The model by Kulkarni et al. (2007) was the only model of KMS success that covered both system and organisational factors (see section 2.4.1 for a discussion of KMS success models). As the research questions of the present study suggest formulating a model involving both system and organisational factors, the model by Kulkarni et al. is of particular interest. Therefore, the study by Kulkarni, which was initially introduced in section 2.4.1, in Table 2-3, is discussed in detail in this section.
Kulkarni et al.’s (2007) KM success model (see Figure 2-5) was developed based on the IS success model of DeLone and McLean (2003). Kulkarni et al. followed Wu and Wang (2006) by interpreting net benefits as the use of knowledge. As discussed in section 2.4.1, although the consequences of knowledge use, such as knowledge worker productivity, are more interesting from the management practice perspective than the knowledge use behaviours per se, it is difficult to measure such consequences.
Kulkarni et al. (2007) followed Wu and Wang (2006) in replacing the system use construct in the DeLone and McLean IS success model by perceived usefulness of knowledge
sharing. As discussed section 2.5, this was motivated by the argument by Seddon (1997) that system use is a consequence of perceived KMS benefits, rather than an antecedent. The model included organisational support factors of leadership, incentives, co-worker support, and supervisor support. The leadership concept represented the extent of support of KM by the management by means other than direct incentives. The incentives construct reflected the support via monetary rewards and promotion opportunities. Although Kulkarni et al. justified the inclusion of the leadership and incentives constructs by referring to the structuration theory from microeconomics, it seems to be much more straightforward to justify the inclusion of these constructs by considering the practice of knowledge management at organisations from the point of view of the transformational and transactional leadership theory by Burns (1978) and Bass (1985), which was introduced in section 2.3.3. The incentives construct corresponds to transactional leadership, and the leadership construct in the Kulkarni et al. model corresponds to transformational leadership.
The co-worker and supervisor concepts represented the support and encouragement of sharing knowledge by the respondents’ co-workers and supervisors. Kulkarni et al. justified the inclusion of the co-worker and supervisor constructs based on the social exchange theory (which was introduced in section 2.3.5). Nonetheless, the items used to measure these constructs did not address interaction, which is an essential part of the social exchange theory. Arguably, these constructs could be justified by referring to subjective norm (see section 2.3.2) and to TAM2 (Venkatesh & Davis, 2000). The TAM2 model suggests that subjective norm affects perceived usefulness. This matches the hypotheses that co-worker and supervisor affect perceived usefulness of knowledge sharing in the Kulkarni et al.’s model.
In terms of content, the content of the co-worker construct in Kulkarni’s study seems somewhat ambiguous. The WordNet entry for term co-worker is “colleague, co-worker, fellow worker, workfellow (an associate that one works with)”. (WordNet is a lexical database at http://wordnet.princeton.edu maintained by Princeton University in the US.) Supervisors may be regarded as co-workers in cultures with low power distance—see, for example, the phenomenological study of supervision by Clarkson and Aviram (1995). Thus, in certain contexts the content of the co-supervisor concept can be seen as having a large overlap with the supervisor concept (even though in case of the data Kulkarni et al.
used to test the model there were no discriminant validity problems between supervisor and co-worker constructs).
The perceived usefulness of knowledge sharing concept represented the extent to which an employee believes that using knowledge sharing capabilities existing at her (or his) organisation can improve her (or his) performance. The items used for this concept did not mention the use of KMS for sharing and contributing, but referred to all possible knowledge sharing capabilities (e.g. sharing via informal face-to-face meetings, not involving KMS). With such a broad view of knowledge sharing, the hypothesis that KMS quality (which was measured by items explicitly suggesting an IT-based system) affects perceived usefulness of knowledge sharing appears to be not entirely justified. Having low opinion of the IT capabilities available does not prevent one from taking a view that informal face-to-face knowledge sharing is highly useful.
The model was tested using data collected in a cross-sectional survey. The survey was administered to a group of 150 midlevel managers enrolled in executive MBA and part- time professional MBA programs at a university in the United States. The respondents represented a broad range of industries. It appears that the questionnaire asked the respondents if they have a “KM program” at their organisation; 22 questionnaires were judged not usable because “the respondents had no KM program in their function” (the article does not explain how respondents that “had no KM program” were distinguished). The article states that the job responsibilities of the respondents showed that they would be routinely involved with knowledge work. Thus, it would appear that excluding these respondents was not necessarily justifiable, unless they had no access to IT enabling knowledge sharing (such as email). Of the 150 questionnaires returned, 111 were used in data analysis (17 questionnaires with uncompleted sections were also excluded).
In the analysis of convergent and discriminant validity, only one item (for the knowledge use construct) was dropped. The item referred to the use of a scheme for classifying knowledge, and dropping it somewhat changed the content of the measure, as a scheme for classifying knowledge was not covered by the remaining items. Dropping the item did not change the essential meaning of the construct.
Fitting the data by using a covariance based SEM technique (with LISREL software), Kulkarni et al. found that the model fit, as measured by RMSEA, NNFI, and CFI global fit
indices, was acceptable according to the criteria suggested by Hartwick and Barki (1994) and Segars and Grover (1993). On the other hand, the value of SRMR was considerably higher than the cut-off recommended by Hu and Bentler (1998), and the value of CFI did not pass the more stringent criterion suggested by Hu and Bentler. The problems with overall fit are not surprising, because the data set was smaller than recommended for analysis using co-variance based techniques (see section 5.4 for a discussion of data set sizes needed for different SEM analysis techniques).
Path coefficients obtained in an alternative analysis using multiple regression were overall consistent with the path coefficients obtained using covariance based SEM. Kulkarni et al. (2007) did not report the values of average variance explained (R2) for dependent constructs.
Organizational Support
Leadership Incentive Coworker Supervisor
Knowledge Content Quality KMS System Quality Perceived Usefulness of Knowledge Sharing User Satisfaction Knowledge Use
Figure 2-5.KM success model (Kulkarni et al., 2007).
Leadership and incentives had medium to large effects on knowledge use and knowledge content quality; co-worker had medium effect, but supervisor had weak effect. Knowledge content quality and system quality did not affect perceived usefulness of knowledge sharing, which was not surprising because perceived usefulness of knowledge sharing did not explicitly relate to using the system (as discussed earlier in this section).
The effects of both leadership and incentives on knowledge use were stronger than the effect of user satisfaction (perceived usefulness was not found to affect knowledge sharing).
The findings from Kulkarni et al.’s (2007) study suggest the importance of organisational factors in determining KMS success.