The purpose of this paper is to identify the several key drivers for developing organizational KM capability and examining their relationships with KM performance. It shows that despite the active interest in managing organizational knowledge as a strategic resource, most organizations do not yet understand the challenges involved in implementing KM initiatives.
In the paper data was collected from a questionnaire survey of 66 Korean firms. The structural equation modeling technique called Partial Least Squares method was chosen for analyzing the research model.
The paper found that KM drivers such as learning orientation, KM system quality, reward, and KM team activity were significantly related to the organizational KM performance – knowledge quality and user knowledge satisfaction. The paper also found that a KM team activity and a reward system have significant effects upon other KM drivers. In addition, the KM stage of an organization was found to have a significant and positive effect on KM team activity.
The paper shows that the sample consists of organizations from only one country, which reduces the generalizability of the results obtained. The paper also shows that the KM stage of the respondent organizations is skewed toward the low stage, which also reduces the representativeness of our sample.
The results of this paper are helpful for researchers to examine and identify the characteristics of KM that may enhance certain outcomes of KM. The paper also shows that a KM team can obtain some direction toward understanding and evaluating KM performance.
This paper identifies the key management drivers to improve KM performance.
Starting from industry 4.0 in Germany and followed by the New Strategy for American Innovation in the USA and the smartization strategy in Japan, developed countries are…
Starting from industry 4.0 in Germany and followed by the New Strategy for American Innovation in the USA and the smartization strategy in Japan, developed countries are pushing nation-wide innovation strategies. Similarly, China is pursuing the Made in China 2025, and Korea announced the Manufacturing Industry Innovation 3.0 strategy. However, few researchers have identified the industrial structure that establishes the foundation of the 4th Industrial Revolution or have derived strengths and weaknesses to provide implications on policy formulation through quantitative comparison with developed countries. Therefore, the purpose of this paper is to analyze the spillover effect of the information and communication technology (ICT) industry (the foundation of the 4th Industrial Revolution) and machinery·equipment industry (the foundation of smart manufacturing through convergence with ICT industry).
This study examines the industrial spillover effects of the ICT industry and machinery·equipment industry in the USA, Germany, Japan, China and Korea by using the World Input–Output Table from 2000 to 2014.
The results showed that backward linkage effect of the ICT Industry are high in the order of Korea≑China>Japan>the USA≑Germany, and forward linkage effect of the ICT industry are high in the order of Japan ≑> the USA≑Korea ≑> China ≑> Germany. Backward linkage effects of the machinery·equipment industry are high in the order of China>Japan≑Korea>the USA>Germany, and forward linkage effects of the machinery·equipment industry are high in the order of China>Korea>Germany≑Japan≑the USA.
China and Korea encourage active government investment in ICT and machinery·equipment industries, especially the intentional convergence between ICT and machinery·equipment industries is expected be generate higher synergy. The “innovation in manufacturing” strategy in the USA that utilizes its strength in ICT services seems appropriate, whereas Germany needs to revitalize the ICT industry to strengthen its manufacturing industry. Japan’s strategy is to focus its ICT capabilities on robot sector. While the scope of innovation is limited, its synergy is worth expecting.
This study attempted to provide a theoretical approach to the determination of national policy strategies and provide practical implications for response to the impacts of the 4th Industrial Revolution, by comparing the inducement effects of ICT and machinery·equipment industries between major countries.