Emergent Themes in the Interface Between Economics of Information Systems and Management of Technology
Bibliographic record
Abstract
In this article, we look at research published over a five‐year time span in the economics of information systems (IS) area in four premier journals, including Management Science, Information Systems Research, MIS Quarterly, and Production and Operations Management, to identify research themes that have implications for future research in the area of Management of Technology (MOT). Through our examination of the literature, we identify three emergent themes that can be used to form foundations for future MOT research from an economics of IS perspective: productivity, vertical relations, and platforms. Within each of these themes, we classify previous research into subthemes, summarize the major findings, and explore future research opportunities within the MOT domain that are relevant to these subthemes. Specifically, we examine how information technology has impacted firm productivity, their product design and development process, innovation capabilities, knowledge management capabilities, and supply chain integration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".