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Institut
- Fachbereich 4 (72) (entfernen)
Despite widespread plans of big companies like Amazon and Google to develop unmanned delivery drones, scholarly research in this field is scarce, especially in the information systems field. From technical and legal perspectives, drone delivery in last-mile scenarios is in a quite mature state. However, estimates of user acceptance are varying between high skepticism and exaggerated optimism. This research follows a mixed method approach consisting both qualitative and quantitative research, to identify and test determinants of consumer delivery drone service adoption. The qualitative part rests on ten interviews among average consumers, who use delivery services on a regular basis. Insights gained from the qualitative part were used to develop an online survey and to assess the influence of associated risks on adoption intentions. The quantitative results show that especially financial and physical risks impede drone delivery service adoption. Delivery companies who are currently thinking about providing a delivery drone service may find these results useful when evaluating usage behaviors in the future market for delivery drones.
This paper describes the robots TIAGo and Lisa used by
team homer@UniKoblenz of the University of Koblenz-Landau, Germany,
for the participation at the RoboCup@Home 2019 in Sydney,
Australia. We ended up first at RoboCup@Home 2019 in the Open Platform
League and won the competition in our league now three times
in a row (four times in total) which makes our team the most successful
in RoboCup@Home. We demonstrated approaches for learning from
demonstration, touch enforcing manipulation and autonomous semantic
exploration in the finals. A special focus is put on novel system components
and the open source contributions of our team. We have released
packages for object recognition, a robot face including speech synthesis,
mapping and navigation, speech recognition interface, gesture recognition
and imitation learning. The packages are available (and new packages
will be released) on http://homer.uni-koblenz.de.
This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2017 in Nagoya, Japan. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on
http://wiki.ros.org/agas-ros-pkg.
This paper describes the robots TIAGo and Lisa used by team homer@UniKoblenz of the University of Koblenz-Landau, Germany, for the participation at the RoboCup@Home 2018 in Montreal, Canada. Further this paper serves as qualification material for the RoboCup-@Home participation in 2018. A special focus is put on novel system components and the open source contributions of our team. This year the team from Koblenz won the biggest annual scientianc robot competition in Montreal in the RoboCup@Home Open Platform track for the third time and also won the RoboCup@Home German Open for the second time. As a research highlight a novel symbolic imitation learning approach was demonstrated during the annals. The TIAGo robotic research platform was used for the first time by the team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg. Further information can be found on our project page http://homer.uni-koblenz.de.
This paper describes the robot Lisa used by team
homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2016 in Leipzig, Germany. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg.
Six and Gimmler have identified concrete capabilities that enable users to use the Internet in a competent way. Their media competence model can be used for the didactical design of media usage in secondary schools. However, the special challenge of security awareness is not addressed by the model. In this paper, the important dimension of risk and risk assessment will be introduced into the model. This is especially relevant for the risk of the protection of personal data and privacy. This paper will apply the method of IT risk analysis in order to select those dimensions of the Six/Gimmler media competence model that are appropriate to describe privacy aware Internet usage. Privacy risk aware decisions for or against the Internet usage is made visible by the trust model of Mayer et al.. The privacy extension of the competence model will lead to a measurement of the existing privacy awareness in secondary schools, which, in turn, can serve as a didactically well-reasoned design of Informatics modules in secondary schools. This paper will provide the privacy-extended competence model, while empirical measurement and module design is planned for further research activities.
Um die Attraktivität eines Unternehmens für Bewerber zu steigern und die Zufriedenheit der Angestellten zu verbessern ist es heutzutage unumgänglich, eine Vielzahl an Work-Life-Balance Maßnahmen anzubieten. Doch die zeitlichen und finanziellen Kosten, welche deren Einführung verursacht, fordern eine Priorisierung der Maßnahmen. Zur Entwicklung einer solchen Empfehlung für Unternehmen untersucht diese Studie ob es Work-Life-Balance Maßnahmen gibt, welche einen höheren Einfluss auf die Arbeitszufriedenheit ausüben als andere, wie groß der relative Effekt von den Maßnahmen im Vergleich zu anderen arbeitsbezogenen und privaten Variablen auf die Veränderung der Arbeitszufriedenheit ist, ob es einen Zusammenhang zwischen der Effektivität einer Maßnahme und deren Nutzung gibt und ob es Unterschiede zwischen den Erwartungen der Angestellten und den Angeboten der Unternehmen gibt.
