Materials experience in design involves the meanings that materials convey to users through its expressive characteristics. Such meaning evoking patterns are influenced by parameters such as context, product (e.g.shape) and user. Consequently, there is a need to standardise experiential material characterisation and large-scale data collection, by means of a meaning-less or ‘neutral’ demonstrator to objectively compare materials.

This paper explores the conception of this neutrality and proposes two opposing strategies: neutrality through complexity or through simplicity. In a pre-study with 20 designers, six associative pairs are selected as neutrality criteria, and shaped in 240 forms by 20 (non) designers in a main workshop. Following the simplicity strategy, these forms are averaged out in three steps by a team of five designers, based on a consensus on of delicate-rugged, aggressive-calm, futuristic-calm, masculine-feminine, traditional-modern, and toylike-professional, resulting in a selection of four averaged neutral forms.

Finally, future research will focus on complexity to increase interactivity, so that consumers might be triggered in extensive material exploration.

Previous research has shown the importance of contextual factors for increasing employee innovativeness, but to effectively support innovative behavior, we need to also understand what forms of support are perceived as meaningful by the employees themselves. The current study investigated the experiences of 35 early-career engineers in creating, championing and implementing new ideas at the workplace. They reported relatively few instances of support that had been experienced as helpful, and nearly all of these were related to either managerial or co-worker support. This support ranged from encouragement and positive feedback to tangible help in troubleshooting and finding resources, and, in the case of managers, providing sufficient autonomy and responsibility to enable the interviewees to pursue their ideas. Managerial support was most frequently reported by those working in self-described innovative positions, whereas co-worker support was more commonly reported by those working in self- described innovative environments. Formal processes and incentives were less likely to have been perceived as helpful than informal interactions with managers and co-workers.

Visual stimuli can be useful in supporting design ideation process. However, researchers still know very little about how stimuli should be delivered to designers during the early design stage. This question is crucial to the effective use of stimuli because previous researches have proved that ill-presented stimuli can have a negative impact on design creativity. Therefore, an empirical study was conducted with the aim of exploring if and how combinational pictorial stimuli can affect designers' creative performance. Results from a total of 36 participants show that the design outcomes presented by the group exposed to combinational pictorial stimuli were more creative than those given by the group exposed to no stimuli or randomly presented pictorial stimuli. These results imply that the form of stimuli delivery can affect creative design outcomes and combinational pictorial stimuli best support design creativity among these three conditions. These findings give us a better understanding of the roles that visual stimuli play in design, which is expected to bring us important implications for both design education and design support tool development

With the surging number of digital devices penetrating our daily routines, the risks inherent to cybersecurity—the protection of data on digital products connected to the Internet—have also increased since these devices (e.g., connected home devices, personal monitoring) collect, process, analyze and store users’ sensitive personal information. Thus, there is a pressing need to assist users in being aware of and dealing with potential cybersecurity threats. With the proposition that fulfilling the need starts with developing an in-depth understanding of the user behaviors in the context of cybersecurity, an exploratory study was conducted that employed three mixed qualitative and quantitative research methods—a trend analysis, an interview study, and an online survey study. The paper reports the user characteristics on (1) awareness levels of cybersecurity issues, (2) uses of digital devices, and (3) means of dealing with the privacy issues in product use. The results of the studies were translated into eight personas that systematically reflect distinct characteristics of users, which can help designers empathize with their potential users vulnerable to cybersecurity risks.

Information collection may affect the design quality and designer's performance through changing the structure of information and the way how information is searched and organized. Based on the theoretical analysis conducted by Wang et al., the present work continues to investigate the influence of designer's natural choice of information collection strategy on his/her mental stress both theoretically and empirically. Designers’ stresses are quantified from HRV data and are compared under different information collection strategies.

Information usage is a key aspect of creative cognition and has been shown to influence design outcomes. The goal of this study was to investigate the information seeking behavior of student designers while validating a previously developed “Typology of Design Information” framework. Participants were asked to use and evaluate pieces of information during the idea generation process. Results show a discrepancy between the information that participants naturally sought out and their perceived utility (helpfulness) of the information. However, individually significant relationships between perceived utility and behavior were found with features generated by participants, suggesting that even though participants' perception of the utility of information pieces and their actual behavior are not related, both constructs have an identifiable influence on design outcomes. This study advances the Typology of Design Information framework by empirically exploring the link between the types of information used by novice designers and the ideas generated, and it illustrates that participants employ complex cognitive behavior when engaging with design information to generate novel ideas.

Automotive systems are changing rapidly from purely mechanical to smart, programmable assistants. These systems react and respond to the driving environment and communicate with other subsystems for better driver support and safety. However, instead of supporting, the complexity of such systems can result in a stressful experience for the driver, adding to the workload. Hence, a poorly designed system, from a usability and user experience perspective, can lead to reduced usage or even ignorance of the provided functionalities, especially concerning Adaptive Driver Assistance Systems.

