Crowdsourcing in Sustainable Retail—A Theoretical Framework of Success Criteria
Bibliographic record
Abstract
Current research about crowdsourcing covers industries like food systems or logistics, leaving out the possible impact of crowdsourcing on sustainable retail. The debate about the sustainable impact of different industries is ongoing, especially discussing the adaption to the Sustainable Development Goals of the United Nations critically. This paper examines the influence of crowdsourcing on the sustainable aspects of retailing by applying a theoretical derivation as well as an empirical observation. After theoretically discussing the linkage between crowdfunding as a crowdsourcing category and sustainable retail utilizing a literature review, a theoretical framework employing the grounded theory approach is constructed. A total of 24 crowdfunding campaigns aiming at the market introduction of new products or services, each worth over 5 million USD funding volume and run on international crowdfunding platforms, have been taken into consideration. The outcome of the analysis is a theoretical framework presenting three different categories, in which successful crowdfunding campaigns impacting sustainable retail excel: sustainable economic behavior, sustainable community management and sustainable market adaptation. The derived model contributes to the theoretical discussion about the impact of crowdfunding and assists practitioners in reflecting about their approach and goal setting prior to and while crowdfunding.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".