Economic Action Does Not Take Place in a Vacuum: Understanding Cisco's Acquisition and Development Strategy
Bibliographic record
Abstract
There are 71 total acquisitions listed, because two acquisitions did not provide locations. 1This includes the seven counties clustered in the San Francisco Bay Area. 2 This includes all of Texas and includes Dallas-Fort Worth, Austin and San Antonio. 3 These are scattered throughout the other states and only Virginia is home too more than one.Also, includes one in Southern California 4 These are scattered throughout Europe and Canada and no nation is home to more than one. Acquisition Success and FailureIt is difficult to link an acquisition to corporate performance, not only because of measurement and access problems, but also because the goals may vary.For example, some acquisitions are undertaken to provide an end-to-end solution, even if the acquisition, in itself, was not profitable.Prior to examining two indicators that Cisco managers believe are highly correlated with acquisition success, retention and market share, we overview some more general indicators of success.Then in the final section, we examine acquisition failures.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".