MITIGATING COMPANY ADOPTION BARRIERS OF DESIGN-DRIVEN INNOVATION WITH HUMAN CENTERED DESIGN
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In Design-Driven Innovation (D-DI) the meaning of a product or service is radically innovated to introduce a new paradigm that ideally can benefit people, companies, and society as a whole. However, due to the associated risks, most companies are hesitant to engage with and adopt D-DI. Human Centered Design (HCD) is preferred while innovation is limited to incremental change. This dichotomy is also reflected in design literature where D-DI is pitted against HCD. We propose the symbiosis of the two approaches as a strategy to create space for and the adoption of D-DI within companies. An instrumental design case study explores a design-driven service innovation and its adoption in a renowned airline. Results show an adopted D-DI where HCD evidence mitigates for the market and organization uncertainty while D-DI enabled a paradigm shift in the company’s current service operation. Advantages and limitations of this mitigation strategy are discussed. With this design precedent, we aim to encourage designers and companies to further explore the benefits of a symbiotic use of D-DI and HCD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it