Re-predict and Improve the Outlook for The Overall Decline of The Big-box Retailer Industry: Case of Target's Tailures in Canada
Bibliographic record
Abstract
The rise of e-commerce in the 21st century has dramatically impacted the Canadian and global consumer markets. During this period of high economic volatility, many big-box retail chains have gone out of business due to ineffective modes of business. Through the case study of the rise and fall of Target Canada between 2013-2015, and cross-referencing the company’s statistics with the successes of other surviving competitors such as Walmart, many flaws of its operations were exposed. The four fundamental flaws in Target Canada’s operations were found to be: Overly-aggressive expansion into a foreign market niche; a high level of competition with other retailers due to a lack of specialties in merchandise; Low brand loyalties due to poor consumer experience, and Lack of user-friendly online shopping platforms, mobile app platforms, and other auxiliary services. This study has concluded that Target Canada’s lack of implementation of technological innovations and its ineffective logistical planning were the two major causes of its ultimate downfall. Suggestions for correction and improvements are discussed, which may give insight to current and future entrepreneurs who wish to enter the Canadian market as a retailer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".