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This study investigates for the first time how public charging infrastructure usage differs under the presence of diverse pricing models. About 3 million charging events from different European countries were classified according to five different pricing models (cost-free, flat-rate, time-based, energy-based, and mixed) and evaluated using various performance indicators such as connection duration; transferred energy volumes; average power; achievable revenue; and the share of charging and idle time for AC, DC, and HPC charging infrastructure. The study results show that the performance indicators differed for the classified pricing models. In addition to the quantitative comparison of the performance indicators, a Kruskal–Wallis one-way analysis of variance and a pairwise comparison using the Mann–Whitney-U test were used to show that the data distributions of the defined pricing models were statistically significantly different. The results are discussed from various perspectives on the efficient design of public charging infrastructure. The results show that time-based pricing models can improve the availability of public charging infrastructure, as the connection duration per charging event can be roughly halved compared to other pricing models. Flat-rate pricing models and AC charging infrastructure can support the temporal shift of charging events, such as shifting demand peaks, as charging events usually have several hours of idle time per charging process. By quantifying various performance indicators for different charging technologies and pricing models, the study is relevant for stakeholders involved in the development and operation of public charging infrastructure.
In any dimension d≥2, there is no known example of a low-discrepancy sequence which possesses Poisssonian pair correlations. This is in some sense rather surprising, because low-discrepancy sequences always have β-Poissonian pair correlations for all 0<β<1/d and are therefore arbitrarily close to having Poissonian pair correlations (which corresponds to the case β=1/d). In this paper, we further elaborate on the closeness of the two notions. We show that d-dimensional Kronecker sequences for badly approximable vectors α→ with an arbitrary small uniformly distributed stochastic error term generically have β=1/d-Poissonian pair correlations.
Previous work has indicated that testing can enhance memory for subsequently studied new information by reducing proactive interference from previously studied information. Here, we examined this forward testing effect in children’s spatial memory. Kindergartners (5–6 years) and younger (7–8 years) and older (9–10 years) elementary school children studied four successively presented 3 x 3 arrays, each composed of the same 9 objects. The children were asked to memorize the locations of the objects that differed across the four arrays. Following presentation of each of the first three arrays, memory for the object locations of the respective array was tested (testing condition) or the array was re-presented for additional study (restudy condition). Results
revealed that testing Arrays 1 to 3 enhanced children’s object location memory for Array 4 relative to restudying. Moreover, children in the testing condition were less likely to confuse Array 4 locations with previous locations, suggesting that testing reduces the buildup of proactive interference. Both effects were found regardless of age. Thus, the current findings indicate that testing is an effective means to resolve proactive interference and, in this way, to enhance children’s learning and remembering of spatial information even before the time of school entry.
This article examines interweaving collective histories in different formerly colonized regions of the world: 1. Migratory movements from the territory of the former Ottoman Empire to the Americas, specifically to Brazil, and 2. transregional migration between different regions within China. On the basis of empirical data, we discuss sociological biographical research as an approach to analyzing migration and social mobility as transgenerational processes. In the case of Syrians in Brazil who have fled from the civil war, these processes are reflected in transnational family structures, transgenerational mandates, and knowledge transmission. In the case of domestic migration within China, the “mission” that families give their children is social advancement through education (e.g., Crabb 2010; Fong 2004). In the context of anti-Western discourses in China, it can be demonstrated that postcolonial discourses are functional in the effort to regain former international strength and national prosperity, and that discourses on “becoming a modern citizen” pervade family aspirations. The article is intended as a plea for i) taking a closer look at historical and contemporary South-South relations, and ii) situating current migration movements historically. It ties into global historical and sociological debates on “shared/common histories” and “intertwined histories."
Die Gesundheitswirtschaft ist im hohen Maße von Technisierung und Digitalisierung betroffen, welche neue Kompetenzen bei den verantwortlichen Akteur:innen erfordert. Die Fähigkeiten, die für den professionellen Umgang mit diesen Entwicklungspro zessen relevant sind, werden in der Literatur mit verschiedenen Begriffen umschrieben: Inhalte wie Technik, Digitalität, Medien, Informatik, Computer oder Informations- und Kommunikationstechnologien (IKT) werden mit Fähigkeiten und Fertigkeiten re präsentierenden Begriffen wie Kompetenzen, Literacy oder Skills verknüpft. Deutlich wird bisher jedoch nicht, welche spezifi schen Fähigkeiten die im Diskurs geforderten Konstrukte jeweils adressieren, worin sie sich unterscheiden und welchen Beitrag sie zum Ziel beruflicher Handlungskompetenz leisten.
Many experts project generative AI will impact the types of competencies that are valued among working professionals. This is the first known academic study to explore the views of business practitioners about the impacts of generative AI on skill sets. This survey of 692 business practitioners showed that business practitioners widely use generative AI, with the most common uses involving research and ideation, drafting of business messages and reports, and summarizing and revising text. Business practitioners report that character-based traits such as integrity and soft skills will become more important. Implications for teaching business communication are discussed.
The bond between polymer fibers and the surrounding cementitious matrix is essential for the development of concrete reinforcement. The single fiber pull-out test (SFPT) is the standard characterization technique for testing the bond strength. However, the different phases of debonding cannot be distinguished by the SFPT. This study investigates the debonding of different polymer fibers from the surrounding cementitious matrix with a modified SFPT and proposes methods to change the SFPT setup to generate more valuable information on the debonding mechanism. The SFPT was equipped with linear variable differential transformers (LVDT), digital image correlation (DIC) and acoustic emission (AE) analysis. The results demonstrate that the modified SFPT allows a better understanding of the different phases of debonding during fiber pull-out. Furthermore, bond strength values calculated by different methods reveal that the chemical bond of the investigated polymers is not different as reported by previous studies. Deformation measurements performed using LVDTs and DIC are suitable measuring techniques to characterize the debonding mechanism in SFPT. A correlation between recorded AE and debonding phases was not found.
The necessity for resource-efficient manufacturing technologies requires new developments within the field of plastic processing. Lightweight design using wood fibers as sustainable reinforcement for thermoplastics might be one solution. The processing of wood fibers requires special attention to the applied thermal load. Even at low processing temperatures, the influence of the dwell time, temperature and shear force is critical to ensure the structural integrity of fibers. Therefore, this article compares different compounding rates for polypropylene with wood fibers and highlights their effects on the olfactory, visual and mechanical properties of the injection-molded part. The study compares one-step processing, using an injection-molding compounder (IMC), with two-step processing, using a twin-scew-extruder (TSE), a heating/cooling mixer (HCM) and an internal mixer (IM) with subsequent injection molding. Although the highest fiber length was achieved by using the IMC, the best mechanical properties were achieved by the HCM and IM. The measured oxidation induction time and volatile organic compound content indicate that the lowest amount of thermal damage occurred when using the HCM and IM. The advantage of one-time melting was evened out by the dwell time. The reinforcement of thermoplastics by wood fibers depends more strongly on the structural integrity of the fibers compared to their length and homogeneity
Die Reinraumtechnik zielt darauf ab, mit gerichteten partikelfreien Luftströmungen die im Reinraum stattfindenden Prozesse vor Fremdeinflüssen zu schützen. Die Spritzgussproduktion stellt die Reinraumtechnik dabei vor besondere Herausforderungen. Im Bereich des Spritzgusswerkzeugs können aufgrund des relativ hohen Temperaturunterschieds zur Reinraumluft Kamineffekte auftreten, die der Reinraumströmung entgegen wirken. Im Folgenden wird deshalb der thermische Einfluss eines Spritzgusswerkzeugs exemplarisch bei unterschiedlichen Temperaturen untersucht. Dazu werden Strömungsvisualisierungen mittels Nebel und Schlierenfotografie sowie Strömungssimulationen genutzt. Bereits relativ
niedrige Werkzeugtemperaturen von 40 °C reichten aus, um einen Kamineffekt im
Werkzeugbereich entstehen zu lassen, der die Reinraumströmung ungünstig beeinflusst. Erst durch den Einsatz einer Filter-Fan-Unit über dem kritischen Werkzeugbereich konnte die Luftströmung auch bei höheren Werkzeugtemperaturen kontrolliert werden.
This study presents an approach to collect and classify usage data of public charging infrastructure in order to predict usage based on socio-demographic data within a city. The approach comprises data acquisition and a two-step machine learning approach, classifying and predicting usage behavior. Data is acquired by gathering information on charging points from publicly available sources. The first machine learning step identifies four relevant usage patterns from the gathered data using an agglomerative clustering approach. The second step utilizes a Random Forest Classification to predict usage patterns from socio-demographic factors in a spatial context. This approach allows to predict usage behavior at locations for potential new charging points. Applying the presented approach to Munich, a large city in Germany, results confirm the adaptability in complex urban environments. Visualizing the spatial distribution of the predicted usage patterns shows the prevalence of different patterns throughout the city. The presented approach helps municipalities and charging infrastructure operators to identify areas with certain usage patterns and, hence different technical requirements, to optimize the charging infrastructure in order to help meeting the increasing demand of electric mobility.
Generalized Ng–Kundu–Chan model of adaptive progressive Type-II censoring and related inference
(2024)
The model of adaptive progressive Type-II censoring introduced by Ng et al. (2009) (referred to as Ng–Kundu–Chan model) is extended to allow switching from a given initial censoring plan to any arbitrary given plan of the same length. In this generalized model, the joint distribution of the failure times and the corresponding likelihood function is derived. It is illustrated that the computation of maximum likelihood and Bayesian estimates are along the same lines as for standard progressive Type-II censoring. However, the distributional properties of the estimators will usually be different since the censoring plan actually applied in the (generalized) Ng–Kundu–Chan model is random. As already mentioned in Cramer and Iliopoulos (2010), we directly show that the normalized spacings are independent and identically exponentially distributed. However, it turns out that the spacings themselves are generally dependent with mixtures of exponential distributions as marginals. These results are used to study linear estimators. Finally, we propose an algorithm for generating random numbers in the generalized Ng–Kundu–Chan model and present some simulation results. The results obtained also provide new findings in the original Ng–Kundu–Chan model; the corresponding implications are highlighted.
