The purpose of this paper is to investigate trends in the dimensions of low, medium, and high knowledge management (KM) capability of business process outsourcing (BPO) firms. It also explores the trends in BPO performance with different levels of KM capabilities of BPO firms. Moreover, the study determines how firm characteristics, such as size, age, industry, and outsourcing age, affect KM capability.
A survey was employed to collect data on managers from 605 firms. K-means cluster analysis was performed on the aggregate measures of the four KM capability dimensions and BPO performance to reveal trends. Subsequently, MANOVA was used to evaluate the effects of four firm characteristics on KM capability, and individual ANOVA tests were performed to examine the specific differences among the four dimensions.
Among the four dimensions of KM capability, knowledge application is the most significant. Knowledge protection is the second highest in terms of expressing the profile for low KM capability firms, but the lowest among the four dimensions of KM capability for medium and high KM capability firms. Each dimension of KM capability affects BPO performance positively. Firm size, age, industry, and outsourcing age differentially affect the dimensions of KM capability.
This study presents a theoretical model of firm characteristics, KM capability, and BPO performance. Through the model, ideas are offered: firms with high KM capability significantly differ from those with low and medium KM capabilities; different firms exhibit different KM capabilities; developing knowledge application capability should be the priority in managing BPO; and improving KM capability is an effective means to enhance BPO performance.
This work was supported by grants from the National Natural Science Foundation of China (Nos 71101060, 71471141, and 71201063). Shan Liu appreciates Zhaohua Deng to work as the corresponding author.
Liu, S. and Deng, Z. (2015), "Understanding knowledge management capability in business process outsourcing: A cluster analysis", Management Decision, Vol. 53 No. 1, pp. 124-138. https://doi.org/10.1108/MD-04-2014-0197
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