Priming on Sustainable Design Idea Creation and Evaluation

Abstract

Although three pillars of sustainable design—social desirability, economic competitiveness, and environmental friendliness—are all important, they are not necessarily equally accessible or salient during the design process. This paper applies a collage priming method to activate designers’ mindsets regarding sustainability pillars prior to conceptual design exercises, and to facilitate early-stage sustainable design. The study tests if collage priming (1) improves ideation outcome in terms of the sustainability pillars, interpreted as user desirability, cost, and environmental impact, and (2) encourages designers to further explore others’ ideas during idea evaluation. For (1), collage priming related to environmental aspect is shown to assist designers with generating more relevant ideas regarding environmental impact and more feasible ideas as compared to the control. The priming is not effective in helping designers generate ideas related to user desirability or cost, potentially because designers lack readily accessible information to be activated by priming. For (2), the collage priming related to user desirability is shown to encourage further exploration when exposed to (simulated) others’ ideas. The study shows the effectiveness of collage priming in improving environmental impact in conceptual design; it also demonstrates the existing challenges of addressing user desirability and cost.

1. Introduction

A sustainable product involves three different pillars—social desirability, economic competitiveness, and environmental friendliness [1]. Therefore, it is valuable to understand how to enhance a designer’s ability to design for all three pillars. Before discussing priming, a process meant to enhance a designer’s abilities, we first describe how we interpret the meaning of each sustainability pillar related to a product’s design.

The social desirability pillar is the most difficult to investigate because it focuses on how a product affects the well-being of a community, including human equality, social justice, and people’s happiness [2,3]. Because of this difficulty, this study focuses only on determining the social effect a product has on the user’s day-to-day quality of life [4]. We further modify the description of this effect as a tangible social characteristic of the product, namely, user desirability, with the understanding that the social pillar has been significantly reduced to “user desirability.” We choose user desirability, related to the user’s quality of life, because it is more-readily mentally accessible to engineering designers and it is one of the concepts encompassed within the social pillar. Further focusing on user desirability would presumably generate interesting and creative design ideas that appeal to customers and can be included in later rating exercises in a balanced way with ideas related to economic competitiveness and environmental friendliness—two pillars that are much more specifically defined.

Similarly, the pillar of economic competitiveness is narrowed down as cost of a product, to be suitable for conceptual design, while acknowledging the sophisticated nature of economic sustainability, especially under the influence of globalization; we interpret the pillar of environmental friendliness as environmental impact.

This study focuses on understanding how to influence a designer’s mindset to better design all aspects related to sustainability. It looks at the conceptual design stage and the process of priming—a psychological technique that aims to affect performance via exposure to a stimulus that activates a particular idea, contextualization, or feeling [5]. Priming alters a designer’s mindset by bringing background knowledge into the foreground so that it increases cognitive accessibility of mental content [6]. For example, experimental psychologists found that people are able to overcome automatic stereotypes when primed to think three situations in which they have to behave creatively [7].

The psychological mechanism of priming is rooted in the concept of “perceptual readiness” proposed by Bruner [8], which claims that the information and feelings that are currently cognitively accessible lead to corresponding thoughts and behavior. Priming, which activates a specific set of information and/or feelings in the brain, increases the accessibility of thoughts, memories, and feelings associated with this activation and thus motivates related perspectives, decisions, and behavior [9,10]. In this study, priming is considered as a subconscious process and is distinguished from directly, consciously engaging a topic, such as reading an article about environmental design [11].

She and MacDonald [9] found that the collage priming method—where participants physically handle images of products to create a paper picture collage—enhances student engineers’ abilities to generate features that communicate environmental friendliness to users. This collage priming method was developed based on the work of Guyton, who demonstrated the collage activity as an effective approach to establish product semantics for sustainable products and to inspire sustainability concerns [12]. Subsequent testing of prototypes built to include the best of the feature brainstorming with this method demonstrated that potential customers increase their consideration of sustainability during hypothetical purchase decisions [13]. Thus, the collage priming method, with respect to designing that improves communication of sustainability, is validated to be effective.

Here, the study tests to see if the collage priming method, adapted from [9], could effectively improve ideation outcome in terms of user desirability, cost, and environmental impact, as design aspects derived from three pillars of sustainability. Since the study focuses on early-stage design of sustainable products, the ideation outcome is evaluated based on design effort rather than the actual energy or cost savings of the existing products. The study also examines if performing the collage priming task could better prepare designers for the next step of the design process in a collaborative environment, namely, idea evaluation, as priming has been known to affect decision-making [14]. While we are not able to fully investigate this question, we focus on how designers, with and without collage priming, judge their own ideas during a mock-up of an idea selection process.

Designers may conduct non-normative behaviors due to different cognitive biases, such as design fixation, confirmation bias, and self-favoring. These behaviors can affect designers’ objectivity during idea selection and can ultimately affect the final product design [15]. In this study, we suspect that activating specific mindset by priming could shift designers’ attention away from the design that they naturally prefer or are already familiar with to encourage a more open attitude to innovative solutions. To measure change in attitude, we measure designers’ tendency to prefer one’s own ideas over the others’ ideas in a simulated collaborative environment and test if priming cultivates a tendency to explore others’ ideas during idea evaluation in engineering design.

This study focuses on engineering designers (referred to as “designers” for the rest of this paper), who are expected to have fundamental knowledge of manufacturing processes, cost analyses, and the environmental impact of the products. We ask: (1) does the collage priming activity improve outcomes in terms of user desirability, cost, and environmental impact relating to three sustainability pillars, as judged by experts? and (2) does the collage priming activity cultivate a more receptive attitude of designers towards others’ ideas?

In this study, designers were divided into five testing conditions, and in each condition, designers were exposed to one of the stimuli (or no stimuli) illustrated in Figure 1:

(A1) A priming stimulus of a collage activity for user desirability

(A2) A priming stimulus of a collage activity for cost

(A3) A priming stimulus of a collage activity for environmental impact

(B) A reading activity that directly engaged the participants on the environmental impact or

(C) No stimuli or activity.

The designers, working alone, generated ideas for washing machines and then made judgments about their ideas and the ideas of other designers (which were simulated). Then, two expert judges, who had experience in sustainable design, rated all ideas generated by designers. We analyzed all results to test the ability of the priming activities to increase relevance of the design ideas regarding the targeted aspects, to improve the originality and feasibility of ideas and to cultivate changes in attitude during idea evaluation.

This paper is organized as follows: Section 2 provides a brief review of sustainable design (Section 2.1), priming techniques (Section 2.2), and the phenomenon and causes of cognitive bias in concept evaluation (Section 2.3). Section 2.3 particularly provides background that leads to the Proposition 2. Section 3 lists our propositions and hypotheses. Section 4 gives an overview of the experiment, while Section 5 is an explanation of how we prepared the experiment. Section 6 is a detailed description of the experiment. The analysis and discussion sections are split into two parts corresponding to two propositions: Section 7 and Section 8 provide the analysis and discussion of Proposition 1, and Section 9 and Section 10 provide the analysis and discussion of Proposition 2. Finally, Section 11 provides the conclusion and a description of future work.

