846 research outputs found
Dumbbell diffusion in a spatially periodic potential
We present a numerical investigation of the Brownian motion and diffusion of
a dumbbell in a two-dimensional periodic potential. Its dynamics is described
by a Langevin model including the hydrodynamic interaction. With increasing
values of the amplitude of the potential we find along the modulated spatial
directions a reduction of the diffusion constant and of the impact of the
hydrodynamic interaction. For modulation amplitudes of the potential in the
range of the thermal energy the dumbbell diffusion exhibits a pronounced local
maximum at a wavelength of about 3/2 of the dumbbell extension. This is
especially emphasized for stiff springs connecting the two beads.Comment: 4 pages, 7 figures, published in Phys. Rev. E (2008
The Impact of Human Resource Sharing on IT Project Risk
The increasing number of sophisticated IT projects and the scarcity of skilled human resources increasingly challenge IT project portfolio managers with the need to do âmore with lessâ. Consequently, resource sharing among projects provides a widely applied instrument to reduce project costs. However, resource sharing may not only result in cost synergies but also in risk effects. In contrast to cost synergies, these risk effects are rarely considered in business practice and quantification efforts of these risk effects are missing in the literature. Our research is the first to provide a systematic quantitative empirical analysis of the relationships between resource sharing and project risk. We find evidence that projects sharing their human resources are more likely to fall short in their planned scope while being more likely to comply with their planned timeline
Can a Button Change your Purchase? â The Effect of the Accessibility of Consumer Reviews on Consumersâ Online Purchase Decisions
This study investigates whether the accessibility of consumer reviews matters for consumersâ purchase decisions. Current research does not provide guidance on how to access consumer reviews to improve consumersâ decision-making. Moreover, there is no consensus on the actual implementation of the access (i.e., immediate access or explicit access by clicking) to consumer reviews on existing online shopping websites. Building on the anchoring-and-adjustment model of belief updating and using an experimental approach, we find that requiring participants to explicitly access consumer reviews (by clicking on a button) significantly improves their purchase decisions: When choosing between products of different quality, they better align their perceived product values with the actual product quality. As a result, they are more likely to purchase the high-quality product. These findings provide important insights for e-commerce retailers and policy makers, as they offer guidance on how consumer reviews should be accessible to support consumersâ decision-making
Context-Aware Marketing Attribution Based on Survival Analysis
Companies increasingly invest in digital marketing channels to promote their products and services. While the expenditures for each marketing channel are known, the contribution of marketing channels to a successful conversion, and therefore the value they generate, is unknown, but highly relevant for strategic decision-making. In this paper, we develop a novel, context-aware additive hazard marketing attribution (CAHMA) model based on survival analysis to address this problem. In addition to channel-specific, time-decaying effects of marketing on the usersâ conversion rate, we control for the effects of contextual features, such as the device or country from which users interact with marketing channels. Based on a prototypical implementation, we demonstrate the modelâs applicability and evaluate it on real-world data from the industry. We find that CAHMA outperforms other models in terms of accuracy while offering unique interpretability of the results and hence, providing deep insights for practitioners into the effects of marketing
DrugExBERT for Pharmacovigilance â A Novel Approach for Detecting Drug Experiences from User-Generated Content
Pharmaceutical companies have to maintain drug safety through pharmacovigilance systems by monitoring various sources of information about adverse drug experiences. Recently, user-generated content (UGC) has emerged as a valuable source of real-world drug experiences, posing new challenges due to its high volume and variety. We present DrugExBERT, a novel approach to extract adverse drug experiences (adverse reaction, lack of effect) and supportive drug experiences (effectiveness, intervention, indication, and off-label use) from UGC. To be able to verify the extracted drug experiences, DrugExBERT additionally provides explications in the form of UGC phrases that were critical for the extraction. In our evaluation, we demonstrate that DrugExBERT outperforms state-of-the-art pharmacovigilance approaches as well as ChatGPT on several performance measures and that DrugExBERT is data- and drug-agnostic. Thus, our novel approach can help pharmaceutical companies meet their legal obligations and ethical responsibility while ensuring patient safety and monitoring drug effectiveness
IT Sourcing Portfolio Management for IT Services Providers - A Risk/Cost Perspective
Utilizing a global IT sourcing strategy bears enormous growth potential. With the main focus on cost reduction in valuation of sourcing alternatives, risk and risk diversification effects are often inadequately considered or completely neglected. This systematically results in wrong decisions about global sourcing. Correct decisions are in particular important for the success of IT services providers (ITSP), which are the major beneficiaries of the market growth, though being faced with intensifying competition. This paper proposes a decision model for allocating software development projects of an ITSP to available sites in a risk/cost efficient way by adapting Markowitzâs Modern Portfolio Theory to IT sourcing decision making. The suggested approach covers not only costs and sourcing risks but also interdependencies between both sites and projects. Additionally, we propose methods for quantifying the necessary input parameters. We demonstrate the practicability of our approach in a case study with data from a major ITSP
Being Informed or Getting the Product?
