing fuel-economical driving behaviour among fleet drivers as per different environmental contexts. It can also be used as a training tool for improving driving efficiency for new drivers. It keeps drivers engaged positively by issuing a relevant warning for significant contextual anomalies and avoids issuing a warning for minor operational errors.Originality/valueThis paper contributes to the existing literature by providing an ML pipeline approach to track and monitor instantaneous fuel economy rather than relying on average fuel economy values. The approach is further extended to detect contextual driving behaviour anomalies and optimises fuel economy. The main contributions for this approach are as follows: (1) a prediction model is applied to fine-grained time series driving data to predict instantaneous fuel consumption. (2) Anomalous fuel economy is detected by comparing prediction error against a threshold and analysing error patterns based on contextual information.

A Bayesian regression analysis of truck drivers’ use of cooperative adaptive cruise control (CACC) for platooning on California highways

Cooperative Adaptive Cruise Control (CACC), as an advanced version of adaptive cruise control (ACC), automates brake and engine controls based on the information received from wireless V2V communications and remote sensors, enabling smaller vehicle-following time gaps. It can improve the safety of vehicle platooning and increase fuel savings. As an extension of our previous investigation of truck drivers’ acceptance of CACC, this case study investigates factors affecting the use of CACC for truck platooning. Nine commercial fleet drivers were recruited to operate two following trucks in a CACC-enabled string on freeways in Northern California. We analyzed the usage of CACC time gaps and its correlation with truck drivers’ stated preferences for these time gaps, and we found that the highest preferred Gap 3 (1.2 s) was used the most. Moreover, a Bayesian regression model was built to show that truck drivers are more likely to disengage CACC when driving in low-speed traffic or on downgrades where this CACC could not provide sufficient braking. In high-speed traffic or on upgrades, truck drivers are more likely to engage CACC, particularly at Gap 3. Truck position, however, does not affect truck drivers’ time gap selection. The findings encourage the adoption of CACC in the trucking industry through implementing driver-preferred time gaps and responsive braking systems, and operating on routes with minimal interference to truck speeds.

Influence of telematics of ubi insurance on the management of the fleet of company vehicles

The advent and development of connected technologies and the adaptation of large collections of data are changing the face of all industries. A technological area that is gaining more and more in the era of automation and digitization of processes is the scope of utility telematics used mainly in the transport industry. The use of devices based on telematics technology allows for effective management of the vehicle fleet. The information collected and processed by the algorithm makes it possible to increase productivity, reduce costs and increase the safety of business fleets. One of the developing global trends is the use of telematics in the insurance industry to improve the area of risk assessment, and thus to better match the offer to a specific entity. The data flow between an insurer and their customers is growing exponentially, making the need for big data adaptation a cornerstone in the insurer's technological landscape. The aim of the article is to present the results of questionnaire studies presenting the driver's assessment before and after installing telematics devices on board the vehicle. The studies indicate the need to deal with aggressive business fleet drivers and their driving behaviour that has an impact on incidents and traffic incidents when traversing short- and long-haul routes. The comprehensive survey is also used to propose a solution that detects the risks posed by unsafe driving incidents on the road, taking into account the behavioural and emotional factors of the driver. The results of these studies will help the insurance industry to assess driving risks more accurately and propose a personalized premium calculation solution based on driver behaviour, which is most important for loss prevention in business fleets

Bringing Behavior-Analytic Theory to Eco-driving Research: Verbal Rules Mediate the Effectiveness of Feedback for Professional and Civilian Drivers

Suboptimal efficiency in activities involving the consumption of fossil fuels, such as driving, contributes to a miscellany of negative environmental, political, economic, and social externalities. Demonstrations of the effectiveness of feedback interventions can be found in countless settings, as can demonstrations of individual differences in sensitivity to feedback interventions. Mechanisms providing feedback to drivers about fuel economy are becoming standard equipment in new vehicles but vary considerably in their constitution. A keystone of the philosophy of radical behaviorism and its related scientific discipline, behavior analysis, is the acknowledgment that verbal behavior plays a role in mediating individual responses to delayed contingencies. In the current feasibility study, samples of individuals’ verbal behavior (rules about how to drive efficiently) were collected in the context of two eco-driving feedback interventions—one with commercial fleet drivers and one with civilian drivers. Analysis revealed that the rate at which drivers generated novel verbal rules (per week) accounted for a substantial proportion of the variability in relative efficiency gains across participants. Findings support the utility of behavior-analytic conceptual tools in this field of research, such as the basic distinction between contingency-shaped and rule-governed behaviors and the elaboration of direct-acting and indirect-acting contingencies.