Driving forest machines on wet soils causes irreversible soil compaction, often associated with intensive rut formation and inaccessibility of wheeled forest machines for future forest operations. The German forestry equipment manufacturer FHS, Forsttechnik Handel & Service GmbH, engineered a forwarder, the Trac 81/11, equipped with conventional, well-proved bogie-axles embraced by a closed rubber track. At the center of the bogie-axle, four additional supportive rollers are placed to increase the load-carrying section between the tires of the bogie-axle. The study aimed to characterize the principle concept and the trafficability of the forwarder by analyzing the footprint area, the contact pressure, the rut formation on forest sites and the slippage during driving. Therefore, the effective contact area was measured on steel plates and rut formation was analyzed on a case study basis. Results showed that the supportive rollers increase the contact surface area by about 1/3. By this, a decrease of peak loads below the wheels and a more homogenous load distribution were observed. However, the contact surface area is still clearly divided into three parts; the area between the supportive rollers and the wheels does not take any load. Results of the rut formation were diverse: After 20 passes with 26,700 kg total mass, rut depth varied between 12.6 and 212.5 mm. Overall, the new undercarriage concept of FHS demonstrated a generally positive performance. The engineered forwarder contributes to reduce the environmental impact associated with log extraction.
Background Personalized mRNA vaccines are promising new therapeutic options for patients with cancer. Because mRNA vaccines are not yet approved for first-line therapy, the vaccines are presently applied to individuals that received prior therapies that can have immunocompromising effects. There is a need to address how prior treatments impact mRNA vaccine outcomes.
Method Therefore, we analyzed the response to BioNTech/Pfizer’s anti-SARS-CoV-2 mRNA vaccine in 237 oncology outpatients, which cover a broad spectrum of hematologic malignancies and solid tumors and a variety of treatments. Patients were stratified by the time interval between the last treatment and first vaccination and by the presence or absence of florid tumors and IgG titers and T cell responses were analyzed 14 days after the second vaccination.
Results Regardless of the last treatment time point, our data indicate that vaccination responses in patients with checkpoint inhibition were comparable to healthy controls. In contrast, patients after chemotherapy or cortisone therapy did not develop an immune response until 6 months after the last systemic therapy and patients after Cht-immune checkpoint inhibitor and tyrosine kinase inhibitor therapy only after 12 months.
Conclusion Accordingly, our data support that timing of mRNA-based therapy is critical and we suggest that at least a 6-months or 12-months waiting interval should be observed before mRNA vaccination in systemically treated patients.
Virtual meeting recordings have become a common part of virtual and hybrid workplace environments. Meeting recordings offer potential benefits (speedy transcript production, expedited information sharing, searchable information, inclusion of visual and tonal expressions) and drawbacks (difficulty discussing sensitive issues, employee privacy, limited off-the-record capabilities, and employee concerns over sharing recordings). Given this variance, policies for virtual meetings are a necessity. Managers can successfully implement a policy by co-creating policy preferences with employees in open-ended and nonjudgmental conversations that openly discuss potential benefits, drawbacks, and employee concerns. Topics such as when to record, when not to record, how to gain consent, and who will have administrative and sharing rights should be covered. Accessibility concerns, use or rejection of software features, for how long and where meeting recordings should be stored, and emerging issues such as use of virtual reality meetings and AI tools are areas of less urgency that may be part of the conversations. Managers should deliver policy preferences to a group of representatives from Human Resources, Information Technology, and the executive team to compose the policy, request a legal review, then introduce and implement it in the organization.
This study investigates the impact of generative AI systems like ChatGPT on semi-structured decision-making, specifically in evaluating undergraduate dissertations. We propose using Davis’ technology acceptance model (TAM) and Schulz von Thun’s four-sides communication model to understand human–AI interaction and necessary adaptations for acceptance in dissertation grading. Utilizing an inductive research design, we conducted ten interviews with respondents having varying levels of AI and management expertise, employing four escalating-consequence scenarios mirroring higher education dissertation grading. In all scenarios, the AI functioned as a sender, based on the four-sides model. Findings reveal that technology acceptance for human–AI interaction is adaptive but requires modifications, particularly regarding AI’s transparency. Testing the four-sides model showed support for three sides, with the appeal side receiving negative feedback for AI acceptance as a sender. Respondents struggled to accept the idea of AI, suggesting a grading decision through an appeal. Consequently, transparency about AI’s role emerged as vital. When AI supports instructors transparently, acceptance levels are higher. These results encourage further research on AI as a receiver and the impartiality of AI decision-making without instructor influence. This study emphasizes communication modes in learning-ecosystems, especially in semi-structured decision-making situations with AI as a sender, while highlighting the potential to enhance AI-based decision-making acceptance.
Exploring stakeholder perspectives: Enhancing robot acceptance for sustainable healthcare solutions
(2023)
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialized robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question but also one of technology acceptance. The answer to this question supports entrepreneurial opportunities to develop sustainable healthcare solutions.
In this paper, we analyze the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appearance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an important factor that is not included in existing technology acceptance models. Finally, the discovery of a significant discrepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved in caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stakeholder mapping is a valid tool to analyze the interdependencies for the acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further analyze these issues.
Recently, the SQL standardization Committee published a specification for support of the concept called Row Pattern Recognition in SQL. That way, the focus for the members of the Committee turned back to a kernel issue of the language, after standardizing the storage and manipulation of data formats, such as XML and JSON. In this paper we discuss the specified features using several examples and show to what extent different relational database systems as well as Data Analytics tools have integrated them. At the end of the paper, we describe the main inaccuracies of the proposal and the ways how to solve them. From our point of view, the following should be modified in one of the future proposals of the standard in relation to this concept: (a) Naming of several pattern navigation operations is inappropriate and should be changed; (b) The concept of implicit definition for row pattern variables in DEFINE should be changed to explicit; (c) The set of existing functions should be extended.
We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling identifies contours of given field limits in less than 3% of the reference measurement time.
Reliability analysis of power MOSFET’s with the help of compact models and circuit simulation
(2002)
High temperature reliability on automotive power modules verified by power cycling tests up to 150°C
(2003)
Das Team levelup der TH Rosenheim hat sich im Rahmen des SDE 21/22 das Ziel gesetzt, mittels Aufstockung den urbanen Raum nachzuverdichten. Hauptaugenmerk ist hierbei die Schaffung neuen Wohnraums mit einer energetischen Sanierung zum Plusenergiegebäude zu kombinieren. Erreicht wird dies durch ein Energiekonzept mit PV- und PVT-Kollektoren, Absorptionswärmepumpe und einer Fassadenheizung. Der bauphysikalische Schwerpunkt in diesem Bericht liegt bei einer Sanierungsfassade mit thermischer Aktivierung der Bestandswand.
The Challenges and Opportunities of AI-Assisted Writing: Developing AI Literacy for the AI Age
(2023)
Generative AI may significantly disrupt the teaching and practice of business communication. This study of 343 communication instructors revealed a collective view that AI-assisted writing will be widely adopted in the workplace and will require significant changes to instruction. Key perceived challenges include less critical thinking and authenticity in writing. Key perceived benefits include more efficiency and better idea generation in writing. Students will need to develop AI literacy—composed of application, authenticity, accountability, and agency—to succeed in the workplace. Recommendations are provided for instructors and administrators to ensure the benefits of AI-assisted writing can outweigh the challenges.
Background
The admission to a nursing home is a critical life-event for affected persons as well as their families. Admission related processes are lacking adequate participation of older people and their families. To improve transitions to nursing homes, context- and country-specific knowledge about the current practice is needed. Hence, our aim was to summarize available evidence on challenges and care strategies associated with the admission to nursing homes in Germany.
Methods
We conducted a scoping review and searched eight major international and German-specific electronic databases for journal articles and grey literature published in German or English language since 1995. Further inclusion criteria were focus on challenges or care strategies in the context of nursing home admissions of older persons and comprehensive and replicable information on methods and results. Posters, only-abstract publications and articles dealing with mixed populations including younger adults were excluded. Challenges and care strategies were identified and analysed by structured content analysis using the TRANSCIT model.
Results
Twelve studies of 1,384 records were finally included. Among those, seven were qualitative studies, three quantitative observational studies and two mixed methods studies. As major challenges neglected participation of older people, psychosocial burden among family caregivers, inadequate professional cooperation and a lack of shared decision-making and evidence-based practice were identified. Identified care strategies included strengthening shared decision-making and evidence-based practice, improvement in professional cooperation, introduction of specialized transitional care staff and enabling participation for older people.
Conclusion
Although the process of nursing home admission is considered challenging and tends to neglect the needs of older people, little research is available for the German health care system. The perspective of the older people seems to be underrepresented, as most of the studies focused on caregivers and health professionals. Reported care strategies addressed important challenges, however, these were not developed and evaluated in a comprehensive and systematic way. Future research is needed to examine perspectives of all the involved groups to gain a comprehensive picture of the needs and challenges. Interventions based on existing care strategies should be systematically developed and evaluated to provide the basis of adequate support for older persons and their informal caregivers.
