Knowledge management in task-based working environment

2.1.1 Knowledge management systems and information technology

Knowledge Management (KM) is a cycle, sometimes repeated process, which generally includes creation, management and sharing activities. [17][26][28][55][82].

Organizations deploy Knowledge Management Systems (KMS) to maximize the effectiveness of knowledge assets in increasing organizational profitability and productivity [30][55]. Contemporary KMS employs Information Technologies (IT), such as document management and workflow management to facilitate the access, reuse and sharing of knowledge assets within and across organizations [17][39].

Generally, information technologies (ITs) mainly focus on two dimensions, explicit and tacit dimensions, to support knowledge management activities [11][29][39]. The former is achieved by codified approach. Intellectual content codified into explicit form can facilitate knowledge retrieval and reuse [12][89].

Knowledge repository, knowledge-based system, knowledge maps are the like to support knowledge storage, organization and dissemination [29][39][89]. The latter put emphasize on dialoging via social networks to facilitate knowledge sharing.

Knowledge expert directories, yellow pages, communities of practices and talk rooms are the like to support interpersonal communication to rapid knowledge sharing [3][13][39][41]. Several researches classified the knowledge management practices based on the two dimensions.

According to Gray (2001a) empirical finding that the knowledge codified into knowledge repository make knowledge workers highly exposit existing resources within organization, whereas community of practices that provide informal personal communication can moderate to explore new possibility. Kankanhalli et al. (2003) pointed out those product-based firms in a high-volatility context are rely both codification and sharing approaches. Xerox, Microsoft, Hewlett-Packard are the examples. In summary, the critical role of ITs are to assist knowledge workers in fully and economic reusing valuable knowledge assets by decreasing the level of skills required inaccomplishing the task successfully [28][39][49]. In addition, KMS with the aid of IT can assists workers in fully and economic reusing valuable

knowledge assets to accomplish the objective of task successfully.

2.1.2 Task-based knowledge retrieval

The repository of structured, explicit knowledge, especially document form, is a codified strategy to manage knowledge [17][29]. However, with the growing amount of information in organizational memories, KMSs face the challenge to help users find pertinent and needed information. The information can be delivered in a specific context of business environments. The information retrieval (IR) technique coupled with workflow management systems (WfMS) was employed to support proactively delivery of task-specific knowledge according to the context of tasks within a process [1][24]. Furthermore, a process meta-model specifying the knowledge-in-context is integrated with workflow systems to capture and retrieve knowledge within a process context [44]. Despite the subtle difference among these works, they provide an appropriate view to achieve knowledge support based on tasks. Moreover, knowledge retrieval is also considered a core component in task-based business environment to access knowledge items in knowledge repository [24][27].

Herein, we categorized the task-based knowledge management work from two perspectives: one is knowledge delivery with the aid of user modeling and the other is context-based proactively delivery knowledge. The perspective is departure from the points of process complexity and knowledge intensiveness [21]. Based on the above points, for classes of business process are derived which are low (or high) business process and weak (or strong) knowledge intensity. In the following, the related works of task-based knowledge management will be given according to the classifying of business process.

Task-based knowledge delivery with the aid of user modeling: This kind of knowledge management framework put emphasizes on codified (e.g., documents) knowledge retrieval and delivery in supporting workers' day-to-day tasks operation.

Translating users’ information needs into compromised queries is not an easy work [75]. Most systems rely on Information Retrieval (IR) techniques to access organizational codified knowledge. The technique of Information Filtering (IF) with a profiling approach to model users’ information needs is an effective approach to proactive delivering relevant information to users. The technique has been widely

used in the areas of Information Retrieval and Recommender Systems [31][52][58].

The profiling approach has also been addressed by some KMSs to enhance knowledge retrieval and further promote knowledge sharing among project-based or interesting groups [1][2][3][18]. Accordingly, the techniques of information filtering with intelligent agent-based architecture are commonly adopted in this type of framework to streamline the knowledge delivery from internal or external knowledge repositories [73][88]. Notably, a promising user modeling method, in which the system delivers the relevant information to the user profile is demanded in this type of knowledge support [7][71]. The idea of cooperative agent architecture has been proposed to achieve task-based Information filtering within work process [19]. Three types of cooperating agents: process agents, document warehouse agents and retrieval agents are designed for evaluating if the retrieved documents are relevant to the workers’ tasks at hand. Furthermore, a CodeBroker system is proposed for supporting software developer to reuse the organizational program components repository properly [88]. Similarly, the information filtering with user modeling and agent-based techniques are applied in the system for making delivered information relevant to the task-at-hand and personalized to the worker’s information needs. The task-based knowledge delivery with the aid of user modeling is quite suit applied in knowledge intensive task due to it has capability to model worker’s task needs and individual needs based on user modeling technique. The chief defect of this framework is that it generally cannot proper incorporate the contextual information of business task into the user profile.

Context-based proactively knowledge delivery: The information can be delivered in a specific context of business environments. To this end, KMSs increasingly emphasize the organization of all the possible task-specific knowledge by supporting context-aware knowledge access and retrieval [1][5][44]. The Kabiria system supports knowledge-based document retrieval in office environments by allowing users to conduct document retrieval according to the operational context of task-associated procedures [15]. Furthermore, a process meta-model specifying the knowledge-in-context is integrated with workflow systems to capture and retrieve knowledge within a process context [44]. That is, context becomes an impartment component that can be utilized for improving the understanding of relevant knowledge of business task within the KMS. Recently, the knowledge context model

is even proposed to support the collaborative work of virtual teams by utilizing the contextual information [4]. Furthermore, acquiring and disseminating role-relevant process views was considered in workflow environments [72]. Alvarado et al. (2004) also proposed acquiring and organizing corporate memory from the perspective of role/job position, in which an Organizational Memory is modeled by adopting UML/XML to specify the ontologies for organization positions, tasks, and application domains. The context-based knowledge delivery model is quite suit applied in knowledge intensive and non- routine task due to it has knowledge context model to capture or utilize the business process context for supporting task execution.

Furthermore, it can even support the operation of business process with high process complexity. However, the kind of knowledge support model still lacks in learning capability to support real time context sensitive knowledge delivery till know. That is, besides understanding the work context of the given task, the model also needs to learn and response the worker’s task-needs in the real time.

2.1.3 Knowledge sharing in community of practices

For complex and knowledge-intensive tasks, the collaboration among knowledge workers may arise around common goals, problems and interests. Domain experts or experienced workers who hold valuable tacit knowledge play important roles in assisting knowledge workers to accomplish business tasks [51]. The ultimate goal of KM is to enable innovative activities by promoting collaboration or communication among knowledge workers in organizations [26][84]. Collaboration may take place in a formal group such as a business project or in an informal group such as a community of practice. A community of practice consists of people who share common needs of information; hence, a community of practice is an effective approach to promote knowledge creation, transfer and sharing within or across organizations [3][13][18][41]. Although user profiles had been employed to stimulate knowledge disseminations in communities of practice, they did not consider the identification of peer-groups with similar task-needs to form communities in task-based business environments.