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Nachhaltiges Innovationsmanagement in KMU: Eine empirische Untersuchung zu Living Labs as a Service
(2016)
Die neue europäische Umweltstrategie der Integrierten Produktpolitik fordert von produzierenden kleinen und mittleren Unternehmen (KMU) eine eigenverantwortliche und produktbezogene Nachhaltigkeitsstrategie. Obgleich die Gestaltung von IKT-Services in nachhaltigkeitsrelevanten Bereichen ein großes Marktpotential verspricht, birgt das Innovationsmanagement für KMU einige Risiken. Um diese Herausforderungen zu adressieren motiviert diese Arbeit Living Labs, als Innovationsinfrastruktur, um den spezifischen Bedarfen von KMU für ein nachhaltiges Innovationsmanagement gerecht zu werden. Auf der Basis von 15 semi-strukturierten Interviews mit 7 KMU, die IKT-Lösungen in den Bereichen Wohnen und Mobilität entwickeln, wurden Herausforderungen sowie etablierte Strategien für ein nachhaltiges Innovationsmanagement erhoben sowie Potenziale und mögliche Risiken von Living Labs exploriert. Die Studie zeigt KMU spezifische Bedarfe auf, die eine Anpassung des Living Lab Ansatzes als Service-Dienstleistungen erforderlich machen.
Kleinere, günstigere und effizientere Sensoren und Aktoren sowie Funkprotokolle haben dazu geführt, dass Smart Home Produkte in zunehmend auch für den privaten Massenmarkt erschwinglich werden. Damit stehen Hersteller und Anbieter vor der Herausforderung, komplexe cyber-physische Systeme für Jedermann handhabbar zu gestalten. Es fehlen allerdings empirische Erkenntnisse über die Rolle von Smart Home im Alltag. Wir präsentieren Ergebnisse aus einer Living Lab Studie, in der 14 Haushalte mit einer am Markt erhältlichen Smart Home Nachrüstlösung ausgestattet und über neun Monate empirisch begleitet wurden. Anhand der Analyse von Interviews, Beobachtungen und Co-Design Workshops in den Phasen der Produktauswahl, Installation, Konfiguration und längerfristigen Nutzung zeigen wir Herausforderungen und Potentiale von Smart Home Systemen auf. Unsere Erkenntnisse deuten darauf hin, dass das Smart Home immer noch von technischen Details dominiert wird. Zugleich fehlen Nutzern angemessene Steuerungs- und Kontrollmöglichkeiten, um weiterhin die Entscheidungshoheit im eigenen Zuhause zu behalten.
Technological objects present themselves as necessary, only to become obsolete faster than ever before. This phenomenon has led to a population that experiences a plethora of technological objects and interfaces as they age, which become associated with certain stages of life and disappear thereafter. Noting the expanding body of literature within HCI about appropriation, our work pinpoints an area that needs more attention, “outdated technologies.” In other words, we assert that design practices can profit as much from imaginaries of the future as they can from reassessing artefacts from the past in a critical way. In a two-week fieldwork with 37 HCI students, we gathered an international collection of nostalgic devices from 14 different countries to investigate what memories people still have of older technologies and the ways in which these memories reveal normative and accidental use of technological objects. We found that participants primarily remembered older technologies with positive connotations and shared memories of how they had adapted and appropriated these technologies, rather than normative uses. We refer to this phenomenon as nostalgic reminiscence. In the future, we would like to develop this concept further by discussing how nostalgic reminiscence can be operationalized to stimulate speculative design in the present.
New cars are increasingly "connected" by default. Since not having a car is not an option for many people, understanding the privacy implications of driving connected cars and using their data-based services is an even more pressing issue than for expendable consumer products. While risk-based approaches to privacy are well established in law, they have only begun to gain traction in HCI. These approaches are understood not only to increase acceptance but also to help consumers make choices that meet their needs. To the best of our knowledge, perceived risks in the context of connected cars have not been studied before. To address this gap, our study reports on the analysis of a survey with 18 open-ended questions distributed to 1,000 households in a medium-sized German city. Our findings provide qualitative insights into existing attitudes and use cases of connected car features and, most importantly, a list of perceived risks themselves. Taking the perspective of consumers, we argue that these can help inform consumers about data use in connected cars in a user-friendly way. Finally, we show how these risks fit into and extend existing risk taxonomies from other contexts with a stronger social perspective on risks of data use.
