Creating New Products from Old Ones: Consumer Motivations for Innovating Autonomously from Firms
Bibliographic record
Abstract
This research provides knowledge and builds theory related to how and why consumers engage in unsolicited innovation with existing products in order to create new ones. Specifically, this research presents an in-depth qualitative exploration of the motivations consumers have for innovating with existing offerings, of their reasons for innovating autonomously from the organization(s) linked to the source material of their innovation, and of their interpretation of the overall context in which they engage in innovation. This paper reveals that there are two main types of ‘creative consumers’ – those who innovate with products in order to solve problems or needs, and those who innovate with products for the sake of creative exploration. Conceptualizations of consumer behavior as either predominately utilitarian (i.e., task-related and rational) or as hedonic (i.e., fun or pleasurable) can be applied to understand innovation by these consumers. In addition, this research reveals that these consumers generally do not have relationships with the firm associated with the source material of their innovation because they do not perceive a benefit to such a relationship. They are indeed enabled by access to technology and by the digital environment more generally. Implications for managers are discussed. This research provides depth and insight on current understanding of the motivations consumers have for innovating with offerings despite not being invited or encouraged to do so by firms.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".