Choosing creativity: the role of individual risk and ambiguity aversion on creative concept selection in engineering design

Abstract

While creativity is often seen as an indispensable quality of engineering design, individuals often select conventional or previously successful options during the concept selection process due to the inherent risk associated with creative concepts and their inadvertent bias against creativity. However, little is actually known about what factors attribute to the promotion or filtering of these creative concepts during concept selection. To address this knowledge gap, an exploratory study was conducted with 38 undergraduate engineering students. This study was aimed at investigating the impact of individual risk aversion, ambiguity aversion, and student educational level on the selection and filtering of creative ideas during the concept selection process. The results from this study indicate that individuals’ ability to generate creative ideas is not significantly related to their preference for creative ideas during concept selection, but individual risk aversion and ambiguity aversion are significantly related to both creative concept selection and creative idea generation. Our results also revealed that first- and third-year students’ creative ability is affected differently by varying levels of tolerance for ambiguity. These results highlight the need for a more directed focus on creativity in engineering education in both concept creation and concept selection. These results also add to our understanding of creativity during concept selection and provide guidelines for enhancing the design process.

Appendices

Appendix 1: Brainstorming and concept assessment instructions

1.1 Individual brainstorming instructions

Upper management has put your team in charge of developing a concept for a new innovative product that froths milk in a short amount of time. Frothed milk is a pourable, virtually liquid foam that tastes rich and sweet. It is an ingredient in many coffee beverages, especially espresso-based coffee drinks (Lattes, Cappuccinos, Mochas). Frothed milk is made by incorporating very small air bubbles throughout the entire body of the milk through some form of vigorous motion. As such, devices that froth milk can also be used in a number of other applications, such as for whipping cream, blending drinks, emulsifying salad dressing, and many others. This design your team develops should be able to be used by the consumer with minimal instruction. It will be up to the board of directors to determine if your project will be carried on into production.

Once again, the goal is to develop concepts for a new, innovative product that can froth milk in a short amount of time. This product should be able to be used by the consumer with minimal instruction.

Sketch your ideas in the space provided in the idea generation sheets. As the goal of this design task is not to produce a final solution to the design problem but to brainstorm ideas that could lead to a new solution, feel free to explore the solution space and focus on both the form and function of the design in order to develop innovative concepts. In other words, generate as many ideas as possible—do not focus on the feasibility or detail of your ideas. You may include words or phrases that help clarify your sketch so that your concept can be understood easily by anyone.

For clarity, please use the provided pen to generate your concepts (i.e., do not use pencil). Your participant number is included on each of the provided idea generation sheets. Generate one idea per sheet and label the idea number at the top of the sheet.

1.2 Individual concept assessment

During this activity, you will review and assess the concepts that you and your team have generated to address the design goal. Once again, the goal of this design problem is to develop concepts for a new, innovative, product that can froth milk in a short amount of time. Your task is to individually assess all of the generated concepts for the extent to which they address the design goal effectively, using the following instructions (illustrated in the diagram below):

• 1. Shuffle all of the concepts that you have generated in random order. Pass all of the designs you have generated to the team member sitting to your right.

• 2. After receiving the concepts that were passed to you from the team member sitting to your left, rate each concept in the order that you received them using the rating table provided to you in this booklet. For each concept that you rate, record the corresponding participant’s number, idea number, and a brief description of the concept (e.g., “Double frothing attachments”). You will be given 5 min to interpret the designs that you receive without conversing with your team members. For your reference, definitions of the rating scale items have been provided below:

  • Consider: Concepts in this category are the concepts that will most likely satisfy the design goals, you want to prototype and test these ideas immediately. It may be the entire design that you want to develop, or only 1 or 2 specific elements of the design that you think are valuable for prototyping or testing.

  • Do not consider: Concepts in this category have little to no likelihood of satisfying the design goals and you find minimal value in these ideas. These designs will not be prototyped or tested in the later stages of design because there are no elements in these concepts that you would consider implementing in future designs.

• 3. Repeat step 2, passing designs that are already rated to your right, and rate designs that are passed to you from the left. You will be given 5 min to rate each set of design ideas.