When dialogues with voice assistants (VAs) fall apart, users often become confused or even frustrated. To address these issues and related privacy concerns, Amazon recently introduced a feature allowing Alexa users to inquire about why it behaved in a certain way. But how do users perceive this new feature? In this paper, we present preliminary results from research conducted as part of a three-year project involving 33 German households. This project utilized interviews, fieldwork, and co-design workshops to identify common unexpected behaviors of VAs, as well as users’ needs and expectations for explanations. Our findings show that, contrary to its intended purpose, the new feature actually exacerbates user confusion and frustration instead of clarifying Alexa's behavior. We argue that such voice interactions should be characterized as explanatory dialogs that account for VA’s unexpected behavior by providing interpretable information and prompting users to take action to improve their current and future interactions.
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.
Organisationen wollen Produkte mit guter User Experience herstellen. Durch die Evaluation der organisationalen UX-Gestaltungskompetenz können Organisationen erkennen, wie stark ihre momentane UX-Gestaltungskompetenz ausgeprägt ist und wie die Kompetenz gezielt gesteigert werden kann. Für die Abbildung der aktuellen Kompetenz werden ein Fragebogen zur theoretischen Kompetenz und ein Fragebogen für die Produktevaluation kombiniert. Durch diese Kombination wird die Kompetenz der Organisation aus der Handlungs- und der Ergebnisperspektive betrachtet. Für die Erarbeitung von Handlungsfeldern zur Verbesserung der Kompetenz werden qualitative Interviews durchgeführt und mit den Ergebnissen der quantitativen Erhebungen verknüpft. Durch einen anschließenden Ergebnisworkshop erarbeiten sich die Mitglieder der Organisation einen effizienten Weg zur Steigerung der organisationalen UX-Kompetenz.
Durch die Digitalisierung befindet sich die Mobilitätsbranche im starken Umbruch. So wird man bei der Verkehrsmittelwahl zukünftig wohl auch auf selbstfahrende Autos zurückgreifen können. Die Studie erweitert die Verkehrs- und Nutzerakzeptanzforschung, indem unter Berücksichtigung relativer Teilmehrwerte tiefergehend analysiert wird, wie sich die neuen Verkehrsmodi autonomer Privat-PKW, autonomes Carsharing und autonomes Taxi aus heutiger Sicht in den bestehenden Verkehrsmix einsortieren. Hierzu wurde auf Basis der Nutzerpräferenztheorie eine Onlineumfrage (n=172) zu den relativen Mehrwerten der neuen autonomen Verkehrsmodi durchgeführt. Es zeigt sich, dass Nutzer im Vergleich zum PKW bei den autonomen Modi Verbesserungen im Fahrkomfort und in der Zeitnutzung sehen, in vielen anderen Bereichen – insbesondere bei Fahrspaß und Kontrolle – hingegen keine Vorteile oder sogar relative Nachteile sehen. Gegenüber dem ÖPNV bieten die autonomen Modi in fast allen Eigenschaften Mehrwerte. Diese Betrachtung auf Teilnutzenebene liefert eine genauere Erklärung für Nutzerakzeptanz des automatisierten Fahrens.
„Industrie 4.0“ und weitere Schlagwörter wie „Big Data“, „Internet der Dinge“ oder „Cyber-physical Systems“ werden gegenwärtig in der Wirtschaft häufig aufgegriffen. Ausgangspunkt hierfür ist die Vernetzung von IT-Technologien sowie die durchgängige Digitalisierung. Nicht nur die Geschäftsfelder und Business-Modelle der Unternehmen selbst unterliegen dabei ei-nem entsprechend radikalen Wandel, dieser bezieht sich auch auf die Arbeitsumgebungen der Mitarbeiter, sowie den privaten und den öffentlichen Raum (Botthof, 2015; Hartmann, 2015).
