**6. Conclusions and discussions**

The results of this study showed that medical professionals had a certain tendency toward supportive systems that help their own fields and concurred that this type of system will always increase usage frequency but will also create dependence on the system to assist their medical strategies. It is evident, then, that medical professionals view usage of the online clinical guideline system as important to provide support and guidance for health‐care work, which corresponds the viewpoints of Isern and Moreno [6] and Dongwen et al. [8]. On the other hand, with regard to medical decisions, they will still depend on their own professional knowledge.

This study also found that medical professionals have a certain degree of satisfaction with the online clinical guideline system. Online clinical guidance system's user satisfaction with the user's conscious satisfaction has successfully increased the functionality and practicality of using the system and indirectly assisted professional health‐care employees to improve individual work performance. Simultaneously, users' satisfaction with the system is also an important factor determining continual usage of the system.

Regarding individual knowledge management behavior, this study developed two dimen‐ sions, "Knowledge Socialization" and "Knowledge Internalization," measuring personal knowledge management behaviors. Analysis of the results indicated that medical profession‐ als expressed a higher degree of individual knowledge internalization related to socializa‐ tion. When agreeing with individual knowledge internalization through "browsing of related professional websites," "obtaining expert knowledge," "educational training," "working," "observation," and related methods, individual knowledge can be increased. In individual knowledge socialization, through methods such as "internal and external department meet‐ ings," "sharing of ideas with colleagues," "team exchange of ideas," "discussion," and "semi‐ nars," a knowledge socialization effect can be achieved.

For individual net benefit, this study showed that medical professionals view the online clini‐ cal guideline system's usage to have a considerable impact on individuals' work and deci‐ sion‐making performance; notably, they expressed, "Using online clinical guideline system allowed for the quality of health‐care strategies to improve," and "An online clinical guideline system can increase my work efficiency." From this, it is evident that the usage of the online clinical guideline system has a positive effect on medical professionals' work performance.

Based on this study's results, the usage of the online clinical guideline system has a positive impact on individual knowledge management behavior and individual net benefit; moreover, individual knowledge management behavior has a positive impact on individual net benefit. In addition, the online clinical guideline system's satisfaction level has an impact on indi‐ vidual net benefit that is greater than that of the online guidance clinical system or individual knowledge management behavior.

Thus, hypotheses H1, H4, and H5 are supported. However, system use did not significantly influence knowledge internalization, user intention did not significantly influence individual net benefits, and individual knowledge socialization did not have a significant impact on indi‐

**Path coefficient** *t***‐Value**

0.192 2.21\*

0.185 2.29\*

0.205 2.35\*

0.008 0.11

0.068 1.2

0.149 2.90\*\*

0.191 1.80\*

0.306 3.48\*\*

0.549 8.27\*\*

0.050 0.83

0.183 2.83\*\*

User intention→ user satisfaction 0.526 7.45\*\* Actual system use →user satisfaction 0.228 3.06\*\*

User intention→knowledge

User intention→knowledge

Actual system use →knowledge

212 Knowledge Management Strategies and Applications

Actual system use→knowledge

User intention→individual net

User satisfaction→knowledge

User satisfaction→knowledge

User satisfaction→individual net

internalization→individual net

Sample size: 500 \**p* < 0.05; \*\**p* < 0.01.

Knowledge socialization→individual

Actual system use→individual net

socialization

socialization

internalization

internalization

benefit

benefit

benefit

benefit

net benefit

Knowledge

socialization

internalization

The results of this study showed that medical professionals had a certain tendency toward supportive systems that help their own fields and concurred that this type of system will always increase usage frequency but will also create dependence on the system to assist their medical strategies. It is evident, then, that medical professionals view usage of the online clinical guideline system as important to provide support and guidance for health‐care work,

vidual net benefit. As a result, hypotheses H2, H3, and H6 are partially supported.

Remarks: path coefficient's statistical significance testing utilized BT method to redraw.

**6. Conclusions and discussions**

**Table 2.** Structural method's path coefficient testing result.

This study uses PLS and constructs a full model of online clinical guideline behaviors. Besides, the integration of the clinical guidance system into the Internet allowed us to know medi‐ cal professionals' level of acceptance of the system by measuring their degree of satisfaction with using the system. This subsequently proved that medical professionals' acceptance level of the online clinical guideline system was recognized. Additionally, medical professionals, through the system's practical operation and usage, discovered that employees strongly value the practicality and reliability of data systems.

This study utilized a survey method focusing on only one medical center to investigate online clinical behavior and individual net benefit. Future research would be suggested to conduct the survey in multiple hospitals so as to improve the generalization of the research. In addition, due to the time restriction, this study fails to further explore the impact of online clinical guideline on patient satisfaction and health‐care quality. Future research is suggested to extend the effect on patient level so as to build a more comprehensive model toward the effectiveness of online clinical guidelines.
