Effective management of international technology transfer projects
Bibliographic record
Abstract
Purpose – The Brazilian textile industry has been facing fierce competition from low-cost imports from China and other Far East countries. To maintain their competitiveness in the local market, Brazilian companies have been adopting the product differentiation strategy. By using new technologies, they are able to develop new products with better quality at lower costs. With regard to new technologies, companies in the Brazilian textile industry have been using get-some and buy-some strategy, and international technology transfer (TT) has become an important part of their business strategies. However, due to lack of planning, many projects failed to achieve the desired results. This paper aims to provide theoretical insights and practical guidance on how textile firms could use a stage-gate model to enhance the effectiveness of their TT projects. Design/methodology/approach – In order to investigate the TT practices in the Brazilian context, three issues are assessed. First, the paper evaluates the possibility of deploying TT practices used by firms in similar industries, to enhance the effectiveness of TT process. Second, it verifies whether it is possible for the textile firms to use a stage-gate model to manage their TT processes, using as a normative framework the stage-gate model proposed by Jagoda and Ramanathan and Jagodaet al.Finally, possible changes to the stage-gate model are evaluated to specifically fit the Brazilian textile sector. This step is accomplished through four case studies from the Brazilian textile industry. Findings – The analyses of TT projects carried out by four companies show that there are many similarities and differences among the TT practices that are employed by the four companies that were investigated. The evaluation of the TT practices of the Brazilian textile companies against the stage-gate framework allowed authors to identify the gaps between the model and the TT practices of the companies investigated. Broader guidelines in adapting the stage-gate model to improve the TT process in the textile industry are discussed in the final part of this study. Originality/value – The TT process in the Brazilian textile industry is not a widely investigated phenomenon; however, this process has been critical to enhancing Brazil's competitiveness. Thus, providing a better framework to support the TT process in the local textile sector could be relevant information for improving management action in the area.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".