Analyzing Costco’s supply chain responsiveness through lean and agile strategies
Bibliographic record
Abstract
Supply chain responsiveness contributes to efficient supply chain performance. Supply chain responsiveness refers to effectively and efficiently meeting customer’s needs in a timely manner. This paper considers the supply chain strategies and practices that lead to the supply chain responsiveness of Costco when compared to its major competitors, Wal-Mart and Loblaws. The evaluation and comparison of key financial performance measures as well as various statistical analyses identify the supply chain strategies that benefit Costco and its competitors. The paper presents a contribution to existing supply chain literature through the in-depth analysis conducted of different supply chain performance measures for three major retailers in Canada - Costco, Wal-Mart and Loblaws. This analysis evaluates a 23-year period from 1999 to 2021. The analysis also contributes to the existing literature on the use of supply chain strategies, such as leanness and agility in the retail industry, Costco’s practices of just-in-time (JIT) inventory management and cross-docking as well as specific characteristics of Costco’s supply chain practices. The findings of the analysis lead to the validation of assertions and propositions of earlier researchers. These include the importance of employing complementary supply chain practices together as well as a focus on aligning supply chain strategies with the company’s corporate strategy. These understandings contribute to the achievement of supply chain responsiveness by encouraging cohesion and balance amongst supply chain strategies.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".