2. Background

2.1. Sustainable Design and Framing of Sustainability

To create more sustainable products and processes, researchers have investigated novel design tools, methods, and models to guide industry and business [9,16,17]. Researchers commonly refer to eco-design as a process of improving product development to reduce environmental load [18]. With a goal of minimizing overall resource consumption, the eco-design process focuses on the whole life cycle of products from extraction of raw materials to final disposal [19,20]. This life-cycle approach has been supported by various objective tools, such as life cycle assessment [16,21], the House of Ecology [21], and quality function deployment [21]. These tools help quantify environmental impacts, enable comparison between multiple design solutions within the same product category, and therefore facilitate design decision making [22]. Researchers have also developed strategic methods to integrate environmental requirements into the product design process, like sustainable product and service development [17], information/inspiration framework [23], and environmental performance strategy map [24]. Beyond the design process, successful development of sustainable products requires integrating sustainability and supply chain management and understanding drivers of supplier environmental performance from the management level [25].

During the sustainable design process, especially for eco-design with a focus on product life cycle, designers sometimes equate “environmentally friendly” products with a sustainable product [20,26]. This is likely due, in part, to their training in engineering, particularly in subjects such as material selection and energy usage. They may also be influenced by users’ familiarity with environmental friendliness [17,27] but lack of familiarity with the broader definition of sustainability. In addition, researchers have developed many metrics to quantify environmental friendliness [9], while the tools to quantify the social impact of a product are either nonexistent or noncomparable across all products in an industry. According to Pack et al. [4], designing products from a social well-being perspective is an emerging topic in academic research, but designers in industry appear to lack the necessary tools to quantify the level of social impact of a given product.

The social pillar of sustainability is malleable in its meaning. For example, Cuthill [2] states that it involves social policy and community development, while Littig and Griessler [3] describe it as “a quality of societies that satisfies an extended set of human needs.” This study focuses on consumer products for the United States. Therefore, social pillar definition(s) that relate more to the developing world may not apply. Although a product such as a washing machine does have a societal impact, the U.S. is equipped to handle many problems with a well-developed community system, such as a sewer system to process dirty water and an electrical grid to allow for variable electricity usage. In this study, the social pillar of sustainability is interpreted at the product-use level and for the individual user, namely, the user desirability of the product. The term user desirability refers the requirement clusters of understanding users, needs, and desires when addressing social issues [20,28]. An environmentally friendly product does not benefit the environment if no user adopts it, and in order to successfully realize the product’s environmental impact, user desires need to be satisfied.

The economic pillar of sustainability has been defined as “cost of supply chain” [29]. Since this study focuses on early-stage design, the full concerns of economic sustainability are too broad for a designer to consider in a single ideation session. Since the economic evaluation is usually considering manufacturing costs (from a business perspective) and life cycle costs (from the customer’s perspective) [30], cost is chosen to represent the economic pillar for this experiment (later broken down into manufacturing cost and use cost for rating purpose). While acknowledging the importance of calculating life-cycle cost and other metrics such as customer value ratio [31], the ideation sessions mainly produce underdeveloped ideas, which cannot be accurately assessed in terms of life-cycle cost.

2.2. Priming Techniques

Psychological priming is a robust method used extensively in psychology, behavioral economics, and organizational behavior to activate specific mindsets, thereby making relevant knowledge more accessible to participants [9,32]. Empirical studies show that stimuli are perceived even when observers are unaware of the stimuli, and this subconscious perception can influence a response to a subsequent activity without conscious guidance or intention [33]. Priming can be thought of as drawing from implicit memory and refers to changes in performance or behavior due to prior experience without intentional recollection of these experiences, whereas explicit memory refers to intentional recollection of prior experience [34]. Priming facilitates perception of objects from cues as a consequence of stimuli [35], and it can occur independently of any conscious recollection of previous experience with a stimulus [35]. Based on the theory of implicit memory, information about a recently encountered object that supports priming is quite different than information acquired from learning a skill [34]. Priming is used by language researchers to understand how words and concepts are retrieved, when knowledge is modeled as a “network” in the brain, and the theory is known as spreading activation theory. Spreading activation also employs the theory of implicit memory [36]. Priming sparks thoughts about related concepts to a central concept, and this neural process aids in generating creative or unanticipated ideas and thoughts.

Priming has been shown to affect purchase decisions [32], increase awareness of a social problem, or change behavior [37]. Priming has inspired sustainability concerns [9,12], pro-social behavior [38,39], rudeness toward the experimenter [10], mimicking of advanced age [10], competitiveness and selfishness [40], and overcoming of racial stereotypes [7]. Various mental and physical activities are used as a priming method, including unscrambling words [41], placing objects [42], creating sensory collages [9,12], simulating a user scenario [10], writing stories [41,42,43], answering questions [10], and playing games [29]. The priming method functions without the awareness or intent of the individual and its effect can last up to 24 h or more [44]. Priming also works in real-world situations. For example, voters whose polling places are located in schools are more likely to support educational propositions on the ballot; this is known as contextual priming [45].

Priming is specifically used in design ideation to improve quality and creativity. Participants who were primed by unscrambling sentences containing harsh words drew more hostile features, such as spikes and claws, in their sketches of hypothetical aliens [41]; participants who answered questions about nutrition habits showed improved productivity and quality of ideas on how to improve health [43]; participants who received positive affective priming—for example, being shown a picture of a laughing baby—generated higher-quality ideas in an alternative uses task [46]; participants who mimicked limited mobility, by wearing gloves, showed more empathy for elderly users, showed more originality in their concepts, and had less design fixation [10]; and participants who received counterfactual priming—that is, they considered events that happened as well as events that almost happened—performed better on the Duncker candle problem (a problem-solving test involving a candle, matches, and box of thumbtacks) by triggering more alternative-use ideas for the given supplies [47].

2.3. Cognitive Bias in Idea Evaluation

Beyond design ideation, idea evaluation or selection is another crucial step in engineering design in a collaborative environment, and a wide set of alternatives are usually reviewed and evaluated by a team of designers [47]. This activity can have a significant impact on the success of the design process [48]. Designers, like anyone else, can be susceptible to non-normative behavior, such as design fixation, anchoring, and confirmation bias [49]. For example, designers tend to fixate on designs similar to the examples presented [50] and to employ a familiar method ignoring better ones, when a considerable number of resources are invested [51].

