Brand as credible commitment in embedded licensing: a transaction cost perspective
Bibliographic record
Abstract
Purpose The purpose of this paper is to study brand embedded licensing (technology licensing and brand licensing combined) and its theoretical difference from standard licensing (technology licensing only). The following research questions are asked: What makes embedded licensing theoretically different from standard licensing, and what determines a licensor's decision to select brand embedded licensing over standard licensing? Design/methodology/approach This paper compares brand embedded licensing to standard licensing and argues that brand embedded licensing is a quasi‐hierarchical organizational structure, while standard licensing is a market‐based structure. Brand embeddedness in licensing serves as a credible commitment from the licensor and induces the licensee to invest sufficiently in complementary assets. Drawing on the transaction cost perspective, the determinants of embedded licensing are examined. Findings Embedded licensing is determined by both the licensee's characteristics and the licensor's brand characteristics. The licensor is more likely to utilize embedded licensing or the licensee is more willing to demand embedded licensing when: the licensee's specific complementary investment is high; the licensee's complementary capacity is high; the market entry is at a late stage; the licensor uses separate branding; the extent of product differentiation is high; and the stage of brand globalization is advanced. A strong intellectual property rights regime and a fast pace of technology change enhance the effects of these six determining factors on the licensor's selection of embedded licensing. Originality/value This paper challenges the classical view that licensing is a market‐based relationship by revealing that embedded licensing is a quasi‐hierarchical organizational structure.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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; both teacher heads agree on what is shown here.
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".