Thinking strategically about professional sports
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we examine the potential value that Professional Sport Franchises (PSFs) have for firms that seek to earn economic rents and obtain a persistent competitive advantage. To do so, we discuss PSFs from two perspectives: 1) Structure‐Conduct‐Performance (most closely associated with Porter's [1979] five‐forces model) and 2) the resource‐based view (RBV) of the firm (Barney, 1991). We argue that, despite operating in a less munificent market than in previous decades, sport franchises should continue to provide a means for corporations to attain a competitive advantage and earn superior economic rents. However, the likelihood of success will be directly dependent upon the particular strategy being pursued, which, we argue here, must combine the characteristics of each franchise with other valuable resources unique to the specific corporation. We go on to argue that such strategy should focus on developing, maintaining, and sustaining a strong, committed fan base. The contribution the paper makes to the sport management literature is as follows. First, by distinguishing a PSF as a strategic economic asset, we show how we can avoid the ambiguity of the term “team”, which we argue is really only a subset of employees who work together to produce the league product. Second, we identify the need for research to move from examining sport organizations'individual business strategies to how sport organizations fit into broader corporate strategies. Finally, we show how a resource‐based view allows for a better understanding of why, despite the apparent financial woes of PSFs, franchises continue to escalate in value and remain as resources that corporations can employ to attain superior economic rents and a persistent competitive advantage.
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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 | 0.002 | 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 | 0.000 |
| 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 it