‘Practice what you preach’ is a phrase occasionally used to refer to those not acting as they want others to act. There are countless opportunities in professional work and daily life to bring such criticism upon ourselves. While the subject is broad, this study focuses on the application of this idea in research practice, and more specifically in design research. One point of departure is the question: ‘how should we practice research if its results are products just like other products?’ The Principle of Reflexive Practice (PRP) states that considering the outcome of design research or research itself as a product, many design principles, tools, methods or knowledge are applicable to design research.

A corollary of the principle is that in order to succeed in contemporary research environments, design researchers would gain significant benefit such as improving the success rate of their research projects, if they exercise design methods and tools in designing their research. By exercising these methods, researchers would gain quick and rich feedback about the methods they develop; they would become aware of issues that require users’ perspective that could not be possible without their own practical use.

The PRP makes participants in design research aware of the reflexive opportunity in studying design that could be mobilized to advancing their practice and making their research results more effective. Notwithstanding, adopting the PRP is not easy; therefore, it is presented as a challenge to design research. Four examples of using the PRP as a guiding principle in research are presented to demonstrate its importance and benefits.

Over the last decade, product/service systems (PSSs) have become a research issue in several disciplines, such as engineering design and marketing. The inherent interdisciplinary nature of this research issue has however remained unexploited. In order to bridge these silos and foster more interaction across relevant disciplines, this research examines PSSs from an interdisciplinary angle by analyzing how engineering design and marketing inform one another, as well as presents insights for PSS design. The research is carried out using a three-stage process for analyzing and evaluating interdisciplinary research: first, through a systematic literature review to identify relevant papers and their level of utilization across disciplines; second, by using a qualitative thematic analysis looking for different perspectives in order to find themes to bridge the gap between the disciplines; and third, by providing a research agenda to advance research by moving from silos to synergy. The results show a limited use of theories, frameworks, methods and tools across disciplines thus far, while the major contribution of this article lies in the implications derived for PSS design for academics and practitioners alike, which are categorized into seven specific themes: business orientation, collaboration, cost aspects, flexibility, performance indicators, requirements and services.

This paper presents results from an experiment using electroencephalography to measure neurophysiological activations of mechanical engineers and industrial designers when designing and problem-solving. In this study, we adopted and then extended the tasks described in a previous functional magnetic resonance imaging study reported in the literature. The block experiment consists of a sequence of three tasks: problem-solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task and then extended to a fourth open design task using free-hand sketching. This paper presents the neurophysiological results from 36 experimental sessions of mechanical engineers and industrial designers. Results indicate significant differences in activations between the problem-solving and the open design tasks. The paper focuses on the two prototypical tasks of problem-solving layout and open design sketching and presents results for both aggregate and temporal activations across participants within each domain and across domains.

The introduction of autonomous vehicles (autonomous vehicles) will reshape the many social interactions that are part of traffic today. In order for autonomous vehicles to become successfully integrated, the social interactions surrounding them need to be purposefully designed. To ensure success and save development efforts, design methods that explore social aspects in early design phases are needed to provide conceptual directions before committing to concrete solutions. This paper contributes an exploration of methods for addressing the social aspects of autonomous vehicles in three key areas: the vehicle as a social entity in traffic, co-experience within the vehicle and the user–vehicle relationship. The methods explored include Wizard of Oz, small-scale scenarios, design metaphors, enactment and peer-to-peer interviews. These were applied in a workshop setting with 18 participants from academia and industry. The methods provided interesting design seeds, however with differing effectiveness. The most promising methods enabled flexible idea exploration, but in a contextualized and concrete manner through tangible objects and enactment to stage future use situations. Further, combinations of methods that enable a shift between social perspectives were preferred. Wizard of Oz and small-scale scenarios were found fruitful as collaboration basis for multidisciplinary teams, by establishing a united understanding of the problem at hand.

In product design engineering (PDE), ideation involves the generation of technical behaviours and physical structures to address specific functional requirements. This differs from generic creative ideation tasks, which emphasise functional and technical considerations less. To advance knowledge about the neural basis of PDE ideation, we present the first fMRI study on professional product design engineers practising in industry. We aimed to explore brain activation during ideation, and compare activation in open-ended and constrained tasks. Imagery manipulation tasks were contrasted with ideation tasks in a sample of 29 PDE professionals. The key findings were: (1) PDE ideation is associated with greater activity in left cingulate gyrus; (2) there were no significant differences between open-ended and constrained tasks; and (3) a preliminary association with activity in the right superior temporal gyrus was also observed. The results are consistent with existing fMRI work on generic creative ideation, suggesting that PDE ideation may share a number of similarities at the neural level. Future work includes: functional connectivity analysis of open-ended and constrained ideation to further investigate potential differences; investigating the effects of aspects of design expertise/training on processing; and the use of novelty measures directly linked to the designer’s internal processing in fMRI analysis.