Fault and anomaly detection in district heating substations: A survey on methodology and data sets
(2023)
District heating systems are essential building blocks for affordable, low-carbon heat supply. Early detection and elimination of faults is crucial for the efficiency of these systems and necessary to achieve the low temperatures targeted for 4th generation district heating systems. Especially methods for fault and anomaly detection in district heating substations are currently of high interest, as faults in substations can be repaired quickly and inexpensively, and smart meter data are becoming widely available. In this paper, we review recent scientific publications presenting data-driven approaches for fault and anomaly detection in district heating substations with a focus on methods and data sets. Our review indicates that researchers use a wide variety of methods, mostly focusing on unsupervised anomaly detection rather than fault detection. This is due to a lack of labeled data sets, preventing the use of supervised learning methods and quantitative analysis. Together with the lack of publicly available data sets, this impedes the accurate comparison of individual methods. To overcome this impediment, increase the comparability of different methods and foster competition, future research should focus on establishing publicly available data sets, and industry-relevant metrics as benchmarks.
Dieser Beitrag untersucht anhand des DAX im Zeitraum Januar 2010 bis Juli 2022, ob Unternehmen mit hohen bzw. niedrigen ESG-Scores einen Performanceunterschied aufweisen. Die Ergebnisse zeigen für kein Portfolio eine signifikante Über- oder Unterperformance. Lediglich die besten ESG-Firmen tendieren in normalen Marktphasen zu einer Unterperformance. Investoren erleiden beim Berücksichtigen von ESG-Scores auf den DAX risikoadjustiert keinen Nachteil und können zugleich ihrem guten Gewissen Genüge tun.
Es ist ein Experiment! In diesem Beitrag wird untersucht, wie das KI-gestützte textbasierte Dialogprogramm „ChatGPT“ im Rechnungswesen und Berichtswesen eingesetzt werden kann, um Routineaufgaben zu automatisieren, die Effizienz zu steigern und Finanzdaten besser zu verstehen. Die Erstellung des gesamten Beitrags selbst erfolgte mithilfe von ChatGPT, d.h., nicht nur die von der KI generierten Passagen, die als Screenshots gezeigt werden, sondern wesentliche Teile des vorliegenden Textes, wurden von der KI erstellt und anschließend inhaltlich und sprachlich durch den Autor redigiert und ergänzt. Damit soll einerseits das Potenzial der Anwendung in der Praxis gezeigt und verdeutlicht werden, dass der Umgang mit den Werkzeugen der KI in Zukunft unerlässlich sein wird, andererseits sollen aber auch die Risiken und Bedenken thematisiert werden. Denn nur allzu leicht werden in Zukunft die Grenzen einer Urheberschaft verschwimmen.
Manufacturing-Execution-Systeme (MES) werden in der Fertigungsindustrie dazu eingesetzt, einen durchgehenden Informationsfluss zwischen den an der Fertigung beteiligten Systemen herzustellen. Von der Vernetzung aller an der Produktion beteiligten Systeme wird dabei eine gesteigerte Produktivität auf Shop-Floor-Ebene erwartet. Beim Durchlauf des beispielhaft gezeigten Fertigungsauftrages wurden durch den Einsatz von MR-CM©, einem von der Maschinen-fabrik Reinhausen entwickelten und implemen-tierten MES, bereits einige Produktivitätspotenziale im Vergleich mit der konventionellen Abwicklung ohne Einsatz des MES deutlich. Diese resultieren im Wesentlichen aus der Eliminierung von nicht wertschöpfenden Schnittstellenproblemen zwischen den an der Auftragsdurchführung beteiligten Maschinen. Die erzielten Produktivitätszuwächse bestehen im Kern aus einer Verkürzung der Maschinenrüstzeiten, was zu einer Reduktion der Produktionskosten und einer Zunahme der Produktionsflexibilität führt und zu einer Reduzierung der Werkzeugbestände sowie der damit verbundenen Kapitalbindungskosten.
Die Projektauswahl stellt eine Herausforderung insbesondere für mittelständische Industrieunternehmen dar. Abhängigkeiten verschiedener Alternativen und vorgegebene Investitionsbudgets führen bei Anwendung von in der Praxis standardmäßig eingesetzten Verfahren regelmäßig zu suboptimalen Projektkombinationen. In enger Abstimmung mit einem Automobilzulieferer wurde ein Ansatz zur Projektauswahl unter Berücksichtigung von Ressourcen und laufenden Projekten entwickelt sowie technisch umgesetzt. Implementierte Praxistests belegen Verbesserungen bei der Projektauswahl, aber auch bei der Budgeteinhaltung, der Fixkostenreduzierung sowie der Angebotspreisbestimmung.
Logistic activity, in particular transportation, produces green house gases (GHG). For different purposes GHG need to be allocated to objects. This paper studies how to allocate the GHG volume of a transportation process (delivery tour) to the single shipments moved by the process. First, it identifies classes of generic allocation schemes and presents 15 allocation methods. Second, since the majority of these methods has not been designed for allocating GHG, we apply and compare them in the short distance transport context within a numerical example. The aim is to study how the schemes perform according to criteria. We suggest using causality, efficiency, empty core robustness, symmetry, individual rationality, coalition stability, ease of application, and set robustness as appraisal criteria and attempt to mainstream the discussion by recommending selected allocation methods.
The assessment of greenhouse gas (GHG) emissions of supply chain activities is performed to create transparency across the supply chain and to identify emission-cutting opportunities. Literature provides several generic and case study approaches to estimate GHG emissions. But research often focuses on products. This paper sheds light on how the greenhouse performance of a fast-moving consumer goods (FMCG) distribution network depends on several (FMCG specific) variables to set up a “CO2 network footprint”. Within a quantitative computational study, the distribution network footprint of an existing FMCG manufacturer is analyzed. Three options being fundamentally able to reduce total GHG emissions are identified: number of distribution centers, performance of the engaged logistics service provider and shipment structure. First, transportation processes for the investigated FMCG manufacturer are analyzed to derive GHG emissions caused by different distribution shipments. Second, initial data are manipulated to simulate variable changes, that is, different logistics structures. Third, results are reported and analyzed to show up how different changes in logistics structures may reduce GHG, without technological propulsion or use of regenerative energy.
Distribution network design is about recommending long-term network structures in an environment where logistic variables like transportation costs or retailer order sizes dynamically change over time. The challenge for management is to recommend an optimal network configuration that will allow for longer term optimal results despite of environmental turbulences. This paper studies the robustness of cost-optimized FMCG (fast-moving consumer goods) distribution networks. It aims at observing the impact of changing variables/conditions on optimized logistic structures in terms of the optimal number and geographical locations of existing distribution centers. Five variables have been identified as relevant to the network structure. A case study approach is applied to study the robustness of an existing, typical, and optimized FMCG network. First, distribution network data of a German manufacturer of FMCG are recorded and analyzed. A quantitative model is set up to reflect the actual cost structure. Second, a cost optimal network configuration is determined as a benchmark for further analysis. Third, the variables investigated are altered to represent changes, both isolated (ceteris paribus) and in combination (scenario analysis). Each one of the variables investigated proves to be fundamentally able to suggest a change of the optimal network structure. However, the scenario analysis indicates that the expected changes will by and large compensate each other, leaving the network in near optimal condition over an extended period of time.
Purpose
Tooling is a common component of an industrial product’s manufacture. Specific tooling is devised to serve the fabrication of a particular product, while generic tooling can be used in the manufacture of multiple products. In the latter case, companies are confronted with the problem of fairly allocating the indirect costs of the tooling. This article studies how to allocate costs of generic tooling to single production orders.
Methodology
Ten allocation methods (AMs) are described that are in principle suited to the distribution of generic tooling costs to production orders. Since the presented methods have for the most part been discussed in differing contexts, we apply them to a specified generic tooling problem for comparison. Evaluation of the various methods is based on 16 criteria. Reasoning is supported by a computational Monte Carlo simulation. Furthermore, we suggest using the Analytical Hierarchy Process (AHP) to elaborate one final proposition concerning the most preferable allocation scheme.
Findings
The article reports the single allocation rules’ performances for different allocation scenarios. The described characteristics refer to fairness, efficiency, and simplicity as well as to empty-core performance. Using AHP analysis allows for the aggregation of the rules’ criteria ratings. Thus, especially suitable allocation schemes for the problem at hand are identified.
Practical implications
An allocation is required for budgeting reasons and also for the definition of projects’ bottom-up sales prices. Selecting the “right” AM is important, as a suboptimal AM can result in unfair allocation vectors, which will act as incentives to stop using the common resource, potentially leading to higher total costs.
Originality/value of the article
Research on the comparison of AMs is typically performed for certain purposes, such as enterprise networks, horizontal cooperative purchasing scenarios, or municipal service units. This article will augment the research evaluating AMs by introducing a novel set of evaluation criteria and by providing an in-depth comparison of AMs suited for the allocation of generic tooling costs.
In this paper, we propose a combined methodology for the selection of distribution centres (DCs) by integrating and balancing economic, environmental and social sustainability aspects. The analytic network process (ANP) permits to systematically evaluate possible DCs on the basis of a situation-specific decision structure. A systematic development of the decision networks, which is one of the core challenges using the ANP, is supported by the process analysis method which we extend for that purpose. The validity and soundness of the proposed framework are demonstrated by means of a case study. The case study results reveal that omitting aspects of sustainability can lead to unfortunate results.
