| Summary: | 碩士 === 國立成功大學 === 國際企業研究所碩博士班 === 97 === Innovation will be critcial and for the company, and Knowledge Stock always that the company own has the siginificant affect on innovation. However, the imporatnce of External Search on innovation development is getting more and more. Previous research has shown the result about External Search's effect, but there is no study to discuss the comprehensive effects on innovation outcome between External Search and Knowledge Stock. So this research is mainly designed to examine the moderating effects of Knowledge Stock. In this research, there are two diemensions to analyse and represent the three constructs respectively.
The primary sample of this study is the american semiconductor industry. According to the company list from the database, there are 186 companies on the list. The next step is to find out the patent data of all the companies, and there are 162 companies that have the patent data. After the deleting process that companies have missing observation, there are still 59 companies in our sample. In addition, this research use the Negative Binomial Regression estimation to test resaerch hypotheses. Besides, there are two regressions to stand for the Innovation Quality and Innovation Quantity respectively.
Our findings can be summarized as follows. First, External Search has the most optimal point to affect the Innovation Quality, without respect to External Search breadth or depth. Secondly, in the quality diemension, the best moderating effect is between External Search depth and Knowledge Stock breadth. Finally, Knowledge Stock has the more significant effect than External Search in the quantity diemension. These findings may contribute to the acaemic research and practical implications.
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