Motivated by overcoming the existing utility-based choice modeling approaches, we present a novel conceptual framework of multidimensional network analysis (MNA) for modeling customer preferences in supporting design decisions. In the proposed multidimensional customer–product network (MCPN), customer–product interactions are viewed as a socio-technical system where separate entities of ‘customers’ and ‘products’ are simultaneously modeled as two layers of a network, and multiple types of relations, such as consideration and purchase, product associations, and customer social interactions, are considered. We first introduce a unidimensional network where aggregated customer preferences and product similarities are analyzed to inform designers about the implied product competitions and market segments. We then extend the network to a multidimensional structure where customer social interactions are introduced for evaluating social influence on heterogeneous product preferences. Beyond the traditional descriptive analysis used in network analysis, we employ the exponential random graph model (ERGM) as a unified statistical inference framework to interpret complex preference decisions. Our approach broadens the traditional utility-based logit models by considering dependency among complex customer–product relations, including the similarity of associated products, ‘irrationality’ of customers induced by social influence, nested multichoice decisions, and correlated attributes of customers and products.

Sustainable design is often practiced and assessed through the consideration of three essential areas: economic sustainability, environmental sustainability, and social sustainability. For even the simplest of products, the complexities of these three areas and their tradeoffs cause decision-making transparency to be lost in most practical situations. The existing field of multiobjective optimization offers a natural framework to define and explore a given design space. In this paper, a method for defining a product’s sustainability space (defined by economic, environmental, and social sustainability objectives) is outlined and used to explore the tradeoffs within the space, thus offering both the design team and the decision makers a means of better understanding the sustainability tradeoffs. This paper concludes that sustainable product development can indeed benefit from tradeoff characterization using multiobjective optimization techniques – even when using only basic models of sustainability. Interestingly, the unique characteristics of the three essential sustainable development areas lead to an alternative view of some traditional multiobjective optimization concepts, such as weak-Pareto optimality. The sustainable redesign of a machine to drill boreholes for water wells is presented as a practical example for method demonstration and discussion.

Supporting designers is one of the main motivations for design research. However, there is an ongoing debate about the ability of design research to transfer its results, which are often provided in form of design methods, into practice. This article takes the position that the transfer of design methods alone is not an appropriate indicator for assessing the impact of design research by discussing alternative pathways for impacting design practice. Impact is created by different means – first of all through the students that are trained based on the research results including design methods and tools and by the systematic way of thinking they acquired that comes along with being involved with research in this area. Despite having a considerable impact on practice, this article takes the position that the transfer of methods can be improved by moving from cultivating method menageries to facilitating the evolution of method ecosystems. It explains what is understood by a method ecosystem and discusses implications for developing future design methods and for improving existing methods. This paper takes the position that efforts on improving and maturing existing design methods should be raised to satisfy the needs of designers and to truly support them.

Sketches are an essential tool for designers. They allow the externalizing of ideas and are therefore economic cognitively. Sketches also provide the designer with new insights, which play an important role in the emergence of ideas. However, some studies tend to show that sketching does not systematically have a positive effect on idea generation. Our research thus aims to analyze the generative effects of sketches by studying the way sketches support the design strategy of designers. We especially focus on the role of knowledge in comparison with concepts. Three sequences of sketches are analyzed employing C–K design theory; we show that drawings refer to both concepts and knowledge, but mostly to knowledge. In particular, sketching helps the architect mobilize knowledge distant from the initial topic. Moreover, the designer carries out through sketching an important work of knowledge structuration that we call ‘knowledge preordering’; by carefully selecting, testing and, if necessary, removing knowledge, the designer organizes a strategically built knowledge space. In particular, all elements involving modularity or determinism in the knowledge basis are abandoned. Such knowledge preordering thus allows the building of a splitting knowledge structure, which offers new rules for concept generation and enhances the production of original and disruptive ideas.

