Ontology-based knowledge management for joint venture projects
Introduction
Communication between project teams comprising members from within extended enterprises and different organizations is often hampered by, among other things, confusion in terms and vocabulary (Lin, Harding, & Shahbaz, 2004). Extended enterprise collaboration, such as joint venture (JV), will raise the difficulty and complexity of communication between the cooperating companies. One of the main technical issues is the knowledge management problem when processing shared implicit and explicit knowledge with different systems. Enterprise collaboration faces knowledge confliction during knowledge sharing and development. Poor knowledge management for involved enterprises can mislead the business processes and cause serious wastage of resources, and even the failure of the JV.
Guarino (1997) defined ontology-based knowledge management (KM) as follows: “For KM systems in enterprises, ontology can be regarded as the classification of knowledge”. Moreover, O’Leary (1998) described ontology-based KM as follows: “In enterprise KM systems, … Ontologies define the shared vocabulary used in the KM system to facilitate communication, search, storage, and representation”. The issue of enterprise ontology (EO) derives from enterprises having their own professional terminology for use in different tasks.
This study proposes a novel solution for KM problems and thus enhances collaboration during JV projects. A framework of ontology-based KM is developed to help managers and participants find solutions to various KM problems. Ambiguous knowledge acquisition from either of the JV organizations can cause serious problems in collaboration. By using an ontology-based analysis of knowledge sharing and development, enterprises involved in JVs can also reduce intellectual property leakage and increase the efficiency and effectiveness of their communication. The ontology-based approach can also help enhance collaborative relationships among knowledge workers from different domains. Finally, the approach advocate in this study is likely to increase the likelihood of success for the JV project.
The remainder of this paper is organized as follows: Section 2 discusses the development of a particular EO in relation to the high technology industry. Additionally, this section reviews the recent literature on KM and JV. Section 3 presents the overall EO framework that forms the central focus of this paper. Issues concerning the processing of the EO, its verification, and the respective domains of joint alliance EO are also described. Moreover, Section 4 discusses an IC industry case in detail. This case is used to demonstrate the generic types of problem that are likely to occur with respect to KM in JVs. Finally, Section 5 provides a conclusion and discussion of future research directions.
Section snippets
Literature review of related issues for JV projects
JVs are considered an important strategy for industries. JVs are typically defined as an alliance between two or more parties in researching, developing, producing, selling, or distributing a product or service for profit (Kukalis & Jungemann, 1995). JVs involving international competitors have attracted growing interest among both researchers and participants (Richter & Vettel, 1995). Many scholars and researchers are working on the issues related to enterprises engaging in JVs.
The literature
Key concept of the framework
Ontologies are increasingly considered a key technology for enabling semantics-driven knowledge processing (Maedche, Motik, Stojanovic, Studer, & Volz, 2003). McKeown (1992) described Semantics-driven approaches as “using knowledge about the case frames of verbs to drive interpretation”. Enterprise KM entails formally managing knowledge resources to facilitate access and reuse of knowledge, typically through the use of advanced information technology (O’Leary, 1998). The development of EO for
Introduction to the IC foundry industry
Fig. 6 shows how IC devices are mostly produced by Integrated Device Manufacturer (IDM) and Application Specific Integrated Circuit (ASIC) in the initial phase of the IC business (Tseng, 2002). The IDM and ASIC companies include functions of system/IC design, wafer manufacturing, assembly and testing. After the emergence of IC design companies (Fabless company), IC Foundries started to play a very important role in the business. Foundries manufacture ICs for design companies or other IDM and
Conclusion
This study provides a reference framework for managers during knowledge sharing and development in a JV project. This work adopts an ontological approach to analyze KM processing in JVs. The IC Foundry industry is used as an example to study the practicality of the proposed approach. The characteristics of complex business processes and high technological issues in the IC Foundry industry increase the challenge of this research. This study aimed to provide managers with assistance to increase
References (63)
- et al.
Technological alliances and the market valuation of new economy firms
Technovation
(2006) - et al.
Learning from international joint ventures – the unintended outcome
Long Range Planning
(2003) Data security
Data & Knowledge Engineering
(1998)- et al.
International joint ventures-partnering skills and cross-cultural issues
Long Range Planning
(2002) - et al.
Capacity planning with capability for multiple semiconductor manufacturing fabs
Computers and Industrial Engineering
(2005) - et al.
Joint venture conflict-the case of Russian international joint ventures
International Business Review
(2000) - et al.
An organisation ontology for enterprise modeling: Preliminary concepts for linking structure and behaviour
Computers in Industry
(1996) - et al.
Knowledge acquisition, modelling and inference through the World Wide Web
International Journal of Human–Computer Studies
(1997) Towards a framework to verify knowledge sharing technology
Expert System With Applications
(1996)A translation approach to portable ontologies
Knowledge Acquisition
(1993)