Although the topic of dynamic design capabilities is emerging in the literature and the design community, no research has yet offered an operationalization that considers the strategic integration of DDCs within the organization. This Research Design paper aims to address this gap by defining, conceptualizing, and measuring DDCs through multiple validation studies. Specifically, a scale development procedure grounded on measurement theory will operationalize DDCs through their operational and regenerative dimensions. Drawing on the theory of dynamic capabilities, this paper also presents a conceptual model that will be used to test and validate the newly developed construct of DDCs. This conceptualization explores the influence of DDCs on business model innovation and innovation performance under varying conditions, such as volatility, uncertainty, complexity, and ambiguity (VUCA).@en

The transition from the old to the new generation of a product is important for various sectors. This type of innovation is often challenging due to the diminishing product lifecycles and rapid technological obsolescence. Despite the managerial relevance, little is known about what abilities of the firms allow them to achieve superior generational product innovativeness. To enrich our understanding, the present study reports on evidence from 201 UK firms conducting generational product innovations. The results reveal that intentional cannibalization significantly enhances decision-making agility. This agility is crucial for innovation, particularly under high technological turbulence, a context that requires rapid adaptation and change. Generally, the findings make a useful contribution to product innovation research (specifically in generational transitions) and add to the emerging research on the role of agility in organizations. Moreover, they suggest managerial propositions regarding how firms can achieve superior generational innovativeness. Finally, they point at future research propositions.@en

As the development of Generative AI technology continues to progress, the opportunity for innovation with AI in the form of user interfaces, products and services within vehicles is expanding. Furthermore, automobiles are undergoing major transformations in design due to changes in the underlying technology resulting in evolved user needs, behaviors, activities and aspirations. This workshop is aimed at providing the participants hands-on experience of designing novel Generative AI interfaces for vehicles. While working on the design challenge as the connecting thread, we will introduce and weave together modules of knowledge domains focusing on Human-centered design, Ethical and Responsible behavior, and Autonomy in vehicles. Participants will learn about and engage collaboratively in employing design methods such as Co-creation using Activity Canvases, Enactment, Wizard of Oz, Bodystorming and inter-group discussion. As the outcome, we aim to publish participant’s design concepts as a booklet and a research paper, and seek new research collaborations.@en

Sustained adoption of automation is a problem for organizations, despite the promised benefits of automation and the propensity for organizations to expect it to transform their workplaces. To address this problem, previous work in HCI has mostly considered the perspectives and experiences of users interacting with automation technologies and has not considered the broader organizational context consisting of different stakeholders with varying needs and expectations around automation. Taking Amsterdam Airport Schiphol as a case study, we examine the challenges faced by practitioners responsible for integrating automation projects in its airside ecosystem, in an interview study conducted with 8 participants. Our findings reveal three challenges to the adoption of automation within the organization - the lack of consensus among different stakeholders, the need to adapt the technology to the specific context, and the undefined procedures required to maintain automation after implementation, that should be further addressed by the HCI community.@en

The Development of Fully Autonomous Vehicles (AVs) would fundamentally change the nature of in-vehicle user interactions, behaviors, needs, and activities. Passengers free from driving would expect to undertake diverse Non-Driving-Related Tasks to keep themselves occupied. Introducing Conversational Artificial Intelligence (CAI) in Level 5 AVs could improve the in-vehicle user experience (UX). To explore this, firstly, we identify what roles and relationships can CAI play towards end-users of AVs through end-user interviews and thematic analysis. Secondly, we examine how end-users qualitatively assess the embodied UX of the CAI roles and relationships through guided brainstorming, post simulator interaction experiments employing Wizard of Oz setup and Participant Enactment methods. Results show that Tour Guide, Mentor, and Storyteller were the most preferred CAI roles, and that Human-CAI relationships are maintained if the CAI mediates in-vehicle user activities, interactions, sharing of vehicle control, and deep conversations. We discuss the research implications and propose design guidelines.@en