There are growing concerns in the food industry about how supply chains can be managed in a more sustainable way. When distribution activities are outsourced to a logistics service provider (LSP), shippers need to evaluate the LSPs they may (potentially) engage in order to ensure that supply chain sustainability goals are met. In this paper, we present a methodology for LSP evaluation and focus on the ecological dimension of sustainability. We examine how the network carbon footprint of a real-world distribution system is affected by the LSP network that is chosen to forward goods from production facilities to customers. To do this, we analyze the shipment data of an existing Fast Moving Consumer Goods (FMCG) manufacturer. A quantitative distribution network model is set up to study the network carbon footprint of 125 scenarios. Real-world shipments are forwarded via five generic, idealized types of LSP networks. In total, 625 network carbon footprints, specified by three distribution logistics variables and the structure of the LSP network, have been calculated. The results show that LSP structures practicing a geographically decentralized consolidation of shipments are most efficient in reducing of greenhouse gas (GHG) emissions. Furthermore, the effects of changing the manufacturer's and the LSP's strategies for deciding on the tonnage to be forwarded via the LSP network or moved by direct transports are quantified. Finally, we estimate the GHG effect of improving the capacity utilization of the vehicles that move the products.
This research studies effects that the average increase in travel times due to road traffic congestion has on characteristics of an existing distribution network. It presents the most detailed estimate of ‘on-the-road’ effects on distribution network characteristics up to now, from the network modelling perspective and from the processed data point of view. A concrete network model allowing for the representation of all relevant transportation flows is presented. The processed traffic information relies on navigation service data. The use of such data allows the requirements that arise for the traffic analysis of a whole distribution network to be met. It is shown that this data source may considerably contribute in forthcoming research. The effects of traffic congestion are quantified to get insights into the extent to which regular traffic congestion affects distribution network characteristics and to understand the mitigating effect when the number of distribution centres is increased.
Purpose
The purpose of this paper is to propose a comprehensive methodology and a problem-specific model for the configuration of the optimal strategic supplier portfolio in terms of traditional, performance-related objectives and sustainability targets.
Design/methodology/approach
To bridge the research gap, i.e., to align strategic supplier portfolio selection with corporate sustainability targets, a hybrid model of the analytic network process (ANP) and goal programming (GP) is developed. To validate the model, a case example is presented and managerial feedback is collected.
Findings
By enabling the integration of sustainability targets into strategic supplier portfolio configuration, the hybrid ANP-GP model contributes to research in the area of sustainable supply chain management. Results indicate that simplifying the model by omitting one or more details may lead to unfortunate actions.
Research limitations/implications
The model has been applied using a case example in the automotive industry. To strengthen the findings, it should be examined under other terms as well.
Practical implications
Integrating economic, environmental, and social targets into strategic supplier portfolio configuration reduces supply risks and promotes the achievement of the sustainability goals of the purchasing company.
Social implications
Strategic supplier selection counts among the decisions that have an impact on the environment and society for several years. Configuring economically rational, environmentally friendly, and socially responsible supplier bases supports worldwide efforts towards sustainable development.
Originality/value
Although sustainable supplier selection has gained importance in recent years, this is the first time that a comprehensive model for the determination of the optimal strategic supplier portfolio in terms of performance-related objectives and sustainability targets has been proposed.
This research quantifies the impact that regular road traffic congestion has on the CO2 emissions of a real-world distribution network, and it studies the consequences when the number of distribution centers changes. For this purpose, this study makes use of a network model allowing for a detailed representation of all relevant transport operations, including production flows between factories and distribution centers, line haul shipments between distribution centers and customers, and round/delivery trips between transshipment points and retailer locations for the last mile. The processed trip and traffic information does not rely on standard traffic data collection approaches, such as interviews, in situ technologies, or floating car data, but the road traffic data are retrieved from an online navigation service, such as Bing Maps, Google Maps, Inrix, Here, and TomTom. This study proves that online navigation services may considerably contribute to future research projects analyzing CO2 sensitivities and greenhouse gas cutting opportunities in logistics networks.
Online-Navigationsdienste ermöglichen die Planung einer Reise von einem Start- zu einem Ziel-Ort. Die Berechnung von Reisedauer und Streckenlänge erfolgt auf Grundlage eines detaillierten Straßennetzes und unter Berücksichtigung Orts- und Zeit-typischer Verkehrsaufkommen. Dieser Beitrag zeigt, inwiefern Online-Navigationsdienste die Planung und Analyse logistischer Systeme unterstützen können. Er thematisiert insbesondere die Qualität der zur Verfügung gestellten Verkehrsinfrastrukturdaten und hebt die komparativen Vorteile des Einsatzes von Online-Navigationsdiensten im Vergleich zu ‚herkömmlichen‘ Verkehrsinformationsquellen hervor. Ein Anwendungsfall, bei dem die durch Transportaktivitäten verursachten CO2-Emissionen eines Güternahverkehrsnetzes untersucht werden, verdeutlicht die gewonnenen Erkenntnisse.
The European Norm EN 16258 was published in 2012 to provide a common methodology for the calculation and declaration of energy consumption and greenhouse gas emissions related to any transport operation. The objective was to offer a pragmatic and scientifically-acceptable approach that allows a wide group of users to prepare standardized, accurate, credible, comparable, and verifiable energy consumption and emission declarations. However, in its current form, EN 16258 contains gaps and ambiguities, and leaves room for interpretation, which makes comparisons of supply chains difficult. This research aims to overcome the shortcomings in the domain of allocating emissions from road freight transport operations to single shipments. Based on a discussion of emission drivers and the results of numerical experiments comparing the allocation vectors created by the EN 16258 allocation rules with those generated by the Shapley value, which is claimed to be the benchmark, ‘distance’ is identified as the single most useful unit for bridging the trade-off between accuracy and simplicity better than the other recommended allocation schemes. Thus, this paper claims that future versions of EN 16258 should only allow the allocation unit ‘distance.’ This will promote the accurateness, simplicity, consistency, transparency, and comparability of emission declarations.
Unternehmen sind häufig mit Situationen konfrontiert, in denen schnell Entscheidungen bezüglich der Auswahl mehrerer Handlungsalternativen gefunden werden müssen. Mathematische Verfahren können hierbei unterstützen, z. B. für die Ermittlung einer ersten Diskussionsbasis. Verfügbare Softwarelösungen errechnen zwar häufig optimale Ergebnisse, zeigen jedoch Schwächen bei der praktischen Anwendbarkeit. So ist eine Einarbeitung in komplexe Optimierungssoftware für die teilweise sporadisch auftretenden Probleme in der Regel für Unternehmen nicht möglich, unter anderem auch unter Anbetracht der teilweise hohen Kosten der Standardsoftware und dem benötigten hohen Einarbeitungsaufwand. Gerade Problemstellungen in Fachbereichen, die nicht auf mathematische Problemlösung spezialisiert sind, münden daher regelmäßig in Ineffizienzen. Basierend auf den in der Literatur diskutierten Lösungsansätzen wurde ein praxisorientierter Ansatz zur Entscheidungsunterstützung für Rucksackprobleme bzw. 0–1 Probleme mithilfe von Genetischen Algorithmen (GA) entwickelt und technisch in Microsoft Excel® umgesetzt. Ein Praxistest bei einem chinesischen Textilunternehmen belegt erhöhte Effektivität und Effizienz. Die Software kann kostenfrei nach MIT Lizenz unter http://www.solvega.de/ heruntergeladen werden.
Differences in road infrastructure, such as capacity, congestion, speed limits affect the productivity and the costs of short-distance freight operations. This article introduces a novel methodology that is based on navigation service data to measure the effects in terms of cost per kilometer using navigation and shipment data. The methodology is applied to five terminals of a forwarding cooperation and has been able to document significant differences in cost per kilometer across the terminals. The research results can be used by logistics service providers to better understand how productivity and thus profitability is affected by the quality of the transportation infrastructure in the particular areas they operate in. Furthermore, the insights will help these companies for better, i.e. cost-based pricing and will allow to document why and where prices need to be adapted.
This research explores logistics-related leverages in the responsibility of retailers for improving the environmental performance of a Fast Moving Consumer Goods (FMCG) distribution network. We examine opportunities for modifying the network carbon footprint by changing network design variables. To do so, a quantitative distribution network model is established, and 150 scenarios are calculated by modifying real-world shipment data from an existing multinational FMCG manufacturer. Four distribution variables are identified for a many-to-many and a hub-and-spoke network structure. Two variables affect the distribution network and two interfere in the shipment structure by manipulating weight and/or the delivery date. This research sheds light on the extent of the changes in greenhouse gas (GHG) emissions of the distribution network that result from modifications in the logistics variables. The greatest effect on the quantity of GHG emissions can be observed when an anticipation horizon for orders is introduced. When shipments are consolidated and delivered only weekly or biweekly from the manufacturer to the retailers, GHG emissions drop significantly. Another opportunity for retailers to cut down GHG emissions is based on the concept of minimum order quantities where shipments to a retailer location are bundled until a certain weight is reached. Additionally, total GHG emissions of distribution may be reduced by raising the tonnage limit, thereby triggering direct shipments between the manufacturer’s facilities and the retailer locations, or by raising the tonnage limit, which triggers direct shipments in the logistics service provider network. The extent of GHG reduction is assessed for all investigated variables.
Purpose
The purpose of this paper is to explore the impact of information technology (IT) on supply chain performance in the automotive industry. Prior studies that analyzed the impact of IT on supply chain performance report results representing the situation of the “average industry.” This research focuses on the automotive industry because of its major importance in many national economies and due to the fact that automotive supply chains do not represent the supply chain of the average industry.
Design/methodology/approach
A research model is proposed to examine the relationships between IT capabilities, supply chain capabilities, and supplier performance. The model divides IT capabilities into functional and data capabilities, and supply chain capabilities into internal process excellence and information sharing. Data have been collected from 343 automotive first-tier suppliers. Structural equation modeling with partial least squares is used to analyze the data.
Findings
The results suggest that functional capabilities have the greatest impact on internal process excellence, which in turn enhances supplier performance. However, frequent and adequate information sharing also contributes significantly to supplier performance. Data capabilities enable supply chain capabilities through their positive impact on functional capabilities.
