Key factors that improve knowledge-intensive business processes which lead to competitive advantage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to empirically test the knowledge-intensive process of creative problem-solving and its outcomes. Design/methodology/approach This study uses survey data from 113 leading Italian companies. To test the structural relations of the research model the authors used the partial least square (PLS) method. Findings Results show that work design and training have a positive direct impact on creative problem-solving process while organizational culture has a positive impact on both creative problem-solving process and its outcomes. Finally creative problem-solving process has a strong direct impact on its outcomes and this, in turn, on firms’ competitiveness. Practical implications This study suggests that managers must highlight the problem-solving process as it affects a firm’s capability to find creative solutions and therefore its competitiveness. Moreover, the present paper suggests managers should invest in specific knowledge management (KM) practices for enhancing knowledge-intensive business processes. Originality/value The present paper fills an important gap in the BPM literature by empirically testing the relationship among KM practices, multistage processes of creative problem-solving and their outcomes, and firms’ competitiveness.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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