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This study aims to minimize the research gap by finding out what are the current state of knowledge management (KM) in the Chinese private science and technology organizations, the essential factors for promoting KM behaviors and the role of knowledge-oriented leadership in determining employees’ KM behaviors. Specifically, this research attempts to create a theoretical framework, which can be used to facilitate KM implementation in general, in the Chinese context in particular.

Semi-structured interviews with executives, senior managers and specialists were used to capture interviewees’ responses to the research question. The responses were analyzed with Nvivo to detect the obstacles of KM behaviors within Chinese private science and technology organizations.

This study highlights that poor KM behaviors are caused by knowledge-oriented leaders’ weak awareness of the KM values, and also these leaders are not equipped with the necessary knowledge-oriented leadership skills. As a result, there is a lack of knowledge sharing and knowledge inheritance. To respond to the identified KM related issues, while maximizing the KM values, some effective countermeasures focusing on the strategic, managerial as well as operational levels are proposed.

There is a need for knowledge-oriented leaders to recognize the growing significance of KM practices, and to increase the level of awareness of KM values. To achieve such ambition, they need to build a corporate knowledge culture, which promotes knowledge development, application, preservation, sharing and inheritance.

This study contributes to deepening the understandings of the linkage between knowledge-oriented leadership and KM behaviors, which is of great significance to promote the soft power of KM on employees’ attitudes and behaviors.

In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this research develops a product pattern design system based on computer-aided design.

First, use the Kansei engineering theory and method to obtain the user's perceptual image, and deconstruct and encode the pattern based on the morphological analysis method, then through the BP neural network to construct the mapping relationship between the user's perceptual image and the pattern design elements, and finally calculate and find the corresponding design code combination according to the design goal to guide the pattern design.

Taking costume paper-cut patterns as an example, the feasibility of this system is verified, the design system can well reflect the user's perceptual image in the pattern design and improve the efficiency of pattern customization service.

Compared with the traditional method that relies on the designer's personal experience to propose a design plan, this research provides scientific and intelligent design methods for product pattern design.