Design thinking and artificial intelligence (AI) capabilities are gaining prominence in today’s dynamic markets. However, research gaps remain regarding their influence on the outcomes of new product development (NPD), such as decision-making agility, and the structural conditions facilitating or impeding their effective implementation. Considering design thinking as a dynamic capability and AI capabilities as technology-driven innovation enablers, this study examines their impact on NPD performance via NPD decision-making agility. An empirical investigation using data collected from 230 U.S. firms shows that design thinking and AI capabilities positively influence agility, which in turn drives NPD performance. This study also uncovers that the moderating role of organizational formalization attenuates the impact of design thinking on NPD decision-making agility but strengthens the impact of AI capabilities on NPD decision-making agility. These findings provide NPD managers with insights into using these capabilities to enhance agility and improve NPD performance in the organizational context.

In organizations, the interest in automation is long-standing. However, adopting automated processes remains challenging, even in environments that appear highly standardized and technically suitable for it. Through a case study in Amsterdam Airport Schiphol, this paper investigates automation as a broader sociotechnical system influenced by a complex network of actors and contextual factors. We study practitioners' collective understandings of automation and subsequent efforts taken to implement it. Using imaginaries as a lens, we report findings from a qualitative interview study with 16 practitioners involved in airside automation projects. Our findings illustrate the organizational dynamics and complexities surrounding automation adoption, as reflected in the captured problem formulations, conceptions of the technology, envisioned human roles in autonomous operations, and perspectives on automation fit in the airside ecosystem. Ultimately, we advocate for contextual automation design, which carefully considers human roles, accounts for existing organizational politics, and avoids techno-solutionist approaches.

As in-car applications evolve, the potential to personalize the user experience through data and AI is becoming a key focus in automotive research. This workshop will explore how real-time data from sensors, user preferences, and behavioral insights can be leveraged to create individual in-car experiences. Current trends in AI-driven personalization, including voice assistants, adaptive interfaces, and predictive algorithms, will be discussed. Participants will dive into challenges such as privacy, data security, and user acceptance, while also exploring new possibilities for enhancing the in-car experience. Through interactive discussions and hands-on case studies, this workshop aims to uncover innovative ways to use data and AI to enrich automotive user interfaces.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

Designers’ choices of methods are well known to shape project outcomes. However, questions remain about why design teams select particular methods and how teams’ decision-making strategies are influenced by project- and process-based factors. In this mixed-methods study, 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- (A), Outcome- (O), or Process- (P) 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

Designing an innovation strategy in a world of rapid technological change has become increasingly challenging. Some companies are finding that anchoring technology choices in deeper understanding of the value users seek allows them to find a better balance among feasibility, viability, and desirability of potential solutions, and thus create more successful user outcomes. They do so by involving designers earlier in the roadmap development to guide product and technology selection, toward a future vision based on user value and aspirations. In this article, we extend two streams of prior research on technology roadmapping (TRM) and design roadmapping (DRM). First, we identify and compare technology and DRM approaches and their distinct strategic emphases: Technology selection and user value, respectively. Second, we compare two cases of DRM deployment in corporations: Siemens and Air France-KLM. The intent is to provide an in-depth understanding of why and how DRM complements TRM and how DRM facilitates making tradeoffs among strategic goals to more comprehensively address the feasibility, viability, and desirability of new product and service designs. We find that DRM embeds a deep understanding of current and future user needs, linking user-centered design and technology selection to strategy in practice.