The significance of knowledge sharing platforms for open innovation success
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of this paper is to contribute to the theoretical background on how organizational change (OC) enhances open innovation (OI) processes and enables a company to reach performance results through implementing knowledge sharing platforms (KSPs). The authors aim to better understand and investigate how the changes introduced by the implementation of KSPs impact the OC and facilitate the OI process. Design/methodology/approach In this paper, an exploratory longitudinal single case study based on a variety of data sources is used: participant observations, focus group discussions and semi-structured interviews with the KSP members and top managers of a Tunisian SME operating in the dairy products sector. The open-ended responses were subsequently exposed to thematic discourse analysis. Findings The case study findings deeply explore and investigate a company’s experience in implementing OCs when using a joint-venture alliance with a French leader to develop OI. Central to this exhibit is the nature and magnitude of the knowledge sharing between the parties in the OI process, and the significant impact it had on the consumers’ reception of the new products. The outcomes show that due to the sharing of external research and development skills, the creation of the KSP has been an incentive for significant changes and customer targeting and for promoting internal absorptive capacity, minimizing complexity, uncertainty and risks and reaching performance results. Originality/value This paper provides a deep understanding of the new product development process and offers a holistic approach with respect to KSP practices. The significant impact on the consumers’ first response and the subsequent adaption of an industrially produced cheese as a subsidiary product to an existing artisan quality product are examined in this study. Examining the implementation of an OI process, this research is one of the few studies revealing the shortcomings of a former process and a subsequent adaption of a newly successful one that targets the consumers in a MENA country.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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