Investigating the Complexity of Organizational Digitization and Firm Performance: A Set-Theoretic Configurational Approach
Why this work is in the frame
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Bibliographic record
Abstract
This study investigates the causal complexity and diversity of the relationship between organizational digitization and firm performance. Digitization – defined as the penetration of IT in the organization – is a complex organizational phenomenon in that it involves changes in organizational strategy, business processes, organizational knowledge and eventually the whole socio-technical organizational system, thus influencing organizational performance. We adopt a holistic configuration theory lens and a set-theoretic method, fuzzy-set qualitative comparative analysis (fsQCA) to explain how such interdependent relationships among digitization and organizational strategic elements result in high firm performance. We apply the set-theoretic method to a longitudinal field data set collected from 1816 Canadian firms. We found multiple equifinal configurations that result in high performance. By comparing the similarities and differences within and between the configurations, we could explain the multifaceted roles that digitization plays in achieving high performance together with organizational strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it