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.

In order to enhance the company’s appeal for potential employees and improve the satisfaction of already salaried workers, it is necessary to offer a variety of work-life balance measures. But as their implementation causes time and financial costs, a prioritization of measures is needed. To express a recommendation for companies, this study is led by the questions if there are work-life balance measures which have more impact on employee satisfaction than others, how big the relative impact of work-life balance measures on job satisfaction in comparison to other work and private life variables is, if there is a relation between the effectiveness of measures and their use and if there is a difference between the measures which are most important from the employees’ perspective and the companies’ offers. These questions are formulated in eight research hypotheses which are examined in a quantitative research design with online survey data from 289 employees of fifteen different German companies. The formation of a hierarchy of the effectiveness of measures towards job satisfaction as well as the investigation of the relative impact in comparison to other variables is performed using a multiple regression analysis, whilst the differences between employees’ expectations and the availability of offers are examined with t-tests. Support in childcare, support in voluntary activities and teambuilding events have a significantly higher impact on job satisfaction than other work-life balance measures, and their potential use is higher than the actual use which leads to the conclusion that there is yet potential for companies to improve their employees’ satisfaction by implementing these measures. In addition, flexible work hours, flexible work locations and free time and overtime accounts are the most important measures from the employees’ point of view and already widely offered by the surveyed companies. In general, the overall use of the available measures and the quantity of offered measures are more important with regard to job satisfaction than the specific kind of measure. In addition, work-life balance measures are more important towards job satisfaction for younger people.

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.