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The Optimal Sequential Strategy of Learning Ambidexterity for High-tech Product R&D Project Based on the Knowledge Accumulation |
Rong Jian1,2,Liu Xilin1,Tong Zehua2 |
1.School of Management, Northwestern Polytechnical University, Xi'an 710072,China;2.School of Business, Shandong University of Technology, Zibo 255049,China |
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Abstract High-tech product is the integration of high-tech knowledge, and its R&D status has become one of the decisive factors in the growth of knowledge economy. Focused on the mechanism of organizational learning-knowledge stock-R&D performance, an optimal model of dynamic ambidexterity is introduced. After the model solving, results are obtained about the decision making of the optimal termination point, the optimal switching point, and the optimal input intensity of exploration and exploitation. Based on these results the optimal sequential ambidexterity strategy is given for the maximization of high-tech product's R&D performance. All of these conclusions can provide reference for the control of R&D rhythm, the formulation of learning strategy and the allocation of investment resources in the implementation of high-tech product development projects.
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Received: 06 June 2017
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Corresponding Authors:
Rong Jian
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