Colorado’s Arapahoe Basin ski area changes its marketing strategy: the Vail epic pass decision
Bibliographic record
Abstract
Research methodology The case was developed from two 2-h interviews with the Chief Operating Officer of A-Basin, Alan Henceroth; there is no CEO of A-Basin. The second interview was recorded on a Zoom call to provide accuracy of quotations and information. A variety of secondary sources were used in terms of better understanding the current state of the ski industry, as well as its history. Case overview/synopsis Arapahoe Basin (A-Basin) is a historic, moderately sized, ski area with proximity to metropolitan Denver, Colorado. For over 20 years A-Basin partnered with Vail, allowing skiers to use the Vail Epic Pass, for which A-Basin received some revenue from Vail for each skier visit. The Epic Pass allowed pass holders unlimited days of skiing at A-Basin. More and more skiers were buying the Epic Pass, thus increasing the customer traffic to A-Basin. However, the skier experience was compromised due inadequate parking, long lift lines and crowded restaurants. The renewal of the contract with Vail was coming due, and A-Basin had to consider whether to renew the contract with Vail. The case is framed primarily as a strategic marketing case. The authors use Porter’s five forces model to assess the external environment of A-Basin, and the authors use the resource-based view and the VRIO tool to assess A-Basin’s internal strengths. Both frameworks provide useful analysis in terms of deciding whether to continue A-Basin’s arrangement with Vail or end the contract and pursue a different strategy. In 2019, after consultation with the Canadian parent company Dream, A-Basin made the decision to disassociate itself from the Epic Pass and Vail to restore a quality ski experience for A-Basin’s customers. No other partner had ever left its relationship with Vail. An epilogue details some of A-Basin’s actions, as well as the outcomes for the ski area. Generally A-Basin’s decision produced positive results and solidified its competitive position among competitors. Other ski areas have since adopted a similar strategy as A-Basin. A-Basin’s success is reflected in a pending offer from Alterra, Inc., to purchase the ski area. Complexity academic level The A-Basin case can be used in both undergraduate and graduate strategic (or marketing) management courses. It is probably best considered during the middle of an academic term, as the case requires students to apply many of the theoretical concepts of strategy. One of the best books to enable students to use Porter’s five forces is Understanding Michael Porter by Joan Magretta (Boston: Harvard Business Review Press, 2012). Magretta was a colleague of Porter for many years and was an Editor of the Harvard Business Review. For a discussion of the VRIN/VRIO concept, see Chapter 4 of Essentials of Strategic Management by Gamble, Peteraf and Thompson (New York: McGraw-Hill Education, 2019).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".