30 research outputs found
Unemployment and online labor
Online labor markets experienced a rapid growth in recent years. They allow for long-distance transactions and offer workers access to a potentially âglobalâ pool of labor demand. As such, they bear the potential to act as a substitute for shrinking local income opportunities. Using detailed U.S. data from a large online labor platform for microtasks, we study how local unemployment affects participation and work intensity online. We find that, at the extensive margin, an increase in commuting zone level unemployment is associated with more individuals joining the platform and becoming active in fulfilling tasks. At the intensive margin, our results show that with higher unemployment rates, online labor supply becomes more elastic. These results are driven by a decrease of the reservation wage during standard working hours. Finally, the effects are transient and do not translate to a permanent increase in platform participation by incumbent users. Our findings highlight that many workers consider online labor markets as a substitute to offline work for generating income, especially in periods of low local labor demand. However, the evidence also suggests that, despite their potential to attract workers, online markets for microtasks are currently not viable as a long run alternative for most workers
Investigating the zoonotic origin of the West African Ebola epidemic
The severe Ebola virus disease epidemic occurring in West Africa stems from a
single zoonotic transmission event to a 2âyearâold boy in Meliandou, Guinea.
We investigated the zoonotic origins of the epidemic using wildlife surveys,
interviews, and molecular analyses of bat and environmental samples. We found
no evidence for a concurrent outbreak in larger wildlife. Exposure to fruit
bats is common in the region, but the index case may have been infected by
playing in a hollow tree housing a colony of insectivorous freeâtailed bats
(Mops condylurus). Bats in this family have previously been discussed as
potential sources for Ebola virus outbreaks, and experimental data have shown
that this species can survive experimental infection. These analyses expand
the range of possible Ebola virus sources to include insectivorous bats and
reiterate the importance of broader sampling efforts for understanding Ebola
virus ecology
AbschÀtzung der Quality of Experience von GeschÀftsanwendungen - Ein crowdsourcing-basierter Ansatz
Nowadays, employees have to work with applications, technical services, and systems every day for hours. Hence, performance degradation of such systems might be perceived negatively by the employees, increase frustration, and might also have a negative effect on their productivity. The assessment of the application's performance in order to provide a smooth operation of the application is part of the application management. Within this process it is not sufficient to assess the system performance solely on technical performance parameters, e.g., response or loading times. These values have to be set into relation to the perceived performance quality on the user's side - the quality of experience (QoE).
This dissertation focuses on the monitoring and estimation of the QoE of enterprise applications. As building models to estimate the QoE requires quality ratings from the users as ground truth, one part of this work addresses methods to collect such ratings. Besides the evaluation of approaches to improve the quality of results of tasks and studies completed on crowdsourcing platforms, a general concept for monitoring and estimating QoE in enterprise environments is presented. Here, relevant design dimension of subjective studies are identified and their impact of the QoE is evaluated and discussed. By considering the findings, a methodology for collecting quality ratings from employees during their regular work is developed. The method is realized by implementing a tool to conduct short surveys and deployed in a cooperating company.
As a foundation for learning QoE estimation models, this work investigates the relationship between user-provided ratings and technical performance parameters. This analysis is based on a data set collected in a user study in a cooperating company during a time span of 1.5 years. Finally, two QoE estimation models are introduced and their performance is evaluated.Heutzutage sind GeschĂ€ftsanwendungen und technische Systeme aus dem Arbeitsalltag vieler Menschen nicht mehr wegzudenken. Kommt es bei diesen zu Performanzproblemen, wie etwa Verzögerungen im Netzwerk oder Ăberlast im Datenzentrum, kann sich dies negativ auf die Effizienz und ProduktivitĂ€t der Mitarbeiter auswirken. Daher ist es wichtig aus Sicht der Betreiber die Performanz der Anwendungen und Systeme zu ĂŒberwachen. Hierbei ist es allerdings nicht ausreichend die QualitĂ€t lediglich anhand von technischen Performanzparametern wie Antwortzeiten zu beurteilen. Stattdessen sollten diese Werte in Relation zu der von den Mitarbeitern wahrgenommenen Performanz oder Quality of Experience (QoE) gesetzt werden.
Diese Dissertation beschÀftigt sich mit dem Monitoring und der AbschÀtzung der QoE von GeschÀftsanwendungen. Neben der PrÀsentation eines generellen Konzepts zum Monitoring und der AbschÀtzung der QoE im GeschÀftsumfeld, befasst sich die Arbeit mit Aspekten der Erfassung von QualitÀtsbewertungen durch die Nutzer. Dies umfasst einerseits die Evaluation von AnsÀtzen zur Verbesserung der QualitÀt von Aufgaben- und Studienergebnissen auf Crowdsourcing-Plattformen. Andererseits werden relevante Dimensionen des Designs von Studien zur Untersuchung der QoE von GeschÀftsanwendungen aufgezeigt und deren Einfluss auf die QoE diskutiert und evaluiert. Letztendlich wird eine Methodik zur Erfassung von QualitÀtsbewertungen durch Mitarbeiter wÀhrend ihrer regulÀren Arbeit vorgestellt, welche implementiert und in einem kooperierenden Unternehmen ausgerollt wurde.
Als Grundlage der Entwicklung eines QoE AbschĂ€tzungsmodells, untersucht diese Arbeit den Zusammenhang zwischen Bewertungen durch die Nutzer und technischen Performanzparametern. Die Untersuchungen erfolgen auf einem Datensatz, welcher in einer Studie ĂŒber 1.5 Jahre in einem kooperierenden Unternehmen gesammelt wurde. Des Weiteren werden zwei Methoden zur AbschĂ€tzung der QoE prĂ€sentiert und deren Performanz evaluiert
Correlating QoE and technical parameters of an SAP system in an enterprise environment
The impact of waiting times on the Quality of Experience (QoE) in enterprise and working environments has not been in the focus of current research. This mostly stems from two factors: i) the high complexity of enterprise systems exacerbates the exact monitoring of relevant application response times on user granularity and ii) disturbances of the day-to-day business by user studies resulting in additional costs due nonproductive times. This paper approaches these challenges by combining non-intrusive application monitoring of response times and subjective user ratings on the perceived application performance. We evaluate the possibility of predicting the QoE based on the objective measurements using different machine learning approaches. The results imply a high correlation for specific users, but do not allow to derive a generic model