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Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
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.
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.
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.
Smart home systems are becoming an integral feature of the emerging home IT market. Under this general term, products mainly address issues of security, energy savings and comfort. Comprehensive systems that cover several use cases are typically operated and managed via a unified dashboard. Unfortunately, research targeting user experience (UX) design for smart home interaction that spans several use cases or covering the entire system is scarce. Furthermore, existing comprehensive and user-centered longterm studies on challenges and needs throughout phases of information collection, installation and operation of smart home systems are technologically outdated. Our 18-month Living Lab study covering 14 households equipped with smart home technology provides insights on how to design for improving smart home appropriation. This includes a stronger sensibility for household practices during setup and configuration, flexible visualizations for evolving demands and an extension of smart home beyond the location.
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.
The technological development of the digital computer and new options to collect, store and transfer mass data have changed the world in the last 40 years. Moreover, due to the ongoing progress of computer power, the establishment of the Internet as critical infrastructure and the options of ubiquitous sensor systems will have a dramatic impact on economies and societies in the future. We give a brief overview about the technological basics especially with regard to the exponential growth of big data and current turn towards sensor-based data collection. From this stance, we reconsider the various dimensions of personal data and and market mechanisms that have an impact of data usage and protection.
Innovations in the mobility industry such as automated and connected cars could significantly reduce congestion and emissions by allowing the traffic to flow more freely and reducing the number of vehicles according to some researchers. However, the effectiveness of these sustainable product and service innovations is often limited by unexpected changes in consumption: some researchers thus hypothesize that the higher comfort and improved quality of time in driverless cars could lead to an increase in demand for driving with autonomous vehicles. So far, there is a lack of empirical evidence supporting either one or other of these hypotheses. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as indicators for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 participants in Germany. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether conventional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, the findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more emphasis should be placed in making public transport more attractive if sustainable mobility is to be developed.
Digitisation has brought a major upheaval to the mobility sector, and in the future, self-driving cars will probably be one of the transport modes. This study extends transport and user acceptance research by analysing in greater depth how the new modes of autonomous private cars, autonomous carsharing and autonomous taxis fit into the existing traffic mix from today's perspective. It focuses on accounting for relative added value. For this purpose, user preference theory was used as a base for an online survey (n=172) on the relative added value of the new autonomous traffic modes. Results show that users see advantages in the autonomous modes for driving comfort and time utilization whereas, in comparison to conventional cars, in many other areas – especially in terms of driving pleasure and control – they see no advantages or even relative disadvantages. Compared to public transport, the autonomous modes offer added values in almost all characteristics. This analysis at the partwor th level provides a more detailed explanation for user acceptance of automated driving.
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.
Designing consumption feedback to support sustainable behavior is an active research topic. In recent years, relevant work has suggested a variety of possible design strategies. Addressing the more recent developments in this field, this paper presents a structured literature review, providing an overview of current information design approaches and highlighting open research questions. We suggest a literature-based taxonomy of used strategies, data source and output media with a special focus on design. In particular, we analyze which visual forms are used in current research to reach the identified strategy goals. Our survey reveals that the trend is towards more complex and contextualized feedback and almost every design within sustainable HCI adopts common visualization forms. Furthermore, adopting more advanced visual forms and techniques from information visualization research is helpful when dealing with ever-increasing data sources at home. Yet so far, this combination has often been neglected in feedback design.
The alternative use of travel time is one of the widely discussed benefits of driverless cars. We therefore conducted 14 co-design sessions to examine how people manage their time, to determine how they perceive the value of time in driverless cars and to derive design implications. Our findings suggest that driverless mobility will affect both people’s use of travel time as well as their time management in general. The participants repeatedly stated the desire of completing tasks while traveling to save time for activities that are normally neglected in their everyday life. Using travel time efficiently requires using car space efficiently, too. We found out that the design concept of tiny houses could serve as common design pattern to deal with the limited space within cars and support diverse needs.
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 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.
Who do you trust: Peers or Technology? A conjoint analysis about computational reputation mechanisms
(2020)
Peer-to-peer sharing platforms are taking over an increasingly important role in the platform economy due to their sustainable business model. By sharing private goods and services, the challenge arises to build trust between peers online mostly without any kind of physical presence. Peer rating has been proven as an important mechanism. In this paper, we explore the concept called Trust Score, a computational rating mechanism adopted from car telematics, which can play a similar role in carsharing. For this purpose, we conducted a conjoint analysis where 77 car owners chose between fictitious user profiles. Our results show that in our experiment the telemetric-based score slightly outperforms the peer rating in the decision process, while the participants perceived the peer rating more helpful in retrospect. Further, we discuss potential benefits with regard to existing shortcomings of user rating, but also various concerns that should be considered in concepts like telemetric-based reputation mechanism that supplements existing trust factors such as user ratings.
Autonomous driving enables new mobility concepts such as shared-autonomous services. Although significant re-search has been done on passenger-car interaction, work on passenger interaction with robo-taxis is still rare. In this paper, we tackle the question of how passengers experience robo-taxis as a service in real-life settings to inform the interaction design. We conducted a Wizard of Oz study with an electric vehicle where the driver was hidden from the passenger to simulate the service experience of a robo-taxi. 10 participants had the opportunity to use the simulated shared-autonomous service in real-life situations for one week. By the week's end, 33 rides were completed and recorded on video. Also, we flanked the study conducting interviews before and after with all participants. The findings provided insights into four design themes that could inform the service design of robo-taxis along the different stages including hailing, pick-up, travel, and drop-off.
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.
Trust is the lubricant of the sharing economy. This is true especially in peer-to-peer carsharing, in which one leaves a highly valuable good to a stranger in the hope of getting it back unscathed. Nowadays, ratings of other users are major mechanisms for establishing trust. To foster uptake of peer-to-peer carsharing, connected car technology opens new possibilities to support trust-building, e.g., by adding driving behavior statistics to users' profiles. However, collecting such data intrudes into rentees' privacy. To explore the tension between the need for trust and privacy demands, we conducted three focus group and eight individual interviews. Our results show that connected car technologies can increase trust for car owners and rentees not only before but also during and after rentals. The design of such systems must allow a differentiation between information in terms of type, the context, and the negotiability of information disclosure.