Confirmation bias, a prevalent cognitive bias, involves a tendency to attend more acutely to information that validates beliefs than to information that invalidates them. One explanation of why it prevails is that humans have an innate desire to conserve cognitive effort and rely on the most available information in memory when making judgements [52,53]. While confirmation bias does not systematically lead to poor design outcomes, it potentially causes deviations from normative decision-making process [54]. Similarly, familiarity bias, or the familiarity heuristic, happens when individuals favor places, people, or things that they have interacted with before over novel ones, especially if they are experiencing a high cognitive load [55]. The familiarity heuristic can encourage customers to stay loyal with a familiar product or brand; it may undermine designers’ abilities to generate innovate solutions [56].

Another non-normative behavior that potentially harms the ultimate design outcome is self-favoring. It is not surprising that designers, like most humans, strive for favorable self-presentation [57]. Behavioral economists found that the feeling of self-favoring originates from the appreciation of solutions developed by individuals [58] and from designers’ perception of themselves [59,60]. Thus, the bias can be intrinsic in personality traits [60]. But this tendency to favor one’s own presentation potentially introduces partiality to the decision-making process, and it challenges team collaboration. To facilitate the idea selection process and eliminate such bias, many systematic selection methods have been developed, such as the analytic hierarchy process (AHP) [41] and the Pugh method [61]. However, many designers still prefer informal selection methods to screen a myriad of early-stage ideas [62].

Cognitive connections that are created by priming stimuli may operate at automatic levels [63] and could result in an “implicit cognitive bias”, as some research refers to it. Since both cognitive bias and priming can be thought of as types of biases, there is likely an interchange between them. That is, when a designer’s thoughts are activated through priming to think from a different perspective, those thoughts may drift away from the designer’s natural tendency toward a particular judgment structure, which would include favoring their own ideas. Because automatic and controlled systems interplay in decision-making, we suspect that activating particular mindset of designers via priming may also decrease cognitive bias such as self-favoring and may encourage receptive attitude when evaluating ideas.

In the existing literature, the evaluative bias is commonly measured in a pair or a team. For example, to measure the bias due to self-favoring, a designer evaluates the self-initiated design ideas along with design ideas generated by others [49]. The bias is confirmed if the design idea is rated higher or more likely to be chosen for further development by the designer who generates it than by the other designers in the team. In this study, we did not include a team discussion during the idea evaluation or a comparison between designers who own the idea or not, to avoid the influence of team dynamics. Instead, we focused on designers’ tendency to prefer one’s own ideas over the ideas of others in a simulated collaborative environment. We tested if priming cultivates a receptive attitude during idea selection in engineering design.

3. Research Propositions and Hypotheses

Proposition 1:

The collage priming activity can promote sustainability of the ideas generated by designers in terms of user desirability, manufacturing cost, use cost, and environmental impact.

To determine if priming successfully activates one of these mindsets/perspectives, we compare how relevant the design intentions are regarding the sustainability-related aspects from the primed conditions with that of a control group, and of a group engaged in a reading activity (a conscious engagement with the topic of environmental impact) judged by experts. We hypothesize:

Hypothesis 1a (H1a):

Priming for user desirability results in more relevant ideas generated by designers when judged on user desirability than those generated by the control condition.

Hypothesis 1b (H1b):

Priming for cost results in more relevant ideas generated by designers when judged on manufacturing cost than those generated by the control condition.

Hypothesis 1c (H1c):

Priming for cost results in more relevant ideas generated by designers when judged on use cost than those generated by the control condition.

Hypothesis 1d (H1d):

Priming for environmental impact results in more relevant ideas generated by designers when judged on environmental impact than those generated by the control condition.

The collage priming activity that focuses on one of three sustainability-related aspects can improve ideation outcome in general by increasing the originality and feasibility. We hypothesize:

Hypothesis 1e (H1e):

Priming of any sustainability-related aspect results in higher originality of the ideas, when judged by experts than ideas generated by the control group.

Hypothesis 1f (H1f):

Priming of any sustainability-related aspect results in higher feasibility of the ideas, when judged by experts than ideas generated by the control group.

Proposition 2:

Engaging in a priming activity that relates to a sustainability pillar makes designers more receptive to ideas of others.

Priming makes latent information related to stimuli more accessible, not only improving the designer’s design ability in an active way but also potentially changing the designer’s attitude toward the targeted perspective and goals of the design process. We investigate if designers being primed are more likely to embrace the ideas generated by hypothetical others when evaluating a mixed set of ideas that includes their own ideas.

Hypothesis 2 (H2):

Engaging in a collage-priming activity that focuses on a sustainability-related aspect decreases a designer’s interest in exploring their own ideas when exposed to ideas generated by hypothetical others, compared to the control group.

4. Method and Experiment Overview

This section provides the overview of the research method and highlights of the experiment; more details are provided in the following sections. This study uses a test-versus-control experiment to test the hypotheses of Section 3. The testing variable is the pre-ideation activity (collage priming vs. reading vs. no activity), and the study collects data of ideation outcome in terms of designers’ text input and data of idea evaluation as classifications. Participants were recruited at the 2016 International Design and Technical Conference via a recruiting e-mail to the engineering design community and on Stanford University campus via a graduate student mailing list in the mechanical engineering department. The experiment was administered on iPad using Qualtrics, a survey platform. The ideation outcome and idea evaluation were compared between testing conditions to investigate if there was any effect of collage priming or reading compared to no activity. The experiment procedure is described with details in Section 6.

Figure 1 shows the five conditions: user desirability prime (A1), cost prime (A2), environmental prime (A3), reading activity (B); and control (C) (no priming nor reading activity). Figure 2 gives an overview of the experiment’s six major steps. All activities were performed alone in each condition. The collage priming activity (pre-ideation activity) involved assessing coffee cups. The main design task of the two ideation steps was to design a washing machine. The rationale for choosing coffee cups and washing machines is provided in Section 5.1.1 and Section 5.3.

Part 1 of the experiment consists of four steps:

• Pre-ideation Activity: Participants in conditions A1, A2, and A3 did the collage priming activity, and participants in condition B did the reading activity. Those in the control condition began in the next step, “Ideation 1.” The collage and reading activities are described in Section 5.1 and Section 5.2.
• Ideation 1: Participants generated design solutions for a washing machine.
• Video Watching: Participants watched a montage of videos that highlighted the sustainability aspects (user desirability, manufacturing, and environmental friendliness) of washing machines. This step was included to further stimulate design ideas, as described in Section 5.4.
• Ideation 2: Participants generated design solutions again for the same product.

Part 2 of the experiment consists of two steps:

• Idea Evaluation: Participants first evaluated a set of their own design ideas, classifying how interested they were in exploring each idea further. Then, they evaluated a mixed set of ideas, which included the same set of their ideas and a number of predetermined, sustainability-related ideas, presented as coming from other designers. The selection of those ideas and more details are described in Section 5.5. (Note that participants did not rate the relevance of design ideas regarding sustainability; this was performed later by expert judges.)
• Questionnaire: All participants filled out a questionnaire about their demographics, knowledge of sustainable design, and awareness of characteristics in sustainable design.

