Reexamining the Value of Relevance of E-Commerce Initiatives
Bibliographic record
Abstract
This study reexamines the value relevance of e-commerce announcements using an event study methodology. Event studies have become an increasingly popular technique for information systems research by giving researchers a tool to measure the notoriously elusive value of information technology. We find evidence that the traditional event study methodology may not provide an accurate measure of abnormal returns during periods of high market volatility, and propose an alternative methodology. The alternative methodology does not use an estimation period, and takes into account extreme or unusual market movements in the period in which the e- commerce announcement was made. Using the alternative methodology, we find evidence of positive abnormal returns for e-commerce announcements made in the fourth quarter of 1998, but no abnormal returns to e- commerce announcements made in the fourth quarter of 2000. We also find significant differences in value depending on the type of e-commerce initiative. In 2000, e-commerce initiatives with a digital product were valued significantly more than e-commerce initiatives with a tangible product, while in 1998 no such difference existed. In 1998, business-to-business e-commerce initiatives, e-commerce initiatives with a tangible product, and e- commerce initiatives by pure-play Internet firms were valued more than similar initiatives in 2000. The study makes a significant contribution for understanding the value of e-commerce initiatives in highly volatile markets and demonstrates how market values of e-commerce changed from 1998 to 2000. Furthermore, this study shows the importance of carefully considering both the time frame examined and the methodology used when assessing the value relevance of e-commerce initiatives as to avoid inflating the magnitude of any observed effects.
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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 | 0.001 | 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".