Using The Internet To Simulate Virtual Organizations In MBA Curricula
Bibliographic record
Abstract
Communications technology is shifting the basic architecture of organizations from hierarchies to networks. Organizations are becoming flatter, increasing the need for peer communication. There are also emerging "virtual" organizations, "temporary network[s] of independent companies ... linked by information technology to share skills, costs, and access to one another's markets" (Byrne et al., 1993). Today, that linking technology is often the Internet, Compuserve or a similar network. For example, one of the authors is currently working with an organization of consultants which is seeking to replace its outdated "F-style" communication (fone, fax and fly) with a much cheaper and more effective Internet-based system. This organization has no headquarters and makes extensive use of ad hoc task forces to address specific issues. This paper describes a project which attempts to offer MBA students realistic exposure to work in a such a virtual organization as a pedagogical exercise. Two MIS classes at widely separated universities were each divided into teams. Each team was assigned to study a local organization. Then, based on the type of organization being studied, teams were paired (one from each university) and asked to exchange results over the Internet and come to some joint conclusions. This type of project also provides potential research opportunities. The length and format are more realistic than typical lab studies, while offering better control and subject availability than field research
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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".