The megatrends towards both a digital and a usership economy have changed entire markets in the past and will continue to do so over the next decades. In this work, we outline what this change means for possible futures of the mobility sector, taking the combination of trends in both economies into account. Using a sys-tematic, scenario-based trend analysis, we draft four general future scenarios and adapt the two most relevant scenarios to the automotive sector. Our findings show that combing the trends from both economies provides new insights that have often been neglected in literature because of an isolated view on digital technology only. However, service concepts such as self-driving car sharing or self-driving taxis have a great impact at various levels including microeconomic (e.g., service and product design, business models) and macroeconomic (e.g., with regard to ecological, economical, and social impacts). We give a brief outline of these issues and show which business mo dels could be successful in the most likely future scenarios, before we frame strategic implications for today’s automobile manufacturers.
Smart home systems change the way we experience the home. While there are established research fields within HCI for visualizing specific use cases of a smart home, studies targeting user demands on visualizations spanning across multiple use cases are rare. Especially, individual data-related demands pose a challenge for usable visualizations. To investigate potentials of an end-user development (EUD) approach for flexibly supporting such demands, we developed a smart home system featuring both pre-defined visualizations and a visualization creation tool. To evaluate our concept, we installed our prototype in 12 households as part of a Living Lab study. Results are based on three interview studies, a design workshop and system log data. We identified eight overarching interests in home data and show how participants used pre-defined visualizations to get an overview and the creation tool to not only address specific use cases but also to answer questions by creating temporary visualizations.
Vertrauen ist das Schmiermittel der Shareconomy. Einen zentralen Mechanismus hierfür stellen Crowd-basierte Reputationssysteme dar, bei denen Informationen und Bewertungen anderer Nutzer dazu dienen Vertrauen aufzubauen. Die Vernetzung zu teilender Gegenstände bietet hierbei neue Potentiale, um die Reputation eines Anbieters oder Nachfragers zu bewerten und einzuschätzen. In diesem Beitrag untersu-chen wir daher das Potential eines IoT-basierten Reputationssystems im Kontext von Peer-to-Peer Car-sharing, bei dem Informationen und Bewertungen mittels Sensorik während der Nutzung des Fahrzeugs erhoben und ausgewertet werden. Hierzu wurden zwei Fokusgruppen mit insgesamt 12 Personen durch-geführt. Die Ergebnisse deuten an, dass datenbasierte Reputationssysteme das Vertrauen nicht nur vor, sondern auch während der Vermietung und in der Nachkontrolle für Ver- und Entleiher steigern können. Jedoch sollten bei der Gestaltung solcher Systeme die Prinzipien der mehrseitigen Sicherheit wie Spar-samkeit, Verhältnismäßigkeit, Transparenz und Reziprozität beachtet werden.
Taste is a complex phenomenon that depends on the individual experience and is a matter of collective negotiation and mediation. On the contrary, it is uncommon to include taste and its many facets in everyday design, particularly online shopping for fresh food products. To realize this unused potential, we conducted two Co-Design workshops. Based on the participants’ results in the workshops, we prototyped and evaluated a click-dummy smart-phone app to explore consumers’ needs for digital taste depiction. We found that emphasizing the natural qualities of food products, external reviews, and personalizing features lead to a reflection on the individual taste experience. The self-reflection through our design enables consumers to develop their taste competencies and thus strengthen their autonomy in decision-making. Ultimately, exploring taste as a social experience adds to a broader understanding of taste beyond a sensory phenomenon.