5. Activity and Stimuli Preparation and Description

5.1. Collage Priming Activity

In this activity, participants rated their preference for various types of coffee cups by creating a collage. First, they physically placed product images on a piece of butcher paper that already had a set of labeled axes drawn on it, as illustrated in Figure 3. Second, participants described their selections by choosing words from a list provided and writing these words next to the product images. Each word had to be used at least once, and each cup had to be described by using at least one word.

Two aspects of the activity created the priming condition: (1) the y-axis directly related to the aspect of sustainability that was being primed; for the user desirability prime, axis-labels “boring” to “delightful” were used; for the cost prime, “inexpensive to make” to “expensive to make” were used; and for the environmental prime, the labels were “low environmental impact” to “high environmental impact.” (2) Descriptive words were chosen based on the strength of each word’s association with the concepts “social,” “economic”, and “environmental” (these associations are described further in Section 5.1. (3) An example of a completed collage is shown in Figure 4.

5.1.1. Selecting of Products

It was important that the collage priming activity in pre-ideation did not include the same product as in the ideation steps. In other words, participants had to be primed using a different product than the one they designed to ensure that it was the priming that caused any effects we saw in the ideation steps, and not, for example, the process of assessing and comparing a variety of washing machines (the focal product of the design exercises).

After pilot-testing various options, we chose coffee cups as the product category for collage priming because coffee cups are a common product that most people are familiar with; they represent a large variety of appearances, prices, and materials, which demonstrate different levels of user desirability, cost, and environmental impact; and they incorporate social elements because coffee is a part of many social experiences. Coffee cups are also very different from washing machines, the product in the main design task. We considered and tested other product categories, such as transportation (planes, cars), but post-pilot-test interviews showed that cost and environmental impact but not “user desirability,” were driving assessments, even in the user desirability prime.

5.1.2. Selection of Axes Labels

All three collage activities used the same x-axis labels (“like”/“dislike”) so that participants could cognitively load as much as they wanted on it (e.g., opinion, features, aesthetics). The y-axis labels varied according to the priming conditions (shown in

Table 1. Axes labels and descriptive words for the collage priming activity.

	User Desirability	Cost	Environmental
Horizontal axis labels	Dislike/Like	Dislike/like	Dislike/Like
Vertical axis labels	Boring/ Delightful	Inexpensive/ Expensive to make	Low/High environmental impact
Collage words	Sociable	Affordable	Recyclable
	Friendly	Budget	Natural
	Warm	Cheap	Efficient
	Helpful	Economical	Organic
	Ergonomic	Bargain	Conserving
	Modern	Valuable	Polluting
	Unfriendly	Inexpensive	Disposable
	Useless	Indulgent	Synthetic
	Useful	Overpriced	Inefficient
	Solitary	Expensive	Wasteful
	Playful	Rich	Reusable
	Stylish	Costly	Consumable

).

5.1.3. Selection of Descriptive Words

To determine the list of descriptive words, we conducted a pilot study in which graduate students at Stanford University first generated words related to product design by consulting design documents and thesauri. Then they sorted the words into four categories (social, economic, environmental, and other) and rated the strength of a word’s association with that concept. The 12 highest-rated words were selected in each category for the lists (Table 1). These words were provided in the collage priming activity to activate the designer’s mindset of sustainability. In pilot testing, students who were prompted to generate “economic” words produced fewer ideas than other students. The words for the cost prime could have stifled ideation if they focused too much on the negative consequences of spending money; therefore, we re-evaluated this list to make sure none of the words were too negative.

5.2. Reading Activity

In the previous work, collage priming method was validated as an effective method to enhance student engineers’ abilities to communicate environmental friendliness to the user [9]. We included an additional condition of reading activity to extend the existing work and to examine the effect of a conscious (reading) activity. Participants assigned to condition B did not engage in the collage priming activity but instead read a document about eco-design drawn from the educational materials of the Sustainable Minds website [64], with edits. The material focuses mostly on the environmental aspect of sustainability. Our goal is to compare the effectiveness of the reading activity (B) with the environmental prime (A3), to see if directly engaging with a conscious, educational activity (which is distinguished from priming in this study) is more effective than subconsciously activating a certain mindset (priming). We performed two comparisons between each activity (collage prime activity or reading activity) and the control, and a comparison between collage priming (A3) and reading (B).

5.3. Design Ideation

In this activity, all participants were prompted to generate ideas for a next-generation sustainable washing machine within a given time. We chose washing machines because they were common consumer products that are familiar to most designers and students in the U.S. Washing machines had much room for improvement in user desirability, cost, and environmental impact.

The prompt given to the designers was

Imagine that you are working on a product design team at Smithfield Appliances, and you have been asked to design the next generation of sustainable washing machine. Product ideas may be related to reducing water and energy usage, improving manufacturing, and increasing the product’s appeal to users. Generate ideas that address this design challenge. You may use scratch paper if necessary but please type all individual ideas in the boxes below. You do not have to fill in all of the boxes. You will have 8 min to complete this task.

We included explicit ideas, e.g., reducing water, to help trigger participants’ thoughts of sustainability because a previous study showed that participants performed much better in terms of number of ideas generated, after more explicit design directions were provided [9].

5.4. Video Montage

In between Ideation 1 and Ideation 2, all participants watched a montage of videos (available at https://youtu.be/7RKSZxOv2g4, accessed on 1 August 2018) for 10.5 min. The videos address, in a balanced way, topics of user desirability (a video describing a sleek, modern, Samsung washing machine with extensive user-centered features; approximately 4 min), environmental impact (two news segments on highly environmentally friendly washing machines; approximately 2.5 min), and manufacturing (a segment from the television show “How It’s Made” on front-loading washing machines; approximately 4 min). We added this video montage in response to pilot testing, which showed that participants needed more inspiration to generate an analyzable number of ideas. Pilot testing honed the montage for balance of ideas and demonstrated that watching it increased the number of ideas generated in Ideation 2. All participants saw the same videos. It is possible that the collage priming activity enhanced the effect of the video, allowing primed participants to obtain more information from the video than non-primed participants, but this was difficult to test specifically.