Practical implications
The findings will help managers to understand the effect of IT implementation on company performance and to decide whether to invest in the expansion of IT capacities.
Originality/value
This research reports the impact of IT on supply chain performance in one of the most important industries in many industrialized countries, and it provides a new perspective on evaluating the contribution of IT on firm performance.
Im Zeitalter von Big Data werden immense Informationsbestände aus unterschiedlichen Quellen gesammelt. Die Daten sind häufig unvollständig, unsicher und ungenau. Ein Beispiel hierfür ist das OpenStreetMap Projekt, bei dem Nutzer auf der ganzen Welt einmal mehr und einmal weniger „sauber“ bzw. vollständig Daten beisteuern. In diesem Beitrag wird gezeigt, ob sich diese Daten eignen um ein betriebswirtschaftliches Problem zu lösen. Ein konkretes Fallbeispiel verdeutlicht, wie gut Standortentscheidungen einer Fast Food Kette unter Anwendung fortgeschrittener datenanalytischer Verfahren, wie bspw. Künstlicher Neuronaler Netze, Entscheidungsbäume und Logit-Modelle, nachempfunden werden können. Als Grundlage dienen die Daten des OpenStreetMap Projekts. Im Konkreten geht es darum, potenzielle Filialstandorte hinsichtlich deren Güte mittels OpenStreetMap Daten zu klassifizieren und die prognostizierten Lokationen mit tatsächlichen Standortentscheidungen zu vergleichen. Dabei zeigt sich, dass die Daten des OpenStreetMap Projekts grundsätzlich für die Prognose von Standorten geeignet sind. Allerdings ist die Wahl des datenanalytischen Verfahrens von Bedeutung. Im vorliegenden Fall konnte mit Hilfe der Künstlichen Neuronalen Netze das beste Prognoseergebnis erzielt werden.
This research presents a decision support methodology for the multi-criteria supplier selection and order allocation problem. The proposed approach supports purchasing managers in assembling mid-term supplier portfolios while making them aware of the trade-offs between the supplier sustainability, the purchasing costs, and the overall supply risk. First, we propose a multi-objective optimization model with three objectives: to maximize the supplier sustainability, to select the supplier portfolio with the lowest purchasing costs, and to minimize the supply risk. Our model extends existing mathematical approaches that follow the portfolio theory fathered by H. Markowitz by integrating the aspect ‘risk’ into the supplier selection problem. Secondly, since we allow for integer variables in our model—in contrast to the classical Markowitz portfolio theory—we use the ε-constraint method to visualize the efficient surface. The possibility of considering the non-dominated set of supplier portfolios is advantageous for purchasing managers as they gain a picture of the different optimal supplier portfolios and are able to analyze the trade-offs between the different purchasing goals before making a decision. Finally, we illustrate the applicability of the proposed methodology in a real-world supplier selection and order allocation case from the automotive industry. In the example case, we identify 1754 optimal supplier portfolios that may be assembled based on the eight available suppliers. Our analyses show that each optimal portfolio consists of two suppliers, with one specific supplier being included in each portfolio. Furthermore, four suppliers are not part of any optimal solution.
At present, there is no globally accepted standard for the allocation of greenhouse gas (GHG) emissions to shipments in road freight transportation. The only official international standard for emission calculation of transport operations is the European Norm EN-16258. However, even this norm still allows choosing from several alternative emission allocation schemes. This research aims to harmonize the process of GHG declarations for supply chains by identifying among all allocation units specified by EN-16258 the one that describes a shipment's contribution to GHG emissions best. For this purpose, concepts of the cooperative game theory are used. First, we develop three transport scenarios that allow studying a shipment's effect on GHG: a vehicle routing problem, a network flow model, and a mixed scenario. Our approach extends previous research projects because we take into account that shipment characteristics in terms of origin, destination, weight, and volume consume transport capacities to different degrees, impact the routing of the commercial vehicles and, thus, determine GHG. Second, we present the results of a computational study that bases on the introduced transport scenarios and that compares the allocation vectors resulting from the EN-16258 allocation rules with the Shapley value, which serves as a benchmark for a shipment's contribution to GHG. Furthermore, we show how often the EN-16258 allocation principles are in line with a set of game theoretical fairness criteria. The results indicate that the allocation unit ‘distance’ is the closest to the game theory benchmark and most often in line with game theoretical fairness criteria.
This research presents a novel, state-of-the-art methodology for solving a multi-criteria supplier selection problem considering risk and sustainability. It combines multi-objective optimization with the analytic network process to take into account sustainability requirements of a supplier portfolio configuration. To integrate ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. The proposed model is a non-standard portfolio selection problem with four objectives: (1) minimizing the purchasing costs, (2) selecting the supplier portfolio with the highest logistics service, (3) minimizing the supply risk, and (4) ordering as much as possible from those suppliers with outstanding sustainability performance. The optimization model, which has three linear and one quadratic objective function, is solved by an algorithm that analytically computes a set of efficient solutions and provides graphical decision support through a visualization of the complete and exactly-computed Pareto front (a posteriori approach). The possibility of computing all Pareto-optimal supplier portfolios is beneficial for decision makers as they can compare all optimal solutions at once, identify the trade-offs between the criteria, and study how the different objectives of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company's strategy best. The approach has been applied to a real-world supplier portfolio configuration case to demonstrate its applicability and to analyze how the consideration of sustainability requirements may affect the traditional supplier selection and purchasing goals in a real-life setting.
Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.
Purpose
Due to the growing percentage share of urban dwellers, the physical distribution of products faces altering conditions. This research explores the effects that urbanization has on the performance of a fast-moving consumer goods distribution network. A focus is set on changes in distribution cost, the cost-minimal network design, and greenhouse gas emissions.
Design/methodology/approach
The analyses are based on a quantitative distribution network model of an existing manufacturer of consumer goods.
Findings
The results indicate that the foreseen population shift will affect the network's economic and environmental performance. Effects are, among others, due to differences in the efficiency of supplying urban and nonurban regions. The combined effects of urbanization and the development of the population size will even more affect the network's performance.
Originality/value
Research dealing with distribution logistics and urbanization primarily focuses on city logistics. In this paper, the object of analysis is the entire distribution system.
Considering climate change, recent political debates often focus on measures to reduce CO2 emissions. One key component is the reduction of emissions produced by motorized vehicles. Since the amount of emission directly correlates to the velocity of a vehicle via energy consumption factors, a general speed limit is often proposed. This article presents a methodology to combine openly available topology data of road networks from OpenStreetMap (OSM) with pay-per-use API traffic data from TomTom to evaluate such measures transparently by analyzing historical real-world circumstances. From our exemplary case study of the German motorway network, we derive that most parts of the motorway network on average do not reach their maximum allowed speed throughout the day due to traffic, construction sites and general road utilization by network participants. Nonetheless our findings prove that the introduction of a speed limit of 120 km per hour on the German autobahn would restrict 50.74% of network flow kilometers for a CO2 reduction of 7.43% compared to the unrestricted state.
Environmental regulations force car manufacturers to renew the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. In turn, automotive companies face the task of identifying the “right” powertrain technology portfolio consisting of, for example, internal combustion engines and electric vehicles, because the selection of a particular powertrain technology portfolio affects different company targets simultaneously. What makes this decision even more challenging is that future market shares of the different technologies are uncertain. Our research presents a new decision-support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable profit, the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines “a posteriori” decision-making with multi-objective optimization. In an application case, we feed the outlooks of selected market studies into the proposed decision-support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Our findings indicate that for the proposed GHG restriction at work in 2030 in the European Union, no optimal powertrain technology portfolio with less than 35% of vehicles equipped with an electric motor exists.
Road freight transportation accounts for a great share of the anthropogenic greenhouse gas (GHG) emissions. In order to provide a common methodology for carbon accounting related to transport activities, the European Committee for Standardization has published the European Norm EN-16258. Unfortunately, EN-16258 contains gaps and ambiguities and leaves room for interpretation, which makes the comparison of the environmental performance of different logistics networks still difficult and hinders the identification of best practices. This research contributes to the identification of particularly meaningful principles for the allocation of GHG to shipments in road freight transportation by presenting an analytical framework for studying the performance of the EN-16258 allocation schemes with respect to accuracy, fairness, and the GHG minimizing incentive. In doing so, we continue previous studies that analyzed two important aspects of the EN-16258 allocation rules: accuracy and fairness. This study provides further insights into this allocation problem by investigating the incentive power of the different allocation schemes to opt for the GHG minimal way of running a road freight network. First, we complement the list of transport scenarios introduced in prior studies and present two novel scenarios. Second, we carry out a series of numerical experiments to compare the EN-16258 allocation rules with respect to accuracy, fairness, and the GHG minimizing incentive. We find that the results may differ significantly for the two scenarios, suggesting a case-by-case recommendation. This is particularly interesting because the first scenario confirms the results of the prior studies, while the second scenario rather contradicts them.
Many supply chains within developing countries lack transparency and are fraught with fraud, corruption, and a substantial number of intermediaries. For several decades, the cocoa sector has faced multiple social, economic, and environmental challenges, some of which include the issue of child labor and very low incomes for farmers, leading to poor living conditions. Blockchain technology has a high potential to reduce—or completely eradicate—some of these hurdles. In this article, we present a blockchain-based solution based on the open-source framework Hyperledger Fabric for the cocoa supply chain to promote transparency and reduce fraud. In doing so, we explicitly describe how farmers can be directly integrated into the whole blockchain solution considering the limited infrastructure, knowledge, and technologies available to them. Since about 70% of all cocoa worldwide is produced in West Africa, this case study uses the cocoa sector in Ghana as an example.