Finish rating all the ideas that your team has generated, including yours. You should end this activity with rating all of the ideas that you have generated.

Appendix 2: Design rating survey (DRS)

Appendix 3: Risk and ambiguity aversion measures and calculation

3.1 Measuring individual risk aversion

Risk aversion is measured using the 10 lottery questions (also found in the online survey link) used in standard behavioral economics (Han et al. 2012). The goal of the assessment is to identify the point at which the individual would take the gamble given fixed odds of winning the gamble (i.e., make the “risky” choice). Potential gamble gains vary randomly within the interval of $20.00 to $300.00.

3.2 Risk aversion questions

The following questions assess an individual’s risk aversion level. Answer the following questions regarding hypothetical lottery scenarios by specifying whether you prefer a fixed payoff of a specified value, or a gamble of fair odds with an uncertain payoff of a specified value (i.e., you are equally likely to win the gamble or lose the gamble).

3.3 Measuring individual ambiguity aversion

Ambiguity aversion is measured using the 10 additional lottery questions (also found in the online survey link) used in standard behavioral economics (Borghans et al. 2009; Charness and Grieco 2013). The goal of the assessment is to identify the point at which the individual would take the gamble given unknown odds of winning the gamble (i.e., make the “uncertain” choice). The individual’s risk aversion can then be calculated using the responses to the risk aversion questionnaire (see below for details). Potential gamble gains once again vary randomly within the interval of $20.00 to $300.00 (identical to risk aversion questionnaire).

The following questions assess an individual’s ambiguity aversion level. Answer the following questions regarding hypothetical lottery scenarios by specifying whether you prefer a fixed payoff of a specified value, or a gamble of unknown odds with an uncertain payoff of a specified value (i.e., it is not known how likely it is for you to win the gamble, as it could range from not at all likely, to extremely likely).

3.4 Calculating individual risk aversion

In order to estimate each individual’s risk aversion, the following computations will be conducted:

The gamble option payoff of the ith participant at the jth question, GP _ij , is

$${\text{GP}}_{ij} = \frac{{0.5 \times {\text{Gain}}_{j}^{{1 - \gamma_{i} }} }}{{1 - \gamma_{i} }}$$

where Gain _j is the gamble gain for question j, and $\gamma_{i}$ is the risk aversion coefficient for participant i.

The safe option payoff is then SP _ij defined as

$${\text{SP}}_{ij} = \frac{{{\text{Safe}}_{j}^{{1 - \gamma_{i} }} }}{{1 - \gamma_{i} }}$$

where Safe _j is the safe gain for the jth question.

Then, the probability of subject i choosing the gamble at question j is linked to GP _ij and SP _ij through the following logistic function:

$${\text{logit}} \left( {P\left( {Y_{ij} = 1} \right)} \right) = {\text{GP}}_{ij} - {\text{SP}}_{ij}$$

$${\text{logit}} \left( {P\left( {Y_{ij} = 1} \right)} \right) = \frac{{0.5 \times {\text{Gain}}_{j}^{{1 - \gamma_{i} }} - {\text{Safe}}_{j}^{{1 - \gamma_{i} }} }}{{1 - \gamma_{i} }}$$

where Y _ij is the response to the survey by the ith participant, for the jth question. To obtain an estimate of the risk aversion coefficient $\gamma_{i}$, the maximum likelihood function of this logistic model is computed.

3.5 Calculating individual ambiguity aversion

In order to estimate an individual’s level of ambiguity aversion $\delta_{i}$, the following formula is used:

$${\text{Ambiguity}}\;{\text{Aversion}},\; \delta_{i} = {\text{AC}}_{i} - {\text{RC}}_{i}$$

where AC _i is the gamble gain for the gamble question in the ambiguity aversion questionnaire that the ith participant first takes (i.e., the cutoff point where the individual prefers taking a gamble over the safe payoff). Similarly, RC _i is the gamble gain for the gamble question in the risk aversion questionnaire that the ith participant first takes. This method is similar to the method used in Borghans et al.’s work (2009) except that the gamble gains are provided to participants in increments of 10 questions, instead of left up to the participant to decide.