Open Innovation (OI) supports companies in systematically collaborating with external partners, offering various advantages. However, companies still face several challenges when applying OI, e.g., identifying relevant OI partners, collaboration methods, and project risks. Often, insufficient planning is the reason for subsequent deficits in OI projects. The analysis of relevant context factors (‘situation’) is important, which affect and constrain OI. To date, a general approach for analyzing (open) innovation situations or guidelines for developing one do not exist. Usually researchers develop their own situation analysis, including extensive literature reviews and experiencing similar challenges. This publication sets the basis for successfully planning OI projects. It focuses on developing an analysis approach for OI situations and supports other researchers in developing their own analysis approaches. The resultant objectives of the publication are to: (1) provide a list of potential situation analysis criteria; (2) provide a guideline for developing a situation analysis; (3) provide initial indications of relevant OI-specific situation criteria. The criteria were derived from the literature and qualitatively evaluated by three industry partners to assess their usability. Although this work is exploratory, and the results are not automatically generalizable, it is an important contribution for ensuring the success of OI, and for analyzing enablers and barriers to knowledge transfer from academia to industry.

Traditional aerospace design methods offer quick and efficient ways to generate new designs, but such that often resemble previous ones. For truly innovative design, however, a different approach is needed. This paper suggests that a general conceptual design method called ‘parameter analysis’ (PA) may be used for teaching and practicing innovative aerospace design. To support this proposition, we investigate four diverse, innovative and unique case studies, all carried out by very experienced aerospace designers: the ‘dam busting’ bouncing bomb of World War II, the Gossamer Condor human-powered plane of the 1970s, the asymmetric Boomerang twin-engine plane of the 1990s and the SpaceShipOne suborbital spacecraft of the early 2000s. The paper elaborates on how the methodology of case-study research has been adapted and applied to provide the evidence supporting the research hypothesis, and presents the results of analyzing the case studies. It shows that the expert aerospace designers followed a thought process similar to PA, even if unknowingly, where the similarity was measured by counting the number of PA characteristics that could be shown to exist in the case studies. Advantages and limitations of the research methodology are also discussed.

There is a well-developed view of artifacts according to which their nature depends on the intentions of their authors or creators. However, in the modern world of artifact design and creation, typically not one but many agents are involved in the process of making an artifact. In this paper, I show how the intentional view can be maintained even for ‘collective’ artifacts having multiple authors. My approach is to combine some basic concepts that have been proposed in the study of collective intentionality with a suitable model of artifact creation that takes account of the multiple agents and processes that arise in design, engineering and manufacturing a new or existing product. In this way, we can explain how an artifactual kind can be understood via a form of collective intentionality. For the design sciences, notions such as we-intentionality and group agency can help to model different types of cooperation and, in particular, to reconcile individualism with strong forms of collectivity at a group level.

It is often assumed in both education and industry that collaboration encourages creativity. This assumption is explored by investigating the influence of designers’ interactions on creativity-relevant thinking processes by extending creative cognition to the group design context. It is proposed that sharing design entities and questions stimulates creativity-relevant thinking processes through four types of collaborative stimulation. Specific patterns are hypothesized to exist between each type of collaborative stimulation and thinking processes. A case study was conducted to determine whether the hypothesized types and patterns of collaborative stimulation exist. The results were analyzed using a directed coding approach and collaborative retrospective protocol analysis, which enable capturing both internal thoughts and external interactions with minimal interference to collaboration. The results indicate that the identified types of collaborative stimulation are observable and that they have recognizable patterns with stimulated thinking processes. Stimulation occurring through design entity questioning had the strongest relationship with generative thinking processes. Although creativity-relevant generative processes are stimulated by collaborative activity, this does not necessarily mean that collaboration results in a more creative product. However, these patterns can be used in future work to develop methods and interventions for promoting group idea generation and improving group creativity.

Design grammars enable the formal representation of a vocabulary and rules that describe how designs can be synthesized just as the grammar rules of a spoken language define how to formulate valid, i.e., grammatically correct, sentences. Design grammars have been successfully applied in numerous engineering disciplines and enable the automated synthesis of designs within a defined design language. Design grammar development, however, is challenging and lacks methodological support. In this paper, a novel method is presented that supports the development and application of design grammars using transition graphs. In these, nodes represent generated designs and edges represent grammar rules that transform one design into another. Rather than using a tree structure to represent the possible application of rules, transition graphs are automatically generated and used to help designers better understand the developed grammar. The grammar designer is given feedback on (a) the rules, and (b) rule application sequences. This feedback can be used to (a) improve the grammar, and (b) apply it more efficiently. Two case studies, a gearbox synthesis task and a sliding tile puzzle, demonstrate the method. The results show the feasibility of the method to support design grammar development and application.

