本研究目的在探究技術知識資源特性,學習能力,核心競爭力與創新績效間之關係。透過97家高科技廠商的調查,以及運用多變量統計和倒傳遞類神經網路的方法,雖然兩種方法所得的結果相類似,不過倒傳遞類神經網路的方法的正確率較高。透過實證所得結論如下所示當技術知識資源的模組化程度念高時,對於核心競爭力的門檻能力和知識學習的問題解決能力為正向且顯著的影響,當技術知識資源的外顯與複雜程度愈高時,對於核心競爭力的重要性能力為正向且顯著的影響;當技術知識資源的路徑相依程度念高時,對於核心競爭力的未來性和知識學習的擴散能力為正向且顯著的影響,然而當技術知識資源的複雜程度愈高時,對於知識學習的擷取能力為負向且顯著的影響。另外,組織學習能力對於核心競爭力有顯著的正向相關;核心競爭力和知識學習能力對於創新績效為正向立顯著的影響。
This research aims at exploring the correlations among features of technical knowledge resources, learning ability, core competence and innovative performance. With the empirical study on 97 high-tech manufacturers, we compare the results from the multivariate analysis and backpropagation neural network system. Though the results of both methods are similar, a higher accuracy rate is obtained from the latter. Conclusions show that when the degree of modularization of technical knowledge resources is higher, the influences are positive and significant on threshold ability in core competence and problem-solving ability in knowledge learning. When the degree of complexity and explicitness is higher, the influences on the ability to importance are positive and significant. When the path dependency is higher, influences on the ability to future and to knowledge dissemination are positive and significant. However, when the degree of resource complexity is higher, the influences on ability to data access are negative and significant. In addition, learning ability of organization have significant and positive relation with on core competition. Core competence and knowledge learning ability have positive and significant influences on innovative performance.