Invention arises from novel combinations of prior technologies. However, prior studies of creativity have suggested that overly novel combinations may be harmful to invention. Apart from the factors of expertise, market, etc., there may be such a thing as ‘too much’ or ‘too little’ novelty that will determine an invention’s future value, but little empirical evidence exists in the literature. Using technical patents as the proxy of inventions, our analysis of 3.9 million patents identifies a clear ‘sweet spot’ in which the mix of novel combinations of prior technologies favors an invention’s eventual success. Specifically, we found that the invention categories with the highest mean values and hit rates have moderate novelty in the center of their combination space and high novelty in the extreme of their combination space. Too much or too little central novelty suppresses the positive contribution of extreme novelty in the invention. Furthermore, the combination of scientific and broader knowledge beyond patentable technologies creates additional value for invention and enlarges the advantage of the novelty sweet spot. These findings may further enable data-driven methods both for assessing invention novelty and for profiling inventors, and may inspire a new strand of data-driven design research and practice.

This paper proposes a relationship between design thinking and computational thinking. It describes design thinking and computational thinking as two prominent ways of understanding how people address design problems. It suggests that, currently, each of design thinking and computational thinking is defined and theorized in isolation from the other. A two-dimensional ontological space of the ways that people think in addressing problems is proposed, based on the orientation of the thinker towards problem and solution generality/specificity. Placement of design thinking and computational thinking within this space and discussion of their relationship leads to the suggestion of a dual process model for addressing design problems. It suggests that, in this model, design thinking and computational thinking are processes that are ontological mirror images of each other, and are the two processes by which thinkers address problems. Thinkers can move fluently between the two. The paper makes a contribution towards the theoretical foundations of design thinking and proposes questions about how design thinking and computational thinking might be both investigated and taught as constituent parts of a dual process.

Governments encourage use of electric vehicles (EV) via regulation and investment to minimize greenhouse gas (GHG) emissions. Manufacturers produce vehicles to maximize profit, given available public infrastructure and government incentives. EV public adoption depends not only on price and vehicle attributes, but also on EV market size and infrastructure available for refueling, such as charging station proximity and recharging length and cost. Earlier studies have shown that government investment can create EV market growth, and that manufacturers and charging station operators must cooperate to achieve overall profitability. This article describes a framework that connects decisions by the three stakeholders (government, EV manufacturer, charging station operator) with preferences of the driving public. The goal is to develop a framework that allows the effect of government investment on the EV market to be quantified. This is illustrated in three scenarios in which we compare optimal public investment for a city in USA (Ann Arbor, Michigan) and one in China (Beijing) to minimize emissions, accounting for customer preferences elicited from surveys conducted in the two countries. Under the modeling assumptions of the framework, we find that high customer sensitivity to prices, combined with manufacturer and charging station operator profit maximization strategies, can render government investment in EV subsidies ineffective, while a collaboration among stakeholders can achieve both emission reduction and profitability. When EV and station designs improve beyond a certain threshold, government investment influence on EV adoption is attenuated apparently due to diminishing customer willingness to buy. Furthermore, our analysis suggests that a diversified government investment portfolio could be especially effective for the Chinese market, with charging costs and price cuts on license plate fees being as important as EV subsidies.

We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period 1991–present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions and others. Upon summarising and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research.

Design processes require the joint effort of many people to collaborate and work on multiple activities. Effective techniques to analyse and model design processes are important for understanding organisational dynamics, for improving collaboration, and for planning robust design processes, reducing the risk of rework and delays. Although there has been much progress in modelling and understanding design processes, little is known about the interplay between people and the activities they perform and its influence on design process robustness. To analyse this interplay, we model a large-scale design process of a biomass power plant with $100+$ people and ${\sim}150$ activities as a bipartite network. Observing that some people act as bridges between activities organised to form nearly independent modules, in order to evaluate process fragility, we simulate random failures and targeted attacks to people and activities. We find that our process is more vulnerable to attacks to people rather than activities. These findings show how the allocation of people to activities can obscure an inherent fragility, making the process highly sensitive and dependent on specific people. More generally, we show that the behaviour of robustness is determined by the degree distributions, the heterogeneity of which can be leveraged to improve robustness and resilience to cascading failures. Overall, we show that it is important to carefully plan the assignment of people to activities.

This position paper presents a new approach based on my experience in the evolution of human-centered design (HCD) during four decades, and how it has struggled to become a discipline in its own right in complex socio-technical systems’ creation, development and operations. The 20th century saw tremendous industrial developments based on tangible materials that were transformed and assembled to make washing machines, cars, aircraft and power plants; during its last three decades, electronics and software were incrementally added to hardware machines. Operationalization issues moved from hardware to software, making automation and user interfaces central issues. From the beginning of the 21st century, we began to do the exact opposite! Currently, we typically start a project by designing and developing technology on computers, using software only, which is later transformed into hardware (and software). I denote this shift, the ‘socio-technical inversion’. Operationalization issues are moving from software to hardware, making tangibility a central issue. Three useful conceptual models are presented: the SFAC (Structure/Function versus Abstract/Concrete) model; the NAIR (Natural/Artificial versus Cognitive/Physical) model; and the AUTOS (Artifact, User, Task, Organization and Situation) pyramid. Concepts developed in this article are based on the rationalization of a long experience in the aerospace domain.

