The Netherlands are one of the frontrunners in stimulating electric mobility in Europe when it comes to the charging infrastructure density and electric vehicle adoption. Municipalities play an instrumental role in the rollout of public charging infrastructure while they have little insight in the relevant key performance indicators of the charging infrastructure as a means to support effective decision making. This paper aims to contribute to providing a more thorough understanding of relevant key performance indicators for public charging infrastructure. An approach is presented that explores result and performance indicators to support policy makers optimizing the roll out of and improvement of the business case for charging infrastructure.
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Het tweejarige onderzoeksprogramma The Network is the Message richt zich op de effectiviteit van sociale media: wanneer zijn sociale media effectief, wat bepaalt die effectiviteit en hoe kunnen we dit meten? Startpunt in deze management summary van thema 2 ‘meten is nog niet weten’ is het inzicht dat het allemaal begint met doelstellingen. Doelstellingen zijn van essentieel belang om te kunnen bepalen of je succes hebt of niet. En bij doelstellingen horen Key Performance Indicators (KPI’s), met een set zorgvuldig geselecteerde metrics die de beste bijdrage leveren om die doelstellingen in kaart te brengen. Op die manier kun je ook bepalen of je je tijd en middelen goed inzet en je misschien effectiever zou zijn deze door deze anders te verdelen.
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From the article: With increasing investments in business rules management (BRM), organizations are searching for ways to value and benchmark their processes to elicitate, design, accept, deploy and execute business rules. To realize valuation and benchmarking of previously mentioned processes, organizations must be aware that performance measurement is essential, and of equal importance, which performance indicators to apply to the performance measurement processes. However, scientific research on BRM, in general, is limited and research that focuses on BRM in combination with performance indicators is nascent. The purpose of this paper is to define performance indicators for previously mentioned BRM processes. We conducted a three round focus group and three round Delphi Study which led to the identification of 14 performance indicators. Presented results provide a grounded basis from which further, empirical, research on performance indicators for BRM can be explored.
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Developers of charging infrastructure, be it public or private parties, are highly dependent on accurate utilization data in order to make informed decisions where and when to expand charging points. The Amsterdam University of Applied Sciences, in close cooperation with the municipalities of Amsterdam, Rotterdam, The Hague, Utrecht, and the Metropolitan Region of Amsterdam Electric, developed both the back- and front-end of a charging infrastructure assessment platform that processes and represents real-life charging data. Charging infrastructure planning and design methods described in the literature use geographic information system data, traffic flow data of non-EV vehicles, or geographical distributions of, for example, refueling stations for combustion engine vehicles. Only limited methods apply real-life charging data. Rolling out public charging infrastructure is a balancing act between stimulating the transition to zero-emission transport by enabling (candidate) EV drivers to charge, and limiting costly investments in public charging infrastructure. Five key performance indicators for charging infrastructure utilization are derived from literature, workshops, and discussions with practitioners. The paper describes the Data Warehouse architecture designed for processing large amounts of charging data, and the web-based assessment platform by which practitioners get access to relevant knowledge and information about the current performance of existing charging infrastructure represented by the key performance indicators developed. The platform allows stakeholders in the decision-making process of charging point installation to make informed decisions on where and how to expand the already existing charging infrastructure. The results are generalizable beyond the case study regions in the Netherlands and can serve the roll-out of charging infrastructure, both public and semi-public, all over the world.
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Objective: The Tilburg Frailty Indicator (TFI) is a self-report user-friendly questionnaire for assessing multidimensional frailty among community-dwelling older people. The main aim of this study is to re-evaluate the validity of the TFI, both cross-sectionally and longitudinally, focusing on the predictive value of the total TFI and its physical, psychological, and social domains for adverse outcomes disability, indicators of healthcare utilization, and falls. Methods: The validity of the TFI was determined in a sample of 180 Dutch communitydwelling older people aged 70 years and older. The participants completed questionnaires including the TFI, the Groningen Activity Restriction Scale (GARS) for assessing disability, and questions with regard to health care utilization and falls in 2016 and again one year later. Results: The physical and psychological domains of the TFI were significantly correlated as expected with adverse outcomes disability, many indicators of healthcare utilization, and falls. Regression analyses showed that physical frailty was mostly responsible for the effect of frailty on the adverse outcomes. The cross-sectional and longitudinal predictive validity of total frailty with respect to disability and receiving personal care was excellent, evidenced by Areas Under the Curves (AUCs) >0.8. In most cases, using the cut-off point 5 for total frailty ensured the best values for sensitivity and specificity. Conclusion: The present study provided new, additional evidence for the validity of the TFI for assessing frailty in Dutch community-dwelling older people aiming to prevent or delay adverse outcomes, including disability.
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The objective of the study described in this paper is to define safety metrics that are based on the effectiveness of risk controls. Service providers define and implement such risk controls in order to prevent hazards developing into an accident. The background of this research is a specific need of the aviation industry where small and medium-sized enterprises lack large amounts of safety-related data to measure and demonstrate their safety performance proactively. The research department of the Aviation Academy has initiated a 4-year study, which will test the possibility to develop new safety indicators that will be able to represent safety levels proactively without the benefit of large data sets. As part of the development of alternative safety metrics, safety performance indicators were defined that are based on the effectiveness of risk controls. ICAO (2013) defines a risk control as “a defence with specific mitigation actions, preventive controls or recovery measures put in place to prevent the realization of a hazard or its escalation into an undesirable consequence”. Examples of risk controls are procedures, education and training, a piece of equipment etc. It is crucial for service providers to determine whether the introduced risk controls are indeed effective in reducing the targeted risk. ICAO (2013) describes the effectiveness of risk control as "the extent to which the risk control reduces or eliminates the safety risks”, but does not provide guidance on how to measure the effectiveness of risk control. In this study, a generic metrics for the effectiveness of risk controls based on their effectiveness was developed. The definition of the indicators allows, for each risk control, derivation of specific indicators based on the generic metrics. The suitability of the metrics will subsequently be tested in pilot studies within the aviation industry.
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This article describes a method for promoting sustainable business practices in the hospitality sector and focusses on energy usage in hotels. It raises questions about the actual impact of eco-labels on actual environmental performance.
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Abstract: Due to rapidly aging human populations, frailty has become an essential concept, as it identifies older people who have higher risk of adverse outcomes, such as disability, institutionalization, lower quality of life, and premature death. The Tilburg Frailty Indicator (TFI) is a user-friendly questionnaire based on a multidimensional approach to frailty, assessing physical, psychologic, and social aspects of human functioning. This review aims to explore the efficiency of the TFI in assessing frailty as a means to carry out research into the antecedents and consequences of frailty, and its use both in daily practice and for future intervention studies. Using a multidimensional approach to frailty, in contexts where health care professionals or researchers may have no time to interview or examine the client, we recommend employing the TFI because there is robust evidence of its reliability and validity and it is easy and quick to administer. More studies are needed to establish whether the TFI is suitable for intervention studies not only in the community, but also for specific groups such as patients in the hospital or admitted to an emergency department. We conclude that it is important to not only determine the deficits that frail older people may have, but also to assess their balancing strengths and resources. In order to be able to meet the individual needs of frail older persons, traditional and often fragmented elderly care should be developed toward a more proactive elderly care, in which frail older persons and their informal network are in charge.
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This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
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