5.5. Idea Evaluation

This activity occurred after Ideation 2, in Part 2 of the experiment, and its purpose was to see if priming encouraged participants to further explore others’ ideas, as articulated in Proposition 2 in Section 3. To design the evaluation activity, we consulted with an expert on team behavior. First, the activity created an anchor by asking participants to evaluate five of their own ideas (randomly drawn from their previous answers using a JavaScript in Qualtrics). They classified each idea into one of three categories/boxes: “definitely want to explore,” “possibly want to explore,” and “do not want to explore”, as shown in Figure 5. On the next screen, the participants saw these 5 ideas again, now randomly interspersed among 12 other ideas, preselected by us from hypothetical other designers, for a total of 17 ideas. All participants saw the same 12 additional ideas, which represented varying sustainability-related aspects (user desirability, cost, and environmental impact) and quality characteristics (originality and feasibility). The participants classified all 17 ideas using the same categories as before. The analysis in Section 9 tests if participants demoted the classification of any of their five ideas after being exposed to the ideas of others.

6. Experiment Procedure

Participants were recruited at the International Design and Technical Conference (IDETC) 2016 in Charlotte, North Carolina, and on Stanford University’s campus; experiments were spaced out over a number of days. To control the experimental environment, we used similar desk set-ups in both locations. At IDETC, 48 participants were tested using a quiet hotel room; at Stanford, 25 participants were tested using a quiet meeting room. We recruited participants by sending a recruiting e-mail to the listserv of Design Theory and Methodology division of IDETC and to the graduate student mailing list in the mechanical engineering department at Stanford University. The majority of participants were graduate students in an engineering-related field. They received $50.00 for participation. The experiment took on average 82.4 min to complete. Participants were encouraged to sketch or draw on scratch paper to help them prepare ideas for entry in the iPad, but only the final typed responses were processed in this study. While including the corresponding sketches could have been useful, the opportunities for bias were too great. First, many of the “non-traditional” design ideas, such as those related to economic factors, simply could not be sketched; thus, all ideas could not be represented equally. Second, there are a number of known biases associated with displaying sketches, for example, the quality of drawings might affect the judges’ perception of the quality of the idea [65].

All activities, except the collage priming activities, took place on an iPad, and all data was collected using Qualtrics. Participants in conditions A1–A3 and B spent 12 min interacting with the collage or reading material before designing, while participants in the control condition, C, started with Ideation 1, which lasted for 8 min for all participants. Then, all participants watched the video for 10.5 min. Next, participants continued to generate additional ideas for the same product (Ideation 2). If a participant generated fewer than five ideas total from both sessions, the participant would see a design prompt for additional encouragement; only one participant required this prompt. Last, participants answered a questionnaire about their demographics, their previous experience designing sustainable products, and their appreciation of various qualities of the washing machine.

7. Data and Analysis of Proposition 1

We collected responses from 73 participants in three separate sections: ideation, idea evaluation, and questionnaire. In ideation (ideation 1 and 2), participants generated 914 design ideas in total. We tested if the location (IDETC 2016 in Charlotte, North Carolina, or Stanford University) had an effect on the ideas’ ratings regarding any aspect for all conditions and found no significant effect. Therefore, the ideas generated by designers from two different locations are combined and analyzed holistically.

In the questionnaire of Part 2, the last step in the experiment (Figure 2), participants reported their previous experience with sustainable products and their awareness of different characteristics of sustainable design, choosing from ratings of “extremely important” to “not at all important”. Thirty-three participants considered “environmental impact” extremely important, and “user desirability”, “safety”, and “ease to maintain” were ranked among the most important aspects of design. Note that this questionnaire was conducted after priming or educational reading, and video exposure. Thirty-six participants reported having no experience working on sustainability-related projects, and 63 participants reported not being familiar with the three pillars of sustainability.

7.1. Judging Preparation and Procedure

We first reviewed all ideas generated in ideation 1 and 2 to correct typos and grammatical errors, so that the type of expression and the clarity of the language would not affect the assessment of the idea. Any idea that consisted of multiple design concepts or features was separated into multiple ideas. Next, we identified ideas that described the same idea but with different language by coding each idea with its key concepts (e.g., solar energy, recycled material). Then, we reviewed ideas with the same concept coding and grouped ideas with the same design into a single idea for rating by the expert judges. This (1) ensured that two very similar ideas would not get different ratings; (2) prevented confusion; and (3) reduced the number of ideas from 914 to 670, requiring less judging work.

Two expert judges were recruited, and both of them had graduate-level mechanical engineering degrees and more than two years of professional experience in design consultancy and sustainable design. They first received a 1-h training, including reviews of score descriptions, example ideas, and corresponding rating scores. After the training, they practiced rating 10 sample ideas independently and then discussed about the discrepancy. The judges rated the rest of unique ideas independently on their own pace. After both judges rated all the unique ideas, the results were compared. The judges were asked to review and discuss the differences together. The rating and discussion took two weeks, and the judges were paid $1000 for this task.

The rating consisted of two sections: one for judging ideas’ relevance to user desirability, manufacturing cost, use cost, and environmental impact and another for ideas’ originality and feasibility. For the first section, the judges rated ideas in terms of how relevant the design intentions were regarding “reducing water and energy usage, improving manufacturing, and increasing the product’s appeal to users”, as asked in the prompt. Cost was broken into “manufacturing cost” and “use cost” based on pilot judging, which indicated a confusion in evaluating product cost as a whole. The judges assigned scores to each idea using a three-point categorical scale: 0 (irrelevant), 1 (slightly relevant), and 2 (strongly relevant). Separately, the judges rated ideas’ originality and feasibility to assess the ideation quality. As a global definition of design quality does not exist, research yielded different definitions and metrics under different circumstances [66]: Shah et al. [67] proposed four effectiveness measures: quality, quantity, novelty, and variety; Kudrowitz et al. suggested three attributes to measure early-stage product ideas: novelty, usefulness, and feasibility [68]. In this study, we adopt a subset of the existing metrics based on the hypotheses at hand, and originality and feasibility are chosen to represent how well a design expands the design space. Originality is chosen over variety because variety measures the explored solution space during the ideation process [67] and because the generation of similar ideas indicates low variety. These metrics are discussed further in [57,58], from which we derive our rating scale. The originality and feasibility ratings are on a scale of 1 to 5, with 5 being the most positive rating (

Table 2. Rating categories and descriptions.

Rating Category	Description of Score 1	Description of Score 3	Description of Score 5
Originality	Not expressed before and ingenious	Not typical, and show some imagination	Common and boring
Feasibility	Easy to implement without major changes or violation of known constraints (financially and physically)	Could be implemented with minor changes to existing conditions	Very hard to implement given the existing conditions and/or requiring significant research and development

). This 5-point scale is adopted from the previous study by She and MacDonald [9] for the comparability of the results.

Table 3. Reliability of sustainability-related ratings before discussion.

	User Desirability	Manufacturing Cost	Use Cost	Environmental Impact
% Agreement	72.9	92.0	66.6	64.9
Cronbach’s α	0.75	0.82	0.70	0.72

summarizes reliability of sustainability-related ratings, including percentage of agreements between two judges, and inter-rater reliability as measured by Cronbach’s α before discussing the discrepancy. The discussion improved the percentage of agreements and Cronbach’s α as shown in

Table 4. Reliability of sustainability-related ratings after discussion.