So far, sustainable HCI has mainly focused on the domestic context, but there is a growing body of work looking at the organizational context. As in the domestic context, these works still rest on psychological theories for behaviour change used for the domestic context. We supplement this view with an organizational theory-informed approach that adopts organizational roles as a key element. We will show how a role-based analysis could be applied to uncover information needs and to give em-ployee’s eco-feedback, which is linked to their tasks at hand. We illustrate the approach on a qualitative case study that was part of a broader, ongoing action research conducted in a German production company.
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.
UX-Professionals stehen vor der Aufgabe ihre Fertigkeiten und Kenntnisse kontinuierlich auszubauen. Eine Möglichkeit dies zu tun sind Communities of Practice, also Gemeinschaften von Personen mit ähnlichen Aufgaben und Schwerpunkten sowie einem gemeinsamen Interesse an Lösungen. Sie agieren weitgehend selbstorganisiert und dienen dem Austausch und der gegenseitigen Unterstützung. So entstehen ein gemeinsamer Wissensschatz sowie ein Netzwerk zwischen allen UX-Interessierten. Der Aufbau einer Community of Practice für UX-Professionals wurde in einem mittelständigen Unternehmen über 18 Monate begleitet und ausgewertet. Die Ergebnisse führten zu Handlungsempfehlungen, um Hindernisse beim Aufbau zu reduzieren und einen Mehrwert für alle Beteiligten herbeizuführen.
Traditionally automotive UI focusses on the ergonomic design of controls and the user experience in the car. Bringing networked sensors into the car, connected cars can provide additional information to car drivers and owners, for and beyond the driving task. While there already are technological solutions, such as mobile applications commercially available, research on users’ information demands in such applications is scarce. We conducted four focus groups to uncover what kind of information users might be interested in to see on a second dashboard. Our findings show that besides control screens of todays’ dashboards, people are also interested in connected car services providing context information for a current driving situation and allowing strategic planning of driving safety or supporting car management when not driving. Our use cases inform the design of content for secondary dashboards for and especially beyond the driving context with a user perspective.
Critical consumerism is complex as ethical values are difficult to negotiate, appropriate products are hard to find, and product information is overwhelming. Although recommender systems offer solutions to reduce such complexity, current designs are not appropriate for niche practices and use non-personalized intransparent ethics. To support critical consumption, we conducted a design case study on a personalized food recommender system. Therefore, we first conducted an empirical pre-study with 24 consumers to understand value negotiations and current practices, co-designed the recommender system, and finally evaluated it in a real-world trial with ten consumers. Our findings show how recommender systems can support the negotiation of ethical values within the context of consumption practices, reduce the complexity of finding products and stores, and strengthen consumers. In addition to providing implications for the design to support critical consumption practices, we critically reflect on the scope of such recommender systems and its appropriation.
Shared Autonomous Vehicles: Potentials for a Sustainable Mobility and Risks of Unintended Effects
(2018)
Automated and connected cars could significantly reduce congestion and emissions through a more efficient flow of traffic and a reduction in the number of vehicles. An increase in demand for driving with autonomous vehicles is also conceivable due to higher comfort and improved quality of time using driverless cars. So far, empirical evidence supporting this hypothesis is missing. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as an indicator for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 German participants. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether traditional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more effort should be placed in making public transportation more attractive if sustainable mobility is to be developed.
In 1991 the researchers at the center for the Learning Sciences of Carnegie Mellon University were confronted with the confusing question of “where is AI” from the users, who were interacting with AI but did not realize it. Three decades of research and we are still facing the same issue with the AItechnology users. In the lack of users’ awareness and mutual understanding of AI-enabled systems between designers and users, informal theories of the users about how a system works (“Folk theories”) become inevitable but can lead to misconceptions and ineffective interactions. To shape appropriate mental models of AI-based systems, explainable AI has been suggested by AI practitioners. However, a profound understanding of the current users’ perception of AI is still missing. In this study, we introduce the term “Perceived AI” as “AI defined from the perspective of its users”. We then present our preliminary results from deep-interviews with 50 AItechnology users, which provide a framework for our future research approach towards a better understanding of PAI and users’ folk theories.