Franchisor–Franchisee Bankruptcy and the Efficacy of Franchisee Governance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Franchisors’ long-term viability is tied to the ongoing operations of their franchisees. To ensure the ongoing performance of franchisees, franchisors deploy multiple governance mechanisms. This study assesses how governance mechanisms deployed to enhance franchisee ability (via selection and socialization) and motivation (via incentives and monitoring) impact franchisee bankruptcy. The authors examine the individual and joint effects of deploying governance mechanisms that share the same underlying objective, namely, to enhance franchisee ability and motivation. They also assess how motivation-inducing mechanisms may serve to counter the motivation-dampening effect of an increased royalty rate. Relying on data from multiple archival sources, the authors identify all bankruptcy filings by franchisees and their franchisors across 1,115 franchise systems over a 13-year observation window. Their findings document a positive and significant relationship between franchisee and franchisor bankruptcy. They also find main and interaction effects of the ability- and motivation-influencing governance mechanisms on the likelihood of franchisee bankruptcy, and the existence of significant bankruptcy spillovers among franchisees within the same franchise system. They discuss implications for franchise theory and management.
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.
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 | 0.018 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it