An Online Community-Based Digital Platform – From Success to Failure
Bibliographic record
Abstract
Digital platforms are becoming the new way of doing business for many ventures and established organizations. Understanding digital platforms is central to understanding organizing through information technology. Digital platforms face unique challenges in engaging an external pool of users for value exchange. These challenges are especially unique when the digital platform is designed to host an online community. Much is known about what motivates online community users to participate and how members coordinate and govern activities. However, less is known about the role played by the digital platform provider and why a digital platform hosting an online community would fail. In this research, we answer this question through a qualitative grounded theorizing approach. We study an empirical case of a propriety collaborative online community and examine how the provider divided decision-making between itself and the online community, establishing such division in the architecture it provided and the interaction it performed with the online community. We conclude that the discrepancy between the community’s activities and the provider’s goals leads the provider to tweak the division of decision-making by either increasing or decreasing centralization. We present four propositions explaining the conditions through which restriction and expansion of communal decision-making can support or undermine the online community. We differentiate between restriction and expansion of communal decision-making through technology modification and content intervention. We explain important implications for research and practice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.011 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".