Big data analytics received much attention in the last decade and is viewed as one of the next most important strategic resources for organizations. Yet, the role of employees' data literacy seems to be neglected in current literature. The aim of this study is twofold: (1) it develops data literacy as an organization competency by identifying its dimensions and measurement, and (2) it examines the relationship between data literacy and governmental performance (internal and external). Using data from a survey of 120 Dutch governmental agencies, the proposed model was tested using PLS-SEM. The results empirically support the suggested theoretical framework and corresponding measurement instrument. The results partially support the relationship of data literacy with performance as a significant effect of data literacy on internal performance. However, counter-intuitively, this significant effect is not found in relation to external performance.
MULTIFILE
This paper investigates whether encouraging children to become more physically active in their everyday life affects their primary school performance. We use data from a field quasi‐experiment called the Active Living Program, which aimed to increase active modes of transportation to school and active play among 8‐ to 12‐year‐olds living in low socioeconomic status (SES) areas in the Netherlands. Difference‐in‐differences estimations reveal that while the interventions increase time spent on physical activity during school hours, they negatively affect school performance, especially among the worst‐performing students. Further analyses reveal that increased restlessness during instruction time is a potential mechanism for this negative effect. Our results suggest that the commonly found positive effects of exercising or participating in sports on educational outcomes may not be generalizable to physical activity in everyday life. Policymakers and educators who seek to increase physical activity in everyday life need to weigh the health and well‐being benefits against the probability of increasing inequality in school performance.
Abstract Business Process Management (BPM) is an important discipline for organizations to manage their business processes. Research shows that higher BPM-maturity leads to better process performance. However, contextual factors such as culture seem to influence this relationship. The purpose of this paper is to investigate the role of national culture on the relationship between BPM-maturity and process performance. A multiple linear regression analysis is performed based on data from six different countries within Europe. Although the results show a significant relationship between BPM-maturity and process performance, no significant moderation effect of national culture has been found. The cultural dimension long term orientation shows a weak negative correlation with both BPM-maturity and process performance. Through a post-hoc moderation analysis on each dimension of BPM-maturity, we further find that long term orientation negatively moderates the relationship between process improvement and process performance. Three other moderation effects are also discovered. The results of this study contribute to insights into the role of culture in the field of BPM.
MULTIFILE
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