Do drivers differ in their attitudes on speed limit compliance between work and private settings? Results from a group of Nigerian drivers

Existing evidence suggests that drivers, particularly those who work in companies with strong road safety cultures exhibit different sets of speeding attitudes and behaviours in work and private driving. Using Ajzen and Fishbein’s (1980) Theory of Planned behaviour (TPB) and on-road driving experiments, this study examined the self-reported and objective behaviour of driving within posted speed limits for a sample of fleet drivers. The findings show that the TPB explained up to 24% of the variance in intention to comply with speed limits. Drivers’ attitude emerged as the most significant predictor and strongest correlate with intentions to comply with the speed limit in both work and private vehicle.Further analysis revealed participants had a higher intention to comply with speed limits in their work than private vehicle. Also, investigation of the relationship between TPB variables and observed speeding behaviour suggests that participants with higher intention to comply with the speed limit or high perceived behavioural control (PBC), exceeded the speed limit less often than those with lower intention to comply with the speed limit or low PBC. The findings have important theoretical and applied implications for development of better speed limit compliance interventions to improve driving behaviour, and road safety in general.

Drivers420.com: Organizing drivers recruitment for transporters

Subject area Entrepreneurship, new venture management, new venture planning. Study level/applicability The case involves various issues within entrepreneurship and the new venture management field such as business model, SWOT analysis, Pros and Cons analysis and challenges faced during the idea commercialization phase. Thus, this case can be used for covering multiple perspectives related to entrepreneurship and new venture planning. This case is useful for discussion in a session on opportunity recognition at ideation stage. This case is also ideal to teach the “Business Model Canvas”, which is fast gaining centre-stage for modern enterprises. The case also covers issues within strategic management such as what actually constitutes a strategy. Case overview The case is based on a field study and primary data collected by interviewing the co-founder of the portal www.drivers420.com. This case describes a situation in which Malkit Singh Bal (Bal) Partner of Bal Road lines shares with Mr Amarpreet Singh (Singh), who was about to be hired as a consultant for Bal Roadlines, information regarding the rise in fraud and crime carried out by fleet drivers and asks him to help him find a solution to the problem. Expected learning outcomes Prepare a “Business Model Canvas” for the successful operation of business by identifying intended customer segment, value proposition, cost structures and revenue streams. Conduct “Pros and Cons” analysis for starting a business. Conduct “SWOT” analysis for starting a business. Understand what actually constitutes a strategy and understand the five elements constituting strategy. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code CSS 3: Entrepreneurship.

Decentralized refueling of compressed natural gas (CNG) fleet vehicles in Southern California

While some compressed natural gas (CNG) vehicle fleets have a station at their base for central refueling, others lack refueling capability at their fleet depot and must rely on publicly available stations. To understand this kind of decentralized refueling behavior, we surveyed 133 drivers of CNG fleet vehicles at six public stations across the Los Angeles region. Nearly one-third of CNG fleet drivers were solely reliant upon public refueling for their operations. For each driver's refueling trip, we used GIS to compare the chosen station's proximity to the driver's fleet base and their deviation from the shortest path between their previous and next stops relative to all other stations they could have chosen. This revealed-preference approach shows that fleet drivers chose the station with the smallest deviation over the station closest to base by a 6:1 ratio, though this ratio varied by the driver's availability of central refueling and type of vehicle and route. Given that public stations remain essential to meeting decentralized refueling demand for other fleets as well as consumers, these findings have important implications for fleets that are both considering the adoption of CNG vehicles and the additional investment of hosting central refueling infrastructure at their base.

Drivers420.com: Organising Transporters

This case describes a situation in which Malkit Singh Bal (Bal) partner of Bal Roadlines shares with Mr. Ghura, who was about to be hired as consultant for Bal Roadlines, about the rise in issue of fraud and crime done by the fleet drivers and asked him to help a way out to solve the problem. The purpose of this case is to provide an opportunity to the participants of an MBA or Management Executive Education Programme to step into the shoes of Ghura, a consultant and to explore the options and to select the best possible option to offer a solution to Bal. The context for this involvement is the rise in fraud and crime done by the fleet drivers.

Role of thrill and adventure seeking in risky work-related driving behaviours

BackgroundRoad trauma had been identified as the leading cause of work-related death in Australia. Research in general driving behaviours has shown that sensation seekers with high levels of thrill and adventure seeking traits are more likely to drive in a risky manner. However, thrill and adventure seeking has not been explicitly examined as a predictor of risky driving behaviour in work-related settings. MethodologyUsing a large sample of fleet drivers (N=892) from three Australian organisations, the current study examined the role of thrill and adventure seeking in predicting risky work-related driving behaviours and involvement in crash and traffic offence. Hardcopies and online version of the questionnaire were sent to the worksite measuring participants' demographic information, work driving exposure, thrill and adventure seeking trait, work-related risky driving behaviours, and self-reported crash and traffic offences in the past 12months. ResultsThe results indicated that thrill and adventure seeking was a significant predictor of risky work-related driving behaviours. However, thrill and adventure seeking did not significantly predict self-reported crashes and traffic offences. ConclusionThe current study implies that dispositional characteristics, such as thrill and adventure seeking, should be considered when implementing interventions in fleet safety.

