From table 4.3 to 4.6, the results for the descriptive statistics showed several elements in the organization context that need to be addressed. From technical perspective, the mean score for IT4 which referred top management ability to use IT to communicate with employees gathered the lowest mean score (M=3.24). Information technology is commonly perceived to be an effective tool in decreasing boundaries among organization members, supporting communication and facilitating collaboration among individuals. Therefore top management may consider making more use of information technology to communicate with employees to reinforce such perceptions. Top management sets the tone within the organization, it is thus crucial that they model all of the desired behavior that they want employees to emulate. As quoted in Lin and Jang (2008, p.604) ‘whatever management does, in whatever direction they push, and how hard they push dictates where the organization eventually goes’
In relation to the support from top management, the mean score for TM3 which indicated that top management provides rewards in efforts of building a knowledge sharing culture (M=3.21) was the lowest. Goodman and Darr (1998) study indentified rewards as an important element in fostering a knowledge sharing culture. With that said, management may need to consider providing adequate rewards in order to developing such a culture. This may indicate how much top management values knowledge sharing. When it comes to organization structure, two items OS1 and OS4 had the lowest mean scores. Therefore in order to increase the flexibility of the organization structure, management may consider addressing issues related to delegation of power and employee participation in decision making. Management may also encourage horizontal communication among members in organization units/ departments as a way to improve employees’ perceptions of organization structure’s flexibility.
Overall the mean scores for collaborative culture compared to other contextual factors were relatively lower. The highest mean score for collaborative culture was related to CC1 which is related with the perception of a supportive and collaborative attitude of organization members towards each other. However, the mean scores for CC2 (M=3.13) and CC3 (M=3.26) implied that employees collaborate to some extent. For example, for CC2 ‘there is a willingness to accept responsibility for failure’ and CC3 ‘there is a willingness to collaborate across organizational units’ indicated that such collaboration may not necessarily translate into a sense of collective
84
responsibility and transcend organization unit boundary. These results suggest that these aspects from a collaborative culture are lacking given that in such a culture, it would be expected that staff members come together to discuss, plan and mutually learn from each other as they share the collective responsibility for organization success. The lower mean for CC3 also indicates that there may be a lack of communication and interaction across organization units.
Furthermore the descriptive statistics results for knowledge sharing in table 4.7 and 4.8 indicated that employees in general had a propensity to share their tacit knowledge rather than their explicit knowledge with co-workers. The mean scores for tacit knowledge sharing were relatively higher than those for explicit knowledge sharing. The overall mean scores results for knowledge sharing showed that the two most common behaviors for tacit knowledge sharing included the ‘sharing of expertise at the request of co-workers’ (M=3.60) and the ‘sharing of job experience with co-workers’ (M=3.54). Whereas the most common observed behavior for explicit knowledge was the ‘sharing of printed or electronic copies of documents and/ or manuals with co-workers’ (M=3.48).
Moreover, the mean score results for tacit and explicit knowledge sharing also signaled that employees knowledge sharing behavior with colleagues seemed to depend on the type of information being shared. For example, the sharing ‘ideas about job with co-workers’ and ‘tips on jobs with co-workers’ gathered substantially lower mean scores (see table 4.10). This could be due to the fact that these modes of sharing may be perceived by employees as involving a competitive advantage cost. Mean scores for the sharing of ‘lectures/ presentations that they have personally prepared’ and ‘data/databases/spreadsheets they have kept for personal use’ also receded (see table 4.11). This could be due to the fact that individuals do not perceived any benefits for sharing the knowledge that they have recorded for personal use. Another possible reason could be sharing this type of knowledge is not articulate in their job responsibilities.
It is widely agreed that organizations that successfully implemented innovation has several important features that include support from top management, and most importantly the tolerance of failure given that failure is seen as a learning opportunity and therefore unsuccessful attempt should not be punished (Nacinovic, Galetic, & Cavlec, 2009). Descriptive statistics analysis results indicated that employees disagreed with the statement that organization members are penalized for ideas that do not work (M=2.84). The findings also showed that employees
85
somewhat agree that innovation is accepted in project/ program management (M=3.41).
Therefore reinforcing employees’ perception that innovation is desired for the organization may require as suggested by (Nacinovic et al., 2009) that innovation may be introduced as an important part of employees’ job which can be done by allocating the necessary time and resources for employees to pursue new ideas.
In relation to KMS effectiveness, the mean score results indicated that employees showed some level agreement with the system’s service quality which include ‘knowledge service has a range of service available to employees’ has a mean (M=3.56).Although the mean score for employees are treated courteously and sympathetically by the service workers’ is among the highest for KMS (M=3.53), its respective standard deviation (S.D=.950) was very high, thus implying that there is some inconsistency. Although the mean score for ‘employees suggest service requirement’ (M=3.40) is slightly lower, however the standard deviation (S.D. =.667) is the lowest, thus indicating that employees are consistent on answering this item.
The descriptive statistics results also showed various aspects of KMS knowledge service can be improved. KMS success is also determined by how well the knowledge service performs its intended function. The most crucial aspect of the knowledge service that need be emphasized upon include KM2 which refers to the knowledge scaffolding had the lowest mean (M=3.19).
Following KM8 ‘the knowledge service assures employees that their concerns and needs are important’ (M=3.21) and KM7 ‘service is reliable, dependable and accurate’ (M=3.24) and KM1
‘all users are able to understand all aspects of the system’ (M=3.26) all gathered low mean scores.
Researchers have indicated that KMS success depends on the perceived usefulness of the system, perceived ease of use/ perceived user friendliness, ability of the user to identify system content, and knowledge quality (Adams & Lamont, 2003; Kuo & Lee, 2009; Whitfield, 2008). If employees do not find valuable knowledge in the KMS that they need to carry out their tasks or increase their performance or if employees cannot locate nor have access to the required knowledge, they may refrain from using KMS which may lead to the system’s failure. Halawi, McCarthy, and Aronson (2007/2008) study findings indicated that the knowledge quality and the system quality of KMS were positively associated to user intention to use the system.
86
Moreover, Withfield (2008) stressed that a KMS that does not provide knowledge that is considered valuable for the organization or does not provide it in a timely manner is considered a failure. In addition a good KMS design must also consider the problem of system design (Kuo &
Lee, 2009). Employees are the main users of KMS, their concerns and needs should be made a priority. With that said, the knowledge staff or KM developers should collaborate with organization members in order to identify ways in which the system can be developed or upgraded to meet users’ needs and to overcome resistance to the system.
87