What is the Role of the Membership Model and Warehouse Model inAttracting and Retaining Costco Customers
Bibliographic record
Abstract
While substantial research has been conducted on Costco’s unique business strategies and models, few researchers have taken an in-depth look into Costco customers. As one of the most famous retailers in North America, Costco’s mission is “to continually provide members with quality goods and services at the lowest possible prices (Costco.com).” This statement reflects Costco’s essential competitiveness in keeping its member pricing as low as possible. Costco chose a novel business model to achieve a low price and profit from membership fees instead of pricing the goods too high. Meanwhile, their warehouse model reduced labor costs and increased the quantity offered for a single product. Costco created a new business model integrating memberships and bulk sales, reducing product prices and attracting more customers. With the increasing development of the economy, especially in North America, various novel business models have been used; however, their essential working principle is rarely emphasized. This paper aims to find out what the roles of warehouse and membership are in gaining more customers and benefiting the company. This study surveyed 30 respondents living in Toronto with Costco stores to determine members’ attitudes toward these two business models. The study also used the quantitative method using secondary data sources such as Costco’s website, annual reports, and various financial websites. Results indicate that by uniquely positioning itself as a paid-membership and warehouse model, Costco’s strategies brought massive attention through the invisible advertisements implicitly found in that positioning.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".