Individual and contextual variables enhance transfer for a workplace eco-driving intervention

The adoption of energy efficient driving styles and practices, eco-driving, has been recognized in the literature as an option for reducing vehicle energy consumption. Prior eco-driving research has looked at the effectiveness of various eco-driving programs. However, the characteristics of the individuals participating in fleet eco-driving programs and the role of the supervisor as an advocate for eco-driving practices have remained relatively unexamined. An eco-driving intervention intended to increase eco-driving behaviors in a work organization was conducted with fleet drivers in three public organizations. Drawing from the workplace training literature, we hypothesized that employee eco-driving behaviors will increase after the implementation of an eco-driving intervention, but that these behaviors will be dependent on the participant’s pre-intervention motivation and support from their supervisor for implementing eco-driving practices. Survey data were collected pre- and post-intervention from 51 fleet drivers (average age 45.3 and 33% female), and results indicate that the eco-driving intervention was effective when either high levels of pre-intervention motivation or supervisor support were present.

Electric vehicle adopters in Lisbon: motivation, utilization patterns and environmental impacts

The introduction of alternative vehicle technologies as a response to pressure regarding fossil fuel dependency in the transportation sector poses several questions regarding their impact on travel and driving behaviour and also on the environment. This project aims to assess electric vehicle users’ motivations, daily patterns and vehicle operation and management. Promoted by EMEL – Lisbon’s mobility and parking municipal company – the project was publicized among Lisbon’s electric vehicle users, who were offered, as an incentive, a green permit which allowed them to park the vehicles for free on the street within the city’s metropolitan central area. Data were gathered over a period of one year from 25 users (private and fleet drivers) through interviews and on-board diaries, comprising a total of 5,132 trips, 49,785 km travelled and a total of 8,529 kWh charged related to 831 charges. The results indicate that environmental and economic (lower running costs) factors are the main drivers for electric vehicle adoption by private users, whereas fleet drivers mention their company’s image as the motive behind the deployment of this technology in fleets. Private users’ energy consumption and CO2 emissions were also estimated. When compared to conventional internal combustion engine vehicles running on gasoline or diesel, electric vehicles reveal considerable reductions in both energy consumption and CO2 emissions in a Well-to-Wheel life cycle approach. These decreases are between 35–43% for energy consumption and 58–63% for CO2 emissions.

Attitudes towards and perceptions of eco-driving and the role of feedback systems

This paper addresses whether eco-driving may be encouraged by providing drivers with feedback, and how eco-driving attitudes fit with other environmental attitudes. Eight focus groups, including fleet drivers, discussed how feedback and other motives might affect driving behaviour. A survey of 350 respondents investigated attitudes towards saving fuel, the role of incentives and use of eco-friendly products. The focus groups' findings show that the environment is a lower priority than comfort and convenience, that feedback might provide a stimulus to eco-driving and that saving money was less important than saving time. The attitude survey showed that price, convenience, attitudes and eco-driving are not conceptually linked together, that convenience is rated as more important than saving money from fuel efficiency and that although the environment is of concern, it is not a high enough priority to increase fuel efficiency. The findings are discussed in relation to the low level of priority given to environmental concerns and the inability of financial incentives presenting significant challenges in terms of changing the subjective norms of the majority of drivers. Practitioner summary: This paper, using focus groups and a questionnaire, aims to understand how feedback devices, attitudes and motivation can improve eco-driving behaviours. The incentive to save money by better fuel economy was found to be insufficient, and roles for feedback devices and how information is presented are identified.

Coaching fleet drivers: A randomised controlled trial (RCT) of ‘short coaching’ interventions to improve driver safety in fleet drivers

The issue of coaching as a potential learning methodology has been highlighted by a European Union task force (HERMES, 2010) and has been the subject of a number of research papers over the past two years. This paper reports the results from a RCT study of coaching with fleet drivers based on a sample of 327 participants, and drawing on results from insurance claims, company fleet car records on mileage and driving convictions. The results indicate there was no statistically significant difference between the intervention (coaching) group and the control (instruction) group. The paper considers why this may be the case and contrasts the results with other papers where statistically significant results are reported in coaching and driving research.

