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September 10, 2025Science Journal of Business and ManagementOpen Access

Presenting a Model for Predicting the Risk of Technology Transfer Using the Backpropagation Algorithm Case Study: The Pharmaceutical-Nutritional Supplement Industry

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Authors

SSSaeed Shavvalpour HHHamideh Heydari

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Implication

This analysis finds technology transfer risk prediction using backpropagation in the pharmaceutical sector, indicating the complexity of tacit knowledge management.

Key Points

The proposed model predicts technology transfer risks in the pharmaceutical-nutritional supplement industry with 68% accuracy.
Key factors impacting technology transfer include tacit knowledge and methods of technology transfer.
The backpropagation algorithm is employed for assessing technology transfer risk in this industry.
Understanding risk assessment is critical for ensuring economic success and sustainability in technology transfer.

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Shavvalpour et al. (2025) studied this question.

synapsesocial.com/papers/68c1b36054b1d3bfb60ea793 https://doi.org/10.11648/j.sjbm.20251303.11

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Implication

This analysis finds technology transfer risk prediction using backpropagation in the pharmaceutical sector, indicating the complexity of tacit knowledge management.

Presenting a Model for Predicting the Risk of Technology Transfer Using the Backpropagation Algorithm Case Study: The Pharmaceutical-Nutritional Supplement Industry

Discussion

Member takes

Implication

Key Points

Cite This Study

Presenting a Model for Predicting the Risk of Technology Transfer Using the Backpropagation Algorithm Case Study: The Pharmaceutical-Nutritional Supplement Industry

Discussion

Member takes

Implication

Key Points

Cite This Study

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