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.

This paper gives a general and logical analysis of the expert position in design research by which methods for innovative design can be derived from expert design practices. It first gives a framework for characterising accounts of design by the way in which they define and relate general, descriptive and prescribed types of design practices. Second, it analyses with this framework the expert position’s conservatism of prescribing existing expert design practices to non-expert designers. Third, it argues that the expert status of expert designers does not provide sufficient justification for prescribing expert design practices to non-expert designers; it is shown that this justification needs support by empirical testing. Fourth, it discusses validation of design methods for presenting an approach to this testing. One consequence of the need to empirically test the expert position is that its prescription has to be formulated in more detail. Another consequence is that it undermines the expert position since expert design practices are not anymore certain sources for deriving design methods with. Yet it also opens the expert position to other sources for developing design methods for innovation, such as the practices of contemporary designers and the insights of design researchers.

Functional technical performance usually follows an exponential dependence on time but the rate of change (the exponent) varies greatly among technological domains. This paper presents a simple model that provides an explanatory foundation for these phenomena based upon the inventive design process. The model assumes that invention – novel and useful design – arises through probabilistic analogical transfers that combine existing knowledge by combining existing individual operational ideas to arrive at new individual operating ideas. The continuing production of individual operating ideas relies upon injection of new basic individual operating ideas that occurs through coupling of science and technology simulations. The individual operational ideas that result from this process are then modeled as being assimilated in components of artifacts characteristic of a technological domain. According to the model, two effects (differences in interactions among components for different domains and differences in scaling laws for different domains) account for the differences found in improvement rates among domains whereas the analogical transfer process is the source of the exponential behavior. The model is supported by a number of known empirical facts: further empirical research is suggested to independently assess further predictions made by the model.

Designers faced with the task of developing a new product model of a brand must balance several considerations. The design must be novel and express attributes important to the customers, while also recognizable as a representative of the brand. This balancing is left to the intuition of the designers, who must anticipate how customers will perceive the new design. Oftentimes, the design freedom used to meet a product attribute can compromise the recognition of the product as a member of the brand. In this paper, an experiment is conducted for measuring changes in ten styling attributes common to both design freedom and brand recognition for automotive designs from four brands, Audi, BMW, Cadillac, and Lexus, using customer responses to two- and three-dimensional vehicle designs created and presented interactively through a crowdsourced web application. Results show that while brand recognition is highly dependent on the manufacturer, two brands have strong negative relationship between design freedom and brand recognition, suggesting that these two manufacturers face a significant challenge when evolving their respective brand styling. This study is a first effort toward quantifying and predicting tradeoffs between design freedom and brand recognition, contributing to existing efforts that augment human intuition during strategic design decisions.

Inspiration is a widely recognized phenomenon in everyday life. However, researchers still know very little about what the process of inspiration entails. This paper investigates designers’ approaches when selecting inspirational stimuli during the initial phases of a design process. We conducted a think-aloud protocol study and interviews with 31 design Masters students while generating ideas for a design problem. The results indicate that searching for and selecting stimuli require different levels of cognitive effort, depending on whether there is unlimited or limited access to stimuli. Furthermore, three important stages of the inspiration process were identified: keyword definition, stimuli search and stimuli selection. For each of these stages, we elaborate on how designers define keywords, which search approaches they use and what drives their selection of stimuli. This paper contributes to an understanding of how designers can be supported in their inspiration process in a more detailed manner.

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.

Although nanoparticles have been shown to have clear technological advantages, their use in some consumer products remains controversial, particularly where these products come in direct contact with our bodies. There has been much discussion about using metal oxide nanoparticles in sunscreens, and numerous technology assessments aimed at predicting the type, size and concentration of nanoparticles and surface treatments that will be best for consumers. Yet, the optimal configuration is ultimately the one that people actually want and are willing to pay for, but until now consumer preferences have not been included in model predictions. We describe and discuss a proof of concept study in which we design and implement a hypothetical sunscreen product configurator to predict how people tradeoff sun protection factor (SPF), product transparency and potential toxicity from reactive oxygen species (ROS) in configuring their most preferred sunscreen. We also show that preferred nanoparticle sizes and concentrations vary across demographic groups. Our results suggest that while consumers choose to reduce or eliminate potential toxicity when possible, they do not automatically sacrifice high SPF and product transparency to avoid the possibility of toxicity from ROS. We discuss some advantages of using product configurators to study potential product designs and suggest some future research possibilities.

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.