This article introduces the Database for Estimation of Road Network Performance (DERNP) to enable wide-scale estimation of relevant Road Network Performance (RNP) factors for major German cities. The methodology behind DERNP is based on a randomized route sampling procedure that utilizes the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) in combination with the tile-based HERE Maps Traffic API v7 and a digital elevation model provided by the European Union’s Earth Observation Programme Copernicus to generate a large set of independent and realistic routes throughout OpenStreetMap road networks. By evaluating these routes using the PHEMLight5 framework, a comprehensive list of RNP parameters is estimated and translated into polynomial regression models for general usage. The applicability of these estimations is demonstrated based on a case study of four major German cities. This case study considers network characteristics in terms of detours, infrastructure, traffic congestion, fuel consumption, and CO2 emissions. Our results show that DERNP and its underlying randomized route sampling methodology overcomes major limitations of previous wide-scale RNP approaches, enabling efficient, easy-to-use, and region-specific RNP comparisons.
The applications for occupancy detection range from controlling building automation and systems, determining heat transfer coefficients and even assessing the risk of infection in rooms. Studies in the literature use various statistical models, physical models and machine learning techniques to detect occupancy. All these methods require data for training the occupancy detection models. However, data generation is time-consuming and expensive. This study demonstrates the feasibility of using simulated learning data. Using three different data sources, we tested the suitability of different methods for generating learning data. We conducted two experiments in two office spaces with a real user and an artificial user, and we generated a third data set using a building simulation model. In addition, this study compares two different machine learning approaches (Random Forest and LASSO) using environmental parameters. Both machine learning approaches could develop models with a sensitivity of at least 83 % and a specificity of at least 97 % with both training data sets. This work shows that it is possible to determine the presence in rooms using simulated data. The results compared to measured data were just slightly less accurate, and the added value due to the lower effort was considerable
This article investigates multimodal elements—images, links, gifs, videos, and galleries—of crowdfunding campaigns on the platform Kickstarter to develop an understanding of characteristics of successful campaigns. The authors scraped 327,586 campaign pages, analyzing the multimodal elements of successful and unsuccessful campaigns. They found that successful campaigns featured more images, links, and gifs and more frequently included a project video than did unsuccessful campaigns. Images, links, and the presence of a project video had a positive impact on success while gifs and project galleries did not. These findings give business communicators practical guidance, develop theoretical aspects of Kickstarter research, and validate previous findings with a larger data set.
A new approach for the friction and wear characterisation of polymer fibres under dry, mixed, and hydrodynamic sliding conditions is developed. The production process of the tested polymer fibres is described and an introduction in fibre-reinforced concrete is given. Tribotesting is done on an optimised tribometer capable of measuring the friction and wear behaviour of polymer fibres with diameters of a few 100 µm under lubricated conditions. Three extruded polypropylene macro fibres with varying diameters are characterised under tribological conditions found in an industrial concrete mixing process. It is shown that detailed friction and wear data of polymer fibres can be gathered.
Background:
3D gait analysis (3DGA) is a common assessment in Cerebral Palsy (CP) to quantify the extent of movement abnormalities. Yet, 3DGA is performed in laboratories and may thus be of debatable significance to everyday life.
Aim
The aim was to assess the relationship between kinematic gait abnormality and everyday mobility in ambulatory children and youth with spastic CP.
Methods:
73 paediatric and juvenile patients with uni- or bilateral spastic CP (N = 21 USCP, N = 52, BSCP, age: 4–20 y, GMFCS I-III) underwent a 3DGA, while the MobQues47 Questionnaire quantified caregiver-reported mobility. We calculated the Gait Profile Score (GPS), a metric that summarizes how far the lower limb joint angles during walking deviate from those of matched controls.
Results:
The GPS correlated well with indoor and outdoor mobility (rho = −0.69 and −0.70, both p < 0.001) and the relationships were not significantly different for USCP and BSCP. Still, mobility was lower in BSCP (p < 0.001) and more compromised outdoors (p = 0.002). Indoor mobility could be predicted by walking speed, GPS and age (adj. R2 = 0.62). Outdoor mobility was best predicted by walking speed and GPS (adj. R2 = 0.60). The additive explained variance by the GPS was even higher outdoors than indoors (17.1% vs. 11.4%).
Conclusions:
Measuring movement deviations with 3DGA seems equally meaningful in uni- and bilaterally affected children and has considerable relevance for real-life ambulation, particurlarly outdoors, where children with spastic CP typically face greater difficulties. Therapeutic strategies that achieve faster walking and reduction of kinematic deviations may increase outdoor mobility.
Background
Vertigo, dizziness or balance disorders (VDB) are common leading symptoms in older people, which can have a negative impact on their mobility and participation in daily live, yet, diagnosis is challenging and specific treatment is often insufficient. An evidence-based, multidisciplinary care pathway (CPW) in primary care was developed and pilot tested in a previous study. The aim of the present study is to evaluate the effectiveness and safety of the CPW in terms of improving mobility and participation in community-dwelling older people with VDB in primary care.
Methods
For this multicentre cluster randomised controlled clinic trial, general practitioners (GP) will be recruited in two regions of Germany. A total of 120 patients over 60 years old with VDB will be included. The intervention is an algorithmized CPW. GPs receive a checklist for standardise clinical decision making regarding diagnostic screening and treatment of VDB. Physiotherapists (PT) receive a decision tree for evidence-based physiotherapeutic clinical reasoning and treatment of VDB. Implementation strategies comprises educational trainings as well as a workshop to give a platform for exchange for the GPs and PTs, an information meeting and a pocket card for home care nurses and informal caregivers and telephone peer counselling to give all participants the capability, opportunity and the motivation to apply the intervention. In order to ensure an optimised usual care in the control group, GPs get an information meeting addressing the national guideline. The primary outcome is the impact of VDB on participation and mobility of patients after 6 month follow-up, assessed using the Dizziness Handicap Inventory (DHI) questionnaire. Secondary outcomes are physical activity, static and dynamic balance, falls and fear of falling as well as quality of life. We will also evaluate safety and health economic aspects of the intervention. Behavioural changes of the participants as well as barriers, facilitating factors and mechanisms of impact of the implementation will be investigated with a comprehensive process evaluation in a mixed-methods design.
Discussion
With our results, we aim to improve evidence-based health care of community-dwelling older people with VDB in primary care.
Die Pflegewissenschaft in Deutschland steht vor der Herausforderung, wissenschaftliche Strukturen und Karrierewege auszubilden. Erschwert wird dies durch einen Mangel an wissenschaftlichem Nachwuchs, der das Potential hat, pflegewissenschaftliche Professuren mit wissenschaftlicher Exzellenz und praktischer Erfahrung zu füllen.
Ziel dieses Beitrags ist es, darzustellen, was auslösende Momente für wissenschaftliche Karrieren sind, die in Professuren pflegebezogener Studiengänge münden, und welche Kontextbedingungen diese Karrieren beeinflussen. Es soll auch aufgezeigt werden, wie wissenschaftliche Nachwuchskräfte vorgehen, um ihre Ziele zu erreichen und welche Konsequenzen sich daraus für sie und für die Pflegewissenschaft ergeben. Auf dieser Grundlage sollen Empfehlungen für die Nachwuchsförderung entwickelt werden, um mehr geeignete Personen für Professuren in pflegebezogenen Studiengängen zu gewinnen.
Vorhandene Daten teilnarrativer Interviews mit ProfessorInnen (n=11) und Masterstudierenden (n=11) sowie Promovierenden (n=10) pflegebezogener Studiengänge wurden im Rahmen einer retrospektiven Datenanalyse mit dem dreistufigen Codierverfahren der Grounded Theory Methodologie ausgewertet.
Die Ergebnisse zeigen, dass in der Pflegepraxis gewonnene Erfahrungen auslösende Momente wissenschaftlicher Karrieren sind. Diese lösen den Drang aus, die dort herrschende Situation zu verändern, wobei sich vier Karrieretypen unterscheiden lassen: Typ A forscht, weil er erlebt hat, dass es für pflegerische Phänomene keine geeigneten Pflegeinterventionen gab. Typ B lehrt, um dazu beizutragen, dass Pflegende zukünftig besser ausgebildet werden. Typ C ist als Pflegeperson von ÄrztInnen nicht ausreichend anerkannt worden und absolviert eine wissenschaftliche Qualifikation, um mit ihnen auf Augenhöhe zu gelangen. Typ D wollte in der Praxis bleiben, ist aber bei Weiterentwicklungsprozessen blockiert worden und nimmt als Kompromiss eine Professur an.
Identifizierte Kontextfaktoren sind u.a. mangelnde Wertschätzung für wissenschaftliches Handeln in der Pflege und das Fehlen von Stellen für hochschulisch qualifizierte Pflegepersonen in der Praxis. Angesichts der bestehenden Bedingungen können hochschulisch qualifizierte Pflegende in der Praxis nicht Fuß fassen. Als Konsequenz für die Pflegewissenschaft als Disziplin zeigt sich, dass in der Pflegepraxis Vorbilder fehlen, die zukünftige Generationen Pflegender dazu anregen könnten, selbst eine wissenschaftliche Karriere in der Pflege einzuschlagen. Dadurch besteht die Gefahr einer Verkümmerung der Pflegewissenschaft.
Auf Grundlage der Ergebnisse wird die durchgängige Implementierung geeigneter Stellen für hochschulisch qualifizierte Pflegepersonen in der Pflegepraxis als Ausgangsbasis wissenschaftlicher Nachwuchsförderung betrachtet. Als Konzept werden Hochschul-Praxis-Partnerschaften skizziert, die beginnend auf Bachelorniveau bis zur Post-doc-Phase Strukturen zu einem systematischen praxisbezogenen wissenschaftlichen Kompetenzauf- und -ausbau für akademisch qualifizierte Pflegende etablieren.
