Date of Award
Doctor of Philosophy (PhD)
Knowledge management systems (KMS) are a class of information systems used by organizations to support knowledge management initiatives. KMS come in many different forms, and serve multiple purposes in organizations. The pervasive implementation of KMS in practice has driven a continuing interest for information systems researchers to gain new insights into its multifaceted purpose. In theorizing the role of KMS in organizations, the majority of scholars have considered its potential in facilitating a wide range of knowledge management processes. Emerging from this early theoretical background, more recent empirical research has developed a firm understanding of the determinants of KMS use but is less clear on how KMS use influences task performance. As such, while theoretical literature has delivered valuable insights into the purposes that KMS serve, and empirical studies have revealed a broad range of antecedents of KMS usage, the central role of the human actor in using KMS to enhance performance has been underemphasized. This dissertation attempts to advance the understanding of how the use of KMS generates sustained value for organizations. In so doing, it builds from prior developments in information system use, organizational learning, and group learning literatures to draw new insights into how actors interact with technology to achieve desired task outcomes in the context of knowledge management.
This dissertation presents three papers which help to advance knowledge management research by expanding the KMS usage nomological network and identifying mechanisms which enable value creation. The first paper reviews empirical KMS articles published between 2001 and 2013 and suggests directions for future research. It presents a view of KMS as a socio-technical system with the primary purpose of transferring knowledge throughout the organization. This paper develops a guiding review framework identifying the organizational elements, behavioral actions, and knowledge outcomes that are inherent in KMS and argues that behavioral actions and knowledge outcomes may be viewed in future research as integrated parts of two value generating sub-processes: learning from technology and learning from task. I argue that the interplay between these sub-processes may present organizations with sustained value by helping to circulate knowledge between all three elements.
The second paper examines how acquisition behavior influences individual performance. Based on the assessment of acquisition constructs used in prior empirical research, and notions from self-regulation theory, I argue that acquisition behavior in the context of knowledge management consists of two primary dimensions: acquisition frequency and acquisition intensity. Furthermore, drawing from arguments in social cognitive theory, I build the case that the performance effects of each behavior are contingent on the personal knowledge (measured as professional experience) and social knowledge (measured as team participation) available to the acquiring individual. I test these hypotheses using a dataset of 18,219 real estate agents participating in a large real estate franchise through the use of hierarchical linear modelling (HLM), nesting individual agents within their franchise office and county. I find that the effects of acquisition frequency and acquisition intensity are positive and significant onto performance. Furthermore, acquisition frequency positively interacts with team membership while acquisition intensity positively interacts with professional experience.
Lastly, the third paper examines the influence of repository KMS usage on group performance when considering the contingencies of group composition. Building from the notion of learning mechanisms, I conceptualize repository KMS usage as a group learning mechanism which increases the amount of organizational knowledge disseminating throughout the work group. Additionally, I identify three
Sweeney, Jeffrey R., "On Value Creation from Knowledge Management Systems" (2017). Management Graduate Theses & Dissertations. 1.
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