Return on Investments in Hotel Franchising: Understanding Moderating Effects of Franchisee Dependence
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
Hotel franchising presents a unique network context for investigating inter‐organizational collaboration. Franchisees and franchisors must collaborate closely but face incompatible incentives in allocating financial and human resources to invest in three types of operations: centralized, network‐level operations run by the franchisor; distributed, outlet‐level operations managed by franchisees; and coordinated operations, which use franchisee and franchisor inputs. This study employs a mixed‐methods design to empirically examine the effects of these three types of investments on outlet‐level performance while considering franchisees' dependence on the franchisor for sales. To ground our understanding of the phenomenon, we interview US hotel industry experts, then test the conceptual model with a panel data set of 3500 franchised US hotel properties. We find that franchisee dependence moderates the impact of all three types of investments. Specifically, a high‐dependence franchisee's centralized investments and coordinated investments, and a low‐dependence franchisee's distributed investments are associated with higher levels of outlet performance. We discuss how structural embeddedness drives these effects and explore its implications for service supply chain design and collaborative operations management.
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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 | 0.000 | 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) | 0.000 | 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