Resource-Based View and Competitive Strategy: An Integrated Model of the Contribution of Information Technology to Firm Performance
Bibliographic record
Abstract
In the information technology (IT) literature, therelationship between IT and firm performance has been examined from aresource-based perspective and from the perspective of strategy. The goal ofthis study is to use the complementary nature of the two perspectives in orderto shed light on the contribution of IT to firm performance. A model that comprises both a competitive strategy framework and theresource-based perspective is used to achieve this objective. By depicting theeffects of IT support on business strategy and firm assets, the model capturesthe impact of IT on firm performance. Data from a survey of 96 Canadian firmsare used to test the model. According to the data, the variance in the sampled firms' market performanceis due, on the one hand,mostly to the direct effect of IT support forstrategy and the indirect effect of IT support for the firms' assets. Thevariance in profitability, on the other hand, is due to the direct effect of ITsupport for the firm's assets and by market performance. (SAA)
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".