	User Desirability	Manufacturing Cost	Use Cost	Environmental Impact
% Agreement	81.2	96.0	81.2	76.0
Cronbach’s α	0.91	0.95	0.90	0.89

. The results indicate excellent internal consistency between judges (α > 0.90) [69].

Table 5. Reliability of quality ratings before discussion.

	Feasibility	Originality
% Agreement	66.3	55.0
Cronbach’s α	0.56	0.41

summarizes reliability of the ideas’ ratings of feasibility and originality before the discussion and

Table 6. Reliability of quality ratings after discussion.

	Feasibility	Originality
% Agreement	81.5	74.9
Cronbach’s α	0.72	0.61

summarizes those after the discussion. The results show acceptable consistency (α > 0.60) after the discussion [69].

7.2. Idea Judging Results

Table 7. Number of ideas generated per condition and per designer.

Condition	Number of Participants	Total Number of Ideas Generated (Including Non-Unique Ones)	Average Number of Ideas Generated Per Participant
User desirability prime (A1)	13	159	12.2
Cost prime (A2)	15	195	13.0
Environmental prime (A3)	16	191	11.9
Reading (B)	14	204	14.6
Control (C)	15	165	11.0
Total	73	914	12.5

shows the total number of ideas generated per testing condition and the average number of ideas generated per participant. Ratings of ideas are averaged across judges;

Table 8. Mean scores of rating categories and test results (* p < 0.05).

Condition	Rating Category
	Relevance to Sustainability-Related Aspects (Scale 0–2)				Quality (Scale 1–5)
	User Desirability	Manufacturing Cost	Use Cost	Environmental Impact	Originality	Feasibility
User desirability prime (A1)	0.846 (0.895)	0.164 (0.924)	0.745 (0.768)	1.30 (0.026 *)	2.55 (0.035 *)	3.22 (0.116)
Cost prime (A2)	0.585 (0.008 *)	0.159 (0.885)	0.764 (0.920)	1.26 (0.057)	2.60 (0.067)	3.23 (0.039 *)
Environmental prime (A3)	0.679 (0.115)	0.145 (0.794)	0.844 (0.424)	1.32 (0.012 *)	2.61 (0.095)	3.26 (0.021 *)
Reading (B)	0.544 (0.004 *)	0.259 (0.072)	0.724 (0.751)	1.31 (0.019 *)	2.64 (0.163)	3.13 (0.382)
Control (C)	0.830	0.161	0.774	1.07	2.77	3.03
Grand Mean	0.685	0.180	0.767	1.26	2.64	3.18

summarizes the mean rating scores across each condition for all rating categories and analysis results of the comparison between each testing condition (A1–A3, B) and the control (C).

To test H1a, H1b, H1c, and H1d (described in Section 3), we first compare ideas’ relevance to each aspect between the corresponding testing conditions and the control. For example, we compare the relevance to user desirability of ideas (0.846, p = 0.895) generated by designers exposed to the user desirability prime (A1) to that of the ideas (0.830) generated by designers in the control (C). We also compare ideas’ relevance to environmental impact (0.159, p = 0.855) in the reading (B) as the reading activity also addresses the environmental impact. Table 8 shows the p-values of the comparisons using Mann–Whitney U test for non-normally distributed ordinal variables [70]. In addition, we compare ideas’ relevance between non-corresponding conditions and the control, for example, ideas’ relevance to environmental impact between the user desirability prime and the control. While the user desirability prime was not intentionally designed to increase ideas’ relevance to environmental impact, the prime has a significant effect on it.

As shown in Table 8, the relevance scores as judged on user desirability of ideas generated by designers in the user desirability condition are not significantly higher than the scores of the control. So H1a is rejected. The cost prime (A2) and the reading (B) have a significant effect on ideas’ relevance to user desirability by decreasing the mean score. In addition, the cost prime (A2) has no significant effect in improving ideas’ relevance to manufacturing cost or use cost. Thus, H1b and H1c are rejected. None of other primes results in a significant effect on the rating categories related to cost.

The relevance scores of the ideas generated by designers who had the environmental prime (A3) are significantly higher compared to the scores of ideas in the control (C), so H1d is supported. The reading activity (B) about eco-design also has a significant effect on ideas’ relevance to environmental impact, and it is as effective as the environmental prime. Moreover, the user desirability prime (A1) has a significant effect on environmental impact while the prime does not target such aspect.

To test H1e and H1f, we compare ideas’ originality and feasibility between each testing condition (A1–A3, B) and the control (C), as summarized in Table 8. The results show that the user desirability prime (A1) has a significant effect, but it undermines ideas’ originality compared to the control. Therefore, H1f is rejected. The cost prime (A2) and the environmental prime (A3) have a significant effect on improving ideas’ feasibility so that H1e is partially supported.

8. Discussion of Proposition 1

The experiment demonstrates that exposing designers to a collage priming activity relating to sustainability pillars (social/user desirability, economic competitiveness, environmental friendliness) produces mixed effects. Particularly, the user desirability prime has no significant effect on improving designers’ ability to generate user desirable ideas during conceptual design. The result supports the argument by Pack et al. that designing products from a social well-being perspective remains challenging for both academic researchers and industrial designers [4]. The cost prime has no significant effect on increasing ideas’ relevance to manufacturing cost or use cost either. As acknowledged in Section 2, economic competitiveness or product cost span many areas such as retailing, utility, supply chain, and manufacturing operation. Designers may be challenged to perform cost estimates within the limited time and information in ideation. Meanwhile, the user desirability prime effectively improves designers’ ability to generate more environmental ideas, but significantly reduces ideas’ originality compared to the ideas in the control, as judged by experts. The cost prime undermines designers’ ability to generate user desirable ideas, but it helps designers to generate more feasible ideas. The primes, which aim at activating targeted mindsets, are likely to help designers focus on addressing particular design aspects at a risk of neglecting design quality.

The environmental prime significantly improves ideas’ relevance when judged on environmental impact. This may be due to the fact that student designers had the most experience with environmental impact, such as reducing energy or resources used during manufacture and/or use of the product. The result is consistent with the finding of the previous study, which found priming effective in helping designers to communicate concepts that caused customers to think about reducing environmental impact [9]. In addition, the environmental prime improves ideas’ feasibility compared to the control.

