Bullwhip effect phenomenon and mitigation in logistic firm's supply chain: Adaptive approach by Transborder Agency, Canada
Bibliographic record
Abstract
This case study explores the bullwhip effect phenomenon and mitigation in supply chain process at Transborder Logistic Canada. Despite being one of the largest logistic chains of Canada, for two years it was facing challenges and problem in shape of bullwhip effects. \nThe theoretical framework for present case study is based on the theory of Lee (1977) to overcome the problems in the supply chain process. "Realism" is the research philosophy undertaken to develop a cross-sectional research design to investigate the research problem at hand. Hypothetico-inductive-deductive model is used to explore research variables. Moreover, researcher used mixed method approach by circulating matrix based semi-structured survey questionnaire in different interlinked departments of Transborder Agency. The questionnaire is based on LIKERT Scale (1-to5) rating. In addition to that, open-ended interviews with the head and subordinates of various departments were commenced to explore qualitative aspects related to research problem. \nResults revealed that logistic firm rely heavily on demand-forecasting information through customers. There was fluctuation in demand order along with order batching, demand forecast updating, rationing and shortage game, and price fluctuation. The Polar diamond approach is considered by Transborder to effectively and efficiently deal with problem at hand and challenges that are hindering the supply chain process. Moreover, VMI, EDI, and POS are tools and techniques used to resolve different types of challenges and find a long term proper rational solution to bullwhip effect (problem at hand). Logistic supply chain inefficiency is mainly caused by bullwhip effect. The rational adoption of model can assist supply chain managers to be proactive in approach.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".