Scarcity cues, which are increasingly implemented on e-commerce platforms, are known to impair cognitive processes and influence consumersâ decision-making by increasing perceived product value and purchase intention. Another feature present on e-commerce platforms are online consumer reviews (OCRs) which have become one of the most important information sources on e-commerce platforms in the last two decades. Nevertheless, little is known about how the presence of scarcity cues affects consumersâ processing of textual review information. Consequently, it is unclear whether OCRs can counteract the effects of scarcity or whether OCRs are neglected due to scarcity cues. To address this gap, this study examines the effects of limited-quantity scarcity cues on online purchase decisions when participants have the possibility to evaluate textual review information. The results of the experimental study indicate that scarcity lowers participantsâ processing of textual review information. This in turn increases perceived product value and has considerable negative consequences for the final purchase decision if the scarcity cue is displayed next to a low-quality product. The studyâs findings provide relevant insights and implications for e-commerce platforms and policymakers alike. In particular, it highlights that e-commerce platforms can easily (ab)use scarcity cues to reduce consumersâ processing of textual review information in order to increase the demand for low-quality products. Consequently, policymakers should be aware of this mechanism and consider potential countermeasures to protect consumers
Explaining Reviewing Effort: Existing Reviews as Potential Driver
Online review systems try to motivate reviewers to invest effort in writing reviews, as their success crucially depends on the helpfulness of such reviews. Underlying cognitive mechanisms, however, might influence future reviewing effort. Accordingly, in this study, we analyze whether existing reviews matter for future textual reviews. From analyzing a dataset from Google Maps covering 40 sights across Europe with over 37,000 reviews, we find that textual reviewing effort, as measured by the propensity to write an optional textual review and (textual) review length, is negatively related to the number of existing reviews. However, and against our expectations, reviewers do not increase textual reviewing effort if there is a large discrepancy between the existing rating valence and their own rating. We validate our findings using additional review data from Yelp. This work provides important implications for online platforms with review systems, as the presentation of review metrics matters for future textual reviewing effort
Dokumentation des "Scientific Use Files der Integrierten Erwerbsbiographien" (IEBS-SUF V1) Version 1.0 (Documentation of the Scientific Use Files of the Integrated Employment Biographies (IEBS-SUF V1), Version 1.0)
"Die Integrierten Erwerbsbiografien (IEB) sind ein Datenangebot des IAB (Institut fĂŒr Arbeitsmarkt- und Berufsforschung) und werden seit 2004 erzeugt. Sie umfassen vier verschiedene Quellen und sind damit die umfangreichste Datenmenge zu erwerbshistorischen Meldungen auf Personenebene, die vom Forschungsdatenzentrum der BA am IAB (FDZ) angeboten werden. Ausgangspunkt der IEB sind Meldungen, die die RentenversicherungstrĂ€ger zu BeschĂ€ftigtenzeiten erfassen und an die Bundesagentur fĂŒr Arbeit (BA) weiterleiten sowie Informationen, die im