The effectiveness of the reading activity is notable—it significantly improves designers’ ability to generate environmentally friendly ideas, while it harms designers’ ability to brainstorm user desirable ideas. This suggests that the student participants, on the whole, had minimum latent mental content to be activated by priming to address sustainable design. The fact that 63 out of 73 designers were not familiar with the three pillars of sustainability supports this explanation. Our study shows that providing participants with basic sustainable design education, rather than activating latent mental content, is effective for generating ideas that are relevant to environmental impact. This finding echoes the inspiration/information framework proposed by Lofthouse, which emphasizes on providing relatable examples and linking existing material [23]. However, while the reading material encourages designers to focus on environmental impact, it potentially limits their ability to think about other aspects, such as user desirability. In this study, we did not combine the reading activity with a collage priming activity in the experiment, but this could have been even more effective. Possibly, priming more-experienced designers, who are accustomed to addressing user desirability and cost concerns, would have been more effective than basic education (which they already have). A better approach might be to combine a priming activity and an education activity for student designers.

This suggests that priming is an effective way to produce environmentally friendly ideas, as proved in previous studies [9,13,14]. However, priming does not provide a method for activating the less-readily-accessible aspects—user desirability and cost—during ideation.

This part of our study has several limitations. The first is that the study used student designers instead of practicing designers. Students reported to have minimum practical experience with and education about the broader concerns of engineering and thus less latent mental content that could be triggered by collage primes (although some graduate students had previously worked for some time). The success of the reading activity supports this limitation. The population were limited to the conference participants and university students in the U.S. Their demographic background could potentially influence the results, and their perspectives may not be representative universally. A larger sample size is always desirable, but the statistical methods presented consider the size of the sample in determining whether or not the findings are significant. In addition, participants in the priming conditions performed activities, either physically placing pictures or reading a document, while participants in the control condition directly started to ideate. Additionally, the participants were not allowed to conduct design research during ideation; perhaps in a more involved exercise that provides a washing machine, users to interview, and life cycle assessment analyses, the priming activities could trigger design actions, which might lead to even better ideation sessions. The idea generation process occurred using only written words, although some respondents also chose to sketch. This difference in modality (sketch and words vs. words only) may have impacted the ratings given by judges. The designs ideas were conceptual, and the ratings could be based on perception of the ideas by the expert judges. As participants viewed a video to inspire them with new ideas, and the prompt was explicit, there could have been some fixation on particular “directions” of ideas. Even though done carefully, the selection of stimuli, including product images, descriptive words, and reading material, could influence the results. There are also a number of potential sources of technical errors in this part of the study. Only one design task was performed on one target product. Testing multiple products would increase the assuredness of the findings.

9. Data and Analysis of Proposition 2

Proposition 2 investigates if priming makes designers more likely to embrace the ideas generated by hypothetical others when evaluating a mixed set of ideas that included their own ideas. The analysis in this section focuses on idea evaluation, where participants classified a set of five of their own ideas (these ideas were randomly drawn and ordered) and then they classified a larger set of 17 ideas composed of the same 5 ideas and 12 ideas by hypothetical others. This mimicked idea evaluation in a collaborative environment, which is one of the crucial steps in the design process. The participants were asked to evaluate their five ideas twice, first alone, which we call the evaluation section ES1, and then within a group of 12 other ideas from hypothetical other designers, which we call ES2.

9.1. Bias Identification

To identify potential bias during idea evaluation, we investigated the effect of prime, source of the ideas (own ideas versus the hypothetical others’ ideas), ideas’ relevance to the targeted aspects, originality, and feasibility, as judged by experts when designers’ own ideas were presented with simulated others’ ideas in ES2. We used multinomial regression model and the idea classification (“definitely want to explore,” “possibly want to explore”, and “do not want to explore”) as the dependent variables, and the independent variables were tested to have low collinearity, which met the test assumptions [71].

The results shown in

Table 9. Results of multinomial regression model on idea classification (* p < 0.05).

Factor	Prime	Source	Relevance to User Desirability	Relevance to Manufacturing Cost
$\chi$2	1.20 (0.980)	33.6 (0.000 *)	11.4 (0.003 *)	7.41 (0.025 *)
Factor	Relevance to Use Cost	Relevance to Environmental Impact	Originality	Feasibility
$\chi$2	6.18 (0.045 *)	35.3 (0.000 *)	20.26 (0.000 *)	1.41 (0.495)

suggest that the idea evaluation depends on ideas’ relevance to user desirability, manufacturing cost, use cost, and environmental impact, when considering all testing conditions holistically. The evaluation also depends on ideas’ originality and the idea source. The significant effect of the source indicates a biased evaluating process. Yet, in the multinominal regression model, the prime or ideas’ feasibility has no significant effect on the idea classification.

We further test the effect of source, relevance to the targeted aspects, originality, and feasibility on idea evaluation in ES2 of each testing condition (A1–A3, B, and C). Shown in

Table 10. Results of multinomial regression model on idea classification (* p < 0.05).

	Source	Relevance to Sustainability-Related Aspects				Quality
		User Desirability	Use Cost	Manufacturing Cost	Environmental Impact	Originality	Feasibility
A1	1.91 (0.385)	6.76 (0.034 *)	2.62 (0.270)	3.39 (0.184)	15.5 (0.000 *)	9.32 (0.009 *)	0.390 (0.823)
A2	17.3 (0.000*)	1.32 (0.517)	0.522 (0.770)	2.01 (0.366)	5.21 (0.074)	0.683 (0.711)	3.26 (0.196)
A3	13.2 (0.001 *)	0.035 (0.983)	4.51 (0.105)	1.52 (0.467)	8.91 (0.012 *)	5.83 (0.054)	0.640 (0.726)
B	1.99 (0.370)	3.34 (0.188)	3.77 (0.152)	1.62 (0.444)	6.54 (0.038 *)	6.87 (0.032 *)	0.752 (0.686)
C	8.17 (0.017 *)	7.65 (0.022 *)	2.36 (0.308)	0.669 (0.716)	0.80 (0.055)	0.094 (0.954)	5.33 (0.070 *)

, for the participants who were exposed to the user desirability prime (A1), source of the ideas has no significant effect; ideas’ relevance to user desirability and Environmental Impact, as well as ideas’ originality, have significant effects on idea classification. For participants in the cost prime condition (A2), only source of ideas has a significant effect on idea evaluation. For participants exposed to the environmental prime (A3), the source and relevance to environmental impact have a significant effect on idea classification. For those in reading condition (B), the idea evaluation depends on the ideas’ relevance to environmental impact and ideas’ originality. Though the results here do not explicitly show that priming reduces the effect of idea source on idea evaluation, which can be a premise of bias, the difference across testing conditions indicates a potential to shift the natural tendency during idea evaluation.

9.2. Changing Attitude in Evaluation

In this section, to investigate the change in idea evaluation when being exposed to others’ ideas across testing conditions, we used Wilcoxon Signed Rank test to examine the reclassification of each condition at individual level [72].

