Knowledge that Transforms

Organizations are attempting to leverage their knowledge resources by employing knowledge management (KM) systems, a key form of which are electronic knowledge repositories (EKRs). A large number of KM initiatives fail due to the reluctance of employees to share knowledge through these systems. Motivated by such concerns, this study formulates and tests a theoretical model to explain EKR usage by knowledge contributors. The model employs social exchange theory to identify cost and benefit factors affecting EKR usage, and social capital theory to account for the moderating influence of contextual factors. The model is validated through a large-scale survey of public sector organizations. The results reveal that knowledge self-efficacy and enjoyment in helping others significantly impact EKR usage by knowledge contributors. Contextual factors (generalized trust, pro-sharing norms, and identification) moderate the impact of codification effort, reciprocity, and organizational reward on EKR usage, respectively. It can be seen that extrinsic benefits (reciprocity and organizational reward) impact EKR usage contingent on particular contextual factors whereas the effects of intrinsic benefits (knowledge self-efficacy and enjoyment in helping others) on EKR usage are not moderated by contextual factors. The loss of knowledge power and image do not appear to impact EKR usage by knowledge contributors. Besides contributing to theory building in KM, the results of this study inform KM practice.

Individual adoption of technology has been studied extensively in the workplace. Far less attention has been paid to adoption of technology in the household. In this paper, we performed the first quantitative test of the recently developed model of adoption of technology in households (MATH). Further, we proposed and tested a theoretical extension of MATH by arguing that key demographic characteristics that vary across different life cycle stages would play moderating roles. Survey responses were collected from 746 U.S. households that had not yet adopted a personal computer. The results showed that the integrated model, including MATH constructs and life cycle characteristics, explained 74 percent of the variance in intention to adopt a PC for home use, a significant increase over baseline MATH that explained 50 percent of the variance. Finally, we compared the importance of various factors across household life cycle stages and gained a more refined understanding of the moderating role of household life cycle stage.

To better explain resistance to information technology implementation, we used a multilevel, longitudinal approach. We first assessed extant models of resistance to IT. Using semantic analysis, we identified five basic components of resistance: behaviors, object, subject, threats, and initial conditions. We further examined extant models to (1) carry out a preliminary specification of the nature of the relationships between these components and (2) refine our understanding of the multilevel nature of the phenomenon. Using analytic induction, we examined data from three case studies of clinical information systems implementations in hospital settings, focusing on physicians’ resistance behaviors. The resulting mixed-determinants model suggests that group resistance behaviors vary during implementation. When a system is introduced, users in a group will first assess it in terms of the interplay between its features and individual and/or organizational-level initial conditions. They then make projections about the consequences of its use. If expected consequences are threatening, resistance behaviors will result. During implementation, should some trigger occur to either modify or activate an initial condition involving the balance of power between the group and other user groups, it will also modify the object of resistance, from system to system significance. If the relevant initial conditions pertain to the power of the resisting group vis-à-vis the system advocates, the object of resistance will also be modified, from system significance to system advocates. Resistance behaviors will follow if threats are perceived from the interaction between the object of resistance and initial conditions. We also found that the bottom-up process by which group resistance behaviors emerge from individual behaviors is not the same in early versus late implementation. In early implementation, the emergence process is one of compilation, described as a combination of independent, individual behaviors. In later stages of implementation, if group level initial conditions have become active, the emergence process is one of composition, described as the convergence of individual behaviors.

Individuals’ knowledge does not transform easily into organizational knowledge even with the implementation of knowledge repositories. Rather, individuals tend to hoard knowledge for various reasons. The aim of this study is to develop an integrative understanding of the factors supporting or inhibiting individuals’ knowledge-sharing intentions. We employ as our theoretical framework the theory of reasoned action (TRA), and augment it with extrinsic motivators, social-psychological forces and organizational climate factors that are believed to influence individuals’ knowledge-sharing intentions. Through a field survey of 154 managers from 27 Korean organizations, we confirm our hypothesis that attitudes toward and subjective norms with regard to knowledge sharing as well as organizational climate affect individuals’ intentions to share knowledge. Additionally, we find that anticipated reciprocal relationships affect individuals’ attitudes toward knowledge sharing while both sense of self-worth and organizational climate affect subjective norms. Contrary to common belief, we find anticipated extrinsic rewards exert a negative effect on individuals’ knowledge-sharing attitudes.