Rahmen der Arbeitsmarktförderung und der Arbeitslosenversicherung durch die Bundesagentur fĂŒr Arbeit erfasst werden. Alle Meldungen liegen in Kontenform vor und sind tagesgenaue Angaben zu Erwerbszeiten. ErgĂ€nzt werden diese Informationen mit Personenmerkmalen als auch mit Leistungs- und Lohnangaben, die fĂŒr den Zeitraum der jeweiligen Erwerbsmeldung gĂŒltig sind. Der vorliegende Datenreport beschreibt eine anonymisierte Stichprobe zu diesen Integrierten Erwerbsbiografien, die der Wissenschaft- und Forschung in Form eines Scientific Use Files (IEBS-SUF) zur VerfĂŒgung gestellt wird. Hierzu dokumentiert der Report die Arbeitsschritte, die im Rahmen zur Erstellung des Scientific Use Files umgesetzt worden sind und liefert eine Dokumentation der enthaltenen Variablen. Im Mittelpunkt des Papiers steht die GegenĂŒberstellung der Informationen aus dem IEBS-SUF V1 und aus der IEBS V1.0 (Stichprobe der IEB). Letzter Datensatz weicht von dem IEBS-SUF V1 durch ein deutlich geringeres AusmaĂ an Anonymisierung ab und steht der Forschung lediglich im Rahmen von Gastaufenthalten und Datenfernverarbeitung ĂŒber das FDZ der Bundesagentur fĂŒr Arbeit (im IAB) zur VerfĂŒgung. Beide DatensĂ€tze basieren auf der gleichen Ausgangsversion der Integrierten Erwerbsbiografien (Version 3.01). Im Gegensatz zur IEBS V 1.0 umfasst der IEBS-SUF V1 ein erweitertes Variablenspektrum. Damit möchte das IAB einen fĂŒr die Forschung attraktiven Datensatz zur VerfĂŒgung stellen, auf dessen Grundlage sich vor allem die Untersuchungen im Rahmen der Evaluation der MaĂnahmen zur Umsetzung der VorschlĂ€ge der Hartz-Kommission (Hartz-Evaluation I-III) nachvollziehen lassen. MaĂgebliches Kriterium fĂŒr die Erstellung eines Scientific Use Files sind jedoch die durch Gesetzgeber vorgegebenen Bestimmungen zum Datenschutz. Diese stellen sicher, dass Persönlichkeitsrechte gewahrt bleiben und regeln, dass in den zur VerfĂŒgung gestellten Daten nicht oder nur sehr schwierig individuelle FĂ€lle identifiziert werden können bzw. dass die Informationen in den Daten 'missbrĂ€uchlich' verwendet werden. Dies fĂŒhrt dazu, dass das Ausgangsmaterial vor einer Veröffentlichung 'faktisch anonymisiert' werden muss. Im Kern wird bei der vorliegenden Anonymisierung der IEB von einem bereits vorhandenen Stichprobenauszug zu den Integrierten Erwerbsbiografien - der IEBS - ausgegangen. Diese wird um bestimmte Variablen (insbesondere Regionalidentifikatoren) reduziert. DarĂŒber hinaus werden je nach Quelle der IEB unterschiedliche Anonymisierungen vorgenommen. Das Einhalten der gesetzlichen Vorgaben zur Umsetzung der faktischen Anonymisierung wird dann auf Grundlage von Heuristiken bzgl. der reprĂ€sentierten Grundgesamtheit umgesetzt. Konkret bedeutet dies, dass fĂŒr das Kriterium der faktischen AnonymitĂ€t eine minimale Fallzahl univariater HĂ€ufigkeitsauszĂ€hlungen verwendet wird. Liegen die Fallzahlen unterhalb bestimmter Werte, dient dies als Entscheidungskriterium fĂŒr eine Anonymisierung des Datenmaterials. Die nachfolgende Dokumentation beschreibt hierzu zunĂ€chst das Ausgangsmaterial fĂŒr diese Anonymisierung und skizziert die angewandten Anonymisierungskriterien sowie das Vorgehen bei der Datenanonymisierung. DarĂŒber hinaus wird dargestellt, in welchem Umfang Informationen durch die Anonymisierung - gegenĂŒber der IEBS - verloren gehen." (Autorenreferat, IAB-Doku)Forschungsdatenzentrum, Integrierte Erwerbsbiografien, Daten - Modell
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