Initial development of a practical safety audit tool to assess fleet safety management practices

Work-related vehicle crashes are a common cause of occupational injury. Yet, there are few studies that investigate management practices used for light vehicle fleets (i.e. vehicles less than 4.5tonnes). One of the impediments to obtaining and sharing information on effective fleet safety management is the lack of an evidence-based, standardised measurement tool. This article describes the initial development of an audit tool to assess fleet safety management practices in light vehicle fleets. The audit tool was developed by triangulating information from a review of the literature on fleet safety management practices and from semi-structured interviews with 15 fleet managers and 21 fleet drivers. A preliminary useability assessment was conducted with 5 organisations. The audit tool assesses the management of fleet safety against five core categories: (1) management, systems and processes; (2) monitoring and assessment; (3) employee recruitment, training and education; (4) vehicle technology, selection and maintenance; and (5) vehicle journeys. Each of these core categories has between 1 and 3 sub-categories. Organisations are rated at one of 4 levels on each sub-category. The fleet safety management audit tool is designed to identify the extent to which fleet safety is managed in an organisation against best practice. It is intended that the audit tool be used to conduct audits within an organisation to provide an indicator of progress in managing fleet safety and to consistently benchmark performance against other organisations. Application of the tool by fleet safety researchers is now needed to inform its further development and refinement and to permit psychometric evaluation.

Dynamics in Behavioral Response to Fuel-Cell Vehicle Fleet and Hydrogen Fueling Infrastructure

Transportation is a major contributor of carbon dioxide and other greenhouse gas emissions from human activity. It accounts for approximately 14% of total anthropogenic emissions globally and about 27% in the United States. Growing concern regarding the impacts of climate change and greenhouse gas emissions, along with petroleum dependence and energy security, has led to innovations in automotive and fuel technology. However, the behavioral response to the newest transportation technologies, such as hydrogen fuel-cell vehicles (FCVs) and fueling infrastructure, is not well understood. The results of an exploratory hydrogen FCV fleet study, which focused on fleet drivers’ attitudes and perceptions over a 7-month period in 2006, are examined. The study employed a longitudinal survey design, with three phases and one focus group. There were limitations to the exploratory data set generated from this study (e.g., small sample size, self-selection bias, and generalizability). However, the results provided insights into participants’ responses to the FCV and hydrogen fueling infrastructure over time and could help to inform further inquiry. Higher levels of hydrogen exposure were correlated with increased comfort with hydrogen, especially among those who were less experienced. Early adopters of the technology generally felt safer driving the FCV than later adopters. Respondents mostly felt safe refueling the FCV. As experience with the FCV increased, participants felt increasingly safe with the vehicles. The driving range was considered a limitation. Furthermore, over the course of the study, participant perception of vehicle range increased because of learning.

Economic pressure, multi‐tiered subcontracting and occupational health and safety in Australian long‐haul trucking

PurposeThe purpose of this research is to analyse the relationship between economic pressure, multi‐tiered subcontracting and occupational health and safety (OHS) outcomes for employee and owner/drivers in long‐haul trucking, using Australian evidence.Design/methodology/approachThe analysis is based on direct interviews with 300 long‐haul drivers, using a structured questionnaire along with an examination of documentary records, statistics and government reports. Qualitative and quantitative data were gathered on self‐reported acute and chronic injuries, the incidence of occupational violence, truck crashes, indicators of illicit drug use, hours of work/fatigue and psychological distress.FindingsVariations between owner/drivers and employees working for small and large firms were investigated. Overall, owner/drivers reported worse OHS than small fleet and, more especially, large fleet drivers. Evidence also indicated a connection between economic pressure, the expansion of contingent work and negative OHS outcomes.Research limitations/implicationsFurther longitudinal and comparative research is needed to test the hypothesized link between competitive pressures, supply chain rationalization and OHS outcomes. Research to investigate these issues in other countries is required in order to compare findings with those for Australia and to assess the effectiveness of new enforcement initiatives.Practical implicationsFindings suggest the need for policy interventions aimed at improving OHS to address commercial practices, including elaborate subcontracting chains, more explicitly than is currently the case with road transport regulation. Recent moves in this direction are identified.Originality/valueUnlike manufacturing, healthcare and the public sector, there have been few studies of the OHS effects associated with contingent work arrangements in transport. In addition to helping to fill this gap the paper provides evidence on the effects of competitive pressure and supply chains on work practices and OHS.

An application of the driver behaviour questionnaire in an Australian organisational fleet setting

This study reports on the utilisation of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours of a sample of Australian fleet drivers (N = 443). Surveys were posted to participants who agreed to participate in the study. PCA factor analysis with oblique rotation identified a three factor solution which supports previous research that has demonstrated distinctions between different driving practices (e.g., errors, highway code violations and aggressive driving violations). However, a larger number of items traditionally related with highway code violations were found to be associated with aggressive driving acts among the current sample. Additional analysis revealed that the DBQ factors were negatively related with self-reported traffic offences, although at a multivariate level only the number of kilometres driven each year (i.e., exposure) proved to be predictive of incurring fines/demerit points. This paper further outlines the major findings of the study and highlights implications regarding the utilisation of the DBQ within fleet settings to examine on-road behaviour among professional drivers.