Boon or bane of open value creation: The impact of business model design and relational trust on competitive advantage
Bibliographic record
Abstract
Increasing digitization and global interconnectedness provide firms with new opportunities for openness in value creation, generating new sources of competitive advantage. We investigate the competitive advantage of open value creation (OVC) and the influencing role of novelty- and efficiency-oriented business model (BM) designs as unique logics of guiding collaborations to access and utilize external resources for value creation. We further examine the role of trust in such collaborative relationships to navigate the relational uncertainties in boundary-spanning transactions within BMs. Based on a survey study with secondary data triangulation, we investigate how companies gain competitive advantage through OVC by adopting an appropriate BM design and relational governance of trust in partners. Our results prove a positive effect of openness in value creation on competitive advantage while the strength of this positive effect is moderated by the BM design and relational trust. Our paper provides guidance on managing openness in value creation under the divergent designs of BMs and relational trust.
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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 | 0.012 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".