In this paper, the authors propose a combined design approach for user behavior evaluation of such systems. At the core of the design is a mixed methods approach, where objective data, which is automatically collected in vehicles, is augmented with subjective data, which is gathered through in- depth interviews with end-users. The aim of the proposed methodology design is to improve current practices on user behavior evaluation, achieve a deeper understanding of driver's behavior, and improve the validity and rigor of the named results.

This paper aims to provide suggestions for the identification of potential new applications for the existing knowledge. A method is presented for extracting information about a product or technology, processing the international patent database (IPD) and extracting useful hints for potential new applications. The approach uses the Cooperative Patent Classification as stimulus for inspiring new potential fields towards which export existing product or technologies. Although some limits inevitably affect the approach, relevant directions for future developments have been inferred for a more comprehensive exploitation of both the firm internal knowledge and the suggestions provided by the international patent database. The achieved results can support firms in expanding market opportunities for their products or technologies.

To objectively and quantitatively study transcribed protocols of design problem solving conversations, we propose a semantic analysis approach based on dynamic semantic networks of nouns constructed with WordNet 3.1 lexical database. We examined the applicability of the semantic approach focused on a dynamic evaluation of the design problem solving process in educational settings. Using a case of real- world design problem-solving conversations, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy or information content, and quantify convergence/divergence of semantic similarity in design conversations between students, instructors and real clients. The approach can also be used to evaluate the aforementioned semantic factors for successful and unsuccessful ideas generated in the process of design problem solving, or to assess the effect of external feedback on the developed design solution. The proposed semantic analysis approach allows fast computation of the semantic factors in real time thereby demavonstrating a potential for both monitoring and support of the design problem solving process.

Techniques and processes used for concept generation rely on composing new concepts and analysis given situational context. Composition and analysis require distinct neurocognitive function. For instance, jazz composition relies heavily on the right brain, while math relies on the left. Similar to music and math, is concept generation hemisphere dominant? What differences exist when using varying techniques? Twelve graduate engineering students were given three design tasks and instructed to use brainstorming, morphological analysis and TRIZ. A device called fNIRS measured cognitive activation. The results find left hemisphere dominance. More specifically, the left dorsolateral PFC (dlPFC), which is central to spatial working memory and filtering information. Temporal differences do exist. Morphological analysis and TRIZ reinforced the use of the left dlPFC, while brainstorming increased the use of the right dlPFC and medial PFC (mPFC) late during concept generation. The right dlPFC contributes to divergent thinking and mPFC facilitates memory retrieval. One explanation is designers relaxed rule constraints and more deeply searched for associations during brainstorming.

In the uncertain process of product development, the developer is decisively responsible for product success. He operates in a complex environment that directly influences his synthesis and analysis activities. The context of the socio-technical system of product development has already been extensively researched and defined by a large number of factors. However, the developer is described as part of the context and not as the centre, which means that many of these factors have no interaction with the developer. For the design of methods and tools that support the developer in his activities in the development process, a summarizing understanding of the influences on and by the developer is necessary. In order to create a unified understanding of the developer at the centre of product development, a Systematic Literature Review was conducted. In this article, the procedure and findings are presented. The aim was to identify factors from the literature that significantly influence the interaction of the developer in his environment. As a result, these were documented in a model, which represents the basis for further, human-centred research in the context of product development.

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power.

Behavioural design is a crucial research area due to its potential in leveraging the positive outcomes of traditional design. Current need for theory building requires discerning the unique characteristics and challenges of behavioural design. To contribute towards this goal, the paper structures the conceptual and operational uniqueness of the behavioural design using the process and cognitive perspective. Process model uses the basic design cycle to discern the tasks and stages of behavioural design. Cognitive perspective uses dual process theory and cognitive strategies used by designers. Integrated model of process and cognitive perspective is the crucial contribution of this paper. A case study involving interview of lead designers from five behavioural design consultancies has been used to present and elaborate the usefulness of the integrated model of behavioural design. Integrated perspective links the process characters like incomplete analysis, simulation and evaluation stages, over reliance on the prescriptive methods, and unequal emphasis to multiple disciplines, with incomplete analytical process, and solution and knowledge driven strategy along cognitive perspective

Recently, design researchers have begun to use neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) to understand a variety of cognitive processes relevant to design. However, common neuroimaging analysis techniques require significant assumptions relating temporal and spatial information during model formulation. In this work, we apply hidden Markov Models (HMM) in order to uncover patterns of brain activation in a design-relevant fMRI dataset. The underlying fMRI data comes from a prior research study in which participants generated solutions for twelve open-ended design problems from the literature. HMMs are generative models that are able to automatically infer the internal state characteristics of a process by observing state emissions. In this work, we demonstrate that distinct states can be extracted from the design ideation fMRI dataset, and that designers are likely to transition between a few key states. Additionally, the likelihood of occupancy within these states is different for high and low performing designers. This work opens up the door for future research to investigate the patterns of neural activation within the discovered states.