Purpose
The purpose of this paper is to investigate how professional football clubs from the English Premier League, German Bundesliga and Spanish Primera División use digital media to expand their international reach in emerging football markets (EFM) outside of Europe. Based on the EPRG framework and Rugman’s home-region hypothesis, the aim is to broaden the perspective where “sports go global” for a further understanding of actors’ international orientation in the digital sphere.
Design/methodology/approach
The study is based on data from desk research and a qualitative survey, comprising information on international digital media activities of 58 European clubs. Cluster analysis is used to identify different international orientations with regard to digital media activities.
Findings
The data provide evidence that clubs differ strongly in their orientations towards EFM. While some global players that provide digital media content in several EFM languages and attract a large share of Facebook followers from EFM exist, other clubs focus on their home region. League-specific differences become apparent.
Originality/value
This study determines the international online orientations of European football clubs by combining two previously separated research streams in football management studies: internationalisation and digital media activities. Most clubs with a strong EFM fan base choose polycentric, multi-language digital media strategies, followed by geocentric, standardised approaches. By offering a novel angle on internationalisation in professional football, this study contributes towards optimising clubs’ international online strategies for EFM, which are markets that promise high growth rates.
Virtual teams that use integrated communication platforms are ubiquitous in cross-border collaboration. This study explores the use of communication media and team outcomes—both social outcomes and task accomplishment—in multilingual virtual teams. Based on surveys from 96 virtual teams (with 578 team members), the research shows that the more time spent in rich communication channels, such as online conferences, increased inclusion and satisfaction, whereas the more time spent with written communication that is lower in richness increased the level of task accomplishment. Team members with lower language proficiency felt less included in all collaboration channels, whereas team members with higher language proficiency felt less satisfied with lean collaboration. In addition, limited language proficiency speakers were significantly less likely to view rich tools as helpful for their teams to reach a mutual decision. Our data support media richness theory in its original context for native and highly proficient English speakers. Our study extends the scope of the theory by applying it to the new context of team members with limited language proficiency. Management should implement a collaboration infrastructure consisting of communication platforms that integrate a variety of media to account for different tasks and different communication needs.
Each year, the Virtual Business Professional (VBP) program brings together professors and students from across the globe to engage in client projects. The VBP program of 2020 occurred from the beginning of March through the middle of April. In this article, we share how the COVID-19 pandemic affected VBP participants and their teams. We present post-project survey results (completed by 440 of 530 participants for an 83 percent response rate), professor comments, and student comments to demonstrate how VBP participants overcame many of the pandemic disruptions to work effectively in virtual teams, develop compassion and empathy for one another, and foster more global mindsets.
This study examines the impact of perceived foreign language proficiency on hybrid culture building in multicultural teams. Hybrid culture includes a mutually shared set of norms, communication patterns, problem-solving approaches, and synergistic task coordination that result from the diverse cultural backgrounds of the team members. Language is the main vehicle for communication and plays a major role in social interaction and therefore hybrid culture building. We argue that the level of perceived language proficiency of multicultural team members influences hybrid culture building; consequently, adequate language skills lead not only to an efficient task solution but are also an important factor in creating interpersonal relationships and building a shared culture. Our empirical analysis supports the positive influence of language proficiency in hybrid teams; however, foreign language proficiency is more influential on cognitively oriented areas of multicultural teamwork than on affective ones.
Artificial intelligence (AI) algorithmic tools that analyze and evaluate recorded meeting data may provide many new opportunities for employees, teams, and organizations. Yet, these new and emerging AI tools raise a variety of issues related to privacy, psychological safety, and control. Based on in-depth interviews with 50 American, Chinese, and German employees, this research identified five key tensions related to algorithmic analysis of recorded meetings: employee control of data versus management control of data, privacy versus transparency, reduced psychological safety versus enhanced psychological safety, learning versus evaluation, and trust in AI versus trust in people. More broadly, these tensions reflect two dimensions to inform organizational policymaking and guidelines: safety versus risk and employee control versus management control. Based on a quadrant configuration of these dimensions, we propose the following approaches to managing algorithmic applications to recording meeting data: the surveillance, benevolent control, meritocratic, and social contract approaches. We suggest the social contract approach facilitates the most robust dialog about the application of algorithmic tools to recorded meeting data, potentially leading to higher employee control and sense of safety.
Artificial Intelligence in Business Communication: The Changing Landscape of Research and Teaching
(2022)
The rapid, widespread implementation of artificial intelligence technologies in workplaces has implications for business communication. In this article, the authors describe current capabilities, challenges, and concepts related to the adoption and use of artificial intelligence (AI) technologies in business communication. Understanding the abilities and inabilities of AI technologies is critical to using these technologies ethically. The authors offer a proposed research agenda for researchers in business communication concerning topics of implementation, lexicography and grammar, collaboration, design, trust, bias, managerial concerns, tool assessment, and demographics. The authors conclude with some ideas regarding how to teach about AI in the business communication classroom.
The annual instructional virtual team Project X brings together professors and students from across the globe to engage in client projects. The 2020 project was challenged by the global disruption of the COVID-19 pandemic. This paper draws on a quantitative dataset from a post-project survey among 500 participating students and a qualitative narrative inquiry of personal experiences of the faculty members. The findings reveal how innovative use of a variety of collaboration and communication technologies helped students and their professors in building emotional connection and compassion to support each other in the midst of the crisis, and to accomplish the project despite connectivity disruptions. The results suggest that the role of an instructor changed to a coach and mentor, and technology was used to create a greater sense of inclusion and co-presence in student-faculty interactions. Ultimately, the paper highlights the role of technology to help the participants navigate sudden crisis affecting a global online instructional team project. The adaptive instructional teaching strategies and technologies depicted in this study offer transformative potential for future developments in higher education.
Usability is considered a major success factor for current and future decision support systems. Such systems are increasingly used to assist human decision-makers in high-stakes tasks in complex domains such as health care, jurisdiction or finance. Yet, many if not most expert systems—especially in health care—fail to deliver the degree of quality in terms of usability that its expert users are used to from their personal digital consumer products. In this article, we focus on clinical decision support systems (CDSS) as an example for how important a human-centered design approach is when designing complex software in complex contexts. We provide an overview of CDSS classes, discuss the importance of systematically exploring mental models of users, and formulate challenges and opportunities of future design work on CDSS. We further provide a case study from a current research project to illustrate how we used codesign as a practical approach to produce usable software in a real-world context.
Practical Relevance: We make a point for usability to be considered a major success factor and non-negotiable characteristic of expert software. With software evolving into virtual coworkers in terms of supporting human decision-making in complex, high-risk domains, the necessity of and demand for systems that are unambiguously understandable and interpretable for their expert users have never been higher. We show that this is a real-world problem with high practical relevance by describing our work in the domain of clinical decision support systems (CDSS) as an example. We introduce the topic and a classification of CDSS. Thus, we highlight a conceptual framework of how to approach complex domains from a technology designer’s point of view. We continue by explaining why usability must be regarded as a major goal in software development. We derive challenges and opportunities that may well be transferred to other domains. Finally, be including a real-world example from our own professional work we propose a practical approach towards taking the challenges and exploiting the associated opportunities.
Background
To date, targeted tyrosine kinase inhibitors have been approved for FGFR2 and FGFR3 fusions (pemigatinib and erdafitinib, respectively), but the importance of FGFR2 mutations for transformation activity and as a druggable gene variant with response to different FGFR inhibitors is poorly understood. FGFR2 inhibitors present a mainstay of treatment for locally advanced or metastatic intrahepatic cholangiocellular carcinoma (iCCA).
Methods
A 74-year-old male was diagnosed with iCCA in liver segments seven and eight with infiltration of the hepatic veins and inferior vena cava revealed a C382R mutation of the intramembrane domain of FGRR2 receptor. We performed an in-silico study to understand the potential mode-of-action of the mutant FGFR2 targets. Based on experimentally determined structures we then used a structure generated by AlphaFold2 as the variation in question is located at a position not determined well in the experiments. This revealed that the C382R mutation is located in the trans-membranal domain at a position crucial for signal transduction, both for activation and inhibition of downstream-signaling. The Molecular Tumor Board decided to start the treatment with 13.5 mg pemigatinib once daily for 14 days, followed by 7 days of free therapy interval resulting in a sustained partial response. The patient continues to be treated of 13.5 mg as described above.
Results
In our case report, we were able to show that the patient in whom an C382R mutation was detected responded to the therapy with pemigatinib. This shows that real-world scenarios differ from the data of the approval studies, thereby illustrating how complex data on patients with FGFR mutations is. One of the main problems of large approval studies is that the functionality of the respective alterations is often disregarded.
Conclusions
Our results suggest that respective mutation may be successfully targeted by FGFR-selective tyrosine-kinase inhibitors, demonstrating the importance of the functional characterization of mutations.
no conflicts of interest.
Point mutations of the fibroblast growth factor receptor (FGFR)2 receptor in intrahepatic cholangiocarcinoma (iCC) are mainly of unknown functional significance compared to FGFR2 fusions. Pemigatinib, a tyrosine kinase inhibitor, is approved for the treatment of cholangiocarcinoma with FGFR2 fusion/rearrangement. Although it is hypothesized that FGFR2 mutations may cause uncontrolled activation of the signaling pathway, the data for targeted therapies for FGFR2 mutations remain unclear. In vitro analyses demonstrated the importance of the p.C382R mutation for ligand-independent constitutive activation of FGFR2 with transforming potential. The following report describes the clinical case of a patient diagnosed with an iCC carrying a FGFR2 p.C382R point mutation which was detected in liquid, as well as in tissue-based biopsies. The patient was treated with pemigatinib, resulting in a sustained complete functional remission in fluorodeoxyglucose-positron emission tomography/computed tomography over 10 months to date. The reported case is the first description of a complete functional remission under the treatment with pemigatinib in a patient with p.C383R mutation.