This paper investigates how an organizational competence in boundary spanning emerges in practice by drawing on the concepts of boundary spanner and boundary object. Using data from two qualitative field studies, we argue that in order for boundary spanning to emerge a new joint field of practice must be produced. Our data illustrate that some agents partially transform their practices in local settings so as to accommodate the interests of their counterparts. While negotiating the new joint field, these agents become what we call boundary spanners-in-practice who produce and use objects which become locally useful and which acquire a common identity—hence, boundary objects-in-use. Moreover, we show how boundary spanners-in-practice use various organizational and professional resources including the influence that comes with being nominated to boundary spanners’ roles to create the new joint field. The conditions necessary for boundary spanners-in-practice to emerge are outlined and discussed, as are important implications for IS implementation and use.

Electronic networks of practice are computer-mediated discussion forums focused on problems of practice that enable individuals to exchange advice and ideas with others based on common interests. However, why individuals help strangers in these electronic networks is not well understood: there is no immediate benefit to the contributor, and free-riders are able to acquire the same knowledge as everyone else. To understand this paradox, we apply theories of collective action to examine how individual motivations and social capital influence knowledge contribution in electronic networks. This study reports on the activities of one electronic network supporting a professional legal association. Using archival, network, survey, and content analysis data, we empirically test a model of knowledge contribution. We find that people contribute their knowledge when they perceive that it enhances their professional reputations, when they have the experience to share, and when they are structurally embedded in the network. Surprisingly, contributions occur without regard to expectations of reciprocity from others or high levels of commitment to the network.

For the last 25 years, organizations have invested heavily in information technology to support their work processes. In today’s organizations, intra-and interorganizational work systems are increasingly IT-enabled. Available evidence, however, suggests the functional potential of these installed IT applications is underutilized. Most IT users apply a narrow band of features, operate at low levels of feature use, and rarely initiate extensions of the available features. We argue that organizations need aggressive tactics to encourage users to expand their use of installed IT-enabled work systems. This article strives to accomplish three primary research objectives. First, we offer a comprehensive research model aimed both at coalescing existing research on post-adoptive IT use behaviors and at directing future research on those factors that influence users to (continuously) exploit and extend the functionality built into IT applications. Second, in developing this comprehensive research model, we provide a window (for researchers across a variety of scientific disciplines interested in technology management) into the rich body of research regarding IT adoption, use, and diffusion. Finally, we discuss implications and recommend guidelines for research and practice.

An enterprise information portal (EIP) is viewed as a knowledge community. Activity theory provides a framework to study such a community: members of an EIP conduct specific tasks that are assigned through a division of labor. Each member of an enterprise information portal can undergo three distinct types of learning processes: learning-by-investment, learning-by-doing, and learning-from-others. Through these three types of learning processes, each member achieves specialized knowledge that is related to his or her own task. Cumulative knowledge resulting from the learning processes is considered in terms of two distinct attributes: depth and breadth of knowledge. This paper formulates a mathematical model and defines the goal of an EIP member as maximizing the net benefits of knowledge resulting from individual investment and effort. Numerical examples are provided to analyze patterns of optimal investment and effort plans as well as the resulting accumulated knowledge. The results provide useful managerial implications. In business conditions characterized by high interest rates or high internal rate of returns, it is preferable for members to delay spending their resources for learning. Intensive investment and efforts to obtain knowledge are preferable when the discount rate of costs is high, when knowledge is durable, when the value of knowledge is high, when the initial level of knowledge is high, when the productivity of the learning process is high, and when sufficient knowledge is transferred from other members. On the other hand, the size of the EIP has a positive or negative effect depending on the attribute of knowledge and the productivity of learning processes. Further properties of the optimal decisions and learning processes are analyzed and discussed.

This paper defines user adaptation as the cognitive and behavioral efforts performed by users to cope with significant information technology events that occur in their work environment. Drawing on coping theory, we posit that users choose different adaptation strategies based on a combination of primary appraisal (i.e., a user’s assessment of the expected consequences of an IT event) and secondary appraisal (i.e., a user’s assessment of his/her control over the situation). On that basis, we identify four adaptation strategies (benefits maximizing, benefits satisficing, disturbance handling, and self-preservation) which are hypothesized to result in three different individual-level outcomes: restoring emotional stability, minimizing the perceived threats of the technology, and improving user effectiveness and efficiency. A study of the adaptation behaviors of six account managers in two large North American banks provides preliminary support for our model. By explaining adaptation patterns based on users’ initial appraisal and subsequent responses to an IT event, our model offers predictive power while retaining an agency view of user adaptation. Also, by focusing on user cognitive and behavioral adaptation responses related to the technology, the work system, and the self, our model accounts for a wide range of user behaviors such as technology appropriation, avoidance, and resistance.