Knowledge Management in Collaborative Business Networks

Knowledge Management in Collaborative Business Networks

Alexander Smirnov (St.Petersburg Institute for Informatics and Automation Russian Academy of Science (SPIIRAS), Russia), Tatiana Levashova (St.Petersburg Institute for Informatics and Automation Russian Academy of Science (SPIIRAS), Russia), Nikolay Shilov (St.Petersburg Institute for Informatics and Automation Russian Academy of Science (SPIIRAS), Russia) and Alexey Kashevnik (St.Petersburg Institute for Informatics and Automation Russian Academy of Science (SPIIRAS), Russia)
Copyright: © 2014 |Pages: 13
DOI: 10.4018/978-1-4666-5202-6.ch124
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Abstract

Current worldwide economy conditions cause increasing popularity of collaborative business networks. Dealing with multiple organizations and multiple processes within a complicated network, identifying and locating a member that has a responsibility and/or a competence in a particular part of the network can be a laborious, time-consuming process. Knowledge management technology is aimed to assist in solving this problem. It requires intelligent interoperability support between information systems of collaborative network members. A presented approach is based on the context management technology. It allows allows describing the collaborative network at a particular moment. The context includes such current situation properties as time, location, competence profiles of collaborative network members, etc. The competence profiles allow formalizing and sharing member's knowledge and competencies.
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Background

The most significant problem is coordination of a large number of independent network members. While dealing with multiple organizations and processes within a complicated collaborative business networks, identifying and locating a member that has responsibility and/or competence in a particular part of the network can be a laborious and time-consuming process (Lesser & Butner, 2005). Developing and maintaining a common distributed knowledge directory for all relevant parties associated with troubleshooting and potential problem solving can significantly reduce the production lead time and network flexibility. Moreover, linking this directory to key decision points and frequent problems can further enhance its effectiveness (Smirnov, Shilov, & Kashevnik, 2008).

Efficient profiling has become one of the major requirements for efficient sharing of knowledge in collaborative business networks (e.g., Sandkuhl et al., 2007). The major components of the profile include competences (a possibility to perform business processes that are supported by necessary resources, practice and actions), preferences (e.g., types of tasks the network member prefers to perform), contact and auxiliary information (e.g., time zone and supported languages). Usage of this information significantly increases the speed and accuracy of the negation processes related to collaborative business network configuration.

Key Terms in this Chapter

Collaborative Business Networks: Is co-operation of companies for producing a certain production or services.

Knowledge Management: Comprises a range of strategies and practices for creating, collection, keeping, utilizing, and provide access to information resources. These recourses include structured databases, text information, and implicit knowledge.

Competence Profile: Is a model of collaborative business network member which describes the main characteristics of the member to use in knowledge management system.

Interoperability: Is the ability of information systems belonging to collaborative business network members to work together and understand each other.

Ontology: Is an explicit specification of the structure of the certain domain that includes a vocabulary (i.e. a list of logical constants and predicate symbols) for referring to the subject area, and a set of logical statements expressing the constraints existing in the domain and restricting the interpretation of the vocabulary; it provides a vocabulary for representing and communicating knowledge about some topic and a set of relationships and properties that hold for the entities denoted by that vocabulary.

Object-Oriented Constraint Network Formalism (OOCN): Is an ontology representation formalism, according to which an ontology (A) is defined as: A = (O, Q, D, C) where: O is a set of object classes (“classes”), Q is a set of class attributes (“attributes”), D is a set of attribute domains (“domains”), and C is a set of constraints.

Context: Is any information that can be used to characterize the situation of an entity where an entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.

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