Fachbereich Wirtschaftswissenschaften
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Konzept zum Umgang mit Prüfungsstress und Lernblockaden bei Studierenden in der Studieneingangsphase
(2021)
IT–Servicemanagement in KMU
(2006)
The design of self-driving cars is one of the most exciting and ambitious challenges of our days and every day, new research work is published. In order to give an orientation, this article will present an overview of various methods used to study the human side of autonomous driving. Simplifying roughly, you can distinguish between design science-oriented methods (such as Research through Design, Wizard of Oz or driving simulator ) and behavioral science methods (such as survey, interview, and observation). We show how these methods are adopted in the context of autonomous driving research and dis-cuss their strengths and weaknesses. Due to the complexity of the topic, we will show that mixed method approaches will be suitable to explore the impact of autonomous driving on different levels: the individual, the social interaction and society.
In intensively used agricultural landscapes, path margins are one of the few refuges and nurseries for wildlife. They provide e. g. food sources and overwintering opportunities for many insects, serve as migration corridors for animals, protect soil from erosion, increase its water-holding capacity, and increase soil organic carbon, contributing thus directly to biodiversity conservation and climate change mitigation. Path margins are often municipally owned but used and managed by agriculture. For a path margin to be functional, certain conditions must be fulfilled, such as the width, the botanical composition, and how it is managed through the seasons. Therefore, it must be managed under specific requirements. A multifunctional path margin can be achieved only through the commitment of all stakeholders (e.g., farmers, municipalities, conservationists, and civil society).
Urban food systems consist of many stakeholders with different perspectives, different interests and different governance tools. This study aimed at developing potential future scenarios for the food system of Cologne by analysing the system with a Delphi approach. In our research-design, the suitability of the Delphi-method was evaluated not only as a tool for future modelling and scenario design, but also as a communication tool among the group of participants on a multi-stakeholder-platform. As a case study, the Food Policy Council of Cologne, Germany was used. Cologne can be seen as a forerunner among German cities in the development of a new urban food policy. Some of the successful steps to re-envisioning food as an urban system include joining the Milan Urban Food Policy Pact, the decision of the City Council to become an edible city and the establishment of a Food Policy Council. For the study it was important to capture participants’ visions of a common goal regarding the governance of the urban food system and also to identify mental ‘silos’. It was obvious that the municipality of Cologne together with the Food Policy Council made great efforts towards participatory processes to build a vision for a sustainable and regional food supply. However, many stakeholder-groups in the process still work exclusively among themselves and do not actively practice the confrontation with the viewpoints of other relevant groups. This supports the maintenance of ‘silos’ and leaves little room for face-to-face discussions. Therefore, the primary aim of this study is to explore key components of food provisioning in the future for Cologne while confronting all stakeholders (municipal administration and politicians, farmers and food activists) with the perspectives of all group members. We used a multi-stakeholder Delphi approach with 19 panellists to find out essential components of the municipal regional food provisioning system in Cologne. Unique in this Delphi study is the bringing together of municipal administration, regional urban farmers and food activists. The research is still on-going, but preliminary results show that more communication among all relevant actors, especially horizontally among different city departments, in the urban food system is needed.
With the debates on climate change and sustainability, a reduction of the share of cars in the modal split has become increasingly prevalent in both public and academic discourse. Besides some motivational approaches, there is a lack of ICT artifacts that successfully raise the ability of consumers to adopt sustainable mobility patterns. To further understand the requirements and the design of these artifacts within everyday mobility adopted a practice-lens. This lens is helpful to get a broader perspective on the use of ICT artifacts along consumers’ transformational journey towards sustainable mobility practices. Based on 12 retrospective interviews with car-free mobility consumers, we argue that artifacts should not be viewed as ’magic-bullet’ solutions but should accompany the complex transformation of practices in multifaceted ways. Moreover, we highlight in particular the difficulties of appropriating shared infrastructures and aligning own practices with them. This opens up a design space to provide more support for these kinds of material-interactions, to provide access to consumption infrastructures and make them usable, rather than leaving consumers alone with increased motivation.
Within qualitative interviews we examine attitudes towards driverless cars in order to investigate new mobility services and explore the impact of such services on everyday mobility. We identified three main issues that we would like to discuss in the workshop: (I) Designing beyond a driver-centric approach; (II) Developing mobility services for cars which drive themselves; and (III) Exploring self-driving practices.
Focus on what matters: improved feature selection techniques for personal thermal comfort modelling
(2022)
Occupants' personal thermal comfort (PTC) is indispensable for their well-being, physical and mental health, and work efficiency. Predicting PTC preferences in a smart home can be a prerequisite to adjusting the indoor temperature for providing a comfortable environment. In this research, we focus on identifying relevant features for predicting PTC preferences. We propose a machine learning-based predictive framework by employing supervised feature selection techniques. We apply two feature selection techniques to select the optimal sets of features to improve the thermal preference prediction performance. The experimental results on a public PTC dataset demonstrated the efficiency of the feature selection techniques that we have applied. In turn, our PTC prediction framework with feature selection techniques achieved state-of-the-art performance in terms of accuracy, Cohen's kappa, and area under the curve (AUC), outperforming conventional methods.
This paper presents the outcomes of an exploratory field study that examined the social impact of an ICT-based suite of exergames for people with dementia and their caregivers. Qualitative data was collected over a period of 8 months, during which time we studied the daily life of 14 people with dementia and their informal and professional caregivers. We focus on the experiential aspects of the system and examine its social impact when integrated into the daily routines of both people with dementia themselves and their professional and family caregivers. Our findings indicate that relatives were able to regain leisure time, whilst people with dementia were able to recapture certain aspects of their social and daily activities that might otherwise have been lost to them. Results suggest that the system enhanced social-interaction, invigorated relationships, and improved the empowerment of people with dementia and their caregivers to face daily challenges.
Exploring Future Work - Co-Designing a Human-robot Collaboration Environment for Service Domains
(2020)
There has been increasing interest in the application of humanoid robots in service domains like retail or care homes in recent years. Here, most use cases focus on serving customer needs autonomously. Frequently, human intervention becomes necessary to support the robot in exceptional situations. However, direct intervention of service operators is often not possible and requires specialized personnel. In a co-design process with 13 service operators from a pharmacy, we designed a remote working environment for human-robot collaboration that enables first-time experiences and collaboration with robots. Five participants took part in an assessment study and reported on their experiences about the utility, usability and user experience. Results show that participants were able to control and train the robot through the remote control environment. We discuss implications of our results for future work in service domains and emphasize a shift of focus from full robot automatization to human-robot collaboration forms.