We explored the change of classifications from ES1 to ES2 at the individual level, for example, one participant classified an idea as “possibly want to explore” in ES1 and changed it to “definitely want to explore” in ES2. The non-parametric Wilcoxon Signed Rank test was used as an alternative of t-test to compare means of two groups for nominal variables that have no observed distribution. The test compares the paired ES1-to-ES2 classification results without and with the hypothetical others’ ideas for each condition [73]. Specifically, higher rank indicates the direction of changes is toward higher importance.

Table 11. Wilcoxon Signed Rank statistic between ES1 and ES2 (* p < 0.05).

Condition	Test Statistics
User desirability prime (A1)	36 (0.03 *)
Cost prime (A2)	30 (0.09)
Environmental prime (A3)	140 (0.20)
Reading (B)	100 (0.90)
Control (C)	70 (0.50)

shows the test statistics along with the p-values by the Wilcoxon Signed Rank test. The results show that the user desirability prime (A1) has a significant effect on encouraging designers to re-classify their own ideas as less important than the control, and potentially to explore others’ ideas more in a collaborative environment. This result echoes the result in Section 9.1, where the effect of idea source is possibly mitigated by the user desirability prime. Neither the cost prime (A2), environmental prime (A3), or reading (B) is effective at shifting designers’ attitude. Therefore, H2 is only supported for the user desirability prime.

10. Discussion of Proposition 2

In Section 9.1, the results of the multinomial regression model show that designers evaluated ideas based on the source, relevance to the targeted aspects, and originality of the ideas (shown in Table 9). At the holistic level, the significant effect of the source suggests the existence of cognitive bias, which may be due to self-favoring or fixation, and demonstrates the interaction of automatic and controlled systems in decision making, as explained in Section 2.3. For each testing condition, the source of ideas has no significant effect on idea evaluation for the participants who were exposed to the user desirability prime and who had the reading activity. This result potentially indicates the effectiveness of priming to mitigate the cognitive bias.

Hypothesis H2 states that priming activities could lead to more receptive attitude when evaluating one’s own ideas in the context of others’ ideas. This hypothesis is supported for the user desirability prime by the Wilcoxon Signed Rank test at the individual level. Even the environmental prime is tested to be effective in improving designers’ ability to generate environmentally friendly ideas in Part 1 of this paper, H2 is not supported for the environmental prime, meaning that participants tended to prefer their own ideas (or ideas they just saw in ES1) over the ideas of others. This is probably because that this prime, instead of decreasing the favoring of one’s own ideas or familiar ideas, triggers an overemphasis on the importance of environmental impact over other aspects. Thus, when a variety of ideas were presented, designers might stick to their own environmentally oriented ideas rather than ideas that addressed the other pillars of sustainability. The reading activity also does not significantly influence idea classification as tested in Section 9.2, potentially due to a similar overemphasis on environmental impact.

In addition, as discussed in Section 2.3, a cognitive connection created by priming stimuli may result in an “implicit cognitive bias”, as individuals tend to rely on most available information in memory when making judgements to simplify information processing [55]. While significant research shows that this type of cognitive bias contributes to design fixation or confirmation bias in a host of real-world and experimental design tasks [51,55], psychological priming—activates specific information in memory that are unfamiliar or neglected—can benefit decision-making process as an intervention to counteract such bias. This aligns with the motivation of this study, which aims to facilitate the design of user desirable and economic products.

One limitation of Part 2 is that the testing of one’s acceptance of others’ ideas was performed with simulated other designers only. We chose this because there were too many factors associated with a real-life design team setting, such as personality fit, language differences, and variability in creativity and communication, that we could not control for. As discussed by Nikander et al. [49], a designer can be prone to favoring certain ideas because these ideas are more available, salient, and familiar during idea evaluation. However, the actual causal relationship is difficult to test. Moreover, we acknowledge that the intrinsic characteristics of designers, such as personality traits and gender, can stimulate biases such as self-favoring [60], but because the focus of this study is not to investigate the cause of the evaluation bias, we did not include the participants’ gender or other demographic in the analysis.

There are also potential sources of technical error in Part 2. For example, we did not observe a known distribution of change of the idea classification in the Section 9.2, and we utilized non-parametric Wilcoxon Signed Rank test to compensate for this, which can be less powerful than the parametric ones.

11. Conclusion and Future Work

The study further illustrates the difficulty that designers have when tackling design aspects that are derived from social and economic perspectives. As stated in the Introduction, designers naturally gravitate toward environmental friendliness in the early stage of sustainable design, even though aspects that address user desirability and cost are also essential for sustainable products to succeed in the market. This issue is well demonstrated in this study: designers who were exposed to the user desirability prime did not improve significantly on generating ideas related to user desirability as judged by experts, and designers who were exposed to the cost prime did not generate more ideas that intended to target the manufacturing cost or use cost of the product either. As mentioned above, this is likely due to the lack of education of these participants; that is, without embedded mental content to “activate”, priming cannot work.

The study contributes to growing evidence that priming is an effective tool to improve ideation in terms of ideas’ relevance to environmental impact. Designers are also prone to generate more feasible ideas in conceptual design, when the latent knowledge about environmental impact is activated by priming. Meanwhile, the reading activity in this experiment helps designers generate more ideas that address environmental impact. The result suggests that, beyond activating particular mindset, providing explicit information and guidelines can significantly benefit designers who have less training or information of certain aspects in sustainable design.

In addition, priming has a potential to influence idea evaluation as a consequence of activating certain mindsets. We found that the collage priming activity that addresses user desirability is effective in cultivating a more open-minded attitude during idea evaluation. In contrary, the collage priming activity and reading activity that address environmental impact are ineffective at encouraging a receptive attitude, probably because both, as effective in helping generate more relevant ideas to environmental impact, reinforce a preference for environmentally driven ideas. Therefore, the priming activity needs to be designed with congruent intentions.

Overall, priming can be effective at activating latent information and building cognitive connections during design activities, when such information is available. Yet, if latent knowledge of an aspect is less accessible to designers, the activities need to be designed carefully—potentially with supplementary training material—in further efforts of supporting sustainable design. Moreover, this priming technique can potentially mitigate cognitive bias when focusing on directions that are not aligned with designers’ own experience, beliefs, and presentations.

A good follow-up study would be to test the effectiveness of priming activities in combination with educational activities, and to explore the order of these two activities and the best types of pairings. It is critical to expose student designers to broader design concerns, such as manufacturing, marketing, and human-centered design, in order to create available mental content that can be accessed during ideation. While life cycle assessment and other environmentally motivated engineering training is important, without design attention to the user desirability and cost aspects, the product will not be profitable and popular with users and may ultimately fail in the market and in use. In addition, as the participants performed the task individually in this study, it would be interesting to conduct the same experiment in a team setting. It is also interesting to explore various modality of providing stimuli and in-depth information. An interactive platform with estimations of eco-cost and carbon-print (e.g., Idemat [74]) is expected to further facilitate novice designers with sustainable product development.