Motivation, Trust, Leadership, and Technology: Predictors of Knowledge Sharing Behavior in the Workplace

of the Dissertation Motivation, Trust, Leadership, and Technology: Predictors of Knowledge Sharing Behavior in the Workplace By Shabnam Ozlati Claremont Graduate University: 2012 Employees’ knowledge is a critical resource for the organization, and if it is not shared, it is lost to other employees and the organization. However, knowledge sharing does not happen easily; knowledge sharing is a personal choice that cannot be forced. This study employs Self-Determination Theory (SDT) as a theoretical framework to study employees’ knowledge sharing behavior and motivations. Data were collected from full-time working professionals (N=208) using an online survey. The effects of autonomy, motivation, trust, authentic leadership style, knowledge self-efficacy, and technology were studied using moderated and mediated regression analyses. The results reveal (a) knowledge is shared more when individuals have more autonomy; (b) benevolence-based and institution-based trust had a moderating effect on autonomy and knowledge sharing behavior (when autonomy was low, if benevolencebased or institution-based trust was high more knowledge sharing occurred); (c) competence-based trust did not have a similar moderating effect, but had a significant main effect predicting knowledge sharing; and (d) a supervisor’s authentic leadership style contributed in explaining the total variance of knowledge sharing behavior and predicted knowledge sharing after controlling for autonomy. All three types of trust mediated the relationship between authentic leadership style and knowledge sharing. Moreover, knowledge self-efficacy is a strong predictor of knowledge sharing, while users’ perception of technology is a moderate predictor. Additionally, a factor analysis was conducted on 15 different types of knowledge sharing technologies used by participants. Technologies were clustered into three groups: a low-interactive group of technologies (e.g., databases), and two high-interactive groups of technologies (e.g., blogs, social networks and emails). The low-interactive group and one of the high-interactive groups of technologies were positively associated with different types of trust. However, the high-interactive groups of technologies which consisted of technologies such as blogs, and social networks was not correlated with different types of trust. Only the high-interactive group of technologies that was positively correlated with trust predicted knowledge sharing. This dissertation advances prior findings and contributes to knowledge sharing research and practice. The current study was the first to examine relationships between authentic leadership style and knowledge sharing, proved that SDT is a strong framework in predicting knowledge sharing behavior and motivations, and showed only highinteractive technologies that are positively linked with trust predict knowledge sharing. Organizations could use these findings to develop appropriate strategies and trainings to foster a knowledge-sharing environment.