Problem framing significantly impacts solution diversity and quality in open innovation challenges.

Why It Matters

Understanding this relationship allows design teams to strategically frame challenges to elicit specific types of innovation, whether it's novel approaches, diverse solutions, or highly feasible designs. This can optimize the outcomes of crowdsourced design efforts and accelerate product development.

Key Finding

The study found that how a design problem is presented in an open innovation challenge affects who participates and the variety and quality of the solutions submitted.

Key Findings

• The structure of the posed problem influences solver engagement and the diversity of solutions.
• Rich data can be collected on solver demographics, expertise, processes, and solution outcomes in open innovation.
• Analysis of all submitted solutions, not just winning ones, reveals a broader spectrum of design possibilities.

Research Evidence

Aim: How does the architectural framing of a technical problem in an open innovation setting influence the characteristics of the solvers who engage and the attributes of the solutions they produce?

Method: Data analysis of an open innovation challenge dataset

Procedure: Researchers analyzed data from a large-scale open innovation challenge involving multiple contests, tracking potential solvers, their engagement, and the submitted solutions. They characterized the relationship between problem formulation, solver attributes, solving processes, and solution outcomes.

Sample Size: 16,249 potential solvers, 6,219 initiated solving, 147 unique solvers submitted 263 solutions.

Context: Open innovation platforms, engineering design challenges, robotic design.

Design Principle

Problem framing is a critical upstream variable in open innovation that dictates downstream solution diversity and quality.

How to Apply

When setting up a design challenge or seeking external innovation, spend time defining and refining the problem statement to guide participants towards desired outcomes.

Limitations

The specific context of a robotic design challenge might not generalize perfectly to all design domains. The dataset is specific to the 'Astrobee Challenge Series'.

Student Guide (IB Design Technology)

Simple Explanation: How you ask a design question in a competition can change the kinds of answers you get and who tries to answer it.

Why This Matters: This research shows that the way you set up a design challenge or ask for ideas can have a big impact on the results you get, helping you get better solutions for your design projects.

Critical Thinking: To what extent can problem framing be used to 'engineer' specific types of innovation, and what are the ethical considerations of such manipulation?

IA-Ready Paragraph: The 'Astrobee Challenge Series' data explainer (Szajnfarber et al., 2023) highlights that the architectural framing of a technical problem in an open innovation context is a significant determinant of solver engagement and solution attributes. This suggests that design practitioners should carefully consider how problem statements are formulated to elicit desired innovation outcomes, such as novelty or diversity.

Project Tips

• When designing a user research study, think about how your questions might influence the responses you receive.
• Consider how to frame a design brief to encourage a wide range of ideas or specific types of solutions.

How to Use in IA

• Reference this study when discussing how the framing of a design brief or problem statement influenced the outcomes of your design process or a comparative analysis of different approaches.

Examiner Tips

• Demonstrate an understanding that the way a design problem is presented can significantly influence the innovation process and outcomes.

Independent Variable: Problem framing (e.g., architectural manipulation of the problem)

Dependent Variable: Solver characteristics (demographics, expertise), solving processes, solution attributes (novelty, variety, feasibility)

Controlled Variables: Open innovation platform, duration of contests, general problem domain (robotics).

Strengths

• Large dataset capturing a wide range of potential solvers and outcomes.
• Rich data linking solver characteristics to solution attributes.
• Analysis of all submitted solutions, not just winners.

Critical Questions

• How might cultural differences in solver populations affect the impact of problem framing?
• What are the trade-offs between framing a problem for novelty versus feasibility?

Extended Essay Application

• Investigate how different problem-framing strategies in a design brief impact the diversity of user-generated concepts for a new product.

Source

Linking solver characteristics, solving processes and solution attributes: A data explainer for an open innovation generated robotic design dataset · Data in Brief · 2023 · 10.1016/j.dib.2023.109547