The Development of Fully Autonomous Vehicles (AVs) would fundamentally change the nature of in-vehicle user interactions, behaviors, needs, and activities. Passengers free from driving would expect to undertake diverse Non-Driving-Related Tasks to keep themselves occupied. Introducing Conversational Artificial Intelligence (CAI) in Level 5 AVs could improve the in-vehicle user experience (UX). To explore this, firstly, we identify what roles and relationships can CAI play towards end-users of AVs through end-user interviews and thematic analysis. Secondly, we examine how end-users qualitatively assess the embodied UX of the CAI roles and relationships through guided brainstorming, post simulator interaction experiments employing Wizard of Oz setup and Participant Enactment methods. Results show that Tour Guide, Mentor, and Storyteller were the most preferred CAI roles, and that Human-CAI relationships are maintained if the CAI mediates in-vehicle user activities, interactions, sharing of vehicle control, and deep conversations. We discuss the research implications and propose design guidelines.@en

Economic deglobalization, characterized by reduced global integration and interaction, presents significant challenges for startups with limited resources to adapt and innovate their resource management and business growth strategies. This paper investigates how innovative technical startups based in the tech incubator program in the Netherlands respond to economic deglobalization, focusing on their strategic management of competitive resources to achieve dynamic stability—-the ability of a business to return to steady or new status after an external disturbance. Findings are thematically concluded with six main resource management strategies: flexible supply chain, comprehensive talent planning, an optimized mix of investments, the value of time and money, diversified marketing strategies, and clear knowledge security. By designing a systematic framework for startups to navigate dynamic stability, our research identified the effectiveness of channel resilience, operational adaptability, and executive innovation in an economically deglobalized world as the strategic designary reactions to economic deglobalization.@en

The aviation industry is one of the sectors that has been heavily impacted by the pandemic. While the major body of literature has focused on passenger experience and behaviour, this study focuses on airport employees instead—their experiences, perceptions, and preferences following the emergence of COVID-19. More than 1000 participants from 4 major airports—Amsterdam Airport Schiphol, Singapore Changi Airport, Taipei Taoyuan Airport, and Zurich Airport—representing over 10 different occupations, have provided a variety of sentiments about the airport as an employment ecosystem in the wake of COVID-19. Quantitatively and qualitatively surveying four different airports enabled a cross-border analysis of the results to identify interesting geographic contrasts, as well as global themes, among the responses. Regional differences regarding, the feeling of preparedness, confidence in measures, and optimism are presented. A significant difference in confidence in non-pharmaceutical measures between employees from Asian and European airports is shown. Wants and needs such as better physical/IT workplace infrastructure and more flexibility regarding job scope and hours are pointed out. The results of this research provide insights for future airport employee experience research by outlining areas to study in greater detail. Furthermore, practical implications for airport stakeholders and companies arising from the challenges experienced by the workforce are laid out to provide guidance to prepare for similar circumstances in the future and navigate the aftermath of and recovery from the pandemic.

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Autonomous products (e.g., home cleaning robots, smart fridges, or autonomous vehicles) take over tasks that require time and effort from their users, redefining both the user roles and context around a product. Consequently, meaningful user experiences should be designed to overcome the risk of relegating humans to undesirable tasks and to take the opportunity of employing users’ newly available time, in contexts such as highly automated vehicles. Meaningful experiences are provided when fundamental user needs (i.e., universal needs that directly contribute to our wellbeing) are fulfilled. Nevertheless, designers face challenges in anticipating and fulfilling user needs related to autonomous products, since autonomous technology continues evolving towards products that are not yet in existence. In this paper, we employ a co-creation workshop method to explore how the typology of thirteen fundamental needs can serve as a starting point to design meaningful user experiences associated with autonomous vehicles. Specifically, our goal is to understand how the typology of thirteen fundamental needs (e.g., autonomy, beauty, comfort...) could help in (1) identifying how deep user needs manifest themselves in a given context and (2) conceptualizing meaningful experiences with autonomous devices. In this aim, we elaborate on the challenge of designing meaningful non-driving- related experiences in fully autonomous vehicles, which could emerge in the future if driving tasks become obsolete. The results propose new clusters of activities and a scenario for each fundamental need, and ultimately show that engaging with the fundamental needs could be a valuable foundation for designing rich human interactions with future technologies.@en

As city-level modal splits are outcomes of city functions, it is essential to understand whether and how city attributes affect modal splits to derive a modal shift toward low-emission travel modes and sustainable mobility in cities. This study elucidates this relationship between modal splits and city attributes in 46 cities worldwide, proposing a two-step data mining framework. First, using the K-Means method, we classify cities into private-vehicle-, public-transit-, and bicycle-dominant groups based on their modal splits. Second, we categorize city attributes into environmental, socio-demographic, and transportation planning factors and quantify their interlocked impacts on cities' modal splits via the decision tree method. We observe that the socio-demographic factor has the highest impact on determining the cities' modal splits. In addition, high population density and employment rate are positively associated with low-emission travel modes. High gasoline tax and low public transit and taxi fares often make people reconsider possessing private vehicles. On the other hand, extreme weather conditions (e.g., hot temperatures) can prevent bicycle usage. Our contribution expands the impact of introduced city planning and policies for modal shifts toward a real-world paradigm and we present implications of the proposed framework in developing practical modal shift strategies.