Diese Fragen sind in acht Forschungshypothesen formuliert, welche in einem quantitativen Design mit Daten von 289 Angestellten von fünfzehn verschiedenen deutschen Unternehmen aus einem Online-Fragebogen überprüft werden. Für die Bildung einer Hierarchie von Maßnahmen nach ihrem Einfluss auf die Arbeitszufriedenheit und die Untersuchung des relativen Effektes im Vergleich zu anderen Variablen wird eine multiple Regressionsanalyse verwendet, während für die Ermittlung der Unterschiede zwischen den Erwartungen der Angestellten und der Verfügbarkeit der Angebote T-Tests durchgeführt werden.
Unterstützung bei der Kindesbetreuung, Unterstützung bei ehrenamtlichen Tätigkeiten und Teambuilding-Events haben einen signifikant höheren Einfluss auf die Arbeitszufriedenheit als andere Maßnahmen, und die hypothetische Nutzung ist höher
als die tatsächliche Nutzung, was auf ein hohes Potenzial dieser Maßnahmen bezüglich der Verbesserung der Arbeitszufriedenheit durch deren Einführung schließen lässt. Darüber hinaus sind aus Sicht der Angestellten flexible Arbeitszeiten und Arbeitsorte sowie Freizeit- und Überstundenkonten die wichtigsten Maßnahmen, welche auch bereits flächendeckend in den befragten Unternehmen angeboten werden. Allgemein sind die Nutzung der verfügbaren Maßnahmen und die Anzahl der angebotenen Maßnahmen wichtiger im Hinblick auf die Arbeitszufriedenheit als die Art der Maßnahmen. Außerdem nehmen Work-Life-Balance Maßnahmen bei jüngeren Menschen einen höheren Stellenwert in Bezug auf die Arbeitszufriedenheit ein als bei älteren Menschen.
Information systems research has started to use crowdsourcing platforms such as Amazon Mechanical Turks (MTurk) for scientific research, recently. In particular, MTurk provides a scalable, cheap work-force that can also be used as a pool of potential respondents for online survey research. In light of the increasing use of crowdsourcing platforms for survey research, the authors aim to contribute to the understanding of its appropriate usage. Therefore, they assess if samples drawn from MTurk deviate from those drawn via conventional online surveys (COS) in terms of answers in relation to relevant e-commerce variables and test the data in a nomological network for assessing differences in effects.
The authors compare responses from 138 MTurk workers with those of 150 German shoppers recruited via COS. The findings indicate, inter alia, that MTurk workers tend to exhibit more positive word-of mouth, perceived risk, customer orientation and commitment to the focal company. The authors discuss the study- results, point to limitations, and provide avenues for further research.
The aim of this paper is to identify and understand the risks and issues companies are experiencing from the business use of social media and to develop a framework for describing and categorising those social media risks. The goal is to contribute to the evolving theorisation of social media risk and to provide a foundation for the further development of social media risk management strategies and processes. The study findings identify thirty risk types organised into five categories (technical, human, content, compliance and reputational). A risk-chain is used to illustrate the complex interrelated, multi-stakeholder nature of these risks and directions for future work are identified.
The way information is presented to users in online community platforms has an influence on the way the users create new information. This is the case, for instance, in question-answering fora, crowdsourcing platforms or other social computation settings. To better understand the effects of presentation policies on user activity, we introduce a generative model of user behaviour in this paper. Running simulations based on this user behaviour we demonstrate the ability of the model to evoke macro phenomena comparable to the ones observed on real world data.