Background:
Data on SARS-CoV-2 infections in oncological patients in the outpatient settings are scarce.
Methods:
During the spread of the delta variant between April 2021 and September 2021, a total of 10.677 patients were tested for SARS-CoV-2 infection by RT-qPCR in seven outpatient clinics in Bavaria, Germany.
Results:
Within the tested patient cohort, 4.960 patients (46.5%) suffered from a malignant disease (74% solid tumors and 26% malignant hematological diseases). This group was compared with 5.717 patients (53.5%) without a malignant disease (33.1% with other hematological diseases and 66.9% patients without a hematological or oncological disease). During the observation period, 119 (2.4%) patients with malignancies were tested positive (88 patients with solid tumors; 31 patients with malignant hematological diseases) compared to 115 positive patients (2.0%) in the control group. 32 of 119 positively tested patients (26.9%) suffering from malignant disease required hospitalization and 9/32 patients (28.1%) died during the clinical course.
Conclusions:
These observations are in clear contrast to data from patients we evaluated during the pre-delta variants period between 15 and 26 April 2020 in the same seven outpatient clinics. In this period, a total of 1.227 patients were tested for SARS-CoV-2 by RT-qPCR. 78/1227 patients (6.3%) were tested positive in RT-qPCR and most showed mild symptoms of infection. None of the SARS-CoV-2 infected patients died. These data were analyzed when no vaccination was available. These data were evaluated during a period where no vaccine was available. Vaccination of patients with malignancies with BiontechPfizer's mRNA vaccines was started in April 2021. The response to the vaccine was tested by an antibody assay (Elecsys Anti-SARS-CoV-2 S-immunoassay, Roche) at the earliest four weeks after the second vaccination. To assess the response, we compared five patient cohorts: Patients who received (i) B cell depleting antibodies, (ii) checkpoint inhibitors (ICI), (iii) chemotherapy, or (iv) tyrosin kinase inhibitors (TKIs), and (v) healthy controls. The patients treated with ICI or TKI showed a comparable vaccination response to the healthy patients, while patients receiving Rituximab/Obinutuzumab showed no significant humoral vaccination response at all. The more severe disease course of patients infected by the SARS-CoV-2 delta variant compared to the initial waves of infections strongly underline the importance of vaccination in cancer patients.
In this contribution the frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) technique is evaluated for post-consumer wood sorting. The fluorescence characteristics of several wood samples were determined, whereby two excitation wavelengths (405 and 488 nm) were used. The measured data were processed using algorithmic methods to identify the wood species and post-consumer wood category. With the excitation wavelength of 405 nm, 16 out of 19 samples could be correctly assigned to the corresponding post-consumer wood category by means of the fluorescence lifetimes. Thus, the experimental results revealed the high potential of the FD-FLIM technique for automated post-consumer wood sorting.
Krisen belasten Organisationen und die darin arbeitenden Menschen nicht nur aufgrund ihrer unvorhersehbaren Veränderungen und ständigen Unsicherheit. Sie konfrontieren uns auch mit den Schwächen unseres Systems und zeigen Schwachstellen auf, die im Normalbetrieb unserer Arbeitswelt meist noch kaschiert werden können. Präsente Führung ist in einer solchen Zeit der Ungewissheit umso wichtiger. Doch auch Führungskräfte stehen unter solchen Bedingungen vor der Herausforderung, wie sie vor dem Hintergrund fehlender oder sich ständig verändernder Informationen mit ihren Mitarbeitern kommunizieren sollen, wie sie die Zusammenarbeit in ihren Teams strukturieren und welche Maßnahmen sie auf Ebene der Organisation ergreifen sollen. In diesem Beitrag der Zeitschrift Gruppe. Interaktion. Organisation. (GIO) wird der Einfluss einer konstruktiven Fehlermanagement- und Vertrauenskultur unter Unsicherheit diskutiert. Es werden verschiedene Handlungsstrategien auf Ebene des einzelnen Mitarbeiters, des Teams und der Organisation aufgezeigt, wie Führungskräfte in Zeiten der Ungewissheit für Orientierung, Sicherheit und eine konstruktive Fehlermanagement- und Vertrauenskultur sorgen können.
Interim tests of previously studied information can potentiate subsequent learning of new information, in part, because retrieval-based processes help to reduce proactive interference from previously learned information. We hypothesized that an effect similar to this forward testing effect would also occur when making judgments of (prior) learning (JOLs). Previous research showed that making JOLs likely prompts covert retrieval attempts and thereby enhances memory, specifically when providing only parts of previously studied information. This study examined the forward effect of different types of JOLs (i.e., with complete or partial prior study information available) on subsequent learning of new materials, compared to restudy and retrieval practice. In a between-subjects design, participants (N = 161) consecutively studied five lists of 20 words with the aim to recall as many of them on a final cumulative recall test. After the presentation of each of the first four lists, participants either restudied the list, made JOLs with complete words, made JOLs with word stems, or they were tested on word stems. Compared to restudy, practicing retrieval and making JOLs with word stems, but not JOLs with complete words, facilitated the List-5 interim recall performance and attenuated the number of intrusions from prior lists. The findings suggest that, similar to overt retrieval, making JOLs with incomplete information can enhance new learning to the extent that it elicits covert retrieval attempts.
Increasing demand for energy-efficient means of transport has steadily intensified the trend towards lightweight components. Thermoplastic glass fiber composites (organo sheets) play a major role in the production of functional automotive components. Organo sheets are cut, shaped and functionalized by injection molding to produce hybrid components, such as those used in car door modules. The cutting process produces a considerable amount of production waste, which has thus far been thermally recycled. This study develops a closed mechanical recycling process and analyzes the different steps of the process. The offcuts were shredded using two shredding methods and implemented directly in the injection-molding process. Using tensile tests and impact bending tests, the material properties of the recycled materials were compared with the virgin material. In addition, fiber length degradation via the injection-molding process and the influence of the waterjet-cutting process on the mechanical properties are investigated. Recycled offcuts are both comparable to new material in terms of mechanical properties and usability, and are also economically and ecologically advantageous. Recycling polypropylene waste with glass fiber reinforcement in a closed loop is an effective way to reduce industrial waste in a sustainable and economical production process.
Für die Analyse, Bewertung und Kontrolle von Investitionsentscheidungen bei Erweiterungs- oder Modernisierungs-Investitionen zur Digitalisierung der Produktion fehlt ein methodisches Vorgehen. Ein dreistufiger Ansatz auf Basis geeigneter betriebswirtschaftlicher Kennzahlen wird vorgestellt und am Beispiel eines heterogenen Maschinen- und Anlagenparks für einen digitalen Schatten der Wert- und Stoffströme zur Steigerung der Ressourceneffizienz angewandt.
Greater public and scholarly awareness of the educational influence of males (men and fathers) on child development has generated a parallel need for empirical research into the gender-related structure and dynamics of relationships between girls/boys and female/male educators in early childhood education institutions. The Austrian W-INN pilot study, carried out between 2010 and 2012, used a cross-sectional mixed-methods design (video-based observation and questionnaires) to research possible pedagogical differences and similarities between male and female educators, and their impact on boys’ and girls’ behaviour in early childhood education institutions. Ten Austrian Early Childhood Education and Care (ECEC) groups were recruited: 5 female-only and 5 mixed-gender teams of educators, 30 children (15 boys, 15 girls) aged 4–6. Analysis of data on educational dimensions reveal male and female educators hardly differ (the exception, men are significantly more permissive). Mixed-gender teams produce significantly greater social mobility among children than do female-only teams. Analysing children’s behaviour towards educators, clear gender specific effects can be found across various levels of inquiry: girls react less obviously to an educator’s gender; boys, especially, are drawn significantly more frequently to a man in the ECEC team. Implications for pedagogical professionalism as well as limitations of the results are discussed.
Objective
Functioning is an important outcome for the management of rheumatoid arthritis (RA). Heterogeneity of respective patient-reported outcome measures (PROMs) challenges direct comparisons between their results. This study aimed to standardize reporting of such PROMs measuring functioning in RA to facilitate comparability.
Methods
Common-item nonequivalent group design with the Health Assessment Questionnaire (HAQ) as a common scale across data sets from various countries (including the UK, Turkey, and Germany) to establish a common metric was used. Other PROMs included are the physical function items of the Multidimensional HAQ (MDHAQ), the Disabilities of the Arm, Shoulder, and Hand questionnaire, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the World Health Organization Disability Assessment Schedule II (WHODAS II), the Medical Outcomes Study Short Form 36 (SF-36) health survey, and 4 short forms (20, 10, 6, and 4 physical function items) from the Patient-Reported Outcomes Measurement Information System. As the HAQ includes mobility, self-care, and domestic life items, this study focuses on these 3 domains. PROMs were described using standard error of measurement (SEM) and smallest detectable difference (SDD). A Rasch measurement model was used to create the common metric.
Results
The range of the SEM was 0.2 (MDHAQ) to 7.4 (SF-36 health survey physical functioning domain). The SDD revealed a range from 9.7% (WOMAC rating scale) to 33.5% (WHODAS physical functioning domain). PROMs co-calibration revealed fit to the Rasch measurement model. A transformation table was developed to allow exchange between PROM scores.
Conclusion
Scores between the daily activity PROMs commonly used in RA can now be compared. Factors such as SEM and SDD help to determine the choice of a PROM in clinical practice and research.