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Resilience is a concept that describes the capability to be restored after unprecedented events, originally emerged from biology and human sciences. This paper aims to explore what a resilient public transportation system is and how nature’s wisdom can be used as an inspiration for the creation of resilience in the area of mobility, by linking public transportation systems, biomimicry and resilience together. To this end, qualitative co-creative workshops were conducted with eleven domain experts from public transportation, biomimicry, and biology. The experts addressed several factors contributing to resilience in public transport that could be categorized into four aggregated dimensions: resilience through system organization, resilience through information management, resilience through operating performance, and resilience through subsystem integration. Finally, a conceptual wheel framework on factors of resilient public transportation systems is proposed, aiming to shed light on future public transport developments, where a systemic perspective is to be adopted. @en

The computing paradigm where sensor and actuator technology work in tandem to track and act on events in real Euclidean space, known as ambient intelligence (AmI), is likely to become increasingly common due to the rapid maturation of computing technology. Installing AmI in the built environment creates ambient intelligent environments (AmIE), which strive to make the places we inhabit (invisibly) sensitive and responsive to our presence, needs, wants, and preferences. Given that built environments and the goings-on therein are complicated in an of them selves, implementing AmI for (increasingly) complicated tasks in (increasingly) complicated scenarios, increases the difficulty of managing the outcomes in AmIEs. Our previous research indicates that industry practitioners attribute the agency of AmI artifacts as responsible for these outcomes; especially when harm perpetuation is (one of) the outcome(s), which we codified as the Agency/Intelligence Axis [1]. Due to the nascence of AmI, research on best practices for the design-engineering of AmI is still emerging. This research seeks to add to this literature by evaluating our formerly identified Agency/Intelligence Axis in the context of AmIE through a case study of VyZee, a retail company working on transitioning their retail stores to “smart” stores. Our findings highlight that while VyZee seems largely unaware of any relationship between agency and perpetuating un-anticipated/-desired outcomes, they do implement an array of levels of AmI agency in their retail stores, and their justifications for their choices are presented in the discussion. Finally, coding the data revealed more nuance then previously documented in the Agency/Intelligence Axis, and a new Ambient Intelligent Agent Model, which suggests that AmI agents have six properties, is proposed.

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As the aviation industry has become more complex and uncertain, we need to teach aviation topics with different pedagogical approaches: making the educational setting interdisciplinary and more design-and user-driven. We developed a design curriculum to address emerging complexity around air travel journeys and piloted the curriculum at a major research university in the Netherlands. Novice students in engineering, design, and social science programs in the Future of Airport minor on campus engaged in a quarter-long design course centered on the seamless air travel experience. The course aims to teach students how to approach the complexity of an airport and the stakeholders involved and design for people in transit. Data were collected from the results of work in document format (project progress reports and final deliverables) from thirty-five student teams who collaborated with aviation industry sponsors to develop solutions to address complex system-level industry design challenges. We classified the detailed project brief and outcomes by different innovation levels (product, service, system, or socio-technical), and examined the design methods implemented by each team over the design process. Our discussion is divided into (D1) trajectory of levels of innovation traveled during the project execution, (D2) descriptive reflection on overall selecting design methods, (D3) design method selection dynamics over design phases in complex problem domains, and (D4) challenges of offering a design approach to novice engineering students, drawn from the reflection by course coordinators and coaches on the course structure and contents.@en

Increasingly digital products and services make cybersecurity a crucial issue for designers. However, human-centered designers struggle to consider it in their work, partially a consequence of the high psychological distance between designers and cybersecurity. In this work, we build on the Design for Cybersecurity (DfC) Cards, an intervention to help designers consider cybersecurity, and examine a project-based design course to understand how and why specific DfC cards were used. Three findings result. First, designers found the intervention useful across all design phases and activities. Second, the cards helped design teams refocus their attention on the problem domain and project outcome. Third, we identify a need for support in framing and converging during user research, opportunity identification, and prototyping. We argue that the psychological distance between designers and the problem space of cybersecurity partially explains these findings, and ultimately exacerbates existing challenges in the design process. These findings suggest that design interventions must consider the psychological distance between designer and problem space, and have application in design practice across many complex problem domains.