Models of products and design processes are key to interacting with engineering designs and managing the processes by which they are developed. In practice, companies maintain networks of many interrelated models which need to be synthesised in the minds of their users when considering issues that cut across them. This article considers how information from product and design process models can be integrated with a view to help manage these complex interrelationships. A framework highlighting key issues surrounding model integration is introduced and terminology for describing these issues is developed. To illustrate the framework and terminology, selected modelling approaches that integrate product and process information are discussed and organised according to their levels and forms of integration. Opportunities for further work to advance integrated modelling in engineering design research and practice are discussed.

Set-based design (SBD), sometimes referred to as set-based concurrent engineering (SBCE), has emerged as an important component of lean product development (LPD) with all researchers describing it as a core enabler of LPD. Research has explored the principles underlying LPD and SBCE, but methodologies for the practical implementation need to be better understood. A review of SBD is performed in this article in order to discover and analyse the key aspects to consider when developing a model and methodology to transition to SBCE. The publications are classified according to a new framework, which allows us to map the topology of the relevant SBD literature from two perspectives: the research paradigms and the coverage of the generic creative design process (Formulation–Synthesis–Analysis–Evaluation–Documentation–Reformulation). It is found that SBD has a relatively low theoretical development, but there is a steady increase in the diversity of contributions. The literature abounds with methods, guidelines and tools to implement SBCE, but they rarely rely on a model that is in the continuum of a design process model, product model or knowledge-based model with the aim of federating the three Ps (People–Product–Process) towards SBCE and LPD in traditional industrial contexts.

Technologies are created through the collective efforts of individual inventors. Understanding inventors’ behaviors may thus enable predicting invention, guiding design efforts or improving technology policy. We examined data from 2.8 million inventors’ 3.9 million patents and found that most patents are created by ‘explorers’: inventors who move between different technology domains during their careers. We mapped the space of latent relatedness between technology domains and found explorers were 250 times more likely to enter technology domains that were highly related to the domains of their previous patents, compared to an unrelated domain. The great regularity of inventors’ behavior enabled accurate prediction of individual inventors’ future movements: a model trained on just 5 years of data predicted inventors’ explorations 30 years later with a log-loss below 0.01. Inventors entering their most related domains were associated with patenting up to 40% more in the new domain, but with reduced citations per patent. These findings may be instructive for inventors exploring design directions, and useful for organizations or governments in forecasting or directing technological change.

The use of decision-making models in the early stages of the development of complex products and technologies is a well-established practice in industry. Engineers rely on well-established statistical and mathematical models to explore the feasible design space and make early decisions on future design configurations. At the same time, researchers in both value-driven design and sustainable product development areas have stressed the need to expand the design space exploration by encompassing value and sustainability-related considerations. A portfolio of methods and tools for decision support regarding value and sustainability integration has been proposed in literature, but very few have seen an integration in engineering practices. This paper proposes an approach, developed and tested in collaboration with an aerospace subsystem manufacturer, featuring the integration of value-driven design and sustainable product development models in the established practices for design space exploration. The proposed approach uses early simulation results as input for value and sustainability models, automatically computing value and sustainability criteria as an integral part of the design space exploration. Machine learning is applied to deal with the different levels of granularity and maturity of information among early simulations, value models, and sustainability models, as well as for the creation of reliable surrogate models for multidimensional design analysis. The paper describes the logic and rationale of the proposed approach and its application to the case of a turbine rear structure for commercial aircraft engines. Finally, the paper discusses the challenges of the approach implementation and highlights relevant research directions across the value-driven design, sustainable product development, and machine learning research fields.

Ecodesign has gained significant traction in recent years ranging from academic research to business applications at a global scale. Initial emphasis on the environmental aspect of design has evolved to include economic and social aspects, with projects ranging from small-scale products to large-scale industrial systems. In this paper, the authors re-analyse 10 of their major ecodesign research projects of the past ten years to identify five categories of challenges and promising future directions for ecodesign research. This paper is primarily a retrospective position paper based on the authors’ experience of actual design studies, providing also a relevant literature review and summary of design practices.