Knowledge sharing is a popular research topic; however, the construct has not been well defined theoretically or in terms of how to operationalize it, as there appears to be little consistency. This apparent lack of consistency is problematic for developing a cumulative understanding of the predictors and outcomes of this behavior. This study examines how other researchers have operationalized knowledge sharing, and conduct a qualitative study to further understand this construct. A knowledge sharing and hoarding classification system is developed, and six knowledge sharing behavioral categories are identified. Finally, recommendations are made for future research in knowledge management.
TopIntroduction
Bill* works in a highly competitive firm in the energy industry. When Denise, a junior associate in the firm, asks Bill for help, he is willing to share any bit of knowledge or expertise he can to help her learn and develop her skills. However, when his close colleague Jenna asks Bill for help, he calculates what knowledge she needs and what knowledge he’s willing to give her and then shares accordingly. He refuses to share any knowledge that gives him his competitive edge over her for promotions; instead, he gives her more “basic knowledge” to assist her with the immediate problem at hand. When asked about sharing through intra-organizational broadcast media such as mass e-mail or the organization’s intranet, Bill guffaws and remarks he hasn’t the time.
Darryl, a project manager in software development, considers himself to be exemplary when it comes to knowledge sharing. He believes very strongly that sharing his knowledge is a part of his job duties as a manager, but that it is also important to share knowledge to set an example for others. He shares not only with individuals directly, but also through the knowledge repository. There is very little that Darryl would consider withholding from a colleague, unless it was of a very confidential nature or on a need-to-know basis.
Allison is a programmer whose organization supports the use of a knowledge repository. Allison enjoys contributing to the repository and does so, on a regular basis. When asked why she enjoys using the repository she replies, “Well, that way I don’t have to deal with all those annoying people asking annoying questions. I can just tell them where to go for the answers!”
* Names have been changed to protect anonymity.
These above scenarios illustrate employees sharing their knowledge within their organizations. All three individuals believe their stories illustrate knowledge sharing, although none of them always fully disclose all of their knowledge. Knowledge sharing is thus a complex phenomenon that cannot be validly conceptualized as a simple binary yes/no behavior. The goal of this study is to examine the complexities of the knowledge sharing construct, from a theoretical and empirical perspective.
There are various ways to share one’s knowledge, and a variety of behaviors can constitute knowledge sharing as illustrated in the opening vignettes. Previous approaches used by researchers to measure knowledge sharing include: media individuals use to communicate the knowledge (e.g., documents and manuals: Bock & Kim, 2002; Lin, 2008); types of knowledge intended to be shared or shared (e.g., Bock, Zmud & Kim, 2005; Kang, Kim & Chang, 2008; Szulanski, 2000); and a single, self-reported item that asks “Do you (intend to) share your knowledge?” (e.g., Fraser, Marcella & Middleton, 2000). Others assume knowledge sharing has occurred successfully or not successfully and investigate contextual variables and outcome variables to the knowledge sharing without actually measuring knowledge sharing (e.g., Buckman, 1998; Lahneman, 2004; Lemons, 2005; Pan & Scarbrough, 1998; Strickland, 2004). Therefore, not surprisingly, it has been noted that “no established and validated [knowledge sharing] measure exists” (Thompson & Heron, 2006, p. 37).
Multiple measures are problematic for the knowledge management field because different operationalizations of the same construct may influence relationships with other constructs and implies “Theory Shyness,” (Kruglanski, 2001). Kruglanski defines theory shyness as the tendency for researchers to fall short of the goal of developing grand theory (theory that is generalizable across contexts and phenomena) and becoming more data-driven (e.g., Sutton & Staw, 1995). The negative consequences of theory shyness include inventing new names for similar concepts, fragmentation of the field, declining interest value of the field’s articles, and isolation from general cultural dialogue (i.e., academic articles become disjointed from practitioner understanding and debate) (Kruglanski, 2001). Therefore, a comprehensive, theoretically-grounded operationalization of knowledge sharing, which is relevant to organizations, is needed. The purpose of this study is to operationalize knowledge sharing in a theoretical manner to enable future research to further develop a measure.