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Creating Spatial Computing (SComp) artifacts (including Virtual Reality, Augmented Reality, Mixed Reality, and Ambient Intelligent artifacts) is a rapidly-emerging domain in need of new design methodologies. In this paper, we examine whether and how ethics are procedurally integrated into the creations of SComp artifacts. After an introduction to terminology—including a re-framed definition of Spatial Computing—findings of interviews with Spatial Computing practitioners are shared. The interviews indicated an awareness among professionals about the inordinate vulnerability of SComp artifacts, and about the need for—and the lack thereof—processes and tests to mitigate negative effects of SComp artifacts. Results from the domain expert interviews are integrated into a proposed framework: The Framework for Ethical Spatial Computing Design Engineering. Our framework serves to support researchers and practitioners in devising new methodologies unique to Spatial Computing by highlighting considerations central to the creation of ethical artifacts. The framework integrates the findings from the in-depth interview study and builds on existing models in Design Process, Methods, and Human-Computer Interaction (HCI) Research that highlight important barriers and opportunities between research and practice. It maps the three-phases journey consisted of (1) Enablers, (2) Synthesizers, and (3) SComp Artifacts. We trust that our work sheds light on considerations necessary to the creation of ethical Spatial Computing artifacts.

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What is meaningful mobility? Understanding meaning and what is meaningful for yourself or other people is no easy feat. Yet as designers, we all hope that our creations will be meaningful for people, society at large and the planet. In this document we present an approach that can help you to get a better grasp of meaning in the domain of mobility: the mobility edition of the 13 fundamental psychological needs typology developed by Desmet and Fokkinga (2020).@en

Design team decision-making underpins all activities in the design process. Simultaneously, goal alignment within design teams has been shown to be essential to the success of team activities, including engineering design. However, the relationship between goal alignment and design team decision-making remains unclear. In this exploratory work, we analyze six student design teams’ decision-making strategies underlying 90 selections of design methods over the course of a human-centered design project. We simultaneously examine how well each design team’s goals are aligned in terms of their perception of shared goals and their awareness of team members’ personal goals at the midpoint and end of the design process, along with three other factors underpinning team alignment at the midpoint. We report three preliminary findings about how team goal alignment and goal awareness influence team decision-making strategy that, while lacking consistent significance, invite further research. First, we observe that a decrease in awareness of team members’ personal goals may lead student teams to use a different distribution of decision-making strategies in design than teams whose awareness stays constant or increases. Second, we find that student teams exhibiting lower overall goal alignment scores appear to more frequently use agent-driven decision-making strategies, while student teams with higher overall goal alignment scores appear to more frequently use process-driven decision-making strategies. Third, we find that while student team alignment appears to influence agent- and process-driven strategy selection, its effect on outcome-driven selection is less conclusive. While grounded in student data, these findings provide a starting place for further inquiry into of designerly behavior at the nexus of teaming and design decision-making.

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Designers' choices of methods are well known to shape project outcomes. However, questions remain about why design teams select particular methodsand how teams' decision-making strategies are influenced by project- and process-based factors. In this work, we analyze novice design teams' decision-making strategies underlying 297 selections of human-centered design methods over the course of three semester-long project-based engineering design courses. We propose a framework grounded in 100+ factors sourced from new product development literature that classifies design teams' method selection strategy as either agent-, outcome-, or process-driven, with eight further subclassifications. Coding method selections with this framework, we uncover three insights about design team method selection. First, we identify fewer outcomes-based selection strategies across all phases and innovation types. Second, we observe a shift in decision-making strategy from user-focused outcomes in earlier phases to product-based outcomes in later phases. Third, we observe that decision-making strategy produces a greater heterogeneity of method selections as compared to the class average as a whole, or project type alone. These findings provide a deeper understanding of designers' method selection behavior and have implications for effective management of design teams, development of automated design support tools to aid design teams, and curation of design method repositories, e.g., theDesignExchange.

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