An Information Processing Model of Information Systems Impact on Interorganizational Coordination
Bibliographic record
Abstract
There has been much speculation that information technology can be used to enhance coordination across organizations. The research on the matter is less than convincing, in part due to the absence of models that capture the complexity of the phenomenon, and in part due to problems of measurement. In this research we use the framing device of the information processing model of organization, extended to interorganizational operations. We test the information processing model in the interorganizational context of the scheduled air cargo industry. Using data from a survey of US forwarders, we find that interactions between several dimensions of information processing requirements and information processing capabilities significantly explain variance in operational performance. In particular we find that the information systems variables interact with task variability, task analyzability, buyer independence and supplier independence on the dependent variable, on-time performance. The findings provide partial support for the proposed information processing model and suggest that information systems do enhance interorganizational coordination, although many challenges remain in fully explicating the ways in which this occurs.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".